Multi-sensor measurement of dynamic deflections and structural health monitoring of flexible and stiff bridges

Abstract

We investigated the response of bridges of different types to controlled and to wind and traffic-induced excitations; the emphasis was on deflections, derived from recordings of geodetic sensors and accelerometers (output-only analysis). Our focus was to push the limits of the existing experimental techniques, in order to cover not only flexible, but also stiff structures, and to present independently validated results. Our study focused on a 700m long, thindeck cable-stayed bridge, a stiff steel pedestrian bridge, a historic composite (masonry/steel) train bridge and a 30m long, gradually decaying, currently swaying pedestrian timber bridge. Our basic strategy was first to develop data measurement and processing techniques using controlled (supervised learning) experiments, and then, (1) use collocated, redundant and distributed geodetic sensors (GPS/GNSS and Robotic Total Stations, RTS), as well as accelerometers, in order to record bridge excitations, especially controlled excitations leading to free attenuating oscillations; (2) develop techniques to denoise recordings of various sensors based on structural/logical constraints and sensor fusion, compensating for the weaknesses inherent in each type of sensor), validate results and avoid pitfalls; (3) monitor the episodic and gradual decay of a pedestrian bridge, through repeated surveys under similar loading and environmental conditions and using similar instrumentation. The output of our studies is to confirm the potential of modern sensors to measure, under certain conditions, reliable mm-level dynamic deflections even of stiff structures (3-6Hz dominant frequencies) and to provide firm constraints for structural analysis, including evidence for changes of first modal frequencies produced by structural decay, even to identify dynamic effects such as foundations response to dynamic loading. The first is the problem of metrology, corresponding to questions of the type: what is the range of displacements of a bridge that can be measured by geodetic sensors, whether an apparently “good” measurement of dynamic displacement is reliable, and under which conditions and with which techniques it is possible to measure dynamic deflections of a stiff or a flexible bridge using instantaneous GPS positioning which is contaminated by long-period noise (see Figure 1). The second is the problem of structural significance of measurement-derived displacements. A common question arising is whether and under which conditions analysis of deflection measurements can lead to estimates of natural frequencies of a structure. In this article we review unpublished and previously presented results and ideas from monitoring deflections of several bridges of different types in Greece, both long-period and stiff structures (roughly, modal frequencies below or above 1Hz), using a specific methodology which was developed, and summarize some conclusions of broader importance for the response of bridges to various excitations and for their structural health. Figure 1 GPS (GNSS) recordings are contaminated by long and short-period noise, as shown in (a), in which a white curve indicates the long-period signal. If this last signal is subtracted, a short-period signal is computed as in (b), and using filtering, dynamic deflections are computed (c). If this repeated filtering is reliable, remnant noise is of the order of a few mm and the graph of dynamic displacements will be consistent with accelerograph recordings (d). In (d) a free attenuation oscillation that can provide information on a first natural frequency is marked by a red frame. Modified after Moschas & Stiros (2011). 2 MONITORING METHODOLOGY Our methodology was developed in the last 15 years and has three main characteristics (i) Development of measurement and data processing methodology in representative, controlled experiments in which the measurement conditions and the expected output was known. Under these conditions, the response (accuracy etc.) of the instruments used (mostly GNSS and Robotic Total Stations with upgraded software and high-quality reflectors, in combination with accelerometers) can be assessed, and there can be developed reliable techniques for denoising data (supervising learning approach). This methodology included a computer code for spectral analysis of RTS data characterized by unstable sampling rate (Psimoulis & Stiros, 2012), specifying also statistical uncertainty limits of spectral peaks (Pytharouli & Stiros, 2008). (ii) Use of collocated and redundant sensors of different types to record dynamic and semistatic defections during bridge excitations. This permits to double-check the output of each instrument and avoid specific types of noise, especially blunders (for example, dynamic multipath in GPS (Figure 2; cf. see section // below), which may be interpreted as high amplitude deflection) and to compensate for the weaknesses inherent in each type of sensor (for example in oscillations above 1Hz GPS overestimates peak amplitude while RTS underestimates them). (iii) Measurements satisfying certain conditions, in particular focusing on forced and free attenuating oscillations (see Figure 1d, inset) permitting to directly derive modal characteristics of bridges, and exploitation of structural and logical constraints in the analysis of monitoring data; for example, comparison of measurements during consecutive intervals of no motion/excitation and of controlled excitation, in order to evaluate noise and statistical significance of recorded deflections. Figure 2. Results of an experiment to simulate dynamic multipath, i.e. noise produced by reflections of a passing two-wagon train, recorded by a GPS receiver setup 2m away from the train track on stable ground. Apparent dynamic displacements may be misinterpreted as dynamic deflections of a bridge. Right and left column indicate solutions with two different software packages and show the signature of the two wagons. After Moschas and Stiros 2014 GPSSol. Multipath amplitude is variable, and may range between a few mm to a few meters (Moschas et al, 2013 SSS) 2.1 Controlled experiments to derive measurement methodology (Dynaic multipath??) A wide range of controlled experiments were used to constrain the measuring strategy. These included measurements of known characteristics, for example recordings of dynamic deflections using sensors fixed on a shaking table (Psimoulis et al., 2008), or simulation of GPS measurements next to a passing train (Moschas and Stiros, 2014). In this last case secondary reflections of the satellite signal to the highly reflective surfaces of the train gave the impression of an unrealistically high deflection (Figure 2; see also section 3.2). This is a basic explanation for some cases of abnormally high deflections of stiff bridges that are reported by various authors. An output of this study is to confirm the potential of application of GPS and of RTS in monitoring not only long, high-period bridges, but of stiffer bridges as well, expanding the limits of application of GPS and RTS (Moschas & Stiros, 2011; Stiros & Psimoulis, 2012; Moschas et al., 2013///). Concerning RTS, their main problem is the low measurement rate of commercial instruments. To overcome this problem, we used an upgraded built-in software permitting to collect measurements with a mean rate of 7Hz and a resolution of 0.01sec. This, in combination with high quality reflectors (AGA-type reflectors) offers an accuracy of ±1-2mm for isolated measurements (not mean values) and makes RTS suitable for monitoring of 3-D deflections of relatively stiff structures (Psimoulis & Stiros, 2008). 2.2 Use of collocated instruments Because we are fully aware of the limitations of all sensors (various types of noise/errors, malfunctions, etc.) our field studies was based on collocated sensors, mostly more than one RTS, GPS and accelerometer were set next or on top of the other, in order to limit the effects of sensor malfunction and to compensate for the weaknesses inherent in each type of sensor (Figure 3a). For example, GPS has higher sampling rate (usually 10 to 100Hz for structural monitoring, compared to 1Hz used for conventional geodetic work), but is noisy, while RTS has a smaller sampling rate but lower noise, so their fusion leads to reliable and useful results (Psimoulis & Stiros, 2008). 2.3 Structural constraints and free attenuating oscillations An efficient way to control sensor noise is to compare recordings during intervals of excitation with measurements of no excitation (cf. section 3.3). Furthermore, if it is possible to record the response of a bridge during free attenuating oscillations, confirmed by accelerograph data, and compute its first modal frequency. 3 CASE STUDIES We present results from the monitoring of four bridges in Greece, with quite different structural characteristics. In the monitoring of these cases we adopted/developed the methodology proposed (instrumentation and data processing method). 3.1 The Evripos (Chalkis) cable-stayed bridge The Evripos (Chalkis) cable-stayed bridge is about 700m long with a very thin (45cm) deck, the first cable-stayed bridge constructed in Greece. The dynamic response of this bridge, especially during an earthquake, derived from the analysis of accelerometers and geodetic sensors have been discussed in the past by Lekidis et al (2005). Monitoring results discussed derive from a survey based on several fully or nearly collocated instruments at the midspan of the bridge: force-balance accelerometers, two passive reflectors each sighted by a different RTS, and four GPS receivers, two of which with large chock ring antennas to minimize secondary reflections (multipath). These sensors (Figure 3a), in combinations with sensors on stable ground were focusing on the response of the bridge to traffic, during a wind-free day, and in particular on traffic characterized by intervals of quiescence interrupted by excitations