A Data-Driven Approach for Bridge Weigh-in-Motion from Impact Acceleration Responses at Bridge Joints
نویسندگان
چکیده
Bridge weigh-in-motion (BWIM) serves as a method to obtain the weight of passing vehicles from bridge responses. Most BWIM systems proposed so far rely on measurement global vibration data, usually strain, determine vehicle load. However, because bridge’s response is sensitive all bridge, vibration-based techniques suffer inaccuracy in case where multiple are present bridge. In this paper, data-driven approach extract vehicle’s and driving speed vertical acceleration at joint. As type local vibration, impulse responses joint can be recorded only during short period when over thus not other locations A field test conducted prepare labeled training data for use convolutional neural network. One accelerometer installed record acceleration, while obtained WIM station camera near respectively. network that detects passage well its lane first proposed, followed by 1-D uses raw input predict gross speed. comparison made between an updated 2-D wavelet coefficients matrix. The latter one shows better performance, indicating it important choose proper trained. transfer learning technique used feasibility method. Results show extended with limited bridges than
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ژورنال
عنوان ژورنال: Structural control & health monitoring
سال: 2023
ISSN: ['1545-2263', '1545-2255']
DOI: https://doi.org/10.1155/2023/2287978