We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Anomaly Detection in Gas Turbines Using Outlet Energy Analysis with Cluster-Based Matrix Profile.
- Authors
Ghazvini, Mina Bagherzade; Sànchez-Marrè, Miquel; Naderi, Davood; Angulo, Cecilio
- Abstract
Gas turbines play a key role in generating power. It is really important that they work efficiently, safely, and reliably. However, their performance can be adversely affected by factors such as component wear, vibrations, and temperature fluctuations, often leading to abnormal patterns indicative of potential failures. As a result, anomaly detection has become an area of active research. Matrix Profile (MP) methods have emerged as a promising solution for identifying significant deviations in time series data from normal operational patterns. While most existing MP methods focus on vibration analysis of gas turbines, this paper introduces a novel approach using the outlet power signal. This modified approach, termed Cluster-based Matrix Profile (CMP) analysis, facilitates the identification of abnormal patterns and subsequent anomaly detection within the gas turbine engine system. Significantly, CMP analysis not only accelerates processing speed, but also provides user-friendly support information for operators. The experimental results on real-world gas turbines demonstrate the effectiveness of our approach in the early detection of anomalies and potential system failures.
- Subjects
GAS turbines; GAS power plants; SYSTEM failures; INTERNAL combustion engines; TIME series analysis; GAS analysis
- Publication
Energies (19961073), 2024, Vol 17, Issue 3, p653
- ISSN
1996-1073
- Publication type
Article
- DOI
10.3390/en17030653