为解决混合主动调谐质量阻尼器(Hybrid Active Tuned Mass Dampers,HATMD)中小质量块有较大冲程的问题,提出了增强混合主动调谐质量阻尼器(Enhanced Hybrid Active Tuned Mass Dampers,EHATMD)。具体地说,是在受控结构与HATMD中的小质...为解决混合主动调谐质量阻尼器(Hybrid Active Tuned Mass Dampers,HATMD)中小质量块有较大冲程的问题,提出了增强混合主动调谐质量阻尼器(Enhanced Hybrid Active Tuned Mass Dampers,EHATMD)。具体地说,是在受控结构与HATMD中的小质量块之间设置一个连接阻尼器而构成EHATMD系统。在频域内,推导出结构-EHATMD系统的动力放大系数解析式,进而定义了EHATMD系统的最优化准则。使用遗传算法(Genetic Algorithm,GA),研究了连接阻尼比和正、负标准化加速度反馈增益系数对EHATMD(简称为正反馈EHATMD和负反馈EHATMD)最优参数和减振有效性以及大、小质量块冲程的影响行为。此外,为比较的目的,同时给出了正反馈HATMD和负反馈HATMD的GA优化结果。数值结果表明,EHATMD系统优于HATMD系统;而且,负反馈EHATMD是一种高性能的减振控制装置。展开更多
Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making...Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making it difficult to identify surface defects. In this study,a method for improving the quality of underwater images is proposed.By analyzing the degradation characteristics of underwater detection image,the image enhancement technology is used to improve the color richness of the image,and then the improved dark channel prior(DCP)algorithm is used to restore it. By modifying the estimation formula of transmittance and background light,the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details,thus effectively enhancing the reliability of visual inspection of NPPs.展开更多
Image enhancement is a popular technique,which is widely used to improve the visual quality of images.While image enhancement has been extensively investigated,the relevant quality assessment of enhanced images remain...Image enhancement is a popular technique,which is widely used to improve the visual quality of images.While image enhancement has been extensively investigated,the relevant quality assessment of enhanced images remains an open problem,which may hinder further development of enhancement techniques.In this paper,a no-reference quality metric for digitally enhanced images is proposed.Three kinds of features are extracted for characterizing the quality of enhanced images,including non-structural information,sharpness and naturalness.Specifically,a total of 42 perceptual features are extracted and used to train a support vector regression(SVR) model.Finally,the trained SVR model is used for predicting the quality of enhanced images.The performance of the proposed method is evaluated on several enhancement-related databases,including a new enhanced image database built by the authors.The experimental results demonstrate the efficiency and advantage of the proposed metric.展开更多
文摘为解决混合主动调谐质量阻尼器(Hybrid Active Tuned Mass Dampers,HATMD)中小质量块有较大冲程的问题,提出了增强混合主动调谐质量阻尼器(Enhanced Hybrid Active Tuned Mass Dampers,EHATMD)。具体地说,是在受控结构与HATMD中的小质量块之间设置一个连接阻尼器而构成EHATMD系统。在频域内,推导出结构-EHATMD系统的动力放大系数解析式,进而定义了EHATMD系统的最优化准则。使用遗传算法(Genetic Algorithm,GA),研究了连接阻尼比和正、负标准化加速度反馈增益系数对EHATMD(简称为正反馈EHATMD和负反馈EHATMD)最优参数和减振有效性以及大、小质量块冲程的影响行为。此外,为比较的目的,同时给出了正反馈HATMD和负反馈HATMD的GA优化结果。数值结果表明,EHATMD系统优于HATMD系统;而且,负反馈EHATMD是一种高性能的减振控制装置。
基金supported by the National Natural Science Foundations of China (Nos. 51674031,51874022)。
文摘Visual inspection of the key components of nuclear power plants(NPPs)is important for NPP operation and maintenance. However,the underwater environment and existing radiation will lead to image degradation,thus making it difficult to identify surface defects. In this study,a method for improving the quality of underwater images is proposed.By analyzing the degradation characteristics of underwater detection image,the image enhancement technology is used to improve the color richness of the image,and then the improved dark channel prior(DCP)algorithm is used to restore it. By modifying the estimation formula of transmittance and background light,the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details,thus effectively enhancing the reliability of visual inspection of NPPs.
基金supported in part by the National Natural Science Foundation of China under Grant 61379143in part by the Fundamental Research Funds for the Central Universities under Grant 2015QNA66in part by the Qing Lan Project of Jiangsu Province
文摘Image enhancement is a popular technique,which is widely used to improve the visual quality of images.While image enhancement has been extensively investigated,the relevant quality assessment of enhanced images remains an open problem,which may hinder further development of enhancement techniques.In this paper,a no-reference quality metric for digitally enhanced images is proposed.Three kinds of features are extracted for characterizing the quality of enhanced images,including non-structural information,sharpness and naturalness.Specifically,a total of 42 perceptual features are extracted and used to train a support vector regression(SVR) model.Finally,the trained SVR model is used for predicting the quality of enhanced images.The performance of the proposed method is evaluated on several enhancement-related databases,including a new enhanced image database built by the authors.The experimental results demonstrate the efficiency and advantage of the proposed metric.
