Vibration sensor data compression and its effect on structural system identification

Yunfeng Zhang; Jian Li

doi:10.1117/12.658797

11 April 2006 Vibration sensor data compression and its effect on structural system identification

Yunfeng Zhang, Jian Li

Proceedings Volume 6174, Smart Structures and Materials 2006: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems; 61743E (2006) https://doi.org/10.1117/12.658797
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2006, San Diego, California, United States

Abstract

Current trend in structural condition monitoring system is towards the use of a large number of networked sensors, which correspondingly generate huge amount of sensor data. High data rates pose challenges in data transmission, storage search and remote retrieval, especially for wireless communication network. To address this problem, innovative sensor data compression techniques are needed to reduce the sensor data size. Lossy data compression techniques have the potential to achieve high compression rates but suffer the problem of signal distortion. This paper presents a waveletbased lossy compression method targeted for vibration sensor data. The trade-off between compression rate and signal distortion due to lossy compression is discussed in this paper. The effect of wavelet-based lossy data compression on both the time domain and frequency domain characteristics of vibration signals is studied. Real sensor data collected from a scaled two-story building structure using wireless accelerometer has been used in this study.

Citation Download Citation

Yunfeng Zhang and Jian Li "Vibration sensor data compression and its effect on structural system identification", Proc. SPIE 6174, Smart Structures and Materials 2006: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, 61743E (11 April 2006); https://doi.org/10.1117/12.658797

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