交通节能与环保2026，Vol.22Issue(3)：133-139,7.DOI:10.3969/j.issn.1673-6478.2026.03.026
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
Structural Optimization of Intelligent Tunnel Inspection Equipment and Detection Accuracy Improvement Algorithms for Complex Tunnels
摘要
Abstract
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.关键词
巡检智能装备/拼插式轻量化框架/悬挂式行走机构/自适应噪声协方差/卡尔曼滤波Key words
intelligent inspection equipment/plug-in lightweight frame/suspended traveling mechanism/adaptive noise covariance/kalman filter分类
交通工程引用本文复制引用
陈尧..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[J].交通节能与环保,2026,22(3):133-139,7.基金项目
京雄云控(北京)2024年第十批数字交通建设专项采购项目(20250013) （北京）
