{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T11:27:12Z","timestamp":1769513232414,"version":"3.49.0"},"reference-count":16,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,4,11]],"date-time":"2017-04-11T00:00:00Z","timestamp":1491868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Nature Science Foundation of China","award":["51276087"],"award-info":[{"award-number":["51276087"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios.<\/jats:p>","DOI":"10.3390\/s17040835","type":"journal-article","created":{"date-parts":[[2017,4,11]],"date-time":"2017-04-11T11:41:42Z","timestamp":1491910902000},"page":"835","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2965-5380","authenticated-orcid":false,"given":"Xiaodong","family":"Chang","sequence":"first","affiliation":[{"name":"Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinquan","family":"Huang","sequence":"additional","affiliation":[{"name":"Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Lu","sequence":"additional","affiliation":[{"name":"Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"517","DOI":"10.2514\/3.20348","article-title":"Advanced detection, isolation, and accommodation of sensor failures\u2014Real-time evaluation","volume":"11","author":"Merrill","year":"1988","journal-title":"J. Guid. Control Dynam."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1115\/1.1850505","article-title":"Evaluation of an enhanced bank of Kalman filters for in-flight aircraft engine sensor fault diagnostics","volume":"127","author":"Kobayashi","year":"2005","journal-title":"J. Eng. Gas Turbines Power"},{"key":"ref_3","unstructured":"Simon, D.L. (2010). An Integrated Architecture for on-Board Aircraft Engine Performance Trend Monitoring and Gas Path Fault Diagnostics."},{"key":"ref_4","unstructured":"Armstrong, J.B., and Simon, D.L. (August, January 31). Implementation of an integrated on-board aircraft engine diagnostic architecture. Proceedings of the 47th Joint Propulsion Conference and Exhibit, San Diego, CA, USA."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Kobayashi, T., and Simon, D.L. (2006). Hybrid Kalman Filter: A New Approach for Aircraft Engine In-flight Diagnostics.","DOI":"10.1115\/GT2006-90870"},{"key":"ref_6","unstructured":"Tan, C.P., and Edwards, C. (2002, January 8\u201310). A robust sensor fault reconstruction scheme using sliding mode observers applied to a nonlinear aero-engine model. Proceedings of the American Control Conference, IEEE, Anchorage, AK, USA."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.conengprac.2014.05.003","article-title":"Development and application of sliding mode LPV fault reconstruction schemes for the ADDSAFE Benchmark","volume":"31","author":"Alwi","year":"2014","journal-title":"Control Eng. Pract."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.conengprac.2015.01.006","article-title":"Adaptive sliding mode observer for sensor fault diagnosis of an industrial gas turbine","volume":"38","author":"Rahme","year":"2015","journal-title":"Control Eng. Pract."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Chang, X., Huang, J., Lu, F., and Sun, H. (2016). Gas-path Health Estimation for an Aircraft Engine Based on a Sliding mode observer. Energies, 9.","DOI":"10.3390\/en9080598"},{"key":"ref_10","unstructured":"Edwards, C., and Spurgeon, S.K. (1988). Sliding Mode Control: Theory and Applications, CRC Press."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1947","DOI":"10.1002\/rnc.3009","article-title":"Robust fault reconstruction for linear parameter varying systems using sliding mode observers","volume":"24","author":"Alwi","year":"2013","journal-title":"Int. J. Robust Nonlinear Control"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1109\/TAC.2012.2186179","article-title":"Strict Lyapunov Functions for the Super-Twisting Algorithm","volume":"57","author":"Moreno","year":"2012","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Edwards, C., Alwi, H., and Tan, C.P. (2012). Sliding Modes for Fault Detection and Fault-Tolerant Control. Sliding Modes after the First Decade of the 21st Century, Springer.","DOI":"10.1007\/978-3-642-22164-4_11"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"492","DOI":"10.3390\/en6010492","article-title":"Gas Path Health Monitoring for a Turbofan Engine Based on a Nonlinear Filtering Approach","volume":"6","author":"Lu","year":"2013","journal-title":"Energies"},{"key":"ref_15","unstructured":"Zhou, W.X. (2006). Research on Object-Oriented Modeling and Simulation for Aeroengine and Control System. [Ph.D. Thesis, Nanjing University of Aeronautics and Astronautics]. (In Chinese)."},{"key":"ref_16","first-page":"1795","article-title":"Engine Component Performance Prognostics based on Decision Fusion","volume":"30","author":"Lu","year":"2009","journal-title":"Acta Aeronaut. Astronaut. Sin."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/4\/835\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:32:25Z","timestamp":1760207545000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/4\/835"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4,11]]},"references-count":16,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2017,4]]}},"alternative-id":["s17040835"],"URL":"https:\/\/doi.org\/10.3390\/s17040835","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,4,11]]}}}