{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T18:31:04Z","timestamp":1779906664199,"version":"3.53.1"},"reference-count":40,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T00:00:00Z","timestamp":1714176000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korean government (MSIT)","award":["RS-2022-00164702"],"award-info":[{"award-number":["RS-2022-00164702"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study introduces a fault diagnosis algorithm based on particle filtering for open-cycle liquid-propellant rocket engines (LPREs). The algorithm serves as a model-based method for the startup process, accounting for more than 30% of engine failures. Similar to the previous fault detection and diagnosis (FDD) algorithm for the startup process, the algorithm in this study is composed of a nonlinear filter to generate residuals, a residual analysis, and a multiple-model (MM) approach to detect and diagnose faults from the residuals. In contrast to the previous study, this study makes use of the modified cumulative sum (CUSUM) algorithm, widely used in change-detection monitoring, and a particle filter (PF), which is theoretically the most accurate nonlinear filter. The algorithm is confirmed numerically using the CUSUM and MM methods. Subsequently, the FDD algorithm is compared with an algorithm from a previous study using a Monte Carlo simulation. Through a comparative analysis of algorithmic performance, this study demonstrates that the current PF-based FDD algorithm outperforms the algorithm based on other nonlinear filters.<\/jats:p>","DOI":"10.3390\/s24092798","type":"journal-article","created":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T08:49:24Z","timestamp":1714380564000},"page":"2798","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Particle-Filter-Based Fault Diagnosis for the Startup Process of an Open-Cycle Liquid-Propellant Rocket Engine"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7445-6711","authenticated-orcid":false,"given":"Jihyoung","family":"Cha","sequence":"first","affiliation":[{"name":"Centre for Aeronautics, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0481-7969","authenticated-orcid":false,"given":"Sangho","family":"Ko","sequence":"additional","affiliation":[{"name":"Department of Smart Air Mobility, Korea Aerospace University, 76 Hanggongdaehang-ro, Deogyang-gu, Goyang-si 10540, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soon-Young","family":"Park","sequence":"additional","affiliation":[{"name":"Rocket Engine Department, Korea Aerospace Research Institute, 169-84 Gwahak-ro, Daejeon 34133, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jsse.2019.05.007","article-title":"Space traffic management in the new space era","volume":"6","author":"Muelhaupt","year":"2019","journal-title":"J. Space Saf. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"269","DOI":"10.5028\/jatm.v9i3.853","article-title":"Status and trends of smallsats and their launch vehicles\u2014An up-to-date review","volume":"9","author":"Wekerle","year":"2017","journal-title":"J. Aerosp. Technol. Manag."},{"key":"ref_3","first-page":"37","article-title":"Low Cost and Reusability of Launch Vehicle","volume":"17","author":"Lu","year":"2019","journal-title":"Aerosp. China"},{"key":"ref_4","first-page":"686","article-title":"Technology Development Prospects and Direction of Reusable Launch Vehicles and Future Propulsion Systems","volume":"44","author":"Kim","year":"2016","journal-title":"J. Korean Soc. Aeronaut. Space Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"138","DOI":"10.6108\/KSPE.2018.22.2.138","article-title":"A survey on recovery technology for reusable space launch vehicle","volume":"22","author":"Choo","year":"2018","journal-title":"J. Korean Soc. Propuls. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sun, H., Cheng, Y., Jiang, B., Lu, F., and Wang, N. (2024). Anomaly Detection Method for Rocket Engines Based on Convex Optimized Information Fusion. Sensors, 24.","DOI":"10.3390\/s24020415"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kawatsu, K., Tsutsumi, S., Hirabayashi, M., and Sato, D. (2020, January 6\u201310). Model-based fault diagnostics in an electromechanical actuator of reusable liquid rocket engine. Proceedings of the AIAA Scitech 2020 Forum, Orlando, FL, USA.","DOI":"10.2514\/6.2020-1624"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.actaastro.2004.05.070","article-title":"Liquid-propellant rocket engines health-monitoring\u2014A survey","volume":"56","author":"Wu","year":"2005","journal-title":"Acta Astronaut."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"50","DOI":"10.6108\/KSPE.2014.18.6.050","article-title":"A survey on health monitoring and management technology for liquid rocket engines","volume":"18","author":"Cha","year":"2014","journal-title":"J. Korean Soc. Propuls. Eng."},{"key":"ref_10","first-page":"22","article-title":"A Survey on Fault Detection and Diagnosis Method for Open-Cycle Liquid Rocket Engines through China R&D Case","volume":"11","author":"Lee","year":"2017","journal-title":"J. Aerosp. Syst. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"108610","DOI":"10.1016\/j.ress.2022.108610","article-title":"A multi-head attention network with adaptive meta-transfer learning for RUL prediction of rocket engines","volume":"225","author":"Pan","year":"2022","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kawatsu, K. (2019, January 2\u20139). PHM by using multi-physics system-level modeling and simulation for EMAs of liquid rocket engine. Proceedings of the 2019 IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO.2019.8741827"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lin, R., Yang, J., Huang, L., Liu, Z., Zhou, X., and Zhou, Z. (2023). Review of Launch Vehicle Engine PHM Technology and Analysis Methods Research. Aerospace, 10.","DOI":"10.3390\/aerospace10060517"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"535","DOI":"10.5139\/IJASS.2016.17.4.535","article-title":"Dynamic simulation and analysis of the space shuttle main engine with artificially injected faults","volume":"17","author":"Cha","year":"2016","journal-title":"Int. J. Aeronaut. Space Sci."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zhang, W., Tian, G., Xu, Z., and Yang, Z. (2016). Failure Characteristics Analysis and Fault Diagnosis for Liquid Rocket Engines, Springer.","DOI":"10.1007\/978-3-662-49254-3"},{"key":"ref_16","unstructured":"Cha, J. (2019). Transient State Modeling, Simulation, and Fault Detection\/Diagnosis of an Open-Cycle Liquid Rocket Engine. [Ph.D. Thesis, Department of Aerospace and Mechanical Engineering, Korea Aerospace University]."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1016\/j.actaastro.2020.08.019","article-title":"Deep neural network approach for fault detection and diagnosis during startup transient of liquid-propellant rocket engine","volume":"177","author":"Park","year":"2020","journal-title":"Acta Astronaut."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Yu, H., and Wang, T. (2021). A method for real-time fault detection of liquid rocket engine based on adaptive genetic algorithm optimizing back propagation neural network. Sensors, 21.","DOI":"10.3390\/s21155026"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, T., Ding, L., and Yu, H. (2022). Research and development of fault diagnosis methods for liquid rocket engines. Aerospace, 9.","DOI":"10.3390\/aerospace9090481"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhang, X., Hua, X., Zhu, J., and Ma, M. (2023). Intelligent Fault Diagnosis of Liquid Rocket Engine via Interpretable LSTM with Multisensory Data. Sensors, 23.","DOI":"10.3390\/s23125636"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.actaastro.2019.03.075","article-title":"Fault detection and diagnosis algorithms for transient state of an open-cycle liquid rocket engine using nonlinear Kalman filter methods","volume":"163","author":"Cha","year":"2019","journal-title":"Acta Astronaut."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"109837","DOI":"10.1016\/j.ress.2023.109837","article-title":"Dynamic model-assisted transferable network for liquid rocket engine fault diagnosis using limited fault sample","volume":"243","author":"Wang","year":"2024","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"108759","DOI":"10.1016\/j.ress.2022.108759","article-title":"A soft-target difference scaling network via relational knowledge distillation for fault detection of liquid rocket engine under multi-source trouble-free samples","volume":"228","author":"Li","year":"2022","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Huang, P., Yu, H., and Wang, T. (2022). A Study Using Optimized LSSVR for Real-Time Fault Detection of Liquid Rocket Engine. Processes, 10.","DOI":"10.3390\/pr10081643"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"924","DOI":"10.2514\/1.A35592","article-title":"Fault Detection and Diagnosis for Thrust Drop of Launch Vehicles against Disturbances","volume":"60","author":"Zhang","year":"2023","journal-title":"J. Spacecr. Rocket."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/s42496-022-00118-5","article-title":"Analysis of space launch vehicle failures and post-mission disposal statistics","volume":"101","author":"Wiedemann","year":"2022","journal-title":"Aerotec. Missili Spaz."},{"key":"ref_27","unstructured":"Harland, D.M., and Lorenz, R. (2007). Space Systems Failures: Disasters and Rescues of Satellites, Rocket and Space Probes, Springer Science & Business Media."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/0094-5765(81)90033-3","article-title":"Hydrodynamic modelling of the starting process in liquid-propellant engines","volume":"8","author":"Kalnin","year":"1981","journal-title":"Acta Astronaut."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1515\/aon-2016-0005","article-title":"Comparison of estimation accuracy of EKF, UKF and PF filters","volume":"23","author":"Konatowski","year":"2016","journal-title":"Annu. Navig"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Gadsden, S., Dunne, D., Habibi, S., and Kirubarajan, T. (2009, January 2\u20136). Comparison of extended and unscented Kalman, particle, and smooth variable structure filters on a bearing-only target tracking problem. Proceedings of the Signal and Data Processing of Small Targets 2009, San Diego, CA, USA.","DOI":"10.1117\/12.825424"},{"key":"ref_31","unstructured":"Steven, M.K. (1998). Fundamentals of Statistical Processing, Volume 2: Detection Theory, Pearson."},{"key":"ref_32","first-page":"6","article-title":"Mathematical modeling and simulation for steady state of a 75-ton liquid propellant rocket engine","volume":"11","author":"Lee","year":"2017","journal-title":"J. Aerosp. Syst. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Cha, J. (2023). Numerical Simulation of Chemical Propulsion Systems: Survey and Fundamental Mathematical Modeling Approach. Aerospace, 10.","DOI":"10.3390\/aerospace10100839"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1109\/MSP.2003.1236770","article-title":"Particle filtering","volume":"20","author":"Djuric","year":"2003","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1109\/78.978374","article-title":"A tutorial on particle filters for online nonlinear\/non-Gaussian Bayesian tracking","volume":"50","author":"Arulampalam","year":"2002","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_36","first-page":"182","article-title":"Methodology of liquid rocket engine diagnosis","volume":"11","author":"Kim","year":"2012","journal-title":"Aerosp. Eng. Technol."},{"key":"ref_37","unstructured":"Basseville, M., and Nikiforov, I.V. (1993). Detection of Abrupt Changes: Theory and Application, Prentice-Hall."},{"key":"ref_38","unstructured":"Bernstein, K.S., Kujala, R., Fogt, V., and Romine, P. (2011). Structural Design Requirements and Factors of Safety for Spaceflight Hardware: For Human Spaceflight."},{"key":"ref_39","unstructured":"Klem, M., and Fry, R. (1997). Guidelines for Combustion Stability Specifications and Verification Procedures for Liquid Propellant Rocket Engines."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.ins.2013.05.032","article-title":"Fault detection and isolation of a dual spool gas turbine engine using dynamic neural networks and multiple model approach","volume":"259","author":"Vanini","year":"2014","journal-title":"Inf. Sci."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2798\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:34:52Z","timestamp":1760106892000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2798"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,27]]},"references-count":40,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["s24092798"],"URL":"https:\/\/doi.org\/10.3390\/s24092798","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,27]]}}}