Application of Microwave Remote Sensing to Dynamic Testing of Stay-Cables
Abstract
:1. Introduction
- establishing the actual displacement sensitivity of the equipment (0.01 ÷ 0.02 mm) through free vibration tests carried out in the laboratory on a simple spring-mass system [9];
- AVT of a reinforced concrete bridge, using simple radar reflectors placed as close as possible to conventional sensors [8,9], in order to perform an extensive comparison between time-histories and modal properties (i.e., resonant frequencies and mode shapes) obtained from radar and traditional measurement techniques. In particular, the modal parameters of the bridge, that were identified from the radar signals, turned out to be as accurate as that obtained with traditional accelerometers;
- static testing of a steel-composite bridge [10], in order to directly compare the deflections provided by the microwave interferometer and conventional techniques.
2. The Microwave Measurement System
- he SF-CW technique (see e.g., [11]), adopted to resolve the scenario in the range direction, i.e., to detect the position of different target surfaces placed along the radar’s line of sight;
- he phase interferometry technique (see e.g., [12], implemented to compute the displacement of each target by comparing the phase information of the back-scattered electromagnetic waves collected at different times.
3. Microwave Remote Sensing of Stay-cables
- the typical position of the sensor in the survey of an array of cables is inclined upward, as schematically shown in Figure 2(a); hence, the only targets encountered along the path of the electromagnetic waves are the stays itself, so that 1-D imaging capability is perfectly adequate to the test scenario;
- arrays of cables generally belong to a vertical plane, where the vibration of the cables mainly take place under the traffic loads. The in-plane motion of a cable can be assumed orthogonal to its axis, so that the actual deflection d can be obtained from the component dr along the radar line of sight as:
4. Application to Full-Scale Structures
4.1. Experimental Verification on a Single Stay-cable
Cable | Sensor | T(f1) (kN) | T(f2) (kN) | T(f3) (kN) | T(f4) (kN) | T(f5) (kN) | Average (kN) |
---|---|---|---|---|---|---|---|
S'12 | Accelerometer | 2,679 | 2,707 | 2,660 | 2,693 | 2,690 | 2,686 |
Radar sensor | 2,679 | 2,707 | 2,679 | 2,693 | 2,690 | 2,689 |
4.2. Dynamic Measurements on the Forestays of the Cable-stayed Bridge over the River Oglio
Cable | T(f1) (kN) | T(f2) (kN) | T(f3) (kN) | T(f4) (kN) | T(f5) (kN) | Average (kN) |
---|---|---|---|---|---|---|
S1U | 2,704 | 2,692 | 2,712 | 2,716 | 2,722 | 2,709 |
S1D | 2,655 | 2,654 | 2,671 | 2,670 | 2,674 | 2,665 |
S2U | 2,923 | 2,943 | 2,924 | 2,924 | 2,939 | 2,931 |
S2D | 3,003 | 2,982 | 2,949 | 2,982 | 2,986 | 2,980 |
S3U | 4,054 | 4,052 | 4,073 | 4,098 | 4,113 | 4,078 |
S3D | 3,990 | 3,997 | 4,031 | 4,037 | 4,039 | 4,019 |
5. Conclusions
- a large number of local resonant frequencies can be identified from radar data on each stay-cable of an array and these natural frequencies seems as accurate as that obtained with conventional accelerometers;
- in the investigated case studies, the number of frequencies identified from radar data was large enough to establish if the cables behave as a taut string or deviate from a taut string, so that accurate estimate of the cable tensions can be retrieved from the identified natural frequencies as well.
Acknowledgements
References and Notes
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Gentile, C. Application of Microwave Remote Sensing to Dynamic Testing of Stay-Cables. Remote Sens. 2010, 2, 36-51. https://doi.org/10.3390/rs2010036
Gentile C. Application of Microwave Remote Sensing to Dynamic Testing of Stay-Cables. Remote Sensing. 2010; 2(1):36-51. https://doi.org/10.3390/rs2010036
Chicago/Turabian StyleGentile, Carmelo. 2010. "Application of Microwave Remote Sensing to Dynamic Testing of Stay-Cables" Remote Sensing 2, no. 1: 36-51. https://doi.org/10.3390/rs2010036
APA StyleGentile, C. (2010). Application of Microwave Remote Sensing to Dynamic Testing of Stay-Cables. Remote Sensing, 2(1), 36-51. https://doi.org/10.3390/rs2010036