A Novel Method for Sensor Data Validation based on the analysis of Wavelet Transform Scalograms

Francesco Cannarile, Piero Baraldi, Pierluigi Colombo, and Enrico Zio
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Full Paper
ijphm_18_002.pdf806.76 KBJune 19, 2018 - 12:36am

Sensor data validation has become an important issue in the operation and control of energy production plants. An undetected sensor malfunction may convey inaccurate or misleading information about the actual plant state, possibility leading to unnecessary downtimes and, consequently, large financial losses. The objective of this work is the development of a novel sensor data validation method to promptly detect sensor malfunctions. The proposed method is based on the analysis of data regularity properties, through the joint use of Continuous Wavelet Transform and image analysis techniques. Differently from the typical sensor data validation techniques which detect a sensor malfunction by observing variations in the relationships among measurements provided by different sensors, the proposed method validates the data collected by a given sensor only using historical data collected from the sensor itself. The proposed method is shown able to correctly detect different types and intensities of sensor malfunctions from energy production plants.

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Submission Keywords: 
sensor validation
scalogram analysis
Image Pattern Recognition
Continuous Wavelet Transforms (CWT)
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
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