Quadratic-Wavelet-Transform-Based Fault Detection Approach for Temperature Sensor

Addressing the problem of online fault detection of a temperature sensor, a fault detection algorithm based on quadratic wavelet transform is proposed in this paper. First, the discrete wavelet transform is used to extract noise from the process signal; since the process noise signal is related to the internal structure and status of the sensor, a Butterworth low-pass filter is used to filter out the high-frequency electrical interference signal to obtain the process noise signal. Second, the continuous wavelet transform is used to detect abrupt fault from the process noise signal. Experimental results show that the noise-analysis-based fault detection algorithm (quadratic wavelet transform) is better than the process-signal-analysis-based approach and that the quadratic wavelet transform is feasible for thermowell drop fault detection of the temperature sensor. (c) 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.