**2.1 Continuous Wavelet Transforms**

When referring to the definition of Fourier Transforms [1], it can be observed that this formulation describes the signal *x t*( ) by means of a set of functions *j t e* which form the basis for signal expansions. These functions are continuous and of infinite duration. The spectrum in question corresponds to the expansion coefficients. An alternative approach consists of decomposing the data in time-localised waveforms. Such waveforms are usually referred to as wavelets. In recent decades, the theoretical background of wavelet transforms has been extensively reported ([14]-[19]).

The Continuous Wavelet Transform (CWT) of the time signal *x t*( ) is defined as:

$$\text{CWT}(a,b) = \frac{1}{\sqrt{a}} \int\_{-\infty}^{+\infty} x(t) \wp^\* \left(\frac{t-b}{a}\right) dt\tag{3}$$

with *aR bR* 0 , .

This is a linear transformation which decomposes the original signal into its elementary functions *a b*, :

$$
\psi\_{a,b}(t) = \frac{1}{\sqrt{a}} \nu \left( \frac{t-b}{a} \right) \tag{4}
$$

On the Use of Wavelet Transform for Practical Condition Monitoring Issues 357

Firstly, as an initial improvement, the Impulse mother wavelet was taken into account in this work due to its capability in analysing impulses in vibration signals. It is defined as

> 0 () 2 cos 2 *if t t impulse t e f t*

Its capabilities and the comparison between Morlet and Impulse mother wavelets in analysing transient signals are well reported in [27] and [28]. In this study, 0*f* assumes the most common values found in literature: 0.8125 Hz for the Morlet mother wavelet and 20

Secondly, a purification method inspired by the work of Yang [29] was considered in order to improve the accuracy of CWT representations and to try and solve the problem of frequency overlapping which has already reported in [10]. In [25] Yang applied the purification method using the Morlet wavelet, while in this paper the Impulse wavelet was

By means of purification methods, new CWT coefficients (*CWT* ) were calculated using the

ˆ *CWT a b t a t CWT a b t* (, ,) (,) (, ,)

cov ( ), ( , ) (,)

deviation, *H* is the sinusoidal function and a indicates the wavelet scale. The expression

 12 1 1 2 2 *Cov x x E x x* (,)

It can be noted that the correlation between the signal and the sinusoid *H* is evaluated over

window moves for the whole duration of the signal. After several tests, the choice of time

obtaining a higher correlation coefficient and the computational time needed for the

sinusoidal function with the frequency of the present wavelet scale given by

'cov' means covariance and is defined for the two data histories 1 *x* and 2 *x* as:

*a t*

a short time period defined by a time window with duration

(,) *a t* is the coefficient of correlation between the original signal and the

 ( ) (, )

is the time duration of the signal *x(t)*,

1 *E x i* .

is based on a reliable compromise between the requirement of

(8)

(9)

*f T H aT xT H aT*

where 0*f* is the central frequency of the mother wavelets.

0 2 2

(6)

(7)

0 /*a* with

is the standard

. In addition, the time

0

Hz for the Impulse wavelet.

also taken into account.

where *Tt t*

window duration

correlation calculation.

as the central frequency of the mother wavelet. The correlation coefficient can be written as:

> /2; /2,

where *E* is the mathematical expectation and

following equation:

The term

follows:

which are determined by the translation (parameter *b* ) and the dilation (parameter *a* ) of a so called "mother (analyzing) wavelet" ( )*t* .

The *b* translation parameter describes the time localization of the wavelet, while the *a* dilation determines the width or scale of the wavelet. It is worth noting that, by decreasing the *a* scale parameter, the oscillation frequency of the wavelet increases, but the duration of the oscillation also decreases, so it can be noted that exactly the same number of cycles is contained within each wavelet.

Therefore, an important difference when compared to the classical Fourier Analysis, in which the time window remains constant, is that the time and frequency resolution now becomes dependent on the *a* scale factor. For CWTs, in fact, the width of the window in the time domain is proportional to *a*, while the bandwidth in the frequency domain is proportional to 1 / *a* . Thus, in the frequency domain, WTs have good resolution for low frequencies and, in the time domain, good resolution for high frequencies; the latter property makes CWTs suitable for the detection of transient signals. More details and applications for CWTs can be found in literature ([20]-[24]).

Two kinds of mother wavelet are known in literature:

Concerning the former, one of the most interesting is the Morlet wavelet which is defined as:

$$\left(\varphi\left(t\right)\_{morlet} = \frac{1}{\pi^{-1/4}} e^{-t^2/2} e^{i2\pi f\_0 t} \tag{5}$$

where 0*f* is the central frequency of the mother wavelet. The term 1/4 1 / is a normalization factor which ensures that the wavelet has unit energy; the Gaussian envelope 2 *t* /2 *e* modulates the complex sinusoidal waveform. Since the Morlet wavelet is a complex mother wavelet, one can separate the phase and amplitude components within any signal when using it. The CWT result is graphically represented in the time-scale plane, while in this chapter the maps are displayed in the time-frequency domain, using the relationship *f f* 0 /*a* between the central frequency of the analyzing wavelet and the scale. Moreover, when complex analyzing wavelets are used, only the amplitude is considered and represented using a linear scale.

Concerning CWT implementation, the algorithm proposed by Wang and Mc Fadden was applied taking advantage of the FFT algorithm [26].

#### **2.1.1 CWT improvements**

Several improvements have been taken into account in this chapter in order to improve CWT power in detecting and localizing transients within a signal. These enhancements concern:

356 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

which are determined by the translation (parameter *b* ) and the dilation (parameter *a* ) of a

The *b* translation parameter describes the time localization of the wavelet, while the *a* dilation determines the width or scale of the wavelet. It is worth noting that, by decreasing the *a* scale parameter, the oscillation frequency of the wavelet increases, but the duration of the oscillation also decreases, so it can be noted that exactly the same number of cycles is

Therefore, an important difference when compared to the classical Fourier Analysis, in which the time window remains constant, is that the time and frequency resolution now becomes dependent on the *a* scale factor. For CWTs, in fact, the width of the window in the time domain is proportional to *a*, while the bandwidth in the frequency domain is proportional to 1 / *a* . Thus, in the frequency domain, WTs have good resolution for low frequencies and, in the time domain, good resolution for high frequencies; the latter property makes CWTs suitable for the detection of transient signals. More details and

Concerning the former, one of the most interesting is the Morlet wavelet which is defined as:

1/4 1 ( ) *t i ft morlet t ee*

normalization factor which ensures that the wavelet has unit energy; the Gaussian envelope 2

Concerning CWT implementation, the algorithm proposed by Wang and Mc Fadden was

Several improvements have been taken into account in this chapter in order to improve CWT power in detecting and localizing transients within a signal. These enhancements

 modulates the complex sinusoidal waveform. Since the Morlet wavelet is a complex mother wavelet, one can separate the phase and amplitude components within any signal when using it. The CWT result is graphically represented in the time-scale plane, while in this chapter the maps are displayed in the time-frequency domain, using the relationship *f f* 0 /*a* between the central frequency of the analyzing wavelet and the scale. Moreover, when complex analyzing wavelets are used, only the amplitude is considered and

where 0*f* is the central frequency of the mother wavelet. The term 1/4 1 /

2 0 /2 2

(5)

is a

( )*t* .

applications for CWTs can be found in literature ([20]-[24]).

Two kinds of mother wavelet are known in literature:

so called "mother (analyzing) wavelet"

contained within each wavelet.

represented using a linear scale.

**2.1.1 CWT improvements**

applied taking advantage of the FFT algorithm [26].

*t* /2 *e*

concern:

Firstly, as an initial improvement, the Impulse mother wavelet was taken into account in this work due to its capability in analysing impulses in vibration signals. It is defined as follows:

$$\left(\psi\left(t\right)\_{impulse} = \sqrt{2\pi}e^{2\pi i f\_0 t - \left|2\pi t\right|}\cos\left(2\pi f\_0 t\right)\tag{6}$$

where 0*f* is the central frequency of the mother wavelets.

Its capabilities and the comparison between Morlet and Impulse mother wavelets in analysing transient signals are well reported in [27] and [28]. In this study, 0*f* assumes the most common values found in literature: 0.8125 Hz for the Morlet mother wavelet and 20 Hz for the Impulse wavelet.

Secondly, a purification method inspired by the work of Yang [29] was considered in order to improve the accuracy of CWT representations and to try and solve the problem of frequency overlapping which has already reported in [10]. In [25] Yang applied the purification method using the Morlet wavelet, while in this paper the Impulse wavelet was also taken into account.

By means of purification methods, new CWT coefficients (*CWT* ) were calculated using the following equation:

$$\text{CV}\hat{\text{V}}\text{T}(a,b,t) = \gamma(a,t) \cdot \text{CV}\text{T}(a,b,t) \tag{7}$$

The term (,) *a t* is the coefficient of correlation between the original signal and the sinusoidal function with the frequency of the present wavelet scale given by 0 /*a* with 0 as the central frequency of the mother wavelet.

The correlation coefficient can be written as:

$$\gamma(a,t) = \left| \frac{\text{cov}\left(\mathbf{x}(T), H(a,T)\right)}{\sigma\_{f(T)}\sigma\_{H(a,T)}} \right| \tag{8}$$

where *Tt t* /2; /2, is the time duration of the signal *x(t)*, is the standard deviation, *H* is the sinusoidal function and a indicates the wavelet scale. The expression 'cov' means covariance and is defined for the two data histories 1 *x* and 2 *x* as:

$$\text{Cov}(\mathbf{x}\_1, \mathbf{x}\_2) = E\left[ (\mathbf{x}\_1 - \mu\_1)(\mathbf{x}\_2 - \mu\_2) \right] \tag{9}$$

where *E* is the mathematical expectation and 1 *E x i* .

It can be noted that the correlation between the signal and the sinusoid *H* is evaluated over a short time period defined by a time window with duration . In addition, the time window moves for the whole duration of the signal. After several tests, the choice of time window duration is based on a reliable compromise between the requirement of obtaining a higher correlation coefficient and the computational time needed for the correlation calculation.

On the Use of Wavelet Transform for Practical Condition Monitoring Issues 359

*j k i i j i c x t t k dt X Y*

, () 2 2 *j j*

and where *j k*, *c* are the wavelet coefficients or detail coefficients representing the timefrequency map of the original signal *x t*( ) . This logarithmic scaling of both the dilation and

The dyadic grid can be considered as the most efficient in discretization terms and leads to the construction of an orthonormal wavelet basis. In fact, discrete dyadic grid wavelets are commonly chosen to be orthonormal, i.e. orthogonal to each other and normalized to have unit energy. This means that the information stored in a *j k*, *c* wavelet coefficient is not repeated elsewhere and allows for the complete regeneration of the original signal without redundancy. Orthonormal dyadic discrete wavelets are associated with scaling functions

/2

\*

*j*

, () 2 2 *j j*

The scaling function is orthogonal to the translation of itself, but not to dilations of itself.

By means of the scaling function, it is possible to obtain the approximation coefficients *j k*, *d* with the same procedure as the wavelet function (i.e. convolving the scaling function with

1 () 2

*d x t t k dt*

It is well known that diesel engines run very roughly at low speed ranges between 500-1000 rpm and that in marine applications they create vibrations in the body of the boat; moreover overall customer satisfaction with marine engines is based on performance in quietness

Since speed limits (4 knots) are usually required to be respected on leaving ports, the duration of the departure is quite high; thus, it is necessary to maintain engine speeds at a minimum. Smooth running with very low vibration levels result from a dynamically balanced design with counterweights. Good torsional vibration analysis is required to enable low speeds without noise and vibration effects. Another typical vibration source at low speeds is diesel engine combustion pressure. If fuel is injected after a small delay, the rapid combustion causes a quick rise in the pressure with high-frequency excitation force

1 () 2

,

/2

translation steps is known as the dyadic grid arrangement.

where the elementary function is

, ( ) *j k*

the signal):

terms.

2

*j k*

*t* . The scaling function has the same form as the wavelet, given by

*j k*

,

**3. Condition monitoring of marine couplings**

2

*j k j*

\*

*n j*

1

(11)

*t t k* (12)

*t tk* (13)

(14)

In terms of the last CWT improvement, a new method which was recently proposed by Halim [30] was applied in order to compute the angular domain which averages across all the scales (TDAS) after CWT calculation. TDAS combines both wavelet analysis and the angular domain average in order to improve the time-frequency representation of the TSA of a signal. While the traditional method consists in taking wavelet transforms of the Time Synchronous Average, this new method performs the wavelet transformation first and then takes the time synchronous averages, obtaining the so-called TDAS distribution.

Assuming that the period of a time series is *P* and the time series has exactly *M* periods, the number of the total time samples is *N PM* . If the number of wavelet scales *s* is *S* the wavelet transformation of the time series generates the complex matrix CWT (since both complex Morlet and Impulse mother wavelets have been applied) of *S N* dimensions. It can be noted that each row of the absolute value of the CWT matrix is a time series corresponding to one *s* scale with a *P* period. If each of these time series is synchronously averaged (based on the period of the time series), the average of all the time series across all the scales can be computed obtaining the final TDAS matrix. Each row of the TDAS matrix represents the time synchronous average of the time series located at each scale. This method has the following advantages:

On the basis of these considerations, this method appears to be helpful when a lower number of averages is available.

It is worth noting that Halim obtained the TDAS matrix using a geometric average and the Morlet wavelet as its basis. In this work, the effectiveness of the method using the Impulse mother wavelet is verified and the linear average is also taken into account in order to be consistent with the traditional method.

#### **2.2 Discrete Wavelet Transforms**

A Discrete Wavelet Transform (DWT) is a technique which enables discrete coefficients to be calculated by replacing the continuous coefficients obtained through CWT calculation [31]. Due to this fact, the *a* and *b* parameters in Eq. 2 become to the power-of-two:

$$a = \mathsf{2}^{\dagger}, b = k\mathsf{2}^{\dagger}, \mathsf{j}, \mathsf{k}, \mathsf{e} \in \mathsf{Z} \tag{10}$$

where *j* is called level, 2 *j* denoted the scale and 2*j k* denotes the shift in the time direction. The DWT is defined as:

$$\mathbf{c}\_{j,k} = \frac{1}{\sqrt{2^j}} \int\_{-\infty}^{+\infty} \mathbf{x}(t) \boldsymbol{\nu}^\* \left(\mathbf{2}^{-j}t - k\right) dt \sum\_{i=1}^n \mathbf{X}\_i \mathbf{Y}\_i \tag{11}$$

where the elementary function is

358 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

In terms of the last CWT improvement, a new method which was recently proposed by Halim [30] was applied in order to compute the angular domain which averages across all the scales (TDAS) after CWT calculation. TDAS combines both wavelet analysis and the angular domain average in order to improve the time-frequency representation of the TSA of a signal. While the traditional method consists in taking wavelet transforms of the Time Synchronous Average, this new method performs the wavelet transformation first and then

Assuming that the period of a time series is *P* and the time series has exactly *M* periods, the number of the total time samples is *N PM* . If the number of wavelet scales *s* is *S* the wavelet transformation of the time series generates the complex matrix CWT (since both complex Morlet and Impulse mother wavelets have been applied) of *S N* dimensions. It can be noted that each row of the absolute value of the CWT matrix is a time series corresponding to one *s* scale with a *P* period. If each of these time series is synchronously averaged (based on the period of the time series), the average of all the time series across all the scales can be computed obtaining the final TDAS matrix. Each row of the TDAS matrix represents the time synchronous average of the time series located at each scale. This

On the basis of these considerations, this method appears to be helpful when a lower

It is worth noting that Halim obtained the TDAS matrix using a geometric average and the Morlet wavelet as its basis. In this work, the effectiveness of the method using the Impulse mother wavelet is verified and the linear average is also taken into account in order to be

A Discrete Wavelet Transform (DWT) is a technique which enables discrete coefficients to be calculated by replacing the continuous coefficients obtained through CWT calculation [31].

where *j* is called level, 2 *j* denoted the scale and 2*j k* denotes the shift in the time direction.

2, 2,, , *j j a bk j k Z* (10)

Due to this fact, the *a* and *b* parameters in Eq. 2 become to the power-of-two:

processed since the transformation is computed over the entire time series.

transformation is computed after the averaging process;

takes the time synchronous averages, obtaining the so-called TDAS distribution.

method has the following advantages:

the wavelet transform operator;

number of averages is available.

consistent with the traditional method.

**2.2 Discrete Wavelet Transforms**

The DWT is defined as:

$$\boldsymbol{\nu}\_{j,k}(t) = 2^{-j/2} \boldsymbol{\nu}\left(2^{-j}t - k\right) \tag{12}$$

and where *j k*, *c* are the wavelet coefficients or detail coefficients representing the timefrequency map of the original signal *x t*( ) . This logarithmic scaling of both the dilation and translation steps is known as the dyadic grid arrangement.

The dyadic grid can be considered as the most efficient in discretization terms and leads to the construction of an orthonormal wavelet basis. In fact, discrete dyadic grid wavelets are commonly chosen to be orthonormal, i.e. orthogonal to each other and normalized to have unit energy. This means that the information stored in a *j k*, *c* wavelet coefficient is not repeated elsewhere and allows for the complete regeneration of the original signal without redundancy. Orthonormal dyadic discrete wavelets are associated with scaling functions , ( ) *j k t* . The scaling function has the same form as the wavelet, given by

$$
\phi\_{j,k}(t) = 2^{-j/2} \phi \left( 2^{-j} t - k \right) \tag{13}
$$

The scaling function is orthogonal to the translation of itself, but not to dilations of itself.

By means of the scaling function, it is possible to obtain the approximation coefficients *j k*, *d* with the same procedure as the wavelet function (i.e. convolving the scaling function with the signal):

$$d\_{j,k} = \frac{1}{\sqrt{2^j}} \prod\_{-\phi}^{+\phi} \varkappa(t) \phi^\* \left( 2^{-j}t - k \right) dt \tag{14}$$

#### **3. Condition monitoring of marine couplings**

It is well known that diesel engines run very roughly at low speed ranges between 500-1000 rpm and that in marine applications they create vibrations in the body of the boat; moreover overall customer satisfaction with marine engines is based on performance in quietness terms.

Since speed limits (4 knots) are usually required to be respected on leaving ports, the duration of the departure is quite high; thus, it is necessary to maintain engine speeds at a minimum. Smooth running with very low vibration levels result from a dynamically balanced design with counterweights. Good torsional vibration analysis is required to enable low speeds without noise and vibration effects. Another typical vibration source at low speeds is diesel engine combustion pressure. If fuel is injected after a small delay, the rapid combustion causes a quick rise in the pressure with high-frequency excitation force

On the Use of Wavelet Transform for Practical Condition Monitoring Issues 361

One experimental investigation was carried out on a marine propulsion package (Fig. 1). The 4-cylinder 4-stroke diesel engine with eight valves was located inboard just forward of the transom. The engine was turbocharged with an exhaust-driven turbo-compressor: the

Marine propulsion was assured by a stern-drive unit that contains the transmission and carries the propeller. The boat was steered by pivoting this unit with good characteristics in terms of speed, acceleration, steering and manoeuvring. In fact, the main advantage of sterndrives versus straight inboards is the possibility of changing the drive angle in order to obtain an optimum angle for speed or acceleration. The flexible coupling was mounted between the flywheel of the marine diesel engine and the propeller shaft. The primary side of the coupling was bolted to the flywheel, the secondary side was mounted onto the output shaft; between the two sides there were rubber elements which compensate for all types of

The vibration signals were measured from two points (see Fig. 2), which were close to the coupling, in order to analyse the vibration induced by the couplings at different angular positions of the stern drive when gears were repeatedly changed. The two accelerometers were mounted on both sides of the transom, that is, the left and right side. In order to compare the vibration behaviour of the two couplings, all compared vibration signals were

Vibration signals were measured by means of piezoelectric tri-axial accelerometers (frequency range: 1-12000 Hz). All signal records were acquired starting from a crankshaft reference position: a tachometer signal was taken using an inductive proximity probe close

In this context, DWTs were used to analyse the transom right-side signal in order to extract the scaling coefficients *j k*, *d* . In fact, the signals in time domain obtained during tests, when the gears were repeatedly changed, revealed a train of impulsive components. Fig. 3 shows that the acceleration peaks are unclear in the signal measured from the transom right-side where the noise level was too heavy. In order to indicate which type of coupling provides better vibrational behaviour, the mean value of the acceleration peaks was obtained directly from the original time history from the transom left-side. Concerning the signal measured at the right side, the mean value was obtained for low frequency components at the first level

Both types of couplings are very sensitive to transient dynamic phenomena due to gear changes. Table 1 shows that the mean value of the acceleration peaks for the Type 1 coupling is higher than the value for Type 2. Thus Type 2 gives better vibrational behaviour than the first type. It can be concluded that the time domain analysis of the coupling acceleration gives good condition monitoring information, if the DWT technique is used for signal denoising purposes. In order to precisely localise the impulsive phenomena in the time-frequency domain and to validate the previous thesis about Type 2 vibrational behaviour, the Continuous Wavelet Transform for a frame of the transom left-side signal is applied. The impulse with the highest amplitude is isolated for this signal in the time domain, (Fig. 5) and the CWT of this part of the signal is calculated for the two different coupling types. In this work, a Morlet

turbo was controlled by a waste-gate valve.

misalignment, particularly angular, and dampen vibrations.

picked up under exactly the same operating conditions.

to a gear wheel mounted onto the engine crankshaft.

1,*k d* , after DWT application (Fig. 4) with the Symlet analysing wavelet.

analysing wavelet was used, since its shape is similar to an impulse component.

components. An optimized injection system may eliminate fuel injection delay and the improved design of rigid cylinder blocks can reduce combustion pressure sources.

Finally, with regard to boat quietness, a general analysis is normally insufficient in evaluating the possibility of avoiding most noise and vibrations passing into the body of the boat through the crankshaft and the rigid coupling between the flywheel and the propeller shaft. It is necessary to highlight which parts are mainly related to vibration absorption. Coupling transmits torque and absorbs vibrations from the engine crankshaft. Placing a highly flexible coupling between the crankshaft and the propeller shaft will bring about further noise and vibration reduction. The vibration levels measured by the accelerometers mounted on different parts of the engine are a means of indicating which coupling works well.

Fig. 1. Propulsion package with the flexible coupling under study.

Fig. 2. Transom: position of accelerometers.

In the present study, Continuous (CWT) and Discrete Wavelet Transforms (DWT) are used to process the signals taken from a marine diesel engine in several operating conditions. The experimental results are presented and the capability of the above-mentioned analysis techniques are discussed.

components. An optimized injection system may eliminate fuel injection delay and the

Finally, with regard to boat quietness, a general analysis is normally insufficient in evaluating the possibility of avoiding most noise and vibrations passing into the body of the boat through the crankshaft and the rigid coupling between the flywheel and the propeller shaft. It is necessary to highlight which parts are mainly related to vibration absorption. Coupling transmits torque and absorbs vibrations from the engine crankshaft. Placing a highly flexible coupling between the crankshaft and the propeller shaft will bring about further noise and vibration reduction. The vibration levels measured by the accelerometers mounted on different parts of the engine are a means of indicating which coupling works

In the present study, Continuous (CWT) and Discrete Wavelet Transforms (DWT) are used to process the signals taken from a marine diesel engine in several operating conditions. The experimental results are presented and the capability of the above-mentioned analysis

improved design of rigid cylinder blocks can reduce combustion pressure sources.

Fig. 1. Propulsion package with the flexible coupling under study.

Fig. 2. Transom: position of accelerometers.

techniques are discussed.

well.

One experimental investigation was carried out on a marine propulsion package (Fig. 1). The 4-cylinder 4-stroke diesel engine with eight valves was located inboard just forward of the transom. The engine was turbocharged with an exhaust-driven turbo-compressor: the turbo was controlled by a waste-gate valve.

Marine propulsion was assured by a stern-drive unit that contains the transmission and carries the propeller. The boat was steered by pivoting this unit with good characteristics in terms of speed, acceleration, steering and manoeuvring. In fact, the main advantage of sterndrives versus straight inboards is the possibility of changing the drive angle in order to obtain an optimum angle for speed or acceleration. The flexible coupling was mounted between the flywheel of the marine diesel engine and the propeller shaft. The primary side of the coupling was bolted to the flywheel, the secondary side was mounted onto the output shaft; between the two sides there were rubber elements which compensate for all types of misalignment, particularly angular, and dampen vibrations.

The vibration signals were measured from two points (see Fig. 2), which were close to the coupling, in order to analyse the vibration induced by the couplings at different angular positions of the stern drive when gears were repeatedly changed. The two accelerometers were mounted on both sides of the transom, that is, the left and right side. In order to compare the vibration behaviour of the two couplings, all compared vibration signals were picked up under exactly the same operating conditions.

Vibration signals were measured by means of piezoelectric tri-axial accelerometers (frequency range: 1-12000 Hz). All signal records were acquired starting from a crankshaft reference position: a tachometer signal was taken using an inductive proximity probe close to a gear wheel mounted onto the engine crankshaft.

In this context, DWTs were used to analyse the transom right-side signal in order to extract the scaling coefficients *j k*, *d* . In fact, the signals in time domain obtained during tests, when the gears were repeatedly changed, revealed a train of impulsive components. Fig. 3 shows that the acceleration peaks are unclear in the signal measured from the transom right-side where the noise level was too heavy. In order to indicate which type of coupling provides better vibrational behaviour, the mean value of the acceleration peaks was obtained directly from the original time history from the transom left-side. Concerning the signal measured at the right side, the mean value was obtained for low frequency components at the first level 1,*k d* , after DWT application (Fig. 4) with the Symlet analysing wavelet.

Both types of couplings are very sensitive to transient dynamic phenomena due to gear changes. Table 1 shows that the mean value of the acceleration peaks for the Type 1 coupling is higher than the value for Type 2. Thus Type 2 gives better vibrational behaviour than the first type. It can be concluded that the time domain analysis of the coupling acceleration gives good condition monitoring information, if the DWT technique is used for signal denoising purposes.

In order to precisely localise the impulsive phenomena in the time-frequency domain and to validate the previous thesis about Type 2 vibrational behaviour, the Continuous Wavelet Transform for a frame of the transom left-side signal is applied. The impulse with the highest amplitude is isolated for this signal in the time domain, (Fig. 5) and the CWT of this part of the signal is calculated for the two different coupling types. In this work, a Morlet analysing wavelet was used, since its shape is similar to an impulse component.

On the Use of Wavelet Transform for Practical Condition Monitoring Issues 363

a

b

Fig. 5. Highest amplitude impulse for transom left-side acceleration. Coupling: Type 1 (a)

a b

Fig. 6. Continuous wavelet transform (Morlet wavelet) for transom left-side acceleration,

700-1500 Hz frequency range; Coupling: Type 1 (a) and Type 2 (b).

and Type 2 (b).

Fig. 6 reports the wavelet analysis results revealing that the highest amplitude wavelet coefficients for Type 1 (Fig. 6(a)) are in the frequency range of around 1100 Hz. Regarding Type 2 (Fig. 6(b)), the wavelet transform amplitude during the transient phenomena assumes lower values and reveals an appreciatively constant amplitude in the 700-1500 Hz frequency range. The time-frequency plot is able to clearly show the frequency content during the impulse and gives a clearer interpretation of the difference vibrational behaviour of two coupling types.

Fig. 3. The vibration signal (TYPE 2) from the transom left-side (a) and the transom rightside (b).

Fig. 4. DWT of the transom right-side signal (TYPE 2).

Fig. 6 reports the wavelet analysis results revealing that the highest amplitude wavelet coefficients for Type 1 (Fig. 6(a)) are in the frequency range of around 1100 Hz. Regarding Type 2 (Fig. 6(b)), the wavelet transform amplitude during the transient phenomena assumes lower values and reveals an appreciatively constant amplitude in the 700-1500 Hz frequency range. The time-frequency plot is able to clearly show the frequency content during the impulse and gives a clearer interpretation of the difference vibrational behaviour

Fig. 3. The vibration signal (TYPE 2) from the transom left-side (a) and the transom right-

Fig. 4. DWT of the transom right-side signal (TYPE 2).

of two coupling types.

side (b).

Fig. 5. Highest amplitude impulse for transom left-side acceleration. Coupling: Type 1 (a) and Type 2 (b).

Fig. 6. Continuous wavelet transform (Morlet wavelet) for transom left-side acceleration, 700-1500 Hz frequency range; Coupling: Type 1 (a) and Type 2 (b).

On the Use of Wavelet Transform for Practical Condition Monitoring Issues 365

The first faulty condition concerned an engine with a connecting rod with incorrectly tightened screws, that is, screws which were only tightened with a preload of 3 kgm, instead of the correct torque of 9. The second faulty condition concerned an engine with an inverted piston, with incorrectly positioned valve sites. This incorrect assembly hindered the correct correspondence between the valve plates and the valve sites. Since the exhaust valve site area is larger than the intake valve site, the exhaust valves knocked against the non-

Fig. 8(a) shows that the CWT map (Impulse wavelet) of the Time Synchronous Average (TSA) detected four cylinder pressurizations and two events related to the faulty condition. Even if a remarkable vertical line at 100 degrees was present in the CWT map of the TSA (Fig. 8 (a)), it is not sufficient to assure the presence of a mechanical fault since its amplitude is comparable to the pressurization peak amplitudes. Therefore, the CWT of the residual signal (i.e. the signal obtained by subtracting the time synchronous average from the raw signal) is an expected step in mechanical fault localization within engine kinematics (Fig. 8(b)). As depicted in Fig. 8(b), the presence of the pre-loaded rod is highlighted by a marked vertical line at about 100º.

As explained in [32] the peak is caused by the absence of controlled bush deformation when the correct tightening torque is not applied. This clearance is abruptly traversed whenever a change in the direction of the resultant force occurs on the rod. In particular, it was demonstrated that the acceleration peak took place at the beginning of the cylinder 3 intake stroke, corresponding to cylinder 2 pressurization (i.e. 'Press 2' in Fig. 8(a)). Hence, fault location can be only achieved by the analysis of the residual signal. It is worth noting that better angular fault localization can be achieved using the Morlet mother wavelet (Fig. 8(c)) which gives lower frequency resolution but higher angular localization of the anglefrequency map. Since the purpose of the proposed approach is to obtain reliable fault diagnostics through accurate angular transient event localization, the Morlet wavelet can be

In order to improve the CWT of the TSA, the purification method was firstly carried out

select which coefficient gives the best match between the frequency of the signal and the

Fig. 9(a) shows that this method provides a clearer representation in terms of sensitivity to background noise. However, the use of the coefficient correlation method does not improve the angular localization of the main engine events. As noted earlier, this enhancement can be obtained using the Morlet mother wavelet. The Morlet mother wavelet was used to compute the wavelet transform by means of both traditional and TDAS methods. No significant improvements in angular faulty localization can be obtained by using the TDAS method (Fig. 9(b)). Therefore, it can be concluded that a traditional CWT map with a Morlet mother

It should be noted that CWT is used in order to distinguish faulty conditions from normal ones for practical fault diagnosis and not to obtain reliable parameters for an automatic

In order to overcome this issue, the DWT technique for the extraction of faulty components from the signal, proposed by Shibata, was evaluated for the second fault which was

(,) *a t* used in this method is able to

using correlation weighted CWT coefficients, i.e. ˆ *CWT* , as described in Section 2.1.1.

considered the most desirable if compared with the Impulse wavelet.

As previously mentioned, the correlation coefficient

frequency corresponding to the Impulse wavelet scale.

wavelet is sufficient for faulty localization purposes.

procedure led by a data acquisition system.

condition tested, i.e. the inverted piston.

correspondent intake valve sites.

Fig. 7. Continuous wavelet transform (Mexican hat wavelet) for transom left-side acceleration, 700-1500 Hz frequency range; Coupling: Type 1 (a) and Type 2 (b).

Moreover, a comparison between two different Morlet and Mexican hat wavelet functions was evaluated. Undeniably, the Mexican hat wavelet function has a shape which is totally inadequate for analysing the signal impulse components. This is shown by the results in Fig. 7 which indicate that the Mexican hat highlighted the different frequency contempt of two coupling types but was not able to precisely localise the higher frequency components of the impulse signal.


# **Clinical Utility of Applying PGx and Deprescribing-Based Decision Support in Polypharmacy Future Perspectives**

Edited by Charlotte Vermehren and Niels Westergaard Printed Edition of the Special Issue Published in *Pharmaceuticals*

www.mdpi.com/journal/pharmaceuticals


*Supporting open minds since 2005*

Direct Torque Control Strategies of Electrical Machines http://dx.doi.org/10.5772/intechopen.80103 Edited by Fatma Ben Salem

#### Contributors

Mohamed Haithem Lazreg, Abderrahim Bentaallah, Fatma Ben Salem, Yuting Gao, Yang Liu, Cherifi Djamila, Miloud Yahia, Dr. Venu Madhav Gopala, Obulesu Y. P., Adhavan Balashanmugham, Maheswaran Mockaisam, Sathiyanathan Murugesan, Tojiddin Khayrullaevich Juraev, Sobir Norov, Musulmanov Furqat Shodiyevich

#### © The Editor(s) and the Author(s) 2021

The rights of the editor(s) and the author(s) have been asserted in accordance with the Copyright, Designs and Patents Act 1988. All rights to the book as a whole are reserved by INTECHOPEN LIMITED. The book as a whole (compilation) cannot be reproduced, distributed or used for commercial or non-commercial purposes without INTECHOPEN LIMITED's written permission. Enquiries concerning the use of the book should be directed to INTECHOPEN LIMITED rights and permissions department (permissions@intechopen.com).

Violations are liable to prosecution under the governing Copyright Law.

Individual chapters of this publication are distributed under the terms of the Creative Commons Attribution 3.0 Unported License which permits commercial use, distribution and reproduction of the individual chapters, provided the original author(s) and source publication are appropriately acknowledged. If so indicated, certain images may not be included under the Creative Commons license. In such cases users will need to obtain permission from the license holder to reproduce the material. More details and guidelines concerning content reuse and adaptation can be found at http://www.intechopen.com/copyright-policy.html.

#### Notice

Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book.

First published in London, United Kingdom, 2021 by IntechOpen IntechOpen is the global imprint of INTECHOPEN LIMITED, registered in England and Wales, registration number: 11086078, 5 Princes Gate Court, London, SW7 2QJ, United Kingdom Printed in Croatia

British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library

Additional hard and PDF copies can be obtained from<EMAIL_ADDRESS>
Direct Torque Control Strategies of Electrical Machines Edited by Fatma Ben Salem p. cm. Print ISBN 978-1-83880-295-0 Online ISBN 978-1-83880-296-7 eBook (PDF) ISBN 978-1-83880-359-9


**11. Conclusion**

Virtual and augmented reality (VR/AR), transportation, healthcare, the environment, and edge computing are just a few of the areas that have seen significant shifts since the introduction of 5G technology. The main effects of 5G on these industries are outlined in this concluding chapter, along with the potential benefits and challenges that lie ahead. 5G's ultra-low latency and high bandwidth capabilities have made it possible to create immersive and seamless VR/AR experiences [83]. Real-time applications like remote collaboration, gaming, and training have been made possible by these enhancements, paving the way for the widespread adoption of VR/AR technologies across various industries. Enhanced connectivity has fueled the growth of autonomous vehicles, smart traffic management systems, and vehicle-to-everything (V2X) communication, resulting in safer and more efficient transportation networks [84]. The transportation sector has also witnessed significant advancements as a result of 5G. The expansion of telemedicine, remote monitoring, and robotic surgery

in the healthcare industry has been made easier by 5G, improving both access to medical services and the overall quality of care. In addition, the integration of 5G with IoT devices has sped up the creation of smart healthcare systems, resulting in better outcomes for patients and lower costs [85]. There are both benefits and drawbacks to the environment from 5G. Through increased efficiency across a variety of industries, 5G has the potential to, on the one hand, cut down on emissions and energy consumption. However, additional research is necessary due to concerns about the potential health risks posed by higher-frequency radio waves and the increased energy requirements for 5G infrastructure. Last but not least, real-time data processing and analytics at the network's edge have been made possible by 5G, which has revolutionized edge computing by lowering latency and increasing system efficiency. Innovative applications have emerged in a variety of fields, including smart cities, agriculture, and manufacturing [82]. 5G will have profound and far-reaching effects on VR/AR, transportation, healthcare, the environment, and edge computing. Stakeholders need to address the obstacles and take full advantage of this revolutionary technology as 5G networks continue to grow.


**Aspasia Karozou 1,\*, Stavroula Konopisi 1, Eleni Pavlidou 2 and Maria Stefanidou 1**

Received: 22 July 2020; Accepted: 25 August 2020; Published: 27 August 2020

**Abstract:** The need to increase the durability of clay-based materials, due to their inherent low strength and vulnerability in contact with water, led researchers to examine different options. In this paper, clay mortars were produced using four different activating solutions. Alkali hydroxides, alkali carbonates, and alkali silicates activating solutions were used. Interest is given to long term properties while their behavior to wetting–drying and freeze–thaw cycles is recorded. In total, the results of the experiments indicated the positive effect of the potassium metasilicate on mechanical characteristics presenting, however, low performance at wetting–drying. The combination of sodium metasilicate with sodium hydroxide solution has also presented a positive effect on both mechanical and physical properties. In contrast, sodium carbonate acted better in enhancing physical properties and granting water-resistant abilities. Moreover, the performance of the specimens mixed with water–glass addition presented excellent volume stability and low mass loss in durability tests.

**Keywords:** clay mortars; activating solutions; wetting–drying; freeze–thaw cycles; microstructure


**2. Classification, structure, and anatomy of salivary glands**

	- **a.** Major salivary glands
		- Parotid
		- Submandibular
		- Sublingual

## **b.** Minor salivary glands

	- **i.** Anterior lingual gland (glands of Blandin and Nuhn)
	- **ii.** Posterior lingual serous gland (von Ebner's glands)
	- **iii.** Posterior lingual mucous gland
	- Serous
	- Mucous

gland and divided into two main groups. The major salivary glands include the paired parotid, submandibular, and sublingual glands. Additionally, the mucosa of the upper aerodigestive tract is lined by hundreds of small, minor salivary glands. The connective tissue forms a capsule around the gland and extends into it, dividing groups of secretory units and ducts into lobes and lobules. Blood vessels, lymphatic vessels and nerves that

The salivary glands are compound glands as they have more than one tubule entering the main duct, and the architectural arrangement is tubuloacinar, where acini are secretory units. These secretory units are merocrine as they release only the secretion of the cell from the secreting units. Myoepithelial cells are contractile cells associated with the secretory end-

supply the gland, are present within the capsule [1].

**Figure 1.** Structural organization of salivary gland [3].

64 Histology

pieces and intercalated ducts of the salivary gland [2].

**a.** Major salivary glands

○ Submandibular

○ Sublingual

○ Parotid

**2. Classification, structure, and anatomy of salivary glands**

• On the basis of size and location, salivary glands are classified as [1, 2]:

#### **2.1. Major salivary glands**

These are the largest, bilaterally paired, and situated extraorally, but their secretion reaches the oral cavity by variable long ducts.

#### *2.1.1. Parotid gland*

The parotid gland is the largest of all the salivary glands and weighs about 15–30 g. It is located below the external acoustic meatus between the ramus of the mandible and the sternocleidomastoid. It is divided by facial nerve into a superficial and deep lobe. The superficial lobe, overlying the lateral surface of the masseter, is defined as the part of the gland lateral to the facial nerve. The deep lobe is medial to the facial nerve and located between the mastoid process of the temporal bone and the ramus of the mandible. An accessory parotid gland may also be present lying anteriorly over the masseter muscle between the parotid duct and zygomatic arch [4].

The parotid duct, also known as Stensen's duct, secretes serous saliva and opens into the vestibule of the mouth (gingiva-buccal vestibule) opposite the crown of the upper second molar tooth [2].

#### *2.1.2. Submandibular gland*

It is the second largest salivary gland, also known as submaxillary salivary gland, weighs about 7–16 g and is almost the size of a walnut. It is situated in the submandibular triangle, which has a superior boundary formed by the inferior edge of the mandible and inferior boundaries formed by the anterior and posterior bellies of the digastric muscle. The gland is approximately J-shaped being indented by the posterior border of the mylohyoid which divides into a larger part superficial to the muscle and a smaller part lying deep to the muscle [4]. The submandibular gland duct, also known as Wharton's duct, is thin-walled, about 5 cm long, and runs forward above the mylohyoid muscle lying just below the mucosa of the floor of the mouth in its terminal portion. The duct opens on the floor of the mouth, on the summit of the sublingual papilla also called the caruncula sublingualis, lateral to the lingual frenulum [2].

**3. Development of the salivary glands**

of the supporting part of the adult gland.

glands.

12th prenatal week.

Stages of development [5, 6]

out the development.

bulbs.

The development of the glandular tissue involves the interaction of the epithelium with the underlying mesenchyme to form the functional part of the tissue [5, 6]. These epithelialmesenchymal interactions are also known as secondary induction in which the mesenchyme is in close proximity with the epithelium and is required for the normal development of the epithelium. For example, epithelial-mesenchymal interactions regulate both the initiation and growth of the glandular tissue and the eventual cytodifferentiation of cells within the salivary glands. The mesenchyme, therefore, is required for normal development as well as formation

Salivary Glands

67

http://dx.doi.org/10.5772/intechopen.81213

All salivary glands follow a similar development pattern. The functional glandular tissue (parenchyma) develops as an epithelial outgrowth (glandular bud) of the buccal epithelium that invades the underlying mesenchyme. The connective tissue stroma (capsule and septa) and blood vessels form from the mesenchyme. The mesenchyme is composed of cells derived from neural crest and is important for the normal differentiation of the salivary

As the bud formation begins during development, the portion of the bud closest to the stomodeum eventually differentiates into the main excretory duct of the gland, while the most distal portion of the bud forms the secretory endpieces or acini. The origin of the epithelial buds is believed to be ectodermal in the parotid and minor salivary glands but endodermal in origin in the submandibular and sublingual glands. The parotid gland originates near the corners of the primitive oral cavity by the sixth week of prenatal life. The submandibular glands arise from the floor of the mouth at the end of the sixth or the beginning of the seventh week in utero. The sublingual gland forms lateral to the submandibular primordium at about eighth week. All the minor salivary glands bud from buccal epithelium but start after their

**I. Bud formation, i.e., induction of oral epithelium by underlying mesenchyme:** The mesenchyme underlying the oral epithelium induces the proliferation in the epithelium

**II. Formation and growth of epithelial cord:** A solid cord of cells forms from the epithelial bud through cell proliferation. Condensation and proliferation occur in the surrounding mesenchyme which is closely associated with the epithelial cord. The basal lamina plays a role in influencing morphogenesis and differentiation of the salivary glands through-

**III. Initiation of branching in terminal parts of epithelial cord and continuation of glandular differentiation:** The epithelial cord proliferates rapidly and branches into terminal

**IV. Dichotomous branching of epithelial cord and lobule formation:** The branching continues at the terminal portion of the cord forming an extension treelike system of bulbs. As branching occurs, the connective tissue differentiates around the branches, eventually

which results in tissue thickening and bud formation.

#### *2.1.3. Sublingual gland*

It is the smallest of all the three major salivary glands that is almond shaped and weighs about 3–4 g. The gland lies above the mylohyoid, below the mucosa of the floor of the mouth, medial to the sublingual fossa of the mandible, and lateral to the genioglossus [4]. It comprises of one main gland duct with various small ducts. The main duct, Bartholin's duct, opens with or near the submandibular duct. Several smaller ducts, duct of Rivinus, open independently along the sublingual fold [2].

#### **2.2. Minor salivary glands**

The minor salivary glands are placed below the epithelium in almost all parts of the oral cavity. These glands comprise numerous small groups of secretory units opening via short ducts directly into the mouth. They lack a distinct capsule, instead mixing with the connective tissue of the submucosa or muscle fibers of the tongue or cheeks [2].

#### *2.2.1. Labial and buccal glands*

These glands are present on the lips and cheeks and comprise of mucous tubules with serous demilunes [1, 2].

#### *2.2.2. Glossopalatine glands*

These are located to the region of the isthmus in the glossopalatine fold but may extend from the posterior extension of the sublingual gland to the glands of the soft palate [1, 2].

#### *2.2.3. Palatine glands*

These are located in the glandular aggregates present in the lamina propria of the posterolateral aspect of the hard palate and in the submucosa of the soft palate and uvula [1, 2].

#### *2.2.4. Lingual glands*

The glands of the tongue can be divided into various groups [1, 2]. The anterior lingual glands (glands of Blandin and Nuhn) are present near the apex of the tongue. The ducts open on the ventral surface of the tongue near the lingual frenulum. The posterior lingual mucous glands are present lateral and posterior to vallate papillae and in association with lingual tonsil. The ducts of these glands open on the dorsal surface of the tongue. The posterior lingual serous glands (von Ebner's glands) are located between the muscle fibers of the tongue below the vallate papillae, and the ducts open into the trough of circumvallate papillae and at the rudimentary folate papillae on the sides of the tongue.


**1. Introduction**

To be effective an active drug or principle must cross the stratum corneum barrier; this process can be influenced to obtain better functional and therapeutical effects. In spite of the wide variety of the methods studied in order to improve the transdermal transfer to obtain systemic effects, the applicability is limited in this field. Attention to the epidermal barrier and penetration of active principles has been reported mostly in studies concerning dermocosmetics. Studies regarding methods of penetration are gaining experimental and clinical interest. Cutaneous bioavailability of most commercially available dermatological formulations is low. Increase of intradermal delivery can relate to chemical, biochemical, or physical manipulations. Chemical enhancers have been adopted to: (a) increase the diffusibility of the substance across the barrier, (b) increase product solubility in the vehicle, (c) improve the partition coefficient. Moreover, methods of interference with the biosynthesis of some lipids allow the modification of the structure of the barrier to increase the penetration. Recent development of these methods are here reported and underline the importance and role of vehicles and other factors that determine effects of partition and diffusion, crucial to absorption of high molecular weight haptens in allergic contact dermatitis.

The skin represents an important barrier of the penetration of exogenous substances into the body and, on the other hand, a potential avenue for the transport of functional active principles into the skin and/or the body. Several studies have shown the modalities through which these molecules cross the horny layer, which represents the most important limiting factor of the process of diffusion and penetration, and have discussed how to increase the penetration of pharmacologically active substances **[1-3].** The stratum corneum has a very peculiar structure: the corneocytes (the *bricks*: about 85% of the mass of horny mass) and intercellular lipids (15%) are arranged in approximately 15-20 layers. It consists of about 70 % proteins, 15 % lipids, and only 15 % water. In the corneocytes contain keratin, filagrin, and demolition products [**4**]. The corneocyte lacks lipids, but is rich in proteins. The lipids are inside extracellular spaces, in a bilayer organization surrounding corneocytes. The very low permeability of the horny layer to hydrosoluble substances is because of this

Topical Delivery of Haptens: Methods of Modulation of the

effects of partition and diffusion in the stratum corneum.

important determinants are solubility and diffusibility.

**4. Conditions that modify the barrier function**

type of preparation.

entities.

the solute.

Cutaneous Permeability to Increase the Diagnosis of Allergic Contact Dermatitis 63

and scalp) and only 0.1 percent in areas where their density is low. This is a possible selective way for some drugs. Follicular penetration may be influenced by sebaceous secretion, which favors the absorption of substances soluble in lipids. The penetration through the pilosebaceous units is dependent upon the property of the substance and

**2. Role of the vehicle and excipients and interaction with the active principles**  A vehicle is defined by the type of preparation (cream, ointment, gel) and the excipients (water, paraffin, propilen glycol); the terms "vehicle" and "excipient" refer to different

Vehicle and excipients deeply influence the velocity and magnitude of absorption and consequently the bioavailability and efficacy. The excipients of the vehicle modulate the

A lipid preparation that promotes occlusion may enhance the penetration of the drug, but ointments and lipid preparations are not always more powerful than creams. Creams, gels and solutions may be formulated so as to obtain an effect equivalent to that of ointments. Topical corticosteroids of different classes of potency may show the same activity when formulated in different vehicles. A gel preparation of kellin, obtaining better penetration, has demonstrated important results in the treatment of vitiligo. Also transfollicular penetration is influenced by vehicle and excipients; better results are given by lipophilic and alcoholic vehicles. Relevant factors include dimension and charge of the molecules of

For the purpose of the study of the mechanisms of transport and the functions of the skin barrier, it can be considered as a membrane or a cluster of membranes (mathematical principles can be applied) [**11**]. On the whole, transport through the horny layer is mainly a molecular passive diffusion. The physico-chemical and structural properties of the substance determine the capacity of diffusion and penetration through the membrane:

The diffusibility and the ability of a solute to penetrate through the barrier is influenced by several factors including the tortuosity of the intercellular route. This passive process of absorption follows Fick's law of diffusion: the velocity of absorption - flow - is proportional to the difference of concentration of the substance in relation to that within the barrier. It can finally be noted that the permeability coefficient relates flow and concentration, resulting

During hydration the greater part of the water is associated with intracellular keratin; the natural factor of hydration or natural moisturizing factor (NMF) absorbs a noticeable amount of water (10% of the weight of the corneocyte). Corneocytes swell and the barrier properties of the stratum corneum are deeply altered. In the intercellular space the small

from partition coefficient, diffusion coefficient, and length of diffusion route [**12-16**].

**3. Pharmacokinetic parameters - Vehicle/ corneous layer partition**

extracellular lipid matrix. Cutaneous penetration of hydrophilic substances is limited because of the convoluted and tortuous intercellular space and hydrophobicity of three lipidic constituents: ceramides, cholesterol, and free fatty acids that are present in the molar ratio: 1: 1: 1 (weight ratio: ceramides 50%, cholesterol 35-40%, free fatty acids 10-15%) **[5].** This ratio is critical: because the diminution of the concentration of one of these types of lipids alters the molar ratio functional to the normality of the barrier and modifies its integrity **[6].** The variations of this lamellar structure and/or its lipid composition are the structural and biochemical basis of permeability variations along with the thickness of the horny layer. The extracellular matrix forms also the so-called the 'horny layer reservoir' (some substances are partially retained in the corneous layer and are slowly released) **[7-8].** Various processes carried out serially or in parallel, are involved in cutaneous penetration of substances and these may cross the stratum corneum via an intercellular or a transcellular route. Moreover, entrance through pilosebaceous units and eccrine glands is possible. Many efforts to obtain therapeutic effects in tissues far from the skin have been made. We may have: topical administration, with a pharmacological effect limited to skin, with some unavoidable systemic absorption; loco-regional delivery, when the therapeutic effect is obtained in tissues more or less deeply beneath the skin (muscles, articulations, vessels, etc.) with limited systemic absorption; and transdermic delivery that aims to obtain, through application of preparations on the skin, pharmacologically active levels for the treatment of systemic diseases through skin vascular network or for the diagnosis of a suspected contact dermatitis.

#### **1.1 Stratum corneum barrier and intradermal delivery**

The penetration through the stratum corneum involves partition phenomena of applied molecules between lipophilic and hydrophilic compartments. For many substances the penetration takes place through an intercellular way, more than transcellular, diffusing around the keratinocytes.

**Intercellular movement.** The lipid lamellae (each one including 2 or 3 bilayers and made mainly of ceramides, cholesterol, and free fatty acids) are the intercellular structure of the horny layer, with the main role in barrier function. Most solute substances, non-polar or polar, penetrate across intercellular lipid avenues. The permeability of very polar solutes is constant and similar to the transport of ions (e.g. potassium ions). Lipophilic solute permeability increases according to specific lipophilic properties.

**Transcellular movement.** Stratum corneum intracellular components are essentially devoid of lipids and lack a functional lipid matrix around keratin and keratohyalin. This results in an almost impenetrability of corneocytes [**9**]. Degradation of the corneodesmosomes causes formation of a continuous lacunar dominio ("aqueous pore") allowing intercellular penetration; the lacunae formed are scattered and not continuous, and form as a result of occlusion, ionophoresis, and ultrasound waves. These may become larger and connect forming a net ("pore-way"). Various methods can induce this type of permeability increase : physical and chemical methods [**10**].

Transport through follicular and gland structures. Movement through hair follicles, pilosebaceous units, and eccrine glands is limited. The orifices of the pilosebaceous units represent about 10 percent of all skin delivery in areas where their density is high (face

extracellular lipid matrix. Cutaneous penetration of hydrophilic substances is limited because of the convoluted and tortuous intercellular space and hydrophobicity of three lipidic constituents: ceramides, cholesterol, and free fatty acids that are present in the molar ratio: 1: 1: 1 (weight ratio: ceramides 50%, cholesterol 35-40%, free fatty acids 10-15%) **[5].** This ratio is critical: because the diminution of the concentration of one of these types of lipids alters the molar ratio functional to the normality of the barrier and modifies its integrity **[6].** The variations of this lamellar structure and/or its lipid composition are the structural and biochemical basis of permeability variations along with the thickness of the horny layer. The extracellular matrix forms also the so-called the 'horny layer reservoir' (some substances are partially retained in the corneous layer and are slowly released) **[7-8].** Various processes carried out serially or in parallel, are involved in cutaneous penetration of substances and these may cross the stratum corneum via an intercellular or a transcellular route. Moreover, entrance through pilosebaceous units and eccrine glands is possible. Many efforts to obtain therapeutic effects in tissues far from the skin have been made. We may have: topical administration, with a pharmacological effect limited to skin, with some unavoidable systemic absorption; loco-regional delivery, when the therapeutic effect is obtained in tissues more or less deeply beneath the skin (muscles, articulations, vessels, etc.) with limited systemic absorption; and transdermic delivery that aims to obtain, through application of preparations on the skin, pharmacologically active levels for the treatment of systemic diseases through skin vascular network or for the diagnosis of a

The penetration through the stratum corneum involves partition phenomena of applied molecules between lipophilic and hydrophilic compartments. For many substances the penetration takes place through an intercellular way, more than transcellular, diffusing

**Intercellular movement.** The lipid lamellae (each one including 2 or 3 bilayers and made mainly of ceramides, cholesterol, and free fatty acids) are the intercellular structure of the horny layer, with the main role in barrier function. Most solute substances, non-polar or polar, penetrate across intercellular lipid avenues. The permeability of very polar solutes is constant and similar to the transport of ions (e.g. potassium ions). Lipophilic solute

**Transcellular movement.** Stratum corneum intracellular components are essentially devoid of lipids and lack a functional lipid matrix around keratin and keratohyalin. This results in an almost impenetrability of corneocytes [**9**]. Degradation of the corneodesmosomes causes formation of a continuous lacunar dominio ("aqueous pore") allowing intercellular penetration; the lacunae formed are scattered and not continuous, and form as a result of occlusion, ionophoresis, and ultrasound waves. These may become larger and connect forming a net ("pore-way"). Various methods can induce this type of permeability increase :

Transport through follicular and gland structures. Movement through hair follicles, pilosebaceous units, and eccrine glands is limited. The orifices of the pilosebaceous units represent about 10 percent of all skin delivery in areas where their density is high (face

suspected contact dermatitis.

around the keratinocytes.

physical and chemical methods [**10**].

**1.1 Stratum corneum barrier and intradermal delivery**

permeability increases according to specific lipophilic properties.

and scalp) and only 0.1 percent in areas where their density is low. This is a possible selective way for some drugs. Follicular penetration may be influenced by sebaceous secretion, which favors the absorption of substances soluble in lipids. The penetration through the pilosebaceous units is dependent upon the property of the substance and type of preparation.