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An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

Chinese Journal of Mechanical Engineering 2017年第6期30卷 1296-1304页

作者： De Z.Li Wilson Wang Fathy Ismail Department of Mechanical Engineering Lakehead University Department of Mechanical & Mechatronics Engineering University of Waterloo

Induction motors （IMs） are commonly used in various industrial applications. To improve energy con- sumption efficiency, a reliable IM health condition moni- toring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is pro- posed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are syn- thesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air- gap eccentricity diagnosis. The effectiveness of the pro- posed harmonic synthesis technique is examined experi- mentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

关键词： Air-gap eccentricity Current signal faultdetection Induction motor

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Probabilistic Anomaly Detection Approach for Data-driven Wind Turbine Condition Monitoring

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CSEE Journal of Power and Energy Systems 2019年第2期5卷 149-158页

作者： Yuchen Zhang Meng Li Zhao Yang Dong Ke Meng School of Electrical Engineering and Telecommunications University of New South WalesSydneyAustralia School of Information and Control Engineering China University of Mining and TechnologyXuzhouJiangsuChina

Continuous monitoring of wind turbine(WT)opera-tion can improve the reliability of the wind turbine and lower the operation and maintenance *** improve the condition mon-itoring(CM)and fault detection performance on WTs,this paper proposes an artificial intelligence-based probabilistic anomaly detection approach that can not only provide a deterministic estimation of the WT condition but also evaluate the uncertainties associated with the *** abnormal WT condition is detected based on the evaluated uncertainties,to provide a noise-free incipient fault *** to the conventional deterministic CM approaches with a residual-based anomaly detection criterion,the proposed probabilistic approach tends to accurately detect the faults earlier,which allows more time for maintenance scheduling to prevent WT component *** early fault detection ability of the proposed approach was verified on an operational WT in China.

关键词： Terms-Condition monitoring faultdetection probabilisticregression SCADA windturbine

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