Convolutional Autoencoders for Health Indicators Extraction in Piezoelectric Sensors
- 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.
Author: | Ivan Kraljevski, Frank Duckhorn, Constanze Tschöpe, Matthias WolffORCiD |
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URL: | https://ieeexplore.ieee.org/document/9323023 |
DOI: | https://doi.org/10.1109/SENSORS47125.2020.9323023 |
ISBN: | 978-1-7281-6801-2 |
Title of the source (English): | 2020 IEEE Sensors, 25-28 Oct. 2020, Rotterdam, Netherlands, |
Place of publication: | Rotterdam, Netherlands |
Document Type: | Conference publication peer-reviewed |
Language: | English |
Year of publication: | 2020 |
Contributing Corporation: | IEEE |
First Page: | 1 |
Last Page: | 4 |
Faculty/Chair: | Fakultät 1 MINT - Mathematik, Informatik, Physik, Elektro- und Informationstechnik / FG Kommunikationstechnik |