Medium and low voltage XLPE cable service life evaluation method based on test data and operation and maintenance information

Abstract

The invention discloses a medium and low voltage XLPE cable life evaluation method based on test data and operation and maintenance information. The method comprises the following steps: 1, establishing a medium and low voltage XLPE cable residual life evaluation system; 2, scoring a to-be-evaluated cable test project; 3, scoring the operation and maintenance information of a to-be-evaluated cable; and 4, evaluating the cable residual life. According to the method, the deviation between laboratory accelerated aging and actual on-site operation is effectively avoided, all assessment item inputcomes from performance test data and related operation and maintenance information of an actual operation cable, the method is mainly a non-destructive test, normal operation of a cable line is not affected, and the method is convenient to apply. No artificially specified index weight exists, so that the objectivity of the evaluation system is ensured. The method does not require complete input ofall projects, can provide cable state rating and service life prediction range under the condition of incomplete evaluation indexes, provides cable maintenance suggestions at the same time, and has important guiding significance for engineering practical application.

Description

technical field [0001] The invention relates to a method for evaluating the life of medium and low-voltage XLPE cables in operation, in particular to a method for scoring the status of cables based on test data and operation and maintenance information, and evaluating the life of medium and low-voltage XLPE cables in operation on site according to the obtained scores. Background technique [0002] Cross-linked polyethylene (XLPE) cables have excellent mechanical and electrical properties, without the limitations of traditional oil-filled cables in terms of fire protection, maintenance, and environment, and their engineering applications are increasing year by year. In my country, 35kV and below medium and low voltage XLPE cables have basically replaced oil-paper cables. With the expansion of application scope and the increase of service life, the remaining life evaluation of medium and low voltage XLPE cables has become an urgent problem to be solved in the field of electric...

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Problems solved by technology

[0004] Huo Xiaojing of Xi’an Jiaotong University built a distribution network cable status evaluation system based on the fuzzy comprehensive evaluation method, including status ratings and test items. The status rating items include economic factors and strategic factors in addition to technical factors, but in fact domestic cable asset management is mainly Pay attention to technical factors, economic factors and strategic factors have little influence on the decommissioning decision of cables; secondly, the test items included in the evaluation system are physical and chemical analysis tests on cable insulation slice samples, and the cables need to be separated from the line and destructively sampled , it is difficult to apply in practice; finally, the system cannot give the predicted value of the remaining life of the cable, and does not give targeted guidance for cables with the same rating, which has limited reference value for users

Huang Xiaowei from North China Electric Power University built a 110kV XLPE cable insulation quality evaluation and life prediction model based on the fuzzy comprehensive rating method and artificial neural network. However, most of the test items in the evaluation model are destructive tests, and the application is difficult; Although "external factors" can partially reflect the cable operating environment, it does not take into account important information such as cable fault conditions and operating years, which is not comprehensive enough, and the method of direct scoring by experts lacks objectivity; at the same time, its life prediction model is based on artificial Neural network, when the amount of sample data i

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