An architecture for distributed wavelet analysis and processing in sensor networks

2006 ◽  
Author(s):  
Raymond S. Wagner ◽  
Richard G. Baraniuk ◽  
Shu Du ◽  
David B. Johnson ◽  
Albert Cohen
Keyword(s):  
Sensor Networks ◽  
Wavelet Analysis

An Activity Monitor Design Based on Wavelet Analysis and Wireless Sensor Networks

2007 ◽  
Vol 11 (3) ◽  
pp. 261-267
Author(s):  
Qian Tian ◽  
◽  
Long Xie ◽  
Noriyoshi Yamauchi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wavelet Analysis ◽  
Physical Condition ◽  
Activity Monitor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Process Data ◽  
Data Resource ◽  
Sensor Module

The activity monitor we designed based on wavelet analysis and wireless sensor networks for monitoring human physical condition consists of sensor nodes to sample and transfer data, an FPGA board as a processing center to process data, and a PC to display results. We connect wireless sensor module Ni3 and MEMS accelerometers to make a sensor node small enough to wear and not limited by space. We propose reducing signal noise based on wavelet analysis to ensure a robust data resource and develop a simple wavelet-lifting architecture to decrease the complexity of implementation in the FPGA board. Experimental results demonstrate that our system provides an efficient platform for human physical condition monitoring.

Principles of Wireless Sensor Networks

2012 ◽  
Author(s):  
Mohammad S. Obaidat ◽  
Sudip Misra
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor

Classification of Acceleration Waveforms during Walking by Wavelet Transform

1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Center Of Gravity ◽  
Dynamic Responses ◽  
Sequential Data ◽  
Acceleration Signal ◽  
Continuous Dynamic

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.

Study of Identification Method of Drunk Driving Based on Wavelet Analysis

ICCTP 2011 ◽  
2011 ◽  
Author(s):  
Xing-jian Zhang ◽  
Xiao-hua Zhao ◽  
Jian Rong ◽  
Shi-li Xu
Keyword(s):  
Wavelet Analysis ◽  
Drunk Driving ◽  
Identification Method

Efficiency of application of the phase-chronometric method and neurodiagnostics for monitoring the degradation of rolling bearings during operation

2020 ◽  
pp. 43-50
Author(s):  
A.S. Komshin ◽  
K.G. Potapov ◽  
V.I. Pronyakin ◽  
A.B. Syritskii
Keyword(s):  
Life Cycle ◽  
Wavelet Analysis ◽  
Metrological Support ◽  
Rolling Bearing ◽  
Technical Condition ◽  
Measurement Information ◽  
Rolling Bearings ◽  
Vibration Diagnostics ◽  
Bearing Life ◽  
Alternative Approach

The paper presents an alternative approach to metrological support and assessment of the technical condition of rolling bearings in operation. The analysis of existing approaches, including methods of vibration diagnostics, envelope analysis, wavelet analysis, etc. Considers the possibility of applying a phase-chronometric method for support on the basis of neurodiagnostics bearing life cycle on the basis of the unified format of measurement information. The possibility of diagnosing a rolling bearing when analyzing measurement information from the shaft and separator was evaluated.

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