A Characteristic Database of Microwave Reflection Signals for Composite Insulator Defect Detection

Abstract

The invention discloses a microwave reflecting signal feature data base used for defect detection of composite insulators, which includes: a frequency spectrum conversion module, a denoising module, a signal restoring module, a peak value comparing module, a warning module, and a storage module. The frequency spectrum conversion module is used for converting a space signal and a detection signal into the form of frequency spectrum; the denoising module denoises the two mentioned signals; the signal restoring module is used for restoring the denoised signals and inputting the restored signals into the peak value comparing module for recognition; the peak value comparing module, according to initial signals and the signals outputted by the signal restoring module; recognition on the number of wave peaks of an echo and calculates intensity of same then is carried out, thereby obtaining actual detection results of all inter-layers in the composite insulators are obtained. The invention provides a space background noise elimination method based on the frequency spectrum conversion technology, so that measurement error due to external noises is greatly reduced. By means of peak value recognition after the denoising, the situations of all the all inter-layers in interior of the composite insulators are accurately determined.

Description

technical field [0001] The invention relates to a composite insulator defect detection technology, in particular to a microwave reflection signal characteristic database for composite insulator defect detection. Background technique [0002] The physical properties of composite insulators greatly affect their electrical properties when they are hung on the grid. Once the sheath or mandrel has internal or skin defects such as cracks, air gaps, and penetrations, it will easily lead to increased leakage current or even flashover of the grid line. At present, the common defect detection methods of composite insulators are divided into on-line method and off-line method. The infrared detection method in the online method and the continuous wave microwave detection method in the offline method are two commonly used methods at present. [0003] Currently common insulator-related feature databases are image-based or online recognition types, such as patent CN 103149512A. This typ...

AI Technical Summary

Problems solved by technology

First of all, once the insulator is offline, this type of method cannot be detected, and the scope of use of the method is greatly restricted

Second, the detection and judgment standard of this type of method is the abnormality of the electrical state of the insulator, such as leakage current, partial discharge, and partial temperature rise. Two deficiencies: (1) Some defects currently do not cause electrical anomalies that obviously meet the detection characteristics, so they cannot be detected; (2) When electrical anomalies occur, they are often only one step away from causing power grid accidents, which are left for detection and replacement. The time window is very short and prone to accidents

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