基于改进小波阈值函数的安全阀排放声信号降噪

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摘要在安全阀测试中，安全阀排放声信号是检验阀门是否合格的重要信息来源。鉴于安全阀排放声信号易受到周边机械系统噪声的干扰，影响测试的准确性，利用指数型函数的衰减特性，提出一种改进的自适应小波阈值降噪方法。在不同尺度上根据小波分解的噪声水平自适应的选取最佳阈值；构建一种在阈值处连续的阈值函数，引入调节因子，优化了传统阈值函数过度降噪、不连续等缺陷。采用该方法分别对仿真信号与安全阀实测信号进行降噪分析，并与传统小波阈值降噪、低通Butterworth滤波降噪进行对比。结果表明该方法降噪效果更好，验证了改进降噪方法的有效性。

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	李树勋1
	2
	王志辉1
	2
	康云星1
	2
	侯建军1
	2

关键词 ：小波降噪, 阈值函数, 分层阈值, 安全阀, 噪声测试系统

Abstract：:In a safety valve test, the discharge acoustic signal of the safety valve is an important source of information to check whether the valve is qualified.In view of the fact that the discharge sound signal of the safety valve is easily interfered by the noise of the surrounding mechanical system, which affects the accuracy of the test, an improved adaptive wavelet threshold noise reduction method was proposed using the attenuation characteristics of the exponential function.Firstly, the optimal threshold was selected adaptively at different scales according to the noise level of wavelet decomposition; then a threshold function was constructed that is continuous at the threshold, and adjustment factors were introduced to optimize the traditional threshold function for excessive noise reduction and discontinuity.This method was used to analyze the noise reduction of a simulated signal and the measured signal of the safety valve, and compare it with the traditional wavelet threshold noise reduction and low-pass Butterworth filter noise reduction.The results show that the noise reduction effect of this method is better, and the effectiveness of the improved noise reduction method was verified.

Key words： wavelet noise reduction threshold function layered threshold safety valve noise test system

收稿日期: 2020-06-08 出版日期: 2021-06-28

引用本文:

李树勋1,2，王志辉1,2，康云星1,2，侯建军1,2. 基于改进小波阈值函数的安全阀排放声信号降噪[J]. 振动与冲击, 2021, 40(12): 143-150.
LI Shuxun1,2,WANG Zhihui1,2,KANG Yunxing1,2,HOU Jianjun1,2. Noise reduction of a safety valve pressure relief signal based on an improved wavelet threshold function. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(12): 143-150.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2021/V40/I12/143

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