Jayabarathi Suganandha Bharathi, Ratnam Mani Maran
Faculty of Engineering and Computer Technology, AIMST University, Semeling, Bedong 08100, Kedah, Malaysia.
School of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal 14300, Penang, Malaysia.
Sensors (Basel). 2022 Apr 7;22(8):2842. doi: 10.3390/s22082842.
Current studies are focused on the correlation between characteristic features extracted from the laser speckle pattern of machined surfaces and 2D surface roughness parameters. Since milled surfaces are 3D in nature, 3D surface roughness parameters will provide a more accurate representation of the surface. Novelties of this work are: (1) an inexpensive laser pointer, which was used for presentation and was used without any spatial filtering setup for producing the laser speckle pattern; (2) a correlation study, which was conducted between characteristic features extracted from the speckle pattern and 3D surface roughness; and (3) the influence of angle of illumination, lens aperture size (-number) and shutter speed on the correlation. A highest coefficient of determination of 0.8955 was obtained for the correlation between the gray level co-occurrence matrix descriptor, namely energy, and 3D surface roughness parameter, namely ten-point height S, at an illumination angle of 45°, -number of 16 and shutter speed of 1/100 s.
当前的研究集中于从加工表面的激光散斑图案中提取的特征与二维表面粗糙度参数之间的相关性。由于铣削表面本质上是三维的，三维表面粗糙度参数将能更准确地表示表面。这项工作的新颖之处在于：（1）一个廉价的激光指示器，它用于演示且在没有任何空间滤波设置的情况下用于产生激光散斑图案；（2）一项相关性研究，该研究在从散斑图案中提取的特征与三维表面粗糙度之间进行；以及（3）照明角度、镜头光圈大小（光圈数）和快门速度对相关性的影响。在照明角度为45°、光圈数为16且快门速度为1/100 s时，灰度共生矩阵描述符（即能量）与三维表面粗糙度参数（即十点高度S）之间的相关性获得了高达0.8955的决定系数。
