Data and code for conditional entropy dissimilarity-based multiplicative incipient fault detection

Description

This dataset accompanies the manuscript “Conditional entropy dissimilarity: a data-driven approach for multiplicative incipient faults”. It contains Python code for the four synthetic process-monitoring scenarios, CED-CUSUM monitoring code for the Tennessee Eastman Process benchmark, numerical verification code for the CED-CCA first-order relationship and the kNN estimator convergence result, machine-readable copies of the numerical values reported in the manuscript, and reference figures. The Tennessee Eastman Process benchmark source is identified and cited in the accompanying README file.

Institutions

• Central South University

  Hunan, Changsha

Categories

Licence