摘要：

航空發(fā)動機匯集各領(lǐng)域高精尖技術(shù)，是國家科技、工業(yè)和國防實力的綜合體現(xiàn)。復(fù)雜結(jié)構(gòu)與惡劣服役環(huán)境致使其故障頻發(fā)，發(fā)動機故障診斷與健康管理技術(shù)成為保障其安全、可靠運行的重要支撐。由于振動類故障是航空發(fā)動機的主要故障模式，本文從整機振動監(jiān)測與故障診斷的系統(tǒng)研制與應(yīng)用、理論研究現(xiàn)狀及發(fā)展方向3個方面，對國內(nèi)外現(xiàn)有航空發(fā)動機振動類故障診斷技術(shù)進行梳理、剖析，具體包括動力學(xué)分析、信號處理及深度學(xué)習(xí)等相關(guān)技術(shù)，分析航空發(fā)動機振動類故障診斷面臨的問題與挑戰(zhàn)，并歸納未來發(fā)展趨勢。

關(guān)鍵詞: 航空發(fā)動機, 故障診斷, 振動分析, 動力學(xué)模型, 信號處理, 智能診斷

Abstract:

Aeroengine amalgamates state-of-the-art technologies across diverse domains， serving as a comprehensive manifestation of a nation’s prowess in science and industry. Frequent malfunctions occur due to its complicated structure and harsh service environment. Therefore， it is essential to employ prognostic and health management technology to provide crucial support for aviation safety and reliable operations. As vibration faults constitute a primary failure mode in aeroengine， this paper， grounded in this premise， systematically reviews and analyzes existing vibration monitoring and fault diagnosis for aviation engines both domestically and internationally. The analysis is categorized into three dimensions， covering the application of overall vibration monitoring and diagnostic systems， typical fault characteristics and diagnostic methods， and the overall vibration fault diagnostic technology， including dynamic analysis， signal processing techniques， and relevant technologies such as deep learning. Then， the problems and challenges faced by the existing vibration fault diagnosis of aeroengine are identified. Furthermore， future development goals are provided.

Key words: aeroengine, fault diagnosis, vibration analysis, dynamical model, signal processing, intelligent diagnosis

中圖分類號: 

V263.6

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