基于梳状式电容传感器的滑油磨粒检测方法
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TP212 TH73

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国家自然科学基金(U2033209)项目资助


Detection method of lube wear particle based on comb type capacitance sensor
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    摘要:

    航空发动机旋转部件的磨损是影响其寿命的重要因素,而滑油内磨粒的参数能直接反映部件的磨损状态,磨粒监测已 是发动机智能诊断的关键技术。 提出一种梳状式电容传感器,采用内置多平行板电极结构,分析磨粒检测机理,通过数值模拟 分析结构优化方向,确定最佳参数。 搭建实验平台进行试验,结果表明,当铁磨粒直径从 0. 3 mm 增至 0. 9 mm 时,电容差值从 3 Ff 增至 17 Ff;当磨粒个数从 1 增至 4 时,差值与数量近似成正线性关系,最大增幅在 200% ~ 350% 左右;电源频率从 10 kHz 增 至 100 kHz 时,差值降幅在 36% ~ 67% 。 研究表明梳状电容传感器内部电场均匀度较好,利于提高结果一致性与磨粒检出率,可 在 10 mm 管路中检测 200 μm 以上的磨粒,具有较好的区分度,可为航空发动机滑油磨粒监测研究提供技术支持。

    Abstract:

    The wear particle monitoring technology has become a key part of the intelligent diagnosis of aero-engine, because the wear of rotating parts of aero-engine is an important factor that affects the lifespan of aero-engine. The parameters of the wear particle in the lubricating oil can directly reflect the wear state of rotating parts. In this article, a comb type capacitance sensor is proposed, which uses the structure of built-in multi-parallel plate electrodes. On the basis of analyzing the wear particle detection principle of the sensor, we determine the structural optimization direction and the optimal parameter through numerical simulation. Experimental results show that when the diameter of iron wear particles increases from 0. 3 mm to 0. 9 mm, the variation in capacitance increases from 3 Ff to 17 Ff. When the number of wear particles increases from 1 to 4, the variation in capacitance is approximately in a positive linear relationship with the particle number, and the maximum increase ratio is about 200% to 350% . When the power frequency increases from 10 kHz to 100 kHz, the drop ratio of variation in capacitance is 36% to 67% . The results show that the comb type capacitive sensor can improve the uniformity of the internal electric field, which could improve the consistency of the results and the detection rate of wear particles, and detect 200 μm diameter particles in 10 mm diameter pipe which shows a good discrimination in outcome. This technology can provide technical support for the monitoring research of aero-engine oil wear particles.

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贾宝惠,丁梓航,肖海建,耿亚南.基于梳状式电容传感器的滑油磨粒检测方法[J].仪器仪表学报,2022,43(12):49-57

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  • 在线发布日期: 2023-07-04
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