Nondestructive evaluation (NDE) of steel cables in long span bridges is necessary to prevent structural failure. Thus, an automated cable monitoring system is proposed that uses a suitable NDE technique and a cable-climbing robot. A magnetic flux leakage- (MFL-) based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults (LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the levels of damage. Measured signals from the damaged specimen were compared with thresholds that were set for objective decision-making. In addition, the measured magnetic flux signals were visualized as a 3D MFL map for intuitive cable monitoring. Finally, the results were compared with information on actual inflicted damages, to confirm the accuracy and effectiveness of the proposed cable monitoring method. 1. Introduction Recently, there have been increasing demands on structural health monitoring (SHM) and nondestructive testing (NDT) in the fields of civil, mechanical, and aerospace engineering. Especially, local monitoring methodologies for specific critical members have been studied to overcome the limitation of global monitoring techniques for whole structures [1–4]. Steel cables in long span bridges are also critical members that suspend almost all of the dead load of the structure. However, cross-sectional damage can occur in a steel cable due to corrosion and fracture, which can lead to stress concentrations. Cross-sectional damage can be a direct cause of structural failure. Therefore, nondestructive evaluation (NDE) is necessary to detect the initial stages of cross-sectional damage in a cable. However, it is difficult to monitor the condition of most cables, as the damage can be invisible and inaccessibly located. To overcome these drawbacks, we propose an automated cable monitoring system, which uses a suitable NDE technique and a cable-climbing robot that can approach the damaged point, which is shown in Figure 1. Figure 1: The cable-climbing robot with suitable NDE equipment. Meanwhile, NDE techniques available for incorporation into cable-climbing robots have been widely researched. In this study,
References
[1]
S. Park, J. -W. Kim, C. Lee, and S. -K. Park, “Impedance-based wireless debonding condition monitoring of cfrp laminated concrete structures,” NDT & E International, vol. 44, no. 2, pp. 232–238, 2011.
[2]
C. Lee and S. Park, “Damage classification of pipelines under water flow operation using multi-mode actuated sensing technology,” Smart Materials and Structures, vol. 20, no. 11, Article ID 115002, 9 pages, 2011.
[3]
J. Min, S. Park, C. -B. Yun, C. -G. Lee, and C. Lee, “Impedance-based structural health monitoring incorporating neural network technique for identification of damage type and severity,” Engineering Structures, vol. 39, pp. 210–220, 2012.
[4]
C. Lee and S. Park, “De-bonding detection on a CFRP laminated concrete beam using self sensing-based multi-scale actuated sensing with statistical pattern recognition,” Advances in Structural Engineering, vol. 15, no. 6, pp. 919–927, 2012.
[5]
M. L. Wang, G. Wang, and Y. Zhao, Sensing Issues in Civil Structural Health Monitoring, Springer, Dordrecht, The Netherlands, 2005.
[6]
M. L. Wang, Z. L. Chen, S. S. Koontz, and G. M. Lloyd, “Magnetoelastic permeability measurement for stress monitoring in steel tendons and cables,” in Nondestructive Evaluation of Highways, Utilities, and Pipelines IV, vol. 3995 of Proceedings of the SPIE, pp. 492–500, March 2000.
[7]
S. Sumitro, A. Jarosevic, and M. L. Wang, “Elasto-magnetic sensor utilization on steel cable stress measurement,” in Proceedings of the 1st Fib Congress, pp. 79–86, Osaka, Japan, 2002.
[8]
M. G？ktepe, “Non-destructive crack detection by capturing local flux leakage field,” Sensors and Actuators A: Physical, vol. 91, no. 1-2, pp. 70–72, 2001.
[9]
C. Mandache, B. Shiari, and L. Clapham, “Defect separation considerations in magnetic flux leakage inspection,” Insight—Non-Destructive Testing and Condition Monitoring, vol. 47, no. 5, pp. 289–293, 2005.
[10]
H. R. Weischedel, “The inspection of wire ropes in service: a critical review,” Materials Evaluation, vol. 43, no. 13, pp. 1592–1605, 1985.
[11]
J. Lee, J. Hwang, J. Jun, and S. Choi, “Nondestructive testing and crack evaluation of ferromagnetic material by using the linearly integrated hall sensor array,” Journal of Mechanical Science and Technology, vol. 22, no. 12, pp. 2310–2317, 2008.
[12]
O. L. Atherton, “Magnetic inspection is key to ensuring safe pipelines,” Oil and Gas Journal, vol. 87, no. 32, pp. 52–61, 1989.
[13]
H. R. Weischedel and C. R. Chaplin, “Inspection of wire ropes for offshore applications,” Materials Evaluation, vol. 49, no. 3, pp. 362–367, 1991.
[14]
K. Mandal, D. Dufour, T. W. Krause, and D. L. Atherton, “Investigations of magnetic flux leakage and magnetic Barkhausen noise signals from pipeline,” Journal of Applied Physics, vol. 30, no. 6, pp. 962–973, 1997.
[15]
K. K. Tandon, “MFL tool hardware for pipeline inspection,” Materials Performance, vol. 36, no. 2, pp. 75–79, 1997.
[16]
K. Mandal and D. L. Atherton, “A study of magnetic flux-leakage signals,” Journal of Physics D, vol. 31, no. 22, pp. 3211–3217, 1998.
[17]
J. E. Lenz, “Review of magnetic sensors,” Proceedings of the IEEE, vol. 78, no. 6, pp. 973–989, 1990.
[18]
E. Ramsden, Hall-Effect Sensors: Theory and Applications, Newnes, Oxford, UK, 2006.
[19]
S. Coles, An Introduction to Statistical Modeling of Extreme Values, Springer, Berlin, Germany, 2001.
