{"title":"基于转向架响应测量的重载铁路桥梁三级损伤诊断方法","authors":"Jiaqi Shi, Hongmei Shi, Jianbo Li","doi":"10.1109/PHM58589.2023.00042","DOIUrl":null,"url":null,"abstract":"Considering an operational scenario that a freight train composed of four wagons runs over a three-span heavy haul railway bridge, the feasibility of detecting bridge damage from bogie responses is investigated and a three-stage indirect damage diagnosis method is put forward. In the data preparation stage, the time-domain subtraction method (TSM) and the Empirical Mode Decomposition (EMD) algorithm are applied to suppress the adverse effect of track irregularity and the vibration coupling effect among spans on the bogie accelerations, respectively. In the damage detection stage, a damage indicator based on the Mahalanobis distance is used to describe the dissimilarity between the train crossings in baseline status and damage status, so as to detect the occurrence of damage. In the damage localization stage, the moving window strategy is exploited to complement preliminary diagnosis with locational information. In order to appraise the efficiency of the proposed method, a blind test is carried out using the supplied data measurements without awareness of the relevant damage information. Regardless of damage location and severity, the results indicate that the proposed method simultaneously has high efficiency and superiority for damage detection and localization.","PeriodicalId":196601,"journal":{"name":"2023 Prognostics and Health Management Conference (PHM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A three-stage damage diagnosis method for heavy haul railway bridge by bogie response measurements\",\"authors\":\"Jiaqi Shi, Hongmei Shi, Jianbo Li\",\"doi\":\"10.1109/PHM58589.2023.00042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Considering an operational scenario that a freight train composed of four wagons runs over a three-span heavy haul railway bridge, the feasibility of detecting bridge damage from bogie responses is investigated and a three-stage indirect damage diagnosis method is put forward. In the data preparation stage, the time-domain subtraction method (TSM) and the Empirical Mode Decomposition (EMD) algorithm are applied to suppress the adverse effect of track irregularity and the vibration coupling effect among spans on the bogie accelerations, respectively. In the damage detection stage, a damage indicator based on the Mahalanobis distance is used to describe the dissimilarity between the train crossings in baseline status and damage status, so as to detect the occurrence of damage. In the damage localization stage, the moving window strategy is exploited to complement preliminary diagnosis with locational information. In order to appraise the efficiency of the proposed method, a blind test is carried out using the supplied data measurements without awareness of the relevant damage information. Regardless of damage location and severity, the results indicate that the proposed method simultaneously has high efficiency and superiority for damage detection and localization.\",\"PeriodicalId\":196601,\"journal\":{\"name\":\"2023 Prognostics and Health Management Conference (PHM)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Prognostics and Health Management Conference (PHM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PHM58589.2023.00042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Prognostics and Health Management Conference (PHM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHM58589.2023.00042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A three-stage damage diagnosis method for heavy haul railway bridge by bogie response measurements
Considering an operational scenario that a freight train composed of four wagons runs over a three-span heavy haul railway bridge, the feasibility of detecting bridge damage from bogie responses is investigated and a three-stage indirect damage diagnosis method is put forward. In the data preparation stage, the time-domain subtraction method (TSM) and the Empirical Mode Decomposition (EMD) algorithm are applied to suppress the adverse effect of track irregularity and the vibration coupling effect among spans on the bogie accelerations, respectively. In the damage detection stage, a damage indicator based on the Mahalanobis distance is used to describe the dissimilarity between the train crossings in baseline status and damage status, so as to detect the occurrence of damage. In the damage localization stage, the moving window strategy is exploited to complement preliminary diagnosis with locational information. In order to appraise the efficiency of the proposed method, a blind test is carried out using the supplied data measurements without awareness of the relevant damage information. Regardless of damage location and severity, the results indicate that the proposed method simultaneously has high efficiency and superiority for damage detection and localization.