Showing papers by "Charles R. Farrar published in 2008"

Energy Harvesting for Structural Health Monitoring Sensor Networks

Abstract: This paper reviews the development of energy harvesting for low-power embedded structural health monitoring (SHM) sensing systems. A statistical pattern recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portion of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized followed by a discussion of SHM sensor network paradigms, power requirements for these networks, and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. The paper concludes by defining some future research directions that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes. Finally, it is noted that many of the technologies discussed herein are applicable to powering any type of low-power embedded sensing system regardless of the application.

A review of nonlinear dynamics applications to structural health monitoring

Abstract: The process of implementing a damage detection strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). In many cases damage causes a structure that initially behaves in a predominantly linear manner to exhibit nonlinear response when subject to its operating environment. The formation of cracks that subsequently open and close under operating loads is an example of such damage. The damage detection process can be significantly enhanced if one takes advantage of these nonlinear effects when extracting damage-sensitive features from measured data. This paper will provide a review of examples from nonlinear dynamical systems theory and from nonlinear system identification techniques that are used for the feature-extraction portion of the damage detection process. This paper is not intended as a comprehensive review of all damage detection methods rooted in nonlinear dynamics, but rather to provide a number of illustrations of complimentary approaches where damage-sensitive data features are based on nonlinear system response. These features, in turn, can either be used as a direct diagnosis of damage or as input to statistical damage classifier. Copyright © 2007 John Wiley & Sons, Ltd.

Development of an Extremely Compact Impedance-Based Wireless Sensing Device

Abstract: This paper describes the development of the next generation of an extremely compact, wireless impedance sensor node for use in structural health monitoring (SHM) and piezoelectric active-sensor self-diagnostics. The sensor node uses a recently developed, low-cost integrated circuit that can measure and record the electrical impedance of a piezoelectric transducer. The sensor node also integrates several components, including a microcontroller for local computing, telemetry for wirelessly transmitting data, multiplexers for managing up to seven piezoelectric transducers per node, energy harvesting and storage mediums, and a wireless triggering circuit into one package to truly realize a comprehensive, self-contained wireless active-sensor node for various SHM applications. It is estimated that the developed sensor node requires less than 60 mW of total power for measurement, computation, and transmission. In addition, the sensor node is equipped with active-sensor self-diagnostic capabilities that can monitor the condition of piezoelectric transducers used in SHM applications. The performance of this miniaturized device is compared to our previous results and its broader capabilities are demonstrated.

A mobile-agent based wireless sensing network for structural monitoring applications

Abstract: A new wireless sensing network paradigm is presented for structural monitoring applications. In this approach, both power and data interrogation commands are conveyed via a mobile agent that is sent to sensor nodes to perform intended interrogations, which can alleviate several limitations of the traditional sensing networks. Furthermore, the mobile agent provides computational power to make near real-time assessments on the structural conditions. This paper will discuss such prototype systems, which are used to interrogate impedance-based sensors for structural health monitoring applications. Our wireless sensor node is specifically designed to accept various energy sources, including wireless energy transmission, and to be wirelessly triggered on an as-needed basis by the mobile agent or other sensor nodes. The capabilities of this proposed sensing network paradigm are demonstrated in the laboratory and the field.

Wireless Sensor Technologies for Monitoring Civil Structures

Abstract: Wireless sensor networks (WSNs) for structural health monitoring (SHM) applications can allow for a rapid assessment of structural integrity after an event such as a natural disaster puts the reliability of civil infrastructure in question. Unfortunately, there are many technical challenges associated with employing such a WSN in civil infrastructure for operation over multiple decades. Maintenance costs must remain low enough to justify the integration of such a WSN into a given structure. The technical challenges include ensuring power is delivered to the sensor nodes, reducing installation and maintenance costs, and automating the collection and analysis of data collected by a wireless sensor network. Here we explore possible solutions to the technical challenges presented by WSN for SHM applications. A “mobile host” WSN has been developed where a civil structure is instrumented with sensor nodes capable of being powered solely on energy transmitted to the sensor node wirelessly by the mobile host. When the sensor node has received adequate energy for making a given measurement, the sensor node performs the necessary measurement operations and then wirelessly transmits the measurement to the mobile host. These operations are then repeated for all desired sensor nodes in the network. In crisis situations such as an earthquake, it is good to have tools in place allowing a rapid condition assessment of civil infrastructures. Often these situations do not allow conventional human inspections due to safety and accessibility issues. It would be desirable to automate the inspection process so that humans are not placed in danger during the assessment and to employ relevant data collection and feature extraction methods to eliminate the need for infrastructure assessment experts at a potentially damaged location. Furthermore, this rapid assessment-monitoring system should be robust enough to be deployed on a structure for multiple decades without any human intervention. The work presented here proposes sensors and nodes that can be integrated into such a rapid assessment-monitoring framework. The sensor nodes investigated here are designed to be placed into a “roving-host,” wireless-sensor network. In this framework an unmanned aerial vehicle (UAV) is used to fly to the sensors of interest. Once the UAV arrives at the relevant sensor node, it wirelessly transmits energy to the sensor node to power it up in a manner similar to the operation of a radio frequency identification (RFID) tag. The sensor node makes a measurement and then transmits data back to the UAV. The UAV then adds the sensor node’s data to its database and repeats the process for other relevant nodes. Such a network allows for periodic energy delivery as well as a centralized data processing capability

Demonstration of a roving-host wireless sensor network for rapid assessment monitoring of structural health

Abstract: A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is developing means to supply power to the sensor nodes in a cost-effective manner. In this work an initial test of a roving-host wireless sensor network was performed on a bridge near Truth or Consequences, NM in August of 2007. The roving-host wireless sensor network features a radio controlled helicopter responsible for wirelessly delivering energy to sensor nodes on an "as-needed" basis. In addition, the helicopter also serves as a central data repository and processing center for the information collected by the sensor network. The sensor nodes used on the bridge were developed for measuring the peak displacement of the bridge, as well as measuring the preload of some of the bolted joints in the bridge. These sensors and sensor nodes were specifically designed to be able to operate from energy supplied wirelessly from the helicopter. The ultimate goal of this research is to ease the requirement for battery power supplies in wireless sensor networks.

Recent Advances in Impedance-Based Wireless Sensor Nodes

Abstract: This paper presents recent developments in an extremely compact, wireless impedance sensor node for use in structural health monitoring (SHM) The sensor node uses a low-cost integrated circuit that can measure and record the electric impedance of a piezoelectric active-sensor The sensor node also integrates several components, including a microcontroller for local computing, telemetry for wireless data transmission, multiplexers for managing up to seven piezoelectric transducers per node, energy storage mediums, and several triggering options including a wireless triggering circuit into one package to truly realize a comprehensive, self-contained wireless active-sensor node for SHM applications It is estimated that this sensor node requires less than 75 mW of total power to operate measurement, computation and data transmission In addition, the sensor node can also be used for the active-sensor self-diagnostic process that can monitor the operational condition of piezoelectric transducers used in SHM applications The performance of this miniaturized and portable device is compared to our previous results and its broader capabilities are demonstratedCopyright © 2008 by ASME