| 基于MIMU的Mann-Kendall输电线路运动趋势及断线预测 |
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| 引用本文： | 杨金显,范耀辉.基于MIMU的Mann-Kendall输电线路运动趋势及断线预测[J].教育技术导刊,2020,19(1):135-139. |
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| 作者姓名： | 杨金显 范耀辉 |
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| 作者单位： | 河南理工大学 电气工程与自动化学院，河南 焦作 454003 |
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| 基金项目： | 国家自然科学基金项目（U1404510，41672363，61440007）；河南省科技攻关项目（172102210289）；河南省创新型科技人才队伍建设工程项目（CXTD2016054）；河南省高校基本科研业务费专项资金项目 |
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| 摘 要： | 为了对输电线路的运动趋势进行准确预测，提出一种基于惯性测量参数的Mann-Kendall（MK）输电线路运动趋势及断线预测方法。首先设计一种微惯性测量单元（MIMU），采集大量导线正常运动及断股时的加速度和角速度，构建时间序列并进行预处理；然后定义运动特征量，采用Mann-Kendall算法对预处理后的数据进行分析，获得输电线路运动趋势及改变时刻的临界值；最后构建输电线路运动模拟系统，通过对输电线平动运动和扭转运动动量的解算，对MK趋势预测曲线发生突变且其特征量呈断崖式增加至4*104]以上的情况，可以判定发生断股并确定断股时刻，以此预测断线情况。实验结果表明，该方法可完成输电线运动趋势和断线预测。
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| 关 键 词： | 输电网络 微惯性测量 Mann-Kendall 趋势预测 断线预测 |
| 收稿时间： | 2019-04-01 |
Trend and Disconnection Prediction of MIMU-based Mann-Kendall Transmission Line Motion |
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| YANG Jin-xian,FAN Yao-hui.Trend and Disconnection Prediction of MIMU-based Mann-Kendall Transmission Line Motion[J].Introduction of Educational Technology,2020,19(1):135-139. |
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| Authors: | YANG Jin-xian FAN Yao-hui |
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| Institution: | School of Electrical Engineering and Automation， Henan Polytechnic University， Jiaozuo 454003，China |
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| Abstract: | In order to accurately predict the movement trend of transmission lines， a Mann-Kendall （MK） transmission line motion trend and disconnection prediction method based on inertial measurement parameters is proposed. Firstly， a Micro inertial measurement unit （MIMU） is designed to collect the acceleration of normal motion of a large number of wires and the angular velocity of the strands. Atime series is constructed and preprocessing is performed. The motion feature quantity is defined and the Mann-Kendall algorithm is employed. The pre-processed data is analyzed to obtain the trend of the transmission line movement and the critical value of the change time. Finally， the transmission line motion simulation system is constructed， and the MK trend prediction curve is abruptly transformed by the calculation of the transmission line translational motion and the torsional motion momentum. And the feature quantity is increased to the above in the form of a cliff 4 times 4 times multiplied by 10， and the breakage occurrence and the break moment are verified. In this way， the situation of the disconnection is predicted. The experimental results show that the method can complete the trend of motion and the prediction of disconnection. |
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| Keywords: | transmission network micro inertial measurement Mann-Kendall trend prediction wire break prediction |
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