Overload recognition method for trucks based on power distribution and self-learning

Abstract

The invention provides an overload recognition method of a truck based on power distribution and self-learning. The method includes: obtaining load identification data of the vehicle, the load identification data including: on-board fault diagnosis system data, global positioning system data, geographic information system data and vehicle information data; calculating the AOP value and STP of the vehicle according to the load identification data of the vehicle value; construct the power distribution curve of the vehicle under the standard full load state according to multiple sets of AOP values ​​and STP values ​​of the vehicle under the standard full load state; The AOP value is compared, and whether the vehicle is overloaded is identified according to the comparison result. The present invention can display the operation status of overloaded vehicles on the road network in real time based on the monitoring platform of heavy truck operation information, and provides convenience for the management of over-limit and overload. Real-time monitoring of the load status of vehicles operating on the road network without additional equipment is required, which improves the range of overload identification.

Description

technical field [0001] The invention relates to the technical field of vehicle overload detection, in particular to a method for identifying truck overload based on power distribution and self-learning. Background technique [0002] Road transportation is an important part of cargo transportation. According to the Statistical Yearbook of the National Bureau of Statistics, in 2017, my country's freight volume totaled 48,048.50 million tons, of which road transportation was 36,868.58 million tons, accounting for 76.7%. As a vehicle for road transportation, heavy goods vehicles undertake heavy cargo transportation tasks. In the market economy environment where interests are pursued, the phenomenon of overloading and exceeding the limit is very common, which seriously endangers the safety of public transportation, and at the same time poses a greater threat to the safety of roads and bridges in the country. In this regard, our country has been unremittingly grasping the problem...

AI Technical Summary

Problems solved by technology

[0008] The disadvantages of the above-mentioned vehicle static weighing system include: (1) the vehicle load can only be measured at a fixed position or at a fixed time; (2) the vehicle speed is slow, resulting in long-term queue congestion; (3) the identification system is huge in size and complex in structure , difficult to install; (4) The purchase cost and maintenance cost of the identification system are high

[0009] The disadvantages of the above-mentioned vehicle dynamic weighing system include: (1) the structure of the identification system is more complex and difficult to install; (2) the cost of purchase and maintenance is higher; (3) it can only be installed at fixed points, and it is difficult to apply on a large scale; 4) The recognition accuracy is greatly affected by external factors (road surface smoothness, slope, vehicle tire pressure, etc.)

[0010] The disadvantages of the above-mentioned on-board weighing system include: the system recognizes the vehicle load through the elastic deformation of the body components after being loaded, so the transmission sensitivity of the sensor directly affects the accuracy of vehicle load identification

The elastic deformation of body components is greatly affected by the vibration of the body, the running speed and acceleration of the vehicle, which affects the accuracy of load recognition

In addition, during long-term use, external factors such as fatigue and mechanical creep will cause irreversible interference to the sensor

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