Partial discharge on-line monitoring and diagnosing method

Abstract

The invention relates to the technical field of cable equipment detection, in particular to a partial discharge on-line monitoring and diagnosis method, which comprises the following steps: step 1, data acquisition, step 2, monitoring system establishment, step 3, detection and diagnosis, step 4, risk classification, step 5, risk tracking and step 6, risk control. According to the invention, through an electromagnetic field sensing module, a noise sensing module, a temperature sensing module, a humidity sensing module and a dust sensing module, the surrounding environment can be conveniently detected, the equipment can be conveniently protected in advance according to the measured data, and the influence of the environment on a discharge signal can be conveniently analyzed; and the accuracy of discharge signal detection is improved by recording the surrounding environment and conveniently comparing the recorded surrounding electromagnetic data, the discharge diagnosis result is more intuitively compared through the discharge accumulation comparison diagram and the similar characteristic pulse comparison diagram, the high-voltage cable edge defect condition is judged, and the detection and diagnosis effect is improved.

Description

technical field [0001] The invention relates to the technical field of cable equipment detection, in particular to a partial discharge online monitoring and diagnosis method. Background technique [0002] On-line monitoring of electric power equipment generally adopts portable testing equipment, which conducts on-site testing of equipment state quantities under running conditions. , suitable for the current my country's electric power production management model and business model. [0003] At present, the state evaluation and condition maintenance of high-voltage electrical equipment at home and abroad are being carried out, and how to obtain accurate state quantities is the key factor for implementation. Partial discharge, as the main manifestation of poor insulation status of high-voltage electrical equipment, is not only the main cause of insulation aging The reason is also the main characteristic parameter to characterize the insulation condition, so it has been widely ...

AI Technical Summary

Problems solved by technology

[0004] In the conventional pulse current method, the measurement frequency band is generally within 1MHz. This method has been fully applied in the laboratory. However, in substations and other sites, due to a large number of on-site interference in this frequency range, in order to avoid interference, currently The mainstream method is to move the frequency of the measurement signal up to the high-frequency band (3MHz-30MHz) or even the ultra-high-frequency band (300MHz-3GHz) to detect partial discharge signals. The sensors generally use Rogowski coils or ultra-high-frequency sensors. The sensor is coupled to the RF amplifier, filter or detector, and then quantified by the digital sampling system, and the digital processing is completed. The RF detection method and the ultra-high frequency detection method can avoid a large number of low-frequency and intermediate-frequency interference in the field, but they still cannot be used. The hardware completely eliminates interference, and the suppression of interference must be carried out in combination with digital algorithms

[0005] At present, a lot of research work has been carried out on partial discharge anti-interference and pattern recognition at home and abroad. The research focus is mainly on how to construct partial discharge patterns that can reflect different types of discharge sources, extract effective characteristic parameters from these patterns, and train appropriate classification The device finally makes a judgment on the type of partial discharge source. These studies are usually carried out in a single-defect insulation system, and it is confirmed that the single partial discharge source type of the artificial defect model can be successfully identified. However, electrical equipment is in the process of manufacturing and operation. Among them, many factors will lead to the formation of insulation defects. Under long-term operating voltage, partial discharges caused by various defects often exist at the same time. The measured partial discharge signal is mostly the sum of these discharge signals, and its identification and classification are quite complicated.

[0006] The existence of the above factors greatly reduces the accuracy and sensitivity of partial discharge detection and diagnosis of high-voltage cable insulation defects, which may easily cause misjudgment. Therefore, how to use the existing advanced technology to minimize the interference on the detection site and accurately Extract the partial discharge signal, provide information for the subsequent insulation diagnosis more reliably and sensitively, and become the key to the on-line monitoring and diagnosis of partial discharge of high-voltage cable insulation defects