Advances in fault detection and diagnosis for thermal power plants: A review of intelligent techniques

S Khalid, J Song, I Raouf, HS Kim - Mathematics, 2023 - mdpi.com
Thermal power plants (TPPs) are critical to supplying energy to society, and ensuring their
safe and efficient operation is a top priority. To minimize maintenance shutdowns and costs …

Diagnosing and balancing approaches of bowed rotating systems: a review

N Rezazadeh, A De Luca, G Lamanna, F Caputo - Applied Sciences, 2022 - mdpi.com
Driven/driving shafts are the most important portion of rotating devices. Misdiagnosis or late
diagnosis of these components could result in severe vibrations, defects in other parts …

A new auto-encoder-based dynamic threshold to reduce false alarm rate for anomaly detection of steam turbines

JU Ko, K Na, JS Oh, J Kim, BD Youn - Expert Systems with Applications, 2022 - Elsevier
This study proposes an ensemble denoising auto-encoder-based dynamic threshold (EDAE-
DT) to overcome the false alarm issue in anomaly detection. The proposed ensemble …

Improvement of marine steam turbine conventional exergy analysis by neural network application

S Baressi Šegota, I Lorencin, N Anđelić… - Journal of Marine …, 2020 - mdpi.com
This article presented an improvement of marine steam turbine conventional exergy analysis
by application of neural networks. The conventional exergy analysis requires numerous …

Extreme learning machine–radial basis function (ELM-RBF) networks for diagnosing faults in a steam turbine

A Dhini, I Surjandari, B Kusumoputro… - Journal of Industrial and …, 2022 - Taylor & Francis
ABSTRACT A fast and reliable fault diagnosis system for a steam turbine in thermal power
plant is crucial. The system will detect and classify a potential or occurring fault, hence …

[HTML][HTML] Artificial intelligence based operational strategy development and implementation for vibration reduction of a supercritical steam turbine shaft bearing

WM Ashraf, Y Rafique, GM Uddin, F Riaz… - Alexandria Engineering …, 2022 - Elsevier
The vibrations of bearings holding the high-speed shaft of a steam turbine are critically
controlled for the safe and reliable power generation at the power plants. In this paper, two …

Machine learning algorithms used in PSE environments: A didactic approach and critical perspective

LF Fuentes-Cortés, A Flores-Tlacuahuac… - Industrial & …, 2022 - ACS Publications
This work addresses recent developments for solving problems in process systems
engineering based on machine learning algorithms. A general description of most popular …

Real-world data-driven machine-learning-based optimal sensor selection approach for equipment fault detection in a thermal power plant

S Khalid, H Hwang, HS Kim - Mathematics, 2021 - mdpi.com
Due to growing electricity demand, developing an efficient fault-detection system in thermal
power plants (TPPs) has become a demanding issue. The most probable reason for failure …

A data-driven health prognostics approach for steam turbines based on xgboost and dtw

Z Que, Z Xu - IEEE Access, 2019 - ieeexplore.ieee.org
A steam turbine is one of the critical components in a power generation system whose
failure may result in unexpected consequences, even catastrophic losses. Thus, the …

Optimizing high-speed rotating shaft vibration control: Experimental investigation of squeeze film dampers and a comparative analysis using Artificial Neural Networks …

RK Gupta, RC Singh - Expert Systems with Applications, 2024 - Elsevier
This research paper presents a comprehensive experimental and statistical approach for the
analysis of vibration amplitudes in a high-speed rotating shaft employing a squeeze film …