An Adaptive Noise Reduction Method for High Temperature and Low Voltage Electromagnetic Detection Signals Based on SVMD Combined with ICEEMDAN DOI Creative Commons

Zhizeng Ge,

Jinjie Zhou, Xingquan Shen

et al.

Micromachines, Journal Year: 2024, Volume and Issue: 15(8), P. 977 - 977

Published: July 30, 2024

In view of the low signal-to-noise ratio (SNR) shear wave electromagnetic acoustic transducers (EMAT) in detection high-temperature equipment, use excitation voltage (LEV) further deteriorates results, resulting echo signal containing defects being drowned noise. For extraction EMAT signal, an adaptive noise reduction method is proposed. Firstly, minimum envelope entropy taken as fitness function for Harris Hawks Optimizer (HHO), and optimal successive variational mode decomposition (SVMD) balance parameter searched by HHO iteration to decompose LEV signals at high temperatures. Then filter carried out according center frequency correlation coefficient threshold function. Then, improved complete ensemble empirical with (ICEEMDAN) used filtered combine kurtosis factor select appropriate intrinsic functions. Finally, extracted Hilbert transform. order verify effectiveness method, it applied low-voltage 40Cr from 25 °C 700 °C. The results show that not only suppresses background clutter but also significantly improves SNR signals, most importantly, able detect extract 2 mm small signals. It has great application prospects value equipment.

Language: Английский

Vibration trend forecasting of motorized spindle on the basis of signal processing and deep learning DOI
Ye Dai, Xiao Liu, Jian Pang

et al.

Nonlinear Dynamics, Journal Year: 2025, Volume and Issue: unknown

Published: April 2, 2025

Language: Английский

Citations

0
Research on rolling bearing fault diagnosis technology based on singular value decomposition DOI Creative Commons
Jingfang Ji,

Jingmin Ge

AIP Advances, Journal Year: 2024, Volume and Issue: 14(8)

Published: Aug. 1, 2024

To solve the difficulty of selecting number effective singular values in Singular Value Decomposition denoising, a new method to determine is proposed. The proposed based on non-zero value distribution law Hankel matrix constructed by signal. Specifically, twice frequencies contained signal, and difference between noisy signal pure very small. for determining perform differential processing normalize obtained. An empirical parameter T provided, determined comparing them with normalized results. applied simulated measured rolling bearing signals, results are compared wavelet threshold denoising method. show that can effectively filter out noise frequency while maintaining characteristic achieving purpose mechanical equipment fault diagnosis.

Language: Английский

Citations

2
An Adaptive Noise Reduction Method for High Temperature and Low Voltage Electromagnetic Detection Signals Based on SVMD Combined with ICEEMDAN DOI Creative Commons

Zhizeng Ge,

Jinjie Zhou, Xingquan Shen

et al.

Micromachines, Journal Year: 2024, Volume and Issue: 15(8), P. 977 - 977

Published: July 30, 2024

In view of the low signal-to-noise ratio (SNR) shear wave electromagnetic acoustic transducers (EMAT) in detection high-temperature equipment, use excitation voltage (LEV) further deteriorates results, resulting echo signal containing defects being drowned noise. For extraction EMAT signal, an adaptive noise reduction method is proposed. Firstly, minimum envelope entropy taken as fitness function for Harris Hawks Optimizer (HHO), and optimal successive variational mode decomposition (SVMD) balance parameter searched by HHO iteration to decompose LEV signals at high temperatures. Then filter carried out according center frequency correlation coefficient threshold function. Then, improved complete ensemble empirical with (ICEEMDAN) used filtered combine kurtosis factor select appropriate intrinsic functions. Finally, extracted Hilbert transform. order verify effectiveness method, it applied low-voltage 40Cr from 25 °C 700 °C. The results show that not only suppresses background clutter but also significantly improves SNR signals, most importantly, able detect extract 2 mm small signals. It has great application prospects value equipment.

Language: Английский

Citations

0