Unmanned Aerial Vehicle (UAV)-based autonomous damage inspection has become a promising technique to replace certain human-performed inspections due to both safety and cost considerations. While current UAV-based damage inspection methods have been successful in minimizing the length of the flying path considering potential defect locations, the impact of flying path on the quality of structural health monitoring (SHM) has been overlooked. This paper proposes a novel Bayes risk-based mission planning method for UAV-based damage inspection by minimizing not only the UAV path length, but also the associated SHM costs. A functional relationship is first established between the UAV flying path length and damage inspection parameters, such as overlap ratio and inspection distance between the UAV and the target structure. The impact of UAV inspection parameters on associated SHM costs is then analyzed based on Bayes risk. Building upon the formulated functions, a multi-objective optimization model is developed to optimize the inspection parameters and thereby achieve a tradeoff between path length of UAV flight and associated SHM costs (e.g., consequence costs of SHM decisions resulting from the UAV inspection). An example of damage detection on a miter gate is employed to demonstrate the proposed method. The effect of different weighting factors on flying path and SHM costs is also evaluated. The results show that the proposed approach can effectively perform UAV mission planning while accounting for the impact of UAV flying path on SHM costs.

出于安全和成本方面的考虑，基于无人机 (UAV) 的自主损伤检测已成为一种很有前途的技术，可以取代某些人工检测。虽然目前基于无人机的损伤检测方法已经成功地在考虑潜在缺陷位置的情况下最大限度地减少了飞行路径的长度，但飞行路径对结构健康监测 (SHM) 质量的影响却被忽视了。本文通过最小化无人机路径长度和相关的 SHM 成本，提出了一种基于贝叶斯风险的新型任务规划方法，用于基于无人机的损伤检测。首先建立了无人机飞行路径长度与损伤检测参数之间的函数关系，例如无人机与目标结构之间的重叠率和检测距离。然后基于贝叶斯风险分析无人机检查参数对相关 SHM 成本的影响。在公式化函数的基础上，开发了一个多目标优化模型来优化检查参数，从而实现无人机飞行路径长度与相关 SHM 成本（例如，无人机检查导致的 SHM 决策的后果成本）之间的权衡。使用斜接门上的损坏检测示例来演示所提出的方法。还评估了不同权重因子对飞行路径和 SHM 成本的影响。结果表明，所提出的方法可以有效地执行无人机任务规划，同时考虑无人机飞行路径对 SHM 成本的影响。开发了一个多目标优化模型来优化检查参数，从而实现无人机飞行路径长度和相关 SHM 成本（例如，无人机检查导致的 SHM 决策的后果成本）之间的权衡。使用斜接门上的损坏检测示例来演示所提出的方法。还评估了不同权重因子对飞行路径和 SHM 成本的影响。结果表明，所提出的方法可以有效地执行无人机任务规划，同时考虑无人机飞行路径对 SHM 成本的影响。开发了一个多目标优化模型来优化检查参数，从而实现无人机飞行路径长度和相关 SHM 成本（例如，无人机检查导致的 SHM 决策的后果成本）之间的权衡。使用斜接门上的损坏检测示例来演示所提出的方法。还评估了不同权重因子对飞行路径和 SHM 成本的影响。结果表明，所提出的方法可以有效地执行无人机任务规划，同时考虑无人机飞行路径对 SHM 成本的影响。使用斜接门上的损坏检测示例来演示所提出的方法。还评估了不同权重因子对飞行路径和 SHM 成本的影响。结果表明，所提出的方法可以有效地执行无人机任务规划，同时考虑无人机飞行路径对 SHM 成本的影响。使用斜接门上的损坏检测示例来演示所提出的方法。还评估了不同权重因子对飞行路径和 SHM 成本的影响。结果表明，所提出的方法可以有效地执行无人机任务规划，同时考虑无人机飞行路径对 SHM 成本的影响。