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随着空间科学技术的不断发展,人们进行的空间活动日益增多。与此同时,空间碎片的数量也随之急剧增多,这使得在轨航天器遭受空间碎片等动能颗粒撞击可能性不断增加,航天器发生密封结构泄漏的可能性越来越大。航天器泄漏不仅会造成航天活动的失败,更会威胁航天员的生命安全,因此,在轨航天器真空泄漏声发射在线检测技术研究具有十分重要的意义。本文以声发射技术为基础,利用精细平均功率谱分析法对不同泄漏孔径下产生的声发射信号特征进行提取分析,并与改进的混沌-BP神经网络模式识方法相结合实现对信号进行分类,从而实现泄漏检测以及漏孔大小评估。通过真空泄漏声发射检测实验验证,本方法最小可检0.4 mm直径的漏孔,满足在轨航天器微弱泄漏检测的需求。
With the continuous development of space science and technology, the space activities carried out by people are increasing day by day. At the same time, the number of space debris also increases sharply, which increases the possibility of in-orbit spacecraft colliding with kinetic energy particles such as space debris and increasing the possibility of leakage of sealing structures in spacecraft. The spacecraft leakage will not only cause the failure of space activities, but also threaten the life safety of astronauts. Therefore, it is of great significance to study the on-line detection of acoustic emission of on-orbit spacecraft vacuum leaks. Based on the acoustic emission technique, the characteristics of acoustic emission signals generated by different leakage apertures were extracted and analyzed by using the method of precise average power spectrum analysis. Combined with the improved chaos-BP neural network pattern recognition method, the signals were classified, Leak detection and hole size assessment are thus achieved. Through the experiment of vacuum leak acoustic emission testing, the method can detect 0.4 mm diameter leak holes to meet the requirement of weak leak detection on orbit spacecraft.