The control and monitoring of power generation plants is being complicated day by day, with
the increase size and capacity of equipments involved in power generation process. This …

This scientific article aims to provide a comprehensive review of fault monitoring, diagnosis,
and prognosis methods based on Artificial Intelligence (AI) for Hydroelectric Generator Units …

This paper presents a survey about several works in the field of predictive maintenance for
hydroelectric power plants related to Assets Performance Management systems. It discusses …

This paper proposes a fault detection method for hydroelectric generators using isolation
forest. In hydroelectric generators, since faults rarely occur, it is difficult to obtain fault data …

Abstract Prognostic and Health Management (PHM) is an emerging maintenance concept
that is highly regarded by the scientific community and practitioners, as its adoption can …

This paper proposes a fault detection method for hydroelectric generators by robust random
cut forest (RRCF) with feature selection using Hilbert-Schmidt Independence Criterion …

This paper proposes feature selection (FS) considering characteristics of operating data and
Random Cut Trees (RCTs) for hydroelectric generator (HG) fault detection (FD) by Robust …

Being an effective long-distance mass transit, the railway will continue to flourish for its
limited carbon footprint in the environment. Ensuring the equipment's reliability and …

The aim of this study is giving continuity to the evolution of the SIMPREBAL methodology
and computer system based on the specification OSA-CBM (Open System Architecture for …

Smart trains nowadays are equipped with sensors that generate an abundance of data
during operation. Such data may, directly or indirectly, reflect the health state of the trains …