scholarly journals Study on the Method of Moving Load Identification Based on Strain Influence Line

2021 ◽  
Vol 11 (2) ◽  
pp. 853 ◽  
Author(s):  
Jing Yang ◽  
Peng Hou ◽  
Caiqian Yang ◽  
Yang Zhang
Keyword(s):  
Moving Load ◽  
Identification Accuracy ◽  
Vehicle Speed ◽  
Load Identification ◽  
Space Problem ◽  
Transverse Distribution ◽  
Identification Error ◽  
Vehicle Weight ◽  
Influence Line ◽  
Moving Load Identification

In order to improve the accuracy of load identification and study the influence of transverse distribution, a novel method was proposed for the moving load identification based on strain influence line and the load transverse distribution under consideration. The load identification theory based on strain influence line was derived, and the strain integral coefficient was proposed for the identification. A series of numerical simulations and experiments were carried out to verify the method. The numerical results showed that the method without considering the load transverse distribution was not suitable for solving the space problem, and the method with the load transverse distribution under consideration has a high identification accuracy and excellent anti-noise performance. The experimental results showed that the speed identification error was smaller than ±5%, and the vehicle speed had no obvious influence on the identification results of the vehicle weight. Moreover, the average identification error of the vehicle weight was smaller than ±10%, and the error of more than 90% of samples was smaller than ±5%.

Moving Load Identification of Small and Medium-Sized Bridges Based on Distributed Optical Fiber Sensing

2016 ◽  
Vol 16 (04) ◽  
pp. 1640021 ◽  
Author(s):  
Cai Qian Yang ◽  
Dan Yang ◽  
Yi He ◽  
Zhi Shen Wu ◽  
Ye Fei Xia ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Moving Load ◽  
Vehicle Speed ◽  
Load Identification ◽  
Structure Response ◽  
Fiber Sensing ◽  
Optical Fiber Sensing ◽  
Fbg Sensors ◽  
Distributed Optical Fiber ◽  
Moving Load Identification

A novel method was proposed for the moving load identification of bridges based on the influence line theory and distributed optical fiber sensing technique. The method of load and vehicle speed identification was firstly theoretically studied, and then numerical simulation was also performed to study its accuracy and robustness. The numerical results showed that this method was characterized by high accuracy and excellent resistance to noise. Finally, the load identification of an actual continuous pre-stressed concrete beam bridge was carried out with the proposed method. The bridge consists of four pre-stressed box beams. At the same time, a weigh-in-motion system was also installed about 200 m in front of the bridge to measure the speed and moving loads with a purpose of comparing the load identification of the proposed method. Long gauge fiber Bragg grating (FBG) sensors with a gauge length of 1.0 m were adhered to the bottom of the beams. The individual loaded vehicles and the corresponding structure response were mainly monitored as standard samples, and the speed and weight of the sample vehicles were monitored and identified with the proposed method. The results revealed that the distributed long gauge FBG sensors were capable of sensing the structure response precisely and identifying the traffic load. On the basis of the design information and ambient vibration testing results, a refined model was established and the response under unit moving load was acquired for load identification. It was also shown that the sensors in different positions can achieve accurate vehicle speed and weight, the relative error of which are within 10% and 15%, respectively.

Parametric Effect on Bidirectional Moving Vehicle Load Identification

2011 ◽  
Vol 66-68 ◽  
pp. 194-198
Author(s):  
Ling Yu ◽  
Xue Gang Wang
Keyword(s):  
Moving Load ◽  
Identification Problem ◽  
Companion Paper ◽  
Identification Accuracy ◽  
Load Identification ◽  
Moving Vehicle ◽  
Vehicle Load ◽  
Parametric Effect ◽  
Bridge Responses ◽  
Moving Load Identification

Parametric effect on bidirectional moving vehicle load identification from plate bridge responses is studied in this paper. The equation of motion of a plate bridge-bidirectional vehicle system is formulated based on Hamilton principle and is rewritten in a state space form, the bidirectional moving load identification problem is considered as a damped least-squares problem and further solved with the regularization method. Finally, the effect of parameters on identification accuracy is investigated in order to evaluate the effectiveness and robustness of the bidirectional moving load identification method proposed in a companion paper. Some numerical simulations show that the proposed method is correct and effective for identifying the bidirectional moving vehicle loads from bridge responses with an acceptable accuracy, but the selection of parameters should be carefully considered in the identification process.

scholarly journals Comprehensive Study of Moving Load Identification on Bridge Structures Using the Explicit Form of Newmark-β Method: Numerical and Experimental Studies

2021 ◽  
Vol 13 (12) ◽  
pp. 2291
Author(s):  
Solmaz Pourzeynali ◽  
Xinqun Zhu ◽  
Ali Ghari Zadeh ◽  
Maria Rashidi ◽  
Bijan Samali
Keyword(s):  
Explicit Form ◽  
Numerical Study ◽  
Moving Load ◽  
Experimental Studies ◽  
Sampling Frequency ◽  
Vehicle Speed ◽  
Load Identification ◽  
Simply Supported ◽  
Bridge Structures ◽  
Moving Load Identification

Bridge infrastructures are continuously subject to degradation due to aging and excess loading, placing users at risk. It has now become a major concern worldwide, where the majority of bridge infrastructures are approaching their design life. This compels the engineering community to develop robust methods for continuous monitoring of bridge infrastructures including the loads passing over them. Here, a moving load identification method based on the explicit form of Newmark-β method and Generalized Tikhonov Regularization is proposed. Most of the existing studies are based on the state space method, suffering from the errors of a large discretization and a low sampling frequency. The accuracy of the proposed method is investigated numerically and experimentally. The numerical study includes a single simply supported bridge and a three-span continuous bridge, and the experimental study includes a single-span simply supported bridge installed by sensors. The effects of factors such as the number of sensors, sensor locations, road roughness, measurement noise, sampling frequency and vehicle speed are investigated. Results indicate that the method is not sensitive to sensor placement and sampling frequencies. Furthermore, it is able to identify moving loads without disruptions when passing through supports of a continuous bridge, where most the existing methods fail.

scholarly journals Moving Load Identification with Long Gauge Fiber Optic Strain Sensing

2021 ◽  
Vol 16 (3) ◽  
pp. 131-158
Author(s):  
Qingqing Zhang ◽  
Wenju Zhao ◽  
Jian Zhang
Keyword(s):  
Fiber Optic ◽  
Moving Load ◽  
Field Testing ◽  
Maximum Strain ◽  
Load Identification ◽  
Moving Vehicle ◽  
Moving Vehicles ◽  
Structural Responses ◽  
Vehicle Loads ◽  
Moving Load Identification

Moving load identification has been researched with regard to the analysis of structural responses, taking into consideration that the structural responses would be affected by the axle parameters, which in its turn would complicate obtaining the values of moving vehicle loads. In this research, a method that identifies the loads of moving vehicles using the modified maximum strain value considering the long-gauge fiber optic strain responses is proposed. The method is based on the assumption that the modified maximum strain value caused only by the axle loads may be easily used to identify the load of moving vehicles by eliminating the influence of these axle parameters from the peak value, which is not limited to a specific type of bridges and can be applied in conditions, where there are multiple moving vehicles on the bridge. Numerical simulations demonstrate that the gross vehicle weights (GVWs) and axle weights are estimated with high accuracy under complex vehicle loads. The effectiveness of the proposed method was verified through field testing of a continuous girder bridge. The identified axle weights and gross vehicle weights are comparable with the static measurements obtained by the static weighing.

Research on moving load identification based on measured acceleration and strain signals

2019 ◽  
Vol 3 (3/4) ◽  
pp. 257-288 ◽  
Author(s):  
Yun Zhou ◽  
Sai Zhou ◽  
Lu Deng ◽  
Songbai Chen ◽  
Weijian Yi
Keyword(s):  
Moving Load ◽  
Load Identification ◽  
Moving Load Identification

Influences of Elastic Supports on Moving Load Identification of Euler–Bernoulli Beams Using Angular Velocity

2020 ◽  
Vol 143 (4) ◽  
Author(s):  
Guandong Qiao ◽  
Salam Rahmatalla
Keyword(s):  
Angular Velocity ◽  
Moving Load ◽  
Load Identification ◽  
Moving Loads ◽  
Elastic Supports ◽  
Wide Range ◽  
Angular Velocities ◽  
Ill Posed ◽  
Translational Spring ◽  
Moving Load Identification

Abstract This work investigates the effect of elastic support stiffness on the accuracy of moving load identification of Euler–Bernoulli beams. It uses the angular velocity response in solving the ill-posed inverse vibration problem and Tikhonov regularization in the load identification process of two moving loads. The effects from moving loads’ traveling direction, measurement location arrangements, number of participant measurements, and damping ratios are considered in the studies under noisy disturbance conditions. Results show that the stiffness of the translational rotational springs at the boundaries can impact the accuracy of identified moving loads considerably. Angular velocities presented much better results than accelerations under low stiffness conditions when vertical elastic supports were used. However, acceleration showed better performance when a very soft translational spring was used at one end and a much stiffer translational spring at the other end, as well as when rotational springs with large stiffness were used with simply supported beam conditions. The combination of angular velocities and accelerations provided a balanced solution for a wide range of elastic supports with different stiffnesses.

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