{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:09:47Z","timestamp":1774364987997,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T00:00:00Z","timestamp":1669334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China National Railway Group Limited","award":["P2021J036"],"award-info":[{"award-number":["P2021J036"]}]},{"name":"China National Railway Group Limited","award":["2020QNRC001"],"award-info":[{"award-number":["2020QNRC001"]}]},{"name":"China National Railway Group Limited","award":["2021JJ40765"],"award-info":[{"award-number":["2021JJ40765"]}]},{"name":"CAST","award":["P2021J036"],"award-info":[{"award-number":["P2021J036"]}]},{"name":"CAST","award":["2020QNRC001"],"award-info":[{"award-number":["2020QNRC001"]}]},{"name":"CAST","award":["2021JJ40765"],"award-info":[{"award-number":["2021JJ40765"]}]},{"name":"Natural Science Foundation of Hunan Province, China","award":["P2021J036"],"award-info":[{"award-number":["P2021J036"]}]},{"name":"Natural Science Foundation of Hunan Province, China","award":["2020QNRC001"],"award-info":[{"award-number":["2020QNRC001"]}]},{"name":"Natural Science Foundation of Hunan Province, China","award":["2021JJ40765"],"award-info":[{"award-number":["2021JJ40765"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Convenient and fast fault diagnosis is the key to improving the service safety and maintenance efficiency of gearboxes. However, the environment and working conditions under complex service conditions are variable, and there is a lack of fault samples in engineering applications. These factors lead to difficulties in intelligent diagnosis methods based on machine learning, while traditional mechanism-based fault diagnosis requires high expertise and long time periods for the manual analysis of data. For the requirements of diagnostic convenience, an automatic fault diagnosis method for gearboxes is proposed in this paper. The method achieves accurate acquisition of rotational speed by constructing a rotational frequency search algorithm. The self-referencing characteristic frequency identification method is proposed to avoid manual signal analysis. On this basis, a framework of anti-interference automatic diagnosis is constructed to realize automatic diagnosis of gear faults. Finally, a gear fault experiment is carried out based on a high-fidelity experimental bench of bogie to verify the effectiveness of the proposed method. The proposed automatic diagnosis method does not rely on a large number of fault samples and avoids the need for diagnosis through professional knowledge, thus saving time for data analysis and promoting the application of fault diagnosis methods.<\/jats:p>","DOI":"10.3390\/s22239150","type":"journal-article","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T04:05:39Z","timestamp":1669349139000},"page":"9150","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Mechanism-Based Automatic Fault Diagnosis Method for Gearboxes"],"prefix":"10.3390","volume":"22","author":[{"given":"Lei","family":"Xu","sequence":"first","affiliation":[{"name":"School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0137-7881","authenticated-orcid":false,"given":"Tiantian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China"},{"name":"School of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7280-3556","authenticated-orcid":false,"given":"Jingsong","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China"}]},{"given":"Jinsong","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China"}]},{"given":"Guangjun","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"106587","DOI":"10.1016\/j.ymssp.2019.106587","article-title":"Applications of Machine Learning to Machine Fault Diagnosis: A Review and Roadmap","volume":"138","author":"Lei","year":"2020","journal-title":"Mech. 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