Online health status monitoring of high voltage insulators using deep learning model
| العنوان: | Online health status monitoring of high voltage insulators using deep learning model |
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| المؤلفون: | Dipu Sarkar, Sravan Kumar Gunturi |
| المصدر: | The Visual Computer. 38:4457-4468 |
| بيانات النشر: | Springer Science and Business Media LLC, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Standard test image, Computer science, business.industry, Deep learning, Motion blur, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Computer Graphics and Computer-Aided Design, Computer graphics, Identification (information), Key (cryptography), Computer vision, Computer Vision and Pattern Recognition, Artificial intelligence, Focus (optics), business, Structured prediction, Software |
| الوصف: | The inspection of electrical components has long been an important issue in the power distribution system. Unmanned drones are impressive surveillance systems with a powerful spatial and remote sensing capability. This paper proposes a system to monitor the health of the ceramic insulators that uses aerial images as a source of information and deep structured learning model for the data interpretation. The key drawbacks of existing monitoring systems are poor detection accuracy and lack of real-time execution, making it more complicated to obtain attributes from aerial photographs. The focus of this paper is to increase accuracy of detection while operating in real-time using You Only Look Once version 3 (YOLOv3). The novelty of the proposed system is that it combines deep learning and the Internet of Things using a single embedded device called Raspberry Pi. For the scientific investigation, we equipped Raspberry Pi with a test image as an input to detect an insulator’s health status using YOLOv3. Many aerial images are not clear due to motion blur. Excluding such low-resolution training images will affect accuracy. So we used a super-resolution CNN to reconstruct a blurred image as high-resolution image. The efficiency of the proposed system has been tested using a private data set consisting of a variety of scenes containing high-voltage power line insulators. The results show that the suggested system is quick and accurate in the identification and classification of insulators. |
| تدمد: | 1432-2315 0178-2789 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_________::febf1f438e6ae2b0bda3c0940faba841Test https://doi.org/10.1007/s00371-021-02308-xTest |
| حقوق: | CLOSED |
| رقم الانضمام: | edsair.doi...........febf1f438e6ae2b0bda3c0940faba841 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14322315 01782789 |
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