Yunpeng Fan , Yingwei Zhang , Chaomin Luo , Zhuming Bi
{"title":"Fault detection for electric magnesium melting furnace based on cooperative modeling","authors":"Yunpeng Fan , Yingwei Zhang , Chaomin Luo , Zhuming Bi","doi":"10.1016/j.conengprac.2025.106490","DOIUrl":null,"url":null,"abstract":"<div><div>A high level of process monitoring is necessary for the safety and product quality of an electric magnesium melting furnace. However, plant upgrading, such as the addition of cameras, has brought challenges to the traditional monitoring methods although more information about furnace conditions can be obtained. This is because graphic data and sensor data are completely different in structure and calculation. Therefore, a compatible collaborative modeling and fault detection method is proposed in this paper. Firstly, the system and residual subspace of data are obtained by minimizing the statistical distance of data from different information sources through collaborative modeling. Then the weighted information fusion of subspace data is carried out to develop and integrate a new hierarchical fault detection and alarm scheme. Finally, the feasibility and effectiveness of the proposed method are verified by the real data of magnesia smelting process.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106490"},"PeriodicalIF":5.4000,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering Practice","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967066125002527","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
A high level of process monitoring is necessary for the safety and product quality of an electric magnesium melting furnace. However, plant upgrading, such as the addition of cameras, has brought challenges to the traditional monitoring methods although more information about furnace conditions can be obtained. This is because graphic data and sensor data are completely different in structure and calculation. Therefore, a compatible collaborative modeling and fault detection method is proposed in this paper. Firstly, the system and residual subspace of data are obtained by minimizing the statistical distance of data from different information sources through collaborative modeling. Then the weighted information fusion of subspace data is carried out to develop and integrate a new hierarchical fault detection and alarm scheme. Finally, the feasibility and effectiveness of the proposed method are verified by the real data of magnesia smelting process.
期刊介绍:
Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper.
The scope of Control Engineering Practice matches the activities of IFAC.
Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.