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/incet49848.2020.9154115
Nikita Rajeshkumar Bagrecha, Ishaq Mustafa Polishwala, P. Mehrotra, Rishabh Sharma, B. Thakare
With ever-evolving technologies, the banking systems can update from their traditional methodologies to a digital, immutable, distributed ledger that can be implemented via Blockchain. Blockchain Technology is a distributed peer to peer linked structure which can solve the problem of maintaining and recording transactions in a banking system. Blockchain provides properties like transparency, robustness, auditability, and security. This paper aims at giving these functionalities in a distributed banking system using blockchain, which will be at par with the current methodologies. It will also focus on the limitations while implementing blockchain and future scope.
{"title":"Decentralised Blockchain Technology: Application in Banking Sector","authors":"Nikita Rajeshkumar Bagrecha, Ishaq Mustafa Polishwala, P. Mehrotra, Rishabh Sharma, B. Thakare","doi":"10.1109/incet49848.2020.9154115","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154115","url":null,"abstract":"With ever-evolving technologies, the banking systems can update from their traditional methodologies to a digital, immutable, distributed ledger that can be implemented via Blockchain. Blockchain Technology is a distributed peer to peer linked structure which can solve the problem of maintaining and recording transactions in a banking system. Blockchain provides properties like transparency, robustness, auditability, and security. This paper aims at giving these functionalities in a distributed banking system using blockchain, which will be at par with the current methodologies. It will also focus on the limitations while implementing blockchain and future scope.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"41 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":"132349303","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/incet49848.2020.9154186
C. Z. Basha, B. Lakshmi Pravallika, D. Vineela, S. Prathyusha
Lung cancer, a massively aggressive, quickly metastasizing and widespread disease, is the primary killer among both men and women worldwide. Regrettably, while the incidence of lung cancer decreased steadily in men over the past several years, it has increased alarmingly in women. In Computed Tomography (CT) lung cancer shows up as an isolated nodule. An Automatic Lung Cancer Detection System using improved Haar Wavelet Transform, Scale-Invariant Feature Transform (SIFT), Back Propagation Neural Network (BPNN), and Watershed Segmentation was proposed in this paper. Further, this work involves the usage of Bag of Visual Words (BOVW) based on K means Clustering to the extracted features from SIFT in the previous step. Later, classification is performed using BPNN which is a supervised learning algorithm from the field of Artificial Neural Networks (ANN). Finally, we detect the nodule in the cancerous lung image using watershed segmentation technique. The validation results have been proposed to be 91% accurate when compared to applying different algorithms.
{"title":"An Effective and Robust Cancer Detection in the Lungs with BPNN and Watershed Segmentation","authors":"C. Z. Basha, B. Lakshmi Pravallika, D. Vineela, S. Prathyusha","doi":"10.1109/incet49848.2020.9154186","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154186","url":null,"abstract":"Lung cancer, a massively aggressive, quickly metastasizing and widespread disease, is the primary killer among both men and women worldwide. Regrettably, while the incidence of lung cancer decreased steadily in men over the past several years, it has increased alarmingly in women. In Computed Tomography (CT) lung cancer shows up as an isolated nodule. An Automatic Lung Cancer Detection System using improved Haar Wavelet Transform, Scale-Invariant Feature Transform (SIFT), Back Propagation Neural Network (BPNN), and Watershed Segmentation was proposed in this paper. Further, this work involves the usage of Bag of Visual Words (BOVW) based on K means Clustering to the extracted features from SIFT in the previous step. Later, classification is performed using BPNN which is a supervised learning algorithm from the field of Artificial Neural Networks (ANN). Finally, we detect the nodule in the cancerous lung image using watershed segmentation technique. The validation results have been proposed to be 91% accurate when compared to applying different algorithms.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"26 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":"128097023","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/incet49848.2020.9153986
Achyut Morbekar, Ashi Parihar, R. Jadhav
Agriculture is the cumulative activity for millions of farmers in India. Planters have a wide range of diversity for selecting suitable crops. But due to scarcity of knowledge, farmers are in a daze about kinds of diseases that affect the farm. Many farmers struggle and waste much of their time in reaping diseased crops. The timely assessment of the problem is necessary to avert major damage and enhance production. The proposed system makes use of a novel approach of the object detection technique to detect plant disease, YOLO(You Only Look Once). YOLO processes leaf images at 45 frames per second in real-time, which is faster than other object detection techniques. It divides the image into several grid cells before processing the image. The bounding boxes and class probabilities are predicted by a single neural network in just one evaluation. This effectively boosts the speed and accuracy of disease detection on the leaf.
农业是印度数百万农民的累积活动。种植者在选择合适的作物方面有广泛的多样性。但是由于知识的缺乏，农民对影响农场的各种疾病都很茫然。许多农民在收割有病的作物上挣扎并浪费了大量时间。及时评估问题对于避免重大损失和提高生产是必要的。该系统利用一种新的目标检测技术YOLO(You Only Look Once)来检测植物病害。YOLO实时处理叶子图像的速度为45帧/秒，比其他目标检测技术要快。在对图像进行处理之前，将图像划分为若干网格单元。边界框和类别概率由单个神经网络在一次评估中预测。这有效地提高了叶片疾病检测的速度和准确性。
{"title":"Crop Disease Detection Using YOLO","authors":"Achyut Morbekar, Ashi Parihar, R. Jadhav","doi":"10.1109/incet49848.2020.9153986","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9153986","url":null,"abstract":"Agriculture is the cumulative activity for millions of farmers in India. Planters have a wide range of diversity for selecting suitable crops. But due to scarcity of knowledge, farmers are in a daze about kinds of diseases that affect the farm. Many farmers struggle and waste much of their time in reaping diseased crops. The timely assessment of the problem is necessary to avert major damage and enhance production. The proposed system makes use of a novel approach of the object detection technique to detect plant disease, YOLO(You Only Look Once). YOLO processes leaf images at 45 frames per second in real-time, which is faster than other object detection techniques. It divides the image into several grid cells before processing the image. The bounding boxes and class probabilities are predicted by a single neural network in just one evaluation. This effectively boosts the speed and accuracy of disease detection on the leaf.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"45 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":"128366664","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/incet49848.2020.9154141
Meha Dave, Rutvik Patel, Ishwariy Joshi, B. Goradiya
Technological advancements in the drone sector posed an arduous challenge of enhancing the collisiontolerance competence of an Unmanned Aerial Vehicle(UAV). This paper presents the design and system integration of an IoT-enabled UAV which comprises a 3D designed and printed spherical frame wound across the UAV consisting of a high definition camera that demonstrates processing of the video feed captured using machine learning algorithm. A truncated icosahedron shaped protective frame is designed such that it can bounce and roll in the near proximity of objects as well as humans, thereby proving to be crash-resistant. Hence, it offers close scrutinization, surveying and inspection of various structures and analyses them using a machine learning model. Another novel feature of this UAV is the sensor module composed of various detachable sensors used for applicationspecific purposes like gas-leakage detection, air-quality monitoring, temperature, humidity etc. in confined and complex environments. These features of the UAV, on collaborating with various indoor and outdoor applications contribute towards the versatility of this drone. The UAV is integrated with LoRa modules and is used for seamless connectivity and networking over astonishingly great distances. The final prototype of this design was successfully flight tested numerous times and was found to be efficient, robust and stable.
{"title":"Versatile Multipurpose Crashproof UAV: Machine Learning and IoT approach","authors":"Meha Dave, Rutvik Patel, Ishwariy Joshi, B. Goradiya","doi":"10.1109/incet49848.2020.9154141","DOIUrl":"https://doi.org/10.1109/incet49848.2020.9154141","url":null,"abstract":"Technological advancements in the drone sector posed an arduous challenge of enhancing the collisiontolerance competence of an Unmanned Aerial Vehicle(UAV). This paper presents the design and system integration of an IoT-enabled UAV which comprises a 3D designed and printed spherical frame wound across the UAV consisting of a high definition camera that demonstrates processing of the video feed captured using machine learning algorithm. A truncated icosahedron shaped protective frame is designed such that it can bounce and roll in the near proximity of objects as well as humans, thereby proving to be crash-resistant. Hence, it offers close scrutinization, surveying and inspection of various structures and analyses them using a machine learning model. Another novel feature of this UAV is the sensor module composed of various detachable sensors used for applicationspecific purposes like gas-leakage detection, air-quality monitoring, temperature, humidity etc. in confined and complex environments. These features of the UAV, on collaborating with various indoor and outdoor applications contribute towards the versatility of this drone. The UAV is integrated with LoRa modules and is used for seamless connectivity and networking over astonishingly great distances. The final prototype of this design was successfully flight tested numerous times and was found to be efficient, robust and stable.","PeriodicalId":174411,"journal":{"name":"2020 International Conference for Emerging Technology (INCET)","volume":"120 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":"133860965","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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