2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)最新文献_第4页

A Digital Twin Framework for Performance Monitoring and Anomaly Detection in Fused Deposition Modeling 熔融沉积建模中性能监测和异常检测的数字孪生框架

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843166

Efe C. Balta, D. Tilbury, K. Barton

引用次数: 25

Damage detection of building structure based on vibration data and hysteretic model 基于振动数据和滞回模型的建筑结构损伤检测

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8842996

J. Morales‐Valdez, M. Lopez, Wen Yu

{"title":"Damage detection of building structure based on vibration data and hysteretic model","authors":"J. Morales‐Valdez, M. Lopez, Wen Yu","doi":"10.1109/COASE.2019.8842996","DOIUrl":"https://doi.org/10.1109/COASE.2019.8842996","url":null,"abstract":"This paper presents a novel approach for damage detection in building structures by using the dissipated energy. In this sense, the hysteretic Bouc-Wen model is introduced as a useful tool for describing the degrading energy, which is directly related to the stiffness loss. Since, parameters and states of this model are unknown, we employ a nonlinear system identification algorithm based on Convolutional Neural Network (CNN) to avoid estimate simultaneously the states and parameters of the model. The used CNN have the sparse connectivity, which ensures that the strong response can be detected by convolution filters. In addition, the shared weights of the CNN reduce the the training complexity and the number of its parameters because the same weights are applied to all inputs. Therefore, the CNN can detect features no matter where they are on the vibration data, also reducing the training complexity. The use of this tool avoids using an adaptive observer, which unlike CNN, the algorithm’s complexity increases with the number of unknown parameters and states. Moreover, the adaptive observer can not guarantee convergence in presence of measurement noise. Experimental results confirmed that the proposed method is promising for real applications.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"19 1","pages":"608-613"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90831068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Variable Neighborhood Search for Home Care Scheduling Under Chargeable Overtime and Preference Matching* 收费加班与偏好匹配下的可变邻域搜索*

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843276

Yanran Zhu, A. Matta, Ettore Lanzarone, Na Geng

引用次数: 1

Flatness-based Powertrain Control for Engine Start Applications in Hybrid Dual-Clutch Transmissions 基于平整度的动力系统控制在混合动力双离合器变速器中的应用

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843248

Michael A. Mrochen, O. Sawodny

引用次数: 2

Optimal Coordination of EVs and HVAC Systems with Uncertain Renewable Supply 不确定可再生能源供应下电动汽车与暖通空调系统的最优协调

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843270

Haoming Zhao, Zhanbo Xu, Jiang Wu, Kun Liu, Lei Yang, X. Guan

{"title":"Optimal Coordination of EVs and HVAC Systems with Uncertain Renewable Supply","authors":"Haoming Zhao, Zhanbo Xu, Jiang Wu, Kun Liu, Lei Yang, X. Guan","doi":"10.1109/COASE.2019.8843270","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843270","url":null,"abstract":"The stochastic demand of electric vehicles (EVs) charging and building’s heating, ventilation and air conditioning (HVAC) system account for a large proportion in social energy consumption. The photovoltaic (PV) system becomes miniaturized and applied on roof of smart buildings with the development of a sequence of PV power generation technologies. Due to the randomness of weather conditions and human behavior, the power supply is random as well as the power demand. To guarantee the power balance in real-time, it is necessary to coordinate the dispatch of EVs and HVACs with the uncertainties from both sides. A mixed integer programming is formulated to model the coordination of the EVs and HVAC systems. The operation strategies of EVs and HVAC systems under uncertainties in both supply and demand are determined based on the model predictive control (MPC) framework. The performance of the coordination of EVs and HVAC systems is demonstrated using numerical case studies. The results show that coordinating the operation of EVs and HVAC systems can significantly reduce the cost and accommodate the uncertainties in the PV supply.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"74 1","pages":"733-738"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90634551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Surface Defect Detection using Hierarchical Features 基于层次特征的表面缺陷检测

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843235

L. Xiao, Tao Huang, Bo Wu, Youmin Hu, Jiehan Zhou

引用次数: 3

Real-Time Path-Constrained Trajectory Tracking for Robot Manipulators with Energy Budget Optimization 基于能量预算优化的机械臂实时路径约束轨迹跟踪

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8842946

Danilo V. Cunha, F. Lizarralde

引用次数: 0

Optimizing a UAV-based Emergency Medical Service Network for Trauma Injury Patients* 基于无人机的创伤损伤应急医疗服务网络优化研究*

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843138

Ruijiu Mao, Bin Du, Dengfeng Sun, N. Kong

引用次数: 9

Energy autonomous automation of Smart Home applications using the example of a wireless Indoor Smart Gardening system 能源自主自动化的智能家居应用，以无线室内智能园艺系统为例

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843000

E. Mackensen, Julius Klose, Axel Rombach, Aaron Spitznagel

{"title":"Energy autonomous automation of Smart Home applications using the example of a wireless Indoor Smart Gardening system","authors":"E. Mackensen, Julius Klose, Axel Rombach, Aaron Spitznagel","doi":"10.1109/COASE.2019.8843000","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843000","url":null,"abstract":"Smart Home or Smart Building applications are a growing market. An increasing challenge is to design energy efficient Smart Home applications to achieve sustainable and green homes. Using the example of the development of an Indoor Smart Gardening system with wireless monitoring and automated watering this paper is discussing in particular the design issue of energy autonomous working sensors and actuators for home automation. Most important part of the presented Smart Gardening system is a 3D printed smart flower pot for single plants. The smart flower pot has integrated a water reservoir for automated plant irrigation and an electronic for monitoring important plant parameters and the water level of the water reservoir. Energy harvesting with solar cells enables energy autonomous working of the flower pot. A low-power wireless interface also integrated in the flowerpot and an external gateway based on a Raspberry Pi 3 enables wireless networking of multiple of those flower pots. The gateway is used for evaluating the plant parameters and as a user interface. Particularly the architecture of the energy autonomous wireless flower pot will be considered, because fully energy autonomous sensors and actuators for home automation could not be implemented without special concepts for the energy supply and the overall electronic.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"57 1","pages":"1087-1092"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84791710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

A Model-Driven Learning Approach for Predicting the Personalized Dynamic Thermal Comfort in Ordinary Office Environment 普通办公环境个性化动态热舒适预测的模型驱动学习方法

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843073

Yadong Zhou, Xukun Wang, Zhanbo Xu, Ying Su, Ting Liu, Chao Shen, X. Guan

{"title":"A Model-Driven Learning Approach for Predicting the Personalized Dynamic Thermal Comfort in Ordinary Office Environment","authors":"Yadong Zhou, Xukun Wang, Zhanbo Xu, Ying Su, Ting Liu, Chao Shen, X. Guan","doi":"10.1109/COASE.2019.8843073","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843073","url":null,"abstract":"Occupants’ thermal comfort plays a critical role in the optimization of building operation, which has thus attracted more and more attention in recent years. However, diversity and uncertainties in the thermal comfort, which is caused by not only the physical environment, but also the psychology and physiology, provide challenges in the modeling of the thermal comfort. In this paper, based on cyber-physical system framework, we develop a thermal comfort model by a model-driven learning approach to dynamically predict the personalized thermal comfort through online learning and computation. This model consists of a physical part and a data-driven part. The physical part is developed based on the traditional heat balance equation. Since in the physical part there are some parameters (such as skin temperature) are difficult to be measured in practice, a data-driven part is thus developed based on the regression model to estimate the uncertain parameters with the feedback of occupants. By integrating the data-driven part into the physical part, the developed model could take both advantages of the model-driven and data-driven methods. The effectiveness and performance of the developed thermal comfort model are demonstrated using field experiments.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"739-744"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85233245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5