Detecting aging of process sensors with noise signal measurement

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • Teollisuuden Voima
  • Aalto University

Abstract

In this paper, methods for detecting failures in process sensors from the noise measurement due to aging issues are examined. The data are acquired from the water level and pressure measurement transmitters in the Olkiluoto nuclear power plant in Finland: units Olkiluoto 1 and Olkiluoto 2. Methods found from the literature about the failure indicators are presented. Changes in the sensor response time as well as in the resonance peaks in the signal are identified from the power spectrum of the signal. In addition, a new method for fingerprinting the sensors using the Principal Component Analysis (PCA) of the signal spectra is presented. By following the changes in these fingerprints and the variations between parallel measurements of the redundant sensors, symptoms of sensor failures can be detected. In the experiments we were able to produce stable fingerprints for the differential pressure transmitters used in the water level measurement. Potential failure in one differential pressure sensor in unit Olkiluoto 2 is found with the fingerprint method and by analyzing the changes in the spectrum.

Details

Original languageEnglish
Title of host publication2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)
Publication statusPublished - 1 Sep 2017
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications - Bucharest, Romania
Duration: 21 Sep 201723 Jan 2018
Conference number: 9

Conference

ConferenceIEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications
CountryRomania
CityBucharest
Period21/09/201723/01/2018

    Research areas

  • fission reactor safety, pressure sensors, principal component analysis, sensors, Olkiluoto 1 data, Olkiluoto nuclear power plant, Principal Component Analysis, aging issues, differential pressure sensor, differential pressure transmitters, failure indicators, fingerprint method, noise measurement, noise signal measurement, parallel measurements, potential failure, power spectrum, pressure measurement transmitters, process sensors, redundant sensors, resonance peaks, sensor failures, sensor response time, signal spectra, stable fingerprints, unit Olkiluoto 2, water level measurement, Aging, Analytical models, Fingerprint recognition, Pressure sensors, Principal component analysis, Time factors, aging, data analysis

ID: 16822477