Fault Diagnosis of Photovoltaic Array Based on Deep Belief Network
The environment of the PV array is harsh and severe, resulting in frequent faults. In order to improve the accuracy of PV array fault diagnosis, a deep belief networks (DBN) based fault diagnosis method is proposed for the common fault types of PV arrays. The experimental feature parameters was obta...
Saved in:
| Main Authors: | Caixia TAO, Xu WANG, Fengyang GAO |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
State Grid Energy Research Institute
2019-12-01
|
| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201901066 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fault diagnosis in photovoltaic arrays: A robust and efficient approach using feature engineering and 1D-CNN
by: Yousif Mahmoud Ali, et al.
Published: (2025-09-01) -
ENGINE FAULT DIAGNOSIS BASED ON DEEP BELIEF NETWORK IMPROVED BY ADAPTIVE CROW SEARCH ALGORITHM (MT)
by: WANG Liang, et al.
Published: (2023-01-01) -
An efficient approach for diagnosing faults in photovoltaic array using 1D-CNN and feature selection Techniques
by: Yousif Mahmoud Ali, et al.
Published: (2025-05-01) -
Fault Diagnosis of the Traction System Based on Wavelet Analysis and Deep Belief Network
by: TANG Lizhe, et al.
Published: (2019-01-01) -
An Intelligent Diagnosis and Fault Detection Model Based on Fuzzy Logic for Photovoltaic Panels
by: Marah Bacha, et al.
Published: (2024-05-01)