首页> 外文会议>2018 IEEE International Symposium on Electromagnetic Compatibility and 2018 IEEE Asia-Pacific Symposium on Electromagnetic Compatibility >A novel line position recognition method in transmission line patrolling with UAV using machine learning algorithms
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A novel line position recognition method in transmission line patrolling with UAV using machine learning algorithms

机译:基于机器学习算法的无人机巡线巡线新位置识别方法

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摘要

Overhead transmission line is the main approach for energy transporting in power systems. To ensure the safety of power system, regular patrolling is required to be carried out. Current UAV patrolling method needs UAV to be controlled by skilled staff on the ground, which brings about low efficiency and high cost. To achieve autonomous line patrolling, magnetic sensors can be placed on the UAV and magnetic field data can be used to determine the relative position between UAV and transmission lines. To realize real-time patrolling, the speed of calculation and line position recognition is expected to be fast, so machine learning algorithm is considered as a good option. Neural network and SVM methods are exploited to achieve line position recognition and the methods are verified in a DC transmission system and a satisfying accuracy is obtained on the randomly picked test set. This method can achieve UAV line patrolling autonomously, which is safer, suitable for various situations and has a broad future prospect.
机译:架空传输线是电力系统中能量传输的主要方法。为了确保电力系统的安全,需要定期巡逻。当前的无人机巡逻方法需要由地面熟练的人员来控制无人机,这导致效率低和成本高。为了实现自动巡线,可以在无人机上放置磁传感器,并且可以使用磁场数据来确定无人机和传输线之间的相对位置。为了实现实时巡逻,计算和线位置识别的速度有望很快,因此机器学习算法被认为是一个不错的选择。利用神经网络和支持向量机方法实现线路位置识别,并在直流输电系统中进行了验证,并在随机选取的测试集上获得了令人满意的精度。该方法可以自主实现无人机巡线,更安全,适用于各种情况,具有广阔的发展前景。

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