Structural health monitoring (SHM) uses an array of sensors to continuously monitor a structure to provide an early indication of problems such as damage to the structure from fatigue, corrosion or impact The use of such a system enables maintenance costs to be reduced, and new structures can be designed to be lighter and more efficient CSIRO has developed an SHM system for detecting high-velocity impacts in the skin of a structure, such as may occur to space vehicles The system is a large sensor network containing about two-hundred nodes, each of which contains multiple sensors The system has been built as a flexible testbed for undertaking research in the use of sensor networks in a wide range of SHM applications This paper outlines the testbed that has been developed and the research that has been conducted using this testbed

Sensor network for structural health monitoring

This chapter describes the development and operation of an experimental structural health monitoring system whose functionality is based on self-organization in a complex multiagent system. Self-organization within a system of many interacting components is generally understood to mean the formation of global patterns, or the production of coordinated global behaviours, solely from the interactions among the lower-level components of the system. The important characteristics are that the resulting patterns or behaviours occur at a larger scale than the individual system components and the interactions among the components are not influenced by a central controller or by reference to the emergent pattern or behaviour; they are purely local interactions. Self-organization in biological systems has been defined and discussed by Camazine et al. (2001), and Prokopenko et al. (2007) have discussed self-organization from an information-theoretic perspective. The system that is described in this chapter consists of a large number (∼200) of semiautonomous local sensing “agents,” each of which can sense, process data, and communicate with its neighbours. In this context self-organization means that the agents will produce a system-level response to external events or damage that is entirely the result of local communication among the agents and is not influenced by a central controller or by any system-level design. The main benefits of this approach lie in scalability (the system performance is not limited by the computational and communication capability of a central controller) and in robustness (there is no single point of vulnerability, such as would be represented by a central controller).

A Self-organizing Sensing System for Structural Health Monitoring of Aerospace Vehicles

This paper describes a new approach to structural health monitoring and management (SHM) that aims to diagnose and respond to damage using the self-organization of a complex system of distributed sensors and processing cells. To develop and evaluate the approach, an experimental SHM test-bed system has been developed, with the aim of detecting and characterising the damage from high-velocity impacts such as those due to micrometeoroids on a space vehicle. An important new feature of the system is an ability to support mobile (robotic) agents that can roam the exterior surface of the test-bed, obtaining additional damage information and providing a crude repair capability. The focus of this paper is the development of a self-organised approach to the operation of such a robotic agent, for which it obtains local information by direct communication with the fixed agents embedded in the underlying structure.

A self-organising sensing system for structural health management

This Chapter describes the development and operation of an experimental structural health monitoring system whose functionality is based on self-organization in a complex multi-agent system. Self-organization within a system of many interacting components is generally understood to mean the formation of global patterns, or the production of coordinated global behaviours, solely from the interactions among the lowerlevel components of the system. The important characteristics are that the resulting patterns or behaviours occur at a larger scale than the individual system components, and that the interactions between the components are not influenced by a central controller or by reference to the emergent pattern or behaviour: they are purely local interactions. Self-organization in biological systems has been defined and discussed by Camazine et al. (Self-organization in biological systems. Princeton University Press, Princeton, 2001), and Prokopenko et al. (Complexity 15:11–28, 2008) have discussed self-organization from an information-theoretic perspective. The system that will be described in this Chapter consists of a large number (∼200) of semi-autonomous local sensing agents, each of which can sense, process data, and communicate with its neighbours. In this context self-organization means that the agents will produce a system-level response to external events or damage that is produced entirely by the local communications between the agents, and is not influenced by a central controller or by any system-level design. The main benefits of this approach lie in scalability (the system performance is not limited by the computational and communication capability of a central controller) and in robustness (there is no single point of vulnerability, such as would be represented by a central controller).

Self-Organizing Sensing of Structures: Monitoring a Space Vehicle Thermal Protection System

The work reported here is the first stage of a project that aims to develop a health monitoring system for Thermal Protection Systems (TPS) that enables a vehicle to safely re-enter the Earth's atmosphere. The TPS health monitoring system is to be integrated into an existing acoustic emissions-based Concept Demonstrator, developed by CSIRO, which has been previously demonstrated for evaluating impact damage of aerospace systems.

Heath Monitoring of Thermal Protection Systems - Preliminary Measurements and Design Specifications

An integrated vehicle health monitoring system is being developed, with its initial application being to detect and locate impacts of fast particles, and characterise and respond to the damage such collisions may cause. Large numbers of sensors are used, with the continuous monitoring and processing of signals being performed by autonomous local agents that communicate only essential information with their nearest neighbours. This multi‐agent system is completely scalable and generates emergent and intelligent responses, making possible the detection and diagnosis of damage even in the presence of existing damage in the system or in the structure it is monitoring.

An Intelligent Sensor System for Detection and Evaluation of Particle Impact Damage

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An Intelligent Sensor System for Detection and Evaluation of Particle Impact Damage