Research On Bit Status Monitoring Method Of Raise Boring Machine With "Virtual And Real Twin,Data And Intelligence Fusion"

With the advantages of high safety,good quality,high environmental friendliness,fast construction speed and high mechanization,the Raise boring machine is widely used in the construction of underground shafts such as hydroelectric power stations,ventilation shafts and elevator shafts.At present,there are several problems in the construction with the use of Raise boring machine,such as the difficulty in selecting drilling parameters due to the uneven distribution of rocks in the geology,the difficulty in matching the drilling tool system with the strata being drilled,the stuck drilling and broken drilling caused by the invisible working condition of the drill bit,and the lack of real-time feedback and prediction during the drilling work.Traditionally,the operation of a Raise boring machine relies on the subjective experience of the operator,which is subject to personal subjective influence and is prone to drilling accidents due to improper operation.In this paper,the main research object is the reaming drilling process of the Raise boring machine,and MATLAB is used as the experimental research platform to provide a new solution to the above problems by using various knowledge such as Simulink programming,Solid Works modeling,and Extreme learning machine prediction model.The main research contents and conclusions of this paper are as follows.(1)MATLAB/Simulink-based Digital Twin System for Reaming Drilling Process Planning.In order to solve the problems of difficult selection of drilling parameters and difficult matching between drilling tool system and the drilled formation caused by uneven distribution of rocks in the geology,this paper constructs a mathematical relationship model between drill pipe tension,drill pipe torque,spindle speed,drilling speed and rock characteristic parameters of the machine using Simulink.The Simulink system model of the positive pressure and hobbing force applied in the rock breaking process of a single hob is established.And the above model was used to establish a digital twin system for reaming drilling process planning,which can be used to provide a reference basis for the selection of relevant parameters of the drilling rig during the construction process.Due to the complex composition of the subsurface rock and the complexity of the raise boring process,the proposed process planning system only considers its simple working process.And MATLAB is used to design the GUI user interface and Android user program for the established digital twin system of reaming drilling process planning,which facilitates the sharing and application of this process planning system.(2)Study on model-data-scene coupled modeling method of the virtual-real twin of Raise boring machine bit.In order to solve the problems of stuck drilling and broken drilling caused by the invisibility of the drill bit when working downhole,this paper uses Solid Works to make a digital 3D model of the reaming drill bit of the BMC400 Raise boring machine and build a system model of the drill bit in Simulink.The simulated sensor signals were used to drive the drill bit,and the visualization of the working state of the drill bit during downhole operation was realized in MATLAB/Mechanics Explorer.The rig stuck drilling condition was added by fault injection technique,and the rig related sensor signals were simulated in the digital twin system of the drill bit during the broken drilling condition,which is important to avoid the stuck drilling and broken drilling problems effectively.(3)Research on the study of digital intelligence fusion monitoring method for the drill bit status of Raise boring machine based on extreme learning machine(ELM).The ELM algorithm prediction model of tension,torque,spindle speed and drilling speed during the reaming drilling work of the Raise boring machine was established using the drilling data of the rig under different working conditions.The ELM classification algorithm model is also used to classify and train the drilling working process working condition data,and the ELM algorithm based working condition monitoring model is established.In order to improve the accuracy of the prediction of rig working conditions,this paper constructs the kernel extreme learning machine algorithm model and completes the research of the digital intelligence fusion monitoring method for the reaming drill bit of the Raise boring machine.