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Remaining Useful Life Prediction Method for Multi-Component System Considering Maintenance:Subsea Christmas Tree System as A Case Study

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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 {3.-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

Single channel signal component separation using Bayesian estimation

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Journal of Systems engineering and electronics 2007年第1期18卷 33-39页

作者： cai quanwei wei ping {3. xianci Coll. of electronic engineering Univ. of Electronic Science and Technology Chengdu 610054 P.R. China

A Bayesian estimation method to separate multicomponent signals with single channel observation is presented in this paper. By using the basis function projection, the component separation becomes a problem of limited parameter estimation. Then, a Bayesian model for estimating parameters is set up. The reversible jump MCMC （Monte Carlo Markov Chain） algorithmis adopted to perform the Bayesian computation. The method can jointly estimate the parameters of each component and the component number. Simulation results demonstrate that the method has low SNR threshold and better performance.

关键词： Signal component separation Single channel Bayesian estimation Reversible jump MCMC

Three-Dimensional Sound Source Location Algorithm for Subsea Leakage Using Hydrophone

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china Ocean engineering 2024年第2期38卷 326-337页

作者： LI Hao-jie cai Bao-ping YUAN xiao-bing KONG Xiang-di LIU Yong-hong Javed Akbar KHAN CHU Zheng-de YANG Chao TANG An-bang college of Mechanical and electronic engineering China University of PetroleumQingdao 266580China Shenzhen Urban Public Safety technology Institute Shenzhen 518000China Institute of Hydrocarbon Recovery Universiti Teknologi PETRONASBandar Seri IskandarPerak Darul Ridzuan 32610Malaysia

Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the ***,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for *** solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf ***,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by ***,the arrival time difference is used to locate the origin of the *** localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.

关键词： grey wolf optimizer variational modal decomposition mean envelope entropy correlation coefficient time difference of arrival

A blind separation method of overlapped multi-components based on time varying AR model

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science in china(Series F) 2008年第1期51卷 81-92页

作者： cai quanwei wei ping XlAO {3. college of electronic engineering University of Electronic Science and Technology of China Chengdu 610054 China

A method utilizing single channel recordings to blindly separate the multicomponents overlapped in time and frequency domains is proposed in this paper. Based on the time varying AR model, the instantaneous frequency and amplitude of each signal component are estimated respectively, thus the signal component separation is achieved. By using prolate spheroidal sequence as basis functions to expand the time varying parameters of the AR model, the method turns the problem of linear time varying parameters estimation to a linear time invariant parameter estimation problem, then the parameters are estimated by a recursive algorithm. The computation of this method is simple, and no prior knowledge of the signals is needed. Simulation results demonstrate validity and excellent performance of this method.

关键词： time varying AR model time and frequency domains overlap single channel multi-components separation recursive algorithm

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多级维修方式下的水下采油树视情维修方法

科学技术与工程 2024年第22期24卷 9365-9373页

作者：龙云李荣康张妍平周玉明袁晓兵蔡宝平中海油能源发展装备技术有限公司深圳518064 中国石油大学(华东)机电工程学院青岛266580 中国石油集团东方地球物理勘探有限责任公司涿州072750 深圳市城市公共安全技术研究院有限公司深圳518046

针对将组件完全恢复到最初运行状态的维修方式导致无法提供准确维修方案,对于实际系统,具有更多的维修细节,需要更复杂的维修方式描述组件维修过程的问题。以水下采油树关键部件为研究对象,提出基于维纳过程的多级维修方式下的视情维修... 详细信息

针对将组件完全恢复到最初运行状态的维修方式导致无法提供准确维修方案,对于实际系统,具有更多的维修细节,需要更复杂的维修方式描述组件维修过程的问题。以水下采油树关键部件为研究对象,提出基于维纳过程的多级维修方式下的视情维修方法。根据历史运行数据建立组件连续状态退化模型。根据历史维修数据结合K近邻分类方法,提出维修方式分级方法。通过多目标优化算法得到系统在使用周期内的维修方案。结果表明,考虑多级维修方式能够为多组件系统提供更准确的维修方案,有效平衡系统可靠性、可用性与维修成本之间的矛盾。

关键词：水下采油树视情维修方法多级维修方式

A Localization Method of High Energy Transients for All-sky Gamma-ray Monitor

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Research in Astronomy and Astrophysics 2024年第10期24卷 25-35页

作者： Yi Zhao Wangchen Xue Shaolin Xiong Qi Luo Yuanhao Wang Jiacong Liu Heng Yu xiaoyun Zhao Yue Huang Jinyuan Liao Jianchao Sun xiaobo Li Qibin Yi Ce cai Shuo xiao Shenglun Xie Chao Zheng Yanqiu Zhang Chenwei Wang Wenjun Tan Zhiwei Guo Chaoyang Li Zhenghua An Gang Chen Yanqi Du Min Gao Ke Gong Dongya Guo Jiang He Jianjian He Bing Li Gang Li Xinqiao Li Jing Liang xiaohua Liang Yaqing Liu Xiang Ma Rui Qiao Liming Song Xinying Song Xilei Sun Jin Wang ping Wang Xiangyang Wen Hong Wu Yanbing Xu Sheng Yang Dali Zhang Fan Zhang Hongmei Zhang Peng Zhang Shu Zhang Zhen Zhang Shijie Zheng Keke Zhang Xingbo Han Haiyan Wu Hu Tai Hao Geng Gaopeng Lu wei Xu Fanchao Lyu Hongbo Zhang Fangjun Lu Shuangnan Zhang Department of Astronomy Beijing Normal UniversityBeijing 100875China Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of sciences Beijing 100049China School of Physics and Optoelectronics Xiangtan UniversityXiangtan 411105China college of Physics Hebei Normal UniversityShijiazhuang 050024China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal UniversityGuiyang 550001China School of Physics and electronic science Guizhou Normal UniversityGuiyang 550001China Institute of Astrophysics Central China Normal UniversityWuhan 430079China college of physics sciences technology Hebei UniversityBaoding 071002China Physics and Space science college China West Normal UniversityNanchong 637002China School of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China college of electronic and information engineering Tongji UniversityShanghai 201804China Innovation Academy for Microsatellites of Chinese Academy of sciences Shanghai 201304China National Space science Center Chinese Academy of SciencesBeijing 100190China School of Earth and Space sciences University of Science and Technology of ChinaHefei 230026China electronic Information School Wuhan UniversityWuhan 430072China Key Laboratory of Transportation Meteorology of china Meteorological Administration Nanjing Joint Institute for Atmospheric SciencesNanjing 210000China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Fast and reliable localization of high-energy transients is crucial for characterizing the burst properties and guiding the follow-up *** based on the relative counts of different detectors has been widely used for all-sky gamma-ray *** are two major methods for this count distribution localization:χ^(2)minimization method and the Bayesian *** we propose a modified Bayesian method that could take advantage of both the accuracy of the Bayesian method and the simplicity of the χ^(2)*** comprehensive simulations,we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than the χ^(2)method,especially for weak *** further proposed a location-spectrum iteration approach based on the Bayesian inference,which could alleviate the problems caused by the spectral difference between the burst and location *** method is very suitable for scenarios with limited computation resources or timesensitive applications,such as in-flight localization software,and low-latency localization for rapidly follow-up observations.

关键词： methods:data analysis methods:analytical (stars:)gamma-ray burst:general

A Dynamic-Bayesian-Networks-Based Resilience Assessment Approach of Structure Systems: Subsea Oil and Gas Pipelines as A Case Study

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china Ocean engineering 2020年第5期34卷 597-607页

作者： cai Bao-ping ZHANG Yan-ping YUAN {3.-bing GAO Chun-tan LIU Yong-hong CHEN Guo-ming LIU Zeng-kai JI Ren-jie National engineering Laboratory of Offshore Geophysical and Exploration Equipment China University of PetroleumQingdao 266580China college of Mechanical and electronic engineering China University of PetroleumQingdao 266580China

Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metrics and assessment approaches are proposed for engineering system, they are not suitable for complex structure systems, since the failure mechanisms of them are different under the influences of natural disasters. This paper proposes a novel resilience assessment metric for structure system from a macroscopic perspective, named structure resilience, and develops a corresponding assessment approach based on remaining useful life of key components. Dynamic Bayesian networks(DBNs) and Markov are applied to establish the resilience assessment model. In the degradation process, natural degradation and accelerated degradation are modelled by using Bayesian networks, and then coupled by using DBNs. In the recovery process, the model is established by combining Markov and DBNs. Subsea oil and gas pipelines are adopted to demonstrate the application of the proposed structure metric and assessment approach.

关键词： structure resilience structure system remaining useful life dynamic Bayesian networks

CEPC Technical Design Report

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Radiation Detection technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua {3. Wenyong {3. Wujun {3. Yijian {3. Yizhou {3. Yuchen {3. Haiying {3. Huacheng {3. Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen wei Chen Xiang Chen xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho Ming-Chung Chu xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH University of science and technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central china Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan china academy of engineering physics MianyangSichuan china building materials academy Beijing china Center of Advanced science and technology Beijing china Institute of Atomic Energy Beijing china Jiliang University HangzhouZhejiang china Nuclear Instrument CO. LTDBeijing china University of Geosciences Beijing china University of Geosciences WuhanHubei china University of Mining and technology XuzhouJiangsu china West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing Chulalongkorn University Bangkok City University of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East china University Of science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by china,fostered through extensive collaboration with international *** complex comprises four accelerators:a 3. GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 3. MW per beam,it can achieve a luminosity of 5×10^(3.)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13.ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3.million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-203.s.

关键词： initiated exceeding precise

Study on ZnO Nanowire Prepared by Nuclear Track Technique

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Study on ZnO Nanowire Prepared by Nuclear Track Technique