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  • 标题:Robust Fault Diagnosis and Load Torque Estimation in Electrical Drives Using Analytical Redundancy Relations and Sliding Mode Observer
  • 本地全文:下载
  • 作者:Slimane Medjmadj ; Demba Diallo ; Mohammed Mostefai
  • 期刊名称:International Journal on Electrical Engineering and Informatics
  • 印刷版ISSN:2085-6830
  • 出版年度:2018
  • 卷号:10
  • 期号:1
  • 页码:186-202
  • DOI:10.15676/ijeei.2018.10.1.13
  • 出版社:School of Electrical Engineering and Informatics
  • 摘要:Electrical drives are more and more used in transportation applications andindustrial process because of their effective cost and high efficiency. They have becomecritical components and therefore any fault or failure affecting them may seriously endangerthe users and/or induce huge financial costs. As a consequence, early detection and isolationof these faults is recommended if not mandatory to enhance the safety, the availability, thereliability and improve the maintenance and the operational efficiency. AnalyticalRedundancy Relations (ARR) are used to compute to structured residuals on which thediagnosis is based. To smooth the residuals and enhance the fault detection capability, asliding mode observer is developed to compute the derivatives. The analysis of the residualsreveals that they are Gaussian signals with a change in the mean. The comparison betweenthe two-sigma and the two-sided CUSUM methods has shown that the latter is more efficientto compute the thresholds. Therefore with the two-sided CUSUM, the rotor resistance faultis detected with no false alarm. Moreover it is proved that the fault diagnosis is robust to theload torque variations. Beside, thanks to the residual, a load torque estimator is alsodeveloped. Extensive simulation results prove the validity of our approach.
  • 关键词:Electrical drives; Redundancy Relations; Sliding mode; Gaussian distribution;Fault detection and isolation (FDI).
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