As the UH-1 aircraft continue to age, there is growing concern for their structural integrity. With corrosion damage becoming a bigger part of the sustainment picture with increasing maintenance burden and cost, it is becoming increasingly important for corrosion management to be updated with more advanced techniques.
The current find-and-fix technique for handling corrosion has many shortfalls, spurring the recent interest in early detection through structural health monitoring. This condition based technique is becoming more prevalent and is recognized for the potential to greatly reduce maintenance cost. Through corrosion monitoring, structural and environmental conditions can be closely observed, preventing excessive maintenance action and saving cost.
Searches for corrosion monitoring system designs revealed several commercial companies with prototype systems installed on commercial aircraft, however, details on system design and data analysis were scarce. This study attempted to bridge the gap in literature by providing insight into the development of a corrosion damage prediction model and the design of a corrosion monitoring system.
This study attempted to use aircraft maintenance data to make prediction models for determining what corrosion damage an aircraft can expect, given varying operating conditions. Although a reliable prediction model could not be created, trends observed in the data were still valuable for identifying problematic areas of the aircraft. In order to create reliable models, more accurate corrosion data is needed. This can be accomplished through the implementation of a corrosion monitoring system.
A custom corrosion monitoring system was designed for the UH-1 aircraft. Commercial off-the-shelf products were fit to the design and a benefits-to-cost analysis was performed for the monitoring system, evaluating the system based on criteria developed from user requirements. The system proved to meet and exceed expectation, making it an ideal choice for the UH-1 aircraft.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/37312 |
| Date | 19 November 2010 |
| Creators | Kersten, Stephanie M. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
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