{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T05:19:13Z","timestamp":1781932753090,"version":"3.54.5"},"reference-count":31,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11202137"],"award-info":[{"award-number":["11202137"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2019025"],"award-info":[{"award-number":["2019025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["XTCX2018-11"],"award-info":[{"award-number":["XTCX2018-11"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Alliance Program","award":["11202137"],"award-info":[{"award-number":["11202137"]}]},{"name":"Shanghai Alliance Program","award":["2019025"],"award-info":[{"award-number":["2019025"]}]},{"name":"Shanghai Alliance Program","award":["XTCX2018-11"],"award-info":[{"award-number":["XTCX2018-11"]}]},{"name":"Collaborative innovation fund of Shanghai Institute of Technology","award":["11202137"],"award-info":[{"award-number":["11202137"]}]},{"name":"Collaborative innovation fund of Shanghai Institute of Technology","award":["2019025"],"award-info":[{"award-number":["2019025"]}]},{"name":"Collaborative innovation fund of Shanghai Institute of Technology","award":["XTCX2018-11"],"award-info":[{"award-number":["XTCX2018-11"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The RAPID (reconstruction algorithm for probabilistic inspection of defect) method based on Lamb wave detection is an effective method to give the position information of a defect in composite plate. In this paper, an improved RAPID imaging method based on machine learning (ML) is proposed to precisely visualize the location and features of defects in composite plate. First, the specific feature information of the defect, such as type, size and direction, can be identified by analyzing the detection signals through multiple machine learning models. Then, according to the obtained defect features, the scaling parameter \u03b2 of the RAPID method which controls the size of the elliptical area is revised, and weights are set to the important detection paths which are related to defect features to realize precise defect imaging. The simulation results show that the proposed method can intuitively characterize the location and related feature information of the defect, and effectively improve the accuracy of defect imaging.<\/jats:p>","DOI":"10.3390\/s22218413","type":"journal-article","created":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T03:44:17Z","timestamp":1667360657000},"page":"8413","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["An Improved RAPID Imaging Method of Defects in Composite Plate Based on Feature Identification by Machine Learning"],"prefix":"10.3390","volume":"22","author":[{"given":"Fei","family":"Deng","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 200235, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiran","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 200235, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 200235, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 200235, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.paerosci.2005.02.004","article-title":"Fibre reinforced composites in aircraft construction","volume":"41","author":"Soutis","year":"2005","journal-title":"Prog. Aerosp. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1436","DOI":"10.1016\/j.compscitech.2004.12.015","article-title":"Functionalized composite structures for new generation airframes: A review","volume":"65","author":"Ye","year":"2005","journal-title":"Compos. Sci. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/s42791-019-0012-2","article-title":"Damage assessment of smart composite structures via machine learning: A review","volume":"1","author":"Khan","year":"2019","journal-title":"JMST Adv."},{"key":"ref_4","first-page":"1218","article-title":"A spatial filter and two linear PZT arrays based composite structure imaging method","volume":"17","author":"Qiu","year":"2015","journal-title":"J. Vibroeng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1177\/1045389X10372003","article-title":"Damage Detection in Thin Composite Laminates Using Piezoelectric Phased Sensor Arrays and Guided Lamb Wave Interrogation","volume":"21","author":"Purekar","year":"2010","journal-title":"J. Intell. Mater. Syst. Struct."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.sna.2011.11.008","article-title":"Non-axisymmetric Lamb wave excitation by piezoelectric wafer active sensors","volume":"174","author":"Moll","year":"2012","journal-title":"Sens. Actuators A Phys."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"N73","DOI":"10.1088\/0964-1726\/13\/5\/N01","article-title":"Structural health monitoring of composite structures using Lamb wave tomography","volume":"13","author":"Prasad","year":"2004","journal-title":"Smart Mater. Struct."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.ultras.2007.07.005","article-title":"The group velocity variation of Lamb wave in fiber reinforced composite plate","volume":"47","author":"Rhee","year":"2007","journal-title":"Ultrasonics"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1088\/0964-1726\/19\/4\/045022","article-title":"Multi-site damage localization in anisotropic plate-like structures using an active guided wave structural health monitoring system","volume":"19","author":"Moll","year":"2010","journal-title":"Smart Mater. Struct."},{"key":"ref_10","first-page":"021001","article-title":"A Defects localization Algorithm Based on the Lamb Wave of Plate Structure","volume":"4","author":"Deng","year":"2021","journal-title":"J. Nondestruct. Eval. Diagn. Progn. Eng. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"108495","DOI":"10.1016\/j.measurement.2020.108495","article-title":"Evaluation of the sparse reconstruction and the delay-and-sum damage imaging methods for structural health monitoring under different environmental and operational conditions","volume":"169","author":"Nokhbatolfoghahai","year":"2021","journal-title":"Measurement"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"112420","DOI":"10.1016\/j.compstruct.2020.112420","article-title":"Using the hybrid DAS-SR method for damage localization in composite plates","volume":"247","author":"Nokhbatolfoghahai","year":"2020","journal-title":"Compos. Struct."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1088\/0964-1726\/13\/2\/020","article-title":"A synthetic time-reversal imaging method for structural health monitoring","volume":"13","author":"Wang","year":"2004","journal-title":"Smart Mater. Struct."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.1177\/1475921719830612","article-title":"Guided wave time-reversal imaging of macroscopic localized inhomogeneities in anisotropic composites","volume":"18","author":"Eremin","year":"2019","journal-title":"Struct. Health Monit."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Guo, J., Zeng, X., Liu, Q., and Qing, X. (2022). Lamb Wave-Based Damage Localization and Quantification in Composites Using Probabilistic Imaging Algorithm and Statistical Method. Sensors, 22.","DOI":"10.3390\/s22134810"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.1177\/14759217211033967","article-title":"Probability-based diagnostic imaging with corrected weight distribution for damage detection of stiffened composite panel","volume":"21","author":"Liu","year":"2022","journal-title":"Struct. Health Monit."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"e1919","DOI":"10.1002\/stc.1919","article-title":"Delamination detection in composite plates by synthesizing time-reversed Lamb waves and a modified damage imaging algorithm based on RAPID","volume":"24","author":"Liu","year":"2017","journal-title":"Struct. Control Health Monit."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"115466","DOI":"10.1016\/j.compstruct.2022.115466","article-title":"Research on composites damage identification based on power spectral density and lamb wave tomography technology in strong noise environment","volume":"289","author":"Su","year":"2022","journal-title":"Compos. Struct."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, S., Wu, W., Shen, Y., Liu, Y., and Jiang, S. (2020). Influence of the PZT sensor array configuration on Lamb wave tomography imaging with the RAPID algorithm for hole and crack detection. Sensors, 20.","DOI":"10.3390\/s20030860"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.1177\/1045389X14549873","article-title":"Validation and evaluation of damage identification using probability-based diagnostic imaging on a stiffened composite panel","volume":"26","author":"Wu","year":"2015","journal-title":"J. Intell. Mater. Syst. Struct."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Pan, H., Wang, X., and Lin, Z. (2020). Machine learning-enriched lamb wave approaches for automated damage detection. Sensors, 20.","DOI":"10.3390\/s20061790"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"136","DOI":"10.3901\/JME.2021.12.136","article-title":"Identification of corrosion damage degree of guided wave bend pipe based on neural network and support vector machine","volume":"57","author":"Zhou","year":"2021","journal-title":"J. Mech. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"125019","DOI":"10.1088\/0964-1726\/22\/12\/125019","article-title":"A novel Bayesian imaging method for probabilistic delamination detection of composite materials","volume":"22","author":"Peng","year":"2013","journal-title":"Smart Mater. Struct."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"112403","DOI":"10.1016\/j.compstruct.2020.112403","article-title":"Detection and classification of matrix cracking in laminated composites using guided wave propagation and artificial neural networks","volume":"246","author":"Mardanshahi","year":"2020","journal-title":"Compos. Struct."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Huo, H., He, J., and Guan, X. (2020). A Bayesian fusion method for composite damage identification using Lamb wave. Struct. Health Monit.","DOI":"10.1177\/1475921720945000"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"114939","DOI":"10.1016\/j.compstruct.2021.114939","article-title":"Investigation of real delamination detection in composite structure using air-coupled ultrasonic testing","volume":"280","author":"Bahonar","year":"2022","journal-title":"Compos. Struct."},{"key":"ref_28","unstructured":"Ke, G.L., Meng, Q., Finley, T., Wang, T.F., Chen, W., Ma, W.D., Ye, Q.W., and Liu, T.Y. (2017, January 4\u20139). Lightgbm: A highly efficient gradient boosting decision tree. Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1007\/s12541-012-0087-2","article-title":"A study on quantitative lamb wave tomogram via modified RAPID algorithm with shape factor optimization","volume":"13","author":"Sheen","year":"2012","journal-title":"Int. J. Precis. Eng. Manuf."},{"key":"ref_30","unstructured":"Zhou, Z.H. (2016). Machine Learning, Tsinghua University Press."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, R., Gu, H., Hu, B., and She, Z. (2019). Multi-feature fusion and damage identification of large generator stator insulation based on Lamb wave detection and SVM method. Sensors, 19.","DOI":"10.3390\/s19173733"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/21\/8413\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:09:00Z","timestamp":1760144940000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/21\/8413"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,1]]},"references-count":31,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2022,11]]}},"alternative-id":["s22218413"],"URL":"https:\/\/doi.org\/10.3390\/s22218413","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,1]]}}}