{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:20:57Z","timestamp":1760239257737,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,10,22]],"date-time":"2020-10-22T00:00:00Z","timestamp":1603324800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This study extracted the featured vectors in the same way from testing data and substituted these vectors into a trained hidden Markov model to get the log likelihood probability. The log likelihood probability was matched with the time\u2013probability curve from where the gyro motor state evaluation and prediction were realized. A core component of gyroscopes is linked to the reliability of the inertia system to conduct gyro motor state evaluation and prediction. This study features the vectors\u2019 extraction from full life cycle gyro motor data and completes the training model to feature the vectors according to the time sequence and extraction to full life cycle data undergoing hidden Markov model training. This proposed model applies to full life cycle gyro motor data for validation, compared with traditional hidden Markov model predictive methods and health condition-trained data. The results suggest precise evaluation and prediction and provide an important basis for gyro motor repair and replacement strategies.<\/jats:p>","DOI":"10.3390\/sym12111750","type":"journal-article","created":{"date-parts":[[2020,10,23]],"date-time":"2020-10-23T02:01:42Z","timestamp":1603418502000},"page":"1750","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Gyro Motor State Evaluation and Prediction Using the Extended Hidden Markov Model"],"prefix":"10.3390","volume":"12","author":[{"given":"Lei","family":"Dong","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China"},{"name":"Tianjin Navigation Instrument Research Institute, Tianjin 300131, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianfei","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin Navigation Instrument Research Institute, Tianjin 300131, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2702-3590","authenticated-orcid":false,"given":"Ming-Lang","family":"Tseng","sequence":"additional","affiliation":[{"name":"Institute of Innovation and Circular Economy, Asia University, Taichung 41354, Taiwan"},{"name":"Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan"},{"name":"Faculty of Economics and Management, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyong","family":"Yang","sequence":"additional","affiliation":[{"name":"Tianjin Navigation Instrument Research Institute, Tianjin 300131, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benfu","family":"Ma","sequence":"additional","affiliation":[{"name":"Tianjin Navigation Instrument Research Institute, Tianjin 300131, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling-Ling","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.microrel.2018.01.017","article-title":"Fault diagnosis for the motor drive system of urban transit based on improved Hidden Markov Model","volume":"82","author":"Darong","year":"2018","journal-title":"Microelectron. 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