2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)最新文献_第7页

Control Architecture and Transport Coordination for Autonomous Logistics Modules in Flexible Automated Material Flow Systems 柔性自动化物流系统中自主物流模块的控制体系结构与运输协调

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560471

Christian Lieberoth-Leden, J. Fischer, J. Fottner, B. Vogel‐Heuser

引用次数: 5

Equipment health assessment and fault-early warning algorithm based on improved SVDD 基于改进SVDD的设备健康评估与故障预警算法

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560464

Lianlian Zhang, F. Qiao, Junkai Wang

{"title":"Equipment health assessment and fault-early warning algorithm based on improved SVDD","authors":"Lianlian Zhang, F. Qiao, Junkai Wang","doi":"10.1109/COASE.2018.8560464","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560464","url":null,"abstract":"With the rapid development of Internet-of-Things and big data, health assessment of equipment has become a hot spot in recent years. It is critical to bridge the gap between real-time factory data and health status evaluation, which helps decide appropriate maintenance time by quantitative fault-early warning. For this purpose, this paper proposes a framework to realize real-time equipment health management. The framework begins with principal component analysis (PCA) for feature reduction and support vector data description (SVDD) method for identifying abnormal observations. To promote the computational efficiency of the static health assessment model, an improved incremental learning SVDD method based on KKT (Karush-Kuhn-Tucker) condition (KISVDD) is proposed. Then health degree (HD) is defined derived from deviation degree (DD) based on Euclidean distance. Subsequently, a fault-early warning threshold setting method based on sliding window is established to realize quantitative maintenance time prediction. Thereafter, the proposed scheme is compared with different types of algorithms in a case study to demonstrate the effectiveness of the proposed model using actual production data. The results show that the proposed model outperforms traditional ones in accuracy and computational efficiency.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"56 12","pages":"716-721"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91501659","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

A Distributed Map Building Approach for Mobile Robotic Networks 移动机器人网络的分布式地图构建方法

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560499

A. Petitti, Donato Di Paola, R. Colella, A. Milella, E. Stella, Antonio Coratelli, D. Naso

引用次数: 2

Outlier Detection for Hydropower Generation Plant 水电厂异常值检测

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560424

Imtiaz Ahmed, A. Dagnino, Alessandro Bongiovi, Yu Ding

{"title":"Outlier Detection for Hydropower Generation Plant","authors":"Imtiaz Ahmed, A. Dagnino, Alessandro Bongiovi, Yu Ding","doi":"10.1109/COASE.2018.8560424","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560424","url":null,"abstract":"A hydropower generation plant is a complex system and composed of numerous physical components. To monitor the health of different components it is necessary to detect anomalous behavior in time. Establishing a performance guideline along with identification of the critical variables causing anomalous behavior can help the maintenance personnel to detect any potential shift in the process timely. To establish any guideline for future control, at first a mechanism is needed to differentiate anomalous observations from the normal ones. In our work we have employed three different approaches to detect the anomalous observations and compared their performances using a historical data set received from a hydropower plant. The outliers detected are verified by the domain experts. Making use of a decision tree and feature selection process, we have identified some critical variables which are potentially linked to the presence of the outliers. We further developed a one-class classifier using the outlier cleaned dataset, which defines the normal working condition, and therefore, violation of the normal conditions could identify anomalous observations in future operations.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"23 1","pages":"193-198"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90412317","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

Towards Automating Precision Irrigation: Deep Learning to Infer Local Soil Moisture Conditions from Synthetic Aerial Agricultural Images 迈向自动化精确灌溉:从合成航空农业图像中推断当地土壤湿度状况的深度学习

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560431

David Tseng, David Wang, Carolyn L. Chen, Lauren Miller, W. Song, J. Viers, S. Vougioukas, Stefano Carpin, J. A. Ojea, Ken Goldberg

{"title":"Towards Automating Precision Irrigation: Deep Learning to Infer Local Soil Moisture Conditions from Synthetic Aerial Agricultural Images","authors":"David Tseng, David Wang, Carolyn L. Chen, Lauren Miller, W. Song, J. Viers, S. Vougioukas, Stefano Carpin, J. A. Ojea, Ken Goldberg","doi":"10.1109/COASE.2018.8560431","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560431","url":null,"abstract":"Recent advances in unmanned aerial vehicles suggest that collecting aerial agricultural images can be cost-efficient, which can subsequently support automated precision irrigation. To study the potential for machine learning to learn local soil moisture conditions directly from such images, we developed a very fast, linear discrete-time simulation of plant growth based on the Richards equation. We use the simulator to generate large datasets of synthetic aerial images of a vineyard with known moisture conditions and then compare seven methods for inferring moisture conditions from images, in which the “uncorrelated plant” methods look at individual plants and the “correlated field” methods look at the entire vineyard: 1) constant prediction baseline, 2) linear Support Vector Machines (SVM), 3) Random Forests Uncorrelated Plant (RFUP), 4) Random Forests Correlated Field (RFCF), 5) two-layer Neural Networks (NN), 6) Deep Convolutional Neural Networks Uncorrelated Plant (CNNUP), and 7) Deep Convolutional Neural Networks Correlated Field (CNNCF). Experiments on held-out test images show that a globally-connected CNN performs best with normalized mean absolute error of 3.4%. Sensitivity experiments suggest that learned global CNNs are robust to injected noise in both the simulator and generated images as well as in the size of the training sets. In simulation, we compare the agricultural standard of flood irrigation to a proportional precision irrigation controller using the output of the global CNN and find that the latter can reduce water consumption by up to 52% and is also robust to errors in irrigation level, location, and timing. The first-order plant simulator and datasets are available at https://github.com/BerkeleyAutomation/RAPID.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"58 1","pages":"284-291"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90714005","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: 25

Technical Program Contents List 技术方案内容一览表

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/coase.2018.8560392

引用次数: 0

Architecture of a Cloud-Based Control System Decentralised at Field Level 基于云的现场级分散控制系统体系结构

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560418

D. Tomzik, X. Xu

{"title":"Architecture of a Cloud-Based Control System Decentralised at Field Level","authors":"D. Tomzik, X. Xu","doi":"10.1109/COASE.2018.8560418","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560418","url":null,"abstract":"Conventional control systems for machine tools and manufacturing systems are often limited in their computational power, connectivity and interoperability. Cloud-based control systems are a solution that addresses these issues. Advantages of the cloud are the elasticity of computational power (Infrastructure as a Service) and a plethora of development tools (Platform as a Service). The developed solutions are based on a local control system with an additional connection to the cloud. Communication and control of the field level run centralised through this control system. To try for more flexibility, we propose an approach where individual components at the field level are directly connected to the cloud. They are equipped with computational resources, connected directly to a TCP/IP network and communicate with each other and perform control tasks. This had been made possible by ever-shrinking integrated circuits at lower prices. In this paper, a possible use scenario, hardware candidates, and firmware aspects are presented. For an initial examination, the findings were compared against requirements for cloud-based control in the application area of soft-tissue interaction. This proposed architecture will be the basis for a prototype in the future.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"28 1","pages":"353-358"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85784557","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: 4

Physical Human-Robot Interaction Coupled with a Moving Environment or Target: Contact and Track 与移动环境或目标耦合的物理人机交互:接触和跟踪

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560702

Hsieh-Yu Li, Ishara Paranawithana, Liangjing Yang, U-Xuan Tan

{"title":"Physical Human-Robot Interaction Coupled with a Moving Environment or Target: Contact and Track","authors":"Hsieh-Yu Li, Ishara Paranawithana, Liangjing Yang, U-Xuan Tan","doi":"10.1109/COASE.2018.8560702","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560702","url":null,"abstract":"There is an increasing number of applications in physical human-robot interaction (pHRI) where the end-effector of the robot is compliant in response to the force exerted by the human. The force sensor is normally mounted with an instrument on the end-effector to measure the human operational force. However, when the robot is in contact with the human and an environment simultaneously, the force sensor reading includes both the human and the environmental force resulting in ineffective contacting interaction within these three objects (robot, human and environment). In addition, if the environment is moving, it is more challenging for the operator to track the target with the robot. Therefore, in this paper, we address the issue of pHRI coupled with a moving environment. More specifically, we use a collaborative robot with an ultrasound probe as an illustration due to its sophisticated condition: the operator needs to contact the environment using a sufficient force to get clearer images and track the moving target. The proposed control scheme is employed using only one force sensor to guarantee a stable physical interaction within three objects and provide the compliant and intuitive operation for human. Experiments with a collaborative robot are conducted to evaluate the effectiveness of the proposed controller.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"17 1","pages":"43-49"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86889790","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: 4

A Multi-Mode Biomimetic Wall-Climbing Robot 多模式仿生爬壁机器人

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560382

Jiajun Xu, Linsen Xu, Jinfu Liu, Xiaohu Li, Xuan Wu

引用次数: 4

An Approach of Optimising S-curve Trajectory for a Better Energy Consumption 一种优化s曲线轨迹的节能方法

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Pub Date : 2018-08-01 DOI: 10.1109/COASE.2018.8560587

Fadi Assad, E. Rushforth, Mus'ab H. Ahmad, B. Ahmad, R. Harrison

引用次数: 3