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China Ocean Engineering 2024年第2期38卷 198-209页

作者： WU Qi-bing CAI Bao-ping FAN Hong-yan WANG Guan-nan RAO Xi ge weifeng SHAO Xiao-yan LIU Yong-hong CNOOC Safety Technology Services Co. Ltd.Tianjin 300456China College of Mechanical and Electronic Engineering China University of PetroleumQingdao 266580China CNOOC EnerTech Safety&Environmental Protection BranchTianjin 300456China

Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health ***,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating *** complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL *** RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is *** performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data *** on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance *** example of a subsea tree system is given to verify the effectiveness of the proposed method.

关键词： remaining useful life Wiener process dynamic Bayesian networks maintenance subsea Christmas tree system

Strain-mediated magnetoelectric control of tunneling magnetoresistance in magnetic tunneling junction/ferroelectric hybrid structures

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Chinese Physics B 2022年第9期31卷 532-539页

作者： Wenyu Huang Cangmin Wang Yichao Liu Shaoting Wang weifeng ge Huaili Qiu Yuanjun Yang Ting Zhang Hui Zhang Chen Gao School of Physics Hefei University of TechnologyHefei 230009China School of Microelectronics Hefei University of TechnologyHefei 230009China Hefei National Laboratory for Physical Sciences at Microscale(HFNL) University of Science and Technology of ChinaHefei 230026China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China

Because of the wide selectivity of ferromagnetic and ferroelectric(FE)components,electric-field(E-field)control of magnetism via strain mediation can be easily realized through composite multiferroic ***,an MgO-based magnetic tunnel junction(MTJ)is chosen rationally as the ferromagnetic constitution and a high-activity(001)-Pb(Mg_(1/3)Nb_(2/3))_(0.7)Ti_(0.3)O_(3)(PMN-0.3PT)single crystal is selected as the FE component to create a multiferroic MTJ/FE hybrid *** shape of tunneling magnetoresistance(TMR)versus in situ E-fields imprints the butterfly loop of the piezo-strain of the FE without magnetic-field *** E-field-controlled change in the TMR ratio is up to-0.27%without magnetic-field ***,when a typical magnetic field(~±10 Oe)is applied along the minor axis of the MTJ,the butterfly loop is changed significantly by the E-fields relative to that without magnetic-field *** suggests that the E-field-controlled junction resistance is spin-dependent and correlated with magnetization switching in the free layer of the *** addition,based on such a multiferroic heterostructure,a strain-gauge factor up to approximately 40 is achieved,which decreases further with a sign change from positive to negative with increasing magnetic *** multiferroic hybrid structure is a promising avenue to control TMR through E-fields in low-power-consumption spintronic and straintronic devices at room temperature.

关键词： tunneling magnetoresistance magneti tunnel junction(MTJ) multiferroic heterostructure magnetoelectric coupling

数字孪生驱动的热交换器降阶建模及智能感知方法研究

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化工学报 2023年第10期74卷 4218-4228页

作者：籍帅航王金江蔡睿孙雪皓葛伟凤中国石油大学(北京)人工智能学院北京102249 中国石油大学(北京)安全与海洋工程学院北京102249 应急管理部油气生产安全与应急技术重点实验室北京102249 中海油安全技术服务有限公司天津300456

管壳式热交换器是能源系统中的重要组成部分,长时间的运行容易在导热管内造成结垢故障,导致热交换器传热效率下降、流动阻力增加、耗能增加、系统压力下降等问题。结垢故障往往隐藏在设备内部,通过运行数据监测或者仿真手段往往不足以... 详细信息

管壳式热交换器是能源系统中的重要组成部分,长时间的运行容易在导热管内造成结垢故障,导致热交换器传热效率下降、流动阻力增加、耗能增加、系统压力下降等问题。结垢故障往往隐藏在设备内部,通过运行数据监测或者仿真手段往往不足以感知和预测多工况下的设备状态,数字化的热交换器状态监测技术为解决问题提供了新思路,但存在数字孪生体难以构建、降阶效果不理想、结垢数据难以获取等问题。为了能够建立数字孪生驱动的热交换器高保真降阶模型,提出了一种基于本征正交分解的径向基自适应模型降阶方法。基于物理信息的自适应采样算法采集更有效的样本数据,利用POD-RBF建立高保真降阶模型,开展热交换器的结垢故障的仿真实验,通过BP神经网络进行热交换器的结垢感知和预测。实验结果表明所建立的自适应采样降阶模型与不使用采样的降阶模型相比求解效率提高了1倍,与全阶模型的误差在4%左右,通过降阶模型快速生成更符合物理机理的结垢数据,预测误差保持在0.0554 mm左右,能有效地对换热器的结垢进行感知和预测。

关键词：热交换器数字孪生模型降阶状态监测故障诊断

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基于权重分析的海上井控设备风险分级方法

石油矿场机械 2017年第5期46卷 80-83页

作者：葛伟凤中海油能源发展股份有限公司安全环保分公司天津300451

针对目前海上老旧井控设备多、报废标准不足的问题,基于权重分析,综合考虑井控设备资料完整性、现场管理措施、井控设备运行状态3项指标,评定井控设备风险等级。风险评级结果表明:J平台环形防喷器、钻井四通风险等级为I级,闸板防喷器风... 详细信息

针对目前海上老旧井控设备多、报废标准不足的问题,基于权重分析,综合考虑井控设备资料完整性、现场管理措施、井控设备运行状态3项指标,评定井控设备风险等级。风险评级结果表明:J平台环形防喷器、钻井四通风险等级为I级,闸板防喷器风险等级为II级;井控设备整体风险较低,但个别设备有一些功能上的问题,需要及时整改。该风险分级方法有助于提高井控设备的可靠性,进一步提升海上井控管理水平。

关键词：井控设备权重分析专家打分法风险分级

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基于深度学习的检修作业过程风险智能预警

中国安全科学学报 2023年第10期33卷 16-22页

作者：王金江关鹏婷陈卓葛伟凤鞠茜中国石油大学(北京)安全与海洋工程学院北京102249 中海油安全技术服务有限公司天津300452 中海油能源发展股份有限公司安全环保分公司天津300452 中国石油西南油气田公司华油公司重庆401120

为提高炼化企业检维修作业过程的安全性,利用目标检测技术,构建基于深度学习的智能风险识别模型;首先,结合贝叶斯网络(BN)及模糊集理论,建立动态风险评估模型;其次,采用分级动态预警方法,实现检修作业过程风险要素的智能监控预警;然后,... 详细信息

为提高炼化企业检维修作业过程的安全性,利用目标检测技术,构建基于深度学习的智能风险识别模型;首先,结合贝叶斯网络(BN)及模糊集理论,建立动态风险评估模型;其次,采用分级动态预警方法,实现检修作业过程风险要素的智能监控预警;然后,以压缩机检修作业过程为例,采用失效模式和影响分析(FMEA)与作业条件危险性分析方法,辨识作业过程风险,再利用基于深度学习的风险智能识别模型,监控现场作业过程并识别风险;最后,采用BN和模糊集理论相结合的方法,评估作业过程中的动态风险,并采用分级预警的方法智能预警作业过程风险。结果表明:该方法可以有效识别压缩机检修作业过程中的风险因素,识别准确率为93%,在此基础上进行动态风险评估,当观测到事件概率发生变化,且超出相应预警阈值时,依据风险等级进行报警,实现风险要素的智能监控。

关键词：深度学习检修作业过程风险智能预警贝叶斯网络(BN)

DecMamba:Mamba Utilizing Series Decomposition for Multivariate Time Series Forecasting

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Computers, Materials & Continua 2025年第1期82卷 1049-1068页

作者： Jianxin Feng Jianhao Zhang ge Cao Zhiguo Liu Yuanming Ding Communication and Network Key Laboratory Dalian UniversityDalian116622China

Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy *** decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time ***,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between *** problems make it difficult to analyze the intricate temporal variations of real-world time *** this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between *** backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend *** with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.

关键词： Data prediction time series Mamba series decomposition

叠合概率法在碳酸盐岩储层评价中的应用——以辽河坳陷西部凹陷高升地区沙四段为例

维普期刊数据库评论

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中国石油勘探 2019年第3期24卷 361-368页

作者：李阳代宗仰黄蕾周晓龙葛伟峰单俊峰刘宁西南石油大学地球科学与技术学院中国石化中原油田分公司物探研究院中国石油辽河油田公司勘探开发研究院

辽河坳陷西部凹陷高升地区沙四段碳酸盐岩储层的形成和发育主要受沉积相、埋藏溶蚀作用及构造破裂作用的共同控制,储层在微观和宏观上具有强烈的非均质性,储层影响因素较多且孔渗关系复杂。为了避免仅靠某一单因素、少数有限的钻井资料... 详细信息

辽河坳陷西部凹陷高升地区沙四段碳酸盐岩储层的形成和发育主要受沉积相、埋藏溶蚀作用及构造破裂作用的共同控制,储层在微观和宏观上具有强烈的非均质性,储层影响因素较多且孔渗关系复杂。为了避免仅靠某一单因素、少数有限的钻井资料及物性测试资料进行区域性碳酸盐岩储层评价容易出现偏差的问题,运用特征选择中的ReliefF算法对碳酸盐岩厚度、粒屑灰(云)岩厚度、孔隙度、渗透率、脆性指数及裂缝密度6项参数进行权重分析,并确定各参数权重值,然后使用叠合概率法将不同特征平面图加权叠合形成一张多因素概率图,通过划分概率区间最终形成储层评价图。同时综合考虑西部凹陷高升地区的构造特征及沉积相特征,对研究区沙四段碳酸盐岩储层进行研究评价,评价结果与研究区已勘探油气分布具有较好的一致性,并预测出有利勘探区带。

关键词：辽河坳陷西部凹陷沙四段碳酸盐岩储层权重分析叠合概率法

Early identification of stroke through deep learning with multi-modal human speech and movement data

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Neural Regeneration Research 2025年第1期20卷 234-241页

作者： Zijun Ou Haitao Wang Bin Zhang Haobang Liang Bei Hu Longlong Ren Yanjuan Liu Yuhu Zhang Chengbo Dai Hejun Wu weifeng Li Xin Li School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Department of Neurology Guangdong Neuroscience InstituteGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Emergency Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina

Early identification and treatment of stroke can greatly improve patient outcomes and quality of *** clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized *** this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute *** collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the *** compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and *** found that the findings of our deep learning model had a higher clinical value compared with the other ***,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech *** results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

关键词： artificial intelligence deep learning diagnosis early detection FAST screening stroke

Bidirectional regulation of the brain-gut-microbiota axis following traumatic brain injury

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Neural Regeneration Research 2025年第8期20卷 2153-2168页

作者： Xinyu You Lin Niu Jiafeng Fu Shining ge Jiangwei Shi Yanjun Zhang Pengwei Zhuang National Key Laboratory of Chinese Medicine Modernization Tianjin University of Traditional Chinese MedicineTianjinChina Haihe Laboratory of Modern Chinese Medicine Tianjin University of Traditional Chinese MedicineTianjinChina First Teaching Hospital of Tianjin University of Traditional Chinese Medicine TianjinChina National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion TianjinChina

Traumatic brain injury is a prevalent disorder of the central nervous *** addition to primary brain parenchymal damage,the enduring biological consequences of traumatic brain injury pose long-term risks for patients with traumatic brain injury;however,the underlying pathogenesis remains unclear,and effective intervention methods are *** dysfunction is a significant consequence of traumatic brain *** the most densely innervated peripheral tissue in the body,the gut possesses multiple pathways for the establishment of a bidirectional“brain-gut axis”with the central nervous *** gut harbors a vast microbial community,and alterations of the gut niche contribute to the progression of traumatic brain injury and its unfavorable prognosis through neuronal,hormonal,and immune pathways.A comprehensive understanding of microbiota-mediated peripheral neuroimmunomodulation mechanisms is needed to enhance treatment strategies for traumatic brain injury and its associated *** comprehensively reviewed alterations in the gut microecological environment following traumatic brain injury,with a specific focus on the complex biological processes of peripheral nerves,immunity,and microbes triggered by traumatic brain injury,encompassing autonomic dysfunction,neuroendocrine disturbances,peripheral immunosuppression,increased intestinal barrier permeability,compromised responses of sensory nerves to microorganisms,and potential effector nuclei in the central nervous system influenced by gut ***,we reviewed the mechanisms underlying secondary biological injury and the dynamic pathological responses that occur following injury to enhance our current understanding of how peripheral pathways impact the outcome of patients with traumatic brain *** review aimed to propose a conceptual model for future risk assessment of central nervous system-related diseases while elucidating novel insights into the bidirectional effec

关键词： traumatic brain injury brain-gut-microbiome axis gut microbiota neuroimmune immunosuppression host defense vagal afferents bacterial infection dorsal root ganglia nociception neural circuitry

Equivalent combined cycle modelling for three-heat-reservoir thermal Brownian heat pump with heat-transfer effect and its optimal performance

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Science China Technological Sciences 2025年

作者： Lingen CHEN Congzheng QI Yanlin ge Huijun FENG Hubei Provincial Key Laboratory of Chemical Equipment Intensification and Intrinsic Safety Wuhan Institute of Technology Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment Wuhan Institute of Technology Institute of Thermal Science and Power Engineering Wuhan Institute of Technology School of Mechanical & Electrical Engineering Wuhan Institute of Technology

Because of the important role of the absorption heat pump in low-grade thermal energy utilization, this paper extends it to micro domain and performs a finite-time thermodynamic modelling for a three-heat-reservoir (THR) thermal Brownian heat pump with heat transfer effect by using an equivalent combined cycle method, which was applied for macro endoreversible THR heat pumps. The working principle and energy transformation rule are studied, and the coefficient of performance (COP) and heating load are derived. With a fixed overall thermal conductance of three heat exchangers, the maximal heating load is determined by optimizing thermal conductance distributions among three heat exchangers and barrier height, and the optimal working temperatures are also obtained. The impact of external heat transfer is elucidated to show the difference between this model and a non-equilibrium thermodynamic one. Results indicate that external heat transfer determines the energy transformation directly, and performance characteristics are closer to reality when external heat transfer is considered. The heating load has a maximal value about thermal conductance allocation ratios. About half the overall heat exchanger inventory needs to be assigned to the heat exchanger of the heating space for maximal heating load. When the cycle is with only heat transfer effect, the net particle numbers are zero, and the cycle fails to pump heat. The research results are expected to offer an idea for thermodynamic optimization and design of micro THR thermal Brownian heat pump devices.

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