Pub Date : 2016-10-24DOI: 10.1109/IConAC.2016.7604938
A. Jaber, P. Lazaridis, B. Saeed, Yong Zhang, David Khan, D. Upton, H. Ahmed, P. Mather, M. D. F. Q. Turnell, R. Atkinson, M. Judd, I. Glover
Partial discharge is measured simultaneously using free-space radiometry (FSR) and a galvanic contact measurement technique based on the IEC 60270 standard. Several types of PD (Partial Discharge) sources are specially constructed: two internal PD emulators and an emulator of the floating-electrode type. The excitation applied to the source is AC and the radiated signal is captured using a wideband biconical antenna. The calibration of PD sources is demonstrated. Effective radiated power of the PD source using a PD calibration device is determined.
{"title":"Comparative study of Partial Discharge emulators for the calibration of Free-Space radiometric measurements","authors":"A. Jaber, P. Lazaridis, B. Saeed, Yong Zhang, David Khan, D. Upton, H. Ahmed, P. Mather, M. D. F. Q. Turnell, R. Atkinson, M. Judd, I. Glover","doi":"10.1109/IConAC.2016.7604938","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604938","url":null,"abstract":"Partial discharge is measured simultaneously using free-space radiometry (FSR) and a galvanic contact measurement technique based on the IEC 60270 standard. Several types of PD (Partial Discharge) sources are specially constructed: two internal PD emulators and an emulator of the floating-electrode type. The excitation applied to the source is AC and the radiated signal is captured using a wideband biconical antenna. The calibration of PD sources is demonstrated. Effective radiated power of the PD source using a PD calibration device is determined.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115788325","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 : 2016-10-24DOI: 10.1109/IConAC.2016.7604914
Jia Song, Jiaming Lin, Erfu Yang
Near Space Hypersonic Vehicle (NSHV) could play significant roles in both military and civilian applications. It may cause huge losses of both personnel and property when a fatal fault occurs. It is therefore paramount to conduct fault-tolerant research for NSHV and avoid some catastrophic events. Toward this end, this paper presents a novel fault-tolerant control strategy by using the LSSVM (Least Squares Support Vector Machine)-based inverse system and Backstepping method. The control system takes advantage of the superiority of the LSSVM in solving the problems with small samples, high dimensions and local minima. The inverse system is built with an improved LSSVM. The adaptive controller is designed via the Backstepping which has the unique capability in dealing with nonlinear control systems. Finally, the experiment results demonstrate that the proposed method performs well.
{"title":"A novel fault-tolerant control strategy for Near Space Hypersonic Vehicles via Least Squares Support Vector Machine and Backstepping method","authors":"Jia Song, Jiaming Lin, Erfu Yang","doi":"10.1109/IConAC.2016.7604914","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604914","url":null,"abstract":"Near Space Hypersonic Vehicle (NSHV) could play significant roles in both military and civilian applications. It may cause huge losses of both personnel and property when a fatal fault occurs. It is therefore paramount to conduct fault-tolerant research for NSHV and avoid some catastrophic events. Toward this end, this paper presents a novel fault-tolerant control strategy by using the LSSVM (Least Squares Support Vector Machine)-based inverse system and Backstepping method. The control system takes advantage of the superiority of the LSSVM in solving the problems with small samples, high dimensions and local minima. The inverse system is built with an improved LSSVM. The adaptive controller is designed via the Backstepping which has the unique capability in dealing with nonlinear control systems. Finally, the experiment results demonstrate that the proposed method performs well.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122187346","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 : 2016-10-24DOI: 10.1109/IConAC.2016.7604963
Yuefan Hao, Zhijie Xu, Jing Wang, Y. Liu, Jiu-lun Fan
With the purpose of achieving automated detection of crowd abnormal behavior in public, this paper discusses the category of typical crowd and individual behaviors and their patterns. Popular image features for abnormal behavior detection are also introduced, including global flow based features such as optical flow, and local spatio-temporal based features such as Spatio-temporal Volume (STV). After reviewing some relative abnormal behavior detection algorithms, a brand-new approach to detect crowd panic behavior has been proposed based on optical flow features in this paper. During the experiments, all panic behaviors are successfully detected. In the end, the future work to improve current approach has been discussed.
{"title":"An approach to detect crowd panic behavior using flow-based feature","authors":"Yuefan Hao, Zhijie Xu, Jing Wang, Y. Liu, Jiu-lun Fan","doi":"10.1109/IConAC.2016.7604963","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604963","url":null,"abstract":"With the purpose of achieving automated detection of crowd abnormal behavior in public, this paper discusses the category of typical crowd and individual behaviors and their patterns. Popular image features for abnormal behavior detection are also introduced, including global flow based features such as optical flow, and local spatio-temporal based features such as Spatio-temporal Volume (STV). After reviewing some relative abnormal behavior detection algorithms, a brand-new approach to detect crowd panic behavior has been proposed based on optical flow features in this paper. During the experiments, all panic behaviors are successfully detected. In the end, the future work to improve current approach has been discussed.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130987432","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 : 2016-10-24DOI: 10.1109/IConAC.2016.7604928
M. Jafari, Jing Wang, Yongrui Qin, M. Gheisari, Amir Shahab Shahabi, Xiaohui Tao
Due to the high volume of information and electronic documents on the Web, it is almost impossible for a human to study, research and analyze this volume of text. Summarizing the main idea and the major concept of the context enables the humans to read the summary of a large volume of text quickly and decide whether to further dig into details. Most of the existing summarization approaches have applied probability and statistics based techniques. But these approaches cannot achieve high accuracy. We observe that attention to the concept and the meaning of the context could greatly improve summarization accuracy, and due to the uncertainty that exists in the summarization methods, we simulate human like methods by integrating fuzzy logic with traditional statistical approaches in this study. The results of this study indicate that our approach can deal with uncertainty and achieve better results when compared with existing methods.
{"title":"Automatic text summarization using fuzzy inference","authors":"M. Jafari, Jing Wang, Yongrui Qin, M. Gheisari, Amir Shahab Shahabi, Xiaohui Tao","doi":"10.1109/IConAC.2016.7604928","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604928","url":null,"abstract":"Due to the high volume of information and electronic documents on the Web, it is almost impossible for a human to study, research and analyze this volume of text. Summarizing the main idea and the major concept of the context enables the humans to read the summary of a large volume of text quickly and decide whether to further dig into details. Most of the existing summarization approaches have applied probability and statistics based techniques. But these approaches cannot achieve high accuracy. We observe that attention to the concept and the meaning of the context could greatly improve summarization accuracy, and due to the uncertainty that exists in the summarization methods, we simulate human like methods by integrating fuzzy logic with traditional statistical approaches in this study. The results of this study indicate that our approach can deal with uncertainty and achieve better results when compared with existing methods.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122211263","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 : 2016-10-24DOI: 10.1109/IConAC.2016.7604941
Naima Hamad, Khaldoon F. Brethee, F. Gu, A. Ball
Motor current signature analysis (MCSA) is regarded as an effective technique for motor and its downstream equipment fault diagnostics. However, limited work has been carried out for motors based on a sensorless variable speed drive (VSD). This study focuses on investigation of mechanical fault detection and diagnosis using electrical signatures from a VSD system. An analytic analysis was conducted to show that the fault can induce sidebands in instantaneous current, voltage and power signals in the VSD system, rather than just the sideband in a drive without closed loop control. Then different degrees of tooth breakages in an industrial two-stage helical gearbox were experimentally studied. It has found that even though the measured signal is very noisy, common spectrum analysis can discriminate the small sidebands for the fault detection and diagnosis. However, it has found that the power signals resulted from the multiplication of the current and voltage can provide a better diagnostic results.
{"title":"An investigation of electrical motor parameters in a sensorless variable speed drive for machine fault diagnosis","authors":"Naima Hamad, Khaldoon F. Brethee, F. Gu, A. Ball","doi":"10.1109/IConAC.2016.7604941","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604941","url":null,"abstract":"Motor current signature analysis (MCSA) is regarded as an effective technique for motor and its downstream equipment fault diagnostics. However, limited work has been carried out for motors based on a sensorless variable speed drive (VSD). This study focuses on investigation of mechanical fault detection and diagnosis using electrical signatures from a VSD system. An analytic analysis was conducted to show that the fault can induce sidebands in instantaneous current, voltage and power signals in the VSD system, rather than just the sideband in a drive without closed loop control. Then different degrees of tooth breakages in an industrial two-stage helical gearbox were experimentally studied. It has found that even though the measured signal is very noisy, common spectrum analysis can discriminate the small sidebands for the fault detection and diagnosis. However, it has found that the power signals resulted from the multiplication of the current and voltage can provide a better diagnostic results.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116803282","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 : 2016-10-24DOI: 10.1109/IConAC.2016.7604909
Mark Lane, Abdulkarim Shaeboub, F. Gu, A. Ball
Inverter driven motor systems have seen wider use in industry as energy reduction methods. Studies have been undertaken previously to understand the effects of voltage imbalances on motor efficiency and deratings. However, this has not been covered in much detail on inverter-driven motor systems. This paper aims to study the effect that motor stator resistance imbalances have on motor efficiency when used on inverter-driven systems. Motor imbalances may remain undetected by the inverter drive and can result in overheating and premature failure of the motor. Motor efficiency monitoring is now of greater interest due to new IEC standards defining new AC motor efficiency classes and this is also reviewed along with the standards for motor efficiency and inverter-operated motors.
{"title":"Investigation of reductions in motor efficiency caused by stator faults when operated from an inverter drive","authors":"Mark Lane, Abdulkarim Shaeboub, F. Gu, A. Ball","doi":"10.1109/IConAC.2016.7604909","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604909","url":null,"abstract":"Inverter driven motor systems have seen wider use in industry as energy reduction methods. Studies have been undertaken previously to understand the effects of voltage imbalances on motor efficiency and deratings. However, this has not been covered in much detail on inverter-driven motor systems. This paper aims to study the effect that motor stator resistance imbalances have on motor efficiency when used on inverter-driven systems. Motor imbalances may remain undetected by the inverter drive and can result in overheating and premature failure of the motor. Motor efficiency monitoring is now of greater interest due to new IEC standards defining new AC motor efficiency classes and this is also reviewed along with the standards for motor efficiency and inverter-operated motors.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129607906","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 : 2016-10-24DOI: 10.1109/IConAC.2016.7604956
Vassiliki Somaraki, Zhijie Xu
SOMA uses longitudinal data collected from the Ophthalmology Clinic of the Royal Liverpool University Hospital. Using trend mining (an extension of association rule mining) SOMA links attributes from the data. However the large volume of information at the output makes them difficult to be explored by experts. This paper presents the extension of the SOMA framework which aims to improve the post-processing of the results from experts using a visualisation tool which parse and visualizes the results, which are stored into XML structured files.
{"title":"Knowledge representation of large medical data using XML","authors":"Vassiliki Somaraki, Zhijie Xu","doi":"10.1109/IConAC.2016.7604956","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604956","url":null,"abstract":"SOMA uses longitudinal data collected from the Ophthalmology Clinic of the Royal Liverpool University Hospital. Using trend mining (an extension of association rule mining) SOMA links attributes from the data. However the large volume of information at the output makes them difficult to be explored by experts. This paper presents the extension of the SOMA framework which aims to improve the post-processing of the results from experts using a visualisation tool which parse and visualizes the results, which are stored into XML structured files.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116600223","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 : 2016-10-20DOI: 10.1109/IConAC.2016.7604962
K. Alheeti, K. Mcdonald-Maier
Emerging self-driving vehicles are vulnerable to different attacks due to the principle and the type of communication systems that are used in these vehicles. These vehicles are increasingly relying on external communication via vehicular ad hoc networks (VANETs). VANETs add new threats to self-driving vehicles that contribute to substantial challenges in autonomous systems. These communication systems render self-driving vehicles vulnerable to many types of malicious attacks, such as Sybil attacks, Denial of Service (DoS), black hole, grey hole and wormhole attacks. In this paper, we propose an intelligent security system designed to secure external communications for self-driving and semi self-driving cars. The proposed scheme is based on Proportional Overlapping Score (POS) to decrease the number of features found in the Kyoto benchmark dataset. The hybrid detection system relies on the Back Propagation neural networks (BP), to detect a common type of attack in VANETs: Denial-of-Service (DoS). The experimental results show that the proposed BP-IDS is capable of identifying malicious vehicles in self-driving and semi self-driving vehicles.
{"title":"Hybrid intrusion detection in connected self-driving vehicles","authors":"K. Alheeti, K. Mcdonald-Maier","doi":"10.1109/IConAC.2016.7604962","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604962","url":null,"abstract":"Emerging self-driving vehicles are vulnerable to different attacks due to the principle and the type of communication systems that are used in these vehicles. These vehicles are increasingly relying on external communication via vehicular ad hoc networks (VANETs). VANETs add new threats to self-driving vehicles that contribute to substantial challenges in autonomous systems. These communication systems render self-driving vehicles vulnerable to many types of malicious attacks, such as Sybil attacks, Denial of Service (DoS), black hole, grey hole and wormhole attacks. In this paper, we propose an intelligent security system designed to secure external communications for self-driving and semi self-driving cars. The proposed scheme is based on Proportional Overlapping Score (POS) to decrease the number of features found in the Kyoto benchmark dataset. The hybrid detection system relies on the Back Propagation neural networks (BP), to detect a common type of attack in VANETs: Denial-of-Service (DoS). The experimental results show that the proposed BP-IDS is capable of identifying malicious vehicles in self-driving and semi self-driving vehicles.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130766548","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 : 2016-10-20DOI: 10.1109/ICONAC.2016.7604929
Ruihao Li, Qiang Liu, Jianjun Gui, Dongbing Gu, Huosheng Hu
In this work, we present a Convolutional Neural Network(CNN) with depth images as its inputs to solve the relocalization problem of a moving platform in night-time indoor environment. The developed algorithm can estimate the camera pose in an end-to-end manner with 0.40m and 7.49° errors in real time during night. It does not require any geometric computation as it directly uses a CNN for 6 DOFs pose regression. The architecture and its encoding methods of depth images are discussed. The proposed method is also evaluated on benchmark datasets collected from a motion capture system in our lab.
{"title":"Night-time indoor relocalization using depth image with Convolutional Neural Networks","authors":"Ruihao Li, Qiang Liu, Jianjun Gui, Dongbing Gu, Huosheng Hu","doi":"10.1109/ICONAC.2016.7604929","DOIUrl":"https://doi.org/10.1109/ICONAC.2016.7604929","url":null,"abstract":"In this work, we present a Convolutional Neural Network(CNN) with depth images as its inputs to solve the relocalization problem of a moving platform in night-time indoor environment. The developed algorithm can estimate the camera pose in an end-to-end manner with 0.40m and 7.49° errors in real time during night. It does not require any geometric computation as it directly uses a CNN for 6 DOFs pose regression. The architecture and its encoding methods of depth images are discussed. The proposed method is also evaluated on benchmark datasets collected from a motion capture system in our lab.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121377812","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 : 2016-09-08DOI: 10.1109/IConAC.2016.7604889
B. Kusumoputro, H. Suprijono, M. A. Heryanto, B. Suprapto
Hexacopter is a type of multicopter that can be used to lift a heavy load, hence very convenient to be utilised in agricultural fields. As the consequence, however, the attitude control of this hexacopter is rather difficult compare with that of a quadcopter with four motors, due to gyroscopic effect of the additional motors and in its combination with the heavy loads. In this paper, we have developed a direct inverse controller system using an Elman neural networks for the attitude and altitude control of the hexacopter. Experiments are conducted using a flight data taken from a test-bed system. Results show that the attitude characteritics of the heavy-lift hexacopter can be controlled successfully, especially when an optimized Elman neural networks as the direct inverse controller system is utilized.
{"title":"Development of an attitude control system of a heavy-lift hexacopter using Elman recurrent neural networks","authors":"B. Kusumoputro, H. Suprijono, M. A. Heryanto, B. Suprapto","doi":"10.1109/IConAC.2016.7604889","DOIUrl":"https://doi.org/10.1109/IConAC.2016.7604889","url":null,"abstract":"Hexacopter is a type of multicopter that can be used to lift a heavy load, hence very convenient to be utilised in agricultural fields. As the consequence, however, the attitude control of this hexacopter is rather difficult compare with that of a quadcopter with four motors, due to gyroscopic effect of the additional motors and in its combination with the heavy loads. In this paper, we have developed a direct inverse controller system using an Elman neural networks for the attitude and altitude control of the hexacopter. Experiments are conducted using a flight data taken from a test-bed system. Results show that the attitude characteritics of the heavy-lift hexacopter can be controlled successfully, especially when an optimized Elman neural networks as the direct inverse controller system is utilized.","PeriodicalId":375052,"journal":{"name":"2016 22nd International Conference on Automation and Computing (ICAC)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114280353","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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