Application of time series analysis for bridge monitoring

Peer reviewedPreprin

Number of successive cycles necessary to achieve stability of selected ground reaction force variables during continuous jumping

Because of inherent variability in all human cyclical movements, such as walking, running and jumping, data collected across a single cycle might be atypical and potentially unable to represent an individual's generalized performance. The study described here was designed to determine the number of successive cycles due to continuous, repetitive countermovement jumping which a test subject should perform in a single experimental session to achieve stability of the mean of the corresponding continuously measured ground reaction force (GRF) variables. Seven vertical GRF variables (period of jumping cycle, duration of contact phase, peak force amplitude and its timing, average rate of force development, average rate of force relaxation and impulse) were extracted on the cycle-by-cycle basis from vertical jumping force time histories generated by twelve participants who were jumping in response to regular electronic metronome beats in the range 2-2.8 Hz. Stability of the selected GRF variables across successive jumping cycles was examined for three jumping rates (2, 2.4 and 2.8 Hz) using two statistical methods: intra-class correlation (ICC) analysis and segmental averaging technique (SAT). Results of the ICC analysis indicated that an average of four successive cycles (mean 4.5 +/- 2.7 for 2 Hz; 3.9 +/- 2.6 for 2.4 Hz; 3.3 +/- 2.7 for 2.8 Hz) were necessary to achieve maximum ICC values. Except for jumping period, maximum ICC values took values from 0.592 to 0.991 and all were significantly ( p <= 0.05) different from zero. Results of the SAT revealed that an average of ten successive cycles ( mean 10.5 +/- 3.5 for 2 Hz; 9.2 +/- 3.8 for 2.4 Hz; 9.0 +/- 3.9 for 2.8 Hz) were necessary to achieve stability of the selected parameters using criteria previously reported in the literature. Using 10 reference trials, the SAT required standard deviation criterion values of 0.49, 0.41 and 0.55 for 2 Hz, 2.4 Hz and 2.8 Hz jumping rates, respectively, in order to approximate the ICC results. The results of the study suggest that the ICC might be a less conservative but more objective method to evaluate stability of the data. Based on these considerations, it can be recommended that a force time history due to continuous, repetitive countermovement jumping should include minimum of four (the average from the ICC analysis) and possibly as many as nine successive jumping cycles (the upper limit of the ICC analysis) to establish stable mean values of the selected GRF data. This information is important for both experimental measurements and analytical studies of GRF signals due to continuous, repetitive countermovement jumping

Identification of unusual events in multi-channel bridge monitoring data using wavelet transform and outlier analysis

Peer reviewedPreprin

Lessons from monitoring the performance of highway bridges

Peer reviewedPreprin

Detection of bridge anomalous behavior and assessment of their impact on structural performance

Peer reviewedPreprin

Vibration testing of a steel girder bridge using cabled and wireless sensors

Being able to significantly reduce system installation time and cost, wireless sensing technology has attracted much interest in the structural health monitoring (SHM) community. This paper reports the field application of a wireless sensing system on a 4-span highway bridge located in Wayne, New Jersey in the US. Bridge vibration due to traffic and ambient excitation is measured. To enhance the signal-to-noise ratio, a low-noise high-gain signal conditioning module is developed for the wireless sensing system. Nineteen wireless and nineteen cabled accelerometers are first installed along the sidewalk of two neighboring bridge spans. The performance of the wireless sensing system is compared with the high-precision cabled sensing system. In the next series of testing, 16 wireless accelerometers are installed under the deck of another bridge span, forming a 4 × 4 array. Operating deflection analysis is successfully conducted using the wireless measurement of traffic and ambient vibrations

Modern facilities for experimental measurement of dynamic loads induced by humans: a literature review.

This paper provides a critical overview of available technology and facilities for determining human-induced dynamic forces of civil engineering structures, such as due to walking, running, jumping and bouncing. In addition to traditional equipment for direct force measurements comprising force plate(s), foot pressure insoles and instrumented treadmills, the review also investigates possibility of using optical motion tracking systems (marker-based and marker-free optoelectronic technology) and non-optical motion tracking systems (inertial sensors) to reproduce contact forces between humans and structures based on body kinematics data and known body mass distribution. Although significant technological advancements have been made in the last decade, the literature survey showed that the state-of-the-art force measurements are often limited to individuals in artificial laboratory environments. Experimental identification of seriously needed group- and crowd-induced force data recorded on as-built structures, such as footbridges, grandstands and floors, still remains a challenge due to the complexity of human actions and the lack of adequate equipment

Ambient vibration re-testing and operational modal analysis of the Humber Bridge

An ambient vibration survey of the Humber Bridge was carried out in July 2008 by a combined team from the UK, Portugal and Hong Kong. The exercise had several purposes that included the evaluation of the current technology for instrumentation and system identification and the generation of an experimental dataset of modal properties to be used for validation and updating of finite element models for scenario simulation and structural health monitoring. The exercise was conducted as part of a project aimed at developing online diagnosis capabilities for three landmark European suspension bridges. Ten stand-alone tri-axial acceleration recorders were deployed at locations along all three spans and in all four pylons during five days of consecutive one-hour recordings. Time series segments from the recorders were merged, and several operational modal analysis techniques were used to analyse these data and assemble modal models representing the global behaviour of the bridge in all three dimensions for all components of the structure. The paper describes the equipment and procedures used for the exercise, compares the operational modal analysis (OMA) technology used for system identification and presents modal parameters for key vibration modes of the complete structure. The results obtained using three techniques, natural excitation technique/eigensystem realisation algorithm, stochastic subspace identification and poly-Least Squares Frequency Domain method, are compared among themselves and with those obtained from a 1985 test of the bridge, showing few significant modal parameter changes over 23 years in cases where direct comparison is possible. The measurement system and the much more sophisticated OMA technology used in the present test show clear advantages necessary due to the compressed timescales compared to the earlier exercise. Even so, the parameter estimates exhibit significant variability between different methods and variations of the same method, while also varying in time and having inherent variability. (C) 2010 Elsevier Ltd. All rights reserved

Real-time performance monitoring of tuned mass damper system for a 183 m reinforced concrete chimney

A 183 m reinforced concrete chimney for a coal-fired power station was instrumented in the latter part of its life during the construction of a replacement chimney. Because of concerns about large-amplitude response induced by interference effects from the new chimney in the prevailing upwind direction, a response monitoring system was installed, quickly followed by a tuned mass damper (TMD) system. As well as providing live display of the chimney response, the monitoring system was also used to check the functioning of the TMD. The monitoring system featured a direct implementation of the stochastic subspace identification procedure in the 'virtual instrument' controlling the system, so that modal damping values for the system were displayed automatically, in real-time. The system thus provided an immediate visual indication of increased damping levels during strong winds, showing the correct functioning of the TMD. The paper describes the chimney, the monitoring system and its installation, the data processing and system identification procedure, together with performance data before, during and after installation of the TMD. (C) 2009 Elsevier Ltd. All rights reserved

Real-life measurement of tri-axial walking ground reaction forces using optimal network of wearable inertial measurement units

Monitoring natural human gait in real-life environment is essential in many applications including quantification of disease progression, and monitoring the effects of treatment and alteration of performance biomarkers in professional sports. Nevertheless, reliable and practical techniques and technologies necessary for continuous real-life monitoring of gait is still not available. This paper explores in detail the correlations between the acceleration of different body segments and walking ground reaction forces GRF( t )in three dimensions and proposes three sensory systems, with one, two and three inertial measurement units (IMUs), to estimate GRF( t )in the vertical (V), medial-lateral (ML) and anterior-posterior (AP) directions. The NARMAX non-linear system identification method was utilized to identify the optimal location for IMUs on the body for each system. A simple linear model was then proposed to estimate GRF( t )based on the correlation of segmental accelerations with each other. It was found that, for the three-IMU system, the proposed model estimatedGRF( t )with average peak-to-peak normalized root mean square error (NRMSE) of 7%, 16% and 18% in V, AP and ML directions, respectively. With a simple subject-specific training at the beginning, these errors were reduced to 7%, 13% and 13% in V, AP and ML directions, respectively. These results were found favorably comparable with the results of the benchmark NARMAX model, with subject-specific training, with 0% (V), 4% (AP) and 1% (ML) NRMSE difference