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Modeling and experimental study on drilling rig anti-jamming valve with BP neural network

Wei Ma ; School of Mechanical Engineering, University of Science and Technology Beijing
Fei Ma ; School of Mechanical Engineering, University of Science and Technology Beijing


Puni tekst: engleski PDF 1.133 Kb

str. 99-106

preuzimanja: 574

citiraj


Sažetak

An effective anti-jamming system is significant in improving the working reliability of hydraulic drilling rigs. An anti-jamming valve is a core component of an anti-jamming system. A back-propagation (BP) neural network model was established for an anti-jamming valve by analyzing the structure and working principle of an anti-jamming valve on a drilling rig and by utilizing the theory of neural network. The established model was employed and applied with the raw information to a stone pit to perform structural topology optimization and obtain the optimal model. The theoretical feed pressure was determined through calculation and analysis after the rock drill became completely jammed. A comparison between the relative error of computed results and the experimental values shows that the forecast data obtained with the BP model (8%) are closer to the experimental values than those obtained with the theoretical formula (14%). The highly nonlinear characteristic of a BP neural network provides a fresh insight into the intellectualization of a drilling rig anti-jamming system.

Ključne riječi

drilling rig, anti-jamming valve, Back-propagation (BP) neural network, hidden layers, rotation pressure control feed (RPCF)

Hrčak ID:

155317

URI

https://hrcak.srce.hr/155317

Posjeta: 827 *