This paper presents a method for measuring stress fields within the framework of coupled data models,aimed at determining stress fields in isotropic material structures exhibiting localized deterioration behavior with...This paper presents a method for measuring stress fields within the framework of coupled data models,aimed at determining stress fields in isotropic material structures exhibiting localized deterioration behavior without relying on constitutive equations in the deteriorated region.This approach contributes to advancing the field of intrinsic equation-free mechanics.The methodology combines measured strain fields with data-model coupling driven algorithms.The gradient and Canny operators are utilized to process the strain field data,enabling the determination of the deterioration region's location.Meanwhile,an adaptive model building method is proposed for constructing coupling driven models.To address the issue of unknown datasets during computation,a dataset updating strategy based on a differential evolutionary algorithm is introduced.The resulting optimal dataset is then used to generate stress field results.Validation against finite element method calculations demonstrates the accuracy of the proposed method in obtaining full-field stresses in specimens with local degradation behavior.展开更多
Extensive penetration of distribution energy resources(DERs)brings increasing uncertainties to distribution networks.Accurate topology identification is a critical basis to guarantee robust distribution network operat...Extensive penetration of distribution energy resources(DERs)brings increasing uncertainties to distribution networks.Accurate topology identification is a critical basis to guarantee robust distribution network operation.Many algorithms that estimate distribution network topology have already been employed.Unfortunately,most are based on data-driven alone method and are hard to deal with ever-changing distribution network physical structures.Under these backgrounds,this paper proposes a data-model hybrid driven topology identification scheme for distribution networks.First,a data-driven method based on a deep belief network(DBN)and random forest(RF)algorithm is used to realize the distribution network topology rough identification.Then,the rough identification results in the previous step are used to make a model of distribution network topology.The model transforms the topology identification problem into a mixed integer programming problem to correct the rough topology further.Performance of the proposed method is verified in an IEEE 33-bus test system and modified 292-bus system.展开更多
This paper proposes a novel intelligent fault detection method,i.e.,combining the subspace identification technique(SIT)with the data-model interactive compensation mechanism for fault detection.More precisely,the des...This paper proposes a novel intelligent fault detection method,i.e.,combining the subspace identification technique(SIT)with the data-model interactive compensation mechanism for fault detection.More precisely,the design process is divided into two primary stages:offline learning process and real-time fault monitoring.In the offline learning phase,the fault isolation algorithm is employed,along with parameter identification using the subspace identification technique.Then the online data undergo normalization processing and are subjected to online fault detection using a trained offline model.In addition,considering the accuracy of fault detection,this paper designs the dynamic optimal threshold based on the fault detection rate(FDR)and the false alarm rate(FAR).In the end,the case studies on PT700 and Tennessee Eastman(TE)process data are provided to confirm that the proposed method achieves the fault detection objectives.展开更多
土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获...土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获取、三维空间推测、三维数据模型、三维模型构建和可视化方法等方面的研究。本文对三维空间土壤推测与土壤模型构建的已有方法进行梳理和评述,以期为三维数字土壤制图的应用和发展提供建议。以三维土壤制图、三维GIS、三维数据模型、三维地质建模、三维可视化、土壤空间变异、空间推测、克里格插值、土壤-景观分析、深度函数、机器学习、地统计学、随机模拟等为关键词检索Web of Science数据库,基于相关度、引用率和文献来源等因素进一步筛选出重点文献进行分析。归纳整理了土壤空间变异性、三维空间土壤推测、三维空间数据模型和三维模型构建等关键技术的现有研究体系,对各种三维推测和建模方法的优缺点和适用场景作出评价。针对目前研究中存在的垂直方向土壤数据稀少、土壤三维推测精度低、三维模型质量待提高等问题,提出一些可行的研究思路。展开更多
基金supported by the Fundamental Research Fund for the Central Universities(Grant No.BLX202226)。
文摘This paper presents a method for measuring stress fields within the framework of coupled data models,aimed at determining stress fields in isotropic material structures exhibiting localized deterioration behavior without relying on constitutive equations in the deteriorated region.This approach contributes to advancing the field of intrinsic equation-free mechanics.The methodology combines measured strain fields with data-model coupling driven algorithms.The gradient and Canny operators are utilized to process the strain field data,enabling the determination of the deterioration region's location.Meanwhile,an adaptive model building method is proposed for constructing coupling driven models.To address the issue of unknown datasets during computation,a dataset updating strategy based on a differential evolutionary algorithm is introduced.The resulting optimal dataset is then used to generate stress field results.Validation against finite element method calculations demonstrates the accuracy of the proposed method in obtaining full-field stresses in specimens with local degradation behavior.
文摘Extensive penetration of distribution energy resources(DERs)brings increasing uncertainties to distribution networks.Accurate topology identification is a critical basis to guarantee robust distribution network operation.Many algorithms that estimate distribution network topology have already been employed.Unfortunately,most are based on data-driven alone method and are hard to deal with ever-changing distribution network physical structures.Under these backgrounds,this paper proposes a data-model hybrid driven topology identification scheme for distribution networks.First,a data-driven method based on a deep belief network(DBN)and random forest(RF)algorithm is used to realize the distribution network topology rough identification.Then,the rough identification results in the previous step are used to make a model of distribution network topology.The model transforms the topology identification problem into a mixed integer programming problem to correct the rough topology further.Performance of the proposed method is verified in an IEEE 33-bus test system and modified 292-bus system.
基金supported by the National Natural Science Foundation of China(Nos.62273058 and U22A2045)the Youth Science and Technology Innovation and Entrepreneurship Outstanding Talents Project of Jilin Province(No.20230508043RC)the Industrial Technology and Development Special Project of Jilin Provincial Development and Reform Commission(No.2024C008-2).
文摘This paper proposes a novel intelligent fault detection method,i.e.,combining the subspace identification technique(SIT)with the data-model interactive compensation mechanism for fault detection.More precisely,the design process is divided into two primary stages:offline learning process and real-time fault monitoring.In the offline learning phase,the fault isolation algorithm is employed,along with parameter identification using the subspace identification technique.Then the online data undergo normalization processing and are subjected to online fault detection using a trained offline model.In addition,considering the accuracy of fault detection,this paper designs the dynamic optimal threshold based on the fault detection rate(FDR)and the false alarm rate(FAR).In the end,the case studies on PT700 and Tennessee Eastman(TE)process data are provided to confirm that the proposed method achieves the fault detection objectives.
文摘土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获取、三维空间推测、三维数据模型、三维模型构建和可视化方法等方面的研究。本文对三维空间土壤推测与土壤模型构建的已有方法进行梳理和评述,以期为三维数字土壤制图的应用和发展提供建议。以三维土壤制图、三维GIS、三维数据模型、三维地质建模、三维可视化、土壤空间变异、空间推测、克里格插值、土壤-景观分析、深度函数、机器学习、地统计学、随机模拟等为关键词检索Web of Science数据库,基于相关度、引用率和文献来源等因素进一步筛选出重点文献进行分析。归纳整理了土壤空间变异性、三维空间土壤推测、三维空间数据模型和三维模型构建等关键技术的现有研究体系,对各种三维推测和建模方法的优缺点和适用场景作出评价。针对目前研究中存在的垂直方向土壤数据稀少、土壤三维推测精度低、三维模型质量待提高等问题,提出一些可行的研究思路。
