油路板泄漏量大小是判断油路板质量的标准,其质量的好坏直接影响系统的效率和可靠程度。油路板具有多个接口,使用单个阈值难以利用多接口综合信息评断油路板质量。为此,提出基于模糊支持向量数据描述法(Fuzzy Support Vector Data Descr...油路板泄漏量大小是判断油路板质量的标准,其质量的好坏直接影响系统的效率和可靠程度。油路板具有多个接口,使用单个阈值难以利用多接口综合信息评断油路板质量。为此,提出基于模糊支持向量数据描述法(Fuzzy Support Vector Data Description,FSVDD)油路板质量评估技术。该方法同时将多个接口的泄漏量作为输入,构造FSVDD模型,计算模糊监测系数ε,并通过对油路板进行质量评判。油路板测试试验表明, FSVDD能较好地对油路板进行质量评分,为油路板的使用和质量管控提供依据。展开更多
To evaluate the quality and damage condition of the electrolyzer,wave velocity detection technology and impact echo technology were used to detect the cathode part of the electrolyzer.The experimental results show tha...To evaluate the quality and damage condition of the electrolyzer,wave velocity detection technology and impact echo technology were used to detect the cathode part of the electrolyzer.The experimental results show that wave velocity is linearly related to the porosity,and there is also a linear relationship between wave velocity and the square root of reciprocal density in cathode carbon blocks(CCBs)before installation into electrolyzer.Combined with detection results of wave velocity and voltage drop,the large-size CCBs with relatively good quality can be found.Through the impact echo technology on cathode steel rods(CSRs),the results of the on-site detection show that the damage condition of CSRs can be effectively evaluated,and the damage location of CSRs can be determined.This study proposes a novel and quantifiable method for the evaluation of cathode quality and damage,which provides a reference for prolonging the service life of the electrolyzer.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
Based on advanced computer technology, internet of things （lOT） technology, project management con- cept and professional technology and combined with the innovative theories, methods and techniques in earlier hy- d...Based on advanced computer technology, internet of things （lOT） technology, project management con- cept and professional technology and combined with the innovative theories, methods and techniques in earlier hy- dropower projects, the life-cycle risk management system of high earth-rock dam project for Nuozhadu project was developed. The system mainly includes digital dam, three-dimensional design, construction quality monito- ring, safety assessment and warning, etc, to integrally manage and analyze the dam design, constructional quality and safety monitoring information. It realized the dynamic updates of the comprehensive information and the safe- ty quality monitoring in the project life cycle, and provided the basic platform for the scientific management of the construction and operation safety of high earth-rock dam. Application in Nuozhadu earth-rock dam showed that construction safety monitoring and warning greatly helped accelerate the construction progress and improve project quality, and provided a new way for the quality safety control of high earth-rock dam.展开更多
文摘油路板泄漏量大小是判断油路板质量的标准,其质量的好坏直接影响系统的效率和可靠程度。油路板具有多个接口,使用单个阈值难以利用多接口综合信息评断油路板质量。为此,提出基于模糊支持向量数据描述法(Fuzzy Support Vector Data Description,FSVDD)油路板质量评估技术。该方法同时将多个接口的泄漏量作为输入,构造FSVDD模型,计算模糊监测系数ε,并通过对油路板进行质量评判。油路板测试试验表明, FSVDD能较好地对油路板进行质量评分,为油路板的使用和质量管控提供依据。
基金The authors are grateful for the financial supports from the National Natural Science Foundation of China(No.42172316)the Natural Science Foundation of Hunan Province,China(No.2021JJ30810)the Research Fund of the State Key Laboratory of Coal Resources and Safe Mining,China(No.CUMT SKLCRSM21KF005).
文摘To evaluate the quality and damage condition of the electrolyzer,wave velocity detection technology and impact echo technology were used to detect the cathode part of the electrolyzer.The experimental results show that wave velocity is linearly related to the porosity,and there is also a linear relationship between wave velocity and the square root of reciprocal density in cathode carbon blocks(CCBs)before installation into electrolyzer.Combined with detection results of wave velocity and voltage drop,the large-size CCBs with relatively good quality can be found.Through the impact echo technology on cathode steel rods(CSRs),the results of the on-site detection show that the damage condition of CSRs can be effectively evaluated,and the damage location of CSRs can be determined.This study proposes a novel and quantifiable method for the evaluation of cathode quality and damage,which provides a reference for prolonging the service life of the electrolyzer.
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.
文摘Based on advanced computer technology, internet of things （lOT） technology, project management con- cept and professional technology and combined with the innovative theories, methods and techniques in earlier hy- dropower projects, the life-cycle risk management system of high earth-rock dam project for Nuozhadu project was developed. The system mainly includes digital dam, three-dimensional design, construction quality monito- ring, safety assessment and warning, etc, to integrally manage and analyze the dam design, constructional quality and safety monitoring information. It realized the dynamic updates of the comprehensive information and the safe- ty quality monitoring in the project life cycle, and provided the basic platform for the scientific management of the construction and operation safety of high earth-rock dam. Application in Nuozhadu earth-rock dam showed that construction safety monitoring and warning greatly helped accelerate the construction progress and improve project quality, and provided a new way for the quality safety control of high earth-rock dam.
