An Adaptive Autogram Approach Based on a CFAR Detector for Incipient Cavitation Detection
| Autor: | Changbo He, Ning Chu, Dazhuan Wu, Bin Huang, Linlin Cao, Liang Yu, Wang Linlin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
square-envelope spectrum
adaptive threshold Computer science Acoustics autocorrelation Feature extraction lcsh:Chemical technology 01 natural sciences Biochemistry Article Autogram method Analytical Chemistry Constant false alarm rate predictive maintenance CFAR detector 0103 physical sciences Demodulation lcsh:TP1-1185 Incipient cavitation Electrical and Electronic Engineering Envelope (radar) 010301 acoustics Instrumentation Noise (signal processing) feature extraction 010401 analytical chemistry Centrifugal pump Atomic and Molecular Physics and Optics 0104 chemical sciences cyclic amplitude model Cavitation False alarm |
| Zdroj: | Sensors, Vol 20, Iss 2303, p 2303 (2020) Sensors Volume 20 Issue 8 Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | Cavitation failure often occurs in centrifugal pumps, resulting in severe harm to their performance and life-span. Nowadays, it has become crucial to detect incipient cavitation ahead of cavitation failure. However, most envelope demodulation methods suffer from strong noise and repetitive impacts. This paper proposes an adaptive Autogram approach based on the Constant False Alarm Rate (CFAR). A cyclic amplitude model (CAM) is presented to reveal the cyclostationarity and autocorrelation-periodicity of pump cavitation-caused signals. The Autogram method is improved for envelope demodulation and cyclic feature extraction by introducing the character to noise ratio (CNR) and CFAR threshold. To achieve a high detection rate, CNR parameters are introduced to represent the cavitation intensity in the combined square-envelope spectrum. To maintain a low false alarm, the CFAR detector is combined with the CNR parameter to obtain adaptive thresholds for different data along with sensor positions. By carrying out various experiments of a centrifugal water pump from Status 1 to 10 at different flow rates, the proposed approach is capable of cavitation feature extraction with respect to the CAM model, and can achieve more than a 90% detection rate of incipient cavitation and maintain a 5% false alarm rate. This paper offers an alternative solution for the predictive maintenance of pump cavitation. |
| Databáze: | OpenAIRE |
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