Qiugen Pei, Zewu Peng, Qiang Chen, Yuhong Shen, Huaquan Su
{"title":"Construction of power equipment fault feature model based on unified semantic expression","authors":"Qiugen Pei, Zewu Peng, Qiang Chen, Yuhong Shen, Huaquan Su","doi":"10.1117/12.2671876","DOIUrl":null,"url":null,"abstract":"In view of the poor recognition effect of power equipment fault features in China, a method for building power equipment fault feature model based on unified semantic expression is proposed. The power equipment fault information is identified by combining the unified semantic expression principle. And the phase space reconstruction algorithm is constructed according to the feature semantics of the identified fault information. The power equipment fault feature model is optimized based on the reconstruction results. Finally, it is verified by experiments, the power equipment fault feature model based on unified semantic expression can quickly identify the semantic features of fault information in the process of practical application, and effectively improve the recognition effect.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Mechatronics Engineering and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2671876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In view of the poor recognition effect of power equipment fault features in China, a method for building power equipment fault feature model based on unified semantic expression is proposed. The power equipment fault information is identified by combining the unified semantic expression principle. And the phase space reconstruction algorithm is constructed according to the feature semantics of the identified fault information. The power equipment fault feature model is optimized based on the reconstruction results. Finally, it is verified by experiments, the power equipment fault feature model based on unified semantic expression can quickly identify the semantic features of fault information in the process of practical application, and effectively improve the recognition effect.