Meshing State Diagnosis Of Moving And Stationary Contacts In Withdrawable Switchgear Based On A Motor

Recently,the intelligent power grid technology had been gaining its progress.The level of equipment monitoring has been continuously improving.Taking advantage of device level information has been improved the stability and security of the power grid.Handcart motors are important devices for medium-voltage switchgear.Now,the general withdrawable switchgear cannot monitor the running state of the motor.In the view of this problem,an intelligent motor used by handcart in withdrawable switchgear was introduced.On the basis of collecting the running data,methods to calculate the meshing distance and the concentricity of the moving and stationary contacts of the switchgear were proposed.Moreover,the corresponding host computer software were developed to display the real-time message and the diagnosis results,in order to provide the operators with intuitive messages.The specific work is as follows:1.An intelligent motor module used to changing the position of withdrawable switchgear was introduced.It included a BLDCM,a reducer and a controller.The controller is responsible to transfer the armature data to the host computer software.Then the BLDCM's mathematical model was analyzed.Factors affecting the armature current and speed were determined,which had been verified by simulation.The result showed that the armature current and speed were only affected by resistance,which found the theoretical foundation for using the message to diagnosis the contacts' states.2.A method which was applicable to different concentricity to calculate the meshing distance of the contacts with the real-time message was proposed.Firstly,the influence of the concentricity deviation on meshing distance was analyzed.Three concentricity deviation classes were set according relative research and the production.Then the method to calculate meshing distance with "meshing points" that was one of the sampled current points and the work to locate it were demonstrated.That included finding the phase during which the "meshing point" occurred,samples reconstruction,building eigenvectors and using a support vector machine to locate the point.At last,progress to calculate the meshing distance was displayed.3.A method to diagnosis the concentricity with running data of the motor was proposed.Firstly,the data in the meshing-in phase was analyzed.A mean filter and Gaussian fitting were used to process data to enhance classification.Then eigenvectors were constructed with fitting parameter A,xmax and the mean current during the meshing-in phase.At last,a BP network was employed to recognize the centricity.4.To test the calculation of meshing distance and recognition of concentricity,collected data under 3 concentricity deviation each for 20 times.Meshing distances were measured by hand then compared with the calculation results and the recognition results.It has been proved that calculations were accurate taking"compared to the manual measurement,the error is within 1mm" as the principle.And the recognition rate is high.The methods provided new way to recognize meshing distance and concentricity of tulip contacts without sensors.5.In order to realize human-computer interaction,the host computer software program was designed and programmed for intelligent motor module.The program framework were written by C#and the data processing module were programmed by MATLAB.The host computer software functions included serial port control,data transmission and reception,function calling and data processing and display.Not only can the smart motor module provide people directly with the operation information,but also do equipment state diagnosis.