Pub Date : 2020-06-01DOI: 10.1109/incet49848.2020.9154021
Trisha, I. Ali
In the past few years, there has been an exponential growth of Diabetes which is also known as the silent killer [1] and become a major concern for health in our society [2]. The ophthalmologists are looking for methods through which they can easily and automatically detect whether a person is affected by Diabetes or not, instead of spending extensive time on finding it out manually [3]. If they are able to have an early-stage detection of this disease, they can control its severity to a great extent [5]–[8]. The eye can be a vital organ for the detection of diabetes since it is among the fundamental organs which get affected at the earliest stage [9]–[15]. Therefore, analyzing the retina of the eye can act as a gateway for automatically detecting Diabetic Retinopathy (DR). Therefore, we have tried to provide a technique via which, we can effortlessly and efficiently find out whether a person is affected by diabetes or not so that the patient can start the further treatments without wasting their time by going through long and tedious processes of various manual tests for detection of DR [16]–[20]. In order to detect DR, it is important to pinpoint three important regions of the eye. In this paper, we have tried to localize these three important regions of retina that is the Outer Boundary of Retina, the Optic Disk, and the Macula.
{"title":"Intensity Based Optic Disk Detection for Automatic Diabetic Retinopathy","authors":"Trisha, I. Ali","doi":"10.1109/incet49848.2020.9154021","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154021","url":null,"abstract":"In the past few years, there has been an exponential growth of Diabetes which is also known as the silent killer [1] and become a major concern for health in our society [2]. The ophthalmologists are looking for methods through which they can easily and automatically detect whether a person is affected by Diabetes or not, instead of spending extensive time on finding it out manually [3]. If they are able to have an early-stage detection of this disease, they can control its severity to a great extent [5]–[8]. The eye can be a vital organ for the detection of diabetes since it is among the fundamental organs which get affected at the earliest stage [9]–[15]. Therefore, analyzing the retina of the eye can act as a gateway for automatically detecting Diabetic Retinopathy (DR). Therefore, we have tried to provide a technique via which, we can effortlessly and efficiently find out whether a person is affected by diabetes or not so that the patient can start the further treatments without wasting their time by going through long and tedious processes of various manual tests for detection of DR [16]–[20]. In order to detect DR, it is important to pinpoint three important regions of the eye. In this paper, we have tried to localize these three important regions of retina that is the Outer Boundary of Retina, the Optic Disk, and the Macula.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126426856","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9153970
V. J. Govindraj, Y. V, Srinidhi V. Bhat, T. K. Ramesh
In this technologically evolving era, with the transition towards a wireless world, security plays a vital role in ensuring the safety. Over the years various methods have been proposed by researchers across the globe which have proven to be successful but have lacked in areas such as security and authentication time. This paper presents an innovative design for a Smart door with the aid of a biometric NFC band and OTP authentication methods which would provide secure and easy access to our homes. Our idea brings forth the opportunity to mitigate the issues faced by these systems by reducing authentication time with the help of a biometric fingerprint sensor and adds an extra layer of security using the help of a local server to generate OTP authentication. This implementation has shown better results and higher performance rate than existing methods.
{"title":"Smart Door Using Biometric NFC Band and OTP Based Methods","authors":"V. J. Govindraj, Y. V, Srinidhi V. Bhat, T. K. Ramesh","doi":"10.1109/incet49848.2020.9153970","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9153970","url":null,"abstract":"In this technologically evolving era, with the transition towards a wireless world, security plays a vital role in ensuring the safety. Over the years various methods have been proposed by researchers across the globe which have proven to be successful but have lacked in areas such as security and authentication time. This paper presents an innovative design for a Smart door with the aid of a biometric NFC band and OTP authentication methods which would provide secure and easy access to our homes. Our idea brings forth the opportunity to mitigate the issues faced by these systems by reducing authentication time with the help of a biometric fingerprint sensor and adds an extra layer of security using the help of a local server to generate OTP authentication. This implementation has shown better results and higher performance rate than existing methods.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121131176","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154109
Ayush Verma, S. Yadav, Ankita Arora, Kartikey Singh
This paper analyzes performance of Artificial Intelligence based optimization controller for the comparative study of maximum power point tracking (MPPT) in PV Systems. Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) control methods are the two such techniques used, and are simulated in MATLAB-Simulink using Trina Solar TSM-250PD05.08. The simulation results suitably depict the performance of these methods on the basis of some parameters like their rise time, settling time, time taken to reach maximum power point and their efficiency. It is found that maximum power point is tracked in PV systems with greater efficiency using PSO as compared to ANN.
{"title":"Comparison of Maximum Power Tracking using Artificial Intelligence based optimization controller in Photovoltaic Systems","authors":"Ayush Verma, S. Yadav, Ankita Arora, Kartikey Singh","doi":"10.1109/incet49848.2020.9154109","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154109","url":null,"abstract":"This paper analyzes performance of Artificial Intelligence based optimization controller for the comparative study of maximum power point tracking (MPPT) in PV Systems. Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) control methods are the two such techniques used, and are simulated in MATLAB-Simulink using Trina Solar TSM-250PD05.08. The simulation results suitably depict the performance of these methods on the basis of some parameters like their rise time, settling time, time taken to reach maximum power point and their efficiency. It is found that maximum power point is tracked in PV systems with greater efficiency using PSO as compared to ANN.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127186273","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154088
Ravneet Punia, L. Kumar, Mohd. Mujahid, Rajesh Rohilla
COVID-19 is spreading rapidly throughout the world. As of 14 April 2020, 128,000 people died of COVID-19, while 1.99 million cases in 210 countries and territories were reported in 219.747 cases. As the virus spreads at a very high rate, there is a huge shortage of medical testing kits all over the world. The respiratory system is the part of the human body most affected by the virus, so the use of X-rays of the chest may prove to be a more efficient way than the thermal screening of the human body. In this paper, we are trying to develop a method that uses radiology, i.e. X-rays for detecting the novel coronavirus. Along with the paper, we also release a dataset for the research community and further development extracted from various medical research hospital facilities treating COVID-19 patients.
{"title":"Computer Vision and Radiology for COVID-19 Detection","authors":"Ravneet Punia, L. Kumar, Mohd. Mujahid, Rajesh Rohilla","doi":"10.1109/incet49848.2020.9154088","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154088","url":null,"abstract":"COVID-19 is spreading rapidly throughout the world. As of 14 April 2020, 128,000 people died of COVID-19, while 1.99 million cases in 210 countries and territories were reported in 219.747 cases. As the virus spreads at a very high rate, there is a huge shortage of medical testing kits all over the world. The respiratory system is the part of the human body most affected by the virus, so the use of X-rays of the chest may prove to be a more efficient way than the thermal screening of the human body. In this paper, we are trying to develop a method that uses radiology, i.e. X-rays for detecting the novel coronavirus. Along with the paper, we also release a dataset for the research community and further development extracted from various medical research hospital facilities treating COVID-19 patients.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"46 13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126843488","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154023
G. Sebastian, D. N. Kyatanavar
Model preparation of evaporation process and optimizing the same have been a challenging task for researchers. Evaporation process in sugar industries is characterized by its highly non-linear nature and conventional control strategies do not yield good results for the control of the same. With the evaporator being the most energy consuming unit in sugar manufacturing process, it has direct impact on sugar quality as well as steam economy. In this paper, a simulation model of an evaporator having four effects has been developed in Simulink. For optimizing this model, Taguchi technique combined with Grey relational analysis has been employed. The level of influence of variables like Temperature of the feed, Rate of flow of the feed and Rate of steam flow, on the steam economy and sugarcane juice concentration has been determined using ANOVA (Analysis of Variance). Minitab 17 software has been used for this. Finally, the relative contribution of each process parameter on the performance characteristics of the evaporator has also been determined.
{"title":"Modeling and Optimization of Evaporation Process in Sugar Industries","authors":"G. Sebastian, D. N. Kyatanavar","doi":"10.1109/incet49848.2020.9154023","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154023","url":null,"abstract":"Model preparation of evaporation process and optimizing the same have been a challenging task for researchers. Evaporation process in sugar industries is characterized by its highly non-linear nature and conventional control strategies do not yield good results for the control of the same. With the evaporator being the most energy consuming unit in sugar manufacturing process, it has direct impact on sugar quality as well as steam economy. In this paper, a simulation model of an evaporator having four effects has been developed in Simulink. For optimizing this model, Taguchi technique combined with Grey relational analysis has been employed. The level of influence of variables like Temperature of the feed, Rate of flow of the feed and Rate of steam flow, on the steam economy and sugarcane juice concentration has been determined using ANOVA (Analysis of Variance). Minitab 17 software has been used for this. Finally, the relative contribution of each process parameter on the performance characteristics of the evaporator has also been determined.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127613156","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154016
P. Raikar, S. Joshi
The field of machine learning is growing in modern times, computational models are able to go beyond the performance of previous forms of artificial intelligence. The use of evaluation model ,selection of model and algorithm selecting techniques play an major role in machine learning study and also in field of industries. In this work, we made evaluation of various supervised, unsupervised machine learning classifiers for flower datasets. We made use of local features such as Histogram of gradient , Kaze, Local binary pattern(LBP) ,Oriented Fast and Rotated Brief( ORB), global features like Color Histograms, Haralick Textures , Hu Moments , fusion of both and Bag of visual words(BOVW) using Vocabulary builder K-Means clustering which represents color ,texture, shape features of image. Experiment is carried out on 20 classes of flower datasets with 100 images each. .Flower datasets have many characteristic in common like sunflower will be similar to daffodil in terms of color and texture .Hence to quantify the image we need to combine different feature descriptors like color, texture and shape features. We develop a Content based classification system to find efficiency comparison of different machine learning algorithms for classification and retrieval problems. Eleven classifiers mainly Support Vector Machine, K Nearest Neighbor, Gaussian Naive Bayes , CART, Kmeans, Linear Discriminant Analysis, Adaboost ,Logistic Regression, MLP, Random Forest, CNN are analyzed on the shape, color ,texture features. Experimentation are carried out and results are recorded using CPU as well as GPU on google cobalatory platform.
{"title":"Efficiency Comparison of Supervised and Unsupervised Classifier on Content Based Classification using Shape, Color, Texture","authors":"P. Raikar, S. Joshi","doi":"10.1109/incet49848.2020.9154016","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154016","url":null,"abstract":"The field of machine learning is growing in modern times, computational models are able to go beyond the performance of previous forms of artificial intelligence. The use of evaluation model ,selection of model and algorithm selecting techniques play an major role in machine learning study and also in field of industries. In this work, we made evaluation of various supervised, unsupervised machine learning classifiers for flower datasets. We made use of local features such as Histogram of gradient , Kaze, Local binary pattern(LBP) ,Oriented Fast and Rotated Brief( ORB), global features like Color Histograms, Haralick Textures , Hu Moments , fusion of both and Bag of visual words(BOVW) using Vocabulary builder K-Means clustering which represents color ,texture, shape features of image. Experiment is carried out on 20 classes of flower datasets with 100 images each. .Flower datasets have many characteristic in common like sunflower will be similar to daffodil in terms of color and texture .Hence to quantify the image we need to combine different feature descriptors like color, texture and shape features. We develop a Content based classification system to find efficiency comparison of different machine learning algorithms for classification and retrieval problems. Eleven classifiers mainly Support Vector Machine, K Nearest Neighbor, Gaussian Naive Bayes , CART, Kmeans, Linear Discriminant Analysis, Adaboost ,Logistic Regression, MLP, Random Forest, CNN are analyzed on the shape, color ,texture features. Experimentation are carried out and results are recorded using CPU as well as GPU on google cobalatory platform.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"115 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114041677","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154177
H. Rakesh, G. Sunitha
In today's smart and fast computing world, the designing of high speed and low energy consumption based Digital Signal Processors (DSPs) is a realistic and ever embryonic area of research. Conversely, the design of a proficient Digital Signal Processor intended to carry out the complex computations associated with image processing or signal processing involves the design of an efficient Multiply-Accumulate (MAC) unit which is one of the most vital blocks of processor. The multiplier, adder, accumulator are the fundamental construction sub-units for MAC units. Moreover, the computation carried out with the extensive and appropriate usage of Vedic Mathematics is set up to be well proficient and capable as compared to the basic Mathematics. This paper has presented the implementation of novel 32-bit MAC unit consisting of Vedic Multiplier using Urdhva Tiryakbhyam sutra and efficient adder circuit using Modified Weinberger adder technique. From comparative analysis, the MAC unit designed was found to be proficient in terms of delay and energy consumed.
{"title":"Design and Implementation of Novel 32-Bit MAC Unit for DSP Applications","authors":"H. Rakesh, G. Sunitha","doi":"10.1109/incet49848.2020.9154177","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154177","url":null,"abstract":"In today's smart and fast computing world, the designing of high speed and low energy consumption based Digital Signal Processors (DSPs) is a realistic and ever embryonic area of research. Conversely, the design of a proficient Digital Signal Processor intended to carry out the complex computations associated with image processing or signal processing involves the design of an efficient Multiply-Accumulate (MAC) unit which is one of the most vital blocks of processor. The multiplier, adder, accumulator are the fundamental construction sub-units for MAC units. Moreover, the computation carried out with the extensive and appropriate usage of Vedic Mathematics is set up to be well proficient and capable as compared to the basic Mathematics. This paper has presented the implementation of novel 32-bit MAC unit consisting of Vedic Multiplier using Urdhva Tiryakbhyam sutra and efficient adder circuit using Modified Weinberger adder technique. From comparative analysis, the MAC unit designed was found to be proficient in terms of delay and energy consumed.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121072066","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154078
I. Garg, Hritik Solanki, Sushma Verma
Speech recognition system has the ability to recognize and interpret lexis in a spoken language and transcript the same. With all the available uses of such system, in this paper, light is shed on another use in automating the applications that manage documents and presentations and a solution is proposed for implementing the same, developed in python programming language that can benefit the regular users as well as the elderly and visually-impaired.
{"title":"Automation and Presentation of Word Document Using Speech Recognition","authors":"I. Garg, Hritik Solanki, Sushma Verma","doi":"10.1109/incet49848.2020.9154078","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154078","url":null,"abstract":"Speech recognition system has the ability to recognize and interpret lexis in a spoken language and transcript the same. With all the available uses of such system, in this paper, light is shed on another use in automating the applications that manage documents and presentations and a solution is proposed for implementing the same, developed in python programming language that can benefit the regular users as well as the elderly and visually-impaired.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"63 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116025732","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9154189
S. Kurnaz, Mohammed Sami Mohammed, S. Mohammed
In spite of availability of patient's data in hospitals, health care institute and websites but still hard to collected especially for a risk disease like thyroid disorders. A new model by using Non Sorting Genetic Algorithm are selected for rows reductions and attributes selected with a three data mining techniques for a faster and accurate thyroid disorders detection. Two types of thyroid disorders with 4 different classes for each type are used for this design, in addition 500+972 are used with 29 attributes as training and testing data respectively with cross validation=5. Performances of this model are measured by using some parameter as accuracy , precision , etc. This model is studied for using all/some features with the proposed model and compare it with Sequential model. A scatter plot and area under curve are also presented in this work for training data to show the classes predication enhancement.
{"title":"A High Efficiency Thyroid Disorders Prediction System with Non-Dominated Sorting Genetic Algorithm NSGA-II as a Feature Selection Algorithm","authors":"S. Kurnaz, Mohammed Sami Mohammed, S. Mohammed","doi":"10.1109/incet49848.2020.9154189","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154189","url":null,"abstract":"In spite of availability of patient's data in hospitals, health care institute and websites but still hard to collected especially for a risk disease like thyroid disorders. A new model by using Non Sorting Genetic Algorithm are selected for rows reductions and attributes selected with a three data mining techniques for a faster and accurate thyroid disorders detection. Two types of thyroid disorders with 4 different classes for each type are used for this design, in addition 500+972 are used with 29 attributes as training and testing data respectively with cross validation=5. Performances of this model are measured by using some parameter as accuracy , precision , etc. This model is studied for using all/some features with the proposed model and compare it with Sequential model. A scatter plot and area under curve are also presented in this work for training data to show the classes predication enhancement.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114269583","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 : 2020-06-01DOI: 10.1109/incet49848.2020.9153987
Rutuja T. Lotekar, R. D. Kulkarni, Gaurava Deep Srivastava
The paper represents design considerations and simulation of a digital control system for six pulse thyristorised rectifier. This rectifier is used to power the thermal hydraulic based R&D experimental facilities to simulate the power and temperature transients occurs in nuclear reactor. In order to maintain precisely the predetermined value of DC output power/output current for simulated nuclear fuel channel of experimental facility, an appropriate digital controller has been designed for generating pulses for triggering thyristors. Design calculations for configuring six pulse thyristorised rectifier system has been presented. The simulation of closed loop feedback control mechanism has been performed using circuit simulation software and the simulation results including waveforms have been highlighted in the paper.
{"title":"Design, Analysis and Simulation of Six-Pulse Thyristorised Rectifier using Digital Controller","authors":"Rutuja T. Lotekar, R. D. Kulkarni, Gaurava Deep Srivastava","doi":"10.1109/incet49848.2020.9153987","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9153987","url":null,"abstract":"The paper represents design considerations and simulation of a digital control system for six pulse thyristorised rectifier. This rectifier is used to power the thermal hydraulic based R&D experimental facilities to simulate the power and temperature transients occurs in nuclear reactor. In order to maintain precisely the predetermined value of DC output power/output current for simulated nuclear fuel channel of experimental facility, an appropriate digital controller has been designed for generating pulses for triggering thyristors. Design calculations for configuring six pulse thyristorised rectifier system has been presented. The simulation of closed loop feedback control mechanism has been performed using circuit simulation software and the simulation results including waveforms have been highlighted in the paper.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115162045","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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