| As the development of the economic and transportation in our country, the road traffic grows rapidly every year and followed by a common and severe phenomenon of overloading of vehicles.In order to solve the problem of overloading of vehicles effectively, people began to set up vehicle weighing systems at roads.As static weighing systems generally are large and are very likely to cause bad traffic, so more and more people choose to use dynamic weighing method.However, there are still many problems in the research on vehicle dynamic weighing systems in our country, and this causes the weighing accuracy can not be improved.Firstly, because of lacking comprehensive analysis for dynamic weighing system, we did not do a depth processing to the weight signal.The other one is that people always thought that the hardware was the core of the weighing system and did a lot of works in hardware of the weighing system, but ignored the important role of the software algorithm to achieve high weighing accuracy.This paper made a basic planning and design for the dynamic weighing system firstly. In order to overcome the drawbacks of dynamic weighing system described above, this paper firstly analyzed the state of motion of vehicle and the disruption factors in the process of weighing, and made a comprehensive summary. From the analysis and summary, found the main interference factors and analyze the frequency range of these interference noises. Then processed the dynamic weighing signals obtained through the traditional signal processing tools FIR filter firstly, through analyzed the results processed by FIR filter, found the drawbacks of this processing method and made up for these deficiencies by using the method of wavelet transform, then used the neural network BP algorithm to fit the signals processed by wavelet transform. Ultimately, the vehicle dynamic weighing signal basically consistent with the real weight of vehicle and this method improved the accuracy of dynamic weighing system. |
PDF Full Text Request