Research On Rapid Detection Method Of Fresh Agricultural Products On Expressway

At present,there are still many problems in the detection of fresh agricultural transport vehicles in China's expressways.On the one hand,the length of detection and the cumbersome detection process lead to an increase in the queue length of the toll station,and the passage rhythm becomes slower.On the other hand,in order to obtain the toll reduction,the driver encloses the goods that are not in the “Catalogue of Fresh Agricultural Products” as“green channel” vehicles.According to the "Green Channel" policy requirements,once the vehicle is found to be cheating,the staff of the toll station will carry out criticism and education work for the driver,and the driver can pay the corresponding toll according to the regulations.Insufficient penalties and low cheating costs have led to a continuous increase in the number of cheating trucks.Common fresh agricultural products transport vehicles inspection methods have manual inspection and radio equipment inspection.Manual inspection and identification is poor and labor-intensive.The radiation device is expensive,expensive to maintain,and has a high radiation hazard.In order to realize the effective identification of cheating vehicles,simplify the inspection process,speed up the passage and improve the charging efficiency,this paper proposes to construct a rapid detection method for fresh agricultural products.Firstly,this paper analyzes the existing "green channel" detection method and inspection process,and expounds the use of big data method to deal with the average axle load of the average empty vehicle weight and empty vehicle state,construct a cargo density library with normal distribution,and apply torque balance.Calculate concepts such as the center of gravity of the goods.Through field research at the Huangmeinan Toll Station in Hubei Province,the traffic data and size information of the “Green Passage” vehicle were obtained,and the cargo density library was constructed to establish a density discrimination method and a cargo center of gravity discrimination method.Using the combination of two discriminating methods,the overall discriminant results of the system are determined to be reasonable,mildly suspected,and seriously suspected.Finally,a rapid detection system for fresh agricultural products will be established to achieve the purpose of quickly and effectively testing green traffic.Through the example verification,10 trucks that were seriously suspected by the system were unpacked and inspected,and 6 trucks were cheating.The effective rate of the system for cheating green traffic is 60%.In addition,the system effectively reduces the vehicle inspection time,reduces the “green channel” manpower input,improves the working efficiency of the toll station,and realizes the expected function of the system design.Thisdesign is beneficial to the management of highway toll stations,and has reference and reference for the inspection of fresh agricultural products transportation vehicles.