contributor author | Yunfeng Zhang | |
contributor author | Jian Li | |
date accessioned | 2017-05-08T21:13:18Z | |
date available | 2017-05-08T21:13:18Z | |
date copyright | November 2006 | |
date issued | 2006 | |
identifier other | %28asce%290887-3801%282006%2920%3A6%28390%29.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/43291 | |
description abstract | Civil infrastructure condition monitoring generates large volumes of sensor data. Huge data size impedes fast and reliable distribution of sensor data, especially for wireless sensor networks. Vibration sensor data plays an important role in many useful structural health monitoring methods. This paper presents a vibration sensor data compression technique based on the lifting scheme wavelet transform (LSWT). Real sensor data from a nine-story building as well as a steel truss bridge was used to examine the compression performance of the LSWT-based vibration sensor data compression technique. It is found that the LSWT-based vibration sensor data compression technique can achieve a very high compression ratio while retaining the basic waveform properties of original sensor data. Additionally, LSWT has a feature that supports progressive compression and thus allows for multiresolution data transmission and retrieval. | |
publisher | American Society of Civil Engineers | |
title | Wavelet-Based Vibration Sensor Data Compression Technique for Civil Infrastructure Condition Monitoring | |
type | Journal Paper | |
journal volume | 20 | |
journal issue | 6 | |
journal title | Journal of Computing in Civil Engineering | |
identifier doi | 10.1061/(ASCE)0887-3801(2006)20:6(390) | |
tree | Journal of Computing in Civil Engineering:;2006:;Volume ( 020 ):;issue: 006 | |
contenttype | Fulltext | |