Deyun Xiao

TL;DR: The Gaussian kernel method is applied to generate pseudo continuous time series from the original binary alarm data to reduce the influence of missed, false, and chattering alarms.

TL;DR: A Kalman filter-based methodology for unified detection and isolation of sensor, actuator, and process faults in the NUSM system with analysis on fault detectability and isolability is investigated.

TL;DR: Two validation methods based on cross-correlation analysis of process data with assumed time delays and transfer entropy are introduced to validate the corresponding paths in SDGs.

TL;DR: In large-scale industrial processes, a fault can easily propagate between process units due to the interconnections of material and information flows so the problem of fault detection and isolation for these processes is more concerned about the root cause and fault propagation before applying quantitative methods in local models.

TL;DR: A procedure based on the similarity of correlation maps of physical process variables and their alarm history in combination with process connectivity information through causal maps to suggest optimal alarm settings to reduce the number of false and missed alarms is outlined.