{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T17:07:05Z","timestamp":1774890425207,"version":"3.50.1"},"reference-count":177,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,4,17]],"date-time":"2019-04-17T00:00:00Z","timestamp":1555459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51805434"],"award-info":[{"award-number":["51805434"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Rotating machinery is widely applied in various types of industrial applications. As a promising field for reliability of modern industrial systems, early fault diagnosis (EFD) techniques have attracted increasing attention from both academia and industry. EFD is critical to provide appropriate information for taking necessary maintenance actions and thereby prevent severe failures and reduce financial losses. A massive amounts of research work has been conducted in last two decades to develop EFD techniques. This paper reviews and summarizes the research works on EFD of gears, rotors, and bearings. The main purpose of this paper is to serve as a guidemap for researchers in the field of early fault diagnosis. After a brief introduction of early fault diagnosis techniques, the applications of EFD of rotating machine are reviewed in two aspects: fault frequency-based methods and artificial intelligence-based methods. Finally, a summary and some new research prospects are discussed.<\/jats:p>","DOI":"10.3390\/e21040409","type":"journal-article","created":{"date-parts":[[2019,4,17]],"date-time":"2019-04-17T11:07:11Z","timestamp":1555499231000},"page":"409","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":201,"title":["A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery"],"prefix":"10.3390","volume":"21","author":[{"given":"Yu","family":"Wei","sequence":"first","affiliation":[{"name":"Department of Astronautical Science and Mechanics, Harbin Institute of Technology (HIT), Harbin 150001, China"}]},{"given":"Yuqing","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Astronautical Science and Mechanics, Harbin Institute of Technology (HIT), Harbin 150001, China"}]},{"given":"Minqiang","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Astronautical Science and Mechanics, Harbin Institute of Technology (HIT), Harbin 150001, China"}]},{"given":"Wenhu","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Astronautical Science and Mechanics, Harbin Institute of Technology (HIT), Harbin 150001, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"66723","DOI":"10.1109\/ACCESS.2018.2873782","article-title":"The entropy algorithm and its variants in the fault diagnosis of rotating machinery: A review","volume":"6","author":"Li","year":"2018","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.measurement.2014.12.032","article-title":"Incipient fault information determination for rolling element bearing based on synchronous averaging reassigned wavelet scalogram","volume":"65","author":"Li","year":"2015","journal-title":"Measurement"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.ymssp.2018.02.016","article-title":"Artificial intelligence for fault diagnosis of rotating machinery: A review","volume":"108","author":"Liu","year":"2018","journal-title":"Mech. 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