Effects of environmental temperature field on bridge weigh-in-motion methods
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摘要: 桥梁动态称重(B-WIM)技术是车重监测的重要手段，其精度受环境温度场影响，但既有研究多忽略了环境温度场对其的动态干扰。本文以混凝土T梁为对象，开展夏、冬两季露天车致振动试验，模拟温度场、车速和车重多工况耦合作用，采集车致应变响应；基于Moses算法与应变面积法2种经典B-WIM算法，量化环境温度场对车辆总重识别精度的影响。研究结果表明：夏季高温导致T梁应变响应极值较冬季提升11.3%，在冬季标定条件下，Moses算法与应变面积法对当季过车总重的识别误差最大值分别为3.68%与1.41%，但同一标定参数用于夏季测试时，2种算法的总重误差分别显著扩大至14.08%与13.84%；分析显示，标定时刻与测试时刻的环境温度差对误差的贡献远超车速与车重，进一步发现秋季标定的B-WIM算法可使年均误差降低至3.8%，低于其他季节标定的年均误差；标定时的环境温度是影响B-WIM全年精度的关键控制因素，建议在实际应用中根据桥梁所在地的气候特征，选择温度场稳定且接近年平均状态的时段作为最佳标定时间，以有效降低温度引起的系统误差，提升桥梁动态称重的长期可靠性。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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图 6 夏季测点截面温度场分布
Figure 6. Cross-sectional temperature field distribution at sensor locations (summer)
图 7 冬季测点截面温度场分布
Figure 7. Cross-sectional temperature field distribution at sensor locations (winter)
图 8 不同温度场下的车致振动响应曲线
Figure 8. Vehicle-induced vibration response curves under different temperature fields
图 9 不同车速下的车致振动响应曲线
Figure 9. Vehicle-induced vibration response curves under different vehicle speeds
图 10 不同车质量下的车致振动响应曲线
Figure 10. Vehicle-induced vibration response curves under different vehicle weights
图 14 测点温度实测结果与计算结果对比
Figure 14. Comparison of measured and calculated temperature results at sensor locations
图 15 不同标定季节下的Moses算法总重识别误差
Figure 15. Gross weight identification error of Moses algorithm under different calibration seasons
图 16 不同标定季节下的应变面积法总重识别误差
Figure 16. Gross weight identification error of strain area method under different calibration seasons
表 1 试验工况
Table 1. Experimental conditions
工况 季节 质量/kg 速度/(m·s-1) 测试温度时刻 W1-1 冬季 35 0.4 7:00 W1-2 冬季 35 0.4 13:00 W1-3 冬季 35 0.4 19:00 W2-1 冬季 35 0.7 13:00 W2-2 冬季 35 1.2 13:00 W3-1 冬季 50 0.4 13:00 W3-2 冬季 20 0.4 13:00 S1-1 夏季 35 0.4 7:00 S1-2 夏季 35 0.4 13:00 S1-3 夏季 35 0.4 19:00 S2-1 夏季 35 0.7 13:00 S2-2 夏季 35 1.2 13:00 S3-1 夏季 50 0.4 13:00 S3-2 夏季 20 0.4 13:00 
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表 2 试验当天气温数据
Table 2. Temperature data on the days of the experiment
首页/历史天气/陕西省/西安市/未央区/未央宫街道/阁老门 日期 最高温/℃ 最低温/℃ 天气 风力风向 日照时长/h 2024-06-29 34.7 21.0 晴 西南风2级 13.2 2024-12-19 7.7 -0.2 晴 东北风3级 8.5
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