The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …

Fault detection and diagnosis (FDD) systems are developed to characterize normal
variations and detect abnormal changes in a process plant. It is always important for early …

Maintenance has gained in importance as a support function for ensuring equipment
availability, quality products, on-time deliveries, and plant safety. Cost-effectiveness and …

In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines
is proposed by develo** an ensemble of dynamic neural network identifiers. For health …

An unappealing characteristic of all real-world systems is the fact that they are vulnerable to
faults, malfunctions and, more generally, unexpected modes of-haviour. This explains why …

Although modern chemical processes are highly automatic, abnormal situation management
(ASM) still heavily relies on human operators. Process fault detection and diagnosis (FDD) …

Abnormal operating conditions (faults) cost process industry billons of dollars per year and
can be prevented if they are predicted and controlled in advance. Advanced software …

Polymerization process can be classified as a nonlinear type process since it exhibits a
dynamic behaviour throughout the process. Therefore, it is highly complicated to obtain an …

The availability of complex rotating machines is vital for the prevention of catastrophic
failures in a significant number of industrial operations. Reliability engineering theories …

This paper proposes an intelligent process fault diagnosis system based on the techniques
of Andrews plot and convolutional neural network. The proposed fault diagnosis method …