The motor fusion diagnosis system is built for reflecting the motor system state in multi-aspect

realizing automatically identifying motor fault patterns and accurately diagnosing the faults by using neural network and evidence theory.After fault feature data are classied and processed in data fusion level

multi-neural networks are used to carry on fusion in motor feature level and carry on local motor fault diagnosis

in order to acquire independent evidence each other.Then D-S evidence theory and fusion algorithm are used to fuse every evidence.Accurate motor fault diagnosis is fulfilled finally.The diagnostic tests prove that the diagnosis system can improve the diagnostic precision and satisfy the requirement for real time.