Data Driven Comprehensive Performance Evaluation of Aeroengines: A Network Dynamic Approach

Abstract

Aeroengines, often regarded as the heart of aircraft, are crucial for flight safety and performance. Comprehensive performance evaluation of aeroengines supports Prognostics and Health Management (PHM) and aeroengine digital engineering. Due to their highly integrated nature, aeroengines present challenges in performance evaluation because their test-run data are high-dimensional, large-scale, and exhibit strong nonlinear correlations among test indicators. To solve this problem, this study proposes a unified framework of the comprehensive performance evaluation of aeroengines to assess performance objectively and globally. Specifically, the network model and the dynamics model of aeroengine performance are constructed driven by test-run data, which can explain the patterns of system state changes and the internal relationship, and depict the system accurately. Based on that, three perturbations in the model are used to simulate three fault modes of aeroengines. Moreover, the comprehensive performance evaluation indexes of aeroengines are proposed to evaluate the performance dynamically from two dimensions, the coupling performance and the activity performance. Thirteen test-run qualified and four test-run failed aeroengines are used to validate and establish the qualified ranges. The results demonstrate that the comprehensive evaluation indexes can distinguish test-run qualified and test-run failed aeroengines. By changing the dynamic parameters, the comprehensive performance under any thrust and inlet guide vanes (IGV) angle can be estimated, broadening the test-run scenarios beyond a few typical states. This novel approach offers significant advancements for the comprehensive performance evaluation and management of aeroengines, paving the way for future PHM and aeroengine digital engineering developments.