scholarly journals An Integrated Denoising Method for Sensor Mixed Noises Based on Wavelet Packet Transform and Energy-Correlation Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Chao Tan ◽  
Yanping Wang ◽  
Xin Zhou ◽  
Zhongbin Wang ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Processing Method ◽  
Signal Denoising ◽  
Current Signal ◽  
Energy Correlation ◽  
Denoising Method ◽  
Impact Noise ◽  
Key Technologies

In order to solve the problem of industrial sensor signal denoising, an integrated denoising method for sensor mixed noises based on wavelet packet transform and energy-correlation analysis is proposed. The architecture of proposed method is designed and the key technologies, such as wavelet packet transformation, energy-correlation analysis, and processing method of wavelet packet coefficients based on energy-correlation analysis, are presented. Finally, a simulation example for a specific signal and an application of shearer cutting current signal, which mainly contain white Gaussian noise and impact noise, are carried out, and the simulation and application results show that the proposed method is effective and is outperforming others.

State Monitoring of Lathes Based on Load Current Signal

2012 ◽  
Vol 201-202 ◽  
pp. 758-762
Author(s):  
Yue Ping Yu ◽  
Guang Lin Yu ◽  
Hong Bin Li ◽  
Guo Fu Li
Keyword(s):  
Wavelet Packet ◽  
Wavelet Denoising ◽  
Wavelet Packet Transform ◽  
Current Signal ◽  
State Monitoring ◽  
Denoising Method ◽  
Load Current ◽  
Time Frequency ◽  
Characteristic Quantity ◽  
Motor Load

According to the characteristics of machine tools such as complex driving chain ,weak signal and enclosed housing,this paper takes horizontal lathes as study objects and selects current signal which is easy to sample as the analytical signal.We collect motor load current signals of idling, cylindrical cutting and end cutting processing state in the experiment to process the condition monitoring based on wavelet denoising and wavelet packet transform. We take advantage of the threshold denoising method to reduce noise of load current signal.Then we use time-frequency analysis methods of wavelet packet transform to extract state characteristic quantity and outstand useful information.So in this paper we monitor the working state of lathes based on the unique advantages of wavelet denoising and wavelet packet transform, and this method can be widely used in various fields of state monitoring.

scholarly journals Wavelet Transform for Signal Processing in Internet-of-Things (IoT)

2021 ◽  
Author(s):  
Indrakshi Dey ◽  
Shama Siddiqui
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Communication Networks ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Wireless Communication Networks ◽  
Impact Noise ◽  
Sensor Signals ◽  
Processing Steps ◽  
Primary Contribution

The primary contribution of this chapter is to provide an overview of different denoising methods used for signal processing in IoT networks from the perspectives of physical layer in the network. The chapter starts with the introduction to different kinds of noise that can be encountered in any kind of wireless communication networks, different kinds of wavelet transform and wavelet packet transform methods that can be used for denoising sensor signals in IoT networks and the different processing steps that are needed to be followed to accomplish wavelet packet transform for the sensor signals. Finally, a universal framework based on energy correlation analysis has been presented for denoising sensor signals in IoT networks, and such a framework can achieve considerable improvement in denoising performance reducing the effective noise correlation coefficient to 0.00001 or lower. Moreover, this method is found to be equally effective for Gaussian or impact noise or both.

Research on Blasting Vibration Signal Denoising Based on Lifting Scheme

2015 ◽  
Vol 713-715 ◽  
pp. 647-650 ◽  
Author(s):  
Quan Min Xie ◽  
Huai Zhi Zhang ◽  
Ying Gao ◽  
Hong An Cao ◽  
Sheng Qiang Guo ◽  
...  
Keyword(s):  
Wavelet Packet ◽  
Mechanical Vibration ◽  
Lifting Scheme ◽  
Vibration Signal ◽  
Wavelet Packet Transform ◽  
Signal Denoising ◽  
Blasting Vibration ◽  
Lifting Wavelet

Considering lifting scheme and traditional wavelet packet transform principle, The optimal lifting wavelet packet threshold denoising algorithm was introduced. Experimental blasting vibration signal was decomposed by optimal lifting wavelet packet, and noise components in blasting vibration measured signals were filtered successfully. Research shows that, lifting wavelet package transform can effectively remove noise components, and it laid an important foundation for lifting algorithm will be introduced into the analysis field of blasting vibration effects and other mechanical vibration signal.

Shaft Vibration Signal Denoising Based on Wavelet Analysis

2013 ◽  
Vol 300-301 ◽  
pp. 1110-1113
Author(s):  
Tie Qiang Sun ◽  
Rong Liu ◽  
Zhi Qi Qiu
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Wavelet Packet ◽  
Mechanical Vibration ◽  
Vibration Signal ◽  
Signal Denoising ◽  
Axial Vibration ◽  
Denoising Method ◽  
Original Source ◽  
Separation Result

In actual , there exist inevitably a lot of interference from neighbor machine and noise from surrondings in mechanical vibration signal measured by sensor ,which is disadvantageous for condition monitoring and fault diagnosis. In order to eliminate the axial vibration signal in the noise, using Wavelet packet denoising method in this article, Emulating experiment s were carried out under the MATLAB software ,original signals adopted vibration impulsion signal produced by vice position of faulty bear. Separation result s confirm this method successfully ext ract original source ,efficiently removes noise.

A New Adaptive Image Denoising Method Based on Wavelet Packet Transform and Neighbor Dependency

2013 ◽  
Vol 433-435 ◽  
pp. 301-305
Author(s):  
Bin Wen Huang ◽  
Yuan Jiao
Keyword(s):  
High Frequency ◽  
Wavelet Packet ◽  
Estimation Method ◽  
Low Frequency ◽  
Adaptive Threshold ◽  
Difficult Problem ◽  
Wavelet Packet Transform ◽  
Denoising Method ◽  
Image Edges ◽  
Orthogonal Wavelet Transform

In image processing, removal of noise without blurring the image edges is a difficult problem. Aiming at orthogonal wavelet transform and traditional thresholds shortage, a new adaptive threshold image de-noising method which is based on wavelet packet transform and neighbor dependency is proposed. Low frequency part and high frequency part can be decomposed at the same time in wavelet packet transform and the information contained in wavelet coefficients is redundant. Using this kind of relativity in wavelet packet coefficients, we use a new variance neighbor estimation method and then neighbor dependency adaptive threshold is produced. From the experiment result, we see that compared with traditional methods, this method can not only effectively eliminate noise, but can also well keep original images information and the quality after image de-noising is very well.

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