Pile static load test data analysis method based on multi-source data fusion and ai

Abstract

The application is suitable for the technical field of test data analysis, and particularly relates to a pile foundation static load test data analysis method based on multi-source data fusion and AI, which comprises the following steps: obtaining load displacement time series data and geotechnical body survey data of a target pile foundation static load test; performing feature recognition and feature extraction on the geotechnical body survey data and the load displacement time series data respectively to generate corresponding geotechnical feature vectors and comprehensive influence feature vectors; inputting the comprehensive influence feature vectors and the geotechnical feature vectors into a preset bearing property degradation prediction model and a limit bearing capacity evaluation model respectively to accurately obtain a bearing capacity degradation rate and a current limit bearing capacity of the target pile foundation; and performing safety evaluation on the service performance of the target pile foundation based on the bearing capacity degradation rate and the current limit bearing capacity and generating a safety evaluation conclusion, thereby improving the comprehensiveness, accuracy and individualization level of pile foundation static load test data analysis, shortening the analysis cycle and reducing the labor cost.

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