Scanning Aircraft Structures Using Open-Architecture Robotic Crawlers as Platforms with NDE Boards and Sensors
Y. Bar-Cohen, Paul Backes
- 发表年份
- 1998
- 引用次数
- 8
摘要
Rapid inspection of large areas has been an ongoing challenge to the nondestructive testing (NDT) profession. The need for such a capability has grown significantly in recent years as a result of the increase in the numbers ofaging aircraft in service, and of aircraft with composite primary structures. While aging aircraft with metallic structures are most susceptible to corrosion and cracking near fastener areas, composites are susceptible to impact damage that can appear anywhere on the structure. Field inspection using manual scanning is labor intensive, time consuming, and subject to human error, whereas removal of parts from an aircraft for a lab test is costly and may be impractical. Effective field inspection requires a portable, user friendly system that can rapidly scan large areas of complex structures. In recent years, various portable inspection systems have emerged, including scanners that are placed at selected locations and sequentially repositioned to cover all the areas of interest. The development of such systems has followed the evolution of the relevant technology, and has required integration of multidisciplinary expertise including NDT, telerobotics, neural networks, automated control, embedded computing, and materials science. The trend has been towards full automation; the desideratum is for completely autonomous inspection capability. Recently, the Jet Propulsion Laboratory (JPL) has developed the multifunction automated crawling system (MACS), which offers an open-architecture robotic platform for NDT boards and sensors. This crawler established the foundations for the development of a walking computer platform with standard plugin NDT boards. This capability will allow a larger pool of companies and individuals to become potential producers of NDT instruments. Thus, a significant cost reduction can be realized with a rapid transition from novel concepts to practical use. The capability and potential of MACS as an enabling technology will be discussed in this paper.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002