Mechanical defect detection of porcelain column high-voltage disconnector based on operating torque

Abstract

Currently, there is no effective detection and diagnosis technology for the frequently happened mechanical defects of disconnectors. A porcelain column high-voltage disconnector is taken as the object to study the influence of mechanical defects, including bearing jamming, axle pin jamming, and three-phase position asynchrony on the operating torque through geometric mechanics deduction. An operating torque detection technology is proposed, which could accurately measure the operating torque of the disconnector without destroying its original shafting. Using this technology, the operating torque curves of the disconnector in normal state and typical mechanical defect simulation states are measured and compared. The results indicate that the operating torque changes with the mechanical state of disconnector, and these changes could be quantified through the proposed detection technology. And the types of mechanical defects can be distinguished according to their different effects on the operating torque curve. Based on this, a practical mechanical defects diagnosis method is summarized to provide reference for maintainers to diagnose the mechanical defects of disconnectors.

Research and Application of Mechanical State Diagnosis Method of Horizontal Telescopic Type Disconnector

“…GW23 type disconnector is a typical open disconnector, with the advantages of obvious fracture and small phase spacing [1][2][3], and has been widely used in power grids in recent years [4][5][6][7]. For the detection of the mechanical state of the isolating switch [8], different scholars have proposed to use different signals such as the driving motor running signal [9][10][11][12], the torque and rotation angle signal IOP Publishing doi:10.1088/1742-6596/2452/1/012024 2 [13][14][15], and the vibration signal [16][17][18][19][20] as the method to judge the mechanical state. After using different detection techniques to obtain samples representing the mechanical state of the isolating switch, classifying the samples according to their characteristics of the samples is called state diagnosis.…”

Research on mechanical state identification method of multi-type disconnectors based on difference curve and SVM

“…Literature [14] collects the motor stator current during the action process of the GW4 disconnector under different mechanical states, uses synchronous squeeze wavelet transform to obtain time-frequency analysis and signal reconstruction, and establishes a fault diagnosis system with a support vector machine as the classifier. Reference [15] proposes a non-implanted detection technology for the operating torque and rotation angle of the disconnector, which uses an external drive motor to drive the disconnector to move at a constant speed through the manual operation shaft, and proposes a mechanical state diagnosis of the GW4-type disconnector based on the operating torque and rotation angle. Reference [16] takes the GW4 isolation switch as the research object, detects the vibration signal of the isolation switch at multiple positions in the simulated mechanical fault test, and uses the method of combining the time domain and the frequency domain to extract the characteristic factors, and combines the multi-SVDD state evaluation algorithm.…”

A novel multi-information decision fusion based on improved random forests in HVCB fault detection application

“…With the development of intelligent detection technology for electrical equipment, as the core equipment for power protection and safety, the status monitoring and management of high-voltage circuit breakers (HVCBs), which play a key * Author to whom any correspondence should be addressed. role in power protection and safety, have become important topics [1,2]. As two typical measurement signals, the contact stroke [3,4] and coil current [5,6] information have been widely analyzed and applied by many researchers in fault identification of HVCBs.…”