摘 要：為進一步提高異步電動機故障檢測的準確性，將人工神經網絡應用于異步電動機故障檢測。通過提出一種基于BP神經網絡的電機故障檢測方法，設計了適合該檢測系統的網絡結構。仿真結果表明：相對于其他算法，該網絡結構具有更快的學習速度和更高的學習精度，完全適用于電動機故障檢測。
關鍵詞：人工神經網絡；異步電動機；故障檢測；模式識別；模式分類
中圖分類號：O242.1；TP751 文獻標識碼：A
文章編號：1672-4984（2008）03-0135-03
Fault diagnosis system for asynchronous electromotor based on artificial neural network
LIU Zhao-you， QIU Shi-hui， WANG Qi
（Department of Electrical Engineering，Chengdu Electromechanical College，Chengdu 610031，China）
Abstract： Artificial neural network was applied to detect the fault of asynchronous electromotor in order to improve the accuracy of asynchronous electromotor fault diagnosis. One fault diagnosis method for electromotor based on BP neural network was proposed，and the network structure was designed for this diagnosis system. The simulation result indicates that the net structure has mush faster learning speed and more superior learning precision compared with other algorithm. It is entirely practical for the fault diagnosis system of the electromotor.
Key words： Artificial neural network； Electromotor； Fault diagnosis system； Pattern recognition； Pattern classification
Editor：liyan
