Method for identifying spatial-temporal distribution of vehicle loads on bridge based on densely connected convolutional networks
US11692885B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 3, 2020 |
| Grant date | Jul 4, 2023 |
| Priority date | — |
| Expiry date | Nov 2, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30236
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention proposes a method for identifying the spatial-temporal distribution of the vehicle loads on a bridge based on the DenseNet. The method includes five steps: firstly, mounting a plurality of cameras in different positions of a bridge, acquiring images of the bridge from different directions, and outputting video images with time tags; secondly, acquiring multichannel characteristics of vehicles on the bridge by using DenseNet, including color characteristics, shape characteristics and position characteristics; thirdly, analyzing the data and characteristics of the vehicles from different cameras at a same moment to obtain vehicle distribution on the bridge at any time; fourthly, continuously monitoring the vehicle distribution in a time period to obtain a vehicle load situation on any section of the bridge; and finally, integrating the time and space distribution of the vehicles to obtain spatial-temporal distribution of the bridge.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.