Chunbing Zhang, Xiaofeng Liu, Daiping Wei and Lin Bo
{"title":"Quantitative characterization of fatigue damage in plate structures based on FSOM","authors":"Chunbing Zhang, Xiaofeng Liu, Daiping Wei and Lin Bo","doi":"10.1088/1361-665x/ad5a58","DOIUrl":null,"url":null,"abstract":"For the problem of fatigue damage detection and damage degree assessment of plate structures, a quantitative damage assessment method based on the fast self-organizing feature mapping (FSOM) algorithm is proposed in this paper. The damage detection problem is transformed into a binary classification problem by extracting multidimensional damage features of the Lamb wave signal in plate to be detected and selecting damage sensitive features. Then, the FSOM network is used to identify the health state of the plate to be inspected, and the damage index is obtained by fusing the damage sensitive features using FSOM to quantitatively evaluate the damage level of the plate to be inspected. Simulation and experimental results show this method has a good dynamic tracking capability for the fatigue damage evolution of aluminum and composite plates, and can achieve quantitative assessment of fatigue damage of plate structures.","PeriodicalId":21656,"journal":{"name":"Smart Materials and Structures","volume":"36 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Materials and Structures","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1088/1361-665x/ad5a58","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
引用次数: 0
Abstract
For the problem of fatigue damage detection and damage degree assessment of plate structures, a quantitative damage assessment method based on the fast self-organizing feature mapping (FSOM) algorithm is proposed in this paper. The damage detection problem is transformed into a binary classification problem by extracting multidimensional damage features of the Lamb wave signal in plate to be detected and selecting damage sensitive features. Then, the FSOM network is used to identify the health state of the plate to be inspected, and the damage index is obtained by fusing the damage sensitive features using FSOM to quantitatively evaluate the damage level of the plate to be inspected. Simulation and experimental results show this method has a good dynamic tracking capability for the fatigue damage evolution of aluminum and composite plates, and can achieve quantitative assessment of fatigue damage of plate structures.
期刊介绍:
Smart Materials and Structures (SMS) is a multi-disciplinary engineering journal that explores the creation and utilization of novel forms of transduction. It is a leading journal in the area of smart materials and structures, publishing the most important results from different regions of the world, largely from Asia, Europe and North America. The results may be as disparate as the development of new materials and active composite systems, derived using theoretical predictions to complex structural systems, which generate new capabilities by incorporating enabling new smart material transducers. The theoretical predictions are usually accompanied with experimental verification, characterizing the performance of new structures and devices. These systems are examined from the nanoscale to the macroscopic. SMS has a Board of Associate Editors who are specialists in a multitude of areas, ensuring that reviews are fast, fair and performed by experts in all sub-disciplines of smart materials, systems and structures.
A smart material is defined as any material that is capable of being controlled such that its response and properties change under a stimulus. A smart structure or system is capable of reacting to stimuli or the environment in a prescribed manner. SMS is committed to understanding, expanding and dissemination of knowledge in this subject matter.