Titlebook: Data-Driven Fault Detection and Reasoning for Industrial Monitoring; Jing Wang,Jinglin Zhou,Xiaolu Chen Book‘‘‘‘‘‘‘‘ 2022 The Editor(s) (i

充气球

Semblance

Global Plus Local Projection to Latent Structures,time delay (Ding .; Aumi et al. .; Peng et al. .; Zhang et al. .; Yin et al. .). Monitoring the process variables related to the quality variables is significant for finding potential harm that may lead to system shutdown with possible enormous economic loss.

sleep-spindles

使声音降低

Locality-Preserving Partial Least Squares Regression,principal components of . and ., two conditions must satisfy: (1) . and . retain the most information about the local nonlinear structure of their respective data sets. (2) The correlation between . and . is the largest. Finally, a quality-related monitoring strategy is established based on LPPLS.

AGATE

Locally Linear Embedding Orthogonal Projection to Latent Structure,m shutdowns and thus possibly huge economic losses. Maximum correlation was extracted between quality variables and process variables by partial least squares analysis (PLS) (Kruger et al. .; Song et al. .; Li et al. .; Hu et al. .; Zhang et al. .).

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New Robust Projection to Latent Structure,ainty part, just as the nonlinearity can be used to represent the uncertainty of a system (Wang et al. .). So this chapter also focuses on how to deal with the nonlinearity in PLS series method, but starts from an different view, i.e., robust PLS. Here the system nonlinearity is considered as uncertainty and a new robust .-PLS is proposed.

arcane

魔鬼在游行

A Further Improvement on Approximating TTP-2d of a batch. Therefore, the complete batch trajectory must be estimated real time, or alternatively only the measured values at the current moment are used for online diagnosis. Moreover, the above approaches do not consider the problem of inconsistent production cycles.

Countermand

迅速成长