Jennifer A. Rice

Structural health monitoring sensor development for the Imote2 platform

The declining state of civil infrastructure has motivated researchers to seek effective methods for real-time structural health monitoring (SHM). Decentralized computing and data aggregation employing smart sensors allow the deployment of a dense array of sensors throughout a structure. The Imote2, developed by Intel, provides enhanced computation and communication resources that allow demanding sensor network applications, such as SHM of civil infrastructure, to be supported. This study explores the development of a versatile Imote2 sensor board with onboard signal processing specifically designed for the demands of SHM applications. The components of the accelerometer board have been carefully selected to allow for the low-noise and high resolution data acquisition that is necessary to successfully implement SHM algorithms.

Characterization of Wireless Smart Sensor Performance

A critical aspect of using wireless sensors for structural health monitoring is communication performance. Unlike wired systems, data transfer is less reliable between wireless sensor nodes owing to data loss. While reliable communication protocols are typically used to reduce data loss, this increase in communication can drain already limited power resources. This paper provides an experimental investigation of the wireless communication characteristics of the Imote2 smart sensor platform; the presentation is tailored toward the end user, e.g., application engineers and researchers. Following a qualitative discussion of wireless communication and packet delivery, a quantitative characterization of wireless communication capabilities of the Imote2 platform, including an assessment of onboard and external antenna performance, is provided. Herein, the external antenna was found to significantly outperform the onboard antenna in both transmission and reception reliability. However, the built environment, including building materials and other wireless networks, can significantly reduce reception rate and thus increase packet loss. Finally, implications of these results for a full-scale implementation are presented.

Hybrid wireless smart sensor network for full-scale structural health monitoring of a cable-stayed bridge

Rapid advancement of sensor technology has been changing the paradigm of Structural Health Monitoring (SHM) toward a wireless smart sensor network (WSSN). While smart sensors have the potential to be a breakthrough to current SHM research and practice, the smart sensors also have several important issues to be resolved that may include robust power supply, stable communication, sensing capability, and in-network data processing algorithms. This study is a hybrid WSSN that addresses those issues to realize a full-scale SHM system for civil infrastructure monitoring. The developed hybrid WSSN is deployed on the Jindo Bridge, a cable-stayed bridge located in South Korea as a continued effort from the previous years deployment. Unique features of the new deployment encompass: (1) the worlds largest WSSN for SHM to date, (2) power harvesting enabled for all sensor nodes, (3) an improved sensing application that provides reliable data acquisition with optimized power consumption, (4) decentralized data aggregation that makes the WSSN scalable to a large, densely deployed sensor network, (5) decentralized cable tension monitoring specially designed for cable-stayed bridges, (6) environmental monitoring. The WSSN implementing all these features are experimentally verified through a long-term monitoring of the Jindo Bridge.

Structural health monitoring utilizing Intel’s Imote2 wireless sensor platform

The computational and wireless communication capabilities of smart sensors densely distributed over structures can provide rich information for structural monitoring. While smart sensor technology has seen substantial advances during recent years, interdisciplinary efforts to address issues in sensors, networks, and application specific algorithms are needed to realize their potential. This paper first discusses each of these issues, and then reports on research that combines the results to develop a structural health monitoring (SHM) system suitable for implementation on a network of smart sensors. Experimental verification is provided using Intels Imote2 smart sensors installed on a threedimensional truss structure. The Imote2 is employed herein because it has the high computational and wireless communication performance required for advanced SHM applications. This SHM system is then investigated from sensing, network, and SHM algorithm perspectives.

Development of high-sensitivity accelerometer board for structural health monitoring

State-of-the-art wireless smart sensor technology enables a dense array of sensors to be distributed through a structure to provide an abundance of structural information. However, the relatively low resolution of the MEMS sensors that are generally adopted for wireless smart sensors limits the networks ability to measure lowlevel vibration often found in the ambient vibration response of building structures. To address this problem, development of a high-sensitivity acceleration board for the Imote2 platform using a low-noise accelerometer is presented. The performance of this new sensor board is validated through extensive laboratory testing. In addition, the use of the high-sensitivity accelerometer board as a reference sensor to improve the capability to capture structural behavior in the smart sensor network is discussed.

Comparison of Visual Inspection and Structural-Health Monitoring As Bridge Condition Assessment Methods

This paper presents the results of a research project aimed at examining the capabilities and challenges of two distinct but not mutually exclusive approaches to in-service bridge assessment: visual inspection and installed monitoring systems. In this study, the intended functionality of both approaches was evaluated on its ability to identify potential structural damage and to provide decision-making support. Inspection and monitoring are compared in terms of their functional performance, cost, and barriers (real and perceived) to implementation. Both methods have strengths and weaknesses across the metrics analyzed, and it is likely that a hybrid evaluation technique that adopts both approaches will optimize efficiency of condition assessment and ultimately lead to better decision making.

A software-defined multifunctional radar sensor for linear and reciprocal displacement measurement

A software-defined multifunctional radar sensor is developed in this paper for linear and reciprocal displacement measurement. Experiments were performed to demonstrate the high accuracy of the two measurement methodologies. When configured in arctangent-demodulated interferometry mode with a 5.46 GHz carrier frequency, the sensor can measure the displacement with sub-millimeter error at a detection distance of 1.2 m. When configured in nonlinear vibrometer mode, the sensor can measure amplitudes of reciprocal motions with a resolution of 0.4 millimeter and less than 3% average error.

A wireless multifunctional radar-based displacement sensor for structural health monitoring

Wireless smart sensor technology offers many opportunities to advance infrastructure monitoring and maintenance by providing pertinent information regarding the condition of a structure at a lower cost and higher density than traditional monitoring approaches. Many civil structures, especially long-span bridges, have low fundamental response frequencies that are challenging to accurately measure with sensors that are suitable for integration with low-cost, low-profile, and power-constrained wireless sensor networks. Existing displacement sensing technology is either not practical for wireless sensor implementations, does not provide the necessary accuracy, or is simply too cost-prohibitive for dense sensor deployments. This paper presents the development and integration of an accurate, low-cost radar-based sensor for the enhancement of low-frequency vibration-based bridge monitoring and the measurement of static bridge deflections. The sensors utilize both a nonlinear vibrometer mode and an arctangent-demodulated interferometry mode to achieve sub-millimeter measurement accuracy for both periodic and non-periodic displacement. Experimental validation results are presented and discussed.

Structural health monitoring system of a cable-stayed bridge using a dense array of scalable smart sensor network

This paper presents a structural health monitoring (SHM) system using a dense array of scalable smart wireless sensor network on a cable-stayed bridge (Jindo Bridge) in Korea. The hardware and software for the SHM system and its components are developed for low-cost, efficient, and autonomous monitoring of the bridge. 70 sensors and two base station computers have been deployed to monitor the bridge using an autonomous SHM application with consideration of harsh outdoor surroundings. The performance of the system has been evaluated in terms of hardware durability, software reliability, and power consumption. 3-D modal properties were extracted from the measured 3-axis vibration data using output-only modal identification methods. Tension forces of 4 different lengths of stay-cables were derived from the ambient vibration data on the cables. For the integrity assessment of the structure, multi-scale subspace system identification method is now under development using a neural network technique based on the local mode shapes and the cable tensions.

Autonomous smart sensor network for full-scale structural health monitoring

The demands of aging infrastructure require effective methods for structural monitoring and maintenance. Wireless smart sensor networks offer the ability to enhance structural health monitoring (SHM) practices through the utilization of onboard computation to achieve distributed data management. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While smart sensor technology is not new, the number of full-scale SHM applications has been limited. This slow progress is due, in part, to the complex network management issues that arise when moving from a laboratory setting to a full-scale monitoring implementation. This paper presents flexible network management software that enables continuous and autonomous operation of wireless smart sensor networks for full-scale SHM applications. The software components combine sleep/wake cycling for enhanced power management with threshold detection for triggering network wide tasks, such as synchronized sensing or decentralized modal analysis, during periods of critical structural response.