{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T02:07:19Z","timestamp":1778983639911,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T00:00:00Z","timestamp":1702512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Beijing Association of Higher Education Project","award":["MS2022314"],"award-info":[{"award-number":["MS2022314"]}]},{"name":"National Research Project on Higher Education in the Coal Industry","award":["2021MXJG44"],"award-info":[{"award-number":["2021MXJG44"]}]},{"name":"MOE Collaborative Projects between Industry and Education for Jointly Cultivating Talents","award":["202102210008"],"award-info":[{"award-number":["202102210008"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,12,14]]},"DOI":"10.1145\/3638884.3638964","type":"proceedings-article","created":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T12:11:26Z","timestamp":1713874286000},"page":"506-511","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on Wind Turbine Fault Diagnosis Technology Based on Big Data"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-1826-8015","authenticated-orcid":false,"given":"Li","family":"Yang","sequence":"first","affiliation":[{"name":"China University of Mining and Technology-Beijing, School of Artificial Intelligence, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1858-0779","authenticated-orcid":false,"given":"Wenchao","family":"Gao","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology-Beijing, School of Artificial Intelligence, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4227-0877","authenticated-orcid":false,"given":"Yi","family":"Liu","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology-Beijing, School of Artificial Intelligence, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1829-6346","authenticated-orcid":false,"given":"Mocun","family":"Zheng","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology-Beijing, School of Artificial Intelligence, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1663-8347","authenticated-orcid":false,"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology-Beijing, School of Artificial Intelligence, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9714-867X","authenticated-orcid":false,"given":"Hengyu","family":"Yang","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology-Beijing, School of Artificial Intelligence, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,4,23]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Research on Daily Maintenance and Fault Handling of Wind Turbine Units. Papermaking Equipment and Materials[J]","year":"2021","unstructured":"Chen, ChangSheng. Research on Daily Maintenance and Fault Handling of Wind Turbine Units. Papermaking Equipment and Materials[J], 2021,50(12), 34-36"},{"key":"e_1_3_2_1_2_1","unstructured":"Bagde P Vanalkar A V Ikhar S R .INNOVATIVE METHODS OF MODELING GEAR FAULTS[J].[2023-09-01]"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","unstructured":"Trifonov M Prochazka K F Saleh Kr\u00fcger.Robust Control of an Input-redundant Aircraft against Atmospheric Disturbances and Actuator Faults[J]. 2019.DOI:10.18178\/ijmerr.8.6.905-910","DOI":"10.18178\/ijmerr.8.6.905-910"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","unstructured":"Lee J Y Lee W T Ko S H et al.Fault Classification and Diagnosis of UAV motor Based on Estimated Nonlinear Parameter of Steady-State Model[J]. 2020.DOI:10.18178\/ijmerr.10.1.22-31","DOI":"10.18178\/ijmerr.10.1.22-31"},{"key":"e_1_3_2_1_5_1","volume-title":"Wind turbine blade cracking fault prediction based on RBM and SVM [J].Power system protection and control","author":"Xin Zhang","year":"2020","unstructured":"Zhang Xin, Xu Zunyi, He Huiru, Wang Fei. Wind turbine blade cracking fault prediction based on RBM and SVM [J].Power system protection and control, 2020, 13 (15) : 134-140. The DOI: 10.19783 \/ j.carol carroll nki PSPC.191093"},{"key":"e_1_3_2_1_6_1","volume-title":"Prediction of Fan Blade Cracking Based on Machine Learning [J]. Journal of measurement and testing technology","author":"Kele Cao","year":"2021","unstructured":"Cao Kele, Yan Liangwen, Huang Shan, Yu Yue, Dong Xudong. Prediction of Fan Blade Cracking Based on Machine Learning [J]. Journal of measurement and testing technology, 2021 (04) : 13 42 to 45 + 48. DOI: 10.15988 \/ j.carol carroll nki. 1004-6941.2021.4.015"},{"key":"e_1_3_2_1_7_1","unstructured":"Liu Yuchen JING Jing. A Method for Predicting Blade Cracking of GBDT Wind Turbine Based on Improved LightGBM Framework [J].Journal of applied technology 2020 20(01): 63-70"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","unstructured":"Jung\u2014Min Yang.Fault Diagnosis for Composite Asynchronous Sequential Machines with Cascade Composition[J]. EJournal Publishing 2017(6).DOI:10.18178\/ijmerr.6.6.502-505","DOI":"10.18178\/ijmerr.6.6.502-505"},{"key":"e_1_3_2_1_9_1","first-page":"1","volume":"2016","author":"Yong Zhao","unstructured":"Zhao Yong, Han Bin, Fang Gangli. A Survey of Condition Monitoring and Fault Diagnosis for Wind Power Generators[J]. Thermal Power Generation,2016,45(10):1-5.","journal-title":"Thermal Power Generation"},{"key":"e_1_3_2_1_10_1","volume-title":"Wind Turbine Blade Damage Detection Using Supervised Machine Learning Algorithms[J]. Journal of vibration and acoustics","author":"Regan T","year":"2017","unstructured":"Regan T , Beale C , Inalpolat M . Wind Turbine Blade Damage Detection Using Supervised Machine Learning Algorithms[J]. Journal of vibration and acoustics, 2017"},{"key":"e_1_3_2_1_11_1","volume-title":"Automatic Detection of Wind Turbine Blade Surface Cracks Based on UAV-Taken Images[J]","year":"2017","unstructured":"Long, Wang, Zijun, Automatic Detection of Wind Turbine Blade Surface Cracks Based on UAV-Taken Images[J]. IEEE Transactions on Industrial Electronics, 2017"},{"issue":"10","key":"e_1_3_2_1_12_1","first-page":"1","volume":"62","author":"Wei Q","year":"2015","unstructured":"Wei Q , Lu D . A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis - Part II: Signals and Signal Processing Methods[J]. IEEE Transactions on Industrial Electronics, 2015, 62(10):1-1","journal-title":"IEEE Transactions on Industrial Electronics"},{"key":"e_1_3_2_1_13_1","first-page":"1","volume-title":"IEEE Transactions on Industrial Electronics","author":"Peng Y","year":"2021","unstructured":"Peng Y , Qiao W , Qu L . Compressive Sensing-Based Missing-Data-Tolerant Fault Detection for Remote Condition Monitoring of Wind Turbines[J]. IEEE Transactions on Industrial Electronics, 2021, PP(99):1-1"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TLA.2019.8896812"},{"issue":"1","key":"e_1_3_2_1_15_1","first-page":"7","volume":"43","author":"Weigang Chen","year":"2020","unstructured":"Chen Weigang, Zhang Huilin.Application of RF-LighTGBM Algorithm in Early Warning of Fan Blade Cracking [J].Electronic Measurement Technology, 2020, 43(1):7","journal-title":"Electronic Measurement Technology"}],"event":{"name":"ICCIP 2023: 2023 the 9th International Conference on Communication and Information Processing","location":"Lingshui China","acronym":"ICCIP 2023"},"container-title":["Proceedings of the 2023 9th International Conference on Communication and Information Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3638884.3638964","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3638884.3638964","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T01:48:01Z","timestamp":1778982481000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3638884.3638964"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,14]]},"references-count":15,"alternative-id":["10.1145\/3638884.3638964","10.1145\/3638884"],"URL":"https:\/\/doi.org\/10.1145\/3638884.3638964","relation":{},"subject":[],"published":{"date-parts":[[2023,12,14]]},"assertion":[{"value":"2024-04-23","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}