Method for configuring an apparatus or method for prediction of a malfunction of a unit, includes providing components of the unit; providing single malfunctions for each component; providing probabilities for the single malfunctions of each component; providing a parameter of each component for each single malfunction of this component; dividing each parameter into discrete value states; providing values of the parameters; determining a transition matrix for each parameter on the basis of the measurements of this parameter, wherein the transition matrix includes for the plurality of discrete value states of each parameter the probabilities to switch from one of the discrete value states to another of the discrete value states within a certain time period; determining the probabilities of the discrete value states on the basis of the measurements of the parameters; and providing the conditional probabilities of the discrete value states given the corresponding single malfunction.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. Method for configuring an apparatus for prediction of a malfunction of a unit, comprising the steps of: receiving, in the apparatus, components of the unit, wherein the components are mechanical or electrical component of the unit, receiving, in the apparatus, single malfunctions for each component, receiving, in the apparatus, probabilities for the single malfunctions of each component), receiving, in the apparatus, at least one parameter of each component for each single malfunction of this component, dividing, in the apparatus, each parameter into a plurality of discrete value states, receiving, in the apparatus, values of the parameters, determining, in the apparatus, a transition matrix for each parameter on the basis of the received values of this parameter, wherein the transition matrix comprises for the plurality of discrete value states of each parameter the probabilities to switch from one of the discrete value states to another of the discrete value states within a certain time period; determining, in the apparatus, the probabilities of the discrete value states of the parameters on the basis of the received values of the parameters; and receiving, in the apparatus, the conditional probabilities of the discrete value states of the parameters given the corresponding single malfunction. 2. Method according to claim 1 comprising the step of determining, in the apparatus, the conditional probability distributions for each single malfunction of each component given the corresponding discrete value states of the parameter used for determining this single malfunction based on the probabilities of the discrete value states of this parameter, on the probability of the single malfunction and on the conditional probabilities of the discrete value states of the parameters given the corresponding single malfunction 3. Method according to claim 1, wherein the step of receiving probabilities for the single malfunctions of each component comprises for each component: receiving, in the apparatus, values indicating the relative probabilities of the single malfunctions of the corresponding component; receiving, in the apparatus, a probability for a malfunction of the corresponding component caused by all of the single malfunctions; determining, in the apparatus, the absolute probabilities of the single malfunctions of the corresponding component on the basis of the relative probabilities and the probability for the malfunction of the corresponding component caused by all of the single malfunctions. 4. Method according to claim 3, wherein the relative probabilities are each indicated by a scale between a minimum and a maximum and the absolute probabilities of the single malfunctions are determined by rescaling the relative probabilities so that the sum of all relative probabilities yields the probability for having a malfunction of the corresponding component. 5. Method according to claim 3, wherein for each single malfunction of the corresponding component additionally the relative impact of the single malfunction is received. 6. Method according to claim 1, wherein the step of receiving the conditional probabilities of the discrete value states of the parameters given the corresponding single malfunction comprises for each single malfunction of each component: receiving, in the apparatus, probabilities that the parameter indicating the single malfunction is in a number of parameter intervals when the single malfunction occurs, wherein the number of parameter intervals is smaller than the number of discrete value states of this parameter, and determining, in the apparatus, the conditional probabilities of the number of discrete value states of the parameters given the corresponding single malfunction, on the basis of the received conditional probabilities of the number of parameter intervals of the parameters given the corresponding single malfunction. 7. Method according to claim 6, wherein the number of parameter intervals is smaller than or equal to five, preferably four. 8. Method according to claim 7, comprising the step of determining, in the apparatus, a wear measuring quantity for each component. 9. Method according to claim 1, wherein one of the components is a gas turbine, and the single malfunction of the gas turbine is one of a bearing defect, compressor defect, flow malfunction, turbine malfunction, or output malfunction, and the parameter for predicting the single malfunction of the gas turbine is temperature, lubricant condition in the bearings or in the oil tank, shaft or casing vibration, pressure of the gas in the turbine, electric output of a generator coupled with the turbine, ambient air condition or humidity, or a combination thereof; and/or one of the components is a transformer, and the single malfunction of the transformer is one of an insulation defect or a cooling system defect of the transformer, and the parameter for predicting the single malfunction of the transformer is one or a combination of temperature of the coils, vibrations of the cooling fans, a condition of the oil surrounding the coils; or one of the components is a diesel engine, and the single malfunction of the diesel engine is one of bearing defect or turbo charger defect, and the parameter for predicting the single malfunction of the diesel engine is one or a combination of temperature, vibrations, lubricant condition, outlet pressure of the compressor and fuel analysis. 10. Non-transitory computer-readable medium storing a program comprising instructions configured to perform the following steps when executed on a processor: receiving, in the processor, components of the unit, wherein the components are mechanical or electrical component of the unit, receiving, in the processor, single malfunctions for each component, receiving, in the processor, probabilities for the single malfunctions of each component, receiving, in the processor, at least one parameter of each component for each single malfunction of this component, dividing, in the processor, each parameter into a plurality of discrete value states receiving, in the processor, values of the parameters, determining, in the processor, a transition matrix for each parameter on the basis of the received values of this parameter, wherein the transition matrix comprises for the plurality of discrete value states of each parameter the probabilities to switch from one of the discrete value states to another of the discrete value states within a certain time period; determining, in the processor, the probabilities of the discrete value states of the parameters on the basis of the received values of the parameters; and receiving, in the processor, the conditional probabilities of the discrete value states of the parameters given the corresponding single malfunction. 11. Apparatus for configuring a prediction of a malfunction of a unit, receiving section configured to receive: components of the unit, single malfunctions for each component, values for determining probabilities for the single malfunctions of each component, at least one parameter of each component for each single malfunction of this component, measurements of the parameters; values for determining the conditional probabilities of the discrete value states of the parameters given the corresponding single malfunction; a dividing section for dividing the parameter range of each parameter into a plurality of discrete value states, a transition matrix section for determining a transition matrix for each parameter on the basis of the measurements of this parameter, wherein the transition matrix comprises for the plurality of discrete value states of each parameter the probabilities to switch from one to another of the discrete value states within a certain time period; a conditional probability section configured to determine the conditional probabilities of the discrete value states of the parameters given the corresponding single malfunction, on the basis of the values for determining the conditional probabilities of the discrete value states of the parameters given the corresponding single malfunction; and a discrete value state probability section for determining the probabilities of the discrete value states of the parameters on the basis of the measurements of the parameters; and a malfunction probability section for determining the probabilities of the single malfunctions, on the basis of the values for determining probabilities for the single malfunctions of each component.