| Budget Amount *help |
¥11,570,000 (Direct Cost: ¥8,900,000、Indirect Cost: ¥2,670,000)
Fiscal Year 2017: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2016: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2015: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2014: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
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| Outline of Final Research Achievements |
The purpose of this study is to establish a new methodology of sustainable knowledge interaction between operators of space systems such as artificial satellites and machine learning-based or data-driven health status monitoring systems. We developed a data-driven health monitoring method based on dimensionality reduction and clustering, which takes into account that artificial satellite systems consist of global discrete mode transition and local continuous state transition. We showed this method is able to provide operators with useful information, to acquire expert knowledge from the operators and to encourage continuing mutual interaction of them.
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