{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T22:13:09Z","timestamp":1766441589686,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:00:00Z","timestamp":1662076800000},"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":["51975494","20720180120"],"award-info":[{"award-number":["51975494","20720180120"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities","award":["51975494","20720180120"],"award-info":[{"award-number":["51975494","20720180120"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In addition to lubricating and cooling, aero-engine lubricating oil is also a transport medium for wear particles generated by mechanical wear. Online identification of the number and shape of wear particles is an important means to directly determine the wear state of rotating parts, but most of the existing research focuses on the identification and counting of wear particles. In this paper, a qualitative classification method of wear particle morphology based on support vector machine is proposed by using the wear particle capacitance signal obtained by the coaxial capacitive sensing network. Firstly, the coaxial capacitive sensing network simulation model is used to obtain the capacitance signals of different shapes of wear particles entering the detection space of different electrode plates. In addition, a variety of intelligent optimization algorithms are used to optimize the relevant parameters of the support vector machine (SVM) model in order to improve the classification accuracy. By using the processed data and optimized parameters, a SVM-based qualitative classification model for wear particles is established. Finally, the validity of the classification model is verified by real wear particles of different sizes. The simulation and experimental results show that the qualitative classification of different wear particle morphologies can be achieved by using the coaxial capacitive sensing network signal and the SVM model.<\/jats:p>","DOI":"10.3390\/s22176653","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6653","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Qualitative Classification of Lubricating Oil Wear Particle Morphology Based on Coaxial Capacitive Sensing Network and SVM"],"prefix":"10.3390","volume":"22","author":[{"given":"Ling","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Aerospace Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangwen","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Aerospace Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diheng","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Aerospace Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yishou","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Aerospace Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1189-3046","authenticated-orcid":false,"given":"Xinlin","family":"Qing","sequence":"additional","affiliation":[{"name":"School of Aerospace Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8045-4867","authenticated-orcid":false,"given":"Wendong","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Aerospace Engineering, Xiamen University, Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.ymssp.2018.08.039","article-title":"A review on lubricant condition monitoring information analysis for maintenance decision support","volume":"118","author":"Wakiru","year":"2018","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1080\/02533839.2019.1708803","article-title":"In situ collection and analysis of oil debris based on multi-physical field synthesis effect","volume":"43","author":"Gao","year":"2020","journal-title":"J. Chin. Inst. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.sna.2011.03.033","article-title":"Application of dielectric spectroscopy for engine lubricating oil degradation monitoring","volume":"168","author":"Guan","year":"2011","journal-title":"Sens. Actuators A Phys."},{"key":"ref_4","first-page":"5","article-title":"Engine Seizure Monitoring System Using Wear Debris Analysis and Particle Measurement","volume":"1","author":"Matsumoto","year":"2016","journal-title":"SAE Tech. Pap."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"203696","DOI":"10.1016\/j.wear.2021.203696","article-title":"Automated 3D ferrograph image analysis for similar particle identification with the knowledge-embedded double-CNN model","volume":"476","author":"Wang","year":"2021","journal-title":"Wear"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1761","DOI":"10.1016\/j.wear.2018.12.087","article-title":"Integrated model of BP neural network and CNN algorithm for automatic wear debris classification","volume":"426\u2013427","author":"Wang","year":"2019","journal-title":"Wear"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"203477","DOI":"10.1016\/j.wear.2020.203477","article-title":"Optimized CNN model for identifying similar 3D wear particles in few samples","volume":"460\u2013461","author":"Wang","year":"2020","journal-title":"Wear"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.wear.2019.01.060","article-title":"Wear particle classification considering particle overlapping","volume":"422\u2013423","author":"Peng","year":"2019","journal-title":"Wear"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1016\/j.triboint.2009.06.019","article-title":"Quantitative estimation of wear amounts by real time measurement of wear debris in lubricating oil","volume":"43","author":"Iwai","year":"2010","journal-title":"Tribol. Int."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.ymssp.2015.01.002","article-title":"Ultrasonic echo waveshape features extraction based on QPSO-matching pursuit for online wear debris discrimination","volume":"60\u201361","author":"Xu","year":"2015","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1080\/10739149.2015.1116007","article-title":"Determination of metal particles in oil using a microfluidic chip-based inductive sensor","volume":"44","author":"Wu","year":"2016","journal-title":"Instrum. Sci. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"095101","DOI":"10.1088\/0957-0233\/26\/9\/095101","article-title":"A new debris sensor based on dual excitation sources for online debris monitoring","volume":"26","author":"Hong","year":"2015","journal-title":"Meas. Sci. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1109\/AERO.2000.877883","article-title":"Use of electrostatic technology for aero engine oil system monitoring","volume":"Volume 6","author":"Powrie","year":"2000","journal-title":"Proceedings of the 2000 IEEE Aerospace Conference"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"075106","DOI":"10.1088\/0957-0233\/24\/7\/075106","article-title":"Improving sensitivity of an inductive pulse sensor for detection of metallic wear debris in lubricants using parallel LC resonance method","volume":"24","author":"Du","year":"2013","journal-title":"Meas. Sci. Technol."},{"key":"ref_15","first-page":"1","article-title":"On-line wear debris detection in lubricating oil for condition based health monitoring of rotary machinery","volume":"4","author":"Du","year":"2011","journal-title":"Recent Adv. Electr. Electron. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Han, Z., Wang, Y., and Qing, X. (2017). Characteristics Study of In-Situ Capacitive Sensor for Monitoring Lubrication Oil Debris. Sensors, 17.","DOI":"10.3390\/s17122851"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1310","DOI":"10.1108\/ILT-09-2017-0256","article-title":"In-situ capacitive sensor for monitoring debris of lubricant oil","volume":"70","author":"Wang","year":"2018","journal-title":"Ind. Lubr. Tribol."},{"key":"ref_18","unstructured":"Bowen, E.R., and Westcott, V.C. (1976). Wear Particle Atlas, Maritime Technical Information Facility."},{"key":"ref_19","unstructured":"Anderson, D.P. (1982). Wear Particle Atlas. (Revised), Foxboro Analytical."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wang, Y., Lin, T., Wu, D., Zhu, L., Qing, X., and Xue, W. (2022). A New In Situ Coaxial Capacitive Sensor Network for Debris Monitoring of Lubricating Oil. Sensors, 22.","DOI":"10.3390\/s22051777"},{"key":"ref_21","first-page":"1","article-title":"Robust visual tracking for UAVs with dynamic feature weight selection","volume":"52","author":"An","year":"2022","journal-title":"Appl. Intell."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2781","DOI":"10.1109\/JSTARS.2021.3059451","article-title":"A hyperspectral image classification method using multifeature vectors and optimized KELM","volume":"14","author":"Chen","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1109\/TSMC.1985.6313426","article-title":"A fuzzy k-nearest neighbor algorithm","volume":"4","author":"Keller","year":"1985","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/0169-7439(87)80084-9","article-title":"Principal component analysis","volume":"2","author":"Wold","year":"1987","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_25","first-page":"100","article-title":"Algorithm AS 136: A k-means clustering algorithm","volume":"28","author":"Hartigan","year":"1979","journal-title":"J. R. Stat. Soc. Ser. C"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ranjan, G.S.K., Verma, A.K., and Radhika, S. (2019, January 29\u201331). K-nearest neighbors and grid search cv based real time fault monitoring system for industries. Proceedings of the 2019 IEEE 5th International Conference for Convergence in Technology (I2CT), Pune, India.","DOI":"10.1109\/I2CT45611.2019.9033691"},{"key":"ref_27","unstructured":"Eberhart, R., and Kennedy, J. (1995, January 4\u20136). A new optimizer using particle swarm theory. Proceedings of the MHS\u201995 Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"105139","DOI":"10.1016\/j.engappai.2022.105139","article-title":"Parameter adaptation-based ant colony optimization with dynamic hybrid mechanism","volume":"114","author":"Zhou","year":"2022","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wu, D., and Wu, C. (2022). Research on the Time-Dependent Split Delivery Green Vehicle Routing Problem for Fresh Agricultural Products with Multiple Time Windows. Agriculture, 12.","DOI":"10.3390\/agriculture12060793"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Holland, J.H. (1992). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, MIT Press.","DOI":"10.7551\/mitpress\/1090.001.0001"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/17\/6653\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:22:35Z","timestamp":1760142155000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/17\/6653"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,2]]},"references-count":30,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["s22176653"],"URL":"https:\/\/doi.org\/10.3390\/s22176653","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,9,2]]}}}