{"title":"控制棒驱动机构滚轮剩余使用寿命预测的混合方法","authors":"K. Zhu, Xinwen Zhao, Liming Zhang, Hang Yu","doi":"10.1155/2022/2383789","DOIUrl":null,"url":null,"abstract":"As one of the rotating components in the reluctance motor type control rod drive mechanism (CRDM), the life of the scroll wheel is closely related to the service life of the CRDM. In addition, the prediction of the remaining useful life of the scroll wheel helps to optimize the maintenance process of the CRDM. This paper proposes a hybrid method to predict its remaining useful life when the available degradation data are rare and the failure threshold cannot be accurately defined. First, the particle filtering algorithm, whose state transfer equation is established on the segmental damage physical model, is used to predict the degradation state of the scroll wheel. Second, the proportional hazard model for the relationship between the scroll wheel damage characteristics and reliability model is established to predict the remaining useful life of it. The proposed method focuses on the establishment of segmental damage physical model and the clustering analysis of damage characteristics extracted from vibration signals, which can be used to predict the remaining useful life of the scroll wheel. In addition, the results provide an opportunity for the condition-based preventive maintenance of the CRDM.","PeriodicalId":21629,"journal":{"name":"Science and Technology of Nuclear Installations","volume":" ","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Hybrid Method to Predict the Remaining Useful Life of Scroll Wheel of Control Rod Drive Mechanism\",\"authors\":\"K. Zhu, Xinwen Zhao, Liming Zhang, Hang Yu\",\"doi\":\"10.1155/2022/2383789\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As one of the rotating components in the reluctance motor type control rod drive mechanism (CRDM), the life of the scroll wheel is closely related to the service life of the CRDM. In addition, the prediction of the remaining useful life of the scroll wheel helps to optimize the maintenance process of the CRDM. This paper proposes a hybrid method to predict its remaining useful life when the available degradation data are rare and the failure threshold cannot be accurately defined. First, the particle filtering algorithm, whose state transfer equation is established on the segmental damage physical model, is used to predict the degradation state of the scroll wheel. Second, the proportional hazard model for the relationship between the scroll wheel damage characteristics and reliability model is established to predict the remaining useful life of it. The proposed method focuses on the establishment of segmental damage physical model and the clustering analysis of damage characteristics extracted from vibration signals, which can be used to predict the remaining useful life of the scroll wheel. In addition, the results provide an opportunity for the condition-based preventive maintenance of the CRDM.\",\"PeriodicalId\":21629,\"journal\":{\"name\":\"Science and Technology of Nuclear Installations\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2022-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science and Technology of Nuclear Installations\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1155/2022/2383789\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"NUCLEAR SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science and Technology of Nuclear Installations","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1155/2022/2383789","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
A Hybrid Method to Predict the Remaining Useful Life of Scroll Wheel of Control Rod Drive Mechanism
As one of the rotating components in the reluctance motor type control rod drive mechanism (CRDM), the life of the scroll wheel is closely related to the service life of the CRDM. In addition, the prediction of the remaining useful life of the scroll wheel helps to optimize the maintenance process of the CRDM. This paper proposes a hybrid method to predict its remaining useful life when the available degradation data are rare and the failure threshold cannot be accurately defined. First, the particle filtering algorithm, whose state transfer equation is established on the segmental damage physical model, is used to predict the degradation state of the scroll wheel. Second, the proportional hazard model for the relationship between the scroll wheel damage characteristics and reliability model is established to predict the remaining useful life of it. The proposed method focuses on the establishment of segmental damage physical model and the clustering analysis of damage characteristics extracted from vibration signals, which can be used to predict the remaining useful life of the scroll wheel. In addition, the results provide an opportunity for the condition-based preventive maintenance of the CRDM.
期刊介绍:
Science and Technology of Nuclear Installations is an international scientific journal that aims to make available knowledge on issues related to the nuclear industry and to promote development in the area of nuclear sciences and technologies. The endeavor associated with the establishment and the growth of the journal is expected to lend support to the renaissance of nuclear technology in the world and especially in those countries where nuclear programs have not yet been developed.