Abstract
Equipment has long service period and high reliability requirements, equipment support personnel not only need to complete the necessary test and repair, but also have to make clear the future development trend of equipment performance and the life expectancy during life cycle. Life prognostic can help them to improve the equipment maintenance and ensure high logistics and readiness capability of equipments. In this paper, the author researches and analyses the life prediction algorithm, pre-treatment method and optimization method of equipment service. These algorithms are applied and validated by calculating and analysis the practical test data, which can provide theories basis and references for the weapon PHM.
| Original language | English |
|---|---|
| Title of host publication | International Conference on Automatic Control and Artificial Intelligence, ACAI 2012 |
| Pages | 2030-2033 |
| Number of pages | 4 |
| Edition | 598 CP |
| DOIs | |
| State | Published - 2012 |
| Event | International Conference on Automatic Control and Artificial Intelligence, ACAI 2012 - Xiamen, China Duration: 3 Mar 2012 → 5 Mar 2012 |
Publication series
| Name | IET Conference Publications |
|---|---|
| Number | 598 CP |
| Volume | 2012 |
Conference
| Conference | International Conference on Automatic Control and Artificial Intelligence, ACAI 2012 |
|---|---|
| Country/Territory | China |
| City | Xiamen |
| Period | 3/03/12 → 5/03/12 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Life prediction
- Polynomial prediction
- Statistical model
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