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Deep learning approaches can automatically identify complex failure patterns in high-dimensional data. These methods have become a research hotspot in this field. However, in practice, the scarcity of fault data limits the models\u2019 ability to extract and distinguish failure features. To break this bottleneck, we propose a multi-auxiliary task learning framework (MATL). Specifically, we first design an adaptive multi-channel filter that adaptively decomposes raw time-domain signals into multiple frequency bands to enhance input quality. MATL strengthens its fault distinction by constructing multiple virtual binary classification auxiliary tasks (ATs). Each task focuses on specific categories. A task-level attention mechanism dynamically adjusts the contribution of each AT to the primary task. This mechanism allows the model to emphasize fault-related features and improve final diagnostic accuracy. Experimental results demonstrate that MATL achieves an average accuracy improvement of 18.61% across multiple real-world flight datasets. This outperforms existing multi-task and single-task learning approaches. The model\u2019s single-sample diagnosis time is only 0.001162 seconds, which satisfies real-time requirements for UAVs. This short diagnosis time indicates strong engineering potential.<\/jats:p>","DOI":"10.1093\/jcde\/qwaf117","type":"journal-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T13:12:04Z","timestamp":1761829924000},"page":"142-160","source":"Crossref","is-referenced-by-count":1,"title":["Fault diagnosis of UAV sensors based on multi-auxiliary task learning with few samples"],"prefix":"10.1093","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5238-1955","authenticated-orcid":false,"given":"Jie","family":"Fang","sequence":"first","affiliation":[{"name":"Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou University , Guiyang 550025 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4759-6000","authenticated-orcid":false,"given":"Shaobo","family":"Li","sequence":"additional","affiliation":[{"name":"Guizhou Institute of Technology , Guiyang 550025 ,","place":["China"]},{"name":"State Key Laboratory of Public Big Data, Guizhou University , Guiyang, Guizhou 550025 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yizong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Guizhou University , Guiyang 550025 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deyong","family":"Xiao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou University , Guiyang 550025 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingzhou","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Public Big Data, Guizhou University , Guiyang, Guizhou 550025 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinsong","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Public Big Data, Guizhou University , Guiyang, Guizhou 550025 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2025,10,31]]},"reference":[{"key":"2025120810070655100_bib1","doi-asserted-by":"publisher","first-page":"18599","DOI":"10.1038\/s41598-024-69462-9","article-title":"UAV propeller fault diagnosis using deep learning of non-traditional \u03c72-selected Taguchi method-tested Lempel\u2013Ziv complexity and Teager\u2013Kaiser energy features","volume":"14","author":"Al-Haddad","year":"2024","journal-title":"Scientific Reports"},{"key":"2025120810070655100_bib2","doi-asserted-by":"publisher","first-page":"176318","DOI":"10.17531\/ein\/176318","article-title":"Vibration signal processing for multirotor uavs fault diagnosis: Filtering or multiresolution analysis?","volume-title":"Eksploat. 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