Research Of The Vehicle Speed And Acceleration To Dynamic Weighing System

In recent years, with the rapid development of China’s market economy, the transportation industry is also growing prosperity. Many kinds of transport vehicles blind pursuit of profit maximization, causing a very serious problem about overload vehicle. It results in that the road infrastructure was severely damaged, induced a large number of traffic accidents, disrupted the transportation market order and caused a serious threat to the safety of the lives and property of the state and the people.In order to governance the overloading vehicles strictly, dynamic weighing system has been widely used in recent years.Dynamic weighing system has two kinds of weighing methods, includes static weighing and dynamic weighing. The static weighing means in the weighing period, there is no relative movement refer to the weighing bearer. This method has a good reproducibility, and is the most accurate weighing method. But it is less efficient, and is easy to cause traffic congestion. Dynamic weighing means in the weighing period, there is some relative movements refer to the weighing bearer. This method can shorten the measurement time, and improve measurement efficiency. But it increases many impact factors which can not be predicted, and also some repeatability error.Found in the actual test, vehicle speed and acceleration have a significant influence to the dynamic weighing system. The errors caused by measured vehicles which go through the weighing platform at different speeds are not the same.In order to decrease weighing errors caused by all kinds of interference as much as possible, to ensure the measurement accuracy to meet the national standards, we need do some error analysis about the vehicle speed, acceleration and load data, and develop effective data processing methods to reduce the weighing errors.This paper analyzes the structure and working principle of the vehicle dynamic weighing system, elaborates the work process, details the interference signals which impact of the weighing results accuracy. The interference signals mainly include the high-frequency noise signal and the low-frequency noise signal, while the low-frequency interference signals such as the vehicle speed and acceleration are the most important factors that affect the weighing results. Through vibration modeling and mechanical analysis to the vehicle, we detailed analysis of the affect caused by the vehicle speed and acceleration to dynamic weighing results.For the acquisition of the vehicle speed and the acceleration signal, and further validate the affect caused by them to the dynamic weighing results, a kind of vehicle traveling state wireless monitoring device is introduced in the third chapter. We use it to collect the vehicle speed and acceleration data at the scene. This chapter introduces the architecture and working principle of the device, and analysis of the structure and precision of the rotary encoder detailed. Then followed by a detailed description of the device from two parts of the hardware and software design.In the fourth chapter, the vehicle weighing signal and vehicle speed and acceleration signals are collected at the scene, and analyzed comprehensively. First, several data preprocessing methods are introduced detailed, and the moving average filter is selected for filter processing of the collecting signals. Subsequently, the effective sample processing is used in the acquisition signals, and the weighing error in different traveling speed of 5km/h, lOkm/h,15km/h, 20km/h and 25km/h is analyzed. At last the analysis conclusion is draw.In order to reduce the impact of the weighing results due to the uncertain interference factors such as vehicle speed and acceleration, finally, the paper details the dynamic weighing data processing based on Kalman filtering method.The modeling process of the system and the Kalman filter algorithm process are described, and Kalman filtering process is used on the sampling signals. Experiments show that, Kalman filtering method can improve the measurement accuracy of the weighing results.