A vibration-based structural monitoring system with integrated sensor data compression and system identification techniques.

摘要

On-line structural health monitoring (SHM) system for long-term monitoring of civil engineering structures is receiving growing attention from engineers, researchers and property owners of civil infrastructures. Data measured by sensors can be used for structural condition diagnosis and prognosis, traffic regulation, emergency response and disaster relief efforts after extreme events. A new trend in on-line SHM system is towards the use of large scale sensor networks because of the large scale and complexity of civil engineering structures. In such a system, huge amounts of data generated from hundreds to thousands of networked sensors are to be on-line transmitted, remotely accessed and efficiently analyzed for knowledge discovery. The huge amounts of sensor data challenge the current practice in data transmission, data retrieval and management, as well as data analysis for SHM systems.; The goal of this dissertation is to establish an integrated SHM system which has a few highly desired functionalities such as sensor data compression, interactive sensor data retrieval, and second order structural system identification. These functionalities are aimed to enhance the reliability, efficiency, and robustness of on-line SHM systems.; Taking advantages of advances in information technology, sensor network, wireless communication, and system science, this dissertation represents an exploratory effort in addressing the less studied area of sensor data transmission, data management and data retrieval methods for large scale engineering structures. The corresponding algorithms including lossless and lossy data compression methods for vibration sensor data, interactive data retrieval and management method, and the PEM-based second order structural parameter identification method were developed and integrated into a SHM system with the data flow being streamlined and different components being unified. To evaluate the performance of the proposed integrated SHM system, real sensor data measured from a prototype integrated SHM system were used in this study. Results of this study clearly show that the proposed methods have the potential to relax the communication bandwidth requirement, speed up the data transmission process, relax the data analysis burden and quantitatively identify damages in SHM systems.