Pile damage identification method and device based on convolutional neural network, and medium

Abstract

The invention discloses a pile damage identification method and device based on a convolutional neural network and a medium, and the method comprises the steps: building a plurality of models for a to-be-detected pile structure according to the condition attributes of a to-be-detected pile, solving the models, and generating a speed time history curve of a preset position point on the to-be-detected pile, and generating a speed-time history recursion plot based on the speed-time history curve, inputting the speed-time history recursion plot into the neural network model for detection, and outputting a pile damage parameter evaluation result. The pile structure of the to-be-detected pile is modeled according to the condition attributes of the to-be-detected pile, and the overall condition of the to-be-detected pile can be analyzed and known more comprehensively. And the neural network model has extremely high non-linear large-scale parameter parallel analysis and processing capability, and can better process the complex damage identification problem in the pile-soil structure and improve the accuracy of pile damage identification in combination with the convolutional neural network processing speed time-history recurrence plot.

Description

technical field [0001] The invention belongs to the technical field of computer deep learning, and relates to a pile damage identification method, equipment and medium based on a convolutional neural network. Background technique [0002] A deep foundation consisting of a pile and a pile cap connected to the top of the pile (referred to as a cap) or a single pile foundation connected by a column and a pile foundation, referred to as a pile foundation. Pile foundations are mainly used to provide bearing capacity for the superstructure (beams, slabs, caps, pile caps, etc.). Pile foundations are widely used. The use of pile foundations can greatly reduce the workload and material consumption on the construction site, and the deformation of pile foundations under the action of earthquake force is small and the stability is good. an effective measure. [0003] Due to the wide variety of pile foundations, large differences in construction techniques, and complex stratum changes,...

AI Technical Summary

Problems solved by technology

However, for the built structure, due to the existence of the superstructure, it is often necessary to arrange multiple excitation points and install sensors at different positions for testing. Due to the difference between the sensor position and the excitation position and the existence of the superstructure, the The nonlinear relationship is strong, which often causes the complexity of the pile foundation damage identification process, and the identification accuracy is not high

As a system technology for simulating human brain behavior, neural network has extremely strong nonlinear large-scale parameter parallel analysis and processing capabilities, and has good adaptability. It can be used as nonlinear system modeling and damage identification evaluation constructed with multiple unknown parameters. , while the accuracy and efficiency of the existing neural network damage identification are not high

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