Hardness indentation detection and classification technology based on image processing

A. C. Shilin, B. Wei
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Abstract

Hardness measurement methods are simple, effective and convenient, and have great practical value. In order to improve the efficiency of hardness detection to adapt to product requirements, automated detection requirements are put forward for hardness indentation detection.Based on image processing, this paper studies the detection and classification technology of hardness indentation, and accomplishes the following research work: identifying the surface condition of hardness block and planning the new indentation trajectory based on the recognition results; Based on deep learning, an indentation classification algorithm is designed to improve the sorting accuracy and speed of hardness blocks. The research results can be used in engineering applications.Through theoretical analysis and experimental verification, the hardness indentation detection and classification technology based on image processing has high positioning, classification and detection speed and accuracy, which meets the automation requirements of hardness detection.
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基于图像处理的硬度压痕检测与分类技术
硬度测量方法简单、有效、方便,具有很大的实用价值。为了提高硬度检测效率以适应产品要求,对硬度压痕检测提出了自动化检测要求。本文以图像处理为基础,研究了硬度压痕的检测与分类技术,完成了以下研究工作:识别硬度块的表面状况,并根据识别结果规划新的压痕轨迹;为了提高硬度块的分类精度和速度,设计了一种基于深度学习的压痕分类算法。研究结果具有一定的工程应用价值。通过理论分析和实验验证,基于图像处理的硬度压痕检测分类技术具有较高的定位、分类和检测速度和精度,满足硬度检测自动化的要求。
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