Performance Monitoring of a Short-Span Integral-Abutment Bridge Using Wireless Sensor Technology

Transcription

1 Performance Monitoring of a Short-Span Integral-Abutment Bridge Using Wireless Sensor Technology ABSTRACT: Michael V. Gangone, Matthew J. Whelan, Michael P. Fuchs, Kerop D. Janoyan Clarkson University, Department of Civil and Environmental Engineering 8 Clarkson Avenue Box 5710, Potsdam, NY Phone: (315) Fax: (315) {gangonmv, whelanmj, fuchsmp, kerop}@clarkson.edu Discussed in this paper is the implementation of a wireless sensor system for performance monitoring of bridges. The advanced wireless sensor system, developed at Clarkson University s Laboratory for Intelligent Infrastructure and Transportation Technologies (LIITT), allows for structural monitoring of bridges. A short-span integralabutment bridge located in New York State is instrumented with a wireless sensor system measuring acceleration, and strain to monitor the behavior of the structure under various loading conditions including ambient, environmental and traffic loading. Strain and acceleration measurements are recorded simultaneously and in real time to validate various performance characteristics of the bridge, including load distribution along an interior girder, as well as additional stiffness factors (end fixity and composite action of the beams and bridge deck), using existing bridge load testing and condition evaluation guidelines used by the New York State Department of Transportation (NYSDOT) and American Association of State Highway and Transportation Officials (AASHTO). Additionally, acceleration measurements are used to extract the superstructure s first five natural frequencies and corresponding mode shapes. Results are compared to a developed Finite Element Method (FEM) model based on the bridge as built drawings. Keywords: Bridge monitoring, Strain, Acceleration, Wireless, Ambient, Integral abutment INTRODUCTION: Many structures around the world are deteriorating due to environmental impacts, long term use and construction defects. Researchers are working to develop methods of structural monitoring to allow the complete and accurate assessment of structural performance in a non-destructive manner. With more than 27 percent of the 590,750 bridges in the United States classified as structurally deficient or obsolete (ASCE, 2005), new diagnostic tools to locate and assess damage for repair is crucial. A common method of structural condition assessment by many state transportation agencies is through manual local and visual inspection techniques by at least one licensed professional engineer. However, due to the limiting constraints and subjectivity on the process, visual inspections alone are not always adequate since they do not provide a complete depiction of the true structural condition. Time constraints as well as lack of accessibility to hidden parts of the structure make it difficult to identify every such defect that may lead to eventual structural failure. In 2001, the Federal Highway Administration (FHWA) concluded a study which found that 56 percent of medium to short span bridges given an average condition rating were improperly assessed (Phares et al., 2001). A robust monitoring system is needed to overcome the difficulty of determining structural defects due to the many constraints outlined as well as the subjectivity involved in the process(frasier, 2006). Structural monitoring is a widely researched topic among many researchers today. A network of sensors collecting measurements and software to interpret the results combined with data analysis methodologies are the essential components of a strong system. Through the use of both accelerometers and strain measuring devices, the behavior of a structure under various loading conditions can be obtained. Accelerometers capture the dynamic characteristics of the structure under ambient and forced vibrations allowing, among other things, the determination of the modal properties (mode shapes, damping ratio and natural frequencies). Strain measurements provide insight into the performance of the structure by determining such behaviors as stresses, moments, impact factor, load

2 transfer and stiffness that can either verify a design method or simply indicate the level of service life remaining in the structure. Whether utilizing global or local monitoring methodologies, providing a greater number of sensors and sensor types (i.e. accelerometers, strain transducers, thermocouples etc.) results in an improved overall representation to the structural performance. Currently, many state agencies such as the New York State Department of Transportation (NYSDOT) utilize load testing with strain transducers to measure the performance and capacity of a bridge. Load distribution, dynamic impact factors, end fixity levels and composite action between the deck and girders are evaluated to illustrate the structural stiffness as well as load transfer and redundancy of the system. California Department of Transportation (Caltrans) employs accelerometers to measure the affects of seismic activity to many structures. This paper focuses on the measurement of both acceleration and strain of a short span integral abutment bridge in New York State using a developed wireless sensor system. As this deployment was the first with the developed system, an initial performance evaluation is of great interest. SENSOR IMPLEMENTATION AND DEVELOPMENT Wireless Sensor Development Performance monitoring methods are critical in assessing the performance and condition of a structure. With the rising demand for technologies to improve the accuracy of structural evaluations, many institutions are devising ways to efficiently and effectively monitor the effects of different loading scenarios. A Wireless Sensor System (WSS) which includes a dual axis accelerometer, strain transducer, and a custom conditioning board has been developed in the Laboratory for Intelligent Infrastructure and Transportation Technologies (LIITT) at Clarkson University. An accelerometer and strain transducer connected to a single conditioning board that attaches to a mote, sending the signal wirelessly in packets to another mote connected to a CPU where the data is collected and processed by a custom software platform. The conditioning boards permit readings to be sampled at 1.0 khz, and then digitally filtered. This provides for a more accurate description of the behavior of the structure, in particular the dynamic response. A total of ten wireless units, consisting of the accelerometer, strain transducer and custom conditioning system were developed and used in the monitoring. All ten units can be transmitting simultaneously in real time to a single mote which is externally connected to the CPU. For more information on the developed wireless system see Whelan et al., (2007a) and (2007b). Typical Bridge Deployment A 56 foot span integral abutment bridge located in St. Lawrence County New York (Wright Road crossing Trout Brook) was instrumented with the developed wireless sensor technology. The deployment took place in August 2006 and was the first field deployment of the developed system. The bridge consist of a reinforced concrete deck on four (4) W36x135 galvanized steel girders, cast into the abutments. A low traffic volume and primarily light weight vehicles, such as cars, SUVs and pickup trucks, comprise the typical everyday bridge loading. The sensors were deployed in locations to capture maximum response, namely near the mid-span and ends where maximum strain measurements are likely to occur. A shift in the neutral axis location for additional stiffness contributions by the bridge deck to the girder stiffness were determined by placement of the strain transducers at the top and bottom flange at the ends. This configuration aided in giving a strain profile along the depth of the beam. The top flange of the mid-span was not monitored due to restrictions in sensor mounting. Two additional strain transducers were located at the quarter spans to determine if a change in inflection (curvature) could be detected. A total of eight strain transducers spaced at 6 foot intervals were placed along a single interior beam, with one additional sensor at the mid-span of the neighboring interior beam. This provides some insight into the load transfer to the neighboring beam. At the time of the deployment, one strain sensor was found to be malfunctioning thus leaving nine available for monitoring. A second deployment was completed in September 2006 with 20 units consisting of 11 strain transducers with single axis acceleration, and the remaining 9 units with dual axis acceleration measurements. While this paper will focus on the 10 unit deployment, information from second deployment can be found in Whelan et. al., 2007a. For this exercise the vertical accelerations were measured simultaneously with strain measurements. Eight wireless sensors were instrumented at 6 foot intervals along the same interior beam as the strain transducers. The remaining two accelerometers were placed on the neighboring beam with the lone strain transducer. Figure 1 shows the sensor layout along the two interior beams along with a single node unit that includes the wireless mote,

3 accelerometer, and strain transducer. This instrumentation plan allows for the determination of modal properties, in particular natural frequencies and mode shapes (a) (b) Wireless Mote Accelerometer (c) Figure 1: (a) Sensor layout on bridge (b) Field deployment (photo from below bridge, NOTE: unit 2 not out of photo) (c) Details of a single sensor node. ANALYSIS OF RESULTS Strain Transducer Located within a rural portion of the Town of Potsdam in St. Lawrence County, New York, this bridge experiences low levels of traffic excitation. Ambient loading, from typical traffic loading and environmental effects, were the primary loads monitored with the sensor system. The expected responses from many of the strain sensors were captured at their respective locations. With an integral abutment design, negative strains are predictable at the bottom flange near the supports and positive within the span between the inflection points. Furthermore, it was expected that the mid-span strains would be higher than the remaining locations away from the ends. Thirteen separate 3-minute intervals of measurements were taken where any loading within the time span was recorded. Results from the strain sensors indicate a high level of noise picked up by the sensors. A sample of the recorded strain measurements are shown in Figure 2. It is important to note that the strain transducers use reverse sign convention and thus as the measurements show negative the actual value is positive. Channels 1, 4, 6, and 7 all display positive strain peaks, corresponding to vehicles crossing, as they are within the inflection point boundaries. Also the peak strains are consistent with the expected results. Channels 4 and 7 are both located 19 feet from the supports, and both demonstrate similar responses in strain magnitudes. Channel 6, located at 31 feet from the south end depicts a higher strain reading than 4 and 7. The highest readings however are located at 25 feet from the south end as it is closest to the mid-span. In short, the strains beyond the inflection points are increasing as they approach the mid-span. This is a encouraging sign in the sensor development as the closer to the mid-span the sensor, the greater the strain should be due to a higher moment generated. The maximum readings varied in the range of 3 to 5 micro strains for all thirteen tests from vehicle loading. The remaining channels recorded predominantly noise, or

4 excessively low strain readings, making them hard to determine. More conclusive results would be obtained with larger weight vehicles as the low strains are not adequate for obtaining load testing values. Figure 2: Recorded strain measurements The accelerometers showed strong acceleration responses under vehicle traffic. While the bridge was not excited at large forced vibrations, the small acceleration produced were stilled captured. Figure 3 illustrates the response for the acceleration at location 6 (31 feet) during test 7. A higher vertical acceleration is seen at this location compared to many of the others during this test due to the greater distance from the support. A typical acceleration history runs 180 seconds (3 minutes simultaneous with strain measurements), where peaks above the noise symbolize a forced excitation such as from vehicle crossing. A peak acceleration of approximately 12 mg for test 7 is shown in Figure 3, where 3(b) is a condensed look at a single vehicle response. This information was combined with the remaining 9 accelerometers for test 7 to produce an average power spectrum of frequencies. The test captured five peaks in the spectrum, corresponding to the natural frequencies shown in Figure 4. For each test, a power spectrum was developed to indicate the natural frequencies of the bridge. The natural frequencies are relatively high and amplitudes of the spectrum low, indicating the structure is stiff. This can also be observed in Figure 5 where the first three mode shapes of one 3 minute data set were extracted from the data. Since the sensors were placed solely on the two interior beams and not the fascia beams, only the middle portion of the bridge was accurately assessed. Prior to deployment, a Finite Element Method (FEM) model using ALGOR of the structure was constructed to compare the experimental results to the theoretical model. Figure 3: (a) Typical acceleration time history (b) Vehicle traffic load

5 Figure 4: Average Normalized Power Spectral Density Figure 5: Experimental Mode Shapes and Comparison with FEM Analysis Upon examination of the results, the experimental findings followed the model well for the center portion of the bridge. Modes 1 and 3 indicate similar responses among the instrumented beams. Beam 2 shows slightly higher response than beam 3 towards the mid-span, however for mode 3 the responses are fairly identical. Mode 2 purposes that some twisting is occurring towards center of the bridge, as beam 3 is displaced higher than beam 2. A vehicle traveling close to the railing helps to induce this mode at a greater magnitude, but this mode would likely occur regardless. CONCLUSION

6 With much of today s infrastructure deteriorating at such a rapid rate, there is high demand for methods of accurately determining the performance level of a structure. Performance monitoring is a widely researched area that encompasses the development of sensor technologies as well as monitoring methods that allow for the optimum results. A Wireless Sensor System (WSS) developed at Clarkson University was tested on an integral abutment bridge. The acceleration and strain measurements suggest the bridge to be very stiff. Low levels of acceleration and strain were captured by the WSS. The strain corresponded well to the expected results, however future tests with larger vehicle loads will be required for a more accurate evaluation. Five natural frequencies were extracted from frequency response spectrum (the first three presented) to produce the mode shapes of the instrumented bridge as well as indicate the structure to be very stiff. The experimental results corresponded well to the theoretical mode shapes produced. ACKNOWLEDGMENTS This research has been funded by the New York State Energy Research and Development Authority (NYSERDA), in collaboration with the St. Lawrence Highway Department, and the New York State Department of Transportation (NYSDOT). The assistance of Kevin Cross and Dan Nyanjom with the field deployment and testing is greatly acknowledged. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not reflect the views of the agencies. REFERENCES Report Card for America s Infrastructure (2005). American Society of Civil Engineers (ASCE). Accessed July 15, Frasier, Michael. (2006) Development and Integration of an Integrated Framework for Structural Health Monitoring, Ph.D. Dissertation, University of California San Diego. Phares, B.M., Rolander, D.D., Graybeal, B.A., Washer, G.A. (2001) Reliability of Visual Bridge Inspection. Public Roads. April. Whelan, M.J, Gangone, M.V, Janoyan, K.D. (2007a) (Submitted) Deployment of a Dense Hybrid Wireless Sensing System for Bridge Monitoring. Journal of Infrastructure Systems ASCE Special Issue: New Sensors, Instrumentation and Signal Interpretation. Whelan, M.J., Fuchs, M.P., Gangone, M.V., and Janoyan, K.D. (2007b) Development of a Wireless Bridge Monitoring System for Condition Assessment using Hybrid Techniques. SPIE Smart Structures Symposium, San Diego, California.