China's "Code for Maintenance of Highway Bridges and Culverts", "Guiding Opinions of the Ministry of Transport on Promoting the Construction of New Infrastructure in the Field of Transportation" and "Tenth Five-Year Development Plan of Modern Comprehensive Transportation System" and other related policies clearly point out that strengthening highway bridge maintenance, establishing highway bridge management system, compiling bridge maintenance quota, encouraging the application of intelligent maintenance facilities and equipment, and improving the ability of inspection, detection, monitoring, evaluation, risk early warning, maintenance decision-making and rapid operation. Promote the implementation of life cycle maintenance, strengthen normalized preventive maintenance, and scientifically implement maintenance operations.
In order to promote the high-quality operation of bridges, effectively improve the comprehensive management level of bridge operation and maintenance safety, speed up the construction of a strong traffic country, and improve the safety risk prevention and control and operation system of highway bridges, Guangdong Ground-to-Air Intelligent Technology Co., Ltd. has innovatively created a "GSI-BOM Bridge Health Operation Management Platform" which integrates the whole scene, three-dimensional monitoring and early warning system, multi-party linkage command and dispatch mechanism and intelligent and accurate information release to realize all-weather digital supervision. Sensors and high-definition cameras inside and outside the bridge have become the "eyes" of the safety management of bridge operation, helping the management of "zero death" of bridge deck traffic, "zero collision" of waterway navigation and "zero intrusion" of space under the bridge.
Links: Web links
The platform starts from three aspects: above the bridge, below the bridge and the bridge structure. On the one hand, it pays attention to healthy operation, on the other hand, it displays diversified data for bridge maintenance. Based on data governance, Internet of Things, cloud computing and other technologies, we can realize data visualization and cloud storage, grasp the running state management of monitored objects in real time, realize AI intelligent automatic analysis and judgment, release early warning information, and help road patrol, rescue, maintenance and other forces to carry out emergency response in the same platform.
The platform includes four parts: digital bridge management, monitoring management, early warning management and decision-making. It has the technical advantages of intelligent perception, accurate early warning and three-dimensional prevention and control. It connects bridge health monitoring data, maintenance management data, on-site intelligent hardware equipment data and Internet data, establishes comprehensive perception of bridge operation scenarios, forms operation support data through deep data fusion, and serves road administration companies, road administration, traffic police and public users through various terminals.
Technical application:
First, big data+cloud computing technology enhances the value of bridge data
The platform adopts advanced data governance and cloud computing technology, and on the basis of ensuring the safe and stable operation of the platform, it realizes the rational allocation of hardware resources and provides multi-dimensional, cross-departmental and full-process data governance capabilities. Through configurable rapid deployment, data assets including data standards, master data, metadata, data quality and rule model will be landed on the GSI-BOM bridge health operation management platform to help users fully control the equipment, bridge structure and management. The platform combines bridge operation safety with structural safety, and through the fusion of multi-source data inside and outside the bridge structure and the environment in the bridge area, through the storage, collection, cleaning, screening, integration, mining, identification and evaluation of massive data, carries out statistical analysis of bridge operation monitoring data, grasps the service status of the bridge in real time, discovers the data change characteristics of equipment, bridge structure, vehicles and ships before the bridge risk occurs, and comprehensively improves the ability of operating units to identify bridge risks.
Second, machine deep learning analysis technology monitors abnormal events and effectively improves inspection efficiency.
Based on the video image analysis technology of machine deep learning, the sensor equipment for heavy vehicle detection combined with the fully automatic detection point established by Internet technology can detect the whole vehicle picture, close-up picture of vehicle front, license plate number, single axle weight, axle number, axle group weight, total vehicle weight, wheelbase, total wheelbase, vehicle length, vehicle speed, vehicle flow, vehicle distance, driving direction and vehicle type without affecting normal traffic operation. The platform can dynamically and accurately detect abnormal events on the bridge deck around the clock, including traffic accidents, bad weather (rain and fog), road splash, pedestrian intrusion, traffic congestion and other abnormal events, thus effectively guiding the staff to carry out targeted inspections, ensuring early detection, early disposal and early diversion of abnormal events, and avoiding the occurrence of secondary accidents.
Third, dynamic risk prevention and control technology can improve the efficiency of "prevention" and "control"
The platform converts the structural response information obtained by the data acquisition system into information reflecting the structural safety state. By constructing a dynamic intelligent risk prevention and control system for bridges, under the guidance of the disposal mechanism based on the responsibility matrix, the disposal strategies are adaptively recommended for different risk levels, so as to realize the automatic allocation of disposal tasks and ensure the efficient disposal of bridge risk events and abnormal events. On this basis, through the comprehensive evaluation of the safety status information, the safety degree and health status of the bridge structure at a specific moment can be obtained, so as to formulate a scientific and reasonable bridge maintenance plan, which will shorten the time for issuing disposal tasks by more than 60% year-on-year.
Fourthly, the bridge icing early warning technology is helpful to the road control in snow and ice weather.
Based on the temperature and humidity sensor data, multi-function weather station data and long-term weather data of the Internet, the machine learning model is trained, and the platform accurately predicts the icing risk at different positions of the bridge, and gives early warning tips through the system, which changes "post-disposal" into "pre-defense", effectively supports the ice melting and snow removal work of bridge operating companies in winter, and can effectively reduce the risk of traffic accidents caused by road icing.
Five, bridge anti-collision early warning technology, effectively guarantee the safety of the bridge.
In order to avoid ships colliding with bridges, the platform uses hardware facilities such as AIS, video surveillance and solid-state radar to identify and track ships and objects on the river surface, effectively eliminating interference in foggy days, at night and other environments where the visual system is invisible, and realizing all-weather monitoring of sensitive areas. The monitoring signal is transmitted through the network. The main control room can control the radar, set the warning zone, and realize the data fusion with the chart, so as to identify and judge the approaching ships and give an alarm. When the ship approaches the warning zone set on the bridge, the target entering the warning zone is continuously tracked and alarmed, and the photoelectric system is linked to locate the target, so as to realize the anti-collision monitoring on the bridge. The platform gives an alarm to the ship according to the information discrimination, prompts the ship to stop moving, and records the information of the ship at the same time. In case of collision, it can be traced back to ensure the safety of the bridge. At present, the ship detection accuracy of the system is higher than 95%, and the arrival rate of control information is 99%.
Six, three-dimensional visual display technology, digital empowerment operation management
The platform adopts 3D laser scanning technology to build regular 3D modeling, and dynamically displays the disease information of bridge bearings, such as voids, cracks, dislocations, falls off, etc., covering all aspects of bridge maintenance management, creating a one-stop data analysis and visualization platform, dynamically simulating bridge operation conditions, fitting bridge operation scene interaction and real-time data monitoring, which can improve the accuracy and intuition of disease description, provide correct information support for maintenance decision-making, and enable users to easily grasp the first-hand dynamic information of bridge operation and empower them.