电子测量与仪器学报

李海青,刘伟,冯松,王龙飞,甘欣凌.感应式磨粒检测传感器信号特征提取方法研究[J].电子测量与仪器学报,2022,36(12):1-9

感应式磨粒检测传感器信号特征提取方法研究

Research on signal feature extraction for inductive debris detection sensor

DOI：

英文关键词:feature extraction debris detection variance numeric characteristic

基金项目:国家自然科学基金（51705057）、重庆市自然科学基金（cstc2020jcyj msxmX0915）项目资助

作者	单位
李海青	1. 重庆邮电大学先进制造工程学院
刘伟	2. 重庆大学机械与运载工程学院
冯松	1. 重庆邮电大学先进制造工程学院
王龙飞	1. 重庆邮电大学先进制造工程学院
甘欣凌	1. 重庆邮电大学先进制造工程学院

Author	Institution
Li Haiqing	1. Advanced Manufacturing Engineering School, Chongqing University of Posts and Telecommunications
Liu Wei	2. College of Mechanical and Vehicle Engineering, Chongqing University
Feng Song	1. Advanced Manufacturing Engineering School, Chongqing University of Posts and Telecommunications
Wang Longfei	1. Advanced Manufacturing Engineering School, Chongqing University of Posts and Telecommunications
Gan Xinling	1. Advanced Manufacturing Engineering School, Chongqing University of Posts and Telecommunications

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中文摘要:

针对感应式磨粒检测传感器信号输出易受噪声干扰而导致微小磨粒难以提取的问题,提出了一种基于方差稳定性的磨粒信号降噪及特征信息提取新方法。首先,利用预处理信号中不同信息成分的差异性进行方差稳定性度量;然后,依据归一化方差稳定度的统计特征实现自适应阈值提取,并在此基础上对预处理信号进行阈值分割;最后,利用目标信号特征判定指标对磨粒感应电压进行识别与计数。实验结果表明,算法能够成功提取出 50 μm(球体等效直径)磨粒产生的感应电压信号,与传统分解类降噪算法相比,所提的新方法能够有效剔除检测信号中的背景噪声,其保护磨粒信号形态特征的优势可以进一步提高传感器在强干扰环境下的微小磨粒检测能力。

英文摘要:

Aiming at the problem of tough extraction about tiny wear particle in the signal output on the inductive debris detection sensor caused by the interference of noise, a new method of noise reduction and extraction of characteristic information to the oil debris signal based on variance stability is proposed in this paper. Making use of the discrepancy in the pre-processed signal about various components, the variance stability has been measured in the first stage. Then, the adaptive threshold is extracted according to the statistical features of normalized variance stability, and the pre-processed signal is segmented by the threshold on this basis. Finally utilizing the characteristic identification index of target signal to further realize the recognition and counting of all debris induced voltage signals. Experiment show that the proposed algorithm can successfully extract the induced voltage signal generated by the tiny debris with the equivalent diameter of 50 μm. Compared with the traditional noise reduction algorithm based on the decomposition principle, the new method proposed in this paper can effectively eliminate the background noise in the detection signal, and its advantages of protecting the morphological characteristics of debris signal can ulteriorly improve the detection ability of small wear particle in the intense interference environment.

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