改进小波阈值-形态学融合算法在振动信号误差抑制中的应用

车守全; 何林; 包从望; 江伟

doi:10.13433/j.cnki.1003-8728.20200131

改进小波阈值-形态学融合算法在振动信号误差抑制中的应用

doi: 10.13433/j.cnki.1003-8728.20200131

六盘水师范学院矿业与土木工程学院, 贵州六盘水 553000

基金项目:

贵州省矿山装备数字化技术工程研究中心黔教合KY字[2017]026号

六盘水市科研创新平台和人才团队建设 52020-2019-5-12

详细信息

作者简介:
车守全(1992-), 讲师, 硕士, 研究方向为装备故障诊断及机器学习, chesq_njtu@163.com

中图分类号: TH-39;TP39
计量
- 文章访问数: 99
- HTML全文浏览量: 48
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2020-03-20
- 刊出日期: 2021-06-01

Application of Improved Wavelet Threshold and Morphological Integrated Algorithm in Vibration Signal Error Suppression

School of Mines and Civil Engineering, Liupanshui Normal University, Liupanshui 553000, Guizhou, China

摘要

摘要: 针对机械装备振动信号采集中含有脉冲噪声及高斯噪声等多种复杂污染源的信号误差抑制去噪, 设计了小波阈值和形态学融合算法。首先, 在高斯平滑思想上引入改进的小波阈值函数, 能够调节阈值函数向小波分解系数真值的收敛趋势达到有效去除高斯噪声及避免稳态偏差的目的, 对比几种常用的函数算法, 提出的阈值函数取得了在信噪比提升及均方根误差抑制度量上的更优的效果。其次, 对比计算了多种形态学算子选择较优的算法用于去除脉冲噪声。最后, 将融合算法应用在机械臂振动信号的去噪实验中。结果表明, 算法能够有效去除噪声并保留信号特征。
- 振动信号 /
- 噪声 /
- 小波阈值 /
- 形态学 /
- 融合算法
Abstract: In this paper, an integrated algorithm combining wavelet threshold denoising method with morphological denoising method was designed to suppress the signal error and denoise the complex pollution sources including impulse noise and Gaussian noise in the vibration signal of mechanical equipment. Firstly, the improved wavelet threshold function was introduced based Gaussian smoothing method, which could adjust the convergence trend of the threshold function to the true value of the wavelet transforms coefficient to effectively remove the Gaussian noise and avoid the steady-state deviation, the threshold function proposed had a better effect on the measurement of SNR and RMSE compared with several commonly used algorithms. Secondly, the best algorithm was selected from several morphological operators for pulse noise removal. Finally, the integrated algorithm was applied to the denoising experiment of the vibration signal of the manipulator. The results showed that the algorithm could effectively remove the noise and retain the signal characteristics.
- vibration /
- noise /
- wavelet transforms /
- morphological /
- integrated algorithm

HTML全文

图 1 改进阈值函数

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图 2 Bumps原信号及染噪信号

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图 3 阈值函数去噪仿真对比

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图 4 原始信号及染噪信号

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图 5 形态学算子去噪对比

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图 6 信号采集平台

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图 7 振动信号

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图 8 不同算法噪声抑制结果

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图 9 振动频率结果

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表 1 信噪比18 dB的Bumps信号去噪结果

指标	SNR	RMSE
硬阈值函数	29.2	0.25
软阈值函数	34.3	0.19
文献[12]阈值函数	33.1	0.19
文献[13]阈值函数	34.4	0.18
文献[14]阈值函数	33.1	0.21
本文阈值函数	35.1	0.14

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表 2 信噪比18 dB的Heavy sine信号去噪结果

指标	SNR	RMSE
硬阈值函数	30.1	0.24
软阈值函数	33.8	0.14
文献[12]阈值函数	33.4	0.15
文献[13]阈值函数	33.5	0.14
文献[14]阈值函数	32.6	0.17
本文阈值函数	34.5	0.13

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参考文献(16)

[1]	蔡艳平, 徐光华, 张恒, 等. 基于内燃机振动信号的可视化识别诊断[J]. 振动与冲击, 2019, 38(24): 150-157 https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ201924021.htm CAI Y P, XU G H, ZHANG H, et al. Visual identification and diagnosis based on IC engine vibration signals[J]. Journal of Vibration and Shock, 2019, 38(24): 150-157 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ201924021.htm
[2]	王金东, 卜庆超, 赵海洋, 等. 最优品质因子信号共振稀疏分解的往复压缩机故障诊断[J]. 机械强度, 2019, 41(3): 557-561 https://www.cnki.com.cn/Article/CJFDTOTAL-JXQD201903009.htm WANG J D, BU Q C, ZHAO H Y, et al. Fault diagnosis of reciprocating compressor on the resonance-based sparse signal decomposition with optimal Q-factor[J]. Journal of Mechanical Strength, 2019, 41(3): 557-561 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXQD201903009.htm
[3]	ATTOUI I, OUDJANI B, BOUTASSETA N, et al. Novel predictive features using a wrapper model for rolling bearing fault diagnosis based on vibration signal analysis[J]. The International Journal of Advanced Manufacturing Technology, 2020, 106(7): 3409-3435 doi: 10.1007%2Fs00170-019-04729-4
[4]	XU X B, LUO M Z, TAN Z Y, et al. Echo signal extraction method of laser radar based on improved singular value decomposition and wavelet threshold denoising[J]. Infrared Physics & Technology, 2018, 92: 327-335 http://www.sciencedirect.com/science/article/pii/S1350449518303141
[5]	BONDA A G Y, NANDA B K, JONNALAGADDA S. Vibration signature based stability studies in internal turning with a wavelet denoising preprocessor[J]. Measurement, 2020, 154: 107520 doi: 10.1016/j.measurement.2020.107520
[6]	VIKHE P S, THOOL V R. A wavelet and adaptive threshold-based contrast enhancement of masses in mammograms for visual screening[J]. International Journal of Biomedical Engineering and Technology, 2019, 30(1): 31-53 doi: 10.1504/IJBET.2019.100274
[7]	童何俊, 付冬梅. 基于免疫遗传形态学的视网膜光学相干断层图像边缘检测方法[J]. 工程科学学报, 2019, 41(4): 539-545 https://www.cnki.com.cn/Article/CJFDTOTAL-BJKD201904015.htm TONG H J, FU D M. Edge detection method of retinal optical coherence tomography images based on immune genetic morphology[J]. Chinese Journal of Engineering, 2019, 41(4): 539-545 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-BJKD201904015.htm
[8]	郭贝贝, 齐山成, 赵斌. 融合小波和形态学的避雷器在线监测方法研究[J]. 电瓷避雷器, 2019(6): 43-48, 54 https://www.cnki.com.cn/Article/CJFDTOTAL-DCPQ201906008.htm GUO B B, QI S C, ZHAO B. Research on the on-line monitoring method of Surge arrester based on wavelet and morphology[J]. Insulators and Surge Arresters, 2019(6): 43-48, 54 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DCPQ201906008.htm
[9]	罗远林, 李朝晖, 程时杰, 等. 结合数学形态学滤波与频谱校正的发电机局部放电离散谱干扰抑制方法[J]. 中国电机工程学报, 2019, 39(21): 6403-6411 https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC201921024.htm LUO Y L, LI Z H, CHENG S J, et al. A method for suppression discrete spectrum interference in partial discharge of generators combining mathematical morphology filter and spectrum correction[J]. Proceedings of the CSEE, 2019, 39(21): 6403-6411 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC201921024.htm
[10]	张景元, 何玉珠. 基于形态学的自动驾驶仪振动信号基线漂移去噪[J]. 北京航空航天大学学报, 2018, 44(5): 907-913 https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK201805002.htm ZHANG J Y, HE Y Z. Removing baseline drift in vibration signal of autopilot based on morphology[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(5): 907-913 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK201805002.htm
[11]	罗远林. 水轮发电机局部放电信号传播特性与去噪方法研究[D]. 武汉: 华中科技大学, 2019 LUO Y L. Research of propagation characteristics and denoising of partial discharge of signal for hydro generator[D]. Wuhan: Huazhong University of Science & Technology, 2019 (in Chinese)
[12]	吕楠楠, 苏淑靖, 翟成瑞. 改进小波包阈值算法在振动信号去噪中的应用[J]. 探测与控制学报, 2018, 40(1): 119-124 https://www.cnki.com.cn/Article/CJFDTOTAL-XDYX201801025.htm LV N N, SU S J, ZHAI C R. Application of improved wavelet packet threshold algorithm in vibration signal denoising[J]. Journal of Detection & Control, 2018, 40(1): 119-124 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XDYX201801025.htm
[13]	于沛, 闫禄, 张金云, 等. 振动条件下陀螺加速度计误差抑制技术[J]. 噪声与振动控制, 2019, 39(2): 37-41 https://www.cnki.com.cn/Article/CJFDTOTAL-ZSZK201902008.htm YU P, YAN L, ZHANG J Y, et al. Research on error suppression technology of PIGA under vibration condition[J]. Noise and Vibration Control, 2019, 39(2): 37-41 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZSZK201902008.htm
[14]	周建, 向北平, 倪磊, 等. 一种新的小波阈值去噪算法研究[J]. 机械设计与研究, 2017, 33(6): 1-5 https://www.cnki.com.cn/Article/CJFDTOTAL-JSYY201706006.htm ZHOU J, XIANG B P, NI L, et al. Study of a new de-noising algorithm based on wavelet threshold[J]. Machine Design & Research, 2017, 33(6): 1-5 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSYY201706006.htm
[15]	WEI N, YANG J H, LIU R X. Denoising for variable density ESPI fringes in nondestructive testing by an adaptive multiscale morphological filter based on local mean[J]. Applied Optics, 2019, 58(28): 7749-7759 http://www.ncbi.nlm.nih.gov/pubmed/31674457
[16]	黄刚劲, 范玉刚, 冯早, 等. 基于广义形态滤波和MRSVD的故障诊断方法研究[J]. 计算机工程与应用, 2018, 54(3): 217-221 https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201803034.htm HUANG G J, FAN Y G, FENG Z, et al. Research on fault diagnosis method based on generalized morphological filter and MRSVD[J]. Computer Engineering and Applications, 2018, 54(3): 217-221 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201803034.htm