Abstract: This paper investigates measurement while drilling for rock strata interface to achieve geological transparency, promote intelligence development, and address the limitations of traditional rock detection methods in coal mines, including slow speed, high costs, and poor accuracy. Firstly, this study proposes a laboratory-level drilling device for real-time data acquisition of displacement, revolutions per minute, torque, and sound pressure level during drilling the formation model poured in the laboratory. Secondly, an exponentially weighted loss function was used for automatic screening of anomalies in displacement data and obtained a penetration rate that better reflect variations in drilling. Then, the accuracy of rock interface identification was analyzed using parameters such as penetration rate, revolution per minute, sound pressure level, and torque using the application of the change point detection algorithm, the strucchange model in RStudio software, and the decision tree algorithm. Finally, the performance of rock interface identification during drilling was evaluated under 2 typical geological conditions. Rresults indicate that the decision tree algorithm is the most effective method for quick and accurate identification of rock interfaces with penetration rate as the input parameter. On-site tests yielded 0.04m of average error in predicting the position of the coal rock interface. Yet, the method produces relatively low accuracy in rock interface identification of composite roof rock strata.