{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:03:21Z","timestamp":1760231001981,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T00:00:00Z","timestamp":1661299200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LQY19E050001"],"award-info":[{"award-number":["LQY19E050001"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accurately detecting the tooth profile parameters of the synchronous belt is crucial for the transmission\u2019s load distribution and service life. However, the existing detection methods have low efficiency, are greatly affected by the manual experience, and cannot realize automatic detection. A measurement method based on point cloud data is proposed to solve this issue. The surface space points of the synchronous belt are acquired by a line-structured light sensor, and the raw point clouds are preprocessed to remove outliers and reduce the number of points. Then, the point clouds are divided into plane and arc regions, and different methods are used for fitting. Finally, the parameters of each tooth are calculated. The experimental results show that the method has high measurement accuracy and reliable stability and can replace the original detection method to realize automatic detection.<\/jats:p>","DOI":"10.3390\/s22176372","type":"journal-article","created":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T23:48:58Z","timestamp":1661384938000},"page":"6372","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Research on Measurement of Tooth Profile Parameters of Synchronous Belt Based on Point Cloud Data"],"prefix":"10.3390","volume":"22","author":[{"given":"Zijian","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou 310012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mao","family":"Pang","sequence":"additional","affiliation":[{"name":"School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou 310012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuanchao","family":"Teng","sequence":"additional","affiliation":[{"name":"School of Mechanical and Energy Engineering, Zhejiang University of Science and Technology, Hangzhou 310012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"106520","DOI":"10.1016\/j.engfailanal.2022.106520","article-title":"Types and causes of damage to the conveyor belt-review, classification and mutual relations","volume":"140","author":"Bortnowski","year":"2022","journal-title":"Eng. Ail. Anal."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1972","DOI":"10.1166\/jno.2021.3161","article-title":"Fault Diagnosis of Synchronous Belt of Machine Tool Based on Improved Back Propagation Neural Network","volume":"16","author":"Shi","year":"2021","journal-title":"J. Nanoelectron. Optoelectron."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.engfailanal.2014.01.022","article-title":"Failure analysis of irreversible changes in the construction of rubber\u2013textile conveyor belt damaged by sharp-edge material impact","volume":"39","author":"Fedorko","year":"2014","journal-title":"Eng. Ail. Anal."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.cirpj.2022.03.013","article-title":"Health monitoring of a conveyor belt system using machine vision and real-time sensor data","volume":"38","author":"Chamorro","year":"2022","journal-title":"CIRP J. Manuf. Sci. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2239","DOI":"10.1016\/j.jsv.2012.11.030","article-title":"Decomposition of noise sources of synchronous belt drives","volume":"332","author":"Chen","year":"2013","journal-title":"J. Sound. Vib."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"083301","DOI":"10.1115\/1.4030204","article-title":"Influence of installation tension on transmission error due to resonance in a synchronous belt","volume":"137","author":"Kagotani","year":"2015","journal-title":"J. Mech. Design."},{"key":"ref_7","first-page":"1004","article-title":"Simulation Analysis Method of Synchronous Belt Transmission Noise Prediction","volume":"15","author":"Shi","year":"2020","journal-title":"J. Nanoelectron. Optoelectron."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1007\/s00170-010-2841-x","article-title":"Automated detection of surface defects on power transmission belts","volume":"53","author":"Perdan","year":"2011","journal-title":"Int. J. Adv. Manuf. Tech."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kim, S.H., and Hwang, Y. (2021). A survey on deep learning based methods and datasets for monocular 3D object detection. Electronics, 10.","DOI":"10.3390\/electronics10040517"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"100545","DOI":"10.1016\/j.rineng.2022.100545","article-title":"3D point cloud recognition of substation equipment based on plane detection","volume":"15","author":"Yuan","year":"2022","journal-title":"Results Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"100157","DOI":"10.1016\/j.rineng.2020.100157","article-title":"Development of manufacturing support system for ship curved shell plate using laser scanner","volume":"7","author":"Mitsuyuki","year":"2020","journal-title":"Results Eng."},{"key":"ref_12","first-page":"458","article-title":"A Self-projected Structured Light System for Fast Three-dimensional Shape Inspection","volume":"30","author":"Gao","year":"2015","journal-title":"Int. J. Robot. Autom."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.optlaseng.2014.05.004","article-title":"A novel orientation and position measuring system for large & medium scale precision assembly","volume":"62","author":"Li","year":"2014","journal-title":"Opt. Laser. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1177\/0018720815602389","article-title":"Visual inspection reliability for precision manufactured parts","volume":"57","author":"See","year":"2015","journal-title":"Hum. Factors"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Li, C., Gao, F., Han, X., and Zhang, B. (2021). A New Density-Based Clustering Method Considering Spatial Distribution of Lidar Point Cloud for Object Detection of Autonomous Driving. Electronics, 10.","DOI":"10.3390\/electronics10162005"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"107166","DOI":"10.1016\/j.compag.2022.107166","article-title":"3D point cloud density-based segmentation for vine rows detection and localisation","volume":"199","author":"Biglia","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Sun, Y., Luo, Y., Chai, X., Zhang, P., Zhang, Q., Xu, L., and Wei, L. (2021). Double-threshold segmentation of panicle and clustering adaptive density estimation for mature rice plants based on 3D point cloud. Electronics, 10.","DOI":"10.3390\/electronics10070872"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"102228","DOI":"10.1016\/j.media.2021.102228","article-title":"Shape registration with learned deformations for 3D shape reconstruction from sparse and incomplete point clouds","volume":"74","author":"Chen","year":"2021","journal-title":"Med. Image. Anal."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Yang, Y., Li, M., and Ma, X. (2020). An Advanced Vehicle Body Part Inspection Scheme Based on Scattered Point Cloud Data. Appl. Sci., 10.","DOI":"10.3390\/app10155379"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Wang, S., Mei, X., Yin, W., Lin, C., Hu, Q., and Mao, Q. (2017). Railway tunnel clearance inspection method based on 3D point cloud from mobile laser scanning. Sensors, 17.","DOI":"10.3390\/s17092055"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.precisioneng.2019.10.013","article-title":"3D measurement of gears based on a line structured light sensor","volume":"61","author":"Guo","year":"2020","journal-title":"Precis. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"109169","DOI":"10.1016\/j.measurement.2021.109169","article-title":"Aircraft skin gap and flush measurement based on seam region extraction from 3D point cloud","volume":"176","author":"Long","year":"2021","journal-title":"Measurement"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"107023","DOI":"10.1016\/j.measurement.2019.107023","article-title":"An approach for extracting curve profiles based on scanned point cloud","volume":"149","author":"Fan","year":"2020","journal-title":"Measurement"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Xu, S., Cheng, G., Pang, Y., Jin, Z., and Kang, B. (2021). Identifying and Characterizing Conveyor Belt Longitudinal Rip by 3D Point Cloud Processing. Sensors, 21.","DOI":"10.3390\/s21196650"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"119919","DOI":"10.1016\/j.conbuildmat.2020.119919","article-title":"Development and application of a non-destructive pavement testing system based on linear structured light three-dimensional measurement","volume":"260","author":"Liang","year":"2020","journal-title":"Constr. Build. Mater."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1016\/j.autcon.2018.09.019","article-title":"Automatic pavement defect detection using 3D laser profiling technology","volume":"96","author":"Zhang","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"110723","DOI":"10.1109\/ACCESS.2021.3097185","article-title":"Overall Filtering Algorithm for Multiscale Noise Removal from Point Cloud Data","volume":"9","author":"Ren","year":"2021","journal-title":"IEEE Access."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1016\/j.robot.2008.08.005","article-title":"Towards 3D point cloud based object maps for household environments","volume":"56","author":"Rusu","year":"2008","journal-title":"Robot. Auton. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"115009","DOI":"10.1088\/1361-6501\/ac10a0","article-title":"Low-speed bearing fault diagnosis based on improved statistical filtering and convolutional neural network","volume":"32","author":"Shuuji","year":"2021","journal-title":"Meas. Sci. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"111173","DOI":"10.1016\/j.measurement.2022.111173","article-title":"A New Point Cloud Simplification Method with Feature and Integrity Preservation by Partition Strategy","volume":"197","author":"Wang","year":"2022","journal-title":"Measurement"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"9450","DOI":"10.1038\/s41598-022-13550-1","article-title":"Feature-preserving simplification framework for 3D point cloud","volume":"12","author":"Xu","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"7241","DOI":"10.1109\/TIP.2021.3104174","article-title":"Approximate intrinsic voxel structure for point cloud simplification","volume":"30","author":"Lv","year":"2021","journal-title":"IEEE. Trans. Image Process."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Xu, G., Pang, Y., Bai, Z., Wang, Y., and Lu, Z. (2021). A fast point clouds registration algorithm for laser scanners. Appl. Sci., 11.","DOI":"10.3390\/app11083426"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1049\/iet-cvi.2010.0223","article-title":"Distributed RANSAC for the robust estimation of three-dimensional reconstruction","volume":"6","author":"Xu","year":"2012","journal-title":"IET Comput. Vis."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2157","DOI":"10.1016\/j.ijleo.2015.05.092","article-title":"Point cloud simplification with preserved edge based on normal vector","volume":"126","author":"Han","year":"2015","journal-title":"Optik"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.measurement.2018.10.013","article-title":"Point cloud filtering on UAV based point cloud","volume":"133","author":"Zeybek","year":"2019","journal-title":"Measurement"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"166936","DOI":"10.1016\/j.ijleo.2021.166936","article-title":"A novel probability iterative closest point with normal vector algorithm for robust rail profile registration","volume":"243","author":"Gao","year":"2021","journal-title":"Optik"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Chen, W., Li, X., Ge, H., Wang, L., and Zhang, Y. (2020). Trajectory planning for spray painting robot based on point cloud slicing technique. Electronics, 9.","DOI":"10.3390\/electronics9060908"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.patcog.2018.04.010","article-title":"Robust statistical approaches for circle fitting in laser scanning three-dimensional point cloud data","volume":"81","author":"Nurunnabi","year":"2018","journal-title":"Pattern. Recogn."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/17\/6372\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:14:41Z","timestamp":1760141681000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/17\/6372"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,24]]},"references-count":39,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["s22176372"],"URL":"https:\/\/doi.org\/10.3390\/s22176372","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,8,24]]}}}