风电叶片智能高效便携式C扫描超声检测系统开发
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摘要
针对传统超声A扫探伤风电叶片存在检测效率低、员工劳动强度大、仪器智能化不够等问题,开发了一套实时显示并保存当前位置信息、波形信息和C扫描彩图的超声扫查系统。给出了系统硬件框图、基于LabVIEW软件设计界面以及C扫描成像框图。分别制作了不同缺陷风电叶片主梁和腹板粘接模型,以模型背面左下角为探伤坐标原点,采用相同的扫查参数设置和速度,对系统进行了实验。实验结果表明,系统能够有效检测粘接区域缺陷的种类、轮廓和位置,且运行稳定可靠。
In order to solve the problems of traditionally testing wind turbine blade by ultrasonic A-scan, such as low detection efficiency, high labor intensity and insufficient intelligence of the instrument, a set of ultrasonic scan detection system is developed, which can real-time display and save the position information, waveform information and C-scan imaging. The system hardware block diagram, software design interface based on LabVIEW and C-scan imaging block diagram are given. Bonding models with different defects of the spar caps and shear webs of wind turbine blades were fabricated respectively. The detection origin was located at the lower left corner of the back of bonding models. Experiments were carried out on the system by using the same scanning parameter setting and speed. The experimental results show that the system can effectively test the type,contour and location of bonding defects with a stable and reliable operation.
In order to solve the problems of traditionally testing wind turbine blade by ultrasonic A-scan, such as low detection efficiency, high labor intensity and insufficient intelligence of the instrument, a set of ultrasonic scan detection system is developed, which can real-time display and save the position information, waveform information and C-scan imaging. The system hardware block diagram, software design interface based on LabVIEW and C-scan imaging block diagram are given. Bonding models with different defects of the spar caps and shear webs of wind turbine blades were fabricated respectively. The detection origin was located at the lower left corner of the back of bonding models. Experiments were carried out on the system by using the same scanning parameter setting and speed. The experimental results show that the system can effectively test the type,contour and location of bonding defects with a stable and reliable operation.
引文
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[11]何杰,杜玲,王冬生.风电叶片的主要缺陷与无损检测技术评价[J].玻璃钢,2013(1):1-7.
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[13]刘美萍,龙士国,李婷.基于LabVIEW和Arduino方位角智能化测控系统设计[J].测控技术,2017,36(5):108-110.
[14]李伟刚,潘怀强,李兵尚.基于虚拟仪器的发射筒开关盖压力检测系统[J].测控技术,2013,32(12):131-133.
[2]Márquez F P G,Tobias A M,P6rez J M P,et al.Condition monitoring of wind turbines:techniques and methods[J].Renewable Energy,2012,46:169-178.
[3]Lee J R,Shin H J,Chia C C,et al.Long distance laser ultrasonic propagation imaging system for damage visualization[J].Optics and Lasers in Engineering,2011,49(12):1361-1371.
[4]安静,徐宇,张淑丽,等.超声波技术用于风电叶片粘结区域检测的探究[J].玻璃钢/复合材料,2015(3):50-53.
[5]杜娟.超声波无损检测在风电叶片粘接部位缺陷检测中的应用[C]//中国农业机械工业协会风能设备分会2010年度论文集.2010.
[6]田松峰,韩强,王美俊,等.复合材料风电叶片静态无损检测方法研究进展[J].工程塑料应用,2016,44(6):137-141.
[7]Juengert A,Grosse C U.Inspection techniques for wind turbine blades using ultrasound and sound waves[C]//Proceedings of Non-Destructive Testing in Civil Engineering.2009.
[8]Yang B,Sun D B.Testing,inspecting and monitoring technologies for wind turbine blades:a survey[J].Renewable and Sustainable Energy Reviews,2013,22:515-526.
[9]王昌盛.风电叶片前缘超声检测技术研究[D].南京:南京航空航天大学,2016.
[10]李凯,郭大勇,阙开良,等.一种新型超声C扫描检测系统[J].无损检测,2012,34(4):70-73.
[11]何杰,杜玲,王冬生.风电叶片的主要缺陷与无损检测技术评价[J].玻璃钢,2013(1):1-7.
[12]王晓宁,刘沛.玻璃纤维结构风电叶片的超声相控阵检测方法研究[J].无损探伤,2014,38(5):8-13.
[13]刘美萍,龙士国,李婷.基于LabVIEW和Arduino方位角智能化测控系统设计[J].测控技术,2017,36(5):108-110.
[14]李伟刚,潘怀强,李兵尚.基于虚拟仪器的发射筒开关盖压力检测系统[J].测控技术,2013,32(12):131-133.