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油田井工厂分布式电源孤岛分析

上海电气技术 2024年第1期17卷 16-24页

作者：冯海林胜利石油管理局有限公司新能源开发中心山东东营257000

防孤岛保护是油田井工厂多能互补系统的关键技术,由此对油田井工厂分布式电源孤岛进行分析。建立由光伏发电、网电、风力发电、燃气轮机等设备组成的油田井工厂分布式电源孤岛仿真模型,进行不含储能电池的分布式电源孤岛瞬时有功功率过... 详细信息

防孤岛保护是油田井工厂多能互补系统的关键技术,由此对油田井工厂分布式电源孤岛进行分析。建立由光伏发电、网电、风力发电、燃气轮机等设备组成的油田井工厂分布式电源孤岛仿真模型,进行不含储能电池的分布式电源孤岛瞬时有功功率过剩仿真分析,检验采用电压相位偏移与电压频率偏移综合进行孤岛检测判断的有效性。

关键词：油田分布式电源孤岛分析

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TTLD-YOLOv7:非结构化环境下茶树病害的检测算法

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茶叶科学 2024年第3期44卷 453-468页

作者：俞淑燕杜晓晨冯海林李颜娥浙江农林大学数学与计算机科学学院浙江杭州311300

茶树病害对茶树种植业和相关行业的影响极为严重。在动态而复杂的茶园环境中检测疾病的传统方法效率低下,检测效果不尽人意。本研究提出一种基于YOLOv7-tiny的模型,增强了茶树病害的细微检测能力。通过整合CoordConv和ECA信道关注机制,... 详细信息

茶树病害对茶树种植业和相关行业的影响极为严重。在动态而复杂的茶园环境中检测疾病的传统方法效率低下,检测效果不尽人意。本研究提出一种基于YOLOv7-tiny的模型,增强了茶树病害的细微检测能力。通过整合CoordConv和ECA信道关注机制,本模型在卷积特征图中实现了更高的空间识别能力,并降低了背景噪声对特征识别的影响。进一步的改进包括采用归一化瓦瑟斯坦距离度量和去耦头,以提高对小病斑的检测能力。使用K-means算法根据茶树病斑的特殊性生成了新的锚框,提高了模型的精确性和通用性。对比分析表明,该模型优于现有模型FasterR-CNN、 SSD、 YOLOv5s、 YOLO-Tea、 YOLOv7-tiny和YOLOv7,平均精确度提高5.39个百分点,达到了93%。改进后的模型可应用于茶树病害监测。

关键词：茶树病害 YOLOv7-tiny 自然环境目标检测

肝癌组织中GPSM2、TGF-β1蛋白表达水平及临床意义

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实用癌症杂志 2024年第3期39卷 406-410页

作者：霍亮骆杨冯海林河南省信阳市中心医院 464000

目的探讨肝癌组织G蛋白信号调节蛋白(GPSM)2、转化生长因子1(TGF-β1)蛋白表达与临床病理参数及预后的关系。方法选取原发性肝癌患者80例,取手术切除的肝癌组织和癌旁正常组织。采用免疫组织化学染色法检测GPSM2、TGF-β1在癌组织和... 详细信息

目的探讨肝癌组织G蛋白信号调节蛋白(GPSM)2、转化生长因子1(TGF-β1)蛋白表达与临床病理参数及预后的关系。方法选取原发性肝癌患者80例,取手术切除的肝癌组织和癌旁正常组织。采用免疫组织化学染色法检测GPSM2、TGF-β1在癌组织和癌旁正常组织中的表达差异,分析癌组织中GPSM2、TGF-β1表达水平与临床病理参数及预后的关系。结果肝癌组织中GPSM2、TGF-β1高表达率分别为71.25%、82.50%,高于癌旁正常组织的18.75%、13.75%(P<0.05)。GPSM2在分化程度低的肝癌组织中高表达率较高(P<0.05),TGF-β1在分化程度低、有血管转移的肝癌组织中高表达率较高(P<0.05)。生存曲线显示,GPSM2、TGF-β1低表达患者的累积生存率(77.27%、85.71%)高于高表达患者(47.37%、48.48%),差异具有统计学意义(P<0.05)。结论 GPSM2、TGF-β1在肝癌组织中高表达率较高,其表达水平与分化程度密切相关,GPSM2、TGF-β1高表达患者预后较差。

关键词：原发性肝癌 G蛋白信号调节蛋白2 转化生长因子1 临床病理参数预后

An Imperfect Grouping Maintenance Strategy for Multi-Component Systems Using the Survival Signature

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Journal of Systems Science and Information 2022年第5期10卷 500-517页

作者： Jiaojiao GUO hailin feng Zhen WANG School of Computing Xijing UniversityXi'an 710123China School of Mathematics and Statistics Xidian UniversityXi'an 710071China

This paper presents an imperfect maintenance strategy for the multi-component *** proposed maintenance strategy takes into account two types of maintenance actions,namely preventive maintenance(PM)and corrective maintenance(CM).The imperfect effect of PM is modeled on the basis of the hybrid hazard rate ***,a new structure importance measure based on the survival signature is *** this new importance measure method,an adjustment function is designed to update the PM maintenance *** CM actions,a decision rule relying on the criticality level of components is *** order to judge the criticality level of components,a novel structure updating method based on the survival signature is ***,a maintenance model considering economic dependence among components is developed.A 10-component system is finally introduced to illustrate the use and advantages of the proposed maintenance strategy.

关键词： hybrid hazard rate model survival signature grouping maintenance importance measure structure updating method

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茭白秆水解制备高价值呋喃平台化合物研究

浙江农业学报 2024年第4期36卷 870-880页

作者：郭威良吴剑张兴一龙吴可荆谢佳家冯海林浙江农林大学数学与计算机科学学院浙江杭州311300 浙江臻泰能源科技有限公司浙江丽水321400 四川大学新能源与低碳技术研究院四川成都610065 国网浙江省电力有限公司双创中心浙江杭州310051

生物质转化为高价值呋喃平台化合物是生物质资源利用的重要方式。以工业副产物偏钛酸作为固体酸催化剂,将茭白秆转化为5-羟甲基糠醛(HMF)和糠醛,研究物理活化、溶剂体系等对茭白秆水解性能的影响,并优化反应工艺条件。结果表明,茭白秆... 详细信息

生物质转化为高价值呋喃平台化合物是生物质资源利用的重要方式。以工业副产物偏钛酸作为固体酸催化剂,将茭白秆转化为5-羟甲基糠醛(HMF)和糠醛,研究物理活化、溶剂体系等对茭白秆水解性能的影响,并优化反应工艺条件。结果表明,茭白秆具有更低的木质素含量和纤维素晶型结构,比茭白叶更容易被物理活化。在200℃、30 min的反应条件下,球磨活化的茭白秆获得了最高的HMF和糠醛收率,分别为11.66%和7.30%。反应动力学分析表明,偏钛酸催化球磨茭白秆转化的活化能低,相较于文献报道的其他木质纤维素生物质,球磨茭白秆的高值化转化具有优势。

关键词：茭白秆 5-羟甲基糠醛物理活化两相体系偏钛酸

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Reliability analysis for WSN based on a modular k-out-of-n system

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Journal of Systems Engineering and Electronics 2017年第2期28卷 407-412页

作者： hailin feng Jieyu Dong School of Mathematics and Statistics Xidian University Xi’an 710126 China

A hierarchical clustering model for a wireless sensor network (WSN) which takes into account the node fault and the balance of energy consumption is built. With the sensing and transmission as the main tasks of the WSN, its working mode is converted to a modular k-out-of-n system whose each modular is also a k-out-of-n structure. By using the theory of signature and its extending, the reliability of the WSN is computed. Finally, the reliability of WSN changing with the number of nodes, coverage requirements and node lifetimes is given by the numerical analysis. The proposed reliability analysis model is suitable for a large-scale WSN. © 2017 Beijing Institute of Aerospace Information.

关键词： Energy utilization Reliability Reliability theory Sensor nodes Wireless sensor networks

Monte Carlo Likelihood Estimation of Mixed-Effects State Space Models with Application to HIV Dynamics

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Journal of Systems Science & Complexity 2016年第4期29卷 1160-1176页

作者： ZHOU Jie TANG Aiping feng hailin Department of Statistics Xidian University

The statistical inference for generalized mixed-effects state space models(MESSM) are investigated when the random effects are unknown. Two filtering algorithms are designed both of which are based on mixture Kalman filter. These algorithms are particularly useful when the longitudinal measurements are sparse. The authors also propose a globally convergent algorithm for parameter estimation of MESSM which can be used to locate the initial value of parameters for local while more efficient algorithms. Simulation examples are carried out which validate the efficacy of the proposed approaches. A data set from the clinical trial is investigated and a smaller mean square error is achieved compared to the existing results in literatures.

关键词：混合效果混合 Kalman 过滤器州的评价说空间模型

Study on the fast elimination of smoke particle based on electro-acoustic coupling agglomeration technology

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Particuology 2024年第5期88卷 1-10页

作者： Jie feng Mingfeng Lu Kaige Wang Kun Luo Mingzhou Yu Guangxue Zhang Jiangrong Xu Shuping Pan hailin Gu The Institute for Energy Engineering China Jiliang UniversityHangzhou310018China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou310027China Qingshanhu Energy Research Center Zhejiang UniversityHangzhou310017China Zhejiang Ecological Environment Monitoring Center Hangzhou310012China

Fire smoke,which consists large amounts of fine particles,is considered as the fatal factor in *** this study,a fast smoke particle elimination method based on electro-acoustic coupling agglomeration technology is ***,the experimental results show that the electro-acoustic coupling agglomeration has higher smoke elimination efficiency compared to *** smoke transmission is much less than 80%after 30s of single acoustic or electric field action,while the coupled field reaches 90%.Then,the effects of acoustic frequency,sound pressure level and voltage on the smoke elimination characteristics are *** is found that the optimal acoustic frequency is *** as the sound pressure level and voltage increase,the elimination efficiency first increases and then tends to stabilize,the critical values of the sound pressure level and voltage are 135 dB and *** indicates that there is an optimal combination of the three ***,through the theoretical analysis of particle movement and the micro-morphology of agglomerates,the particle agglomeration mechanism under the electro-acoustic coupling is *** study provides a new idea for the fast elimination of fire smoke particle.

关键词： Smoke particle Agglomeration Electro-acoustic coupling Smoke elimination

Tree species classification using deep learning and RGB optical images obtained by an unmanned aerial vehicle

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Journal of Forestry Research 2021年第5期32卷 1879-1888页

作者： Chen Zhang Kai Xia hailin feng Yinhui Yang Xiaochen Du School of Information Engineering Zhejiang A&F UniversityHangzhou 311300People’s Republic of China Key Laboratory of State Forestry and Grassland Administration on Forestry Sensing Technology and Intelligent Equipment Hangzhou 311300People’s Republic of China Zhejiang Provincial Key Laboratory of Forestry Intelligent Monitoring and Information Technology Hangzhou 311300People’s Republic of China

The diversity of tree species and the complexity of land use in cities create challenging issues for tree species *** combination of deep learning methods and RGB optical images obtained by unmanned aerial vehicles(UAVs) provides a new research direction for urban tree species *** proposed an RGB optical image dataset with 10 urban tree species,termed TCC10,which is a benchmark for tree canopy classification(TCC).TCC10 dataset contains two types of data:tree canopy images with simple backgrounds and those with complex *** objective was to examine the possibility of using deep learning methods(AlexNet,VGG-16,and ResNet-50) for individual tree species *** results of convolutional neural networks(CNNs) were compared with those of K-nearest neighbor(KNN) and BP neural *** results demonstrated:(1) ResNet-50 achieved an overall accuracy(OA) of 92.6% and a kappa coefficient of 0.91 for tree species classification on TCC10 and outperformed AlexNet and VGG-16.(2) The classification accuracy of KNN and BP neural network was less than70%,while the accuracy of CNNs was relatively higher.(3)The classification accuracy of tree canopy images with complex backgrounds was lower than that for images with simple *** the deciduous tree species in TCC10,the classification accuracy of ResNet-50 was higher in summer than that in ***,the deep learning is effective for urban tree species classification using RGB optical images.

关键词： Urban forest Unmanned aerial vehicle(UAV) Convolutional neural network Tree species classification RGB optical images