| 王占利,傅骁,梁春疆,段发阶,蒋佳佳,李存军,陈贤雷,郝华东.基于连续小波变换与曲线拟合的油液金属屑末传感信号检测方法*[J].电子测量与仪器学报,2021,35(11):32-38 |
| 基于连续小波变换与曲线拟合的油液金属屑末传感信号检测方法* |
| Detecting method of oil debris sensor signal based on continuous wavelet transform and curve fitting |
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| DOI： |
| 中文关键词: 连续小波变换 曲线拟合 干扰信号 信号检测 |
| 英文关键词:continuous wavelet transform curve fitting interference signal signal detection |
| 基金项目:国家重点研发计划(2020YFB2010800)、国家自然科学基金（61905175,51775377,61971307)、国家科技重大专项(2017-V-0009)、霍英东教育基金会(171055)、中国博士后科学基金(2020M680878)、广东省重点研发计划(2020B0404030001)、天津市科技计划(20YDTPJC01660)、中国航发四川燃气涡轮研究院外委课题(GJCZ-2020-0040, GJCZ-2020-0041)项目资助 |
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| Author | Institution |
| Wang Zhanli | State Key Lab of Precision Measuring Technology&Instruments, Tianjin University, Tianjin 300072, |
| Fu Xiao | State Key Lab of Precision Measuring Technology&Instruments, Tianjin University, Tianjin 300072, |
| Liang Chunjiang | Smartmens (Tianjin) Technology Co, Ltd, Tianjin 300380, China |
| Duan Fajie | State Key Lab of Precision Measuring Technology&Instruments, Tianjin University, Tianjin 300072, |
| Jiang Jiajia | State Key Lab of Precision Measuring Technology&Instruments, Tianjin University, Tianjin 300072, |
| Li Cunjun | Zhoushan Institute of Calibration and Testing for Quality and Technology Supervision, Zhoushan 316000,China |
| Chen Xianlei | Zhoushan Institute of Calibration and Testing for Quality and Technology Supervision, Zhoushan 316000,China |
| Hao Huadong | Zhoushan Institute of Calibration and Testing for Quality and Technology Supervision, Zhoushan 316000,China |
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| 中文摘要: |
| 三线圈式电感型传感器是润滑油金属屑末监测的主流传感器,但润滑油中的气泡会使该型传感器产生干扰信号。针对传统的双阈值法存在将气泡干扰信号误检为是金属屑末信号的问题,提出了基于连续小波变换与曲线拟合的信号检测方法。利用金属屑末信号波形与Gaussian1小波相似性高的特点,使用Gaussian1小波对预处理后信号进行连续小波变换(CWT)，在小波域使用阈值法过滤干扰信号并对信号波形进行提取,使用高斯牛顿法对提取出的信号波形进行曲线拟合,使用可决系数作为标准对拟合结果进行判断,检测金属屑末信号,去除干扰信号。在内径20 mm传感器上实际测试表明,方法可以准确检测直径150 μm以上的球形铁屑末与直径250 μm以上的球形铜屑末,准确率分别达到了99%与97%,并可有效去除气泡干扰信号。 |
| 英文摘要: |
| The triple coil inductive debris sensor is the main sensor for the monitoring of metal debris in lubricating oil. But the bubble in the lubricating oil will make the sensor produce interference signal. Aiming at the problem that the traditional method mistakenly detects the bubble interference signal as the metal debris signal, a signal detection method based on continuous wavelet transform and curve fitting is proposed. Taking advantage of the high similarity between the metal debris signal and Gaussian1 wavelet, the continuous wavelet transform (CWT) threshold method is used in wavelet domain to filter interference signal and extract signal waveform, the Gauss Newton method is used to fit the extracted signal waveform, and the R squared is used as the standard to judge the fitting results, detect the metal debris signal and remove the interference signal. The actual test on the sensor with an inner diameter of 20 mm shows that it can accurately detect the spherical ferromagnetic debris with a diameter of more than 150 μm and the spherical copper debris with a diameter of more than 250 μm, with an accuracy of 99% and 97% respectively, and can effectively remove the bubble interference signal. |
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