Research And Application Of Intelligent Fault Diagnosis System For Asynchronous Motor

As a kind of device can convert electrical energy into mechanical energy, motor has a pivotal role in industrial production, especially as a main motive force and driving device in industrial production, asynchronous motors have its importance beyond doubt. In the coal mine,energy, chemical and other industries, large asynchronous motor is the core equipment, once the fault of the asynchronous motor occurs, the entire industrial operation system may face the risk of a full paralysis, causing unpredictable economic losses, and even endanger the life safety of the staff in the field. Therefore, the fault diagnosis of asynchronous motor has important research significance.This paper aiming at the operation state detection of the asynchronous motor, adopting PT100, current transformer, voltage transformer, acceleration sensor and Advantech PCI1711 as the hardware and using LabVIEW and MATLAB mixed programming technology developed a asynchronous motor real-time state monitoring and fault diagnosis system. The data acquisition function of this system is mainly composed of Advantech PCI1711 data acquisition card. Data acquisition function of the system mainly completed by Advantech data acquisition card pci1711,which is a high speed multi function data acquisition card based on PCI bus, and can achieve the digital quantity, analog input and output control. Data signals collected by data acquisition system are to do some data analysis in the signal analysis system developed by LabVIEW software in the host computer.For the induction relation between rotor winding and stator winding of asynchronous motor,signal analysis system used the park vector transformation to do some data analysis for the stator three phase current of asynchronous motor,then gave the simulation images of the Phase fault and rotor broken bars fault. At the same time, in order to solve the defect which Park vector transformation graph is not obvious owing to the rotor fault signal’s weakness, using the optimal compensate method to deal with the noise of stator current and getting the spectrum of the stator current to do auxiliary judgment. For vibration signal, used virtual filter to do filtering processing. Then carried on the envelope analysis through the MATLAB Hilbert transformation,geting the corresponding waveform diagram, and the fault characteristics of the envelope signal.The data of fault feature signal extract by signal analysis system was stored in the database system, and compared with the data in knowledge base throng the fault diagnosis expert system.Finally determine the failure results.The database of the expert system developed by Access software, and established the knowledge base by fault tree theory, finally completeexpert system design by C language programming 。 LabVIEW call the expert system through the CIN function node(Interface Node Code).The design of intelligent motor fault diagnosis system in this topic had been tested in coal storage plant in Yanzhou Mining Group Baodian coal mine and had a good real-time data monitoring and accurate fault diagnosis ability been proved. The design had achieved the expected goal, and had an important role in promoting the production safety and optimal management of coal storage workshop.