Shield construction ground subsidence prediction system and method based on big data analysis

Abstract

The invention discloses a shield construction ground subsidence prediction system and a method based on big data analysis, and mainly aims to solve the problem that ground subsidence cannot be predicted in an efficient and timely manner in a shield construction big data scene. A big data platform comprises a data collection module, a data preprocessing module, a feature extraction module, a prediction model building module, a model application module, and the like, which provide massive data storage and parallel computing services, and constitute the ground subsidence prediction system. The prediction method comprises the following steps: building a big data platform; collecting ground subsidence data during shield construction; preprocessing the data; extracting features; building a ground subsidence prediction model; packaging the function interfaces of the prediction model; and predicting ground subsidence in the construction process. The whole scheme is rigorous and complete in design, has massive data storage and parallel computing ability, is efficient and accurate in ground subsidence prediction, is used to predict ground subsidence caused by subway construction, and ensures the project quality and safety.

Description

technical field [0001] The present invention belongs to the technical field of industrial big data, and in particular relates to ground subsidence prediction in the field of subway shield construction, specifically a system and method for prediction of ground subsidence in shield construction based on big data analysis technology, which can be used for ground subsidence prediction during shield construction Prediction of settlement. Background technique [0002] With the continuous expansion of the scale of subway construction, shield excavation equipment for subway tunnel construction has been widely used. The shield machine is a large-scale mechanical-electrical-hydraulic control integrated equipment with a complex structure. At the same time, due to the relatively harsh construction environment of the shield machine and the complex and changeable geological environment, many problems will arise during the construction process. Among them, the construction of the subway is...

AI Technical Summary

Problems solved by technology

[0004] Regarding the establishment of the land subsidence prediction model, the traditional method is usually to train the model in a stand-alone and serial mode. When faced with massive data, due to the huge amount of data, the storage and processing of data will expose poor fault tolerance, slow speed, low efficiency

This is contrary to the real-time, rapidity and accuracy required for shield ground subsidence prediction

At the same time, the amount of data used by traditional methods is small, which has a great impact on the accuracy of the established forecasting model

[0005] With the continuous expansion of the scale of subway construction and the increasing mass of shield construction data, traditional analysis methods are faced with intractable speed and efficiency problems brought about by the huge amount of data, which seriously affects the storage capacity and processing speed of shield construction data. , which in turn affects the real-time prediction of ground subsidence during shield tunneling

At the same time, traditional methods can only deal with small sample data, which will reduce the prediction accuracy of the prediction model

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