Volume 26 Issue 7
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CHEN Shi-zhi, XU Jia-lin, ZHAO Meng-xiang, CHEN Jia-qi, YANG Gan, WANG Tao, HAN Wan-shui. Effects of environmental temperature field on bridge weigh-in-motion methods[J]. Journal of Traffic and Transportation Engineering, 2026, 26(7): 98-110. doi: 10.19818/j.cnki.1671-1637.2026.100
Citation: CHEN Shi-zhi, XU Jia-lin, ZHAO Meng-xiang, CHEN Jia-qi, YANG Gan, WANG Tao, HAN Wan-shui. Effects of environmental temperature field on bridge weigh-in-motion methods[J]. Journal of Traffic and Transportation Engineering, 2026, 26(7): 98-110. doi: 10.19818/j.cnki.1671-1637.2026.100
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Effects of environmental temperature field on bridge weigh-in-motion methods

doi: 10.19818/j.cnki.1671-1637.2026.100

  • School of Highway, Chang'an University, Xi'an 710064, Shaanxi, China

Funds:

Young Talent Fund of Association for Science and Technology in Shaanxi 20220407

General Project of Shaanxi Province Natural Science Basic Research Program 2025JC-YBMS-443

General Project of Shaanxi Province Natural Science Basic Research Program 2025JC-YBQN-597

Funding of China Postdoctoral Science Foundation 2024M762770

More Information
  • Corresponding author: YANG Gan, lecturer, PhD, E-mail: ygchd@chd.edu.cn
  • Received Date: 2025-06-03
  • Accepted Date: 2025-11-27
  • Rev Recd Date: 2025-09-30
  • Publish Date: 2026-07-28
    Abstract
  • Bridge weigh-in-motion (B-WIM) technology is an important means for vehicle load monitoring, and its accuracy is affected by the environmental temperature field; however, existing studies mostly overlook the dynamic interference of the environmental temperature field to it. Taking a concrete T-beam as the object, outdoor vehicle-induced vibration tests were conducted in summer and winter to simulate the coupling effect of multiple conditions including temperature field, vehicle speed, and vehicle weight, and vehicle-induced strain responses were collected. Based on two classical B-WIM methods, i.e., the Moses algorithm and the strain area method, the influence of the environmental temperature field on the identification accuracy of gross vehicle weight was quantified. The results show that high temperature in summer causes the extreme value of strain response of the T-beam to increase by 11.3% compared with winter; under the winter calibration condition, the maximum identification errors of the Moses algorithm and the strain area method for the gross weight of passing vehicles in the same season are 3.68% and 1.41%, respectively, but when the same calibration parameters are applied to the summer tests, the gross weight errors of the two algorithms are significantly expanded to 14.08% and 13.84%, respectively; the analysis shows that the environmental temperature difference between the calibration moment and the testing moment contributes far more to the error than the vehicle speed and vehicle weight, and it is further found that the B-WIM method calibrated in autumn can reduce the annual average error to 3.8%, which is lower than the annual average errors calibrated in other seasons. It can be seen that the environmental temperature during calibration is the key control factor affecting the year-round accuracy of B-WIM. It is recommended that in practical applications, a time period with a stable temperature field and close to the annual average state should be selected as the optimal calibration time according to the climatic characteristics of the bridge location, so as to effectively reduce the temperature-induced systematic error and improve the long-term reliability of bridge weigh-in-motion.

     

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