Modeling and Experimental Study on Drilling Rig Anti-jamming Valve with Bp Neural Network

Article history: Received: 17.3.2015. Received in revised form: 22.9.2015. Accepted: 24.9.2015. 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 backpropagation (BP) neural network model was established for an anti-jamming valve by analyzing the structure and working principle of an antijamming 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.