With the rapid development of the transportation industry, it also brings the phenomenon of overloaded trucks. In order to put an end to this bad phenomenon, China vigorously promotes the way of charging by weight. With the popularization of the method of weighing and charging, the requirement of dynamic weighing technology is becoming higher and higher. Hengyi mainly completed the design of weighing instrument in WIM system and the improvement of weighing accuracy of instrument. Based on the analysis of the function of the full-vehicle weighing instrument and the realization of the weighing algorithm, the design scheme of the full-vehicle dynamic weighing instrument based on STM32 is given. The design scheme is divided into three parts :1) algorithm simulation. 2) Hardware design. 3) Software design. The algorithm simulation mainly completes the simulation and comparison of the weighting preprocessing algorithm and the weighting core processing algorithm. The hardware design mainly completes the circuit design of the weighing instrument. The software design mainly completes the realization of the basic functions of the instrument. In the algorithm simulation, the composition of the weighing signal is analyzed. Based on the simulation and comparison of the algorithm, the algorithm combination of FIR filter and three-layer back propagation neural network is obtained. The algorithm combination has significantly improved the weighing accuracy. In the hardware design, the basic components of THE WIM system are introduced and some circuits of the weighing instrument are studied and analyzed. In the software design, the design idea and key technologies of each module are emphatically introduced, and the comparison and implementation of typical algorithms are completed. It is verified that the algorithm combination selected in this paper meets the national standards, and is obviously better than the traditional algorithm, and effectively improves the weighing accuracy of the weighing instrument.
Post time: 2021-08-13 14:04:24