Research on deep learning in the field of mechanical equipment fault diagnosis image quality

Image quality assessment (IQA) is an indispensable technique in computer vision, which is widely applied in image classification, image clustering. With the development of deep learning, deep neural network (DNN)-based methods have shown impressive performance. Thus, in this paper, we propose a novel method for mechanical equipment fault diagnosis based on IQA. More specifically, we first conduct data acquisition base on our practice. Afterwards, we leverage image processing method for removing noise. Subsequently, we leverage CNN-based method for image classification. Finally, different mechanical equipment images will be grouped into different categories and fault detection can be achieved. Extensive experiments demonstrate the effectiveness and robustness of our method. (C) 2019 Published by Elsevier Inc.