无人机巡检图像防振锤缺陷识别技术

Defect recognition technology for UAV patrol inspection image of vibration damper

针对输电线路外界影响因素过多,导致防振锤缺陷检测精准度较差且效率偏低的问题,提出了一种基于图像表达及像素点坐标的防振锤缺陷智能识别技术。利用非线性映射描述防振锤的细节及轮廓,预估防振锤因受力形变引起的阻尼力、刚度、质量与位移等参数变化情况。利用变换矩阵建立识别坐标系,计算防振锤各轴上关键点的旋转角及动态位姿,与待识别节点中参数表达不一致的节点即为缺陷部位。实验结果表明,所提技术在复杂背景形态下也能实现精准的缺陷识别,且噪声及失真现象的处理效果也较优,具有良好的鲁棒性及适用性。

To solve the problem of poor accuracy and low efficiency of vibration damper defect detection due to too many external influencing factors of transmission lines,an intelligent recognition technology based on image representation and pixel coordinates for damper defects was proposed.The details and contour of damper were described by nonlinear mapping,and the change of damping force,stiffness,mass and displacement caused by stress deformation of vibration damper was estimated.The transformation matrix was used to establish the identification coordinate system,and to calculate the rotation angle and dynamic position of key points on each axis of vibration damper.The calculated node inconsistent with the parameter expression of the identified node was confirmed as the defect part.The experimental results show that the as-proposed technology can also achieve accurate defect recognition in complex background sceneries,and the processing effect of noise and distortion is also better,indicating its good robustness and applicability.