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According to the damage condition of conveyor belt, an improved Faster R-CNN method for surface damage detection of conveyor belt is proposed. Based on the Faster R-CNN neural network, the detection method preferred MobileNet network for image lightweight feature extraction, and then introduced the background classification of the fusion of anchor original features and convolution into the RPN module to enhance the damage feature information of the conveyor belt. Finally, data sets of conveyor belt surface damage were constructed for data test, and VGG-19 and ResNet-18 backbone networks were used for test comparison, respectively. The results showed that the improved Faster R-CNN algorithm could effectively identify the damage states of conveyor belt scratches, tears and ruptures.<\/jats:p>","DOI":"10.1177\/14727978251322041","type":"journal-article","created":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T19:10:56Z","timestamp":1740683456000},"page":"438-454","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Conveyor belt damage detection based on machine learning"],"prefix":"10.66113","volume":"25","author":[{"given":"Yuan","family":"Yuan","sequence":"first","affiliation":[{"name":"Taiyuan University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongchao","family":"Li","sequence":"additional","affiliation":[{"name":"Taiyuan Heavy Industry Co., Ltd."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Gao","sequence":"additional","affiliation":[{"name":"Taiyuan University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yichao","family":"Bai","sequence":"additional","affiliation":[{"name":"Taiyuan University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miao","family":"Wang","sequence":"additional","affiliation":[{"name":"Taiyuan University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hang","family":"Wang","sequence":"additional","affiliation":[{"name":"Taiyuan University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lidong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Taiyuan University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","published-online":{"date-parts":[[2025,2,27]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12206-022-1208-1"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/app11062564"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.3390\/app10155053"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.2298\/TSCI2303099L"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2021.110177"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/pr10091679"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2023.113814"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2018.10.001"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.wear.2018.08.001"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.engfailanal.2021.105615"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.3390\/s23073652"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.3390\/s22093485"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.3390\/app132011464"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2021.110469"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2932731"}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14727978251322041","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/14727978251322041","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14727978251322041","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:06:00Z","timestamp":1776809160000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/14727978251322041"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":15,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["10.1177\/14727978251322041"],"URL":"https:\/\/doi.org\/10.1177\/14727978251322041","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]}}}