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首页> 外文期刊>Applied Computational Electromagnetics Society journal >Position Deviation Evaluation for UAV Inspecting Overhead Transmission Line Based on Measured Electric Field
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Position Deviation Evaluation for UAV Inspecting Overhead Transmission Line Based on Measured Electric Field

机译：基于测量电场的UAV检查架空传输线的位置偏差评估

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摘要

Unmanned aerial vehicle (UAV) used in overhead transmission lines (OTLs) inspection are required to fly along a preset path to conduct special tasks. However, UAVs sometimes deviate from the preset path due to positioning error or control error in practice, thereby reducing the quality of the inspection task or even leading to serious line collision accidents. In this study, a method is proposed to evaluate the UAV position deviation from the preset path in real time on the basis of a measurement and analysis on the electric field generated by transmission lines. A new idea is presented to solve the obstacle avoidance problem for UAV in transmission line inspection. To improve evaluation accuracy, the influences of transmission tower and UAV body are considered in the theoretical calculation model for electric field, and the electric field data are preprocessed to diminish the influence of environmental noise and measurement inherent error. To improve the real-time performance of the evaluation algorithm, the dynamic programming and hidden Markov model (HMM) are combined to form a dynamic-hidden Markov model algorithm, in which the parameters of the HMM are determined by the expected maximization parameter estimation and corrected in real time. The feasibility and accuracy of the proposed method are verified by several simulation examples and experiments.
机译：在架空传输线（OTLS）检查中使用的无人驾驶飞行器（UAV）需要沿着预设路径飞行以进行特殊任务。然而，由于在实践中定位错误或控制误差，UAV有时偏离预设路径，从而降低了检查任务的质量甚至导致严重的线路碰撞事故。在该研究中，提出了一种方法，以基于由传输线产生的电场的测量和分析来评估与预设路径的UAV位置偏差。提出了一个新的想法，解决了传输线检查中的无人机障碍避免问题。为了提高评估准确性，在电场的理论计算模型中考虑了传输塔和UAV体的影响，并且预处理电场数据以减少环境噪声和测量固有误差的影响。为了改善评估算法的实时性能，组合动态编程和隐藏的马拉可型模型（HMM）以形成动态隐藏的马尔可夫模型算法，其中HMM的参数由预期的最大化参数估计确定实时纠正。所提出的方法的可行性和准确性通过若干模拟实施例和实验验证。

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