Power system event identification based on deep neural network with information loading
Online power system event identification and classification are crucial to enhancing the
reliability of transmission systems. In this paper, we develop a deep neural network (DNN) …
reliability of transmission systems. In this paper, we develop a deep neural network (DNN) …
End to end machine learning for fault detection and classification in power transmission lines
F Rafique, L Fu, R Mai - Electric Power Systems Research, 2021 - Elsevier
This paper proposes a new machine learning approach for fault detection and classification
tasks in electrical power transmission networks. This method exploits the temporal sequence …
tasks in electrical power transmission networks. This method exploits the temporal sequence …
Online power system event detection via bidirectional generative adversarial networks
Accurate and speedy detection of power system events is critical to enhancing the reliability
and resiliency of power systems. Although supervised deep learning algorithms show great …
and resiliency of power systems. Although supervised deep learning algorithms show great …
Online event detection in synchrophasor data with graph signal processing
Online detection of anomalies is crucial to enhancing the reliability and resiliency of power
systems. We propose a novel data-driven online event detection algorithm with …
systems. We propose a novel data-driven online event detection algorithm with …
Matrix profile-based approach to industrial sensor data analysis inside RDBMS
M Zymbler, E Ivanova - Mathematics, 2021 - mdpi.com
Currently, big sensor data arise in a wide spectrum of Industry 4.0, Internet of Things, and
Smart City applications. In such subject domains, sensors tend to have a high frequency and …
Smart City applications. In such subject domains, sensors tend to have a high frequency and …
Matrix profile implementation perspective in Industrial Internet of Things production maintenance application
The matrix profile processing is considered for the implementation of production
maintenance tasks in the context of data acquisition by industrial Internet of Things solutions …
maintenance tasks in the context of data acquisition by industrial Internet of Things solutions …
Signal Processing and Pattern Recognition for Leak Detection in a Water Distribution Network
DB Barros, TC Pereira, G Meirelles… - Journal of Water …, 2024 - ascelibrary.org
Leaks are a constant problem in water distribution systems, resulting in wasted resources,
environmental impacts, and financial losses. Thus, it is crucial to develop effective and agile …
environmental impacts, and financial losses. Thus, it is crucial to develop effective and agile …
Power system event identification with transfer learning using large-scale real-world synchrophasor data in the United States
The lack of sufficient labeled events and long training time limit the applicability of deep
neural network-based power system event identification using synchrophasor data. In this …
neural network-based power system event identification using synchrophasor data. In this …
Real-time event detection using rank signatures of real-world pmu data
Timely detection of power system events is a crucial task, which can facilitate the
implementation of remedial actions to improve reliability, resiliency, and security of the …
implementation of remedial actions to improve reliability, resiliency, and security of the …
On the ranking of variable length discords through a hybrid outlier detection approach
HE Khansa, C Gervet, A Brouillet - International Conference on Discovery …, 2022 - Springer
In this paper we are interested in identifying insightful changes in climate observations
series, through outlier detection techniques. Discords are outliers that cover a certain length …
series, through outlier detection techniques. Discords are outliers that cover a certain length …