基于门控循环单元网络的输电杆塔螺栓紧固检测  

Transmission Tower Bolt-Fastening Detection Based on Gated Recurrent Unit Network

作　　者：鲁炜 顾安琪 骆昊骏 朱炜 王火根 文颖[2] LU Wei;GU An-Qi;LUO Hao-Jun;ZHU Wei;WANG Huo-Gen;WEN Ying(Shanghai Electric High Voltage Industrial Co.Ltd.,Shanghai 200072,China;East China Normal University,Shanghai 200072,China;Xitu Information Technology Co.Ltd.,Shanghai 200437,China)

机构地区：[1]上海电力高压实业有限公司,上海200062 [2]华东师范大学,上海200062 [3]上海曦途信息科技有限公司,上海200437

出　　处：《计算机系统应用》2021年第4期277-282,共6页Computer Systems & Applications

基　　金：国家自然科学基金(61773166)。

摘　　要：输电塔杆螺栓紧固检测是保障高压电网安全的重要依据,传统的人工检测方法需要员工爬上输电杆塔检测操作,通常伴有一定程度的风险,而采用无人机巡检受许多外在的因素的影响,其检测效果并不理想.因此,本文提出一种基于门控循环单元网络的输电杆塔螺栓紧固检测方法,利用振动传感器和传感分析仪构建一套采集输电铁塔声波数据的作业流程,提取训练样本中声波数据的线性预测倒谱系数LPCC构成特征向量;训练门控循环单元网络(Gated Recurrent Unit,GRU)分类模型从而检测未知紧固状态的声波样本,实验结果达到实用分析性能.通过本算法的应用,解决了在检测输电铁塔螺栓紧固问题上传统方法上的人力和方法性能问题.The bolt-fastening detection of transmission towers is critical to the safety of high-voltage power grids.Traditional detection methods are often risky it needs manual detection high on transmission towers.What’s more,UAV detection fails to live up to our expectation affected by multiple external factors.Therefore,this study proposes a boltfastening detection method for transmission towers based on Gated Recurrent Unit(GRU)networks.Specifically,the vibration sensor and sensor analyzer are used to construct a work flow for collecting acoustic wave data of transmission towers,and then the Linear Predictive Cepstral Coefficients(LPCCs)of acoustic wave data in training samples are extracted to form feature vectors.The classification model of GRU networks is trained to predict unknown fastened acoustic wave samples.As a result,this method is practical.The application of this algorithm can avoid the much manpower of traditional ones and is superior to them in bolt-fastening detection of transmission towers.

关 键 词：声波数据采集 线性预测倒谱系数 门控循环单元网络 

分 类 号：TM75[电气工程—电力系统及自动化] TN912.3[电子电信—通信与信息系统]