- Institute for Energy Technology IFE
- Teollisuuden Voima
In this article we examine the methods for detecting and predicting aging related process sensor failures by analyzing the noise of the sensor output signal. The study uses data from non-differential and differential pressure transmitters used in the pressure and water level measurements of the reactor pressure vessels of units 1 and 2 of the Olkiluoto nuclear power plant in Finland. The article contains a review of the current methods for detection of sensor failures. Additionally, we present a new method for detecting changes in the sensor output signal. The method creates fingerprints of the power spectra of the sensors by using Principal Component Analysis (PCA). The changes in these fingerprints together with the measurements of the redundant sensors can be used to detect indications of some of the impending sensor failures. In the experimental study we are able to produce stable fingerprints for both the non-differential and differential pressure transmitters. Also, a potential failure in one of the differential pressure transmitters in Olkiluoto unit 2 is detected by inspecting the fingerprints and analyzing the spectral changes of the transmitter output signal.
|Number of pages||12|
|Journal||GSTF INTERNATIONAL JOURNAL ON COMPUTING|
|Publication status||Published - 2019|
|MoE publication type||A1 Journal article-refereed|
- aging, failure prediction, data analysis, noise analysis, nuclear power plant, pressure sensors, principal component analysis, process sensors, spectral analysis.