• Proceedings of the Korean Statistical Society Conference
• /
• 2003.05a
• /
• pp.295-297
• /
• 2003

본 논의에서는 cDNA 마이크로어레이 분석에서 다변량 분석의 한 방법인 Hotelling의 T제곱 통계량을 이용하여 유의적 유전자군을 검색하고, 이 유전자군을 사용하여 검사자료를 두군으로 분류하는데 단변량 t통계량에 기초한 접근보다 얼마나 효율적인지를 평가하고자 한다.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.663-668
• /
• 2024

This paper applies statistical analysis methods in the time domain to the fault diagnosis of wafer transfer robots, and proposes a methodology to discern the critical characteristics of vibration and torque signals. Subsequently, principal component analysis (PCA) is applied to diminish the data's dimensionality, followed by the development of a fault diagnosis algorithm utilizing Euclidean distance and Hotelling's T-square statistics. The algorithm establishes decision boundaries to categorize failure states based on the observed data. Our findings indicate that data classification incorporating velocity parameters enhances diagnostic accuracy. This approach serves to enhance the precision and efficacy of fault diagnosis.