复杂隧道巡检智能装备结构优化与检测精度提升算法研究OA

To address the issues of inadequate operational stability and vulnerable detection accuracy of intelligent inspection equipment in complex tunnel environments,this paper carries out the research from two perspectives:structural optimization and novel algorithms.At the structural level,a plug-in lightweight frame is designed with aluminum alloy as the core material.The mortise-and-tenon structure is adopted to disperse stress,and modular interfaces are equipped to enhance the flexibility of peripheral mounting,which can achieve the organic integration of lightweight design and expandability.An anti-derailment suspended traveling mechanism is developed,featuring a side-mounted track design to reduce detection blind spots.In order to ensure the operational reliability of the equipment,a dual anti-derailment mechanism is constructed by combining physical locking with a track-encapsulating wheel system.At the algorithm level,an adaptive noise covariance adjustment strategy is proposed.Based on residual analysis,the process noise covariance matrix Q and observation noise covariance matrix R of the Kalman filter are dynamically optimized to improve the resistance to airflow disturbances.Experimental verification demonstrates that the proposed algorithm outperforms the traditional Kalman filter under various disturbance conditions:the root-mean-square error(RMSE)is reduced by 6.25%under no disturbance,28.24%under moderate disturbance,28.21%under strong disturbance,with an overall average reduction of 25.27%.The research results significantly improve the environmental adaptability and detection accuracy of the inspection equipment.