{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T21:06:38Z","timestamp":1761599198529,"version":"3.40.5"},"reference-count":28,"publisher":"World Scientific Pub Co Pte Ltd","issue":"14","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2020,12,30]]},"abstract":"<jats:p> With the development of information theory and image analysis theory, the studies on fault diagnosis methods based on image processing have become a hot spot in the recent years in the field of fault diagnosis. The gearbox of wind turbine generator is a fault-prone subassembly. Its time frequency of vibration signals contains abundant status information, so this paper proposes a fault diagnosis method based on time-frequency image characteristic extraction and artificial immune algorithm. Firstly, obtain the time-frequency image using wavelet transform based on threshold denoising. Secondly, acquire time-frequency image characteristics by means of Hu invariant moment and correlation fusion gray-level co-occurrence matrix of characteristic value, thus, to extract the fault information of the gearing of wind turbine generator. Lastly, diagnose the fault type using the improved actual-value negative selection algorithm. The application of this method in the gear fault diagnosis on the test bed of wind turbine step-up gearbox proves that it is effective in the improvement of diagnosis accuracy. <\/jats:p>","DOI":"10.1142\/s0218001420540348","type":"journal-article","created":{"date-parts":[[2020,2,21]],"date-time":"2020-02-21T08:21:22Z","timestamp":1582273282000},"page":"2054034","source":"Crossref","is-referenced-by-count":9,"title":["Fault Diagnosis Method for Wind Turbine Gearbox Based on Image Characteristics Extraction and Actual Value Negative Selection Algorithm"],"prefix":"10.1142","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7503-1237","authenticated-orcid":false,"given":"Xiaoli","family":"Xu","sequence":"first","affiliation":[{"name":"Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University, Beijing 100192, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiuli","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University, Beijing 100192, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2020,5,23]]},"reference":[{"issue":"1","key":"S0218001420540348BIB001","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.ymssp.2013.07.022","volume":"47","author":"Avendano-Valencia L. 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