Motion Detection Using Wavelet Analysis and Hierarchical Markov Models

2006 ◽  
pp. 64-75 ◽  
Author(s):  
Cédric Demonceaux ◽  
Djemâa Kachi-Akkouche
Keyword(s):  
Wavelet Analysis ◽  
Motion Detection ◽  
Markov Models

Motion Detection for a Precision Positioning System by Wavelet Analysis

1997 ◽  
Author(s):  
Hung-Ming Tai ◽  
Cheng-Kuo Sung
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Motion Detection ◽  
Experimental Setup ◽  
Positioning System ◽  
Precision Positioning ◽  
Band Energy ◽  
Pitch Motion ◽  
The Difference ◽  
Short Time

Abstract The defects due to wear or improper assembly processes may induce undesirable vibrations that in turn cause mechanical failures. This paper employs Wavelet Transform to analyze the vibration of the pitch motion of the carriage in a precision positioning system. Two accelerometers are attached to the carriage at different locations and the accelerations are used to investigate the vibration of the pitch motion. By using Wavelet Transform, the signal measured from the proposed experimental setup are appropriately processed and used for the diagnosis of the defects. The percentage of the band energy (PBE)is found to be a helpful reference for detecting the abnormal conditions. This method successfully combines the techniques of measurement with the theory of the wavelet analysis in monitoring a precision positioning system. The difference between the results obtained both from the Short-Time Fourier analysis and wavelet analysis is also discussed.

Transition (markov) models for the analysis of survival times in clinical research

1999 ◽  
Vol 28 (1) ◽  
pp. 165-176
Author(s):  
Sati Mazumdar ◽  
Kenneth Liu ◽  
Sang Ahnn ◽  
Patricia R. Houck ◽  
Charles F. Reynolds
Keyword(s):  
Clinical Research ◽  
Markov Models ◽  
Survival Times

Markov models—Markov chains

2019 ◽  
Vol 16 (8) ◽  
pp. 663-664 ◽  
Author(s):  
Jasleen K. Grewal ◽  
Martin Krzywinski ◽  
Naomi Altman
Keyword(s):  
Markov Chains ◽  
Markov Models

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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