Proactive Real-Time Anomaly Detection and Alert System for Industrial Turbines to Improve Operational Resilience

The purpose of the turbine alert system is to monitor turbine problems in real time and react quickly in industrial settings. It allows for rapid action by simulating three scenarios: high risk, low risk, and immediate reset to reflect different levels of urgency. The system combines administrative controls and audio-visual alarms, enabling notifications to be temporarily halted and terminated when problems are fixed. According to simulation data, the technology minimizes operational disruptions by improving reaction efficiency and reducing downtime. Predictive analytics for turbine maintenance and a more user-friendly user interface are two potential future additions. In order to preserve turbine performance and avoid problems, this technology provides a proactive approach.

Authors

Institutions

Publication Details

Published
2025-05-21
DOI
https://doi.org/10.1109/icaiss61471.2025.11041813
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Proactive Real-Time Anomaly Detection and Alert System for Industrial Turbines to Improve Operational Resilience

Manpreet Kaur, Nongmeikapam Thoiba Singh, Manoj Wadhwa, Amit Tiwari et al.
Fault Detection and Control Systems
article

Proactive Real-Time Anomaly Detection and Alert System for Industrial Turbines to Improve Operational Resilience

Manpreet Kaur, Nongmeikapam Thoiba Singh, Manoj Wadhwa, Amit Tiwari, Hrithikvanth VH
article en

Abstract

The purpose of the turbine alert system is to monitor turbine problems in real time and react quickly in industrial settings. It allows for rapid action by simulating three scenarios: high risk, low risk, and immediate reset to reflect different levels of urgency. The system combines administrative controls and audio-visual alarms, enabling notifications to be temporarily halted and terminated when problems are fixed. According to simulation data, the technology minimizes operational disruptions by improving reaction efficiency and reducing downtime. Predictive analytics for turbine maintenance and a more user-friendly user interface are two potential future additions. In order to preserve turbine performance and avoid problems, this technology provides a proactive approach.

Chandigarh University (IN)
Affordable and clean energy
Openalex Percentile: Top 84%
Fault Detection and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Proactive Real-Time Anomaly Detection and Alert System for Industrial Turbines to Improve Operational Resilience — Manpreet Kaur, Nongmeikapam Thoiba Singh, et al. · (2025) | TGRS Research Map | TGRS