Condition evaluation of energized test devices based on multi-source heterogeneous data

Xian Meng; XinXi Yu; XiaoPing Li; Zhu Zhu

doi:10.1117/12.2628670

22 April 2022 Condition evaluation of energized test devices based on multi-source heterogeneous data

Xian Meng, XinXi Yu, XiaoPing Li, Zhu Zhu

Proceedings Volume 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021); 121740F (2022) https://doi.org/10.1117/12.2628670
Event: International Conference on Internet of Things and Machine Learning (IoTML 2021), 2021, Shanghai, China

Abstract

The condition of energized test devices directly affects the quality of power grid condition-based maintenance. At present, the condition of energized test devices is mainly judged by the qualified or unqualified test reports. In this paper, the condition quantities affecting devices quality are divided into four categories: test report, quality information, subjective evaluation and special inspection, and the quantitative scores are given. Taking UHF partial discharge detector and infrared thermal imager as examples, the special detection and evaluation are carried out, and the test result range is refined. The modified Wilson confidence interval ranking algorithm is introduced to realize the objective and fair ranking of energized test devices manufacturer quality.

Citation Download Citation

Xian Meng, XinXi Yu, XiaoPing Li, and Zhu Zhu "Condition evaluation of energized test devices based on multi-source heterogeneous data", Proc. SPIE 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021), 121740F (22 April 2022); https://doi.org/10.1117/12.2628670

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