{"title":"金属设备低压热处理检漏的分析与预测","authors":"S. Klos, J. Patalas-Maliszewska, M. Bazel","doi":"10.17531/ein.2022.4.12","DOIUrl":null,"url":null,"abstract":"The low-pressure heat treatment of metals enables the continuous improvement of the mechanical and plastic properties of products, such as hardness, abrasion resistance, etc. A significant problem related to the operation of vacuum furnaces for heat treatment is that they become unsealed during operation, resulting from the degradation of seals or the thermal expansion of the construction materials. Therefore, research was undertaken to develop a prediction model for detecting leaks in vacuum furnaces, the use of which will reduce the risk of degradation in the charge being processed. Unique experimental studies were carried out to detect leakages in a vacuum pit furnace, simulated using the ENV 116 reference slot. As a consequence, a prediction model for the detection of leaks in vacuum furnaces- which are used in the heat treatment of metals- was designed, using an artificial neural network. (93% for MLP 15-10-1) was developed. The model was implemented in a predictive maintenance system, in a real production company, as an element in the monitoring of the operation of vacuum furnaces.","PeriodicalId":50549,"journal":{"name":"Eksploatacja I Niezawodnosc-Maintenance and Reliability","volume":"598 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis and prediction of leak detection in the low-pressure heat treatment of metal equipment\",\"authors\":\"S. Klos, J. Patalas-Maliszewska, M. Bazel\",\"doi\":\"10.17531/ein.2022.4.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The low-pressure heat treatment of metals enables the continuous improvement of the mechanical and plastic properties of products, such as hardness, abrasion resistance, etc. A significant problem related to the operation of vacuum furnaces for heat treatment is that they become unsealed during operation, resulting from the degradation of seals or the thermal expansion of the construction materials. Therefore, research was undertaken to develop a prediction model for detecting leaks in vacuum furnaces, the use of which will reduce the risk of degradation in the charge being processed. Unique experimental studies were carried out to detect leakages in a vacuum pit furnace, simulated using the ENV 116 reference slot. As a consequence, a prediction model for the detection of leaks in vacuum furnaces- which are used in the heat treatment of metals- was designed, using an artificial neural network. (93% for MLP 15-10-1) was developed. The model was implemented in a predictive maintenance system, in a real production company, as an element in the monitoring of the operation of vacuum furnaces.\",\"PeriodicalId\":50549,\"journal\":{\"name\":\"Eksploatacja I Niezawodnosc-Maintenance and Reliability\",\"volume\":\"598 1\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2022-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eksploatacja I Niezawodnosc-Maintenance and Reliability\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.17531/ein.2022.4.12\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eksploatacja I Niezawodnosc-Maintenance and Reliability","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.17531/ein.2022.4.12","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Analysis and prediction of leak detection in the low-pressure heat treatment of metal equipment
The low-pressure heat treatment of metals enables the continuous improvement of the mechanical and plastic properties of products, such as hardness, abrasion resistance, etc. A significant problem related to the operation of vacuum furnaces for heat treatment is that they become unsealed during operation, resulting from the degradation of seals or the thermal expansion of the construction materials. Therefore, research was undertaken to develop a prediction model for detecting leaks in vacuum furnaces, the use of which will reduce the risk of degradation in the charge being processed. Unique experimental studies were carried out to detect leakages in a vacuum pit furnace, simulated using the ENV 116 reference slot. As a consequence, a prediction model for the detection of leaks in vacuum furnaces- which are used in the heat treatment of metals- was designed, using an artificial neural network. (93% for MLP 15-10-1) was developed. The model was implemented in a predictive maintenance system, in a real production company, as an element in the monitoring of the operation of vacuum furnaces.
期刊介绍:
The quarterly Eksploatacja i Niezawodność – Maintenance and Reliability publishes articles containing original results of experimental research on the durabilty and reliability of technical objects. We also accept papers presenting theoretical analyses supported by physical interpretation of causes or ones that have been verified empirically. Eksploatacja i Niezawodność – Maintenance and Reliability also publishes articles on innovative modeling approaches and research methods regarding the durability and reliability of objects.