Cable local aging detection method and detection device

Abstract

The invention relates to a cable local aging detection method and detection device, and the method comprises the steps of: measuring a transfer function of a cable in a frequency range, detecting thelocal aging of the cable through employing a detection deep neural network D-CNN and a positioning deep neural network L-CNN according to the amplitude of the transfer function and based on a deep learning algorithm, and estimating the aging position and the aging degree. Because the transfer function is not influenced by the phase angle error caused by real-time communication in the system, online detection is easy to realize. The detection method provided by the invention is suitable for the detection of various local aging modes, and can achieve the estimation of the aging degree, thereby providing a basis for the subsequent preventive maintenance. Meanwhile, the problem of local aging positioning under the variable load condition is solved based on transfer learning, the precision of the detection method under a variable load condition can be improved based on parameter fine adjustment, and the calculation cost and the calculation time are saved.

Description

technical field [0001] The invention relates to the technical field of power system equipment detection, in particular to a method and a detection device for local cable aging detection. Background technique [0002] The underground cables in the distribution network are often aging due to moisture or overheating, which will eventually cause insulation breakdown and short-circuit faults, which will affect the safe and reliable operation of the power system and bring huge economic losses. Especially for the current urban distribution network that is gradually expanding in scale, the operating environment of underground cables is complex. A certain branch cable may be partially aging due to overheating caused by long-term high-load current operation, or due to some insulation in the production and processing process. Defects lead to localized hot spot aging. However, most of the current research focuses on the location of the short-circuit fault of the cable, which is a passi...

AI Technical Summary

Problems solved by technology

[0004] (1) It can only realize offline detection, which limits the application of this method in practical systems; (2) This method relies on the significant change of impedance at the end of the aging section of the locally aged cable, resulting in low monitoring sensitivity, and it is difficult to apply to the environment with smooth impedance changes (3) This method can only determine the impedance change point, and it is difficult to estimate the aging degree

It is also difficult to apply to the case of terminal aging

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