Pub Date : 2018-05-03DOI: 10.1109/EIT.2018.8500272
M. Kahlon, S. Ganesan
In this paper, driver drowsiness detection algorithm based on the state of eyes of the driver which is determined by his iris visibility has been implemented. If eyes remain in one state either open or closed longer than expected time as well as if the driver is not looking straight front, it is an indication that driver is drowsy and then the system warns the driver. System is capable of detecting the state of eyes with or without the regular glasses. Matlab with image processing tools has been used to process the image provided by a camera. Matlab creates System Object using Viola_Jones algorithm to detect the objects such as nose, mouth or upper body. After capturing an image, rectangular eyes area was adjusted to reduce the noise. RGB to Gray scale and finally to Binary image conversion is with a suitable threshold value. A median filter was used to reduce the noise and then the image was smoothened. The drowsiness detection is done based on the conditions like Black to White pixels ratio, number of pixels in the column greater than the threshold value and eye's shape. Light and position of the driver plays an important role. System can be set to self-learn at startup to setup threshold values.
{"title":"Driver Drowsiness Detection System Based on Binary Eyes Image Data","authors":"M. Kahlon, S. Ganesan","doi":"10.1109/EIT.2018.8500272","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500272","url":null,"abstract":"In this paper, driver drowsiness detection algorithm based on the state of eyes of the driver which is determined by his iris visibility has been implemented. If eyes remain in one state either open or closed longer than expected time as well as if the driver is not looking straight front, it is an indication that driver is drowsy and then the system warns the driver. System is capable of detecting the state of eyes with or without the regular glasses. Matlab with image processing tools has been used to process the image provided by a camera. Matlab creates System Object using Viola_Jones algorithm to detect the objects such as nose, mouth or upper body. After capturing an image, rectangular eyes area was adjusted to reduce the noise. RGB to Gray scale and finally to Binary image conversion is with a suitable threshold value. A median filter was used to reduce the noise and then the image was smoothened. The drowsiness detection is done based on the conditions like Black to White pixels ratio, number of pixels in the column greater than the threshold value and eye's shape. Light and position of the driver plays an important role. System can be set to self-learn at startup to setup threshold values.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123472095","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500186
Johannes Zenkert, André Klahold, M. Fathi
Multidimensional knowledge representation (MKR) is the result of integrative text mining. Analysis results from individual text mining methods such as named entity recognition, sentiment analysis, or topic detection are represented as dimensions in a knowledge base to support knowledge discovery, visualization or complex computer-aided writing tasks. Extractive text summarization is a content-oriented task which uses available information from text to shorten its length in order to summarize it. In this regard, a MKR knowledge base provides a structure which is applicable as an innovative selection instrument for text summarization. This paper introduces cross-dimensional text summarization based on dimensional selection and filtering of results retrieved from MKR knowledge base.
{"title":"Towards Extractive Text Summarization Using Multidimensional Knowledge Representation","authors":"Johannes Zenkert, André Klahold, M. Fathi","doi":"10.1109/EIT.2018.8500186","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500186","url":null,"abstract":"Multidimensional knowledge representation (MKR) is the result of integrative text mining. Analysis results from individual text mining methods such as named entity recognition, sentiment analysis, or topic detection are represented as dimensions in a knowledge base to support knowledge discovery, visualization or complex computer-aided writing tasks. Extractive text summarization is a content-oriented task which uses available information from text to shorten its length in order to summarize it. In this regard, a MKR knowledge base provides a structure which is applicable as an innovative selection instrument for text summarization. This paper introduces cross-dimensional text summarization based on dimensional selection and filtering of results retrieved from MKR knowledge base.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125192078","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500098
Todd A. Perkins, M. Das
To meet the ever-increasing demands for fuel economy and performance, the once mundane open-loop mechanical torque converter now includes a mechanical bypass clutch that can improve efficiency by controlling the slip speed between the input and output. To control this highly nonlinear system, this paper investigates several single-input-single-output and multi-input-multi-output one-step-ahead control schemes that include weighted and adaptive variants to achieve a balance between tracking error and controller effort.
{"title":"Modeling and Adaptive Control of an Automotive Torque Converter Clutch System","authors":"Todd A. Perkins, M. Das","doi":"10.1109/EIT.2018.8500098","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500098","url":null,"abstract":"To meet the ever-increasing demands for fuel economy and performance, the once mundane open-loop mechanical torque converter now includes a mechanical bypass clutch that can improve efficiency by controlling the slip speed between the input and output. To control this highly nonlinear system, this paper investigates several single-input-single-output and multi-input-multi-output one-step-ahead control schemes that include weighted and adaptive variants to achieve a balance between tracking error and controller effort.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122388930","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500188
Divaakar Siva Baala Sundaram, R. Balasubramani, Suganti Shivaram, Anjani Muthyala, S. P. Arunachalam
Diagnosis and treatment of sleep apnea in its various forms such as obstructive, central and complex syndrome is extremely important to prevent various diseases such as hypertension, diabetes, coronary artery disease, metabolic syndrome, and cerebrovascular diseases. Current methods to detect sleep apnea interfere with sleep and also require long hours of data recording and therefore, single lead ECG based sleep apnea detection is gaining popularity due to its simplicity and practicality for real-time sleep apnea monitoring. The purpose of this research was to test the feasibility of discriminating single lead ECG's with normal sinus rhythm (NSR) and sleep apnea with intrinsic mode function (IMF) complexity index using empirical mode decomposition for real-time detection of sleep apnea. Ten sets of ECG's with NSR and ECG's with sleep apnea were obtained from Physionet database. Custom MATLAB® software was written to compute IMF complexity index for each of the data set and compared for statistical significance test $(mathbf{p} < 0.01)$. The mean IMF complexity for NSR across 10 data sets was $0.41pm 0.06$ and the mean MSF for ECG with sleep apnea was $0.32 pm 0.05$ showing robust discrimination with statistical significance $(mathbf{p} < 0.01)$. IMF complexity robustly discriminates single lead ECG with normal sinus rhythm and sleep apnea. Further validation of this result is required on a larger dataset.
{"title":"Single Lead ECG Discrimination Between Normal Sinus Rhythm and Sleep Apnea with Intrinsic Mode Function Complexity Index Using Empirical Mode Decomposition","authors":"Divaakar Siva Baala Sundaram, R. Balasubramani, Suganti Shivaram, Anjani Muthyala, S. P. Arunachalam","doi":"10.1109/EIT.2018.8500188","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500188","url":null,"abstract":"Diagnosis and treatment of sleep apnea in its various forms such as obstructive, central and complex syndrome is extremely important to prevent various diseases such as hypertension, diabetes, coronary artery disease, metabolic syndrome, and cerebrovascular diseases. Current methods to detect sleep apnea interfere with sleep and also require long hours of data recording and therefore, single lead ECG based sleep apnea detection is gaining popularity due to its simplicity and practicality for real-time sleep apnea monitoring. The purpose of this research was to test the feasibility of discriminating single lead ECG's with normal sinus rhythm (NSR) and sleep apnea with intrinsic mode function (IMF) complexity index using empirical mode decomposition for real-time detection of sleep apnea. Ten sets of ECG's with NSR and ECG's with sleep apnea were obtained from Physionet database. Custom MATLAB® software was written to compute IMF complexity index for each of the data set and compared for statistical significance test $(mathbf{p} < 0.01)$. The mean IMF complexity for NSR across 10 data sets was $0.41pm 0.06$ and the mean MSF for ECG with sleep apnea was $0.32 pm 0.05$ showing robust discrimination with statistical significance $(mathbf{p} < 0.01)$. IMF complexity robustly discriminates single lead ECG with normal sinus rhythm and sleep apnea. Further validation of this result is required on a larger dataset.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126958912","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500165
A. R. Taleqani, K. Nygard, R. Bridgelall, J. Hough
This paper describes a set of real-world potential cyber threats in the aviation industry. Various Machine Learning approaches are available to address security issues in this context. Given the growing number of cyber threats, machine learning has become a promising approach to identify and immunize against such threats.
{"title":"Machine Learning Approach to Cyber Security in Aviation","authors":"A. R. Taleqani, K. Nygard, R. Bridgelall, J. Hough","doi":"10.1109/EIT.2018.8500165","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500165","url":null,"abstract":"This paper describes a set of real-world potential cyber threats in the aviation industry. Various Machine Learning approaches are available to address security issues in this context. Given the growing number of cyber threats, machine learning has become a promising approach to identify and immunize against such threats.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115593075","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500288
A. Denton, Rahul Gomes, D. Franzen
Slope computations in Geographic Information Systems are typically done over windows of sizes as small as $3times 3$ pixels, and the algorithms that are used do not scale to very large windows. Considering the abundance of high-resolution Digital Elevation Model (DEM) data, these algorithms are inadequate for providing high-quality processed data efficiently. We propose an iterative aggregation strategy, in which four values are aggregated in each iteration, and aggregates from previous iterations are reused. Our approach, thereby, scales logarithmically in the size of the windows. It is enabled by the observation that all quantities that are needed for determining slope are linear in the number of data points considered, allowing reuse in the next iteration. We show the usefulness of the proposed strategy for artificial data as well as actual Digital Elevation Model data.
{"title":"Scaling up Window-Based Slope Computations for Geographic Information System","authors":"A. Denton, Rahul Gomes, D. Franzen","doi":"10.1109/EIT.2018.8500288","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500288","url":null,"abstract":"Slope computations in Geographic Information Systems are typically done over windows of sizes as small as $3times 3$ pixels, and the algorithms that are used do not scale to very large windows. Considering the abundance of high-resolution Digital Elevation Model (DEM) data, these algorithms are inadequate for providing high-quality processed data efficiently. We propose an iterative aggregation strategy, in which four values are aggregated in each iteration, and aggregates from previous iterations are reused. Our approach, thereby, scales logarithmically in the size of the windows. It is enabled by the observation that all quantities that are needed for determining slope are linear in the number of data points considered, allowing reuse in the next iteration. We show the usefulness of the proposed strategy for artificial data as well as actual Digital Elevation Model data.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129509560","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500159
Ashwin Arunmozhi, Jungme Park
Autonomous vehicles may be the most significant innovation in transportation since automobiles were first invented. Environmental perception plays a pivotal role in the development of self-driving vehicles which need to navigate in a complex environment of static and dynamic objects. It is required to extract dynamic objects like vehicles and pedestrians more precisely and robustly to estimate the current position, motion and predict its future position. In this article, the performance of three commonly used object detection approaches, Histogram of Oriented Gradients (HOG), Haar-like features and Local Binary Pattern (LBP) is investigated and analyzed using a public dataset of camera images. The detection results show that for the same dataset, LBP features perform better than the other two feature types with a higher detection rate. Finally, a unique and robust detection algorithm using a combination of all the three different feature descriptors and AdaBoost cascade classification is proposed.
{"title":"Comparison of HOG, LBP and Haar-Like Features for On-Road Vehicle Detection","authors":"Ashwin Arunmozhi, Jungme Park","doi":"10.1109/EIT.2018.8500159","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500159","url":null,"abstract":"Autonomous vehicles may be the most significant innovation in transportation since automobiles were first invented. Environmental perception plays a pivotal role in the development of self-driving vehicles which need to navigate in a complex environment of static and dynamic objects. It is required to extract dynamic objects like vehicles and pedestrians more precisely and robustly to estimate the current position, motion and predict its future position. In this article, the performance of three commonly used object detection approaches, Histogram of Oriented Gradients (HOG), Haar-like features and Local Binary Pattern (LBP) is investigated and analyzed using a public dataset of camera images. The detection results show that for the same dataset, LBP features perform better than the other two feature types with a higher detection rate. Finally, a unique and robust detection algorithm using a combination of all the three different feature descriptors and AdaBoost cascade classification is proposed.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125406813","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500243
V. Vasudevan, Guojun Yang, J. Saniie
Navigation to a specific destination indoors can be a challenge due to different reasons such as visual impairment, unknown environments, etc. There has been much work done to solve this issue such as indoor positioning systems, navigation using sensors and even using a robotic guide. In this paper, a novel and straightforward method of path planning (including object avoidance) is presented as a way of navigating to a desired location within a complex environment. The system proposed uses the combination of depth information from an RGB-D camera and the object information from a Neural Network based object identification technique, to efficiently calculate and plan a path in real-time, to a pre-specified destination. Persons to be helped are identified using object detection, and the most practical path to the desired destination is calculated. The path information would be sent to the handheld device of the person being helped in the suitable form of interface, such as visual, audio, etc. The surveillance type nature of the system enables it to help multiple persons in the same area. The model was tested in a controlled environment with one individual person being guided to nearby specified locations. While the testing showed promising results, strong conclusions are yet to be made with the current system.
{"title":"Autonomous Indoor Pathfinding Using Neural Network in Complex Scenes","authors":"V. Vasudevan, Guojun Yang, J. Saniie","doi":"10.1109/EIT.2018.8500243","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500243","url":null,"abstract":"Navigation to a specific destination indoors can be a challenge due to different reasons such as visual impairment, unknown environments, etc. There has been much work done to solve this issue such as indoor positioning systems, navigation using sensors and even using a robotic guide. In this paper, a novel and straightforward method of path planning (including object avoidance) is presented as a way of navigating to a desired location within a complex environment. The system proposed uses the combination of depth information from an RGB-D camera and the object information from a Neural Network based object identification technique, to efficiently calculate and plan a path in real-time, to a pre-specified destination. Persons to be helped are identified using object detection, and the most practical path to the desired destination is calculated. The path information would be sent to the handheld device of the person being helped in the suitable form of interface, such as visual, audio, etc. The surveillance type nature of the system enables it to help multiple persons in the same area. The model was tested in a controlled environment with one individual person being guided to nearby specified locations. While the testing showed promising results, strong conclusions are yet to be made with the current system.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124442273","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500274
Mitch Campion, P. Ranganathan, S. Faruque
The utility of unmanned aerial vehicles (UAVs) has significantly disrupted aviation-related industries. As technology and policy continue to develop, this disruption is likely to continue and become even larger in magnitude. A specific technology poised to disrupt industry is UAV swarm. UAV swarm has the potential to distribute tasks and coordinate operation of many drones with little to no operator intervention. This paper surveys literature regarding UAV swarm and proposes a swarm architecture that will allow for higher levels of swarm autonomy and reliability by utilizing cellular mobile network infrastructure. Additionally, this paper chronicles initial testbed development to meet this proposed architecture. Specific development of higher levels of autonomous swarms with UAV-to-UAV communication and coordination ability is central to advancing the utility of UAV swarms. The use of cellular mobile framework alleviates many limiting factors for UAVs including range of communication, networking challenges, size-weight-and-power (SWaP) considerations, while leveraging a robust and reliable infrastructure for machine to machine (M2M) communication proposed by 5G systems.
{"title":"A Review and Future Directions of UAV Swarm Communication Architectures","authors":"Mitch Campion, P. Ranganathan, S. Faruque","doi":"10.1109/EIT.2018.8500274","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500274","url":null,"abstract":"The utility of unmanned aerial vehicles (UAVs) has significantly disrupted aviation-related industries. As technology and policy continue to develop, this disruption is likely to continue and become even larger in magnitude. A specific technology poised to disrupt industry is UAV swarm. UAV swarm has the potential to distribute tasks and coordinate operation of many drones with little to no operator intervention. This paper surveys literature regarding UAV swarm and proposes a swarm architecture that will allow for higher levels of swarm autonomy and reliability by utilizing cellular mobile network infrastructure. Additionally, this paper chronicles initial testbed development to meet this proposed architecture. Specific development of higher levels of autonomous swarms with UAV-to-UAV communication and coordination ability is central to advancing the utility of UAV swarms. The use of cellular mobile framework alleviates many limiting factors for UAVs including range of communication, networking challenges, size-weight-and-power (SWaP) considerations, while leveraging a robust and reliable infrastructure for machine to machine (M2M) communication proposed by 5G systems.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124536143","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500141
S. P. Gladyshev, P. S. Gladyshev, I. S. Okrainskaya
Under hardware, we consider magnetic circuits, windings, and power electronic circuits of a machine. Under software, we consider algorithms and electrical circuits with low level current for design: direct current, induction, or synchronous machine with wireless rotor. The basic hardware element is one phase machine with magnetic circuit, wireless rotor, and two coils on the stator. One coil used for excitation and another for output application. In the paper, we consider theoretical basics operation of one, or two, or three phase wireless DC and AC machines, when they designed by using the same hardware. The prototype of the two-phase electrical machine based on the two one phase machine placed on the same stator or on the common shaft where designed. Results of verification proves the theoretical results. Advantage of this design is in the simplification of fabrication electrical machines with wireless rotor. In high voltage machines, design machines with common shaft, facilitate isolation problems between different phases.
{"title":"Hardware and Software Technology in Design Electrical DC and AC Machines with Wireless Rotor","authors":"S. P. Gladyshev, P. S. Gladyshev, I. S. Okrainskaya","doi":"10.1109/EIT.2018.8500141","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500141","url":null,"abstract":"Under hardware, we consider magnetic circuits, windings, and power electronic circuits of a machine. Under software, we consider algorithms and electrical circuits with low level current for design: direct current, induction, or synchronous machine with wireless rotor. The basic hardware element is one phase machine with magnetic circuit, wireless rotor, and two coils on the stator. One coil used for excitation and another for output application. In the paper, we consider theoretical basics operation of one, or two, or three phase wireless DC and AC machines, when they designed by using the same hardware. The prototype of the two-phase electrical machine based on the two one phase machine placed on the same stator or on the common shaft where designed. Results of verification proves the theoretical results. Advantage of this design is in the simplification of fabrication electrical machines with wireless rotor. In high voltage machines, design machines with common shaft, facilitate isolation problems between different phases.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125738199","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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