Piervincenzo Rizzo

Lingyu (Lucy) Yu

Alessandro Marzani

Structural Health Monitoring of Civil Structures: New Methodologies and Field Applications 2012

Guided wave technique is an efficient method for monitoring structural integrity by detecting and forecasting possible damages in distributed pipe networks. Efficient detection depends on appropriate selection of guided wave modes as well as signal processing techniques. Fourier analysis and wavelet analysis are two popular signal processing techniques that provide a flexible set of tools for solving various fundamental problems in science and engineering. In this paper, effective ways of using Fourier and Wavelet analyses on guided wave signals for detecting defects in steel pipes are discussed for different boundary conditions. This research investigates the effectiveness of Fourier transforms and Wavelet analysis in detecting defects in steel pipes. Cylindrical Guided waves are generated by piezo-electric transducers and propagated through the pipe wall boundaries in a pitch-catch system. Fourier transforms of received signals give information regarding the propagating guided wave modes which helps in detecting defects by selecting appropriate modes that are affected by the presence of defects.  Continuous wavelet coefficients are found to be sensitive to defects. Several types of mother wavelet functions such as Daubechies, Symlet, and Meyer have been used for the continuous wavelet transform to investigate the most suitable wavelet function for defect detection. This research also investigates the effect of different boundary conditions on wavelet transforms for different mother wavelet functions.

Rais Ahmad

Tribikram Kundu

Structural Health Monitoring of Steel Pipes under Different Boundary Conditions and Choice of Signal Processing Techniques

This paper describes the application of a probabilistic structural health monitoring (SHM) method to detect global damage in a highway bridge in Connecticut. The proposed method accounts for the variability associated with environmental and operational conditions. The bridge is a curved three-span steel dual-box girder bridge located in Hartford, Connecticut. The bridge, monitored since Fall 2001, experienced a period of settling in the Winter of 2002-2003. While this change was not associated with structural damage, it was observed in a permanent rotation of the bridge superstructure. Three damage measures are identified in this study: the value of fundamental natural frequency determined from peak picking of autospectral density functions of the bridge acceleration measurements; the magnitude of the peak acceleration measured during a truck crossing; the magnitude of the tilt measured at 10-minute intervals. These damage measures, including thermal effects, are shown to be random variables and associated P values are calculated to determine if the current probability distributions are the same as the distributions of the baseline bridge data from 2001. Historical data measured during the settling of the bridge is used to verify the performance of the bridge, and the field implementation of the proposed method is described.

Adam Scianna

Zhaoshuo Jiang

Richard Christenson

John DeWolf

Implementation of a Probabilistic Structural Health Monitoring Method on a Highway Bridge

Major threats to bridges primarily consist of the aging of the structural elements, earthquake-induced shaking and standing waves generated by windstorms. The necessity of information on the state of health of structures in real-time, allowing for timely warnings in the case of damaging events, requires structural health monitoring (SHM) systems that allow the risks of these threats to be mitigated. Here we present the results of a short-duration experiment carried out with low-cost wireless instruments for monitoring the vibration characteristics and dynamic properties of a strategic civil infrastructure, the Adolphe Bridge in Luxembourg City. The Adolphe Bridge is a masonry arch construction dating from 1903 and will undergo major renovation works in the upcoming years. Our experiment shows that a network of these wireless sensing units is well suited to monitor the vibration characteristics of such a historical arch bridge and hence represents a low-cost and efficient solution for SHM.

Adrien Oth

Matteo Picozzi

Structural Health Monitoring Using Wireless Technologies: An Ambient Vibration Test on the Adolphe Bridge, Luxembourg City

Monitoring of fatigue cracking in steel bridges is of high interest to many bridge owners and agencies. Due to the variety of deterioration sources and locations of bridge defects, there is currently no single method that can detect and address the potential sources globally. In this paper, we presented a dual mode sensing methodology integrating acoustic emission and ultrasonic wave inspection based on the use of low-profile piezoelectric wafer active sensors (PWAS). After introducing the research background and piezoelectric sensing principles, PWAS crack detection in passive acoustic emission mode is first presented. Their acoustic emission detection capability has been validated through both static and compact tension fatigue tests. With the use of coaxial cable wiring, PWAS AE signal quality has been improved. The active ultrasonic inspection is conducted by the damage index and wave imaging approach. The results in the paper show that such an integration of passive acoustic emission detection with active ultrasonic sensing is a technological leap forward from the current practice of periodic and subjective visual inspection and bridge management based primarily on history of past performance.

Lingyu Yu

Sepandarmaz Momeni

Valery Godinez

Victor Giurgiutiu

Paul Ziehl

Jianguo Yu

Dual Mode Sensing with Low-Profile Piezoelectric Thin Wafer Sensors for Steel Bridge Crack Detection and Diagnosis

Some recent advances of a recently developed structural health assessment procedure proposed by the research team at the University of Arizona, commonly known as generalized iterative least-squares extended Kalman filter with unknown input (GILS-EKF-UI) are presented. The procedure is a finite elements-based time-domain system-identification technique. It can assess structural health at the element level using only limited number of noise-contaminated responses. With the help of examples, it is demonstrated that the structure can be excited by multiple loadings simultaneously. The method can identify defects in various stages of degradation in single or multiple members and also relatively less severe defect. The defective element(s) need not be in the substructure, but the defect detection capability increases if the defect spot is close to the substructure. Two alternatives are suggested to locate defect spot more accurately within a defective element. The paper advances several areas of GILS-EKF-UI to assess health of large structural systems.

Ajoy Kumar Das

Achintya Haldar

Subrata Chakraborty

Health Assessment of Large Two Dimensional Structures Using Limited Information: Recent Advances

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Advances in Civil Engineering

Structural Health Monitoring of Civil Structures: New Methodologies and Field Applications 2012

Structural Health Monitoring of Civil Structures: New Methodologies and Field Applications 2012

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