Research On Digital Intelligent Diagnosis Technology Of Mechanical Defect For Disconnectors

Intelligent operation and inspection centered on equipment status warning and fault prediction are the developing directions of the power grid operations.As the high voltage equipment with the most failures and largest number,disconnector still judge mechanical failures by the backward traditional maintenance methods such as manual judgment and disassembly maintenance,so it is of great significance to propose a convenient and reliable fault diagnosis method for disconnector.Based on the fault reasons and research status,the driving torque is proposed as the diagnosis basis for the state of the disconnector in this paper.The reliability of driving torque to judge the mechanical state of isolation switch is verified by various ways.Finally,a digital intelligent diagnosis method of mechanical fault of isolation switch based on operating torque-angle curve is proposed.In the aspect of dynamic simulation,this paper firstly builds three-dimensional model of disconnector according to the real size.The flexible body was analyzed by finite element method and then coupled with the rigid body.Based on this rigid-flexible coupling model,the motion process of the disconnector can be simulated.Then the simulation methods of three typical mechanical faults are put forward innovatively,the result shows that the operating torque changes obviously in different states,which can be used as the diagnosis basis for the isolation switch state.In the aspect of operating torque detection,the paper points out the instability of manual operating torque detection scheme,the matching detection method of torque for disconnector is proposed instead.The experiment results show the variation law of torque waveform under each typical state is basically consistent with the simulation conclusion.In order to identify the mechanical state,this paper pick the meshing-angle,mean torque before meshing and stopping-angle as the characteristic from seven features through Pierce correlation coefficient analysis.The intelligent judgment of the mechanical state of the disconnector is realized with neural network and is optimized with the classification standard and angle relationship.The disconnecting grade is output when the disconnecting fault is judged to be stuck,the angle difference is output when the disconnector is judged not in place,and the distance between the contact fingers of the disconnecting switch is output when the three phases are different,which provides reference for the disconnector maintenance.