scholarly journals Optical Interference Signal Processing in Precision Dimension Measurement

Automation ◽  
10.5772/50529 ◽  
2012 ◽  
Author(s):  
Haijiang Hu ◽  
Fengdeng Zhang ◽  
Juju Hu ◽  
Yinghua Ji
Keyword(s):  
Signal Processing ◽  
Interference Signal ◽  
Optical Interference ◽  
Dimension Measurement

Fast white light interference signal processing method based on effective signal extraction

2019 ◽  
Vol 48 (10) ◽  
pp. 1013002
Author(s):  
马 龙 Ma Long ◽  
贾 竣 Jia Jun ◽  
裴 昕 Pei Xin ◽  
胡艳敏 Hu Yanmin ◽  
周 航 Zhou Hang ◽  
...  
Keyword(s):  
Signal Processing ◽  
White Light ◽  
Processing Method ◽  
Signal Extraction ◽  
Interference Signal ◽  
Light Interference ◽  
Signal Processing Method ◽  
White Light Interference ◽  
Effective Signal

scholarly journals Issues of developing receiving equipment for the passive method of induced polarization

2021 ◽  
Vol 2094 (2) ◽  
pp. 022080
Author(s):  
P V Belolipetskii ◽  
G Y Shajdurov ◽  
V S Potylitsyn ◽  
V V Romanov
Keyword(s):  
Signal Processing ◽  
Field Work ◽  
Induced Polarization ◽  
Interference Signal ◽  
Digital Converter ◽  
Post Processing ◽  
Passive Method ◽  
Channel Interference ◽  
Input Gain ◽  
Analogue To Digital

Abstract The article deals with the design of receiving equipment for the passive method of induced polarization (IP). It is shown that the best option for recording this kind of signals is a circuit with an input analogue part and amplification of 50-100 times, as well as an input gain of at least 3 MΩ and a digital part based on a modern twenty-four-bit analogue-to-digital converter (ADC). In this case, it is preferable to use one ADC per channel without multiplexing, for better suppression of inter-channel interference. Signal processing is performed using modern microcontrollers based on the Cortex M4 core, and then the data is transmitted via Bluetooth to a laptop or tablet, where visualization and post-processing is carried out. Thus, the proposed scheme for the implementation of the receiving equipment meets all the requirements for the receiving equipment for the passive IP method, and can be introduced into the practice of field work.

scholarly journals Using Nonlinear Diffusion Model to Identify Music Signals

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Qiang Li
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Signal Processing ◽  
Equation System ◽  
Interference Signal ◽  
Signal Recognition ◽  
Partial Differential ◽  
Music Signal ◽  
Linear Homogeneous Differential Equation ◽  
Music Signals

In this paper, combined with the partial differential equation music signal smoothing model, a new music signal recognition model is proposed. Experimental results show that this model has the advantages of the above two models at the same time, which can remove noise and enhance music signals. This paper also studies the music signal recognition method based on the nonlinear diffusion model. By distinguishing the flat area and the boundary area of the music signal, a new diffusion coefficient equation is obtained by combining these two methods, and the corresponding partial differential equation is discretized by the finite difference method with numerical solution. The application of partial differential equations in music signal processing is a relatively new topic. Because it can accurately model the music signal, it solves many complicated problems in music signal processing. Then, we use the group shift Fourier transform (GSFT) to transform this partial differential equation into a linear homogeneous differential equation system, and then use the series to obtain the solution of the linear homogeneous differential equation system, and finally use the group shift inverse Fourier transform to obtain the noise frequency modulation time-dependent solution of the probability density function of the interference signal. This paper attempts to use the mathematical method of stochastic differentiation to solve the key problem of the time-dependent solution of the probability density function of noise interference signals and to study the application of random differentiation theory in radar interference signal processing and music signal processing. At the end of the thesis, the application of stochastic differentiation in the filtering processing of music signals is tried. According to the inherent self-similarity of the music signal system and the completeness and stability of the empirical mode decomposition (EMD) algorithm, a new kind of EMD music using stochastic differentiation is proposed for signal filtering algorithm. This improved anisotropic diffusion method can maintain and enhance the boundary while smoothing the music signal. The filtering results of the actual music signal show that the algorithm is effective.

scholarly journals Crack Growth Signal Processing Approach Combining Wavelet Threshold Denoising and Variable Amplitude DCPD Technique

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chenqiang Ni ◽  
He Xue ◽  
Shuai Wang ◽  
Xiurong Fang ◽  
Hongliang Yang
Keyword(s):  
Signal Processing ◽  
Crack Growth ◽  
Potential Drop ◽  
Compact Tension ◽  
Growth Monitoring ◽  
Interference Signal ◽  
Adaptive Wavelet ◽  
Processing Approach ◽  
Reference Potential ◽  
Unbiased Risk

The direct current potential drop (DCPD) method is widely used in laboratory environments to monitor the crack initiation and propagation of specimens. In this study, an anti-interference signal processing approach, combining wavelet threshold denoising and a variable current amplitude DCPD signal synthesis technique, was proposed. Adaptive wavelet threshold denoising using Stein’s unbiased risk estimate was applied to the main potential drop signal and the reference potential signal under two different current amplitudes to reduce the interference caused by noise. Thereafter, noise-reduced signals were synthesized to eliminate the time-varying thermal electromotive force. The multiplicative interference signal was eliminated by normalizing the main potential drop signal and the reference potential drop signal. This signal processing approach was applied to the crack growth monitoring data of 316 L stainless steel compact tension specimens in a laboratory environment, and the signal processing results of static cracks and propagation cracks under different load conditions were analyzed. The results showed that the proposed approach can significantly improve the signal-to-noise ratio as well as the accuracy and resolution of the crack growth measurement.

Mutual interference signal processing for active sonar

2011 ◽  
Vol 130 (4) ◽  
pp. 2410-2410
Author(s):  
Stephen D. Unruh ◽  
Jason M. Aughenbaugh ◽  
James M. Gelb
Keyword(s):  
Signal Processing ◽  
Mutual Interference ◽  
Interference Signal ◽  
Active Sonar
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