{"title":"半自磨工艺运行负荷与效率的模糊综合评价","authors":"Zhenhong Liao;Jinhua She;Wen Chen;Min Wu;Yanglong Zhang","doi":"10.1109/TFUZZ.2025.3583874","DOIUrl":null,"url":null,"abstract":"Semiautogenous grinding (SAG) processes are widely used in mineral processing. In industrial production, operators often lack a comprehensive and objective assessment of the operating conditions of an SAG process and usually make different control decisions based on experience to meet production demands. This article explains a two-level fuzzy comprehensive evaluation method for the load and efficiency of an SAG process. First, the operation mechanism of an SAG process is analyzed, and the evaluation indicators of load and efficiency are determined. Then, the levels and weights of each indicator are determined by combining expert experience and actual production data. Finally, the operating load level is first evaluated by combining the information entropy weight and fuzzy computation. When the load level is within an acceptable range, a fuzzy comprehensive evaluation of the efficiency level is then performed. The modeling method of efficiency indicator, circulating load ratio (CLR), is integrated with random forest and Bayesian optimization to carry out the efficiency evaluation. Experiments using actual production data demonstrate CLR modeling performance with a mean absolute error of 1.084% and a mean absolute percentage error of 9.415%. The accuracy of the operating efficiency evaluation is 81.69%. This method provides an objective and uniform criterion for operators to evaluate the operating load and efficiency of an SAG process, thus guiding the regulation of actual production.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 9","pages":"3145-3155"},"PeriodicalIF":11.9000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fuzzy Comprehensive Evaluation for Operating Load and Efficiency of Semiautogenous Grinding Process\",\"authors\":\"Zhenhong Liao;Jinhua She;Wen Chen;Min Wu;Yanglong Zhang\",\"doi\":\"10.1109/TFUZZ.2025.3583874\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Semiautogenous grinding (SAG) processes are widely used in mineral processing. In industrial production, operators often lack a comprehensive and objective assessment of the operating conditions of an SAG process and usually make different control decisions based on experience to meet production demands. This article explains a two-level fuzzy comprehensive evaluation method for the load and efficiency of an SAG process. First, the operation mechanism of an SAG process is analyzed, and the evaluation indicators of load and efficiency are determined. Then, the levels and weights of each indicator are determined by combining expert experience and actual production data. Finally, the operating load level is first evaluated by combining the information entropy weight and fuzzy computation. When the load level is within an acceptable range, a fuzzy comprehensive evaluation of the efficiency level is then performed. The modeling method of efficiency indicator, circulating load ratio (CLR), is integrated with random forest and Bayesian optimization to carry out the efficiency evaluation. Experiments using actual production data demonstrate CLR modeling performance with a mean absolute error of 1.084% and a mean absolute percentage error of 9.415%. The accuracy of the operating efficiency evaluation is 81.69%. This method provides an objective and uniform criterion for operators to evaluate the operating load and efficiency of an SAG process, thus guiding the regulation of actual production.\",\"PeriodicalId\":13212,\"journal\":{\"name\":\"IEEE Transactions on Fuzzy Systems\",\"volume\":\"33 9\",\"pages\":\"3145-3155\"},\"PeriodicalIF\":11.9000,\"publicationDate\":\"2025-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Fuzzy Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11054308/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Fuzzy Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11054308/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Fuzzy Comprehensive Evaluation for Operating Load and Efficiency of Semiautogenous Grinding Process
Semiautogenous grinding (SAG) processes are widely used in mineral processing. In industrial production, operators often lack a comprehensive and objective assessment of the operating conditions of an SAG process and usually make different control decisions based on experience to meet production demands. This article explains a two-level fuzzy comprehensive evaluation method for the load and efficiency of an SAG process. First, the operation mechanism of an SAG process is analyzed, and the evaluation indicators of load and efficiency are determined. Then, the levels and weights of each indicator are determined by combining expert experience and actual production data. Finally, the operating load level is first evaluated by combining the information entropy weight and fuzzy computation. When the load level is within an acceptable range, a fuzzy comprehensive evaluation of the efficiency level is then performed. The modeling method of efficiency indicator, circulating load ratio (CLR), is integrated with random forest and Bayesian optimization to carry out the efficiency evaluation. Experiments using actual production data demonstrate CLR modeling performance with a mean absolute error of 1.084% and a mean absolute percentage error of 9.415%. The accuracy of the operating efficiency evaluation is 81.69%. This method provides an objective and uniform criterion for operators to evaluate the operating load and efficiency of an SAG process, thus guiding the regulation of actual production.
期刊介绍:
The IEEE Transactions on Fuzzy Systems is a scholarly journal that focuses on the theory, design, and application of fuzzy systems. It aims to publish high-quality technical papers that contribute significant technical knowledge and exploratory developments in the field of fuzzy systems. The journal particularly emphasizes engineering systems and scientific applications. In addition to research articles, the Transactions also includes a letters section featuring current information, comments, and rebuttals related to published papers.