Self-Mixing Interferometer Based on Four-Bucket Integration Technique for Micro-Displacement Measurement

2008 ◽  
Vol 381-382 ◽  
pp. 53-56
Author(s):  
Dong Mei Guo ◽  
Ming Wang
Keyword(s):  
Phase Modulation ◽  
Signal Analysis ◽  
External Cavity ◽  
Laser Cavity ◽  
Interference Signal ◽  
Analysis Method ◽  
Integration Technique ◽  
Electro Optic ◽  
Signal Analysis Method ◽  
Electro Optic Modulator

A novel self-mixing interference signal analysis method is proposed based on the use of an electro-optic modulator (EOM). Self-mixing interference occurs in the laser cavity by reflecting the light from a mirror-like target in front of the laser. Sinusoidal phase modulation of the beam is obtained by an EOM in the external cavity. The phase of the interference signal is calculated by four-bucket integration technique. The interferometer is applied to measure the displacement of a high-precision commercial PZT with an accuracy of a few nanometers.

Research on Applied-Information Technology in Digital Speech Based on LMD Algorithm

2014 ◽  
Vol 1014 ◽  
pp. 447-451
Author(s):  
Dong Kang He ◽  
You Cai Xu ◽  
Xin Shi Li ◽  
Ran Tao ◽  
Shu Guo ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Production Function ◽  
Signal Analysis ◽  
Training Model ◽  
Recognition System ◽  
Analysis Method ◽  
End Effects ◽  
Local Mean ◽  
Non Stationary Signal ◽  
Signal Analysis Method

As a new nonlinear and non-stationary signal analysis method,local mean decomposition (LMD) has a good adaptability. We decompose the original non-stationary acceleration vibration signals into several stationary production function (PF).But performing LMD will produce end effects which make results distorted. A hidden Markov model (HMM)-based speech recognition system for Chinese spell.After analyzing reasons for end effects of LMD in detail,a new method based on weighted matching similar waveform was proposed.Experiments in speech recognition to the production function as the training model, the more traditional identification method to identify higher rates. LMD is an effective method. It is feasible to extract the feature from speech signals with LMD.

scholarly journals Bolt Detection Signal Analysis Method Based on ICEEMD

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Chunhui Guo ◽  
Zhan Zhang ◽  
Xin Xie ◽  
Zhengyu Yang
Keyword(s):  
Signal Analysis ◽  
Approximate Entropy ◽  
Ensemble Empirical Mode Decomposition ◽  
Analysis Method ◽  
Détection Signal ◽  
Mode Function ◽  
Mode Decomposition ◽  
Signal Analysis Method ◽  
Detection Signal

The construction quality of the bolt is directly related to the safety of the project, and, as such, it must be tested. In this paper, the improved complete ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt detection signal analysis. The ICEEMD is used in order to decompose the anchor detection signal according to the approximate entropy of each intrinsic mode function (IMF). The noise of the IMFs is eliminated by the wavelet soft threshold denoising technique. Based on the approximate entropy and the wavelet denoising principle, the ICEEMD-De anchor signal analysis method is proposed. From the analysis of the vibration analog signal, as well as the bolt detection signal, the result shows that the ICEEMD-De method is capable of correctly separating the different IMFs under noisy conditions and also that the IMF can effectively identify the reflection signal of the end of the bolt.

The Damped Eigenfrequency Analysis for an Elastic Disk Clamped by a Water-Filled Cylinder

2012 ◽  
Vol 490-495 ◽  
pp. 3742-3747
Author(s):  
Zhi Xi Yang
Keyword(s):  
Signal Analysis ◽  
Effective Means ◽  
Three Dimensional ◽  
Vibration Signal ◽  
Analysis Method ◽  
Obvious Effect ◽  
Coupled Numerical Model ◽  
Elastic Disk ◽  
Vibration Signal Analysis ◽  
Signal Analysis Method

A vibroacoustic testing model in laboratory for the damped eigenfrequencies and eigenmodes is introduced in this paper. The unsymmetric (u, p) variational formulas are implemented for three dimensional structures based on the elastodynamic displacement field u and the fluid acoustic pressure field p. The damping coefficients of materials seem to have no obvious effect on the coupled numerical model. Then the damped eigenfrequencies can alternately be obtained by vibration signal analysis method. The Fast Fourier Transform for the spectrum domain analysis illustrates an effective means to evaluate the damped eigenfrequencies.

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