关键词: 融合特征, 特征热图像, 转动副间隙, 词频特征, 卷积神经网络

Abstract: The matching accuracy of the revolute pair is directly affected by its matching clearance.Considering the energy loss caused by collision in the operation of the revolute pair with clearance,a thermal image monitoring method was proposed for clearance of revolute pair with words frequency features.To effectively obtain the abnormal heat distribution,the feature thermal image extraction method of revolute pair with clearance based on the Euclidean-channel separation was proposed.Words frequency matrix of feature thermal image was extracted by constructing the bag model of visual words,and words frequency feature of words frequency matrix was extracted using multi-layer perceptron.The convolutional neural network embedded with attention mechanism was used to extract the feature from feature thermal imaging of the revolute pair with clearance.Through integrating the words frequency feature into the thermal image feature,a clearance monitoring method based on feature fusion was proposed,which could overcome the problem of low accuracy of clearance monitoring using single thermal image feature.Finally,a revolute pair clearance fault simulated experiment platform was built to verify the effectiveness of the revolute pair clearance monitoring method based on fusion features.

Key words: fusion feature, feature thermal image, revolute pair clearance, words frequency feature, convolutional neural network