Bridge bearing disease identification method based on transfer learning between convolutional neural networks

Abstract

The invention provides a bridge bearing disease identification method based on transfer learning between convolutional neural networks. The method comprises the steps that bridge bearing disease photos are acquired, and label information is assigned to each photo; an image processing method is used to increase the volume of data used for training the convolutional neural networks; all pictures ina training set and a test set are scaled to color pictures of a predetermined size, and image preprocessing is carried out; a convolutional neural network model which is trained on other data sets isacquired; and a knowledge transfer method is used to acquire a convolutional neural network model with the function of automatic bridge bearing disease identification. According to the automatic bridge bearing disease identification method based on the convolutional neural networks, the convolutional neural networks trained in a knowledge transfer mode have obvious advantages in accuracy and convergence speed; the volume of data required for training the neural networks is greatly reduced; and the method is of practical significance for bridge bearing diseases with complex disease scenes and difficult data collection.

Description

technical field [0001] The invention relates to the intersecting field of civil engineering and artificial intelligence, in particular to an automatic recognition method for bridge bearing diseases based on a convolutional neural network. Background technique [0002] With the rapid development of my country's infrastructure construction in recent years, the civil engineering industry has developed rapidly, and a large number of roads and bridges have been constructed, followed by later inspection and maintenance work. The bridge bearing is an important component connecting the upper and lower structures of the bridge. It can be called the throat of a bridge and has a great relationship. Once a disease occurs, if it is not detected and treated in time, it will affect the stress state of the structure and traffic safety. At present, the main method of inspection of bridge bearings is manual inspection, which is time-consuming, laborious and will affect traffic. Some bridges ...

AI Technical Summary

Problems solved by technology

At present, the main method of bridge bearing inspection is manual inspection, which is time-consuming, laborious and will affect traffic

Some bridges built in deep mountains and on the sea are difficult to realize through manual inspection, or it is difficult to ensure the safety of bridge inspection personnel

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