{"title":"Fault diagnosis and intelligent maintenance of industry 4.0 power system based on internet of things technology and thermal energy optimization","authors":"","doi":"10.1016/j.tsep.2024.102902","DOIUrl":null,"url":null,"abstract":"<div><p>The application of Internet of Things technology provides a new opportunity for the fault diagnosis and maintenance of power system. This study aims to explore how to improve the fault diagnosis ability of power system through Internet of Things technology, and realize the efficient utilization of heat energy, so as to achieve the goal of intelligent maintenance. Based on the analysis of current power system operation status, this paper determines the key role of thermal energy management in improving system operation efficiency and reducing energy consumption. It then uses iot sensors and data analytics to monitor heat flow and loss in the power system in real time, identifying potential points of failure through big data. In order to realize intelligent maintenance, this paper designs a fault prediction model based on thermal energy optimization, combined with machine learning algorithm, to further improve the accuracy of fault diagnosis. The experimental results show that the fault diagnosis method combined with the Internet of Things technology can significantly reduce the fault incidence and optimize the efficiency of heat energy use. By applying this model, the overall operating cost of the power system is reduced and the maintenance efficiency is improved.</p></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":null,"pages":null},"PeriodicalIF":5.1000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Thermal Science and Engineering Progress","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451904924005201","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
The application of Internet of Things technology provides a new opportunity for the fault diagnosis and maintenance of power system. This study aims to explore how to improve the fault diagnosis ability of power system through Internet of Things technology, and realize the efficient utilization of heat energy, so as to achieve the goal of intelligent maintenance. Based on the analysis of current power system operation status, this paper determines the key role of thermal energy management in improving system operation efficiency and reducing energy consumption. It then uses iot sensors and data analytics to monitor heat flow and loss in the power system in real time, identifying potential points of failure through big data. In order to realize intelligent maintenance, this paper designs a fault prediction model based on thermal energy optimization, combined with machine learning algorithm, to further improve the accuracy of fault diagnosis. The experimental results show that the fault diagnosis method combined with the Internet of Things technology can significantly reduce the fault incidence and optimize the efficiency of heat energy use. By applying this model, the overall operating cost of the power system is reduced and the maintenance efficiency is improved.
期刊介绍：
Thermal Science and Engineering Progress (TSEP) publishes original, high-quality research articles that span activities ranging from fundamental scientific research and discussion of the more controversial thermodynamic theories, to developments in thermal engineering that are in many instances examples of the way scientists and engineers are addressing the challenges facing a growing population – smart cities and global warming – maximising thermodynamic efficiencies and minimising all heat losses. It is intended that these will be of current relevance and interest to industry, academia and other practitioners. It is evident that many specialised journals in thermal and, to some extent, in fluid disciplines tend to focus on topics that can be classified as fundamental in nature, or are ‘applied’ and near-market. Thermal Science and Engineering Progress will bridge the gap between these two areas, allowing authors to make an easy choice, should they or a journal editor feel that their papers are ‘out of scope’ when considering other journals. The range of topics covered by Thermal Science and Engineering Progress addresses the rapid rate of development being made in thermal transfer processes as they affect traditional fields, and important growth in the topical research areas of aerospace, thermal biological and medical systems, electronics and nano-technologies, renewable energy systems, food production (including agriculture), and the need to minimise man-made thermal impacts on climate change. Review articles on appropriate topics for TSEP are encouraged, although until TSEP is fully established, these will be limited in number. Before submitting such articles, please contact one of the Editors, or a member of the Editorial Advisory Board with an outline of your proposal and your expertise in the area of your review.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
