Time-Frequency Methods for Structural Health Monitoring

Proceedings of the 2nd European Workshop on Structural Health Monitoring, Munich, Germany, 2004, pp. 836-843, doi: 10.13140/2.1.1043.1044, 2004

Despite the recent considerable advances in structural health monitoring (SHM) technology applied to civil infrastructure, converting large amount of data from operating SHM systems into usable information and knowledge still remains a great challenge. This study attempts to address this problem through analysis of time histories of static strain data recorded by an SHM system installed in a major bridge structure and operating continuously for a long time. The reported efforts establish a vector seasonal autoregressive integrated moving average (ARIMA) model for the recorded multi-channel strain signals. An important feature of the proposed ARIMA model is that its parameters are allowed to vary with time and are identified on-line using an adaptive Kalman filter approach. By observing various changes in the model parameters, unusual events as well as structural change or damage sustained by the structure can be revealed. Such events or structural changes may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. The proposed method has been tested using known events recorded during construction of the bridge, and later used for detection of anomalous post-construction incidents.

Bulletin of Earthquake Engineering, 2014

The dynamic characteristics of a structure are commonly defined by its modal properties: modal frequencies, damping ratios, and mode shapes. Significant changes in modal properties of a structure after an extreme event, such as an earthquake, or during its service life can be strongly related to damage in the structures. This makes it crucial that the modal properties are accurately estimated and continuously tracked to detect any changes by the structural health monitoring (SHM) system. This paper introduces an algorithm and a MATLAB-based software that includes modules for real-time data processing, modal identification, damage detection, and stakeholder warnings for vibration-based SHM systems. The data processing and modal identification techniques used are based on the classical and stochastic techniques, and utilize running time windows to keep track of time variations in real-time data. The damage detection algorithm makes use of inter-story drifts to detect and locate damage. Since the calculation of inter-story drifts involves double integration and subtraction of acceleration signals, it is extremely hard to get accurate values of inter-story drifts in real-time monitoring. To improve the accuracy, inter-story drifts are calculated for each mode of the structure separately, and then combined synchronously. The displacements at non-instrumented floors are estimated by assuming that the mode shapes can be approximated as a linear combination of those of a shear beam and a bending beam. A software package, REC_MIDS, is developed for this purpose, and it has been operating in a large number of different structures with SHM systems in Turkey (tall buildings, suspension bridges, mosques, museums), and in seven high-rise buildings in UAE.

Springer Series in Reliability Engineering, 2011

This paper focuses on the application of two methodologies, namely modal curvature and instantaneous phase, for bridge health monitoring. The algorithms are applied to the structural vibration data acquired from numerical simulation of a benchmark bridge, which includes specified damage scenarios. The modal curvature method utilizes the second derivative of structural mode shapes acquired using the peak picking method. Instantaneous phase information is derived through the Hilbert transform of intrinsic mode functions generated from the decomposition of vibration data. The modal curvature method demonstrates ability to detect and locate damage, but needs further development to predict damage severity consistently. The instantaneous phase method fails to detect damages.

2022

Safety of dams and other hydraulic structures is a complex procedure that must consider the individual characteristics of each structure and provide an insight in the structural health at every stage of the structure's life cycle. Failures of structures permanently or temporarily retaining water may cause large economic damage, environmental disasters, and loss of lives. An engineering design should, therefore, guarantee maximum security of such structures or maximize their reliability not only in ordinary operating conditions but also under extreme hydrological load. By performing structural heath monitoring (SHM), the safety can be optimized, including the performance and life expectancy of a structure by adopting an appropriate methodology to observe the identified failure modes for a selected dam type. To adopt SHM to hydraulic structures it is important to broaden the knowledge and understanding of the ageing processes on hydraulic structures, which can be achieved by laboratory testing and application and development of novel monitoring techniques, e.g., vibration monitoring. In Slovenia, we are increasingly faced with the problem of ageing of dam structures. At the same time, we are also faced with changes in the environment, especially with the variability in time-dependent loads and with new patterns of operation on dams used for hydropower, with several starts and stops of turbines happening on a daily basis. These changes can lead to a decrease in structural and operational safety of dams. In this paper we propose a methodology where the dynamic response of concrete dams is continuously monitored in few locations on the dam using accelerometers, while all significant structural members are measured in discrete time intervals using portable vibrometers. We focused on run-of-the-river dams, which are a common dam type in Slovenia. The pilot case for the system is lower Sava River with a cascade of 5 dams used for hydropower.

Applied Sciences, 2021

Recently, a number of authors have been focusing on drive-by monitoring methods, exploiting sensors mounted on the vehicle rather than on the bridge to be monitored, with clear advantages in terms of cost and flexibility. This work aims at further exploring the feasibility and effectiveness of novel tools for indirect health monitoring of railway structures, by introducing a higher level of accuracy in damage modelling, achieve more close-to-reality results. A numerical study is carried out by means of a FE 3D model of a short span Warren truss bridge, simulating the dynamic interaction of the bridge/track/train structure. Two kinds of defects are simulated, the first one affecting the connection between the lower chord and the side diagonal member, the second one involving the joint between the cross-girder and the lower chord. Accelerations gathered from the train bogie in different working conditions and for different intensities of the damage level are analyzed through two time-...

Advances in Civil Engineering, 2011

Real-time monitoring of civil infrastructure provides valuable information to assess the health and condition of the associated systems. This paper presents the recently developed shape acceleration array (SAA) and local system identification (SI) technique, which constitute a major step toward long-term effective health monitoring and analysis of soil and soil-structure systems. The SAA is based on triaxial micro-electro-mechanical system (MEMS) sensors to measure in situ deformation (angles relative to gravity) and dynamic accelerations up to a depth of one hundred meters. This paper provides an assessment of this array's performance for geotechnical instrumentation applications by reviewing the recorded field data from a bridge replacement site and a full-scale levee test facility. The SI technique capitalizes on the abundance of static and dynamic measurements from the SAA. The geotechnical properties and constitutive response of soil contained within a locally instrumented ...

2006

Despite the recent considerable advances in structural health monitoring (SHM) of civil infrastructure, converting large amount of data from SHM systems into usable information and knowledge remains a great challenge. This paper addresses the problem through analysis of time histories of static strain data recorded by an SHM system installed in a major bridge structure and operating continuously for a long time. The reported study formulates a vector seasonal autoregressive integrated moving average (ARIMA) model for the recorded strain signals. The coefficients of the ARIMA model are allowed to vary with time and are identified using an adaptive Kalman filter. The proposed method has been used for analysis of the signals recorded during construction and service life of the bridge. By observing various changes in the ARIMA model coefficients, unusual events as well as structural change or damage sustained by the structure can be revealed.

2012

V. Volkovas*, K. Petkevičius**, M. Eidukevičiūtė***, T.C. Akinci**** *Kaunas University of Technology, Technological Systems Diagnostics Institute, Kaunas, Lithuania, E-mail: [email protected] **Kaunas University of Technology, Technological Systems Diagnostics Institute, Lithuania, E-mail: [email protected] ***Kaunas University of Technology, Technological Systems Diagnostics Institute, Lithuania, E-mail: [email protected] ****Kirklareli University, Engineering Faculty, Department of Electrical & Electronics Engineering, Kirklareli, Turkey, E-mail:[email protected]

Mechanical Systems and Signal …, 2011

Automated modal parameter identification of civil engineering structures has been analyzed in a previous paper. An original algorithm, named LEONIDA, working in frequency domain, has been presented and a number of test cases have been discussed in order to point out advantages and drawbacks. It has been demonstrated that LEONIDA represents a promising and reliable tool, in particular for modal testing. Conversely, integration of such a procedure into a fully automated structural health monitoring (SHM) system has shown that it can be used as modal information engine, but length of record durations, amount of computational burden and response time lead to recognize that serious drawbacks and limitations exist for a class of applications, such as continuous monitoring of structures in seismically prone areas.

International Journal of Civil and Structural Engineering, 2012

Due to damage, vibrations of bridge piers compared with undamaged state would be changed. A new signal-based algorithm is proposed to extract feature and detect damage in complex bridges. According to the proposed algorithm, it is necessary to vibrate the bridge before and after damage by exciting force and record responses at the middle and top of the piers. For this purpose, sine and cosine transient forces were applied to the analytical model of Ghotour Bridge and the signals of pier responses were recorded. Using reduced interference distribution, the response signals were processed and time-frequency plans were calculated. Modified matrix subtraction method was proposed to detect damage. Based on the results, damage was identified and located with good accuracy. The proposed algorithm is an outputonly method and in practice there is no need to create an analytical model of an existing complex bridge for damage detection.

2014

Structural health monitoring (SHM) systems is a relatively new discipline, studying the structural condition of buildings and other constructions. Current SHM systems are either wired or wireless, with a relatively high cost and low accuracy. This thesis exploits a blend of digital signal processing methodologies, for structural health monitoring (SHM) and develops a wireless SHM system in order to provide a low cost implementation yet reliable and robust. Existing technologies of wired and wireless sensor network platforms with high sensitivity accelerometers are combined, in order to create a system for monitoring the structural characteristics of buildings very economically and functionally, so that it can be easily implemented at low cost in buildings. Well-known and established statistical time series methods are applied to SHM data collected from real concrete structures subjected to earthquake excitation and their strong and weak points are investigated. The necessity to combine parametric and non-parametric approaches is justified and to this direction novel and improved digital signal processing techniques and indexes are applied to vibration data recordings, in order to eliminate noise and reveal structural properties and characteristics of the buildings under study, that deteriorate due to enviromental, seismic or anthropogenic impact. A characteristic and potential harming specific case study is presented, where consequences to structures due to a strong earthquake of magnitude 6.4 M are investigated. Furthermore, is introduced a seismic influence profile of the buildings under study related to the seismic sources that exist in the broad region of study.

Mechanika, 2012

TJPRC, 2013

Structures are normal or special; these are precious part and are promptly associated with living as well as non living things. Sometimes minute fault inside the structure might affect whole body and it would lead to collapse the structure which might create a significant loss of property and human beings too. So, increased awareness of structural Health Monitoring Techniques (SHM) gives an idea and remedies for the concerned defect due to aging, deterioration and fault during construction. Previous day’s people used just a visual inspection for defect detection but extreme and worst damage in infrastructure leads to invent new technologies for the recognition of new methods on Structural Health Monitoring as a damage detection tools. Different kind of sensors is linked with computer system along with special hardware and software which gives the signature and helps to point out the risk zone. This paper emphasis on wired and wireless techniques under which several sub techniques like Impedance-Based, Nondestructive Evaluation using vibration signature, Limit strain measurement, Data fusion method, Inverse method etc studied and their comparative study on the performance based approach for the infrastructure like Building, Bridges, Towers are noted which most likely concerned with civil infrastructure. This paper mainly emphasis on the presence of different SHM Techniques briefly on one paper which might give access for knowing it in a glance.

Smart Materials and Structures, 2006

... approach to damage detection, which does not use the modal characteristics, was ... Continuouslyoperating SHM systems generally produce various 'raw' signals, such as displacements ... is classified as temporary or permanent and quantified using the intervention analysis. 3.1. ...