Abstract
Aero-engines are faced with severe challenges of availability and reliability in the increasing operation, and traditional gas path filtering diagnostic methods have limitations restricted by various factors such as strong nonlinearity of the system and lack of critical sensor information. A method based on the aerothermodynamic inverse model (AIM) is proposed to improve the adaptation accuracy and fault diagnostic dynamic estimation response speed in this paper. Thermodynamic mechanisms are utilized to develop AIM, and scaling factors are designed to be calculated iteratively in the presence of measurement correction. In addition, the proposed method is implemented in combination with compensation of the nonlinear filter for real-time estimation of health parameters under the hypothesis of estimated dimensionality reduction. Simulations involved experimental datasets revealed that the maximum average simulated error decreased from 13.73% to 0.46% through adaptation. It was also shown that the dynamic estimated convergence time of the improved diagnostic method reached 2.183 s decrease averagely without divergence compared to the traditional diagnostic method. This paper demonstrates the proposed method has the capacity to generalize aero-engine adaptation approaches and to achieve unbiased estimation with fast convergence in performance diagnostic techniques.
Highlights
Received: 30 November 2021Aero-engine is an aerothermodynamic system with a complicated structure and strong nonlinearity
Aero-engine gas path fault diagnosis can be divided into three categories: modelbased approach, data-driven approach, and information fusion approach [3], wherein model-based diagnostic method is a practical tool with respect to on-board implementation considerations and low model complexity
The main contribution of this paper proposes a novel method with the capacity to refine model adaptation and performance diagnosis, and it is integrated into a thermodynamic model of turbofan engine in the development stage
Summary
Aero-engine is an aerothermodynamic system with a complicated structure and strong nonlinearity. These primary problems are the core elements generating high misdiagnosis incidences To address this dilemma, the main contribution of this paper proposes a novel method with the capacity to refine model adaptation and performance diagnosis, and it is integrated into a thermodynamic model of turbofan engine in the development stage. This paper is organized as follows: Section 2 introduces the establishment of component AIMs to calculate scaling factors considering measurement correction for model adaptation; Section 3 gives an introduction of computation of health parameters with the compensation of EKF; a set of simulation cases are conducted in Section 4 to test the quality of the proposed performance adaptation and diagnostic method, and Section 5 presents a summary of the research
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