Wear surface three-dimensional morphology measurement method based on fused convolutional neural network

Abstract

The invention discloses a fused convolutional neural network-based wear surface three-dimensional topography measurement method, which comprises the following steps of: generating a random rough surface through a two-dimensional digital filtering technology, and obtaining a luminosity image sequence of the random wear surface by utilizing Blender rendering software so as to generate a data set forneural network training; designing a feature extraction module, a fusion module and a normal vector estimation and refinement module to obtain a fused convolutional neural network applied to wear surface normal vector estimation; defining a training loss function of the neural network, and training and adjusting a network model based on the data set; and in combination with priori knowledge of the abraded surface, solving the depth information of the abraded surface based on a regularization algorithm. According to the method, the neural network method and the photometric stereo technology are effectively combined, the problem that the reflection characteristics of the abraded surface are not matched with the Lambert model is solved, and accurate reconstruction of the abraded surface is achieved in combination with priori knowledge of the abraded surface.

Description

technical field [0001] The invention belongs to the technical field of machine wear state monitoring, and in particular relates to a three-dimensional shape measurement method of a wear surface based on a fusion convolutional neural network. Background technique [0002] The friction and wear of key components has become one of the important reasons restricting the operation and service of equipment. The friction pair of mechanical equipment wears and accumulates during operation, causing the parts to lose their original functions and even fail. This will not only increase the failure rate of equipment operation, but also reduce production efficiency, resulting in huge economic losses and waste of resources. Therefore, the study of wear state characterization methods for key components of mechanical equipment plays an important role in improving the operating performance and service capability of equipment, and has become an urgent need for the development of high-end equip...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a method for measuring the three-dimensional topography of the worn surface based on the fusion convolutional neural network, which solves the problem of overall warping in the reconstruction results of the worn surface in the past. , the precise information of the worn surface is obtained, and the accuracy of the 3D reconstruction of the worn surface is improved

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