Monitoring and evaluation of fatigue damage for orthotropic steel deck using acoustic emission technology

DUAN Lan1 WANG Chun-sheng1 ZHAI Mu-sai1 WANG Shi-chao1 SI Hai-peng1

(1.School of Highway, Chang’an University, Xi’an, Shaanxi, Province, China 710064)

【Abstract】Based on the integration of multiple monitoring technologies, the fatigue damage was analyzed and assessed for the orthotropic steel deck (OSD), including the fatigue test of a fullscale OSD segment in lab and the fatigue damage monitoring of a cable-stayed highway steel bridge with the OSD during service stage. For the fatigue test study of the OSD in lab, two kinds of acoustic emission (AE) sensors, including physical acoustics corporation (PAC) commercial AE sensors and smart piezoelectric paint sensors made of lead-zirconate-titanate (PZT), and supplementary strain gages were comprehensively used to detect and monitor the fatigue crack activities before and after the cold reinforcement of bonding steel plate. For the in-service highway steel bridges with detected fatigue cracks in the OSD, the cold reinforcement of bonding angel steel was proposed for the fatigue sensitive details in the OSD. Both AE monitoring and strain monitoring were conducted to study the fatigue crack activity and verify the effectiveness of the cold reinforcement. Learn from the fatigue test and monitoring results in lab, both PAC commercial AE sensors and smart PZT sensors are efficient ways to capture the fatigue propagation signals that have the characteristic of a peak amplitude and then fading gradually. The application of both PAC commercial AE sensors and smart PZT sensors achieve smart monitoring for the fatigue crack activity. The PAC commercial AE sensor group can locate the fatigue crack propagation length and direction in the rib accurately. After adopting bonding steel plate, the stress level keeps at 64.8 MPa stably, and no fatigue crack propagation is observed until the cyclic loading accumulates to 5.12 million times, testifying fine workability of the OSD model after the cold reinforcement. The PAC commercial AE sensor and smart PZT sensor have good agreement in detecting fatigue crack propagation during fatigue loading process, and can capture more fatigue crack activity information in-time than the strain gage. Learn from the monitoring and evaluation results for the in-service steel bridge with the OSD, the peak energy of AE monitoring result before the cold reinforcement is 5 times as that after the cold reinforcement, and the accumulated AE signals decreasing from intensive to scatter indicate the stability of fatigue cracks. After the cold reinforcement, the peak stresses nearby the fatigue crack tips decrease by 40% to 50% when the loading vehicles pass, and the maximum stress near the fatigue detail declines from 78 MPa before the cold reinforcement to 48 MPa after the cold reinforcement during 24 h monitoring. The peak energy and accumulated number of AE signals and the stress level testify the effectiveness of cold reinforcement for the fatigue cracks in the OSD.

【Keywords】 bridge engineering; steel bridge; orthotropic steel deck; AE monitoring; fatigue damage; cold reinforcement;


【Funds】 National Natural Science Foundation of China (51578073) National Ten-thousand Talents Program of China (W03020659) Special Foundation for Basic Scientific Research of Central Colleges of China (300102219309)

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    [1] TSAKOPOULOS P A, FISHER J W. Full-scale fatigue tests of steel orthotropic decks for the Williamsburg Bridge [J]. Journal of Bridge Engineering, 2003, 8 (5): 323–333.

    [2] TSAKOPOULOS P A, FISHER J W. Full-scale fatigue tests of steel orthotropic deck panel for the Bronx-Whitestone Bridge rehabilitation [J]. Bridge Structures, 2005, 1 (1): 55–66.

    [3] MALJAARS J, DOOREN F V, KOLSTEIN H. Fatigue assessment for deck plates in orthotropic bridge decks [J]. Steel Construction, 2012, 5 (2): 93–100.

    [4] WANG Chun-sheng, WANG Yu-zhu, DUAN Lan, et al. Fatigue performance evaluation and cold reinforcement for old steel bridges [J]. Structural Engineering International, 2019, 29 (4): 563–569.

    [5] WANG Chun-sheng, ZHAI Mu-sai, DUAN Lan, et al. Fatigue service life evaluation of existing steel and concrete bridges [J]. Advanced Steel Construction, 2015, 11 (3): 305–321.

    [6] WANG Chun-sheng, WANG Qian, XU Yue. Fatigue evaluation of a strengthened steel truss bridge [J]. Structure Engineering International, 2013, 23 (4): 443–449.

    [7] WANG Chun-sheng, CHEN Ai-rong, CHEN Wei-zhen. Assessment of remaining fatigue life and service safety for old steel bridges based on fracture mechanics [J]. China Journal of Highway and Transport, 2006, 19 (2): 42–48 (in Chinese).

    [8] WANG Chun-sheng, HAO Long, FU Bing-ning. Fatigue reliability updating evaluation of existing steel bridges [J]. Journal of Bridge Engineering, 2012, 17 (6): 955–965.

    [9] WANG Chun-sheng, CHEN Wei-zhen, CHEN Ai-rong. Damage safety assessment and maintenance management strategy of bridges [J]. Journal of Traffic and Transportation Engineering, 2002, 2 (4): 21–28 (in Chinese).

    [10] XU Jun, SUN Hua-huai, CAI Shun-yao. Effect of symmetrical broken wires damage on mechanical characteristics of stay cable [J]. Journal of Sound and Vibration, 2019, DOI: 10.1016/j.jsv.2019.114920.

    [11] NAKAMURA S I, SUZUMURA K, TARUI T. Mechanical properties and remaining strength of corroded bridge wires [J]. Structural Engineering International, 2004, 14 (1): 50–54.

    [12] NAKAMURA S I, SUZUMURA K. Experimental study on fatigue strength of corroded bridge wires [J]. Journal of Bridge Engineering, 2013, 18 (3): 200–209.

    [13] BETTI R, WEST A C, VERMAAS G, et al. Corrosion and embrittlement in high-strength wires of suspension bridge cables [J]. Journal of Bridge Engineering, 2005, 10 (2): 151–162.

    [14] FISHER J W, BARSOM J M. Evaluation of cracking in the rib-to-deck welds of the Bronx-Whitestone Bridge [J]. Journal of Bridge Engineering, 2016, 21 (3), DOI: 10.1061/(ASCE)BE.1943-5592.0000823.

    [15] WANG Chun-sheng, WANG Yu-zhu, CUI Bing, et al. Numerical simulation of distortion-induced fatigue crack growth using extended finite element method [J]. Structure and Infrastructure Engineering, 2020, 16 (1): 106–122.

    [16] WANG Chun-sheng, ZHAI Mu-sai, DUAN Lan, et al. Cold reinforcement and evaluation of steel bridges with fatigue cracks [J]. Journal of Bridge Engineering, 2018, 23 (4): 04018014-1–11.

    [17] SHEN Gong-tian, GENG Rong-sheng, LIU Shi-feng. Acoustic emission source location [J]. Nondestructive Testing, 2002, 24 (3): 114–117, 125 (in Chinese).

    [18] DING You-liang, DENG Yang, LI Ai-qun. Advances in researches on application of acoustic emission technique to health monitoring for bridge structures [J]. Journal of Disaster Prevention and Mitigation Engineering, 2010, 30 (3): 341 –351 (in Chinese).

    [19] POLLOCK A A, SMITH B. Stress–wave–emission monitoring of a military bridge [J]. Non-Destructive Testing, 1972, 5 (6): 348–353.

    [20] COLOMBO I S, MAIN I G, FORDE M C. Assessing damage of reinforced concrete beam using “b-value” analysis of acoustic emission signals [J]. Journal of Materials in Civil Engineering, 2003, 15 (3): 280–286.

    [21] YUYAMA S, YOKOYAMA K, NIITANI K, et al. Detection and evaluation of failures in high-strength tendon of prestressed concrete bridges by acoustic emission [J]. Construction and Building Materials, 2007, 21 (3): 491–500.

    [22] YU Jian-guo, ZIEHL P, ZÁRATE B, et al. Prediction of fatigue crack growth in steel bridge components using acoustic emission [J]. Journal of Constructional Steel Research, 2011, 67 (8): 1254–1260.

    [23] ROBERTS T M, TALEBZADEH M. Acoustic emission monitoring of fatigue crack propagation [J]. Journal of Constructional Steel Research, 2003, 59 (6): 695–712.

    [24] ZHOU Chang-jiang, ZHANG Yun-feng. Particle filter based noise removal method for acoustic emission signals [J]. Mechanical Systems and Signal Processing, 2012, 28: 63–77.

    [25] YAPAR O, BASU P K, VOLGYESI P, et al. Structural health monitoring of bridges with piezoelectric AE sensors [J]. Engineering Failure Analysis, 2015, 56: 150–169.

    [26] NAIR A, CAI C S. Acoustic emission monitoring of bridges: review and case studies [J]. Engineering Structures, 2010, 32 (6): 1704–1714.

    [27] ZHANG Yun-feng. In situ fatigue crack detection using piezoelectric paint sensor [J]. Journal of Intelligent Material Systems and Structures, 2006, 17 (10): 843–852.

    [28] LI Zhen, ZHANG Yue-feng, WANG Chun-sheng. A sensor-driven structural health prognosis procedure considering sensor degradation [J]. Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance, 2013, 9 (8): 764–776.

    [29] LI Xin. Electroelastic properties of piezoelectric paint for ultrasonic guided wave sensing and damage detection [D]. Bethlehem: Lehigh University, 2009.

    [30] LI Zhen, ZHANG Yun-feng. Extreme value theory-based structural health prognosis method using reduced sensor data [J]. Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance, 2014,19 (8): 988–997.

    [31] SHI Z, JARZYNSKI J, BAIR S, et al. Characterization of acoustic emission signals from fatigue fracture [J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2000, 214 (9): 1141–1149.

This Article


CN: 61-1369/U

Vol 20, No. 01, Pages 60-73

February 2020


Article Outline


  • 0 Introduction
  • 1 AE monitoring
  • 2 AE monitoring and evaluation of a full-scale OSD model
  • 3 Field AE monitoring and evaluation
  • 4 Conclusions
  • References