M OTIVATION AND O BJECTIVE

In SHM, integration of cross discipline is essential for developing a flexible and robust system. For example, Civionics is currently the use of electronics for structural health monitoring (SHM) of civil structures. It is combination of electronic engineering with civil engineering, in a manner similar to avionics (aviation and electronics) and mechatronics (mechanical engineering and electronics) [7].

Generally, sensors comprise a significant portion of the SHM process. Recent developments in smart sensor technology enable new applications in structural health monitoring. The main features of a typical smart sensor are on-board microprocessor, sensing capability, data storage, wireless communication, battery power, and low cost.

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Sensors are being deployed in civil infrastructures. Long term recorded data for monitoring are extensive. Smart sensors can process data before outputs are recorded, which reduces the quantity of data required and computing power [8].

When many sensors are implemented, wireless communication appears to be an attractive approach. Wired sensor systems can only deploy limited numbers of sensors because of cost constraints or excessive complexity. Wireless sensors are expected to minimize these problems by simplifying the installation of wired sensors [9-11].

Smart sensor-based wireless sensor networks (WSNs) are an attractive sensing technology for structural health monitoring applications because of their low manufacture costs, low power requirements, small size, and simple deployment (i.e., lack of cables) [12, 13].

Although numerous researchers have demonstrated the advantages of WSN [12-17], there are still existing many limitations. First, the wireless throughput is heavy to collect all of the measured information in SHM. The aggregation of dynamic measurement data consumes power- and time- consuming even when data are not collected in real time. For instance, Kim et al. [18] developed a multi-hop wireless sensor network to monitor the Golden Gate Bridge. They reported that transferring KB data from 64 nodes required over 12 hours. Moreover, sensor nodes are not synchronized with separate clocks. Packets may be lost in communication or sensing, and storage memory space is always limited. Therefore, an effective time-scheduling and data transmission protocol should be developed.

Additional, the processing ability of processor of node in WSN is slower than that of a PC. In SHM, a complex parameter identification-based embedded damage detection approach may not perform adequately when using resource-constrained

WSN hardware. Therefore, a non-parameter embedded damage detection approach such may be considered a appreciate approach.

Next, battery powered wireless nodes have limitations on consuming large amounts of power in packets delivering. Hence, power sources and power consumption are the critical issue if batteries have to be periodically replaced.

Therefore, an intelligent self -powered wireless sensor networks via harvest and store ambient sources of energy should be considered to solve this barrier.

Furthermore, implementing an embedded algorithm in a complex development environment commonly involves hardware and software complexities, making the task quite challenging, especially for civil engineers with limited experience of WSN.

Also, robust system development is problematic in a complex programming environment. Accordingly, a WSN-based SHM system should be developed based on an easy-to-use development environment. Related applications can be implemented efficiently in this the friendly environment.

The main purpose of this dissertation is to propose a framework of an integrated wireless sensor network-based structural health monitoring system in buildings and civil infrastructures. Figure 1.2 illustrates the proposed framework. In this framework, it is considered three main parts which are the physical sensing, information fusion and management, and inference and decision making. To achieve this goal, an integrated WSN-based SHM system is developed. This system consists of sensing nodes, cluster head nodes, transfer node, and base station. The purpose of sensing node is to measure the responses of structure or the environmental parameters. Cluster head node can communicate with the sensing nodes or other cluster heads of the neighboring communities to exchange information or triggering sensing task. The

transfer node is functions as coordinate node for managing the cluster heads and hoping the data. The base station is the highest level end device that has largest memory, most powerful processor and highest communication capability. The base station node is the gateway between smart sensor networks and the Host computer.

The base station uploads the data to remote monitoring and control server via satellite, 3G telecommunication or WiMAX communication. A three-tier software framework is also developed in this work serving as reliable data-sensing and transmission, data logging and data storage, user interface, data analyzing, and signal processing. Based on this software framework, a SHM application for specific purpose can be easily developed. Power sources and power consumption are the critical issue in WSN if batteries have to be periodically replaced. Hence, a novel windmill-magnet integrated piezoelectric (WMIP) energy harvesting system was also proposed.

Both local and global SHM each has its own benefits and shortcoming, hence integrating aforesaid two approaches can obtain more effective damage detection result than only using one of them. This work proposed a global-local-integrated damage detection approach to localize damage. Substructure-based frequency response function approaches are proposed as global damage detection approach.

Electro-Mechanical-Impedance (EMI)-Based damage detection method is used to identify local damage of structure in this study. In addition to theoretical developments in damage assessment approach and developing of wireless SHM system, experimental study is also conducted to complete this thesis.

Figure 1.2 A framework of an integrated wireless sensor network-based structural health monitoring system.