Multiple vehicle axle load identification from continuous bridge bending moment response

P. Asnachinda, T. Pinkaew, J. A. Laman

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


The identification of multiple vehicle dynamic axle loads on multi-span continuous bridge is presented. The objective of the present study was to develop a practical technique to determine dynamic axle loads of multiple vehicles based on the measured bridge response. Based on the inverse problem of turning bridge responses into time-varying point loads, the solution can be determined using least squares regularization optimization. The updated static component (USC) technique is adopted to improve the accuracy and eliminate the difficulty of an optimal regularization selection. The computer simulation and experimental studies were conducted to investigate the effectiveness of the proposed method. A scaled model of a three-span, continuous bridge and two scaled 2-axle vehicles were designed, constructed and fabricated in the laboratory. Various moving schemes of multiple vehicle travel including following, overtaking and side-by-side movements were considered. The actual dynamic axle loads of the model vehicles during the travel were directly monitored and used in accuracy evaluation. From the obtained results, it is observed that the USC technique effectively improved the accuracy and robustness of the problem, particularly in correction of the absence of identified axle loads around the internal bridge supports. The method is robust and accurately identifies every dynamic axle load for all moving schemes of vehicles. No conflict of the identified axle loads during axle overlapping and passing the bridge support is observed because the axle loads are identified independently and controlled by static influence lines from the USC algorithm. The comparison between the measured and reconstructed bending moments indicates that the approach is correct. The accuracy of identified dynamic axle loads for all cases of study is within a relative percentage error of 13%.

Original languageEnglish (US)
Pages (from-to)2800-2817
Number of pages18
JournalEngineering Structures
Issue number10
StatePublished - Oct 2008

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering


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