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Enhanced Component Analytical Solution for Performance Adaptation and Diagnostics of Gas Turbines

Author

Listed:
  • Binbin Yan

    (Beijing Key Laboratory of High-end Mechanical Equipment Health Monitoring and Self-Recovery DSE, Beijing University of Chemical Technology, Chaoyang District, Beijing 100029, China)

  • Minghui Hu

    (Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education, Beijing University of Chemical Technology, Chaoyang District, Beijing 100029, China)

  • Kun Feng

    (Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education, Beijing University of Chemical Technology, Chaoyang District, Beijing 100029, China)

  • Zhinong Jiang

    (Joint Laboratory of Aero Engine Vibration Health Monitoring, Beijing University of Chemical Technology, Chaoyang District, Beijing 100029, China)

Abstract

Accurate component analytical solution is very important to gas path prognostics and diagnostics of a gas turbine. However, due to the highly complex nonlinear behavior of component performance, the nonlinear relationships between various key parameters still should be further studied. For this purpose, a new component analytical solution is proposed to enhance the current adaptation and diagnostics scheme of gas turbines. First, the tuning factors are defined to construct the enhanced component analytical solution and identify the nonlinear behaviors more accurately. Second, a sensitivity analysis for tuning factors is performed to understand the effect of each factor on the shape of component maps. Then, a particle swarm optimization algorithm is used to capture the optimal tuning factors, and then the performance adaptation is implemented. Finally, the proposed method has been validated with normal field data and fouling fault field data of a PGT25+ gas turbine. Compared with two earlier off-design point adaptation methods, the proposed method shows some advantages in performance adaptation and diagnostics.

Suggested Citation

  • Binbin Yan & Minghui Hu & Kun Feng & Zhinong Jiang, 2021. "Enhanced Component Analytical Solution for Performance Adaptation and Diagnostics of Gas Turbines," Energies, MDPI, vol. 14(14), pages 1-20, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4356-:d:597272
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    References listed on IDEAS

    as
    1. Li, Y.G. & Pilidis, P., 2010. "GA-based design-point performance adaptation and its comparison with ICM-based approach," Applied Energy, Elsevier, vol. 87(1), pages 340-348, January.
    2. Tsoutsanis, Elias & Meskin, Nader & Benammar, Mohieddine & Khorasani, Khashayar, 2014. "A component map tuning method for performance prediction and diagnostics of gas turbine compressors," Applied Energy, Elsevier, vol. 135(C), pages 572-585.
    3. Qingcai Yang & Shuying Li & Yunpeng Cao & Fengshou Gu & Ann Smith, 2018. "A Gas Path Fault Contribution Matrix for Marine Gas Turbine Diagnosis Based on a Multiple Model Fault Detection and Isolation Approach," Energies, MDPI, vol. 11(12), pages 1-21, November.
    4. Yulong Ying & Yunpeng Cao & Shuying Li & Jingchao Li, 2015. "Nonlinear Steady-State Model Based Gas Turbine Health Status Estimation Approach with Improved Particle Swarm Optimization Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-12, June.
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