基于雙邊型直線電機的故障信息融合診斷方法的研究
徐鳴飛，余海濤，程帆，胡敏強
東南大學 電氣工程學院，江蘇 南京 210096
摘 要：針對雙邊型直線電機的氣隙偏心故障、繞組匝間短路故障，提出了一種基于雙邊型直線電機的故障信息融合診斷方法，該法通過數據層融合、特征層融合、決策層融合以及兩級診斷的方式來實現，其中數據層采用了Park矢量融合方法以及改進的基8FFT算法，特征層采用了模糊人工神經網絡法。將改進的基8FFT算法、模糊人工神經網絡法結合在一起，提高了雙邊型直線電機各種故障的診斷能力。
關鍵詞：雙邊型直線電機；故障信息融合診斷；改進的基8FFT算法；蝶形單元；模糊人工神經網絡
中圖分類號：TM359.4 文獻標識碼：A 文章編號：1007-3175(2015)06-0015-04
Study on Fusion Diagnosis Method of Fault Information Based on Bilateral Linear Motor
XU Ming-fei, YU Hai-tao, CHENG Fan, HU Min-qiang
School of Electrical Engineering, Southeast University, Nanjing 210096, China
Abstract: Aiming at air gap eccentricity fault and winding turn-to-turn short circuit of bilateral linear motor, this paper proposed a kind of fusion diagnosis method of fault information based on bilateral linear motor. This method consisted of the data level fusion, feature level fusion, decision level fusion and the mode of two level diagnosis, of which the data layer adopted the Park vector fusion method and improved 8FFT algorithm, and the feature level adopted the fuzzy artificial neural network. The improved 8FFT algorithm was combined with the fuzzy artificial neural network to raise the diagnosis ability of various kinds of faults of bilateral linear motor.
Key words: bilateral linear motor; fault information fusion diagnoses; improved 8FFT algorithm; butterfly unit; fuzzy artificial neural network
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