| 自适应差异多尺度形态学的风力机叶片红外图像增强研究 |
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| 引用本文： | 康爽,陈长征,赵思雨,罗园庆,孔祥希. 自适应差异多尺度形态学的风力机叶片红外图像增强研究[J]. 中国机械工程, 2021, 32(7): 786-792. DOI: 10.3969/j.issn.1004-132X.2021.07.004 |
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| 作者姓名： | 康爽 陈长征 赵思雨 罗园庆 孔祥希 |
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| 作者单位： | 1.沈阳工业大学机械工程学院，沈阳，1108702．辽宁省振动噪声控制技术工程研究中心，沈阳，110870 |
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| 基金项目： | 国家自然科学基金（51675350,51705337）；辽宁省自然科学基金（2019MS245） |
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| 摘 要： | 为提高采用红外检测技术检测风力发电机叶片内部缺陷的能力,改善红外热像图的清晰度低、背景光照不均和细节识别能力弱等问题,提出了一种自适应差异多尺度形态学(ADMM)的图像增强算法.在膨胀和腐蚀运算中分别选择不同尺度的结构元素作为操作对象,采用对比度改善系数比最大值作为多尺度及差异尺度选择的目标函数;利用开、闭及顶帽运算的...
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| 关 键 词： | 风力发电机叶片 红外检测 直方图均衡化 结构元素 图像增强 |
Study on Infrared Image Enhancement of Wind Turbine Blades Based on Adaptive Differential Multiscale Morphology(ADMM) |
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| KANG Shuang,CHEN Changzheng,ZHAO Siyu,LUO Yuanqing,KONG Xiangxi. Study on Infrared Image Enhancement of Wind Turbine Blades Based on Adaptive Differential Multiscale Morphology(ADMM)[J]. China Mechanical Engineering, 2021, 32(7): 786-792. DOI: 10.3969/j.issn.1004-132X.2021.07.004 |
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| Authors: | KANG Shuang CHEN Changzheng ZHAO Siyu LUO Yuanqing KONG Xiangxi |
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| Affiliation: | 1.School of Mechanical Engineering，Shenyang University of Technology，Shenyang，1108702.Liaoning Engineering Center for Vibration and Noise Control，Shenyang，110870 |
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| Abstract: | In order to improve the ability of infrared detection of internal defects of wind turbine blades and overcome the problems of low definition of infrared thermal images, uneven background illumination, and weak ability of detail recognition, an image enhancement algorithm was proposed based on ADMM. Different scale structural elements were selected as the operation objects in the expansion and corrosion operations, and the maximum contrast improvement coefficient ratio was used as the objective function of multi-scale and difference scale selection. The light and dark details of multi-scale images were extracted by using the advantages of open, close, and top-hat operations. Then, the differences between the white cap and the black cap were calculated to get the detail enhancement information, and the enhanced infrared images were obtained by fusing with the original images. Finally, the grayscale distribution of the image was adjusted to achieve the best visual effectiveness. Simulation results show that the algorithm has strong robustness and may effectively enhance the infrared image details under uneven illumination, improve the detection ability of infrared detection in wind turbine blades. |
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| Keywords: | wind turbine blade infrared detection histogram equalization structural element image enhancement |
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