Application of Improved Wavelet Threshold De-noising Method in the High-performed Dynamic Centrifuge-Vibration Composite System

JIANG Chenwei; YAN Xia; MAO Yongjian

doi:10.7643/ issn.1672-9242.2024.06.016

PDF(3322 KB)

Equipment Environmental Engineering ›› 2024, Vol. 21 ›› Issue (6) : 119-126. DOI: 10.7643/ issn.1672-9242.2024.06.016

Application of Improved Wavelet Threshold De-noising Method in the High-performed Dynamic Centrifuge-Vibration Composite System

JIANG Chenwei, YAN Xia^*, MAO Yongjian

Author information +

History +

Abstract

In order to solve the problem that the control signal in the vibration-high dynamic centrifugal composite test control system is disturbed by noise, leading to poor control effect, the work aims to carry out noise reduction to improve the test control ability. The improved wavelet threshold de-noising method was used to de-noise the control signal in the vibration-high dynamic centrifugal composite test control system. By analyzing the signal characteristics and combining the principle of wavelet threshold de-noising method, an improved method of threshold criterion changing adaptively with decomposition scale was proposed. The comparative analysis of the improved method and other wavelet threshold noise reduction methods showed that the proposed method could significantly suppress the medium and high frequency noise interference in the vibration-high dynamic centrifugal system, effectively retain the characteristics of the control signal, and obtain a better comprehensive noise reduction effect. The signal-to-noise ratio was improved by nearly 10 dB, which met the noise reduction requirements of the test control. The wavelet threshold de-noising method based on adaptive dynamic threshold criterion is effective and reliable for de-noising the control signal of vibration-high dynamic centrifugal composite test system, which can provide a feasible idea for the research direction of related test technology in the following.

Key words

high dynamic / vibration-centrifugal composite control system / noise / wavelet threshold de-noising method / threshold criterion / dynamic change

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

JIANG Chenwei, YAN Xia, MAO Yongjian. Application of Improved Wavelet Threshold De-noising Method in the High-performed Dynamic Centrifuge-Vibration Composite System[J]. Equipment Environmental Engineering. 2024, 21(6): 119-126 https://doi.org/10.7643/ issn.1672-9242.2024.06.016

References

[1] 董雪明, 王敏林. 离心-振动复合校准技术研究[J]. 计测技术, 2021, 41(4): 49-58.
DONG X M, WANG M L.Research on Centrifugal Vibration Compound Calibration Technology[J]. Metrology & Measurement Technology, 2021, 41(4): 49-58.
[2] 王遥遥. 基于小波理论的信号降噪方法的研究[D]. 武汉: 武汉理工大学, 2013.
WANG Y Y.Research on Signal Denoising Based on Wavelet Theory[D]. Wuhan: Wuhan University of Technology, 2013.
[3] BURRUS C S, GOPINATH R A, GUO H T, et al.Introduction to Wavelets and Wavelet Transforms: A Primer[M]. London: Pearson Education, 1998.
[4] 李士心, 刘鲁源. 小波域中值滤波器设计的研究[J]. 电子科技大学学报, 2003, 32(1): 18-21.
LI S X, LIU L Y.Design of Wavelet Domain Median Filter[J]. Journal of University of Electronic Science and Technology of China, 2003, 32(1): 18-21.
[5] KARIMIPOUR H, DINAVAHI V.Extended Kalman Filter-Based Parallel Dynamic State Estimation[J]. IEEE Transactions on Smart Grid, 2015, 6(3): 1539-1549.
[6] HE X K, HU C, HONG Y G, et al.Distributed Kalman Filters with State Equality Constraints: Time-Based and Event-Triggered Communications[J]. IEEE Transactions on Automatic Control, 2020, 65(1): 28-43.
[7] YOO G R, OWHADI H.De-Noising by Thresholding Operator Adapted Wavelets[J]. Statistics and Computing, 2019, 29(6): 1185-1201.
[8] 肖鑫龙, 杨洪涛, 陈贺, 等. 基于FFT-SVD算法的转子轴心轨迹提纯与故障检测[J]. 惠州学院学报, 2022, 42(6): 22-28.
XIAO X L, YANG H T, CHEN H, et al.Rotor Axis Trajectory Purification and Fault Detection Based on FFT-SVD Algorithm[J]. Journal of Huizhou University, 2022, 42(6): 22-28.
[9] ZHANG Y, DING W F, PAN Z F, et al.Improved Wavelet Threshold for Image De-Noising[J]. Frontiers in Neuroscience, 2019, 13: 39.
[10] SRIVASTAVA M, FREED J H.A New Wavelet Denoising Method for Selecting Decomposition Levels and Noise Thresholds[J]. IEEE Access: Practical Innovations, Open Solutions, 2016, 13(2): 176-183.
[11] 李树勋, 王志辉, 康云星, 等. 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 S X, WANG Z H, KANG Y X, et al.Noise Reduction of a Safety Valve Pressure Relief Signal Based on an Improved Wavelet Threshold Function[J]. Journal of Vibration and Shock, 2021, 40(12): 143-150.
[12] 曹玲玲, 李晶, 彭镇, 等. 基于改进小波阈值降噪的滚动轴承故障诊断方法[J]. 振动工程学报, 2022, 35(2): 454-463.
CAO L L, LI J, PENG Z, et al.Rolling Bearing Fault Diagnosis Method Based on Improved Wavelet Threshold Denoising[J]. Journal of Vibration Engineering, 2022, 35(2): 454-463.
[13] DONOHO D L.De-Noising by Soft-Thresholding[J]. IEEE Transactions on Information Theory, 1995, 41(3): 613-627.
[14] 余腾, 胡伍生, 吴杰, 等. 基于小波阈值去噪与EMD分解方法提取润扬大桥振动信息[J]. 振动与冲击, 2019, 38(12): 264-270.
YU T, HU W S, WU J, et al.Extraction of Runyang Bridge Vibration Information Based on a Fusion Method of Wavelet Threshold Denoising and EMD Decomposition[J]. Journal of Vibration and Shock, 2019, 38(12): 264-270.
[15] 王普, 李天垚, 高学金, 等. 分层自适应小波阈值轴承故障信号降噪方法[J]. 振动工程学报, 2019, 32(3): 548-556.
WANG P, LI T Y, GAO X J, et al.Bearing Fault Signal Denoising Method of Hierarchical Adaptive Wavelet Threshold Function[J]. Journal of Vibration Engineering, 2019, 32(3): 548-556.
[16] 王洁, 郭天翔, 卢云山, 等. 针对锋电位的启发式阈值检测算法[J]. 计算机工程与应用, 2022, 58(7): 192-196.
WANG J, GUO T X, LU Y S, et al.Heuristic Threshold Detection Algorithm for Spike[J]. Computer Engineering and Applications, 2022, 58(7): 192-196.
[17] KONG S, KONG Z.Application and Optimization of Wavelet Threshold Denoising Algorithm in Signal Processing[C]//2022 International Conference on Artificial Intelligence in Everything (AIE). Lefkosa: IEEE, 2022.
[18] 黎锁平, 周勇, 周永强. 自适应小波阈值去噪算法在低空飞行声目标的应用[J]. 振动与冲击, 2017, 36(9): 153-158.
LI S P, ZHOU Y, ZHOU Y Q.An Adaptive Wavelet Shrinkage De-Noising Algorithm for Low Altitude Flying Acoustic Targets[J]. Journal of Vibration and Shock, 2017, 36(9): 153-158.
[19] YAN R Q, GAO R X, CHEN X F.Wavelets for Fault Diagnosis of Rotary Machines: A Review with Applications[J]. Signal Processing, 2014, 96: 1-15.
[20] 周祥鑫, 王小敏, 杨扬, 等. 基于小波阈值的高速道岔振动信号降噪[J]. 振动与冲击, 2014, 33(23): 200-206.
ZHOU X X, WANG X M, YANG Y, et al.De-Noising of High-Speed Turnout Vibration Signals Based on Wavelet Threshold[J]. Journal of Vibration and Shock, 2014, 33(23): 200-206.
[21] 刘翠伟, 李玉星, 王武昌, 等. 输气管道气体流经阀门气动噪声产生机理分析[J]. 振动与冲击, 2014, 33(2): 152-157.
LIU C W, LI Y X, WANG W C, et al.Analysis on the Mechanism of Aero-Acoustic Noise Generated by Gas Flow through Valves of Natural Gas Pipelines[J]. Journal of Vibration and Shock, 2014, 33(2): 152-157.
[22] 乔志城, 刘永强, 廖英英. 改进经验小波变换与最小熵解卷积在铁路轴承故障诊断中的应用[J]. 振动与冲击, 2021, 40(2): 81-90.
QIAO Z C, LIU Y Q, LIAO Y Y.Application of Improved Wavelet Transform and Minimum Entropy Deconvolution in Railway Bearing Fault Diagnosis[J]. Journal of Vibration and Shock, 2021, 40(2): 81-90.
[23] HU H P, AO Y, YAN H C, et al.Signal Denoising Based on Wavelet Threshold Denoising and Optimized Variational Mode Decomposition[J]. Journal of Sensors, 2021, 2021: 5599096.
[24] WANG S Y, MENG D S, ZHANG K.Study on the Application of Wavelet Threshold Denoising in the Detection of Coal Spectra by LIBS[J]. Journal of Physics: Conference Series, 2022, 2396(1): 012024.
[25] XIAO H, HU D F, WANG J J.Threshold Selection of Wavelet Denoising Based on Optimization Algorithms[C]//2022 International Conference on Innovations and Development of Information Technologies and Robotics (IDITR). Chengdu: IEEE, 2022.