Research Progress in Aero-Engine Gas-Path Electrostatic Monitoring Technology
DOI:
https://doi.org/10.6919/ICJE.202609_12(9).0015Keywords:
Electrostatic Monitoring Technology; Aero-engine; Electrostatic Sensor; Electrostatic Signal.Abstract
Gas-path electrostatic monitoring for aero-engines provides a new source of information for early fault detection and health management by sensing charged particles generated during fault evolution. This paper reviews the development of gas-path electrostatic monitoring technology, including particle charging and electrostatic induction mechanisms, sensor design, weak-signal denoising, feature extraction, health baseline modeling, and sensor-array-based inversion. Its applications to rub-impact, ablation, carbon deposition, oil leakage, and foreign object monitoring are also discussed. Key challenges are further summarized, including quantitative characterization of fault severity, particle-cloud inversion, dynamic baseline construction, scarcity of real fault samples, standardization, and airworthiness validation. Finally, future research directions are outlined, with emphasis on multiphysics modeling, intelligent sensing, multisource information fusion, and remaining useful life prediction.
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References
[1] Hess, A. (2001). The Joint Strike Fighter (JSF) Prognostics and Health Management. NDIA Conference.
[2] Hess, A., Calvello, G., & Dabney, T. (2004). PHM-A key enabler for the JSF autonomic logistics support concept. IEEE Aerospace Conference, 3543–3550.
[3] Hess, A., & Fila, L. (2002). The Joint Strike Fighter PHM concept: Potential impact on aging aircraft problems. IEEE Aerospace Conference, 3021–3026.
[4] Novis, A., & Powrie, H. (2006). PHM sensor implementation in the real world-A status report. IEEE Aerospace Conference, 1–9.
[5] Couch, R. P., & Rossbach, D. R. (1972). Sensing jet engine performance and incipient failure with electrostatic probes. DTIC.
[6] Couch, R. P., Rossbach, D. R., & Burgess, R. W. (1974). Sensing incipient engine failure with electrostatic probes. Instrumentation for Airbreathing Propulsion, 515–529.
[7] Mitchell, J. E. (1975). Exploding wire simulation of jet-engine gas-path microdistresses. Air Force Institute of Technology.
[8] Dunn, R. W. (1976). The electrostatic sensing of simulated MA-1A gas path distresses. Air Force Institute of Technology.
[9] Gifford, W. E., III. (1976). A method for analysis of electrostatic probe signals relating to jet-engine microdistresses. Air Force Institute of Technology.
[10] Couch, R. P. (1978). Detecting abnormal turbine engine deterioration using electrostatic methods. Journal of Aircraft, 15(10), 692–695.
[11] Cartwright, R. A., & Fisher, C. (1991). Marine gas turbine condition monitoring by gas path electrostatic detection techniques. International Gas Turbine and Aero-engine Congress and Exposition.
[12] Powrie, H. E. G., & McNicholas, K. (1997). Gas path condition monitoring during accelerated mission testing of a demonstrator engine. 33rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference, AIAA-97-2904.
[13] Powrie, H. E. G., & Fisher, C. E. (1999). Engine health monitoring: Towards total prognostics. IEEE Aerospace Conference, 3, 11–20.
[14] Powrie, H. E. G., & Fisher, C. E. (1999). Monitoring of foreign objects ingested into the intake of a gas turbine aero-engine. International Conference on Condition Monitoring, Swansea, 175–190.
[15] Fisher, C. E. (2000). Gas path debris monitoring-A 21st century PHM tool. IEEE Aerospace Conference, 6, 441–448.
[16] Fisher, C. E. (2001). Data and information fusion for gas path debris monitoring. IEEE Aerospace Conference, 3017–3022.
[17] Powrie, H. E. G., & Worsfold, J. (2001). Gas path debris monitoring for heavy-duty gas turbines-A pilot study. IDGTE Gas Turbine Symposium, 168–179.
[18] Lapini, G. L., Zippo, M., & Tirone, G. (2001). The use of electrostatic charge measurements as an early warning of distress in heavy-duty gas turbines. ASME Turbo Expo, V004T04A027.
[19] Powrie, H. E. G., Wood, R. J. K., Harvey, T. J., & et al. (2002). Electrostatic charge generation associated with machinery component deterioration. IEEE Aerospace Conference, 2927–2934.
[20] Angello, L. (2004). Combustion turbine electrostatic debris monitoring system (EDMS) assessment. Electric Power Research Institute.
[21] Powrie, H. E. G., & Novis, A. (2006). Gas path debris monitoring for F-35 Joint Strike Fighter propulsion system PHM. IEEE Aerospace Conference, 1–8.
[22] Wilcox, M., Ransom, D., Henry, M., & Platt, J. (2010). Engine distress detection in gas turbines with electrostatic sensors. ASME Turbo Expo, 39–51.
[23] Lawton, J., & Weinberg, F. J. (1969). Electrical aspects of combustion. Clarendon Press.
[24] Kidin, N., & Makhviladze, G. (1976). Electric field of laminar flame with high degree of ionization. Combustion, Explosion and Shock Waves, 12(6), 763–767.
[25] Vatazhin, A. B., Golentsov, D. A., Likhter, V. A., & Shulgin, V. I. (1997). Aircraft engine state nonobstructive electrostatic monitoring: Theoretical and laboratory modelling. Journal of Electrostatics, 40–41, 711–716.
[26] Vatazhin, A. B., Golentsov, D. A., Likhter, V. A., & Shulgin, V. I. (1999). Electrical aspects of body disintegration in a gas dynamic flow. Fluid Dynamics, 34(4), 516–520.
[27] Vatazhin, A. B., & Ulybyshev, K. (2000). Model of formation of the electric current in aircraft jet engine ducts. Fluid Dynamics, 35(5), 748–755.
[28] Sorokin, A., Vancassel, X., & Mirabel, P. (2003). Emission of ions and charged soot particles by aircraft engines. Atmospheric Chemistry and Physics, 3(2), 325–334.
[29] Sorokin, A., & Arnold, F. (2004). Electrically charged small soot particles in the exhaust of an aircraft gas-turbine engine combustor: Comparison of model and experiment. Atmospheric Environment, 38(17), 2611–2618.
[30] Sorokin, A., & Arnold, F. (2006). Organic positive ions in aircraft gas-turbine engine exhaust. Atmospheric Environment, 40(32), 6077–6087.
[31] Lacks, D. J., & Shinbrot, T. (2019). Long-standing and unresolved issues in triboelectric charging. Nature Reviews Chemistry, 3(8), 465–476.
[32] Baytekin, H. T., Baytekin, B., Incorvati, J. T., & Grzybowski, B. A. (2012). Material transfer and polarity reversal in contact charging. Angewandte Chemie International Edition, 51(20), 4843–4847.
[33] Pandey, R. K., Kakehashi, H., Nakanishi, H., & et al. (2018). Correlating material transfer and charge transfer in contact electrification. The Journal of Physical Chemistry C, 122(28), 16154–16160.
[34] Vasandani, P., Mao, Z. H., Jia, W., & et al. (2017). Relationship between triboelectric charge and contact force for two triboelectric layers. Journal of Electrostatics, 90, 147–152.
[35] Wen, Z., Zuo, H., & Li, Y. (2008). Electrostatic monitoring technology and experiments for gas-path particles. Journal of Aerospace Power, 23(12), 2321–2326. (in Chinese)
[36] Wen, Z., Zuo, H., Wang, H., & et al. (2008). Characteristics of an electrostatic sensor for aero-engine gas-path monitoring. Transducer and Microsystem Technologies, 27(11), 28–31. (in Chinese)
[37] Wen, Z., Zuo, H., & Li, Y. (2009). A new gas-path monitoring method for aero-engines. Journal of Nanjing University of Aeronautics & Astronautics, 41(2), 248–252. (in Chinese)
[38] Li, Y., Zuo, H., & Wen, Z. (2009). Simulation experiments on electrostatic monitoring technology for aero-engine gas-path particles. Acta Aeronautica et Astronautica Sinica, 30(4), 604–608. (in Chinese)
[39] Li, Y., & Zuo, H. (2010). Electrostatic monitoring method and simulation experiment for rubbing faults. Acta Aeronautica et Astronautica Sinica, 31(6), 1156–1163. (in Chinese)
[40] Li, Y., Zuo, H., & Liu, P. (2010). Exploratory experiment on exhaust electrostatic monitoring for a turboshaft aero-engine. Acta Aeronautica et Astronautica Sinica, 31(11), 2174–2181. (in Chinese)
[41] Wen, Z., Zuo, H., & Pecht, M. G. (2011). Electrostatic monitoring of gas path debris for aero-engines. IEEE Transactions on Reliability, 60(1), 33–40.
[42] Sun, J., Zuo, H., Fu, Y., & et al. (2012). Analysis of influencing factors on exhaust electrostatic monitoring signals of a turboshaft engine. Acta Aeronautica et Astronautica Sinica, 33(3), 709–716. (in Chinese)
[43] Liu, P., Zuo, H., Sun, J., & et al. (2012). Online monitoring of gas-path oil-leakage faults in a turbojet engine. Chinese Journal of Scientific Instrument, 33(11), 2601–2607. (in Chinese)
[44] Sun, J., Zuo, H., & Liu, P. (2013). Analysis and application of a baseline model for aero-engine exhaust electrostatic signals. Journal of Aerospace Power, 28(3), 531–540. (in Chinese)
[45] Liu, P., Zuo, H., Fu, Y., & et al. (2013). Exhaust electrostatic monitoring and gas-path fault characteristics of a turbojet engine. Journal of Aerospace Power, 28(2), 473–480. (in Chinese)
[46] Liu, P., Zuo, H., Sun, J., & et al. (2013). Application of gas-path electrostatic monitoring technology in turbojet-engine testing. China Mechanical Engineering, 24(20), 2758–2763, 2790. (in Chinese)
[47] Fu, Y., Zuo, H., Wang, R., Liu, P., Cai, J., & Wen, Z. (2013). A monitoring experiment for gas path electrostatic probe-type sensor on turbojet engine. Information Technology Journal, 12(2), 331–337.
[48] Wen, Z., Ma, X., & Zuo, H. (2014). Characteristics analysis and experiment verification of electrostatic sensor for aero-engine exhaust gas monitoring. Measurement, 47, 633–644. https://doi.org/10.1016/j.measurement.2013.09.041
[49] Liu, P. P., Zuo, H. F., & Sun, J. Z. (2014). The electrostatic sensor applied to the online monitoring experiments of combustor carbon deposition fault in aero-engine. IEEE Sensors Journal, 14(3), 686–694.
[50] Chen, Z., Tang, X., Hu, Z., & Yang, Y. (2014). Investigations into sensing characteristics of circular thin-plate electrostatic sensors for gas path monitoring. Chinese Journal of Aeronautics, 27(4), 812–820.
[51] Lin, J., Chen, Z. S., Hu, Z., Yang, Y. M., & Tang, X. (2014). Analytical and numerical investigations into hemisphere-shaped electrostatic sensors. Sensors, 14(8), 14021–14037.
[52] Yin, Y., Zuo, H., & et al. (2015). Simulation experiment and analysis of electrostatic induction characteristics of particles ingested by an aero-engine. Acta Aeronautica et Astronautica Sinica, 36(2), 691–702. https://doi.org/10.7527/S1000-6893.2014.0111 (in Chinese)
[53] Wen, Z., Hou, J., & Jiang, Z. (2015). Formation mechanism analysis and detection of charged particles in an aero-engine gas path. International Journal of Aeronautical and Space Sciences, 16(2), 247–253.
[54] Wen, Z., Hou, J., & Zuo, H. (2015). Characteristic analysis and extraction of aero-engine electrostatic monitoring signals. Journal of Vibration, Measurement & Diagnosis, 35(3), 453–458. (in Chinese)
[55] Addabbo, T., Fort, A., Garbin, R., & et al. (2015). Theoretical characterization of a gas path debris detection monitoring system based on electrostatic sensors and charge amplifiers. Measurement, 64, 138–146.
[56] Addabbo, T., Fort, A., Mugnaini, M., & et al. (2015). Theoretical modeling of an electrostatic gas-path debris detection system with experimental validation. IEEE Sensors Applications Symposium, 1–5.
[57] Tang, X., Chen, Z. S., Li, Y., Hu, Z., & Yang, Y. M. (2016). Analysis of the dynamic sensitivity of hemisphere-shaped electrostatic sensors' circular array for charged particle monitoring. Sensors, 16(9), 1403.
[58] Yin, Y., Zuo, H., Fu, Y., & et al. (2016). Airborne monitoring experiment of an electrostatic sensor on a turbofan aero-engine. Journal of Aerospace Power, 31(12), 3054–3063. (in Chinese)
[59] Wen, Z., Hou, J., & Atkin, J. (2017). A review of electrostatic monitoring technology: The state of the art and future research directions. Progress in Aerospace Sciences, 94, 1–11. https://doi.org/10.1016/j.paerosci.2017.07.003
[60] Liu, R., Zuo, H., Sun, J., & Bei, S. (2017). A review on electrostatic monitoring. 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control, 128–131. https://doi.org/10.1109/SDPC.2017.33
[61] Yin, Y., Cai, J., Zuo, H., & et al. (2017). Experimental investigation on electrostatic monitoring technology for civil turbofan engine. Journal of Vibroengineering, 19(2), 967–987.
[62] Fu, Y., Yin, Y, & Zuo, H. (2018). Aero-engine exhaust electrostatic monitoring and analysis of signal characteristics. Chinese Journal of Scientific Instrument, 39(2), 160–168. (in Chinese)
[63] Fu, Y., Yin, Y., & Zuo, H. (2018). An electrostatic-signal denoising method based on sparse decomposition. Journal of Aerospace Power, 33(11), 2573–2582. (in Chinese)
[64] Tang, X., Chen, Z., Li, Y., & Yang, Y. (2018). Compressive sensing-based electrostatic sensor array signal processing and exhausted abnormal debris detecting. Mechanical Systems and Signal Processing, 105, 404–426.
[65] Fu, Y., Yin, Y., Feng, Z., Zuo, H., & Sun, S. (2019). Engine performance assessment method integrating electrostatic signals and gas-path parameters. Journal of Propulsion Technology, 40(2), 449–455. (in Chinese)
[66] Fu, Y., Yin, Y., Mao, H., Zuo, H., & Feng, Z. (2019). Typical aero-engine fault diagnosis based on electrostatic monitoring and neural networks. Computer Integrated Manufacturing Systems, 25(11), 2852–2862. (in Chinese)
[67] Addabbo, T., Fort, A., Mugnaini, M., & et al. (2019). Measurement system based on electrostatic sensors to detect moving charged debris with planar-isotropic accuracy. IEEE Transactions on Instrumentation and Measurement, 68(3), 837–844.
[68] Wang, C., Zhang, S., Li, Y., & Jia, L. (2020). Gas-path debris monitoring based on electrostatic cross-correlation sensitivity weighting. Journal of Beijing University of Aeronautics and Astronautics, 46(3), 457–464. https://doi.org/10.13700/j.bh.1001-5965.2019.0102 (in Chinese)
[69] Zhong, Z., Zuo, H., Guo, J., & et al. (2020). Method for estimating particle charge based on an electrostatic sensor array. Chinese Journal of Scientific Instrument, 41(7), 80–90. (in Chinese)
[70] Guo, J., Zhong, Z., Jiang, H., & Zuo, H. (2021). Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array. Science Progress, 104(2). https://doi.org/10.1177/00368504211023691
[71] Jiang, H., Zuo, H., Guo, J., & et al. (2021). Electrostatic monitoring method for aero-engine blade-tip radial clearance. Journal of Aerospace Power, 36(3), 466–476. (in Chinese)
[72] Guo, J., Zuo, H., Zhong, Z., & Jiang, H. (2021). New instrument based on electrostatic sensor array for measuring tribo-electrification charging due to single particle impacts. Review of Scientific Instruments, 92(9), 095001. https://doi.org/10.1063/5.0056948
[73] Zhong, Z., Zuo, H., & Jiang, H. (2022). A nonlinear total variation based denoising method for electrostatic signal of low signal-to-noise ratio. Advances in Mechanical Engineering, 14(11), 1–10. https://doi.org/10.1177/16878132221136942
[74] Guo, J., Zuo, H., Zhong, Z., & Jiang, H. (2022). Foreign object monitoring method in aero-engines based on electrostatic sensor. Aerospace Science and Technology, 123, 107489. https://doi.org/10.1016/j.ast.2022.107489
[75] Yin, Y., Wen, Z., & Zuo, H. (2023). Gas-path fault identification method based on variational mode decomposition of electrostatic signals and random forest. Journal of Propulsion Technology, 44(5), 292–304. (in Chinese)
[76] Yin, Y., Wen, Z., & Guo, X. (2024). A novel method of gas-path health assessment based on exhaust electrostatic signal and performance parameters. Measurement, 224, 113810. https://doi.org/10.1016/j.measurement.2023.113810
[77] Liu, Y., Liu, Z., Bai, F., Zuo, H., Guo, Z., & Li, X. (2024). The electrostatic induction characteristics of SiC/SiC particles in aero-engine exhaust gases: A simulated experiment and analysis. Aerospace, 11(6), 481. https://doi.org/10.3390/aerospace11060481
[78] Liu, Y., Zuo, H., Liu, Z., Fu, Y., Jia, J. J., & Dhupia, J. S. (2024). Electrostatic signal self-adaptive denoising method combined with CEEMDAN and wavelet threshold. Aerospace, 11(6), 491. https://doi.org/10.3390/aerospace11060491
[79] Ali, M., He, J., Memon, M. M., Ali, A., & Zhou, X. (2024). Multiphysics coupling modeling and simulation of electrostatic sensors for gas path monitoring. IEEE Transactions on Instrumentation and Measurement, 73, 3526111. https://doi.org/10.1109/TIM.2024.3428596
[80] Liu, Y., Liu, Z., Bai, F., Guo, Z., & Zuo, H. (2024). Combined denoising method for aero-engine gas-path electrostatic signals. Journal of Nanjing University of Aeronautics & Astronautics, 56(6), 1036–1047. https://doi.org/10.16356/j.1005-2615.2024.06.006 (in Chinese)
[81] Guo, J., Zuo, H., Zhen, B., & Zhang, G. (2025). Application analysis of electrostatic sensors for aero-engine overspeed monitoring. Journal of Nanjing University of Aeronautics & Astronautics, 57(2), 361–370. https://doi.org/10.16356/j.1005-2615.2025.02.017 (in Chinese)
[82] Yan, C., Liu, Y., & Lu, F. (2026). A denoising method for aeroengine gas path electrostatic signal of low signal-to-noise ratio based on IMFs optimized reconstruction and wavelet threshold. Scientific Reports, 16, 2762. https://doi.org/10.1038/s41598-025-32599-2
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