{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,18]],"date-time":"2024-07-18T09:08:28Z","timestamp":1721293708659},"reference-count":30,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,22]],"date-time":"2023-05-22T00:00:00Z","timestamp":1684713600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2166212"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Sichuan Science and Technology Program","award":["2021YFG0101"]},{"DOI":"10.13039\/501100018542","name":"Natural Science Foundation of Sichuan Province","doi-asserted-by":"publisher","award":["2022NSFSC0250"],"id":[{"id":"10.13039\/501100018542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Seriously abnormal data exist in the synchronous monitoring data of transformer DC bias, which causes serious data feature contamination and even affects the identification of transformer DC bias. For this reason, this paper aims to ensure the reliability and validity of synchronous monitoring data. This paper proposes an identification of abnormal data for the synchronous monitoring of transformer DC bias based on multiple criteria. By analyzing the abnormal data of different types, the characteristics of abnormal data are obtained. Based on this, the abnormal data identification indexes are introduced, including gradient, sliding kurtosis and Pearson correlation coefficient. Firstly, the Pauta criterion is used to determine the threshold of the gradient index. Then, gradient is used to identify the suspected abnormal data. Finally, the sliding kurtosis and Pearson correlation coefficient are used to identify the abnormal data. Data for synchronous monitoring of transformer DC bias in a certain power grid are used to verify the proposed method. The results show that the accuracy of the proposed method in identifying mutated abnormal data and zero-value abnormal data is claimed to be 100%. Compared with traditional abnormal data identification methods, the accuracy of the proposed method is significantly improved.<\/jats:p>","DOI":"10.3390\/s23104959","type":"journal-article","created":{"date-parts":[[2023,5,22]],"date-time":"2023-05-22T07:57:32Z","timestamp":1684742252000},"page":"4959","source":"Crossref","is-referenced-by-count":2,"title":["Identification of Abnormal Data for Synchronous Monitoring of Transformer DC Bias Based on Multiple Criteria"],"prefix":"10.3390","volume":"23","author":[{"given":"Zhongqing","family":"Kou","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6334-268X","authenticated-orcid":false,"given":"Sheng","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China"}]},{"given":"Aimin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, China"}]},{"given":"Yuanda","family":"He","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China"}]},{"given":"Long","family":"Chen","sequence":"additional","affiliation":[{"name":"Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518028, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1109\/TPWRD.2020.2975367","article-title":"Evaluation Model of DC Current Distribution in AC Power Systems Caused by Stray Current of DC Metro Systems","volume":"36","author":"Wang","year":"2021","journal-title":"IEEE Trans. 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