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用于航空发动机齿轮故障监测的自驱动振动传感器

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目前传统振动监测手段受限于航空发动机高温环境影响,导致振动传感器探测精度难以进一步提升.鉴于此,本文设计了一种基于摩擦电效应和压电效应的自驱动振动传感器,通过对敏感层材料配比的合理选择,实现电学输出性能与高温输出稳定性的兼顾.在最佳振动条件下,摩擦电器件的输出可达5.1V和0.42 μA,而压电器件输出可达1.8V和0.3 μA.基于自驱动传感器优异的电学输出性能,在机器学习算法的帮助下,开发的自驱动振动传感器可对齿轮的点蚀故障以及断齿故障进行精准识别,其识别准确率高达98.2%.实验证明本文开发的自驱动振动传感器能够有效监测航空发动机齿轮的运行状态,为航空发动机智能化健康管理提供了重要的参考价值.
Self-driven vibration sensor for monitoring gear faults in aircraft engine
However,traditional vibration monitoring methods are constrained by the high-temperature environment of aircraft engines,which results in difficulty of enhancement of vibration sensor detection precision. So,a selfpowered vibration sensor based on triboelectric and piezoelectric effects is proposesd. By selecting an optimal ratio of sensitive layer materials,a balance between electrical output performance and stability in high-temperature output is achieved. Under optimal vibration conditions,output of triboelectric device 5. 1 V and 0. 42 μA,whereas piezoelectric device is 1. 8 V and 0. 3 μA. Based on the superior electrical output of property self-powered sensor and with the help of machine learning algorithms,the developed sensor can accurately identify gear faults such as pitting and tooth breakage,achieving an accuracy of up to 98. 2％ . Experimental results demonstrate that the developed self-powered vibration sensor can effectively monitor the operational status of aircraft gears,offering critical reference value for intelligent engine health management of aircraft engine.

aircraft enginegear fault monitoringvibration sensortriboelectric nanogenerator

郭瑞、王晓畔、张继鹏、赵瑞豪、张阳、崔楠

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太原科技大学机械工程学院,山西太原 030024

中国船舶集团汾西重工有限责任公司,山西太原 030024

华信咨询设计研究院有限公司,浙江杭州 310052

航空发动机 齿轮故障监测 振动传感器 摩擦电纳米发电机

国家自然科学基金面上项目山西省基础研究计划项目山西省基础研究计划项目山西省回国留学人员科研资助项目山西省优秀来晋博士科研资助项目太原科技大学科研启动基金资助项目

523753662023030212221772022030212221932023-1502023205620222079

2024

10.13873/J.1000-9787(2024)10-0075-04

传感器与微系统
中国电子科技集团公司第四十九研究所

传感器与微系统

CSTPCD北大核心
影响因子：0.61
ISSN：1000-9787
年,卷(期)：2024.43(10)