Research, Virtual Detection Method Based On Labview Mechanical And Electrical Equipment

Status monitoring and fault diagnosis technology of large-scale complex electromechanical system is a hot research field. Though many approaches and methods have provided for large complex equipment maintenance training, when compared to actual needs, there are still many issues yet to be studied.Focusing on existing research on the state detection system for electromechanical equipments online monitoring technology, And the deficiency of LabVIEW, a type of state virtual detection system based on LabVIEW for electromechanical equipments is proposed. In this paper, a new efficient intelligent fault detection method based on the wavelet transform and the artificial neural networks and the theoretical background of wavelet transform is presented. In addition, the method of the State Virtual Detection System based on LabVIEW is also studied, while a much better BP algorithm based on the traditional BP algorithm is introduced. Accordingly, a wavelet neural networks fault diagnosis systems is developed on LabVIEW and the proposed intelligent fault diagnosis system is simulated. The results shows that the developed system is effective. By using this method, performances of fault diagnosis are improved. Therefore, experts can spend less time on analyzing frequency data. The design method of training sets for neural network is also discussed. A well designed training set is benefit to training and improving generalization capability of neural networks.The system provides online fault diagnosis and state detection; its desirable dynamic and adaptive properties can also meet the processing demands of different electromechanical equipments and testing signals.