AI identification Model for Continuous Box Girder Displacement Process of Cross-Sea Channel Project under Gantry Crane Track Crossing
In order to improve the quality of continuous box girder displacement and ensure the orderly and smooth progress of the project,an AI identification model for the continuous box girder displacement process of cross-sea channel project under the crossing of a gantry crane track is designed.The process flow of continuous box girder displacement is analyzed,and it is divided into five processes:reinforcement processing,formwork installation,and concrete steam curing.The AI recognition model of the continuous box girder shift process is built using threshold Boltzmann machine and support vector machine in artificial intelligence technology.Continuous box girder shift working images are collected,and these collected images are taken as the model input.The convolution layer and pooling layer in the convolutional neural network are utilized to optimize the threshold Boltzmann machine model.The optimized model is then used to collect the characteristics of the continuous box girder shift working images.Based on different image features,support vector machine is used to classify image categories and complete process recognition.The experimental results show that the model can accurately identify the displacement process of continuous box girder and effectively improve the construction performance and economic benefits of the project.
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