Analysis of sound signal of five internal organs based on wavelet packet

2010 ◽  
Author(s):  
Jianjun Yan ◽  
Siyuan Mao ◽  
Chunming Xia ◽  
Chao Wang ◽  
Yiqin Wang ◽  
...  
Keyword(s):  
Wavelet Packet ◽  
Sound Signal ◽  
Internal Organs

Wavelet packet based analysis of sound of five internal organs in TCM

2010 ◽  
Author(s):  
Jianjun Yan ◽  
Siyuan Mao ◽  
Chunming Xia ◽  
Qingwei Shen ◽  
Yiqin Wang ◽  
...  
Keyword(s):  
Wavelet Packet ◽  
Internal Organs

scholarly journals Algorithm for Feature Extraction of Heart Sound Signal Based on Sym7 Wavelet

2011 ◽  
Vol 1 ◽  
pp. 252-256 ◽  
Author(s):  
Guo Hua Zhang ◽  
Zhong Fan Yuan ◽  
Shi Xuan Liu
Keyword(s):  
Feature Extraction ◽  
Heart Sound ◽  
Wavelet Packet ◽  
High Energy ◽  
Sound Signal ◽  
Energy Concentration ◽  
Good Time ◽  
Band Energy ◽  
Four Levels ◽  
Heart Sound Signal

In order to extract pathological features of heart sound signal accurately, an algorithm for extracting the sub-band energy is developed based on the wavelet packet analysis. Through the spectrum analysis of heart sound signal, the sym7 wavelet, with high energy concentration and good time localization, is taken as the mother function, and the best wavelet packet basis of heart sound signal is picked out. Then, various heart sound signals are decomposed into four levels and the wavelet packet coefficients of the best basis are obtained. According to the equal-value relation between wavelet packet coefficients and signal energy in time domain, the normalized sub-band energy of the best basis is extracted as the feature vector. The mean of class separability measure is 3.049, which indicates that the algorithm is effective for feature extraction of heart sound signal.

Wavelet Packet Algorithm to Feature Extraction of Heart Sound

2011 ◽  
Vol 317-319 ◽  
pp. 1211-1214 ◽  
Author(s):  
Guo Hua Zhang ◽  
Shi Xuan Liu
Keyword(s):  
Heart Sound ◽  
Wavelet Packet ◽  
Sound Signal ◽  
Identification Accuracy ◽  
Bp Network ◽  
Band Energy ◽  
Signal Energy ◽  
The Mean ◽  
Four Levels ◽  
Heart Sound Signal

In order to extract pathological features of heart sound signal accurately, an algorithm for extracting the sub-band energy is developed based on the wavelet packet. The db6 wavelet is taken as the mother function, and the best wavelet packet basis of heart sound signal is picked out. Then, various heart sound signals are decomposed into four levels and the wavelet packet coefficients of the best basis are obtained. According to the equal-value relation between wavelet packet coefficients and signal energy in time domain, the normalized sub-band energy of the best basis is extracted as the feature vector. Based on BP network, seven identification models for seven kinds of heart sound were trained separately. Then, these models were tested by using 70 heart sounds, and the mean of identification accuracy is 72.9%.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Numerical and experimental investigation on internal membrane pressure wave inside sealed structure

2013 ◽  
Vol 61 (3) ◽  
pp. 613-621 ◽  
Author(s):  
W. Barnat
Keyword(s):  
Experimental Investigation ◽  
Pressure Wave ◽  
Pressure Increase ◽  
Internal Organs ◽  
Pressure Impulse ◽  
Internal Membrane ◽  
Contaminated Area

Abstract The article presents an approach to modeling the internal membrane pressure wave inside a sealed structure. During an explosion near a vehicle when a pressure wave reaches a hull, a pressure wave inside arises due to the hull’s bottom and the deformation of sides. They act like the piston - membrane. This membrane transfers the pressure impulse into the vehicle’s interior. A pressure increase causes the damage of internal organs or even death of occupants. In case of an armor penetration the pressure increase may be even larger. One of basic methods to protect a crew is to open hatches. However, such a method cannot be used in a contaminated area.

Sign in / Sign up

Export Citation Format

Share Document