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First, this article introduces the overall architecture of the intelligent operation and maintenance system for electromechanical equipment. Second, based on the electromechanical equipment operation and maintenance data access service, data cleaning, and fault prediction, this article constructs an electromechanical equipment intelligent operation and maintenance platform based on Kafka message queue, Spark cluster, and other components, and introduces the functional composition of the system in detail. Finally, the article describes the functions of each component of data access service, data cleaning, and fault prediction in detail. To address the cost issue associated with sufficient labeled sample data for data analysis, we propose a semi-supervised learning algorithm, IF-GBDT, based on improved independent forests and Gradient Boosting Decision Tree. The independent forest algorithm supplements labels for unlabeled data based on the learning results of a small number of labeled samples. We also use the gradient lifting tree algorithm to train the model based on the new tag data set for fault prediction, thereby reducing the impact of lack of tags on the accuracy of the prediction model. Experiments show that this method improves classification accuracy and has good adaptability and concurrency performance for a small number of tags.<\/jats:p>","DOI":"10.1515\/pjbr-2022-0121","type":"journal-article","created":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T06:50:44Z","timestamp":1690872644000},"source":"Crossref","is-referenced-by-count":0,"title":["Application of big data technology in electromechanical operation and maintenance intelligent platform"],"prefix":"10.1515","volume":"14","author":[{"given":"Wenjuan","family":"Yang","sequence":"first","affiliation":[{"name":"School of Information Engineering, Shanghai Zhongqiao Vocational and Technical University , Shanghai , 201514 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongbin","family":"Chan","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Zhongqiao Vocational and Technical University , Shanghai , 201514 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Zhongqiao Vocational and Technical University , Shanghai , 201514 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuli","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Zhongqiao Vocational and Technical University , Shanghai , 201514 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2023,8,1]]},"reference":[{"key":"2025073006061530599_j_pjbr-2022-0121_ref_001","doi-asserted-by":"crossref","unstructured":"M. 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