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A Novel MDFA-MKECA Method With Application to Industrial Batch Process Monitoring

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1446-1454页

作者： yinghua yang Xiang Shi Xiaozhi Liu Hongru Li College of Information Science and Engineering Northeastern UniversityShenyang 110819China

For the complex batch process with characteristics of unequal batch data length,a novel data-driven batch process monitoring method is proposed based on mixed data features analysis and multi-way kernel entropy component analysis(MDFA-MKECA)in this *** the mechanistic knowledge,different mixed data features of each batch including statistical and thermodynamics entropy features,are extracted to finish data *** that,MKECA is applied to reduce data dimensionality and finally establish a monitoring *** proposed method is applied to a reheating furnace industry process,and the experimental results demonstrate that the MDFA-MKECA method can reduce the calculated amount and effectively provide on-line monitoring of the batch process.

关键词： MDFA MKECA process monitoring reheating furnace statistical features thermodynamics entropy feature

氨氯地平过量致多器官功能障碍综合征1例分析

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中国药物警戒 2024年第2期21卷 204-207页

作者：郭清华彭笑笑朱萍刘西霖杨颖华陈志海首都医科大学大兴教学医院急诊科北京102600 首都医科大学附属北京地坛医院感染性疾病临床中心北京100102

目的强调独居老人氨氯地平的规范化使用,提高临床医生对药品不良反应或过量的认识。方法分析1例独居老人氨氯地平过量引起多器官功能障碍综合征(MODS)的临床资料,查阅国内外相关案例报道,总结临床特征、治疗方法和预后。结果氨氯地... 详细信息

目的强调独居老人氨氯地平的规范化使用,提高临床医生对药品不良反应或过量的认识。方法分析1例独居老人氨氯地平过量引起多器官功能障碍综合征(MODS)的临床资料,查阅国内外相关案例报道,总结临床特征、治疗方法和预后。结果氨氯地平过量可能会引起MODS,主要表现为心率减慢、严重的心肌抑制、高乳酸血症、难治性休克、肝肾功能不全。治疗方法以停用责任药物,脏器功能支持为主,包括呼吸支持、循环支持、肾脏替代治疗等。结论氨氯地平在特殊人群中存在MODS风险,对于不明原因MODS患者要警惕药品不良反应或过量中毒的风险,尽早识别并采取相应的治疗措施可改善预后。

关键词：氨氯地平中毒多器官功能障碍综合征药品不良反应血浆置换体外膜氧合过量

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焦作矿区煤系含气系统基本要素研究

能源与环保 2024年第6期46卷 116-125页

作者：徐影宛宗瑞卢玉杰杨樱花河南豫中地质勘查工程有限公司河南郑州450016 河南省能源钻井工程技术研究中心河南郑州450016 河南省地质研究院河南郑州450016 河南省自然资源科技创新中心(非常规天然气开发研究) 河南郑州450016

煤系气是重要的天然气资源,明确煤系含气系统的基本要素对于煤系气勘探开发至关重要。以焦作矿区石炭—二叠系海陆过渡相含煤岩系为例,基于区内煤系气勘探资料,从生、储、盖及上覆岩层4方面,探讨了研究区煤系含气系统的基本要素及其特... 详细信息

煤系气是重要的天然气资源,明确煤系含气系统的基本要素对于煤系气勘探开发至关重要。以焦作矿区石炭—二叠系海陆过渡相含煤岩系为例,基于区内煤系气勘探资料,从生、储、盖及上覆岩层4方面,探讨了研究区煤系含气系统的基本要素及其特征。研究表明,焦作矿区石炭—二叠系烃源岩以煤和暗色泥岩为主,马厂1井太原组、山西组和下石盒子组泥岩的TOC含量分别为1.68%、0.905%和4.35%,二1煤顶底板泥岩的S_(1)+S_(2)含量分别为0.452、0.576 mg/g,达到了较好—好烃源岩级别;从镜质组含量、类型指数等方面,判定烃源岩为Ⅲ型有机质类型;烃源岩热演化程度整体处于成熟—过成熟阶段,处于主生气期。储集层以煤为主,其次为泥岩和部分砂岩,其含气量分为11.54~23.16、1~3、0.18~1.47 m^(3)/t,储集层矿物组成主要为石英和黏土矿物,主要发育植物胞腔孔和气孔,孔隙度介于0.80%~11.08%,渗透率介于0.004×10^(-3)~0.012×10^(-3)μm^(2),具有低孔低渗的物性特征;太原组、山西组和下石盒子组泥岩的饱和气突破压力为5.88~9.80 MPa,饱和煤油突破压力为13.72~14.11 MPa,具有很好的封闭能力。研究认为,焦作矿区石炭—二叠系煤系含气系统基本要素的组合关系为,烃源岩发育于太原组至下石盒子组,优势储集层为山西组,上石盒子组为区域盖层,第四系及新近系为研究区上覆岩层。

关键词：煤系含气系统烃源岩储集层盖层上覆岩层基本要素

Fault Diagnosis Based On One-Dimensional Deep Convolution Neural Network

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Fault Diagnosis Based On One-Dimensional Deep Convolution Ne...

Research of Quality Prediction Based on Extreme Learning Machine

第32届中国控制与决策会议

作者： yang yinghua Li Doliang Liu Xiaozhi College of Information Science and Engineering Northeastern University

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

Aiming at the problems of low accuracy and poor generalization ability of bearing fault diagnosis based on machine learning（ML）, this paper proposes the method of deep learning（DL） to solve the above problems. Combined with the bearing signal one-dimensional characteristics, this paper proposes a one-dimension deep convolutional neural network（1 D-DCNN）. First of all, the original bearing vibration signal is directly input the 1 D-DCNN frame structure, then 1 D-DCNN frame structure is used to automatic feature extraction. Next, we use softmax regression to classified fault samples and normal samples, the confusion matrix shows that the accuracy of the 1 D-DCNN model for fault diagnosis. Finally, T-SNE algorithm is used to reduce the dimension of extracted features and visualize data features, which proves that the 1 D-DCNN model has a good feature extraction ability. We use bearing data sets from Case Western Reserve University（CWRU） to verify the model of 1 D-DCNN. According to the result, we can see that the 1 D-DCNN frame structure not only effectively extracts and diagnoses the original signal, but also has high fault identification accuracy. It shows the advantages of the 1 D-DCNN model in extracting data features and fault diagnosis. The model of 1 D-DCNN is better than the mainstream fault diagnosis method of support vector machine（SVM） and probabilistic neural networks（PNN）.

关键词： ML Fault diagnosis Deep learning 1D-DCNN T-SNE

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Research of Quality Prediction Based on Extreme Learning Mac...

Fault Diagnosis Based on Sparse Semi-supervised GAN Model

第32届中国控制与决策会议

作者： yang yinghua Song Zeping Liu Xiaozhi College of Information Science and Engineering Northeastern University

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

Aiming at the problems of poor stability and generalization performance in quality prediction based on extreme learning machine（ELM）,this paper presents an improved method of *** is named as the DAE-P-ELM algorithm,which integrates denoising autoencoder（DAE） with principal component analysis（PCA）.First,in order to reflect the characteristics and intrinsic relationship of the modeling data as much as possible,DAE technology is introduced to reconstruct the input ***,output weight sufficiently containing the input data information is obtained,which is used as input weight of the ***,the PCA technology is used to reduce the dimension of the hidden layer output matrix to avoid the multicollinear problem in calculation of output weight matrix,which solves the problem of poor stability of the model due to too many hidden layer ***,the method is applied to the Tennessee Eastman（TE） *** simulation results show that the content of components G and H predicted by this method is basically consistent with the real value,which proves that the proposed method has a good prediction effect.

关键词： Quality prediction ELM DAE PCA TE

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Fault Diagnosis Based on Sparse Semi-supervised GAN Model

穿采空区煤层气水平井井眼与管柱相容性分析及应用研究

第32届中国控制与决策会议

作者： Liu Xiaozhi Wang Yinan yang yinghua College of Information Science and Engineering Northeastern University

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

In this paper we propose a new fault diagnosis model based on sparse semi-supervised GAN（SSGAN）.The SSGAN-based fault diagnosis can use a large amount of unmarked data to improve the accuracy of the marked training *** the problem that the general neural network requires a large amount of tag *** particular, we improved the discriminator to get a more sparse network, which further improved the classification *** the same time we choose Leaky ReLU as the activation function which solve the problem that the ReLU activation function has a dead *** studies on the Tennessee–Eastman（TE） benchmark process evaluate the performance of the developed method, which indicate that the SSGAN method performs better than BPNN.

关键词： Fault diagnosis Semi-supervised learning SSGAN TE

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煤 2024年第9期33卷 28-31页

作者：徐影李亚辉杨樱花刘卫娟河南豫中地质勘查工程有限公司河南郑州450000 河南省自然资源科技创新中心(非常规天然气开发研究) 河南郑州450000 河南省地质研究院河南郑州450000 河南省能源钻井工程技术研究中心河南郑州450000 河南省范钦明示范性劳模与工匠人才创新工作室河南郑州450000

穿采空区煤层气水平井是目前在山西沁水盆地实施的一种穿3号煤层采空区,并在下部9号、15号煤层进行水平段钻进的一种井型,由于3号煤层大部分已采空放塌形成采空区,与下部9号、15号煤垂直距离45~90 m,因而在施工时必须以一定的曲率穿越... 详细信息

穿采空区煤层气水平井是目前在山西沁水盆地实施的一种穿3号煤层采空区,并在下部9号、15号煤层进行水平段钻进的一种井型,由于3号煤层大部分已采空放塌形成采空区,与下部9号、15号煤垂直距离45~90 m,因而在施工时必须以一定的曲率穿越采空区才能确保在靶点位置精准着陆并确保水平段目的层钻遇率,同时应尽可能以较小的井斜角穿采空区钻进,以降低穿采空区钻井及下套管难度。因而,文章通过对穿采空区煤层气水平井定向段钻进及下套管过程中管柱与井眼的相容性进行分析,以API和IADC推荐的套管允许最大井眼曲率计算公式为基础,考虑上提力、螺纹强度、套管扶正器外径等影响因素,对井眼曲率计算公式进行优化,并将优化后的公式应用于SHH28-L1井的施工设计中,得出该井二开、三开钻井时的最大井眼曲率,确保了该井顺利实施,可为该区今后实施该类井型提供一定的参考和借鉴。

关键词：最大井眼曲率相容性穿采空区煤层气水平井

Design,preparation,and characterization of a novel ZnO/CuO/Al energetic diode with dual functionality:Logic and destruction

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Defence Technology（防务技术） 2024年第4期34卷 57-68页

作者： Jialu yang Jiaheng Hu yinghua Ye Jianbing Xu Yan Hu Ruiqi Shen School of Chemistry and Chemical Engineering Nanjing University of Science and TechnologyNanjing 210094China Micro-Nano Energetic Devices Key Laboratory of MIIT Nanjing 210094China Institute of Space Propulsion Nanjing University of Science and TechnologyNanjing 210094China

Self-destructing chips have promising applications for securing *** paper proposes a new concept of energetic diodes for the first time,which can be used for self-destructive chips.A simple two-step electrochemical deposition method is used to prepare ZnO/CuO/Al energetic diode,in which N-type ZnO and P-type CuO are constricted to a PN *** paper comprehensively discusses the material properties,morphology,semiconductor characteristics,and exploding performances of the energetic *** results show that the energetic diode has typical rectification with a turn-on voltage of about 1.78 V and a reverse leakage current of about 3×10^(-4)*** a constant voltage of 70 V loads to the energetic diode in the forward direction for about 0.14 s or 55 V loads in the reverse direction for about 0.17 s,the loaded power can excite the energetic diode exploding and the current rises to about100 *** to the unique performance of the energetic diode,it has a double function of rectification and *** energetic diode can be used as a logic element in the normal chip to complete the regular operation,and it can release energy to destroy the chip accurately.

关键词： Energetic diode ZnO—CuO—Al thermite ZnO/CuO PN junction Electrical explosion performance Self-destructing chips

Validity and reliability of the Brain Health Self-Efficacy Scale for the elderly

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General Psychiatry 2020年第5期33卷 319-327页

作者： Yining Gao Ming Cui Chunyan yang Yuejing Wu Yun Long Yaopian Chen Hongshen Liu Lin Sun yinghua yang Xia Li Shanghai Mental Heatth Center Shanghai Jiao Tong University Schoo of MedicineShanghaiChina Yinhang Community HealthCenter Yangpu DistrictShanghaiChina Shanghai Municipal Center forDisease Control and Prevention ShanghaiChina

Background With the rapid increase in ageing population,China is confronted with the daunting challenge of a growing number of patients with neurocognitive disorders(NCDs).This trend makes the maintenance of self-health and early intervention essential,highlighting the need for a tool that assesses self-efficacy of older adults in maintaining brain health or cognitive *** This study aimed to design the Brain Health Self-Efficacy Scale(BHSES)to measure elderly individuals'attitudes to NCDs,motivations and future plans for controlling *** psychometric properties of BHSES have been *** Based on the current literature and relevant models,a 19-item scale was created during the first stage.A total of 660 older adults in the Yinhang community of Shanghai were *** statistical approaches of item analysis,exploratory factor analysis(EFA),confirmatory factor analysis(CFA),criterion-related validity and reliability test were used to evaluate the quality of *** addition,the Geriatric Depression Scale(GDS)and the Self-Rating Anxiety Scale(SAS)were used as criteria to test the criterion-related *** To test item differentiation,the study adopted item analysis and excluded item *** a random half of the sample for EFA,the BHSES was refined to 16 items,which were categorised into the following three dimensions:'memory belief efficacy','self-care efficacy'and'future planning efficacy'.These were highly consistent with the hypothesis *** cumulative variance contribution rate reached 61.14%,with factor loads of all items above *** three-factor model was confirmed by the remaining data through *** fit indices reached the acceptable level(x2=3.045,Goodness of Fit Index=0.898,adjusted Goodness of Fit Index=0.863,Comparative Fit Index=0.916,Incremental Fit Index=0.917,Tucker-Lewis Index=0.900,root mean square error of approximation=0.079 and root mean residual=0.068).The GDS and SAS scores revealed significant corr

关键词： dimensions criterion validity