Research On Dynamic Loads Measurement And Vehicle Classification On Highway

Vehicle dynamic loads and vehicle classification has been a research hotspot and difficult problems for highway researchers. With the rapid development of the national economy, the state highway construction cost inputs to increase year by year, which leads our country highway mileage in front of the word. At the same time the costs for the damage of the roads is also as high as several hundreds billions of RMB each year. Due to the disadvantage such as high costs, less information gaining and slow weighing measurement, the traditional vehicle dynamic loads measurement system (ie, weigh in motion, WIM) is hardly to meet the requirements for highway vehicle load monitoring and vehicle classification. Thus it is very important to study a dynamic weighing system for increasing the accuracy and feasibility in weighing the vehicle axle loads and classifying the vehicles. This research has been aided by Heilongjiang Communications Fund (No: HJZ₂004₁2). The purpose for the research work is to find a cheap way to meet the requirements for vehicle load monitoring and vehicle classification in the dynamic weighing system. It can provide objective and accurate vehicle load and vehicle classification data for heavy-duty vehicles damaging effects of rigid pavement research. For this purpose, according to the analysis of abundant experimental data, a novel dynamic weighing classification models based on strain response of pavement structure has been provided. According to these technical characteristics, a number of key technical issues were carried out, which was listed as follows:R&D of the WIM and vehicle classification in the world was reviewed in detail. Consequently, the existing problems in WIM and vehicle classification were pointed out.According to the mechanical properties of rigid pavement structure, the rigid pavement response model under different moving load has been studied. The response of the rigid pavement under the two-axle moving loads of constant amplitude and harmonic loads using a triple Fourier transform were simulated and the relationship between loads, strain response and speed were derived. These results may lead a theoretical foundation for studying on rigid pavement strain response dynamic loads measurement technology.This dissertation studied the main factors affecting the accuracy and speed of dynamic loads measurement; pointed out that the efficiency and accuracy of dynamic loads measurement was mainly affected by vehicle dynamic vibration; presented that multi-sensor of multi-point measurement methods can improve dynamic weighing accuracy and efficiency. Furthermore, the design methods and formulas of multi-sensor spacing system are introduced. Dynamic loads measurement system prototype based on the multiple embedded strain sensors was designed and set up using this method and formula.On the basis of many experimental vehicle sample data, Multi-sensor vehicle classification methods based on two multi-class Support Vector Machines (OAA, OAO) and two data fusion are researched in this dissertation. Different algorithms and different fusion strategies on classification accuracy using the experimental data show that vehicle classification accuracy can be reached more than 94.6 percent.Multi-sensor dynamic loads measurement system calibration using the actual experiment and multi-sensor fusion modeling method based on support vector regression and entropy weight were researched in this dissertation. Experimental data show that the model can be tested within 6% dynamic loads measurement prediction error.