智能异构模型在电机故障诊断中的研究

提出以测试电机的三相电流噪声为电机故障特征信号的诊断方法,建立电机电流噪声多元时序模型,将时序模型的多元残差序列化为一元序列作为故障总体检测指标。针对多元时序模型参数φi的特点,提出了多层NN的故障类型识别模型,应用APEX网络提取初始模式向量的分类信息,利用前馈网络建立其识别函数,实践证明该诊断方法是正确的。

Research of Intelligent Various Structure Models in Motor Faults Diagnosis

The paper puts forward a set of faults diagnosis methods of testing the noise of the three-phase motor current which shows the characteristics of the motor faults. and multi-varieties time series models of the noise is established, the multi-varieties residual series is changed to the monistical as the fault detection index. In the fight of trait of the model parameter φi, presenting a faults classification recognition model based on the multi -layer NN structure, using APEX network extracts classification Information of the initial pattern vector,making use of feedforward network establishes the classification function. The diagnosis way is correct by practising.