Hongki Jo

Development and Application of High-Sensitivity Wireless Smart Sensors for Decentralized Stochastic Modal Identification

State-of-the-art smart sensor technology enables deployment of dense arrays of sensors, which is critical for structural health monitoring (SHM) of complicated and large-scale civil structures. Despite recent successful implementation of various wireless smart sensor networks (WSSNs) for full-scale SHM, the low-cost micro-electro-mechanical systems (MEMS) sensors commonly used in smart sensors cannot readily measure low-level ambient vibrations because of their relatively low resolution. Combined use of conventional wired high- sensitivity sensors with low-cost wireless smart sensors has been shown to provide improved spectral estimates of response that can lead to improved experimental modal analysis. However, such a heterogeneous network of wired and wireless sensors requires central collection of an enormous amount of raw data and off-network processing to achieveglobal time synchronization; consequently, many of the advantages of WSSNs for SHM are lost. In this paper, the development of a new high-sensitivity accelerometer board (SHM-H) for the Imote2 wireless smart sensor (WSS) platform is presented. The use of a small number of these high-sensitivity WSSs, composed of the SHM-H and Imote2, as reference sensors in the Natural Excitation Technique—based decentralized WSSN strategy is explored and is shown to provide a cost- effective means of improving modal feature extraction in the decentralized WSSN for SHM. DOI: 10.1061/(ASCE)EM.1943-7889 .0000352.

Sensitivity analysis of non-conservative eigensystems

An expression for the derivatives of eigenvalues and eigenvectors of non-conservative systems is presented. Contrary to previous methods that use state space form (2N-space) to consider damping, proposed method solves the eigenpair derivatives of damped system explicitly. The computation size of N-order is maintained and the eigenpair derivatives are obtained simultaneously from one equation so that it is efficient in CPU time and storage capacity. Moreover, this method can be extended to asymmetric non-conservative damped systems. Although additional problems are generated contrary to the eigenpair sensitivity methods of symmetric systems, in asymmetric case, an algebraic method for the eigenpair derivatives can be obtained through similar procedure. The proposed expression is derived by combining the differentiations of the eigenvalue problem and normalization condition into one linear algebraic equation. The numerical stability is proved by showing non-singularity of the proposed equation, and the efficiency of the derived expression is illustrated by considering a cantilever beam with lumped dampers and a whirling beam.

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.

A wireless smart sensor network for automated monitoring of cable tension

As cables are primary load carrying members in cable-stayed bridges, monitoring the tension forces of the cables provides valuable information regarding structural soundness. Incorporating wireless smart sensors with vibration-based tension estimation methods provides an efficient means of autonomous long-term monitoring of cable tensions. This study develops a wireless cable tension monitoring system using MEMSIC’s Imote2 smart sensors. The monitoring system features autonomous operation, sustainable energy harvesting and power consumption, and remote access using the internet. To obtain the tension force, an in-network data processing strategy associated with the vibration-based tension estimation method is implemented on the Imote2-based sensor network, significantly reducing the wireless data transmission and the power consumption. The proposed monitoring system has been deployed and validated on the Jindo Bridge, a cable-stayed bridge located in South Korea.

Dynamic Assessment of Timber Railroad Bridges Using Displacements

Abstract Infrastructure spending is such a large component of a railroad budget that it must be prioritized to meet the concurrent safety and line capacity requirements. Current bridge inspection and rating practices recommend observing bridge movements under a live load to help assess bridge conditions. However, measuring bridge movements under trains in the field is a challenging task. Even when they are measured, the relationships between bridge displacements and different loads/speeds are generally unknown. The research reported herein shows the effects of known train loadings, speeds, and traffic directions on the magnitude and frequency of displacements as measured on timber pile bents of a Class I railroad bridge. Researchers collected both vertical and transverse (lateral) displacements under revenue service traffic and work trains using LVDTs with a sampling frequency of 100 Hz. To investigate the effect of traffic on timber railroad bridges, displacements were measured under crossing events at d...

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.

Low-Latency Data Acquisition Hardware for Real-Time Wireless Sensor Applications

Wireless sensor networks (WSNs) are an attractive alternative to traditional tethered systems for monitoring and feedback control of civil structures. In civil engineering, research has focused on the application of WSN to structural health monitoring (SHM); as a result, hardware has been tailored to SHM applications. However, the real-time performance requirements of WSNs for control are more stringent than for monitoring applications. Wireless communication, processing time, and data-acquisition hardware are a few of the many sources of time-delay in wireless control systems; this paper will focus on the latency due to the acquisition and actuation hardware in the control loop, i.e., the time between capturing a measurement and its availability on the processor. Previous work on smart sensor hardware focuses either on resolution for SHM applications or the actuation interface for control applications. Overall, an analysis of latency due to the data-acquisition hardware and an understanding of the inherent limitations have been lacking. This paper illustrates the limitations of a common analog-to-digital converter (ADC) architecture for SHM applications and presents a low-latency hardware solution for wireless control nodes. The performance of the two different data-acquisition techniques emphasizes the implication of ADC architecture on the latency and resolution of the data. Ultimately, through the use of an successive-approximation-register-type ADC and careful design of the corresponding driver, the latency due to the hardware is almost negligible.

Feasibility study of wind generator for smart wireless sensor node in cable-stayed bridge

Long-term structural health monitoring (SHM) systems using wireless smart sensors for civil infrastructures such as cable-stayed bridges has been researched due to its cost-effectiveness and ease of installation. Wireless smart sensors are usually powered by high capacity batteries because they consume low power. However, theses batteries require regular replacements for long-term continuous and stable operation. To overcome this limitation of wireless smart sensor-based SHM, considerable attention has been recently paid to alternative power sources such as solar power and vibration-based energy harvesting. Another promising alternative ambient energy source might be a wind-generated power; in particular, it can be very useful for structures in windy area such as coastal and mountainous area. In this study, the feasibility of the wind-powered generation for wireless smart senor nodes is investigated by through experimental and analytical approaches, and the possibility of practical application to actual SHM system of a cable-stayed bridge is discussed.

Reference-Free Displacements for Condition Assessment of Timber Railroad Bridges

Current railroad bridge inspection and rating practices include observing bridge movement under live loads to help assess bridge conditions. Recent research has shown that transverse displacements of timber trestle bridges can capture critical changes in bridge serviceability (the ability to safely carry out railroad operations) as a function of railroad loading, speed, and direction. Measuring bridge movement under trains in the field is difficult and expensive because a fixed reference point is not normally available, thus creating the need to erect independent scaffolding to create good reference points near a timber bridge. This research demonstrates the potential of using reference-free accelerations collected with wireless smart sensors to estimate railroad bridge transverse displacements under live train loads. Focus is placed on timber trestle bridges, which comprise approximately 24% of the total inventory length of railroad bridges in the United States. The results show that wireless smart sensors can estimate transverse displacements of timber railroad trestles and could become an effective tool for campaign monitoring of railroad bridges (with applications toward helping overall bridge assessment).

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.