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Correlation-based dynamic sampling for online high dimensional process monitoring
  • Quality

Correlation-based dynamic sampling for online high dimensional process monitoring

Publication:
Journal of Quality Technology
Date:
July 2021
Issue:
Volume 53 Issue 3
Pages:
pp. 289-308
Author(s):
Nabhan, Mohammad, Mei, Yajun, Shi, Jianjun

Abstract

Effective process monitoring of high-dimensional data streams with embedded spatial structures has been an arising challenge for environments with limited resources. Utilizing the spatial structure is key to improve monitoring performance. This article proposes a correlation-based dynamic sampling technique for change detection. Our method borrows the idea of Upper Confidence Bound algorithm and uses the correlation structure not only to calculate a global statistic, but also to infer unobserved sensors from partial observations. Simulation studies and two case studies on solar flare detection and carbon nanotubes (CNTs) buckypaper process monitoring are used to validate the effectiveness of our method.

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