Abstract: A high-precision intelligent detection method for bridge diseases based on spatial position. The method comprising: collecting images based on the high-definition image acquisition system; importing the image data and position information data into image processing software to create a mosaic image of each part of the bridge; importing the prepared spliced image map into the bridge disease intelligent identification system; obtaining the corresponding position and bridge of the bridge disease in the three-dimensional model of the bridge; identifying the stitched image map to obtain the size of the disease after identifying the bridge disease image and locating the bridge disease. The high-precision intelligent detection method for bridge diseases based on spatial position realizes automatic collection and intelligent analysis of bridge inspection data, reduces the workload of the inspection technicians and improves the detection efficiency.

Abstract: An control system for unmanned highway entrance is provided. The control system includes a server system and a toll collection system. The server system includes an unmanned entrance management system, a data center database, a speech synthesis component, and a speaker component. The unmanned entrance management system electrically is connected with the data center database, the speech synthesis component and the speaker component respectively. The toll collection system includes a data synchronization system, a toll collection database, a vehicle data collection system, a core data processing system, a watchdog system, a variable-message sign system, a card dispensing system, and an unmanned entrance toll collection system.

Abstract: A high-precision intelligent detection method for bridge diseases based on spatial position. The method comprising: collecting images based on the high-definition image acquisition system; importing the image data and position information data into image processing software to create a mosaic image of each part of the bridge; importing the prepared spliced image map into the bridge disease intelligent identification system; obtaining the corresponding position and bridge of the bridge disease in the three-dimensional model of the bridge; identifying the stitched image map to obtain the size of the disease after identifying the bridge disease image and locating the bridge disease. The high-precision intelligent detection method for bridge diseases based on spatial position realizes automatic collection and intelligent analysis of bridge inspection data, reduces the workload of the inspection technicians and improves the detection efficiency.

Abstract: An anti-rutting pavement structure is arranged consecutively from bottom to top, a semi-rigid base layer, a SBS emulsified asphalt adhesive layer, a Type II latex cement mortar poured asphalt concrete lower layer, a Type I latex cement mortar poured asphalt concrete middle layer and a high viscosity modified asphalt SMA-13 concrete surface layer.