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The Mixture of Experts based meritocracy architecture selects different expert systems for various features in the dataset by categorizing the expert systems according to combinatorial principles and setting corresponding weight assignments. ConvNeXt, Bidirectional Transformer (BiTransformer), and Bidirectional Long Short-Term Memory are then employed to capture the image features and perform fault diagnosis on the composite one-dimensional mechanical wear data, respectively. An attention mechanism is added to optimize the algorithm globally, weighting the feature information across multiple dimensions to ensure the reliability and completeness of the results. The final results show that the accuracy of fault diagnosis exceeds 95%, demonstrating ideal performance.<\/jats:p>","DOI":"10.1007\/s40747-025-02061-x","type":"journal-article","created":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T06:53:14Z","timestamp":1756191194000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Enhancing multimodal fault diagnosis in mechanical systems via mixture of experts"],"prefix":"10.1007","volume":"11","author":[{"given":"Qifan","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Bosong","family":"Chai","sequence":"additional","affiliation":[]},{"given":"Chenchao","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Yingqing","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Kun","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wangyu","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Boqian","family":"Cao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3346-4640","authenticated-orcid":false,"given":"Yun","family":"Ye","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,26]]},"reference":[{"issue":"2","key":"2061_CR1","doi-asserted-by":"crossref","first-page":"13360","DOI":"10.1111\/exsy.13360","volume":"41","author":"AR Sahu","year":"2024","unstructured":"Sahu AR, Palei SK, Mishra A (2024) Data-driven fault diagnosis approaches for industrial equipment: a review. 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