Automatic identification method for inhaul cable jacket diseases based on transfer learning and inhaul cable robot

Abstract

The invention discloses an automatic identification method for inhaul cable jacket diseases based on transfer learning and inhaul cable robot, and the method comprises the steps: preparing a concretecrack picture, building a ResNet network model in deep learning, and carrying out training, to obtain a training model; obtaining a disease picture of a stay cable PE jacket, dividing the data set into a training set, a verification set and a test set, establishing a transfer learning model of the ResNet convolutional neural network, and training the model; and controlling the stay cable robot tocarry out image acquisition, and carrying out stay cable PE jacket disease automatic identification by using the trained ResNet model. The detection precision is high, the stay cable robot can replacemanual work to perform automatic crawling detection, the automation degree is high, real-time recognition can be achieved, efficiency is high, cost is low, and compared with a traditional manual detection method for stay cable PE jacket diseases, the method has obvious advantages.

Description

technical field [0001] The invention relates to the technical field of interaction between civil engineering and artificial intelligence, in particular to an automatic identification method for cable jacket defects based on transfer learning and cable robots. Background technique [0002] Cable-stayed cables are the main load-bearing components of cable-stayed bridges, and most of the load of the span structure of cable-stayed bridges is transmitted to the tower columns through cable-stayed cables. The loss of bearing capacity of any cable-stayed cable will lead to the overall instability and destruction of the cable-stayed bridge. Therefore, the safety of cable-stayed cables must be highly valued. The PE jacket of the stay cable is scratched and cracked by the external environment, causing the inner steel cable to rust or even break, which will seriously affect the bearing capacity and service life of the stay cable. The current detection methods are still manual visual in...

AI Technical Summary

Problems solved by technology

The PE jacket of the stay cable is scratched and cracked by the external environment, causing the inner steel cable to rust or even break, which will seriously affect the bearing capacity and service life of the stay cable

The current detection method is still based on manual visual inspection and bridge inspection method. This method is time-consuming, laborious, expensive, and low in automation. Therefore, there is an urgent need for an automatic identification method for cable-stayed PE jacket defects.

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