{"title":"Research on Power Equipment Status Detection Based on Deep Learning","authors":"Bao YuDe","doi":"10.1109/EEI59236.2023.10212769","DOIUrl":null,"url":null,"abstract":"In response to the higher requirements for the intelligence, reliability, and availability of images in equipment status inspection business applications, a deep learning based power equipment status detection scheme is proposed. The scheme is based on heterogeneous platform technology for state detection and efficiency improvement of multiple types of power equipment, achieving efficient recognition of typical power equipment states. Through low-power power equipment state image acquisition and analysis devices, various forms of detection are provided for applications, achieving state detection of multiple types of power equipment. This plan improves the inspection mode of power equipment, enhances the control of equipment status and the decision-making level of operation and inspection, accelerates the speed of management decision-making, and further enhances the level of power production management.","PeriodicalId":363603,"journal":{"name":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEI59236.2023.10212769","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 response to the higher requirements for the intelligence, reliability, and availability of images in equipment status inspection business applications, a deep learning based power equipment status detection scheme is proposed. The scheme is based on heterogeneous platform technology for state detection and efficiency improvement of multiple types of power equipment, achieving efficient recognition of typical power equipment states. Through low-power power equipment state image acquisition and analysis devices, various forms of detection are provided for applications, achieving state detection of multiple types of power equipment. This plan improves the inspection mode of power equipment, enhances the control of equipment status and the decision-making level of operation and inspection, accelerates the speed of management decision-making, and further enhances the level of power production management.