{"title":"基于迭代策略的概率正则化负载重建方法","authors":"","doi":"10.1016/j.jsv.2024.118719","DOIUrl":null,"url":null,"abstract":"<div><p>In view of the poor solution accuracy of the traditional Green's function-based load reconstruction method, this paper proposes a load reconstruction method based on an iterative solution strategy. Using Green's function matrix as the gradient information of the load and dynamic response, the load history is continuously updated to minimize the residual difference between the measured response and the reference model response to obtain a reconstruction result closer to the real load history. In addition, this paper derives a Green's function matrix based on the acceleration response time series, which extends the application scope of the traditional Green's function-based load reconstruction method. Furthermore, considering the influence of uncertainty factors such as measurement noise and model error on the reconstruction results, this paper proposes a probabilistic regularized load reconstruction method based on an iterative strategy by using probability theory to describe the uncertainty. The influence of uncertainty factors is considered both in the selection of regularization parameters and in the load reconstruction process. The effectiveness of the proposed method is verified by an example of a 35-rod truss, and the effects of model error and measurement noise on the reconstruction results are discussed. Compared with the traditional method, the proposed method can achieve more accurate and robust load reconstruction results, and the effect of uncertainty on the load reconstruction results can be quantified in the framework of probability theory.</p></div>","PeriodicalId":17233,"journal":{"name":"Journal of Sound and Vibration","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probabilistic regularization load reconstruction method based on iterative strategy\",\"authors\":\"\",\"doi\":\"10.1016/j.jsv.2024.118719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In view of the poor solution accuracy of the traditional Green's function-based load reconstruction method, this paper proposes a load reconstruction method based on an iterative solution strategy. Using Green's function matrix as the gradient information of the load and dynamic response, the load history is continuously updated to minimize the residual difference between the measured response and the reference model response to obtain a reconstruction result closer to the real load history. In addition, this paper derives a Green's function matrix based on the acceleration response time series, which extends the application scope of the traditional Green's function-based load reconstruction method. Furthermore, considering the influence of uncertainty factors such as measurement noise and model error on the reconstruction results, this paper proposes a probabilistic regularized load reconstruction method based on an iterative strategy by using probability theory to describe the uncertainty. The influence of uncertainty factors is considered both in the selection of regularization parameters and in the load reconstruction process. The effectiveness of the proposed method is verified by an example of a 35-rod truss, and the effects of model error and measurement noise on the reconstruction results are discussed. Compared with the traditional method, the proposed method can achieve more accurate and robust load reconstruction results, and the effect of uncertainty on the load reconstruction results can be quantified in the framework of probability theory.</p></div>\",\"PeriodicalId\":17233,\"journal\":{\"name\":\"Journal of Sound and Vibration\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Sound and Vibration\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022460X24004814\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ACOUSTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Sound and Vibration","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022460X24004814","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ACOUSTICS","Score":null,"Total":0}
Probabilistic regularization load reconstruction method based on iterative strategy
In view of the poor solution accuracy of the traditional Green's function-based load reconstruction method, this paper proposes a load reconstruction method based on an iterative solution strategy. Using Green's function matrix as the gradient information of the load and dynamic response, the load history is continuously updated to minimize the residual difference between the measured response and the reference model response to obtain a reconstruction result closer to the real load history. In addition, this paper derives a Green's function matrix based on the acceleration response time series, which extends the application scope of the traditional Green's function-based load reconstruction method. Furthermore, considering the influence of uncertainty factors such as measurement noise and model error on the reconstruction results, this paper proposes a probabilistic regularized load reconstruction method based on an iterative strategy by using probability theory to describe the uncertainty. The influence of uncertainty factors is considered both in the selection of regularization parameters and in the load reconstruction process. The effectiveness of the proposed method is verified by an example of a 35-rod truss, and the effects of model error and measurement noise on the reconstruction results are discussed. Compared with the traditional method, the proposed method can achieve more accurate and robust load reconstruction results, and the effect of uncertainty on the load reconstruction results can be quantified in the framework of probability theory.
期刊介绍:
The Journal of Sound and Vibration (JSV) is an independent journal devoted to the prompt publication of original papers, both theoretical and experimental, that provide new information on any aspect of sound or vibration. There is an emphasis on fundamental work that has potential for practical application.
JSV was founded and operates on the premise that the subject of sound and vibration requires a journal that publishes papers of a high technical standard across the various subdisciplines, thus facilitating awareness of techniques and discoveries in one area that may be applicable in others.