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基于油气运移最小能耗率原理的成藏期地层倾角窗口研究——以鄂尔多斯盆地上古生界致密气藏为例

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天然气地球科学 2024年第1期35卷 30-40页

作者：王任一许彪李江涛张登辉陈之龙浙江海洋大学石油化工与环境学院浙江舟山316022 中国石油青海油田分公司甘肃敦煌736202

对于成藏期地层倾角与油气聚集资源量之间关系的研究,国内外学者多局限在勘探实践案例统计分析及简化物理模拟实验研究方面,缺少对成藏期地层倾角与油气聚集资源量之间理论关系的研究。从油气运移最小能耗率原理出发,在理论上严格证明... 详细信息

对于成藏期地层倾角与油气聚集资源量之间关系的研究,国内外学者多局限在勘探实践案例统计分析及简化物理模拟实验研究方面,缺少对成藏期地层倾角与油气聚集资源量之间理论关系的研究。从油气运移最小能耗率原理出发,在理论上严格证明了油气运聚系统成藏期地层倾角窗口的存在。处于成藏期地层倾角窗口,油气运移有效驱动功率最弱,油气运聚系统能耗率最小,油气运聚效率最高,赋存发育油气资源量最大。回答了成藏期地层倾角到底是较大还是较小时有利于成藏的问题,揭开了侯连华等(2021)对国内已投入商业开发的44个天然气有效区带和49个石油有效区带的油气资源量,与其主成藏期平均地层倾角二者间呈一“开口向下抛物线”统计特征之谜。同时,利用该理论对鄂尔多斯盆地上古生界致密气藏地层倾角窗口演化变迁进行研究。上古生界高压致密古气藏由净浮力梯度、剩余压力梯度和排驱压力梯度三者之和为其油气运移有效驱动力,缓慢减小到由净浮力梯度与排驱压力梯度二者之和为其油气运移有效驱动力的现今低压致密气藏。与之相对应,高压致密古气藏由较小成藏期地层倾角窗口(0.2°~0.3°)缓慢变为现今低压致密气藏相对较大成藏期地层倾角窗口(0.35°~0.45°)。

关键词：油气运移最小能耗率原理成藏期地层倾角窗口鄂尔多斯盆地低压致密气藏气藏调整

基于并行异构图和序列注意力机制的中文实体关系抽取模型

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计算机应用 2024年第7期44卷 2018-2025页

作者：毛典辉李学博刘峻岭张登辉颜文婧食品安全大数据技术北京市重点实验室(北京工商大学) 北京100048 农产品质量安全追溯技术及应用国家工程实验室(北京工商大学) 北京100048

近年来,随着深度学习技术的快速发展,实体关系抽取在许多领域取得了显著的进展。然而,由于汉语具有复杂的句法结构和语义关系,面向中文的实体关系抽取任务中仍然存在着多项挑战。其中,中文文本中的重叠三元组问题是领域中的重要难题之... 详细信息

近年来,随着深度学习技术的快速发展,实体关系抽取在许多领域取得了显著的进展。然而,由于汉语具有复杂的句法结构和语义关系,面向中文的实体关系抽取任务中仍然存在着多项挑战。其中,中文文本中的重叠三元组问题是领域中的重要难题之一。针对中文文本中的重叠三元组问题,提出了一种混合神经网络实体关系联合抽取(HNNERJE)模型。HNNERJE模型以并行方式融合序列注意力机制和异构图注意力机制,并结合门控融合策略构建了深度集成框架。该模型不仅可以同时捕获中文文本的语序信息和实体关联信息,还能够自适应地调整主客体标记器的输出,从而有效解决重叠三元组问题。另外,通过引入对抗训练算法提高模型对未见样本和噪声的适应能力。运用SHAP(SHapley Additive exPlanations)方法对HNNERJE模型进行解释分析,基于模型的识别结果解析它在抽取实体和关系时所依据的关键特征。HNNERJE模型在NYT、WebNLG、CMeIE和DuIE数据集上的F1值分别达到了92.17%、93.42%、47.40%和67.98%。实验结果表明:HNNERJE模型可以将非结构化的文本数据转化为结构化的知识表示,有效提取其中蕴含的有价值信息。

关键词：实体关系抽取异构图注意力机制对抗训练 SHAP方法

Privacy‐preserving remote sensing images recognition based on limited visual cryptography

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1166-1177页

作者： denghui zhang Muhammad Shafiq Liguo Wang Gautam Srivastava Shoulin Yin Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhouChina Department of New Networks Peng Cheng LaboratoryShenzhenChina College of Information and Communications Engineering Dalian Minzu UniversityDalianChina Department of Mathematics and Computer Science Brandon UniversityBrandonManitobaCanada Research Centre for Interneural Computing China Medical UniversityTaichungTaiwanChina Department of Computer Science and Math Lebanese American UniversityBeirutLebanon College of Information and Communications Engineering Harbin Engineering UniversityHarbinChina

With the arrival of new data acquisition platforms derived from the Internet of Things(IoT),this paper goes beyond the understanding of traditional remote sensing technologies.Deep fusion of remote sensing and computer vision has hit the industrial world and makes it possible to apply Artificial intelligence to solve problems such as automatic extraction of information and image interpretation.However,due to the complex architecture of IoT and the lack of a unified security protection mechanism,devices in remote sensing are vulnerable to privacy leaks when sharing data.It is necessary to design a security scheme suitable for computation‐limited devices in IoT,since traditional encryption methods are based on computational complexity.Visual Cryptography(VC)is a threshold scheme for images that can be decoded directly by the human visual system when superimposing encrypted images.The stacking‐to‐see feature and simple Boolean decryption operation make VC an ideal solution for privacy‐preserving recognition for large‐scale remote sensing images in IoT.In this study,the secure and efficient transmission of high‐resolution remote sensing images by meaningful VC is achieved.By diffusing the error between the encryption block and the original block to adjacent blocks,the degradation of quality in recovery images is mitigated.By fine‐tuning the pre‐trained model from large‐scale datasets,we improve the recognition performance of small encryption datasets for remote sensing images.The experimental results show that the proposed lightweight privacy‐preserving recognition framework maintains high recognition performance while enhancing security.

关键词： activity recognition feature extraction image classification KNN privacy protection remote monitoring remote sensing

YOLO-Banana:An Effective Grading Method for Banana Appearance Quality

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Journal of Beijing Institute of Technology 2023年第3期32卷 363-373页

作者： Dianhui Mao Xuesen Wang Yiming Liu denghui zhang Jianwei Wu Junhua Chen School of Computer Beijing Technology and Business UniversityBeijing 100048China Research Center of Information Technology Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China Beijing PAIDE Science and Technology Development Co.Ltd. Beijing 100097China Institute of Standardization Theory and Strategy China National Institute of StandardizationBeijing 100088China

The increasing trend towards independent fruit packaging demands a high appearance quality of individually packed fruits.In this paper,we propose an improved YOLOv5-based model,YOLO-Banana,to effectively grade banana appearance quality based on the number of banana defect points.Due to the minor and dense defects on the surface of bananas,existing detection algorithms have poor detection results and high missing rates.To address this,we propose a densitybased spatial clustering of applications with noise(DBSCAN)and K-means fusion clustering method that utilizes refined anchor points to obtain better initial anchor values,thereby enhancing the network’s recognition accuracy.Moreover,the optimized progressive aggregated network(PANet)enables better multi-level feature fusion.Additionally,the non-maximum suppression function is replaced with a weighted non-maximum suppression(weighted NMS)function based on distance intersection over union(DIoU).Experimental results show that the model’s accuracy is improved by 2.3%compared to the original YOLOv5 network model,thereby effectively grading the banana appearance quality.

关键词： YOLOv5 banana appearance grading clustering algorithm weighted non-maximum suppression(weighted NMS) progressive aggregated network(PANet)

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音圈电机全局自适应非奇异快速终端滑模控制

轻工机械 2024年第2期42卷 44-49页

作者：张登辉盛晓超石英男沈丹峰西安工程大学机电工程学院陕西西安710048 西安工程大学西安市现代智能纺织装备重点实验室陕西西安710048

为了改善音圈电机驱动系统的动态性能,课题组提出了一种全局自适应非奇异快速终端滑模控制策略。在非奇异快速终端滑模控制器的基础上,引入全局滑态因子,改善系统的瞬态响应;同时将自适应控制和非奇异快速终端滑模控制相结合,利用自适... 详细信息

为了改善音圈电机驱动系统的动态性能,课题组提出了一种全局自适应非奇异快速终端滑模控制策略。在非奇异快速终端滑模控制器的基础上,引入全局滑态因子,改善系统的瞬态响应;同时将自适应控制和非奇异快速终端滑模控制相结合,利用自适应控制可以根据系统的实时状态和外部干扰自动调整参数的特点,来减小扰动、提高系统的鲁棒性和抗干扰性;将控制律中的符号函数改为一种边界层的饱和函数来削弱振动;通过李亚普诺夫稳定性理论证明所提出的控制器的稳定性;最后,将全局自适应非奇异快速终端滑模控制与比例积分微分控制(proportional integral derivative,PID)和滑模控制(sliding mode control,SMC)进行仿真对比。结果表明:与PID控制和滑模控制相比,所提出的全局自适应非奇异快速终端滑模控制提高了系统的动态响应速度和控制精度,有效改善了系统的动态性能。

关键词：音圈电机全局滑态因子自适应控制饱和函数滑模控制

Dynamic risk assessment of gas pipeline operation process by fusing visual and olfactory monitoring

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Journal of Safety Science and Resilience 2024年第2期5卷 156-166页

作者： Denglong Ma Weigao Mao Guangsen zhang Chaoyi Liu Yi Han Xiaoming zhang Hansheng Wang Kang Cen Wan Lu denghui Li Hanyue zhang School of Mechanical Engineering Xi'an Jiaotong UniversityXi'an 710049China Hanzhong Natural Gas Investinent Development Co.Ltd Hanzhong723011China Shaanxi Special Equipment Inspection and Testing Institute Xi'an710038China School of Civil Engineering and Architecture Southwest Petroleum UniversityChengdu610500China Sichuan Tianxin Gas Co.Ltd. Mianyang62100China Petro China Southwest Oil and Gas Field Company Gas Branch Chengdu610500China

With the rapid increase in urban gas consumption,the frequency of maintenance and repair of gas pipelines has escalated,leading to a rise in safety accidents during these processes.The traditional manual supervision model presents challenges such as inaccurate monitoring results,incomplete risk factor analysis,and a lack of quantitative risk assessment.This research focuses on developing a dynamic risk assessment technology for gas emergency repair operations by integrating the monitoring outcomes of artificial olfactory for gas leakage information and video object recognition for visual safety factor monitoring data.To quantitatively evaluate the risk of the operation process,a three-dimensional risk assessment model combining gas leakage with riskcorrelated sensitivity was established as well as a separate three-dimensional risk assessment model integrating visual risk factors with predictable risk disposition.Furthermore,a visual risk quantification expression mode based on the risk matrix-radar map method was introduced.Additionally,a risk quantification model based on the fusion of visual and olfactory results was formulated.The verification results of simulation scenarios based on field data indicate that the visual-olfactory fusion risk assessment method can more accurately reflect the dynamic risk level of the operation process compared to simple visual safety factor monitoring.The outcomes of this research can contribute to the identification of safety status and early warning of risks related to personnel,equipment,and environmental factors in emergency repair operations.Moreover,these results can be extended to other operational scenarios,such as oil and gas production stations and long-distance pipeline operations.

关键词： Gas pipelinemaintenance Dynamicriskassessment Visual-olfactoryfusion Risk matrix Risk quantification model

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考虑侧窗约束的模型预测静态规划末制导方法

宇航学报 2022年第10期43卷 1322-1332页

作者：权申明晁涛张登辉杨明哈尔滨工业大学航天学院控制与仿真中心哈尔滨150080 上海机电工程研究所上海201109 沈阳飞机设计研究所沈阳110031

针对红外导引头侧窗探测模式下,非对称视场约束造成末制导阶段目标易丢失的问题,提出一种考虑侧窗约束的模型预测静态规划末制导方法。首先,基于体视线坐标系建立三维相对运动模型,得到不依赖于“小攻角”假设的准确模型。在处理无过程... 详细信息

针对红外导引头侧窗探测模式下,非对称视场约束造成末制导阶段目标易丢失的问题,提出一种考虑侧窗约束的模型预测静态规划末制导方法。首先,基于体视线坐标系建立三维相对运动模型,得到不依赖于“小攻角”假设的准确模型。在处理无过程约束问题的模型预测静态规划方法基础上,引入松弛变量与虚拟控制量,设计出考虑侧窗视场约束的末制导算法。为了进一步降低末制导算法对初始猜测轨迹的依赖性,提高适应性与计算效率,提出逐步增加约束条件的计算策略。仿真结果表明,该方法在末制导过程中满足侧窗约束,相比于凸优化方法,优化变量减少,计算速度更快;相比于基于障碍李雅普诺夫函数的末制导律,能够满足侧窗约束,同时能适应不同的初始条件。

关键词：红外导引头模型预测静态规划体视线坐标系松弛变量

结合显著特征筛选和ViT的面部表情识别方法

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计算机工程与应用 2023年第22期59卷 136-143页

作者：封红旗黄伟铠张登辉常州大学计算机与人工智能学院江苏常州213100 浙江树人大学信息科技学院杭州310000

真实的人机交互场景中,人的动态行为(转头、行走等)以及不稳定的光源,会导致面部细节特征无法有效提取,从而降低面部表情识别的准确率。针对该问题,提出了一种结合显著特征筛选和视觉转化器(ViT)的优化模型。采用加权求和光照归一化方... 详细信息

真实的人机交互场景中,人的动态行为(转头、行走等)以及不稳定的光源,会导致面部细节特征无法有效提取,从而降低面部表情识别的准确率。针对该问题,提出了一种结合显著特征筛选和视觉转化器(ViT)的优化模型。采用加权求和光照归一化方法对原图进行亮度平衡,并利用卷积神经网络提取面部特征;使用显著特征筛选模块聚合面部局部-全局上下文信息;应用多层Transformer编码器来加强面部特征之间的关联性;最后采用Softmax函数对面部表情结果进行预测。实验结果表明,该网络模型在RAF-DB、FERPlus和AffectNet数据集上取得了良好的性能。

关键词：面部表情识别显著特征筛选视觉转化器多层Transformer编码器

A Virtual Machine Placement Strategy Based on Virtual Machine Selection and Integration

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Journal on Internet of Things 2021年第4期3卷 149-157页

作者： denghui zhang Guocai Yin College of Information Science Zhejiang shuren universityHangzhou310015China School of Beihua Institute of Aerospace Technology University of LangfangLangfang065201China

Cloud data centers face the largest energy consumption.In order to save energy consumption in cloud data centers,cloud service providers adopt a virtual machine migration strategy.In this paper,we propose an efficient virtual machine placement strategy(VMP-SI)based on virtual machine selection and integration.Our proposed VMP-SI strategy divides the migration process into three phases:physical host state detection,virtual machine selection and virtual machine placement.The local regression robust(LRR)algorithm and minimum migration time(MMT)policy are individual used in the first and section phase,respectively.Then we design a virtual machine migration strategy that integrates the process of virtual machine selection and placement,which can ensure a satisfactory utilization efficiency of the hardware resources of the active physical host.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.

关键词： Cloud data centers virtual machine selection virtual machine placement migration energy consumption