{"title":"考虑单个任务载荷严重程度,提高损伤诊断可靠性","authors":"Qiuhui Xu , Yixing Meng , Shenfang Yuan, Jian Chen","doi":"10.1016/j.ijmecsci.2025.110836","DOIUrl":null,"url":null,"abstract":"<div><div>Among different Structural Health Monitoring (SHM) targets, damage diagnosis is always one of the most important as timely diagnosis of structural damage with high reliability can greatly facilitate the implementation of efficient maintenance and accurate structural life prediction. However, both the damage propagation process and the SHM method are always affected by complex uncertainties in service loads. To address this issue, a novel method for enhancing the reliability of damage diagnosis in individual aircraft structures is proposed in this paper, by accounting for both mission load severity and monitored damage features. Unlike conventionally employed load compensation techniques, it is proposed to extract the monitored flight mission load spectrum information, including the load spectrum amplitude and load spectrum mean feature, together with the damage index to form a new kind of multidimensional feature, taking advantage of hybrid Fiber Bragg Grating (FBG)-based load monitoring and Guided Wave (GW)-based damage monitoring. Besides, a Hybrid Monitoring-based Gaussian Process (HMGP) probabilistic model is established with the multidimensional feature to quantify the damage. Validation fatigue test is designed by using different complex variable load spectra. The results demonstrate a 36 % improvement in the Probability of Detection (POD) and a 44 % increase in crack sizing reliability, representing a significant enhancement in diagnostic reliability.</div></div>","PeriodicalId":56287,"journal":{"name":"International Journal of Mechanical Sciences","volume":"306 ","pages":"Article 110836"},"PeriodicalIF":9.4000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing damage diagnosis reliability by considering individual mission load severity\",\"authors\":\"Qiuhui Xu , Yixing Meng , Shenfang Yuan, Jian Chen\",\"doi\":\"10.1016/j.ijmecsci.2025.110836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Among different Structural Health Monitoring (SHM) targets, damage diagnosis is always one of the most important as timely diagnosis of structural damage with high reliability can greatly facilitate the implementation of efficient maintenance and accurate structural life prediction. However, both the damage propagation process and the SHM method are always affected by complex uncertainties in service loads. To address this issue, a novel method for enhancing the reliability of damage diagnosis in individual aircraft structures is proposed in this paper, by accounting for both mission load severity and monitored damage features. Unlike conventionally employed load compensation techniques, it is proposed to extract the monitored flight mission load spectrum information, including the load spectrum amplitude and load spectrum mean feature, together with the damage index to form a new kind of multidimensional feature, taking advantage of hybrid Fiber Bragg Grating (FBG)-based load monitoring and Guided Wave (GW)-based damage monitoring. Besides, a Hybrid Monitoring-based Gaussian Process (HMGP) probabilistic model is established with the multidimensional feature to quantify the damage. Validation fatigue test is designed by using different complex variable load spectra. The results demonstrate a 36 % improvement in the Probability of Detection (POD) and a 44 % increase in crack sizing reliability, representing a significant enhancement in diagnostic reliability.</div></div>\",\"PeriodicalId\":56287,\"journal\":{\"name\":\"International Journal of Mechanical Sciences\",\"volume\":\"306 \",\"pages\":\"Article 110836\"},\"PeriodicalIF\":9.4000,\"publicationDate\":\"2025-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mechanical Sciences\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S002074032500918X\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mechanical Sciences","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S002074032500918X","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Enhancing damage diagnosis reliability by considering individual mission load severity
Among different Structural Health Monitoring (SHM) targets, damage diagnosis is always one of the most important as timely diagnosis of structural damage with high reliability can greatly facilitate the implementation of efficient maintenance and accurate structural life prediction. However, both the damage propagation process and the SHM method are always affected by complex uncertainties in service loads. To address this issue, a novel method for enhancing the reliability of damage diagnosis in individual aircraft structures is proposed in this paper, by accounting for both mission load severity and monitored damage features. Unlike conventionally employed load compensation techniques, it is proposed to extract the monitored flight mission load spectrum information, including the load spectrum amplitude and load spectrum mean feature, together with the damage index to form a new kind of multidimensional feature, taking advantage of hybrid Fiber Bragg Grating (FBG)-based load monitoring and Guided Wave (GW)-based damage monitoring. Besides, a Hybrid Monitoring-based Gaussian Process (HMGP) probabilistic model is established with the multidimensional feature to quantify the damage. Validation fatigue test is designed by using different complex variable load spectra. The results demonstrate a 36 % improvement in the Probability of Detection (POD) and a 44 % increase in crack sizing reliability, representing a significant enhancement in diagnostic reliability.
期刊介绍:
The International Journal of Mechanical Sciences (IJMS) serves as a global platform for the publication and dissemination of original research that contributes to a deeper scientific understanding of the fundamental disciplines within mechanical, civil, and material engineering.
The primary focus of IJMS is to showcase innovative and ground-breaking work that utilizes analytical and computational modeling techniques, such as Finite Element Method (FEM), Boundary Element Method (BEM), and mesh-free methods, among others. These modeling methods are applied to diverse fields including rigid-body mechanics (e.g., dynamics, vibration, stability), structural mechanics, metal forming, advanced materials (e.g., metals, composites, cellular, smart) behavior and applications, impact mechanics, strain localization, and other nonlinear effects (e.g., large deflections, plasticity, fracture).
Additionally, IJMS covers the realms of fluid mechanics (both external and internal flows), tribology, thermodynamics, and materials processing. These subjects collectively form the core of the journal's content.
In summary, IJMS provides a prestigious platform for researchers to present their original contributions, shedding light on analytical and computational modeling methods in various areas of mechanical engineering, as well as exploring the behavior and application of advanced materials, fluid mechanics, thermodynamics, and materials processing.