Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Vehicle overload discrimination method, system and device based on BP neural network

A technology of BP neural network and discriminant method, which is applied in the field of physics and can solve problems that have been published in the literature and have no relevant research

Inactive Publication Date: 2019-02-22
上海经达信息科技股份有限公司
View PDF4 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, there is no relevant research on the quantitative evaluation of vehicle driving behavior based on massive data mining.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Vehicle overload discrimination method, system and device based on BP neural network
  • Vehicle overload discrimination method, system and device based on BP neural network
  • Vehicle overload discrimination method, system and device based on BP neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] The method, system and device for judging vehicle overload based on BP neural network of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0052] Such as figure 1 Shown, the present invention is based on the vehicle overload discrimination method of BP neural network, comprises:

[0053] (1) Overload source data preparation process

[0054] The original data is vehicle positioning data (including license plate number, driving time, longitude, latitude, speed, etc.), CAN bus data collected by OBD (including time, speed, speed, engine load, expected engine speed, instantaneous fuel consumption) and vehicle operation conditions Table (including license plate number, vehicle type, operating time, loading location, unloading location, cargo weight).

[0055] Preprocess the vehicle positioning data, CAN bus data and vehicle operation conditions to obtain overload source data (including license plate number, time, ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a vehicle overload discrimination method based on BP neural network, which comprises the following steps: S1, preprocessing the overload source data; S2, establishing an overload model by using a BP neural network structure; S3, substituting the pretreated overload source data into the overload model to obtain the load prediction value. The invention firstly carries out data preprocessing and integration on the collected various data so as to obtain source data for overload analysis. Then on the basis of distinguishing transport time and road type, the source data is divided into transport time and road type (freeway, urban expressway, urban main road, urban secondary road, urban common road). In different periods of transportation, for each road type, the BP neural network is used to model, and the mathematical model between vehicle driving behavior and vehicle load is obtained. The rated load of specific vehicle type is compared to determine whether there isoverload phenomenon in the vehicle.

Description

technical field [0001] The invention relates to the field of physics, in particular to measurement technology, in particular to a method, system and device for judging vehicle overload based on BP neural network. Background technique [0002] With the gradual development of science and technology, the substantial improvement of people's living standards, the increasingly developed transportation, and the increasing number of vehicles, traffic safety has become the theme of today's road traffic. Among them, the traffic safety problems caused by violations of large trucks are particularly serious. While overweight caused serious damage to the road surface, it also caused many major traffic safety accidents. In order to check the overweight violations of trucks, the traffic management department usually sets up overweight monitoring points on the main roads. Due to the fixed time and location of the monitoring points, it cannot effectively monitor the overloading violations of ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/06G06N3/04
CPCG06Q10/0639G06N3/045
Inventor 罗赞文吴华玲
Owner 上海经达信息科技股份有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com