Fault diagnosis of electric impact drills using thermal imaging
Fault diagnosis of electric impact drills using thermal imaging
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DOI：
10.1016/j.measurement.2020.108815
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发表时间：
2021-02-01
期刊：
影响因子：
5.6
通讯作者：
Glowacz, Adam
中科院分区：
文献类型：
--
作者：
Glowacz, Adam
故障诊断可以节省维护费用。介绍了一种基于热图像分析的故障诊断方法。提出了一种新颖的热图像特征提取方法BCAoID（Binarized Common Areas of Image Differences）。使用三种电动冲击钻（EID）的热图像进行分析：健康的EID、风扇故障的EID（10个风扇叶片断裂）、齿轮系损坏的EID。使用BCAoID提取热图像的特征。使用最近邻分类器和反向传播神经网络的计算功能进行了分析。所执行分析的识别结果在97.91- 100%范围内。基于热图像的故障诊断可以应用于旋转机械和发动机的保护。
Fault diagnosis enables to make savings related to maintenance. The presented work describes fault diagnosis method based on analysis of thermal images. An original method for feature extraction of thermal images BCAoID (Binarized Common Areas of Image Differences) is proposed. Thermal images of three electric impact drills (EID) were used for an analysis: healthy EID, EID with faulty fan (10 broken fan blades), EID with damaged gear train. Features of thermal images were extracted using the BCAoID. The computed features were analyzed using the Nearest Neighbor classifier and the backpropagation neural network. The recognition results of the performed analysis were in the range of 97.91-100%. Fault diagnosis based on thermal images can find application for protecting of rotating machinery and engines.