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Development of a cable suspension and balance system and its novel calibration methods for effective wind tunnel tests
Measurement ( IF 5.6 ) Pub Date : 2020-11-17 , DOI: 10.1016/j.measurement.2020.108717
Keum-Yong Park , Yeol-Hun Sung , Jae-Hung Han

Based on the advantages of the cable-driven parallel robot (CDPR), we developed a cable suspension and balance system (CSBS) as a multi-purpose device for wind tunnel tests with motion control and load measurement capability. The CSBS was designed to serve as both a wind tunnel model mount and balance.

This paper suggests two novel methodologies to improve the CSBS performance, one for more accurate motion control and the other for improved load measurement. The motion control correction was implemented by applying a multi-variable polynomial function that adjusts motion commands to generate the required response utilizing the measured motion data. For more accurate load measurement, a multi-layer perceptron (MLP) is proposed as a correction function. This MLP was trained to provide corrected three forces and three moments according to the reference balance data.

Several motion tests, loading tests, and statistical analyses were carried out before and after correction to investigate the correction effectiveness. Differences between the motion command and response were dramatically reduced by the polynomial correction, and the MLP learning methodology effectively enhanced the load measurement accuracy of the CSBS.

Using both of the suggested corrections, the CSBS was equipped with enhanced motion control and load measurement performance. Several wind tunnel tests were conducted to examine the CSBS reliability as a model mount and load measurement system, and test results showed reasonably good agreement with reference data for a cylinder model and a NACA0015 airfoil model.



中文翻译:

电缆悬挂和平衡系统的开发及其用于有效风洞测试的新型校准方法

基于电缆并联机器人(CDPR)的优势,我们开发了电缆悬挂和平衡系统(CSBS)作为具有运动控制和负载测量功能的风洞测试多功能设备。CSBS设计为既可以用作风洞模型,又可以用作天平。

本文提出了两种新颖的方法来改善CSBS性能,一种方法用于更精确的运动控制,另一种方法用于改善负载测量。运动控制校正是通过应用多变量多项式函数来实现的,该函数通过使用测量的运动数据来调整运动命令以生成所需的响应。为了更精确地测量负载,提出了多层感知器(MLP)作为校正函数。根据参考平衡数据,对该MLP进行了培训,可以提供校正的三个力和三个力矩。

校正前后进行了几次运动测试,载荷测试和统计分析,以研究校正效果。通过多项式校正,大大减少了运动命令和响应之间的差异,并且MLP学习方法有效地提高了CSBS的负载测量精度。

使用这两个建议的更正,CSBS配备了增强的运动控制和负载测量性能。进行了数次风洞测试,以检验CSBS作为模型安装和载荷测量系统的可靠性,测试结果表明,该模型与气缸模型和NACA0015机翼模型的参考数据相当吻合。

更新日期:2020-11-17
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