Application of interpretability method based on FN-v8 in defect detection of photovoltaic panels

Li Zhou; Xueliang Sun; Yiming Liu

doi:10.1117/12.3008834

27 October 2023 Application of interpretability method based on FN-v8 in defect detection of photovoltaic panels

Li Zhou, Xueliang Sun, Yiming Liu

Proceedings Volume 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023); 129220N (2023) https://doi.org/10.1117/12.3008834
Event: The Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 2023, Xiamen, China

Abstract

Aiming at the problems of poor interpretability of traditional neural network and bloated traditional model in photovoltaic panel defect detection. Firstly, an FN-v8 model was proposed for detecting various types of defects in photovoltaic panels. The FN-v8 model reduces redundant computing and memory access, while also reducing the GFLOPs of the model. Then, Grad-CAM was used to further demonstrate the stronger interpretability of the new model through passive interpretation. Compared with other traditional models with relatively bulky structures, the proposed new model has smaller parameter quantities and stronger interpretability. Experiments were conducted on devices with the same performance and the same dataset of photovoltaic panel defects. The results showed that the proposed new model has a smaller volume, faster calculation speed, and higher accuracy than the original model. The GFLOPs of the new model have decreased by 18.25% compared to the original model, significantly reducing the computational complexity, and the visualization of the thermodynamic diagram is more accurate, further indicating an improvement in interpretability. Moreover, the new model has better detection accuracy for photovoltaic panel detection, with an average detection accuracy ( mAP@0.5) improved by 2.1% compared to the original model.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Li Zhou, Xueliang Sun, and Yiming Liu "Application of interpretability method based on FN-v8 in defect detection of photovoltaic panels", Proc. SPIE 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 129220N (27 October 2023); https://doi.org/10.1117/12.3008834

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Solar cells

Defect detection

Object detection

Neural networks

Performance modeling

Atmospheric modeling

Instrument modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years