Smartness and IoT along with machine learning (ML) lead the research directions
nowadays. Smart city, smart campus, smart home, smart vehicle, etc; or if we call it “Smart x” …

This paper proposes a new model, called rotor finite element mimetic neural network
(RFEMNN), for diagnosing rotor unbalance and shaft crack faults. RFEMNN uses a …

Traditional fault classification methods typically rely on manual feature extraction and the
application of machine-learning algorithms. However, these approaches encounter …

Modern advancements in computing power and the ability of machine learning (ML) to
model complex relationships between input and output have opened new prospects for data …

Modern electrical power systems are characterized by a high rate of transient processes, the
use of digital monitoring and control systems, and the accumulation of a large amount of …

Faults can seriously damage high-voltage (HV) power systems, particularly if they occur on
the long overhead transmission line (OHTL) that connects the nuclear power plant (NPP) to …

Abstract Fault diagnosis of Medium Voltage power Cables (MVCs) research nuclear reactor,
incredibly inaccessible/remote ones, has to be carefully identified, located, and fixed within a …

High-speed traveling wave acquisition devices often use a mutation start algorithm with a
low threshold value, which can collect a large number of interference clutters. If the devices …

针对核电棒控系统电源(PWE) 早期故障状态辨识问题, 提出一种基于融合时域与时频域的故障
特征和灰狼优化算法(GWO) 的极限学习机(ELM) 辨识方法. 首先, 根据棒控电源PWE …

Nuclear power plants (NPPs) have witnessed significant advancements in intelligent
accident identification in recent years. However, comprehensive research on fine-grained …