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دسته بندی:
یادگیری عمیق - deep learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
Intelligent fault diagnosis of cooling radiator based on deep learning analysis of infrared thermal images
ترجمه فارسی عنوان مقاله:
تشخیص خطای هوشمند رادیاتور خنک کننده بر اساس تجزیه و تحلیل یادگیری عمیق از تصاویر حرارتی مادون قرمز
منبع:
Sciencedirect - Elsevier - Applied Thermal Engineering, 163 (2019) 114410: doi:10:1016/j:applthermaleng:2019:114410
نویسنده:
Amin Nasiria, Amin Taheri-Garavandb,⁎, Mahmoud Omida, Giovanni Maria Carlomagnoc
چکیده انگلیسی:
Detection of faults and intelligent monitoring of equipment operations are essential for modern industries.
Cooling radiator condition is one of the factors that affects engine performance. This paper proposes a novel and
accurate radiator condition monitoring and intelligent fault detection based on thermal images and using a deep
convolutional neural network (CNN) which has a specific configuration to combine the feature extraction and
classification steps. The CNN model is constructed from VGG-16 structure that is followed by batch normalization
layer, dropout layer, and dense layer. The suggested CNN model directly uses infrared thermal images as
input to classify six conditions of the radiator: normal, tubes blockage, coolant leakage, cap failure, loose
connections between fins & tubes and fins blockage. Evaluation of the model demonstrates that leads to results
better than traditional computational intelligence methods, such as an artificial neural network, and can be
employed with high performance and accuracy for fault diagnosis and condition monitoring of the cooling
radiator under various working circumstances.
Keywords: Cooling radiator | Fault detection | Thermal image analysis | Deep learning | Convolutional neural network
قیمت: رایگان
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