Method for Collision Relationship of Hydraulic Supports Considering Multilayer Sensing Errors

To address the issues of low accuracy and insufficient information in the pose measurement of hydraulic support caused by complex working conditions, this article proposes a method for pose optimization and collision resolution. First, based on the structure and significance, the pose is divided into “three layers of base pose-one layer of internal pose.” A mapping model of each layer’s pose and sensing error is established to accurately resolve errors. Then, the Bayesian algorithm is employed to infer the single pose under a normal distribution. A multimodel system is constructed through five steps: updating measurement, updating error, prior calculation, Bayesian estimation, and pose correction, to optimize the complete pose of support. Subsequently, three highly credible virtual support scenes are constructed. Sensor information is input into the pose optimization scene to generate the pose distribution, which is synchronized to the collision-solving scene to visualize and solve collision probabilities. This probability is then fed back to the monitoring scene for warning judgment. Finally, various conditions are set for pose optimization and collision-solving experiments. The results show that the accuracy of the optimized support pose is enhanced by an average of 11.57% and the collision between supports is accurately simulated. This verifies the accuracy of the theoretical research and the Bayesian algorithm. The approach is beneficial to warn the timely abnormal situation warnings, enhancing the reliability of underground support, and providing an important reference to support following control and adjustment.