Pub Date : 2018-09-01DOI: 10.1109/ETFA.2018.8502608
Weili Yan, Jun-Hong Zhou
In this paper, a classification-based anomaly detection model is proposed to detect the aircraft component fault by exploring the historical flight sensor data. Detection of the aircraft component fault is formulated as a classification problem. Firstly, several sensors relevant to the fault are selected using statistical analysis. Secondly, flight phase-based statistical features are extracted using the selected sensors. Thirdly, several important features are selected using correlation analysis with the flight label. Finally, the random forest algorithm is applied to build the fault classification model based on the selected features. Experimental results show the proposed method can detect the component fault earlier than or as early as the current aircraft alarming system.
{"title":"Early Fault Detection of Aircraft Components Using Flight Sensor Data","authors":"Weili Yan, Jun-Hong Zhou","doi":"10.1109/ETFA.2018.8502608","DOIUrl":"https://doi.org/10.1109/ETFA.2018.8502608","url":null,"abstract":"In this paper, a classification-based anomaly detection model is proposed to detect the aircraft component fault by exploring the historical flight sensor data. Detection of the aircraft component fault is formulated as a classification problem. Firstly, several sensors relevant to the fault are selected using statistical analysis. Secondly, flight phase-based statistical features are extracted using the selected sensors. Thirdly, several important features are selected using correlation analysis with the flight label. Finally, the random forest algorithm is applied to build the fault classification model based on the selected features. Experimental results show the proposed method can detect the component fault earlier than or as early as the current aircraft alarming system.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"382 1","pages":"1337-1342"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84006410","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}
Pub Date : 2018-09-01DOI: 10.1109/etfa.2018.8502521
{"title":"Intelligent Sensors, Sensor Networks, and Information Processing","authors":"","doi":"10.1109/etfa.2018.8502521","DOIUrl":"https://doi.org/10.1109/etfa.2018.8502521","url":null,"abstract":"","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86148419","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}
Pub Date : 2018-09-01DOI: 10.1109/etfa.2018.8502570
{"title":"Industrial Communication Technologies and Systems","authors":"","doi":"10.1109/etfa.2018.8502570","DOIUrl":"https://doi.org/10.1109/etfa.2018.8502570","url":null,"abstract":"","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"2014 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86457704","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}
Pub Date : 2018-09-01DOI: 10.1109/ETFA.2018.8502533
Le Anh Dao, Alireza Dehghani Pilehvarani, L. Ferrarini
This paper addresses the problem of sharing a private Electrical energy Storage System (ESS) for thermoelectrical energy management in a group of buildings. Each building is equipped with an ESS which can be used partly or completely by other buildings in the same group. This sharing strategy creates coupling constraints among the controllers of each individual building. In this context, an increment proximal minimization method has been employed to manage the energy flows among the various ESS's through a distributed approach. The local controller of each building employs a Model Predictive Control (MPC) which focuses on balancing economic optimization and occupant comfort while fulfilling various local technical constraints. The proposed technique allows local controllers to operate with maximum autonomy and privacy since, at each iteration, a little amount of information is exchanged between each local controller to a centralized coordination unit. Indeed, only the information related to the coupling constraints is required to exchange with the centralized unit. The most significant advantage of the method is to allow the individual building to exploit effectively not only its own ESS but also any excess power and energy capacity of the ESSs of other buildings. The simulation results show the accuracy and efficiency of the proposed method.
{"title":"A Consensus-Based Distributed MPC Approach for Batteries Sharing in Group of Buildings","authors":"Le Anh Dao, Alireza Dehghani Pilehvarani, L. Ferrarini","doi":"10.1109/ETFA.2018.8502533","DOIUrl":"https://doi.org/10.1109/ETFA.2018.8502533","url":null,"abstract":"This paper addresses the problem of sharing a private Electrical energy Storage System (ESS) for thermoelectrical energy management in a group of buildings. Each building is equipped with an ESS which can be used partly or completely by other buildings in the same group. This sharing strategy creates coupling constraints among the controllers of each individual building. In this context, an increment proximal minimization method has been employed to manage the energy flows among the various ESS's through a distributed approach. The local controller of each building employs a Model Predictive Control (MPC) which focuses on balancing economic optimization and occupant comfort while fulfilling various local technical constraints. The proposed technique allows local controllers to operate with maximum autonomy and privacy since, at each iteration, a little amount of information is exchanged between each local controller to a centralized coordination unit. Indeed, only the information related to the coupling constraints is required to exchange with the centralized unit. The most significant advantage of the method is to allow the individual building to exploit effectively not only its own ESS but also any excess power and energy capacity of the ESSs of other buildings. The simulation results show the accuracy and efficiency of the proposed method.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"60 1","pages":"871-878"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82959327","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}
Pub Date : 2018-09-01DOI: 10.1109/ETFA.2018.8502560
K. Ali, A. Telmoudi, Said Gattoufi
This paper addresses an improved Genetic Algorithm (GA) combined with local search technique to solve the dynamic job shop scheduling problem (DJSSP) with new job arrivals and change in processing time. The objective function is the minimization of the makespan known to be one of the performance criterion used to optimize manufacturing system requirements. To enhance the scheduling process, a rescheduling strategy is used to solve dynamic disturbances. Various problems including the number of jobs, the number of machines and the number of new job arrivals are compared with a collection of state of the art Dispatching Rules(DRs) and other metrics. Obtained results are satisfactory for rescheduling of new job arrivals, change in processing time and makespan minimization.
{"title":"An Improved Genetic Algorithm with Local Search for Solving the DJSSP with New Dynamic Events","authors":"K. Ali, A. Telmoudi, Said Gattoufi","doi":"10.1109/ETFA.2018.8502560","DOIUrl":"https://doi.org/10.1109/ETFA.2018.8502560","url":null,"abstract":"This paper addresses an improved Genetic Algorithm (GA) combined with local search technique to solve the dynamic job shop scheduling problem (DJSSP) with new job arrivals and change in processing time. The objective function is the minimization of the makespan known to be one of the performance criterion used to optimize manufacturing system requirements. To enhance the scheduling process, a rescheduling strategy is used to solve dynamic disturbances. Various problems including the number of jobs, the number of machines and the number of new job arrivals are compared with a collection of state of the art Dispatching Rules(DRs) and other metrics. Obtained results are satisfactory for rescheduling of new job arrivals, change in processing time and makespan minimization.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":" 18","pages":"1137-1144"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91416094","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}
Pub Date : 2018-09-01DOI: 10.1109/ETFA.2018.8502495
Riccardo Colelli, S. Panzieri, F. Pascucci
Industrial Control systems traditionally achieved security by using isolation from the outside and proprietary protocols to communicate inside. This paradigm is changed with the advent of the Industrial Internet of Things that foresees flexible and interconnected systems. In this contribution, the threats coming from this new approach are analyzed and a framework for identify them is proposed. It is based on the common signature based intrusion detection system developed in the information technology domain, however, to cope with the constraints of the operation technology domain, it exploits anomaly based features. Specifically, it is able to analyze the traffic on the network at application layer by mean of deep packet inspection, parsing the information carried by the proprietary protocols. Two different topologies are adopted to cope also with legacy systems. A simple set up is considered to prove the effectiveness of the approach.
{"title":"Exploiting System Model for Securing CPS: the Anomaly Based IDS Perspective","authors":"Riccardo Colelli, S. Panzieri, F. Pascucci","doi":"10.1109/ETFA.2018.8502495","DOIUrl":"https://doi.org/10.1109/ETFA.2018.8502495","url":null,"abstract":"Industrial Control systems traditionally achieved security by using isolation from the outside and proprietary protocols to communicate inside. This paradigm is changed with the advent of the Industrial Internet of Things that foresees flexible and interconnected systems. In this contribution, the threats coming from this new approach are analyzed and a framework for identify them is proposed. It is based on the common signature based intrusion detection system developed in the information technology domain, however, to cope with the constraints of the operation technology domain, it exploits anomaly based features. Specifically, it is able to analyze the traffic on the network at application layer by mean of deep packet inspection, parsing the information carried by the proprietary protocols. Two different topologies are adopted to cope also with legacy systems. A simple set up is considered to prove the effectiveness of the approach.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"68 1","pages":"1171-1174"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88200334","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}
Pub Date : 2018-09-01DOI: 10.1109/ETFA.2018.8502559
G. Kalogeras, C. Koulamas, A. Kalogeras, A. Moronis
Software models that simulate the energy performance and behavior of buildings provide experts, engineers and building administrators with a powerful predictive tool that allows users to analyze and predict the future impact of a possible energy saving measure without any costly physical intervention or the need for measurements. To achieve this, models have to be validated and tested for precision robustness, in order to be able to maintain an acceptable predictive capability. The present work deals with the implementation a calculation-based monthly quasi-steady state simulation model for energy use in buildings based on the ISO 13790 standard methodologies and presents its robustness testing methodology.
{"title":"Precision Robustness Testing of a Simulation Model for Energy Use in Buildings","authors":"G. Kalogeras, C. Koulamas, A. Kalogeras, A. Moronis","doi":"10.1109/ETFA.2018.8502559","DOIUrl":"https://doi.org/10.1109/ETFA.2018.8502559","url":null,"abstract":"Software models that simulate the energy performance and behavior of buildings provide experts, engineers and building administrators with a powerful predictive tool that allows users to analyze and predict the future impact of a possible energy saving measure without any costly physical intervention or the need for measurements. To achieve this, models have to be validated and tested for precision robustness, in order to be able to maintain an acceptable predictive capability. The present work deals with the implementation a calculation-based monthly quasi-steady state simulation model for energy use in buildings based on the ISO 13790 standard methodologies and presents its robustness testing methodology.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"41 1","pages":"932-939"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90544831","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}
Pub Date : 2018-09-01DOI: 10.1109/ETFA.2018.8502510
Marcus Lindner, J. A. Rivera, Henrik Tjader, P. Lindgren, Johan Eriksson
C programming dominates the mainstream of embedded development as of today. To aid the development, hardware abstractions, libraries, kernels, and light-weight operating systems are commonplace. However, these typically offer little or no help to automatic worst-case execution time (WCET) estimation, and thus manual test and measurement based approaches remain the de facto standard. For this paper, we take the outset from the Real-Time For the Masses (RTFM) framework, which is developed to facilitate embedded software development for IoT devices and provides highly efficient implementations, suitable to the mainstream of embedded system design. Although the Rust language plays currently a minor part in embedded development, we believe its properties add significant improvements and thus implement our RTFM framework in Rust. We present an approach to worst-case execution time estimation in the context of RTFM tasks and critical sections, which renders sufficient information for further response time and schedulability analysis. We introduce our test bench, which utilizes the KLEE tool for automatic test vector generation and subsequently performs cycle accurate hardware-in-the-loop measurements of the generated tests. The approach is straightforward and fully automatic. Our solution bridges the gap in between measurement based and static analysis methods for WCET estimation. We demonstrate the feasibility of the approach on a running example throughout the paper and conclude with a discussion on its implications and limitations.
{"title":"Hardware-in-the-loop based WCET analysis with KLEE","authors":"Marcus Lindner, J. A. Rivera, Henrik Tjader, P. Lindgren, Johan Eriksson","doi":"10.1109/ETFA.2018.8502510","DOIUrl":"https://doi.org/10.1109/ETFA.2018.8502510","url":null,"abstract":"C programming dominates the mainstream of embedded development as of today. To aid the development, hardware abstractions, libraries, kernels, and light-weight operating systems are commonplace. However, these typically offer little or no help to automatic worst-case execution time (WCET) estimation, and thus manual test and measurement based approaches remain the de facto standard. For this paper, we take the outset from the Real-Time For the Masses (RTFM) framework, which is developed to facilitate embedded software development for IoT devices and provides highly efficient implementations, suitable to the mainstream of embedded system design. Although the Rust language plays currently a minor part in embedded development, we believe its properties add significant improvements and thus implement our RTFM framework in Rust. We present an approach to worst-case execution time estimation in the context of RTFM tasks and critical sections, which renders sufficient information for further response time and schedulability analysis. We introduce our test bench, which utilizes the KLEE tool for automatic test vector generation and subsequently performs cycle accurate hardware-in-the-loop measurements of the generated tests. The approach is straightforward and fully automatic. Our solution bridges the gap in between measurement based and static analysis methods for WCET estimation. We demonstrate the feasibility of the approach on a running example throughout the paper and conclude with a discussion on its implications and limitations.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"05 1","pages":"345-352"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80083923","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}
Pub Date : 2018-09-01DOI: 10.1109/etfa.2018.8502617
{"title":"WIP Complex Engineering Systems and Systems Engineering","authors":"","doi":"10.1109/etfa.2018.8502617","DOIUrl":"https://doi.org/10.1109/etfa.2018.8502617","url":null,"abstract":"","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78231286","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}
Pub Date : 2018-09-01DOI: 10.1109/ETFA.2018.8502515
Maryam Pahlevan, R. Obermaisser
Time-Sensitive Networking (TSN) is introduced as a series of Ethernet extensions to address strict temporal constraints of modern mission-critical applications. TSN offers determinism using global Time-Triggered (TT) transmission schedules. Most of existing scheduling solutions ignore interdependence of routing and scheduling problems and derive the design space of system implementations only from scheduling constraints. This strategy limits the capability of former approaches to compute a global schedule of TT communication for several real-time systems. In this paper, we present a heuristic scheduling approach based on a genetic algorithm. Our approach combines the routing and scheduling constraints and generates static global schedules using joint constraints in a single-step. The number of scheduling possibilities within the design space that is derived from joint routing and scheduling constraints increases in comparison to the approaches that only use the fixed routing. Thereby, the schedulability is improved by our solution. Our genetic-based approach also considers the distribution of real-time applications, multicast patterns and interdependencies of TT flows in the scheduling process. Due to optimized task binding and resource allocation, the experimental results show a significant enhancement of schedulability, TT transmission efficiency and resource utilization compared to the state-of-art solutions.
{"title":"Genetic Algorithm for Scheduling Time-Triggered Traffic in Time-Sensitive Networks","authors":"Maryam Pahlevan, R. Obermaisser","doi":"10.1109/ETFA.2018.8502515","DOIUrl":"https://doi.org/10.1109/ETFA.2018.8502515","url":null,"abstract":"Time-Sensitive Networking (TSN) is introduced as a series of Ethernet extensions to address strict temporal constraints of modern mission-critical applications. TSN offers determinism using global Time-Triggered (TT) transmission schedules. Most of existing scheduling solutions ignore interdependence of routing and scheduling problems and derive the design space of system implementations only from scheduling constraints. This strategy limits the capability of former approaches to compute a global schedule of TT communication for several real-time systems. In this paper, we present a heuristic scheduling approach based on a genetic algorithm. Our approach combines the routing and scheduling constraints and generates static global schedules using joint constraints in a single-step. The number of scheduling possibilities within the design space that is derived from joint routing and scheduling constraints increases in comparison to the approaches that only use the fixed routing. Thereby, the schedulability is improved by our solution. Our genetic-based approach also considers the distribution of real-time applications, multicast patterns and interdependencies of TT flows in the scheduling process. Due to optimized task binding and resource allocation, the experimental results show a significant enhancement of schedulability, TT transmission efficiency and resource utilization compared to the state-of-art solutions.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"17 1","pages":"337-344"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84777368","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}
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