Aircraft engine vibration signals carry crucial operational information, necessitating accurate monitoring and analysis to ensure flight safety. However, the detection accuracy of vibration sensors is significantly compromised in high-temperature environments, posing substantial challenges for traditional battery-powered models. Here, we present a self-powered piezoelectric vibration sensor based on a polyvinylidene fluoride-polyimide nanofiber membrane, which can effectively mitigate the performance degradation in high-temperature environments. The piezoelectric vibration sensor is capable of distinguishing the vibration signals generated by healthy gears, pitting gears, and broken gears, achieving a recognition accuracy of 96.3 % by using machine-learning algorithms. Finally, we develop a digital twin system to identify failure modes in aircraft engine gears, promising intelligent engine health management.

中文翻译：

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基于压电振动传感器的飞机发动机齿轮故障监测与数字孪生示范，用于发动机健康管理


飞机发动机振动信号携带关键的运行信息，需要准确监测和分析以确保飞行安全。然而，振动传感器的检测精度在高温环境中会受到严重影响，这对传统的电池供电模型构成了巨大的挑战。在这里，我们提出了一种基于聚偏二氟乙烯-聚酰亚胺纳米纤维膜的自供电压电振动传感器，它可以有效缓解高温环境下的性能下降。压电式振动传感器能够区分健康齿轮、点蚀齿轮和破齿轮产生的振动信号，通过使用机器学习算法实现 96.3% 的识别准确率。最后，我们开发了一个数字孪生系统来识别飞机发动机齿轮的故障模式，有望实现智能发动机健康管理。