An explainable artificial intelligence approach for unsupervised fault detection and diagnosis in rotating machinery
The monitoring of rotating machinery is an essential task in today's production processes.
Currently, several machine learning and deep learning-based modules have achieved …
Currently, several machine learning and deep learning-based modules have achieved …
Non-linear precoding for 5G NR
F Hasegawa, H Nishimoto, N Song… - … IEEE Conference on …, 2018 - ieeexplore.ieee.org
Non-linear precoding gained attention recently in 3GPP (the third generation partnership
project) as a possible technique to improve the performance of multi-user multiple input …
project) as a possible technique to improve the performance of multi-user multiple input …
Vibration anomaly detection of wind turbine based on temporal convolutional network and support vector data description
K Lin, J Pan, Y Xi, Z Wang, J Jiang - Engineering Structures, 2024 - Elsevier
Due to the complex working conditions and harsh environment, wind turbines often
encounter abnormalities, resulting in great operation and maintenance difficulties. As …
encounter abnormalities, resulting in great operation and maintenance difficulties. As …
A new vibration-based hybrid anomaly detection model for preventing high-power generator failures in power plants
This paper presents a new vibration-based hybrid anomaly detection model to prevent high-
power generator failures in power plants. This idea was conceived as it causes large …
power generator failures in power plants. This idea was conceived as it causes large …
Acoustic Camera-Based Anomaly Detection for Wind Turbines
Health monitoring of wind turbines (WTs) has gained a lot of attention recently. Prevalent
solutions mainly rely on the status data from Supervisory Control And Data Acquisition …
solutions mainly rely on the status data from Supervisory Control And Data Acquisition …
Explainable artificial intelligence approaches for fault diagnosis in rotating machinery
LC Brito - 2022 - repositorio.ufu.br
Devido ao crescente interesse pelo aumento da produtividade e redução de custos no
ambiente industrial, novas técnicas de monitoramento de máquinas rotativas estão …
ambiente industrial, novas técnicas de monitoramento de máquinas rotativas estão …
Anomaly Prediction for Wind Turbines Using an Autoencoder with Vibration Data Supported by Power-Curve Filtering
M Takanashi, S Sato, K Indo, N Nishihara… - … on Information and …, 2022 - search.ieice.org
The prediction of the malfunction timing of wind turbines is essential for maintaining the high
profitability of the wind power generation industry. Studies have been conducted on …
profitability of the wind power generation industry. Studies have been conducted on …
Anomaly Prediction of Wind Turbines using Metric Learning with Vibration Data
M Takanashi, S Sato, K Indo… - 2022 11th …, 2022 - ieeexplore.ieee.org
Machine learning methods have attracted interest in automatically detecting and predicting
anomalies in wind turbines by exploiting condition monitoring system data, such as vibration …
anomalies in wind turbines by exploiting condition monitoring system data, such as vibration …
Anomaly Prediction for Wind Turbines Using an Autoencoder Based on Power-Curve Filtering
M Takanashi, SI Sato, K Indo, N Nishihara… - … on Information and …, 2021 - search.ieice.org
Predicting the malfunction timing of wind turbines is essential for maintaining the high
profitability of the wind power generation business. Machine learning methods have been …
profitability of the wind power generation business. Machine learning methods have been …
Health assessment of wind turbines based on output power modelling
X Yin - Eighth International Conference on Energy Materials …, 2023 - spiedigitallibrary.org
Machine learning based performance assessment of wind turbines using the widely
available SCADA data has been receiving growing interest. This work proposes a pragmatic …
available SCADA data has been receiving growing interest. This work proposes a pragmatic …