为提高内河码头结构健康监测系统中的模态参数识别分辨率,考虑模态独立性和正交性原则进行振动传感器的非均匀布置及优化,并提出基于MAC矩阵的最小均方差算法(Minimum Root Min Square,MRMS)的传感器优化配置流程。针对典型内河框架码...为提高内河码头结构健康监测系统中的模态参数识别分辨率,考虑模态独立性和正交性原则进行振动传感器的非均匀布置及优化,并提出基于MAC矩阵的最小均方差算法(Minimum Root Min Square,MRMS)的传感器优化配置流程。针对典型内河框架码头建立有限元模型,建立模型传感器布置优化和评价的框架流程,以结构面板垂向前十阶振型为主要模态参数,对传感器配置最优数量进行研究,并采用模态置信度矩阵、模态振型条件数以及Fisher信息矩阵行列式评价布点算法的效果及优劣,仿真过程中考虑1%的建模误差和环境噪声的影响。仿真研究结果表明:MRMS算法能够取得良好的模态振型正交性和独立性指标,可为内河框架码头结构健康在线监测系统提供优良的模态识别参数。展开更多
A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objective...A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.展开更多
提出了一种基于CAE_ViT网络模型和顺序层状耦合信息框架(sequential hierarchical coupled information framework,SHCIF)的多粒度多缺陷图像分类识别方法,并结合模糊综合评价(FCE)方法,以桥梁设施为例,对其表面缺陷进行细致的分类及安...提出了一种基于CAE_ViT网络模型和顺序层状耦合信息框架(sequential hierarchical coupled information framework,SHCIF)的多粒度多缺陷图像分类识别方法,并结合模糊综合评价(FCE)方法,以桥梁设施为例,对其表面缺陷进行细致的分类及安全评价。首先,研究提出了SHCIF及对应3个层次粒度的识别模型,并构建和增强了对应不同粒度的数据集。SHCIF框架和跨粒度分类决策旨在通过利用桥梁组件和缺陷类型这两个粒度的信息和准确性,提升对缺陷严重程度的识别。其次,使用迁移学习对CAE_ViT预训练模型进行微调,以满足桥梁缺陷检测的具体需求,并通过跨粒度分类决策进一步提升分类的准确性。最后,基于层次分析法与熵权法(AHP⁃EWM)的权重体系,通过模糊综合评价,综合考虑桥梁部位、桥梁组件、缺陷类型及其严重程度,实现了基于表观健康状态对桥梁安全状态等级的定量评价。实验结果显示,在3个层次粒度的识别模型中的宏平均F1⁃Score分数分别达到94.1%、81.6%和75.3%,而跨粒度分类决策的准确率为82%。最终通过一个桥梁的安全评价案例证明了方法的有效性、系统性和可拓展性。展开更多
随着我国轨道交通系统的快速发展,提高运维效率、降低运营成本和保障安全运行已成为当务之急。本文基于热辅助探测和测距(heat-assisted detection and ranging,HADAR)技术,针对当前智能运维系统中基础数据不全、数据质量不高的问题,提...随着我国轨道交通系统的快速发展,提高运维效率、降低运营成本和保障安全运行已成为当务之急。本文基于热辅助探测和测距(heat-assisted detection and ranging,HADAR)技术,针对当前智能运维系统中基础数据不全、数据质量不高的问题,提出了轨道交通智能运维系统框架和功能设计方案,并对其在轨道交通智能运维系统中的应用进行了深入探讨。采用该方案将有助于提高轨道交通设备整体运维效率,提高数据的准确性和利用率,保障轨道交通智能运维系统的健康可持续性发展。展开更多
文摘为提高内河码头结构健康监测系统中的模态参数识别分辨率,考虑模态独立性和正交性原则进行振动传感器的非均匀布置及优化,并提出基于MAC矩阵的最小均方差算法(Minimum Root Min Square,MRMS)的传感器优化配置流程。针对典型内河框架码头建立有限元模型,建立模型传感器布置优化和评价的框架流程,以结构面板垂向前十阶振型为主要模态参数,对传感器配置最优数量进行研究,并采用模态置信度矩阵、模态振型条件数以及Fisher信息矩阵行列式评价布点算法的效果及优劣,仿真过程中考虑1%的建模误差和环境噪声的影响。仿真研究结果表明:MRMS算法能够取得良好的模态振型正交性和独立性指标,可为内河框架码头结构健康在线监测系统提供优良的模态识别参数。
文摘A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.
文摘提出了一种基于CAE_ViT网络模型和顺序层状耦合信息框架(sequential hierarchical coupled information framework,SHCIF)的多粒度多缺陷图像分类识别方法,并结合模糊综合评价(FCE)方法,以桥梁设施为例,对其表面缺陷进行细致的分类及安全评价。首先,研究提出了SHCIF及对应3个层次粒度的识别模型,并构建和增强了对应不同粒度的数据集。SHCIF框架和跨粒度分类决策旨在通过利用桥梁组件和缺陷类型这两个粒度的信息和准确性,提升对缺陷严重程度的识别。其次,使用迁移学习对CAE_ViT预训练模型进行微调,以满足桥梁缺陷检测的具体需求,并通过跨粒度分类决策进一步提升分类的准确性。最后,基于层次分析法与熵权法(AHP⁃EWM)的权重体系,通过模糊综合评价,综合考虑桥梁部位、桥梁组件、缺陷类型及其严重程度,实现了基于表观健康状态对桥梁安全状态等级的定量评价。实验结果显示,在3个层次粒度的识别模型中的宏平均F1⁃Score分数分别达到94.1%、81.6%和75.3%,而跨粒度分类决策的准确率为82%。最终通过一个桥梁的安全评价案例证明了方法的有效性、系统性和可拓展性。
文摘随着我国轨道交通系统的快速发展,提高运维效率、降低运营成本和保障安全运行已成为当务之急。本文基于热辅助探测和测距(heat-assisted detection and ranging,HADAR)技术,针对当前智能运维系统中基础数据不全、数据质量不高的问题,提出了轨道交通智能运维系统框架和功能设计方案,并对其在轨道交通智能运维系统中的应用进行了深入探讨。采用该方案将有助于提高轨道交通设备整体运维效率,提高数据的准确性和利用率,保障轨道交通智能运维系统的健康可持续性发展。
