{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T13:27:23Z","timestamp":1769693243830,"version":"3.49.0"},"reference-count":37,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T00:00:00Z","timestamp":1624579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["No.2018YFB1201500"],"award-info":[{"award-number":["No.2018YFB1201500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Science Foundation of China","award":["No. 61873201, No.U2034209, and No.U1934222"],"award-info":[{"award-number":["No. 61873201, No.U2034209, and No.U1934222"]}]},{"name":"Natural Science Foundation of Shaanxi Province of China","award":["2021JC-42"],"award-info":[{"award-number":["2021JC-42"]}]},{"DOI":"10.13039\/501100010228","name":"Natural Science Foundation of Shaanxi Provincial Department of Education","doi-asserted-by":"publisher","award":["19JS051"],"award-info":[{"award-number":["19JS051"]}],"id":[{"id":"10.13039\/501100010228","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Laboratory of Complex System Intelligent Control and Decision","award":["Beijing Institute of Technology"],"award-info":[{"award-number":["Beijing Institute of Technology"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, a fault diagnosis method is proposed based on multi-sensor fusion information for a single fault and composite fault of train braking systems. Firstly, the single mass model of the train brake is established based on operating environment. Then, the pre-allocation and linear-weighted summation criterion are proposed to fuse the monitoring data. Finally, based on the improved expectation maximization, the braking modes and braking parameters are identified, and the braking faults are diagnosed in real time. The simulation results show that the braking parameters of systems can be effectively identified, and the braking faults can be diagnosed accurately based on the identification results. Even if the monitoring data are missing or abnormal, compared with the maximum fusion, the accuracies of parameter identifications and fault diagnoses can still meet the needs of the actual systems, and the effectiveness and robustness of the method can be verified.<\/jats:p>","DOI":"10.3390\/s21134370","type":"journal-article","created":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T11:07:40Z","timestamp":1624619260000},"page":"4370","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Fault Diagnosis of Brake Train Based on Multi-Sensor Data Fusion"],"prefix":"10.3390","volume":"21","author":[{"given":"Yongze","family":"Jin","sequence":"first","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Guo","family":"Xie","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Yankai","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Xiaohui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Ning","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Anqi","family":"Shangguan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Wenbin","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"104215","DOI":"10.1016\/j.jweia.2020.104215","article-title":"Aerodynamic drag optimization of a high-speed train","volume":"204","year":"2020","journal-title":"J. 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