Research on Bridge Health Management Prediction System Based on deep learning
Zhichao Liu
Abstract
Zhichao Liu
Abstract
The bridge management is investigated and studied. At present, the bridge management mode and management means are old. The bridge data collected, analyzed and managed by manual method brings a lot of inconvenience to the maintenance and management; If the technical archives of some bridges are lost, we can only rely on qualitative understanding and the experience of technicians to analyze the technical status of bridges, and make decisions according to past experience to determine the bridge maintenance and repair scheme; At the same time, as the maintenance funds are not guaranteed and the technical force is low, the necessary daily maintenance of the bridge cannot be guaranteed, resulting in the rapid deterioration of the diseases and defects of the bridge, reducing the bearing capacity of the bridge and affecting the normal use of the bridge. Research on the prediction system of bridge health management based on deep learning, and develop an artificial intelligence system, which can predict the bridge health status according to the data collected from the sensors installed on the bridges all over the world.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The bridge management is investigated and studied. At present, the bridge management mode and management means are old. The bridge data collected, analyzed and managed by manual method brings a lot of inconvenience to the maintenance and management; If the technical archives of some bridges are lost, we can only rely on qualitative understanding and the experience of technicians to analyze the technical status of bridges, and make decisions according to past experience to determine the bridge maintenance and repair scheme; At the same time, as the maintenance funds are not guaranteed and the technical force is low, the necessary daily maintenance of the bridge cannot be guaranteed, resulting in the rapid deterioration of the diseases and defects of the bridge, reducing the bearing capacity of the bridge and affecting the normal use of the bridge. Research on the prediction system of bridge health management based on deep learning, and develop an artificial intelligence system, which can predict the bridge health status according to the data collected from the sensors installed on the bridges all over the world.
Key concepts: Bridge (graph theory), Bridge maintenance, Management system, Computer science, Health management system, Health maintenance, Engineering, Operations management