Abstract

In coal mines, precise attitude measurement systems are crucial for enhancing reliability and accuracy. These systems typically integrate multiple sensors to overcome various limitations, such as distance constraints, distractions, and not clear vision. Gyroscopes are employed to tackle these challenges; however, they are very highly critical to slight erosion, which can affect their performance in maximum time. On the other hand, accelerometers do not experience drift but have slower dynamics, posing a between accuracy and response. This study investigates the implementation of a Complemtry filter to offer real-time monitoring of the position and orientation of a mining vehicle in underground mines. The Compatible filter is specifically developed to address various practical challenges, such as sensor output fluctuations and extended periods without receiving local data updates The presentation highlights the application of the Alarm Filter and Kalman filter for bias ratio and mood measurements. The initial focus is on utilizing these filters to measure the yaw angle. By incorporating the Compatible Filter, which employs a data integration algorithm utilizing gyro and compass measurements, a significant improvement in the filter's performance is achieved. This integrated approach simplifies the dynamic modeling of signal sensor activity within the atmospheric network, particularly when dealing with gyro modeling. Applying MATLAB Simulink application k. Additionally, the integration of a magnetic compass and gyro compass into the filter further enhances the accuracy of the sensor device. The primary benefit of this approach lies in the sensor signal independence, making it compatible with any system that utilizes the same set of sensors. By implementing these advancements in attitude measurement systems, underground mines can significantly improve the safety and efficiency of their operations.

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