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Firstly, a dataset of blade surface defects is constructed. To solve the problem that the original faster RCNN is hard to detect tiny defects, RoI align is adopted to replace RoI pooling in the improved faster RCNN and the feature pyramid networks (FPN) combined with ResNet\u201050 are introduced for feature extraction. To address the issue of discontinuous defects on the full image, the nonmaximum suppression (NMS) algorithm is improved to ensure the continuity of defects. A four\u2010degree\u2010of\u2010freedom (4\u2010DOF) motion platform and an industrial camera are used to collect images of blade surfaces. The detection results generated by the improved faster RCNN are compared with the results of the unimproved method. The experimental results prove that the defect detection system based on the improved faster RCNN can realize automatic defect detection on the blade surface with high accuracy. It also solves the issues of tiny defect detection and discontinuous defects on the full result image of the blade.<\/jats:p>","DOI":"10.1155\/2023\/1992415","type":"journal-article","created":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T20:49:04Z","timestamp":1683751744000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Aeroengine Blade Surface Defect Detection System Based on Improved Faster RCNN"],"prefix":"10.1155","volume":"2023","author":[{"given":"Liu","family":"Yixuan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4071-3051","authenticated-orcid":false,"given":"Wu","family":"Dongbo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5359-6862","authenticated-orcid":false,"given":"Liang","family":"Jiawei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang","family":"Hui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,5,10]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2022.111569"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1115\/1.4051883"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.precisioneng.2021.08.020"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1115\/1.4044421"},{"key":"e_1_2_9_5_2","first-page":"2319","article-title":"Review of development and application of defect detection technology","volume":"46","author":"Shao-Bo L.","year":"2020","journal-title":"Acta Automatica Sinica"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rsase.2021.100522"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2022.104061"},{"key":"e_1_2_9_8_2","volume-title":"Evaluation of In-Service Non-destructive Inspection Methods for Composite Aerospace Structures","author":"Heida J. 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