摘要
应用2D-VMD算法对图像信号进行去噪,以提升图像质量。采用2D-VMD技术对含有噪声的轴承缺陷图像进行分解,将其分解为有限个固有模态函数(IMF)分量;利用模糊线性指数和标准差筛选各IMF分量,剔除噪声项,实现图像去噪。对比2D-VMD去噪算法和均值滤波、中值滤波的去噪效果,使用均方差和峰值信噪比对去噪后的图像进行客观评价。结果表明:使用2D-VMD算法去噪效果更好,去噪后的图像能保留更多有效信息、图像质量更好,能够满足铁路部门对轴承检修的需求。
2D-VMD algorithm was used to remove noise to improve image quality.The bearing defect image containing noise was decomposed into finite intrinsic mode function(IMF) components by using 2D-VMD technology;the IMF components were screened by using fuzzy linear exponent and standard deviation to eliminate the noise items to achieve image denoising.The denoising effects of 2D-VMD algorithm, mean and median filtering were compared, and the denoised images were objectively evaluated by using means of mean square error and peak signal-to-noise ratio.The results show that by using 2 D-VMD algorithm, the denoising effect is better, and the denoised image can retain more effective information and has better image quality, which can meet the requirements of railway departments for bearing maintenance.
作者
张惠丽
李嘉楠
石炜
黄迎久
ZHANG Huili;LI Jianan;SHI Wei;HUANG Yingjiu(Department of Electrical Engineering,Baotou Vocational&Technical College,Baotou Inner Mongolia 014010,China;School of Mechanical Engineering,Inner Mongolia University of Science and Technology,Baotou Inner Mongolia 014010,China;Engineering Training Center,Inner Mongolia University of Science and Technology,Baotou Inner Mongolia 014010,China)
出处
《机床与液压》
北大核心
2022年第8期204-208,共5页
Machine Tool & Hydraulics
基金
内蒙古自治区自然科学基金项目(2018LH050248)
2018年内蒙古自治区高等学校科学技术研究项目(NJZY18149)。
关键词
二维变分模态分解
模糊线性指数
标准差
均方差
峰值信噪比
Two-dimensional variational mode decomposition
Fuzzy linear exponent
Standard deviation
Mean square error
Peak signal-to-noise ratio
