杨金显,杨雨露,李田田,郑泽南,申刘阳.基于 MIMU 的输电塔损伤检测研究[J].电子测量与仪器学报,2022,36(12):219-228
基于 MIMU 的输电塔损伤检测研究
Damage detection of transmission tower based on MIMU
  
DOI:
中文关键词:  输电塔  损伤检测  惯性测量  结构熵  平动/ 转动
英文关键词:transmission tower  damage detection  inertial measurement  structure entropy  translation / rotation
基金项目:国家自然科学基金(41672363)、河南省高校科技创新团队(20IRTSTHN019)项目资助
作者单位
杨金显 1.河南理工大学电气工程与自动化学院 
杨雨露 1.河南理工大学电气工程与自动化学院 
李田田 1.河南理工大学电气工程与自动化学院 
郑泽南 1.河南理工大学电气工程与自动化学院 
申刘阳 1.河南理工大学电气工程与自动化学院 
AuthorInstitution
Yang Jinxian 1.School of Electrical Engineering and Automation, Henan Polytechnic University 
Yang Yulu 1.School of Electrical Engineering and Automation, Henan Polytechnic University 
Li Tiantian 1.School of Electrical Engineering and Automation, Henan Polytechnic University 
Zheng Zenan 1.School of Electrical Engineering and Automation, Henan Polytechnic University 
Shen Liuyang 1.School of Electrical Engineering and Automation, Henan Polytechnic University 
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中文摘要:
      为了进行输电塔结构损伤程度及损伤轴向检测,从而缩小检测范围并实现高效低成本的精准损伤定位,提出了一种基 于 MIMU 的输电塔结构损伤检测方法。 基于输电塔结构角度出发,利用 MIMU 微惯性测量系统监测输电塔结构变化,结合结构 熵构建平动、转动熵矩阵,然后基于熵距及变异熵的损伤指标检测输电塔结构的损伤程度及损伤轴向,最后设计多种工况下的 模拟输电塔和在役输电塔实验验证该算法的合理性。 结果表明,衡量损伤程度的熵距指标的计算值与理论值误差低于 3%,可 有效检测结构的损伤程度;衡量损伤轴向的变异熵指标较未损伤轴向高出 20% ~ 53. 9%,可有效检测结构的损伤轴向。 该方法 可为桁架结构损伤检测提供现实依据。
英文摘要:
      To detect structural damage degree and damage axial direction, reduce detection range and achieve accurate damage location with high efficiency and low cost, a transmission tower structural damage detection method based on MIMU was proposed. Firstly, based on the Angle of transmission tower structure, the MIMU micro-inertial measurement system is used to monitor the structure change of transmission tower, and the translation and rotation entropy matrices are constructed combined with the structural entropy. Then, the damage degree and damage axial direction of transmission tower structure are detected by using the damage index of entropy distance and variation entropy. Finally, simulation and in-service transmission towers under various working conditions are designed to verify the rationality of the algorithm. The results show that the error between the entropy distance index and the theoretical value is less than 3%, which can effectively detect the damage degree of the structure. The variation entropy index of damaged axial direction is 20% ~ 53. 9% higher than that of undamaged axial direction, which can effectively detect the damaged axial direction of structures. This method can provide a practical basis for truss structure damage detection.
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