The transformation of energy networks from passive to active systems requires the
embedding of intelligence within the network. One suitable approach to integrating …

Data-driven condition monitoring is an essential function for power plant because of its
potential to enhance asset longevity and reduce the operation and maintenance costs. This …

The power system is presently experiencing vital changes: it is advancing from a centralized
structure to a decentralized one, primarily because of the enormous advancement of …

Retrofitting condition monitoring systems to aging plant can be problematic, since the
particular signature of normal behavior will vary from unit to unit. This paper describes a …

In this paper, we propose a Bayesian estimation scheme for hidden Markov model (HMM)
parameters, as well as a method for monitoring systems whose degradation processes are …

In this article, a novel data-driven approach to monitoring of systems operating under
variable operating conditions is described. The method is based on characterizing the …

For two centuries, the industrial sector has never stopped evolving. Since the dawn of the
Fourth Industrial Revolution, commonly known as Industry 4.0, deep and accurate …

This paper considers the use of a multiagent system (MAS) incorporating hidden Markov
models for the condition monitoring of gas turbine (GT) engines. Hidden Markov models …

Partial discharge (PD) monitoring is a key method of tracking fault progression and
degradation of insulation systems. Recent research discovered that the harmonic regime …

This paper describes the end-to-end components of an on-line system for diagnostics and
anomaly detection. The system provides condition monitoring capabilities for two in service …