An intelligent decision-making method and system for hard rock TBM tunneling control parameters

Abstract

The present invention proposes an intelligent decision-making method and system for hard rock TBM tunneling control parameters. The method includes the following components: establishment of an engineering database; establishment of a rock-machine mutual-feedback model and an intelligent control decision-making model based on the engineering database; output display and update of model parameters ;automatic / manual excavation parameter control method; model self-learning self-updating algorithm; the system includes the following components: engineering database unit; rock-machine interaction model unit; intelligent control decision-making model unit; Parameter control module; model self-learning and self-updating unit. The rock machine mutual feed model of the present invention predicts the current surrounding rock state parameters according to the equipment operating parameters to sense the TBM tunneling environment in real time; the intelligent control decision-making model predicts the optimal control tunneling parameters according to the current tunneling environment, and adjusts the current tunneling parameters in time by controlling the tunneling parameters. Adapt to the current excavation environment and maintain safe, efficient and stable excavation.

Description

technical field [0001] The invention relates to the technical field of intelligent control of tunnel excavation equipment construction, in particular to an intelligent decision-making method and system for hard rock TBM excavation control parameters. Background technique [0002] Hard rock tunnel boring machine (hereinafter referred to as hard rock TBM) is a large-scale high-tech construction equipment specially used for excavating rock tunnels and underground passages. In the traditional construction method, the driver in the main control room evaluates the state parameters of the surrounding rock through the slow trial excavation process, and then repeatedly adjusts the excavation parameters until the excavation parameters remain stable. On the one hand, such an operation method will consume a lot of construction time due to continuous slow trial excavation and repeated adjustment of excavation parameters; The parameters cannot adapt to the current excavation environment,...

AI Technical Summary

Problems solved by technology

[0003] In view of the existing operation mode, only the main driver’s artificial experience can be used to guess the state parameters of the surrounding rock, and the time-consuming and labor-intensive, abnormal wear of the TBM cutter, the decline in the rock-breaking performance of the cutterhead system, etc. To solve technical problems such as key component damage and downtime, the present invention proposes an intelligent decision-making method and system for hard rock TBM tunneling control parameters, which uses data mining and machine learning technology to predict tunneling parameters, and can adapt to different environments through self-learning and self-updating. Rock, TBMs with different diameters, different performances, and the use of the same TBM in different stages of the life cycle

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