This study suggests a method for quantitatively estimating the drilling performance of the down-the-hole (DTH) hammer during percussive drilling of rock surfaces. A pneumatic dynamic model of the DTH hammer was developed that considers the mass flow rate relations representing the orifice opening areas of the air tube, the piston, and bit flushing channels. A drill bit motion model was developed to represent the dynamics of a drill bit impacted by a dropped piston and explain the impact stress propagation and rock-crushing mechanism. The rock-crushing effect of the drill button bit was measured through a piston drop test. The pneumatic hammer model and drill bit motion model were then combined in a prediction model to determine the impact efficiency according to different rock types (i.e., soft, medium-hard, and very hard). The drilling efficiency was defined as the input value of the prediction model, which was used to simulate the drilling performance of DTH hammers considering the rock type and dynamic effect of the drill bit. Finally, the simulation results were compared with the results of in situ drilling tests for verification.

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In this article, we propose a new regression equation to predict the noise of a power transformer based on the winding vibration under a loading condition. A regression between load noises and tank vibrations for multiple transformers with different rated powers was confirmed through measurements and regression analysis. A regression equation for load noise and winding vibration was derived considering the fact that the winding vibration level is proportional to the tank vibration level. The electromagnetic force, which is the excitation force of the winding, was obtained using the equivalent magnetic circuit network method to obtain the winding vibration required for the regression equation. Subsequently, the obtained force was applied to a finite element model for the winding to achieve the vibration response. The winding vibration obtained through these methods is closely correlated with the load noise, and the amount of winding vibration transferred to the tank could be changed according to the distance between the tank and the winding. Accordingly, an equation for predicting the load noise was established considering the winding vibration and the correlation factors according to the distance of the transmission path. The proposed prediction equation is considerably more accurate than the previous prediction equation.

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