A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge

© The Author(s) 2018. A large-scale cable-stayed bridge in the state of New South Wales, Australia, has been extensively instrumented with an array of accelerometer, strain gauge, and environmental sensors. The real-time continuous response of the bridge has been collected since July 2016. This study aims at condition assessment of this bridge by investigating three aspects of structural health monitoring including damage detection, damage localization, and damage severity assessment. A novel data analysis algorithm based on incremental multi-way data analysis is proposed to analyze the dynamic response of the bridge. This method applies incremental tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies. A total of 15 different damage scenarios were investigated; damage was physically simulated by locating stationary vehicles with different masses at various locations along the span of the bridge to change the condition of the bridge. The effect of damage on the fundamental frequency of the bridge was investigated and a maximum change of 4.4% between the intact and damage states was observed which corresponds to a small severity damage. Our extensive investigations illustrate that the proposed technique can provide reliable characterization of damage in this cable-stayed bridge in terms of detection, localization and assessment. The contribution of the work is threefold; first, an extensive structural health monitoring system was deployed on a cable-stayed bridge in operation; second, an incremental tensor analysis was proposed to analyze time series responses from multiple sensors for online damage identification; and finally, the robustness of the proposed method was validated using extensive field test data by considering various damage scenarios in the presence of environmental variabilities

Non-contact based structural damage assessment using stochastic subspace identification and finite element model updating.

This research proposed and verified an innovative method to identify and locate structural damage using only the response of operational vibration, that is the displacement acquired by a non-contact optical method. The most efficient and economical way to detect damage within the structure is to monitor its structural health while in operation. However, the uncertainties and the randomness of ambient vibrations due to the operation and environments cause a challenge in conducting the operational analysis. Current technology limits the ability to collect data on the properties of the structure without the interruption of operation. Frequencies and mode shapes have been widely used in structural damage detection, but they are not sensitive enough and cannot provide sufficient information for identifying damage locations and their quantification. Therefore, the goal of this research is to design and verify a method to detect the damage, as well as its location and severity, of structures in operation without any physical contacts for data acquisition (i.e., non-contact based structural health monitoring (SHM)). Three algorithms are integrated into this SHM process. The first algorithm is the determination of structural characteristics (frequencies and mode shapes) of a vibrating structure from output-only data. Stochastic Subspace Identification (SSI) method is applied to measured displacements over time to extract the structural characteristics. The second algorithm is to estimate the scaling factor. The mode shapes obtained from the output-only model analysis are unscaled due to the absence of the information of input excitation forces. Mass Change Modal Scale (McMS) algorithm is used to estimate the modal scaling factors and determine the scaled mode shapes. The third algorithm is to estimate the structural system matrices (i.e., mass and stiffness matrices) and assess the damages. A Finite Element Model Updating (FEMU) is applied and the system matrices are updated from frequencies and scaled mode shapes. The damage within the structure can then be detected by analysing changes in mass and stiffness matrices. All three phases are verified by numerical simulation and laboratory experiments with deflections acquired by non-contact optical methods through video system. At last, to achieve the non-contact based SHM, a modal scaling method based on temperature change is proposed and verified by numerical simulation. Experimental program reveals that the proposed algorithm using McMS method is applicable to detect damage locations and their mass losses. With proposed non-contacted based SHM, the limitations of contact based sensor can be addressed, and the structural damage can be assessed without any interruption of structure operation

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Wireless sensor networks and structural health monitoring: Experiences with slab track infrastructures

Slab track systems have the potential to become a more sustainable option for high-speed railway infrastructures than traditional ballasted tracks. Traditionally, the systems that monitor these infrastructures have been costly, but advances in the last few decades have made the use of wireless sensor networks within these infrastructures a feasible solution that can be used to evaluate their degradation for failure detection and prediction. Since the cost of these systems is steadily decreasing, it is now possible to use permanent wireless sensor networks as an integral part of the overall system to pave the way for smart infrastructures that can get real-time information about the structural health of the infrastructure at a relatively low cost. In order to show the suitability of this kind of system to monitor the structural health, three demonstrators, developed in the context of the FASTRACK project, related to the design and construction of a monitoring system for slab track systems that measures vibrations and displacements in the track, are presented. FASTRACK uses an innovative approach where data read by sensors are sent to passing trains, which are used as data mules to upload the information to a remote server. On arrival at the station, the data are stored in a database, which is queried by an application to extract relevant information by means of analysis algorithms to detect and predict failures. The first real scenario tests the limits of the system under stress situations. The second one tests the system in an actual, installed slab track to analyze the suitability of the communication architecture and to study a transition zone between slab tracks to a ballast track. The last scenario deals with the data mule performance tests

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Correlating low energy impact damage with changes in modal parameters: diagnosis tools and FE validation

This paper presents a basic experimental technique and simplified FE based models for the detection, localization and quantification of impact damage in composite beams around the BVID level. Detection of damage is carried out by shift in modal parameters. Localization of damage is done by a topology optimization tool which showed that correct damage locations can be found rather efficiently for low-level damage. The novelty of this paper is that we develop an All In One (AIO) package dedicated to impact identification by modal analysis. The damaged zones in the FE models are updated by reducing the most sensitive material property in order to improve the experimental/numerical correlation of the frequency response functions. These approximate damage models(in term of equivalent rigidity) give us a simple degradation factor that can serve as a warning regarding structure safety

Cracking assessment in concrete structures by distributed optical fiber

In this paper, a method to obtain crack initiation, location and width in concrete structures subjected to bending and instrumented with an optical backscattered reflectometer (OBR) system is proposed. Continuous strain data with high spatial resolution and accuracy are the main advantages of the OBR system. These characteristics make this structural health monitoring technique a useful tool in early damage detection in important structural problems. In the specific case of reinforced concrete structures, which exhibit cracks even in-service loading, the possibility to obtain strain data with high spatial resolution is a main issue. In this way, this information is of paramount importance concerning the durability and long performance and management of concrete structures. The proposed method is based on the results of a test up to failure carried out on a reinforced concrete slab. Using test data and different crack modeling criteria in concrete structures, simple nonlinear finite element models were elaborated to validate its use in the localization and appraisal of the crack width in the testing slab.Peer ReviewedPostprint (author’s final draft

Application of distributed optical fiber sensors for the health monitoring of two real structures in Barcelona

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Structure and Infrastructure Engineering on 2018, available online at: http://www.tandfonline.com/10.1080/15732479.2018.1438479The versatility and ease of installation of Distributed Optical Fibre Sensors (DOFS) compared with traditional monitoring systems are important characteristics to consider when facing the Structural Health Monitoring (SHM) of real world structures. The DOFS used in this study provide continuous (in space) strain data along the optical fibre with high spatial resolution. The main issues and results of two different existing structures monitored with DOFS, are described in this paper. The main SHM results of the rehabilitation of an historical building used as hospital and the enlargement of a pre-stressed concrete bridge are presented. The results are obtained using a novel DOFS based on an Optical Backscattered Reflectometry (OBR) technique. The application of the optical fibre monitoring system to two different materials (masonry and concrete) provides also important insights on the great possibilities of this technique when monitoring existing structures. In fact, the influence of strain transfer between the DOFS and the bonding surface is one of the principal effects that should be considered in the application of the OBR technique to real structures. Moreover, and because structural surfaces generally present considerable roughness, the procedure to attach the optical fibre to the two monitored structures is described.Peer ReviewedPostprint (author's final draft