Convolutional Autoencoders for Health Indicators Extraction in Piezoelectric Sensors
| Autor: | Ivan Kraljevski, Constanze Tschoepe, Frank Duckhorn, Matthias Wolff |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
business.industry Computer science Piezoelectric sensor Feature extraction Pattern recognition 02 engineering and technology Health indicator 020901 industrial engineering & automation Component (UML) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Extraction (military) Artificial intelligence Hidden Markov model business |
| Zdroj: | 2020 IEEE SENSORS. |
| DOI: | 10.1109/sensors47125.2020.9323023 |
| Popis: | We present a method for extracting health indicators from piezoelectric sensors applied in the case of microfluidic valves. Convolutional autoencoders were used to train a model on the normal operating conditions and tested on signals of different valves. The results of the model performance evaluation, as well as, the qualitative presentation of the indicator plots for each tested component, showed that the used approach is capable of detecting features that correspond to increasing component degradation. The extracted health indicators are the prerequisite and input for reliable remaining useful life prediction. |
| Databáze: | OpenAIRE |
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