requires the a-priory definition of the wavelet family, the scales explored and the temporal stride.

Detection of Anomalous Conditions in Flight Test {#sec:casestudy}
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Helicopters accelerometers use case
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The use case on which we illustrate different ways to encode time series into images is relative to flight test helicopters vibration measurements. The dataset has been collected and released by [@airbus18][^1]. A main challenge in flight tests of heavily instrumented aircraft (helicopters or airplanes alike) is the validation of the generated data because of the number of signals to validate. Manual validation requires too much time and manpower. Automation of this validation is crucial.

In this case, different accelerometers are placed at different positions of the helicopter, in different directions (longitudinal, vertical, lateral) to measure the vibration levels in all operating conditions of the helicopter. The data set consists of multiple 1D time series with a constant frequency of 1024 Hz taken from different flights, cut into 1 minute sequences. Labels (normal, anomalous) are associated per flight and attributed to each sequence of the flight.

The data set is split into two parts:

-   : it consists only of 1677 sequences from normal flights;

-   : it consists of 594 