As humanity advances into the virtual world and the era of mixed reality,high-fidelity gesture mapping has become a key interface connecting the physical world and the digital space.However,the existing solutions are ...As humanity advances into the virtual world and the era of mixed reality,high-fidelity gesture mapping has become a key interface connecting the physical world and the digital space.However,the existing solutions are limited by the bottlenecks of active sensors in terms of information richness and structure and have insufficient precise reconstruction capabilities for high-degree-of-freedom hand movements,making it difficult to achieve a natural and seamless interaction experience.Here,a dynamic gesture mapping system(DGMS)has been developed,which combines a lightweight and efficient hand motion signal acquisition device(HSAD)with an efficient signal processing algorithm(SPA).HSAD captures the motion information on 17°of freedom for the hand through sensor clusters and wirelessly transmits the data to the signal processing platform.On this platform,SPA converts electrical signals into bending angle information,with an error below 1°.DGMS synchronously and accurately maps the hand movement information output by SPA to the virtual environment,achieving real-time interaction with objects in the virtual space.This study has for the first time achieved such a high-degree-of-freedom and high-fidelity gesture mapping using passive sensors and explored the application of gesture mapping in the virtual-real coexisting intelligent enhancement platform,offering a novel technical route for digital twin applications.展开更多
Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods...Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.展开更多
An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of a...An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.展开更多
The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,th...The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.展开更多
Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two im...Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two imaging methods in different injury grades and different cartilage subregions,and provide evidence-based basis for the accurate diagnosis of clinical cartilage injury.Methods:Clinical and imaging data of 286 patients with knee joint lesions admitted to the Affiliated Hospital of Xiangtan Medicine and Health Vocational College from January 2020 to June 2023 were collected retrospectively.All patients underwent both traditional MRI sequences and T2 Mapping sequences.The knee joint cartilage was divided into 14 subregions.Two senior radiologists independently diagnosed the images of the two imaging technologies using a blind method and recorded the cartilage injury grades.The sensitivity,specificity,accuracy,positive predictive value,negative predictive value,and area under the receiver operating characteristic curve(AUC)of the two technologies for diagnosing cartilage injury were calculated and compared,and the differences in their diagnostic efficacy in different injury grades and different subregions were analyzed.Results:A total of 4004 cartilage subregions from 286 patients were included in the analysis,including 1836 injured subregions and 2168 normal subregions.The overall sensitivity(89.7%),accuracy(91.2%),and AUC(0.946)of T2 Mapping quantitative imaging for diagnosing cartilage injury were significantly higher than those of traditional MRI(76.3%,82.5%,and 0.852 respectively),with statistically significant differences(p<0.001);there was no significant difference in specificity between the two(93.5%vs 90.8%,p=0.062).Subgroup analysis showed that T2 Mapping had the most significant diagnostic advantage in early cartilage injury(Grade 1),with sensitivity(78.5%)33.2%higher than that of traditional MRI(45.3%)(p<0.001).Conclusion:The diagnostic efficacy of T2 Mapping quantitative imaging for knee joint cartilage injury is significantly superior to that of traditional MRI,especially in the detection of early cartilage injury and accurate evaluation of weight-bearing area injury.Data verify its clinical applicability and reliability.It can be used as an important supplementary method to traditional MRI,and is recommended for the early diagnosis,grading evaluation,and clinical follow-up of cartilage injury.展开更多
Cotton is an important global cash crops that serve as the primary source of natural fiber for textiles.A thorough understand-ing of the long-term variations in cotton cultivation is vital for optimizing cotton cultiv...Cotton is an important global cash crops that serve as the primary source of natural fiber for textiles.A thorough understand-ing of the long-term variations in cotton cultivation is vital for optimizing cotton cultivation management and promoting the sustainable development of the cotton industry.Xinjiang is the primary cotton-producing region in China.However,long-term data of cotton cultiv-ation areas with high spatial resolution are unavailable for Xinjiang,China.Therefore,this study aimed to identify and map an accurate 30-m cotton cultivation area dataset in Xinjiang from 2000 to 2020 by applying a Random Forest(RF)-based method that integrates Landsat and Moderate Resolution Imaging Spectroradiometer(MODIS)images,and validated the applicability and accuracy of dataset at a large spatial scale.Then,this study analyzed the spatiotemporal variations and influencing factors of cotton cultivation in the study period.The results showed that a high classification accuracy was achieved(overall accuracy>85%,F1>0.80),strongly agreeing with county-level agricultural statistical yearbook data(R2>0.72).Significant spatiotemporal variation in the cotton cultivation areas was found in Xinjiang,with a total increase of 1131.26 kha from 2000 to 2020.Notably,cotton cultivation area in southern Xinjiang expan-ded substantially,with that in Aksu increasing from 20.10%in 2000 to 28.17%in 2020,representing an expansion of 374.29 kha.In northern Xinjiang,the cotton areas in the Tacheng region also exhibited significant increased by almost ten percentage points in the same period.In contrast,cotton cultivation in eastern Xinjiang declined,decreasing from 2.22%in 2000 to merely 0.24%in 2020.Standard deviation ellipse analysis revealed a‘northeast-southwest’spatial distribution,with the centroid consistently located in Aksu and shifting 102.96 km over the 20-yr period.Pearson correlation analysis indicated that socioeconomic factors had a stronger influence on cotton cultivation than climatic factors,with effective irrigation area(r=0.963,P<0.05)and total agricultural machinery power(r=0.823)showing significant positive correlations,whereas climatic variables exhibiting weak associations(r<0.200).These results provide valuable scientific data for informed agricultural management,sustainable development,and policymaking.展开更多
With the support by the National Natural Science Foundation of China and East China Normal University,the research team led by Prof.Tian Yang(田阳)at the Shanghai Key Laboratory of Green Chemistry and Chemical Process...With the support by the National Natural Science Foundation of China and East China Normal University,the research team led by Prof.Tian Yang(田阳)at the Shanghai Key Laboratory of Green Chemistry and Chemical Processes,East China Normal University,developed a novel SERS Optophysiological probe for brain research,which was published in Angew Chem Int Ed(2019,58:5256—5260).展开更多
Three-dimensional(3D)fetal ultrasound has been widely used in prenatal examinations.Realistic and real-time volumetric ultrasound volume rendering can enhance the effectiveness of diagnoses and assist obstetricians an...Three-dimensional(3D)fetal ultrasound has been widely used in prenatal examinations.Realistic and real-time volumetric ultrasound volume rendering can enhance the effectiveness of diagnoses and assist obstetricians and pregnant mothers in communicating.However,this remains a challenging task because(1)there is a large amount of speckle noise in ultrasound images and(2)ultrasound images usually have low contrasts,making it difficult to distinguish different tissues and organs.However,traditional local-illumination-based methods do not achieve satisfactory results.This real-time requirement makes the task increasingly challenging.This study presents a novel real-time volume-rendering method equipped with a global illumination model for 3D fetal ultrasound visualization.This method can render direct illumination and indirect illumination separately by calculating single scattering and multiple scattering radiances,respectively.The indirect illumination effect was simulated using volumetric photon mapping.Calculating each photon’s brightness is proposed using a novel screen-space destiny estimation to avoid complicated storage structures and accelerate computation.This study proposes a high dynamic range approach to address the issue of fetal skin with a dynamic range exceeding that of the display device.Experiments show that our technology,compared to conventional methodologies,can generate realistic rendering results with far more depth information.展开更多
冶金尘泥的转底炉处理工艺是目前钢铁行业采用的主要处置工艺,但在实际生产过程中经常出现还原焙烧不均匀的问题。利用微观扫描电子显微镜(scanning electron microscopy,SEM)分析结合宏观Maps统计分析,对冶金尘泥还原焙烧的不均匀性进...冶金尘泥的转底炉处理工艺是目前钢铁行业采用的主要处置工艺,但在实际生产过程中经常出现还原焙烧不均匀的问题。利用微观扫描电子显微镜(scanning electron microscopy,SEM)分析结合宏观Maps统计分析,对冶金尘泥还原焙烧的不均匀性进行详细的可视化、数据化分析。研究结果表明,冶金尘泥在焙烧温度为1250℃、焙烧时间为15 min的条件下,熟球金属化率达到89.04%、脱锌率达到81.66%、抗压强度达到3.03 kN,熟球金属化率和脱锌率会随着焙烧温度提高和焙烧时间延长而进一步提高,但熟球抗压强度在焙烧时间过长时反而逐渐降低;熟球Maps统计分析表明,提高焙烧温度更有利于提高熟球外圈和下部的还原程度,而延长焙烧时间也更有利于提高熟球下部还原程度,但对熟球内部和外圈还原程度的提升作用比较相似;同时,提高焙烧温度也更有利于提升熟球下部的致密化程度,降低熟球上、下孔隙结构的不均匀性,进而显著提高熟球整体抗压强度;但焙烧时间过长会导致熟球中小孔隙融合为大孔隙,反而降低熟球抗压强度。此外,熟球中硅酸盐(渣相)和浮氏体(FexO)更容易破裂,而金属铁(Fe)可延缓裂纹蔓延,因而,适当提高熟球金属化率、降低硅酸盐(渣相)含量也有利于提高其抗压强度。基于Maps统计分析探究了冶金尘泥还原焙烧过程中物相及孔隙的变化规律,分析结果可以为转底炉工艺处理冶金尘泥的生产实践提供指导和建议。展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52372107)the Zhongyuan Talent Program(Talent Cultivation Series)-Leading Talents in Zhongyuan Basic Research,the Henan Center for Outstanding Overseas Scientists(Grant No.GZS2024003)+1 种基金the Natural Science Foundation of Henan Province in China(Grant No.252300421801)the China Postdoctoral Science Foundation(Grant No.2023M740992).
文摘As humanity advances into the virtual world and the era of mixed reality,high-fidelity gesture mapping has become a key interface connecting the physical world and the digital space.However,the existing solutions are limited by the bottlenecks of active sensors in terms of information richness and structure and have insufficient precise reconstruction capabilities for high-degree-of-freedom hand movements,making it difficult to achieve a natural and seamless interaction experience.Here,a dynamic gesture mapping system(DGMS)has been developed,which combines a lightweight and efficient hand motion signal acquisition device(HSAD)with an efficient signal processing algorithm(SPA).HSAD captures the motion information on 17°of freedom for the hand through sensor clusters and wirelessly transmits the data to the signal processing platform.On this platform,SPA converts electrical signals into bending angle information,with an error below 1°.DGMS synchronously and accurately maps the hand movement information output by SPA to the virtual environment,achieving real-time interaction with objects in the virtual space.This study has for the first time achieved such a high-degree-of-freedom and high-fidelity gesture mapping using passive sensors and explored the application of gesture mapping in the virtual-real coexisting intelligent enhancement platform,offering a novel technical route for digital twin applications.
基金National Key Scientific Instrument and Equipment Development Project under Grant No.61827801the open research fund of State Key Laboratory of Integrated Services Networks,No.ISN22-11+1 种基金Natural Science Foundation of Jiangsu Province,No.BK20211182open research fund of National Mobile Communications Research Laboratory,Southeast University,No.2022D04。
文摘Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.
基金support of the National Natural Science Foundation of China(No.52274176)the Guangdong Province Key Areas R&D Program(No.2022B0101070001)+5 种基金Chongqing Elite Innovation and Entrepreneurship Leading talent Project(No.CQYC20220302517)the Chongqing Natural Science Foundation Innovation and Development Joint Fund(No.CSTB2022NSCQ-LZX0079)the National Key Research and Development Program Young Scientists Project(No.2022YFC2905700)the Chongqing Municipal Education Commission“Shuangcheng Economic Circle Construction in Chengdu-Chongqing Area”Science and Technology Innovation Project(No.KJCX2020031)the Fundamental Research Funds for the Central Universities(No.2024CDJGF-009)the Key Project for Technological Innovation and Application Development in Chongqing(No.CSTB2025TIAD-KPX0029).
文摘An innovative real-time monitoring method for surrounding rock damage based on microseismic time-lapse double-difference tomography is proposed for delayed dynamic damage identification and insufficient detection of adverse geological conditions in deep-buried tunnel construction.The installation techniques for microseismic sensors were optimized by mounting sensors at bolt ends which significantly improves signal-to-noise ratio(SNR)and anti-interference capability compared to conventional borehole placement.Subsequently,a 3D wave velocity evolution model that incorporates construction-induced disturbances was established,enabling the first visualization of spatiotemporal variations in surrounding rock wave velocity.It finds significant wave velocity reduction near the tunnel face,with roof and floor damage zones extending 40–50 m;wave velocities approaching undisturbed levels at 15 m ahead of the working face and on the laterally undisturbed side;pronounced spatial asymmetry in wave velocity distribution—values on the left side exceed those on the right,with a clear stress concentration or transition zone located 10–15 m;and systematically lower velocities behind the face than in front,indicating asymmetric rock damage development.These results provide essential theoretical support and practical guidance for optimizing dynamic construction strategies,enabling real-time adjustment of support parameters,and establishing safety early warning systems in deep-buried tunnel engineering.
基金supported by the National Natural Science Foundation of China(Grant No.62403486)。
文摘The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.
基金Application Research of MRI Physiological Quantitative Imaging Technology in the Diagnosis of Cartilage Injury(Project No.:RCYJ2021-04)。
文摘Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two imaging methods in different injury grades and different cartilage subregions,and provide evidence-based basis for the accurate diagnosis of clinical cartilage injury.Methods:Clinical and imaging data of 286 patients with knee joint lesions admitted to the Affiliated Hospital of Xiangtan Medicine and Health Vocational College from January 2020 to June 2023 were collected retrospectively.All patients underwent both traditional MRI sequences and T2 Mapping sequences.The knee joint cartilage was divided into 14 subregions.Two senior radiologists independently diagnosed the images of the two imaging technologies using a blind method and recorded the cartilage injury grades.The sensitivity,specificity,accuracy,positive predictive value,negative predictive value,and area under the receiver operating characteristic curve(AUC)of the two technologies for diagnosing cartilage injury were calculated and compared,and the differences in their diagnostic efficacy in different injury grades and different subregions were analyzed.Results:A total of 4004 cartilage subregions from 286 patients were included in the analysis,including 1836 injured subregions and 2168 normal subregions.The overall sensitivity(89.7%),accuracy(91.2%),and AUC(0.946)of T2 Mapping quantitative imaging for diagnosing cartilage injury were significantly higher than those of traditional MRI(76.3%,82.5%,and 0.852 respectively),with statistically significant differences(p<0.001);there was no significant difference in specificity between the two(93.5%vs 90.8%,p=0.062).Subgroup analysis showed that T2 Mapping had the most significant diagnostic advantage in early cartilage injury(Grade 1),with sensitivity(78.5%)33.2%higher than that of traditional MRI(45.3%)(p<0.001).Conclusion:The diagnostic efficacy of T2 Mapping quantitative imaging for knee joint cartilage injury is significantly superior to that of traditional MRI,especially in the detection of early cartilage injury and accurate evaluation of weight-bearing area injury.Data verify its clinical applicability and reliability.It can be used as an important supplementary method to traditional MRI,and is recommended for the early diagnosis,grading evaluation,and clinical follow-up of cartilage injury.
基金Under the auspices of the National Natural Science Foundation of China(No.42101342,U2243205)the Third Comprehensive Scientific Expedition to Xinjiang(No.2021XJKK1403)。
文摘Cotton is an important global cash crops that serve as the primary source of natural fiber for textiles.A thorough understand-ing of the long-term variations in cotton cultivation is vital for optimizing cotton cultivation management and promoting the sustainable development of the cotton industry.Xinjiang is the primary cotton-producing region in China.However,long-term data of cotton cultiv-ation areas with high spatial resolution are unavailable for Xinjiang,China.Therefore,this study aimed to identify and map an accurate 30-m cotton cultivation area dataset in Xinjiang from 2000 to 2020 by applying a Random Forest(RF)-based method that integrates Landsat and Moderate Resolution Imaging Spectroradiometer(MODIS)images,and validated the applicability and accuracy of dataset at a large spatial scale.Then,this study analyzed the spatiotemporal variations and influencing factors of cotton cultivation in the study period.The results showed that a high classification accuracy was achieved(overall accuracy>85%,F1>0.80),strongly agreeing with county-level agricultural statistical yearbook data(R2>0.72).Significant spatiotemporal variation in the cotton cultivation areas was found in Xinjiang,with a total increase of 1131.26 kha from 2000 to 2020.Notably,cotton cultivation area in southern Xinjiang expan-ded substantially,with that in Aksu increasing from 20.10%in 2000 to 28.17%in 2020,representing an expansion of 374.29 kha.In northern Xinjiang,the cotton areas in the Tacheng region also exhibited significant increased by almost ten percentage points in the same period.In contrast,cotton cultivation in eastern Xinjiang declined,decreasing from 2.22%in 2000 to merely 0.24%in 2020.Standard deviation ellipse analysis revealed a‘northeast-southwest’spatial distribution,with the centroid consistently located in Aksu and shifting 102.96 km over the 20-yr period.Pearson correlation analysis indicated that socioeconomic factors had a stronger influence on cotton cultivation than climatic factors,with effective irrigation area(r=0.963,P<0.05)and total agricultural machinery power(r=0.823)showing significant positive correlations,whereas climatic variables exhibiting weak associations(r<0.200).These results provide valuable scientific data for informed agricultural management,sustainable development,and policymaking.
文摘With the support by the National Natural Science Foundation of China and East China Normal University,the research team led by Prof.Tian Yang(田阳)at the Shanghai Key Laboratory of Green Chemistry and Chemical Processes,East China Normal University,developed a novel SERS Optophysiological probe for brain research,which was published in Angew Chem Int Ed(2019,58:5256—5260).
基金supported by a grant from General Research Fund of Hong Kong Research Grants Council,No.15218521a grant under the scheme of Collaborative Research with World-leading Research Groups in the Hong Kong Polytechnic University,No.G-SACF。
文摘Three-dimensional(3D)fetal ultrasound has been widely used in prenatal examinations.Realistic and real-time volumetric ultrasound volume rendering can enhance the effectiveness of diagnoses and assist obstetricians and pregnant mothers in communicating.However,this remains a challenging task because(1)there is a large amount of speckle noise in ultrasound images and(2)ultrasound images usually have low contrasts,making it difficult to distinguish different tissues and organs.However,traditional local-illumination-based methods do not achieve satisfactory results.This real-time requirement makes the task increasingly challenging.This study presents a novel real-time volume-rendering method equipped with a global illumination model for 3D fetal ultrasound visualization.This method can render direct illumination and indirect illumination separately by calculating single scattering and multiple scattering radiances,respectively.The indirect illumination effect was simulated using volumetric photon mapping.Calculating each photon’s brightness is proposed using a novel screen-space destiny estimation to avoid complicated storage structures and accelerate computation.This study proposes a high dynamic range approach to address the issue of fetal skin with a dynamic range exceeding that of the display device.Experiments show that our technology,compared to conventional methodologies,can generate realistic rendering results with far more depth information.
文摘冶金尘泥的转底炉处理工艺是目前钢铁行业采用的主要处置工艺,但在实际生产过程中经常出现还原焙烧不均匀的问题。利用微观扫描电子显微镜(scanning electron microscopy,SEM)分析结合宏观Maps统计分析,对冶金尘泥还原焙烧的不均匀性进行详细的可视化、数据化分析。研究结果表明,冶金尘泥在焙烧温度为1250℃、焙烧时间为15 min的条件下,熟球金属化率达到89.04%、脱锌率达到81.66%、抗压强度达到3.03 kN,熟球金属化率和脱锌率会随着焙烧温度提高和焙烧时间延长而进一步提高,但熟球抗压强度在焙烧时间过长时反而逐渐降低;熟球Maps统计分析表明,提高焙烧温度更有利于提高熟球外圈和下部的还原程度,而延长焙烧时间也更有利于提高熟球下部还原程度,但对熟球内部和外圈还原程度的提升作用比较相似;同时,提高焙烧温度也更有利于提升熟球下部的致密化程度,降低熟球上、下孔隙结构的不均匀性,进而显著提高熟球整体抗压强度;但焙烧时间过长会导致熟球中小孔隙融合为大孔隙,反而降低熟球抗压强度。此外,熟球中硅酸盐(渣相)和浮氏体(FexO)更容易破裂,而金属铁(Fe)可延缓裂纹蔓延,因而,适当提高熟球金属化率、降低硅酸盐(渣相)含量也有利于提高其抗压强度。基于Maps统计分析探究了冶金尘泥还原焙烧过程中物相及孔隙的变化规律,分析结果可以为转底炉工艺处理冶金尘泥的生产实践提供指导和建议。
