Institute of Fundamental Technological Research

A railway bridge has been the object of investigation in the context of structural health monitoring (SHM). The current work is focused on utilization of experimental data for refining a numerical model of the structure as well as on tests of dynamic excitations using a controlled hydraulic shaker and passing trains. The numerical model has been matched to experimental measurements using experimental modal analysis - classical and operational. The tailored SHM system for monitoring of the bridge consists of 15 piezoelectric strain sensors taking advantage of wireless communication for data transfer. Experimental responses of the bridge collected by the SHM system are confronted with the ones produced by the FE numerical model of the bridge. The long-term objective of the investigation is to elaborate a method for assessment of structural condition and prediction of remaining lifetime of the bridge.

Bridge Monitoring, Experimental Measurements, Modal Analysis, Wireless SHM

A railway bridge has been the object of investigation since mid 2007 as a response to increasing interest in structural health monitoring (SHM) from Polish Railways. It is a typical 40 m long, steel truss structure spanning a channel in Nieporet near Warsaw. There is over 1500 similar bridges in the railway network in Poland. The integrated system consists of two components – weigh in motion (WIM) part for identification of train load and SHM part for assessing the state of the bridge. Two aspects of wireless transmission are considered – short range (in the vicinity of the bridge, 2.4GHz) and far range (from the bridge to the data analysis center, GSM). The system is designed to be energetically self-sufficient, batteries are recharged by solar panels. Both the subsystems use piezoelectric strain sensors. Numerical model of the bridge corresponds well to the experimental data and provides a good starting point for considering different scenarios of simulated damage in the structure.

SHM, Piezo sensors, Wireless transmission, Bridge dynamics, Railway infrastructure

This paper presents results of in situ investigation of a railway truss bridge in the context of structural health monitoring (SHM). Three experimental methods are examined. Dynamic responses of the bridge recorded by strain gauges are confronted with alternative ways of acquisition using piezoelectric patch sensors and ultrasonic probeheads. All types of sensors produce similar output. Also the corresponding responses of the numerical model of the bridge match experimental data.

The proposed approach assumes that the composite structure is equipped with a specially designed electrical circuit with a 3D grid layout, composed of high resistivity elements embedded in the structure. The special layout of the electrical circuit activated by small currents provides scattered sources of thermal field in the laminate. It is assumed that the circuit elements exhibit failure which is coincident with the commencement of delamination. These breaks in the electrical circuit cause variations in the thermal field which can be observed by a long-wave thermovision camera. The paper is focused on two research aspects. First, some numerical simulations are presented to examine the potential of the idea itself. Next, a simple experiment using a composite sample with a hand-fabricated electrical grid is described. The performance of the grid for an arbitrarily selected position of defect in the investigated composite shows high potential for damage detection.

The problem of modelling and identification of delamination in double-layer beams has been undertaken within the framework of the virtual distortion method. For delamination modelling, a concept of the contact layer has been proposed, assuming simple but effective truss connections. The laminate layers have been modelled with Bernoulli beams. Good correspondence of the delamination model with experiments has been observed despite disregarding the friction between layers. An algorithm for off-line identification of delamination, solving an inverse problem with the use of gradient optimization, has been proposed. For double cantilever beam examples, two co-existing delamination zones have been successfully detected. An idea of on-line identification of delamination has been put forward, too.

Delamination, Double-layer beams, Identification, Inverse problem

The paper is a continuation of research on the application of a structural reanalysis method—the virtual distortion method—to structural health monitoring. The first approach, formulated previously in the time domain, suffered from a considerable numerical cost. In order to reduce it, this paper presents an alternative approach, formulated in the frequency domain thanks to the assumption of using harmonic excitation (quasi-static problem). The hardware devices supposed to collect structural responses are piezoelectric patch sensors. The software tool for damage identification solves a nonlinear least squares optimization problem by employing analytically derived sensitivities. Strains are the analyzed quantities, contributing to the objective function. Considerations are restricted to skeletal structures and a simplified dynamic problem with no damping. Effectiveness of the frequency-domain identification is demonstrated in numerical examples. Experimental verification is envisaged.

Damage identification, Inverse problem, Frequency domain, Skeletal structures, Reanalysis methods

For 20 years of development, the virtual distortion method (VDM) has proved to be a versatile reanalysis tool in various applications, including structures and truss-like systems. This article presents a summary of principal achievements, demonstrating the capabilities of the VDM both in statics and dynamics, in linear and nonlinear analysis. The major advantage of VDM is its exactness and no need for matrix inversion in the reanalysis algorithm. The influence matrix—numerical core of the VDM—contains the whole mechanical knowledge about a structure, by looking at all global responses due to local disturbances. The strength of the method is demonstrated for truss structures.

Exact structural reanalysis, Sherman–Morrison–Woodbury formulas, Nonlinear statics and dynamics, System analysis

Frequency-Based Analysis, Inverse Problem, Piezo Devices, Structural Damage Identification

This article presents two approaches for structural damage identification, each based on a different philosophy. The virtual distortion method (VDM) is a model-updating method of damage assessment, utilizing gradient-based optimization techniques to solve the resulting inverse dynamic problem in the time domain. Case-based reasoning (CBR) is a softcomputing method utilizing wavelet transformation for signal processing and neural networks for training a base of damage cases to use for retrieving a similar relevant case. Advantages and drawbacks of each approach are discussed. Successful calibration of a numerical model from experiments has been shown as a sin equa non for the VDM approach. A numerical example of a beam is presented including a demonstration of the complexity of the inverse problem. Qualitative and quantitative comparisons between the two approaches are made.

damage identification, inverse problem, model updating, soft computing, software tools

A health monitoring tool for leakage identification in water networks is presented. It is assumed that the water heads at the network’s nodes can be measured in different locations of some inspected area. Then, making use of the analytical network model of the actual installation and using the proposed Virtual Distortion Method (VDM) approach, leakages (single as well as in multiple locations, and their intensities) can be detected and identified in the system. The identification methodology takes advantage of a gradient-based optimization technique.

damage identification, water networks, system theory

Two alternative software tools for damage identification are presented. The first tool, developed on the basis of the Virtual Distortion Method (VDM), takes advantage of an analytical formulation of the damage identification problem. Consequently, gradient-based optimization method is applied to solve the resulting dynamic inverse problem in time domain. Finite element model of the structure is necessary for the VDM approach. The second tool utilizes the Case-Based Reasoning (CBR) for damage identification. This method consists in i) extracting principal features of the response signal by wavelet transform, ii) creating a base of representative damage cases, iii) organizing and training the base by neural networks, and finally iv) retrieving and adapting a new case (possible damage) by similarity criteria. Basic description of both approaches is given. A comparison of numerical effectiveness, in terms of accuracy and computational time, is provided for a simple beam structure. Advantages and weaknesses of each approach are highlighted.

Damage Identification, Inverse Dynamic Problem, Software Tools

In this paper we numerically study simple two dimensional frame structure loaded by impulse-like excitations. Various configurations of time duration of a single impact load and location of this excitation are investigated. The aim of this research is to indicate the best possible load case for identification of a specific damage. Two kinds of structural modifications are considered. The first group concerns the element stiffness changes (axial and bending) which can be simulated by alternating the Young‘s modulus. The second group covers the modifications of stiffness nodal connections. In a numerical model, these kinds of defects can be implemented using rotational spring with different characteristics. Obtained selected responses for the original and modified structure are numerically generated.

structural modification, semi-rigid joint, virtual distortion method, gradient-based optimization

This study presents the numerical analysis and experimental tests of a planar frame structure with semi-rigid joints. Based on structural responses the identification of nodal parameters is performed.

Frame structures, Semi-rigid joints, Inverse problem, SHM

The nodal connections in the standard analysis of frame structures are idealized assuming either pinned or fully rigid joints. State of such structural connections is highly important for safe operation of skeletal structures. In this work, the authors propose modeling, detection and identification of semi-rigid joints, i.e. nodal connections covering the range between pinned and fully rigid joints. The presented approach is based on the Virtual Distortion Method (VDM) and dedicated to statically or dynamically loaded two-dimensional frame structures.

In the last years one can observe an increasing interest in structural health monitoring (SHM) from Polish Railways. There are several hundreds of steel truss bridges of various spans and similar topologies in Polish railway infrastructure. One of them, located over a canal in Nieporęt near Warsaw with span of 40m became an object of investigation and implementation of an integrated SHM system. The system consists of two components – weigh in motion (WIM) part for identification of train load and SHM part for assessing the bridge state. The WIM module supplies load data required for SHM inverse analyses, however it can operate as an independent system for monitoring of railway traffic providing information about axle loads and rolling stock identification. Many in-situ installations of SHM systems suffer from a troublesome and time- consuming way of data acquisition via standard cables. In order to facilitate data collection related with this way of acquisition, an alternative solution of wireless transmission of the measured data from the field to analysis centre is proposed. Two aspects of wireless transmission are considered – short range (in the vicinity of the bridge) and far range (from the bridge to the centre of analysis). This paper takes up the practical issue of design and implementation of the integrated SHM system for truss steel railway bridge with a special insight into the monitoring of railway traffic.

Structural Health Monitoring, monitoring of steel railway bridges

The authors propose an idea of monitoring the state of skeletal structures of high importance (e.g. roof structures over large area buildings) with the aim of identification of slowly-developing plastic zones. This is formulated as an inverse problem within the framework of the Virtual Distortion Method, which was used previously to identify stiffness/mass modifications in similar manner. Permanent plastic strains developed in a truss element can be modeled by an initial strain (virtual distortion) introduced to the structure. The formation of subsequent plastic zones in the structure is assumed to be slow. Consequently, the design variable (plastic strain) is time-independent, which makes the inverse analysis efficient. This article presents problem formulation and numerical algorithm for identification of the plastic strains in truss structures. The identification relies on gradient-based optimization. A numerical example is included to demonstrate the efficiency of the algorithm.

In the last years one can observe an increasing interest in structural health monitoring (SHM) from Polish Railways. There are several hundreds of steel truss bridges of various spans and similar topologies in Polish railway infrastructure. One of them, located over a canal in Nieporęt near Warsaw with span of 40m became an object of investigation and implementation of an integrated SHM system.
The system consists of two components – weigh in motion (WIM) part for identification of train load and SHM part for assessing the bridge state. The WIM module supplies load data required for SHM inverse analyses, however it can operate as an independent system for monitoring of railway traffic providing information about axle loads and rolling stock identification.
Many in-situ installations of SHM systems suffer from a troublesome and time-consuming way of data acquisition via standard cables. In order to facilitate data collection related with this way of acquisition, an alternative solution of wireless transmission of the measured data from the field to analysis centre is proposed. Two aspects of wireless transmission are considered – short range (in the vicinity of the bridge) and far range (from the bridge to the centre of analysis).
This paper takes up the practical issue of design and implementation of the integrated SHM system for truss steel railway bridge with a special insight into the monitoring of railway traffic.

SHM systems, monitoring of railway bridges

The paper presents results of in-situ investigation of a railway truss bridge in the context of SHM. Three experimental methods are examined. Dynamic responses of the bridge recorded by strain gauges are confronted with alternative ways of acquisition using piezoelectric sensors and ultrasonic probeheads. Numerical model corresponds to experimental data.

In-situ measurements collected with standard cabling suffer from the serious disadvantage of no automation, which implies frequent visits to the monitored structure in order to gather the requested data. For minimizing the man effort involved, a system of wireless transmission (WT) of in-situ collected data has been proposed. Principal ideas of such system should be pretty universal in a number of applications related to structural health monitoring (SHM). However each WT system should be customized for a specific application to provide the best performance. The proposed WT system is dedicated to rail traffic monitoring and SHM of railway bridges. The idea is to design smart sensors to be mounted on the bridge and equipped with electronic modules for short-range wireless transfer of SHM data. The far-range wireless transfer from the local bridge unit to a remote analysis centre will be performed using the GSM technology.

SHM, monitoring of railway bridges

This paper presents an improved numerical tool for identification of damage in skeletal structures. The problem of identification has been formulated in the time domain within the framework of the Virtual Distortion Method (VDM). VDM generally belongs to fast structural reanalysis methods and can be applied to Structural Health Monitoring problems, among others. The major computational asset of VDM is the influence matrix, containing all the local-global inter-relations for a structure due to given perturbations e.g. initial strain or external force. A non-linear least squares problem with strains, entering the objective function, is the subject of consideration. Strains are used in order to have relatively smooth variations (compared to accelerations) of the analyzed signal in time. The change of stiffness is the design variable. Analytical gradients are implemented in the optimization code based on the Levenberg-Marquardt algorithm with some penalty function terms. The efficiency of the software tool is demonstrated for a numerical example of a 2D truss structure. A breakthrough in terms of computational time reduction has been observed compared to the previously used steepest-descent optimization. The presented software assumes the feasibility of reliable measurements of strains in time for real skeletal structures (e.g. truss bridges). Future research will include experimental verification of the idea with piezoelectric sensors acting as tensometers.