Adelaide Research & Scholarship
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https://hdl.handle.net/2440/77023
| Type: | Journal article |
| Title: | Intelligent condition monitoring systems for unmanned aerial vehicle robots |
| Author: | Anvar, A. Dowling, T. Putland, T. Anvar, A. Grainger, S. |
| Citation: | Proceedings of the World Academy of Science, Engineering and Technology, 2012; 70:1402-1408 |
| Publisher: | WASET |
| Issue Date: | 2012 |
| ISSN: | 2010-3778 |
| Statement of Responsibility: | A. P. Anvar, T. Dowling, T. Putland, A. M. Anvar, and S. Grainger |
| Abstract: | This paper presents the application of Intelligent Techniques to the various duties of Intelligent Condition Monitoring Systems (ICMS) for Unmanned Aerial Vehicle (UAV) Robots. These Systems are intended to support these Intelligent Robots in the event of a Fault occurrence. Neural Networks are used for Diagnosis, whilst Fuzzy Logic is intended for Prognosis and Remedy. The ultimate goals of ICMS are to save large losses in financial cost, time and data. |
| Keywords: | Intelligent Techniques, Condition Monitoring Systems, ICMS Robots Fault Unmanned Aerial Vehicle UAV Neural Networks Diagnosis Fuzzy Logic Prognosis Remedy. |
| Rights: | Copyright status unknown |
| Published version: | http://www.waset.org/journals/waset/v70/v70-113.pdf |
| Appears in Collections: | Aurora harvest Mechanical Engineering publications |
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