{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T05:54:42Z","timestamp":1772690082570,"version":"3.50.1"},"reference-count":22,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T00:00:00Z","timestamp":1603238400000},"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":["51675019, 51575019"],"award-info":[{"award-number":["51675019, 51575019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>An inductive debris sensor can monitor a mechanical system\u2019s debris in real time. The measuring accuracy is significantly affected by the signal aliasing issue happening in the monitoring process. In this study, a mathematical model was built to explain two debris particles\u2019 aliasing behavior. Then, a cross-correlation-based method was proposed to deal with this aliasing. Afterwards, taking advantage of the processed signal along with the original signal, an optimization strategy was proposed to make the evaluation of the aliasing debris more accurate than that merely using initial signals. Compared to other methods, the proposed method has fewer limitations in practical applications. The simulation and experimental results also verified the advantage of the proposed method.<\/jats:p>","DOI":"10.3390\/s20205949","type":"journal-article","created":{"date-parts":[[2020,10,22]],"date-time":"2020-10-22T20:51:00Z","timestamp":1603399860000},"page":"5949","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Cross-Correlation Algorithm-Based Optimization of Aliasing Signals for Inductive Debris Sensors"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0506-1833","authenticated-orcid":false,"given":"Xingjian","family":"Wang","sequence":"first","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China"},{"name":"Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beihang University, Beijing 100191, China"},{"name":"Ningbo Institute of Technology, Beihang University, Ningbo 315800, China"},{"name":"Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3515-0629","authenticated-orcid":false,"given":"Hanyu","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China"},{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaoping","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China"},{"name":"Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beihang University, Beijing 100191, China"},{"name":"Ningbo Institute of Technology, Beihang University, Ningbo 315800, China"},{"name":"Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhao","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.3390\/e12051021","article-title":"On the Thermodynamics of Friction and Wear\u2014A Review","volume":"12","author":"Amiri","year":"2010","journal-title":"Entropy"},{"key":"ref_2","first-page":"404","article-title":"Full-life dynamic identification of wear state based on on-line wear debris image features","volume":"42","author":"Wu","year":"2014","journal-title":"Meas. Sci. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1016\/j.cja.2015.12.020","article-title":"Remaining useful life prediction based on the Wiener process for an aviation axial piston pump","volume":"29","author":"Wang","year":"2016","journal-title":"Chin. J. Aeronaut."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1243\/1350650001543025","article-title":"Wear debris and associated wear phenomena-fundamental research and practice","volume":"214","author":"Williams","year":"2000","journal-title":"Proc. Inst. Mech. Eng. Part J J. Eng. Tribol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/0043-1648(72)90247-5","article-title":"A method for the study of wear particles in lubricating oil","volume":"21","author":"Seifert","year":"1972","journal-title":"Wear"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1016\/j.triboint.2017.01.015","article-title":"Lubricating oil conditioning sensors for online machine health monitoring\u2014A review","volume":"109","author":"Zhu","year":"2017","journal-title":"Tribol. Int."},{"key":"ref_7","unstructured":"Edmonds, J., Resner, M.S., and Shkarlet, K. (2000, January 25\u201325). Detection of precursor wear debris in lubrication systems. Proceedings of the 2000 IEEE Aerospace Proceedings, Big Sky, MT, USA."},{"key":"ref_8","unstructured":"Tucker, J.E., Reintjes, J., Galie, T.R., Schultz, A., Lu, C., Tankersley, L.L., Sebok, T., Holloway, C., and Howard, P.L. (2000, January 1\u20134). Lasernet fines optical wear debris monitor: A Navy shipboard evaluation of CBM enabling technology. Proceedings of the 54th Meeting of the Society for Machinery Failure Prevention Technology, Virginia Beach, VA, USA."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/0043-1648(88)90146-9","article-title":"Real time simultaneous in-line wear and lubricant condition monitoring","volume":"123","author":"Centers","year":"1998","journal-title":"Wear"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1109\/TR.2016.2628412","article-title":"A Novel Indicator for Mechanical Failure and Life Prediction Based on Debris Monitoring","volume":"66","author":"Hong","year":"2017","journal-title":"IEEE Trans. Reliab."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1108\/ILT-05-2016-0106","article-title":"Online condition monitoring of misaligned meshing gears using wear debris and oil quality sensors","volume":"70","author":"Kumar","year":"2018","journal-title":"Ind. Lubr. Tribol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"53","DOI":"10.4028\/www.scientific.net\/KEM.644.53","article-title":"Innovative on-Line Oil Sensor Technologies for the Condition Monitoring of Wind Turbines","volume":"644","author":"Gorritxategi","year":"2015","journal-title":"Key Eng. Mater."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"125103","DOI":"10.1088\/0957-0233\/24\/12\/125103","article-title":"Radial inductive debris detection sensor and performance analysis","volume":"24","author":"Hong","year":"2013","journal-title":"Meas. Sci. Technol."},{"key":"ref_14","unstructured":"Miller, J.L., and Kitaljevich, D. (2000, January 25). In-line oil debris monitor for aircraft engine condition assessment. Proceedings of the 2000 IEEE Aerospace Proceedings, Big Sky, MT, USA."},{"key":"ref_15","unstructured":"Kempster, R.W., and George, D.B. (1994). Detection and Discrimination between Ferromagnetic and Non-Ferromagnetic Conductive Particles in a Fluid. (5,315,243), U.S. Patent."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/0043-1648(88)90067-1","article-title":"An on-line ferromagnetic wear debris sensor for machinery condition monitoring and failure detection","volume":"128","author":"Chambers","year":"1988","journal-title":"Wear"},{"key":"ref_17","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_18","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Wang, S., Hong, W., and Tomovic, M. (2016, January 5\u20137). Aliasing signal separation of oil debris monitoring. Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, Hefei, China.","DOI":"10.1109\/ICIEA.2016.7603856"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Li, T., Wang, S., Zio, E., Shi, J., and Hong, W. (2018). Aliasing signal separation of superimposed abrasive debris based on degenerate unmixing estimation technique. Sensors, 18.","DOI":"10.3390\/s18030866"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"015104","DOI":"10.1088\/0957-0233\/21\/1\/015104","article-title":"In-line identification of oil debris signals: An adaptive subband filtering approach","volume":"21","author":"Bozchalooi","year":"2010","journal-title":"Meas. Sci. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Liu, H., Wang, S., Hong, W., Zhang, C., Wang, X., Haokuo, L., Shaoping, W., Wei, H., Chao, Z., and Xingjian, W. (2015, January 4\u20136). Design and experimental test of an on-line particle detection sensor based on symmetrical magnetic field. Proceedings of the 2015 International Conference on Fluid Power and Mechatronics (FPM), Harbin, China.","DOI":"10.1109\/FPM.2015.7337119"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"084102","DOI":"10.1103\/PhysRevLett.100.084102","article-title":"Detrended Cross-Correlation Analysis: A New Method for Analyzing Two Non-stationary Time Series","volume":"100","author":"Podobnik","year":"2008","journal-title":"Phys. Rev. Lett."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/20\/5949\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:25:15Z","timestamp":1760178315000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/20\/5949"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,21]]},"references-count":22,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["s20205949"],"URL":"https:\/\/doi.org\/10.3390\/s20205949","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,21]]}}}