摘要
针对螺栓球节点在安装、使用过程中连接区受力变化将导致螺栓、套筒等部件破坏,进而发生节点连接失效的问题,利用压电陶瓷传感器,基于小波包能量分析法对螺栓球节点连接区受力监测进行研究.设计并制作一个包含螺栓球节点的缩尺网架模型.通过对螺栓球节点连接区的套筒施加不同的扭矩,使连接区处于不同的松紧状态,构建不同的连接区受力.将两个压电陶瓷片分别粘贴在中心螺栓球和靠近该螺栓球的杆端,作为激励器和接收器.对接收到的不同扭矩下应力波进行小波包分析,得到相应的应力波能量,通过计算危险指数RMSD,实现对螺栓球节点连接区受力的监测.试验结果验证了小波包能量分析法的有效性、抗噪性和抗干扰性,最终证明基于小波包能量法的螺栓球节点连接区受力状态监测是可行的.
Aiming at the problem that the bolts,sleeves and other components will be damaged by the force change in the connection area during the installation and use of the bolt ball joint,and the joint failure will occur thereby,piezoelectric(PZT)ceramic sensor are used,based on wavelet packet energy analysis method to study the force monitoring of the bolt ball joint connection area.A scaled grid model composed of bolted ball nodes is designed and made.By applying different torques to the sleeves in the connection area of the bolt ball node,the connection area is in a different tightness state,and different connection areas are constructed.Two PZTs are sticked on the center bolt ball and the rod end close to the bolt ball,respectively,as an exciter and receiver.The wavelet packet analysis is performed on the received stress waves under different torques,and the corresponding stress wave energy is obtained.By calculating the risk index RMSD,the monitoring of the force on the connection area of the bolt ball joint is realized.The test results verify the effectiveness,anti-noise and anti-interference of the wavelet packet energy analysis method,and finally proved the feasibility of monitoring the force state of the bolted ball joint connection area based on the wavelet packet energy method.
作者
徐菁
苟康康
刘客
张春巍
XU Jing;GOU Kang-kang;LIU Ke;ZHANG Chun-wei(Department of Civil Engineering, Qingdao Technological University, Qingdao 266033, China)
出处
《兰州理工大学学报》
CAS
北大核心
2022年第1期134-142,共9页
Journal of Lanzhou University of Technology
基金
国家自然科学基金(51678322,51650110509)
国家科技部资助项目(2017YFC0703603)
山东省自然科学基金(ZR2021ME033,ZR2021ME239)
山东省泰山学者优势特色学科人才团队。
关键词
螺栓球节点连接区
受力监测
压电陶瓷传感器
小波包能量分析
bolted spherical joint connection area
load monitoring
piezoelectric sensor
wavelet packet energy analysis