From Anomaly Detection to Novel Fault Discrimination for Wind Turbine Gearboxes With a Sparse Isolation Encoding Forest-Reference-Cited by-同舟云学术

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From Anomaly Detection to Novel Fault Discrimination for Wind Turbine Gearboxes With a Sparse Isolation Encoding Forest

Published:2022 Issue: Volume:71 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Du Wenliao¹^ORCID,Guo Zhen¹^ORCID,Li Chuan¹^ORCID,Gong Xiaoyun¹^ORCID,Pu Ziqiang¹^ORCID

Affiliation:

1. Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou, China

Funder

National Natural Science Foundation of China

Chongqing Natural Science Foundation

Basic and Applied Basic Research Foundation of Guangdong Province

Intelligent Manufacturing PHM Innovation Team Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09819973.pdf?arnumber=9819973

Reference44 articles.

1. On Information and Sufficiency

2. Fault diagnosis for wind turbine gearboxes by using deep enhanced fusion network;pu;IEEE Trans Instrum Meas,2020

3. Novelty detection: a review—part 1: statistical approaches

4. A deep learning-based surface defect inspection system using multi-scale and channel-compressed features

5. Anomaly detection and critical SCADA parameters identification for wind turbines based on LSTM-AE neural network

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1. Machine learning applications in health monitoring of renewable energy systems;Renewable and Sustainable Energy Reviews;2024-01

2. Efficient channel attention residual learning for the time-series fault diagnosis of wind turbine gearboxes;Measurement Science and Technology;2023-10-12

3. Condition monitoring of wind turbine using novel deep learning method and dynamic kernel principal components Mahalanobis distance;Engineering Applications of Artificial Intelligence;2023-10

4. A Hybrid Feature Selection and Construction Method for Detection of Wind Turbine Generator Heating Faults;2023 4th International Conference on Clean and Green Energy Engineering (CGEE);2023-08-26

5. Elderly People Care Support System Under COVID-19 Environment Using Advanced ICT/AI Data Science and Its Field Trials;2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT);2023-05-10

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