Research And Application Of On-line Condition Monitoring And Fault Diagnosis System For Asynchronous Motor

Asynchronous motors have found an increasingly wide utilization in fields such as industry and agriculture,but its operation condition is more and more complex.Even if it is regularly repaired,various failures are inevitable.The failure of a single machine will cause the whole production line to stop production and cause huge economic losses.Therefore,the research and application of on-line condition monitoring and fault diagnosis of asynchronous motor is of great significance in engineering application to effectively improve production safety,improve production efficiency and reduce failure shutdown rate.In this paper,the fault mechanism of rotor bar breaking,bearing defect,phase loss,rotor unbalance and foundation looseness of squirrel cage asynchronous motor is studied,and rigorous theoretical derivation is made.In view of the problem that the fault component of rotor bar is easy to be submerged by the fundamental wave,the solution of Butterworth notch filter to restrain or weaken the fundamental wave component is proposed,which effectively highlights the fault component.For bearing fault,unbalance and foundation looseness,Butterworth low-pass filter is designed to filter vibration signal to eliminate the influence of high-frequency noise.The existing algorithm of motor fault diagnosis is studied,and its advantages and disadvantages are analyzed.An improved Hilbert-Huang Transform method based on Butterworth filter and correlation theory is proposed.The correlation analysis of Intrinsic Mode Functions and original signal is used to judge the authenticity of Intrinsic Mode Functions,which can effectively solve the problem of false components and mode aliasing.Based on LabVIEW,an asynchronous motor on-line monitoring and fault diagnosis system is established.The current and vibration signals are collected by NI6009 Data Acquisition Board,and the sensor data is stored in the access database in OLE field format.Data acquisition and real-time monitoring are realized,and early faults can be found in time through alarm indication when the equipment is abnormal.By using the variant-to-data conversion function to read data from the database,a comprehensive analysis platform is established with the improved Hilbert-Huang Transform method as the main method,Fast Fourier Transform and time-domain statistical analysis as the auxiliary.It makes full use of the good human-computer interface of LabVIEW,and overcomes the problems of large hardware expenditure and slow algorithm operation of the joint programming of LabVIEW and MATLAB.Based on the system,the typical faults of the motor,such as rotor broken bar,bearing defect,rotor imbalance,foundation looseness and rotor broken bar compound fault,are verified by experiments.By changing the power supply frequency and load size,a large number of laboratory analysis and optimization are carried out,so that the system has engineering application conditions.Experiments and field tests show that the system has high reliability and accuracy for on-line monitoring and fault diagnosis of asynchronous motor,and has good theoretical and practical value.