Erik A. Johnson

Monitoring civil structures with a wireless sensor network

Structural health monitoring (SHM) is an active area of research devoted to systems that can autonomously and proactively assess the structural integrity of bridges, buildings, and aerospace vehicles. Recent technological advances promise the eventual ability to cover a large civil structure with low-cost wireless sensors that can continuously monitor a buildings structural health, but researchers face several obstacles to reaching this goal, including high data-rate, data-fidelity, and time-synchronization requirements. This article describes two systems the authors recently deployed in real-world structures.

Structural damage detection and localization using NETSHM

Structural health monitoring (SHM) is an important application area for wireless sensor networks. SHM techniques attempt to autonomously detect and localize damage in large civil structures. Structural engineers often implement and test SHM algorithms in a higher level language such as C/Matlab. In this paper, we describe the design and evaluation of NETSHM, a sensor network system that allows structural engineers to program SHM applications in Mat-lab or C at a high level of abstraction. In particular, structural engineers do not have to understand the intricacies of wireless networking, or the details of sensor data acquisition. We have implemented a damage detection technique and a damage localization technique on a complete NETSHM prototype. Our experiments on small and medium-scale structures show that NETSHM is able to detect and localized damage perfectly with very few false-positives and no false negatives, and that it is robust even in realistic wireless environments

Response of stochastic dynamical systems driven by additive Gaussian and Poisson white noise: Solution of a forward generalized Kolmogorov equation by a spectral finite difference method

Abstract A numerical method is given for the solution of the probability density function of the response process of memoryless one- and two-state dynamical systems having polynomial restoring forces and which are subjected to a combination of Gaussian and Poisson white noises. The method employs the Fourier transformed forward generalized Kolmogorov equation to arrive at an initial-boundary value problem for the characteristic function, which is solved using a high-order finite difference procedure. The probability density function is recovered by numerical inverse Fourier transformation. Several examples are given, the results of which are compared with, analytical solutions where available and with simulation otherwise.

Parallel processing in computational stochastic dynamics

Abstract Studying large complex problems that often arise in computational stochastic dynamics (CSD) demands significant computer power and data storage. Parallel processing can help meet these requirements by exploiting the computational and storage capabilities of multiprocessing computational environments. The challenge is to develop parallel algorithms and computational strategies that can take full advantage of parallel machines. This paper reviews some of the characteristics of parallel computing and the techniques used to parallelize computational algorithms in CSD. The characteristics of parallel processor environments are discussed, including parallelization through the use of message passing and parallelizing compilers. Several applications of parallel processing in CSD are then developed: solutions of the Fokker–Planck equation, Monte Carlo simulation of dynamical systems, and random eigenvector problems. In these examples, parallel processing is seen to be a promising approach through which to resolve some of the computational issues pertinent to CSD.

Distributed Mass Damper System for Integrating Structural and Environmental Controls in Buildings

The writers recently proposed a new type of mass damper system to integrate structural and environmental control systems for buildings. External shading fins are used as mass dampers such that they can (1) control building energy consumption by adjusting the fins and, thus, the amount of sunlight entering the building; and (2) control structural movements by dissipating energy with the dampers during strong motions. Because shading fins are placed along the height of the building, the mass dampers are distributed along the building height instead of concentrated in one or a few locations like traditional tuned mass dampers (TMDs). The distributed mass damper (DMD) system is formulated and simulated for earthquake motions. Optimization is performed on damper parameters (i.e., masses, stiffness, and damping coefficients) of the passive DMD system to minimize structural responses. A near-optimal DMD system outperforms a single TMD system. The movable shading fins are also briefly discussed; they show a subst...

Embedded sensing of structures: a reality check

With the advent of miniaturized sensing technology, it has become possible to envision smart structures containing millions of sensors embedded in concrete for autonomously detecting and locating incipient damage. Where are we today in our march towards this vision of autonomous structural health monitoring (SHM) using networked embedded sensing? In this paper, we summarize some of the systems we have developed towards this vision. Wisden is a wireless sensor network that allows continuous monitoring of structures and NetSHM is a programmable system that allows civil engineers to implement and deploy SHM techniques without having to understand the intricacies of wireless sensor networking. We highlight our experiences in developing these systems, and discuss the implications of our experiences on the achievability of the overall vision.

Semi-active building base isolation

Passive base isolation systems are one of the most successful and widely implemented technologies for seismic hazard mitigation. However, recent changes to the building codes have made the design requirements such that some of the potential gains of such systems may not be realized. This paper investigates the effects of using controllable semi-active dampers, such as magnetorheological fluid dampers, in a base isolation system. A two degree-of-freedom model of a base isolated building is used, with linear viscous, active, and semi-active supplemental damping devices in the isolation layer. Using an H/sub 2//LQG control design, semi-active and active devices are able to achieve a notable decrease in base drifts, compared to the optimal linear passive designs, with no accompanying increase in accelerations imparted into the superstructure.

Substructure identification for shear structures: cross-power spectral density method

In this paper, a substructure identification method for shear structures is proposed. A shear structure is divided into many small substructures; utilizing the dynamic equilibrium of a one-floor substructure, an inductive identification problem is formulated, using the cross-power spectral densities between structural floor accelerations and a reference response, to estimate the parameters of that one story. Repeating this procedure, all story parameters of the shear structure are identified from top to bottom recursively. An identification error analysis is performed for the proposed substructure method, revealing how uncertain factors (e.g. measurement noise) in the identification process affect the identification accuracy. According to the error analysis, a smart reference selection rule is designed to choose the optimal reference response that further enhances the identification accuracy. Moreover, based on the identification error analysis, explicit formulae are developed to calculate the variances of the parameter identification errors. A ten-story shear structure is used to illustrate the effectiveness of the proposed substructure method. The simulation results show that the method, combined with the reference selection rule, can very accurately identify structural parameters despite large measurement noise. Furthermore, the proposed formulae provide good predictions for the variances of the parameter identification errors, which are vital for providing accurate warnings of structural damage.

Structural Damage Detection Using Wireless Sensor-Actuator Networks

Structural health monitoring (SHM) is a well-established multi-disciplinary research field, in which the goal is to develop technologies and techniques to automatically detect, localize, and classify damage in large structures. This paper is focused, starting with a simple SHM problem and a simple structure, on how wireless sensor networking technologies can help advance SHM. Specifically, a distributed damage detection algorithm is developed based on shifted spectra of response at the sensor nodes. While damage detection using frequency shifts is fairly well-understood in the SHM community, the development here adheres to sensor network architectural principles: the technique is amenable to in-network processing and duty-cycling, and can be implemented on a long-running sensor network. The efficacy is demonstrated using simulations on structural models, and actual measurements on real, albeit simple, structures

Substructure Identification for Shear Structures with Nonstationary Structural Responses

AbstractIn previous studies by the authors, a substructure identification method for shear structures was proposed to identify all structural story stiffness and damping parameters from top to bottom inductively. In the method derivation, the structural responses were required to be wide sense stationary to convert structural dynamic equations to differential equations in the correlation functions of structural responses, which are used to formulate substructure identifications. In this paper, this method is extended to accommodate nonstationary structural responses. A different derivation procedure is adopted to formulate substructure identifications directly from the Fourier transform of the structural dynamic equations, resulting in a formulation nearly the same as its stationary response predecessor. An identification error analysis for the substructure identification method reveals how structural responses affect the identification accuracy. On the basis of this result, a smart reference selection ru...