Pub Date : 2017-08-01DOI: 10.1109/ISITIA.2017.8124099
Muhammad Sipan, N. S. M. Susiki, E. M. Yuniarno
Colorization is a coloring process in the image or video, which is done to provide detail and clarity to the image or video. This study used image gray scale to be colored by matching both color image pixel blocks and grayscale images based on GLCM texture feature (gray level co-occurance matrix) using a sum of absolute difference. Color image blocks are used as templates and grayscale image blocks as targets, searching for similarities between two image blocks by subtracting both GLCM texture feature values and comparing the target of GLCM value with the template value to obtain the smallest or near-zero value in the color block. The smallest in the color image block is a pair of grayscale image blocks, as both have similar features of the GLCM texture. Further, color of color image blocks are transferred to the grayscale block in accordance with the existing resemblance (pair), until all areas that have similarity are colored.
{"title":"Image block matching based on GLCM (gray level co-occurence matrix) texture feature on grayscale image auto coloring","authors":"Muhammad Sipan, N. S. M. Susiki, E. M. Yuniarno","doi":"10.1109/ISITIA.2017.8124099","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124099","url":null,"abstract":"Colorization is a coloring process in the image or video, which is done to provide detail and clarity to the image or video. This study used image gray scale to be colored by matching both color image pixel blocks and grayscale images based on GLCM texture feature (gray level co-occurance matrix) using a sum of absolute difference. Color image blocks are used as templates and grayscale image blocks as targets, searching for similarities between two image blocks by subtracting both GLCM texture feature values and comparing the target of GLCM value with the template value to obtain the smallest or near-zero value in the color block. The smallest in the color image block is a pair of grayscale image blocks, as both have similar features of the GLCM texture. Further, color of color image blocks are transferred to the grayscale block in accordance with the existing resemblance (pair), until all areas that have similarity are colored.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129508707","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124093
Fathurrozi Winjaya, M. Rivai, D. Purwanto
Many methods of coffee roasting in the market today are only based on the temperature in the certain time period. However, if the coffee beans have no uniformity in size, weight, and moisture, the roasting process will not produce the consistent results. In this study, the measurement and identification of cracking sounds of coffee beans under roasting are applied to determine the temperature control mechanism. Roaster uses an oven-type controlled by heating element at a temperature of 260°C. In the roasting process, there are the first and second cracking sounds in the time span of 3–10 minutes. Voice Activity Detection is used to identify the cracking sound using Fast Fourier Transform to determine the starting point of sound recording. The data would be learned by the Neural Network to recognize the cracking sounds automatically. The Neural Network can obtain the best result during the period of 1-second recording with success rate of 100%.
{"title":"Identification of cracking sound during coffee roasting using neural network","authors":"Fathurrozi Winjaya, M. Rivai, D. Purwanto","doi":"10.1109/ISITIA.2017.8124093","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124093","url":null,"abstract":"Many methods of coffee roasting in the market today are only based on the temperature in the certain time period. However, if the coffee beans have no uniformity in size, weight, and moisture, the roasting process will not produce the consistent results. In this study, the measurement and identification of cracking sounds of coffee beans under roasting are applied to determine the temperature control mechanism. Roaster uses an oven-type controlled by heating element at a temperature of 260°C. In the roasting process, there are the first and second cracking sounds in the time span of 3–10 minutes. Voice Activity Detection is used to identify the cracking sound using Fast Fourier Transform to determine the starting point of sound recording. The data would be learned by the Neural Network to recognize the cracking sounds automatically. The Neural Network can obtain the best result during the period of 1-second recording with success rate of 100%.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"10 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115560896","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124081
Umesh Kumar Soni, R. K. Tripathi
In this paper the phase back EMF Zero Difference Point (ZDP) detection based sensorless control has been applied with the estimated back EMF using unknown input observer. The performance of VSI fed BLDC has been studied with various load torque and input speed reference. The phase to phase back EMFs estimated by the unknown input observer is used in place of Phase back EMF differences to get Zero Difference Points (ZDP). The proposed method has improved performance due to low to extra high speed precise control together with zero speed starting. This method is sensing fault tolerant and has excellent robustness towards noise in the estimated variables.
{"title":"Novel estimated back EMF ZDP based sensorless controlled BLDCM using unknown input observer","authors":"Umesh Kumar Soni, R. K. Tripathi","doi":"10.1109/ISITIA.2017.8124081","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124081","url":null,"abstract":"In this paper the phase back EMF Zero Difference Point (ZDP) detection based sensorless control has been applied with the estimated back EMF using unknown input observer. The performance of VSI fed BLDC has been studied with various load torque and input speed reference. The phase to phase back EMFs estimated by the unknown input observer is used in place of Phase back EMF differences to get Zero Difference Points (ZDP). The proposed method has improved performance due to low to extra high speed precise control together with zero speed starting. This method is sensing fault tolerant and has excellent robustness towards noise in the estimated variables.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115566590","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124076
T. Taufik, R. Muchtar, Mohammad Taufik
When integrating multiple sources to supply power to a single load, it is necessary to ensure that excess power available from a single source does not flow into the other sources. This is commonly done with OR diodes placed for each source being used. Despite its simplicity, this protection method suffers apparent efficiency loss through the diodes, especially when large current is involved. This paper discusses other and less intuitive consequences of using OR Diodes including distortion, system versatility, and cost in component sizing. Results of our study show that these consequences are largely resultant of unequal power sharing between the sources to power the load and are more prominent as the difference in presented input voltages increases.
{"title":"Performance analysis of multiple input boost converter with inherent OR diode configuration","authors":"T. Taufik, R. Muchtar, Mohammad Taufik","doi":"10.1109/ISITIA.2017.8124076","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124076","url":null,"abstract":"When integrating multiple sources to supply power to a single load, it is necessary to ensure that excess power available from a single source does not flow into the other sources. This is commonly done with OR diodes placed for each source being used. Despite its simplicity, this protection method suffers apparent efficiency loss through the diodes, especially when large current is involved. This paper discusses other and less intuitive consequences of using OR Diodes including distortion, system versatility, and cost in component sizing. Results of our study show that these consequences are largely resultant of unequal power sharing between the sources to power the load and are more prominent as the difference in presented input voltages increases.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116041497","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124109
Z. E. Fitri, I. Purnama, Eko Pramunanto, Mauridhi Hery Pumomo
Thrombocyte disease is usually caused by abnormalities, such as abnormalities based on the number and morphological deformities of platelets. Examples of platelet abnormalities include small platelets in Wiskottldrich syndrome, giant platelets in some chronic myeloproliferative diseases, Benard Soulier syndrome and Macrothrombocytopenia in gray platelet syndrome. The usual problem of automatic FBC analysis is that undetectable morphological abnormalities of platelets so the microscopic examination is required using peripheral blood smear. But microscopic examination also has some weakness such as subjective depend on medical analyst/pathologist. We propose an accurate method to classify plateles from digitalization microscopic peripheral blood smear using combination of second order statistic feature extraction and comparing several methods. The comparing methods are K-Nearest Neighbor (KNN) and Learning Vector Quantization (LVQ). In this feature extraction, we use Gray Level Co-occurrence Matrix (GLCM) to get Angular Second Moment (ASM), Invers Different Moment (IDM) and entropi values. Those values will be inserted as input in KNN classifier method to classify blood cell in peripheral blood smear. Classify of cells based on feature extraction values is divided into three classes (leukocytes, normal platelets and giant platelets). Based on the result of experiments, both of methods can classify platelets on all color channels with average accuracy are 83.67% for KNN and 74.75% for LVQ. So, The KNN classification method is better able than LVQ to classify platelets in peripheral blood smear.
{"title":"A comparison of platelets classification from digitalization microscopic peripheral blood smear","authors":"Z. E. Fitri, I. Purnama, Eko Pramunanto, Mauridhi Hery Pumomo","doi":"10.1109/ISITIA.2017.8124109","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124109","url":null,"abstract":"Thrombocyte disease is usually caused by abnormalities, such as abnormalities based on the number and morphological deformities of platelets. Examples of platelet abnormalities include small platelets in Wiskottldrich syndrome, giant platelets in some chronic myeloproliferative diseases, Benard Soulier syndrome and Macrothrombocytopenia in gray platelet syndrome. The usual problem of automatic FBC analysis is that undetectable morphological abnormalities of platelets so the microscopic examination is required using peripheral blood smear. But microscopic examination also has some weakness such as subjective depend on medical analyst/pathologist. We propose an accurate method to classify plateles from digitalization microscopic peripheral blood smear using combination of second order statistic feature extraction and comparing several methods. The comparing methods are K-Nearest Neighbor (KNN) and Learning Vector Quantization (LVQ). In this feature extraction, we use Gray Level Co-occurrence Matrix (GLCM) to get Angular Second Moment (ASM), Invers Different Moment (IDM) and entropi values. Those values will be inserted as input in KNN classifier method to classify blood cell in peripheral blood smear. Classify of cells based on feature extraction values is divided into three classes (leukocytes, normal platelets and giant platelets). Based on the result of experiments, both of methods can classify platelets on all color channels with average accuracy are 83.67% for KNN and 74.75% for LVQ. So, The KNN classification method is better able than LVQ to classify platelets in peripheral blood smear.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122499582","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124066
D. Leng, Kittichot Soontorntaweesub, S. Polmai
The energy crisis and environmental concern lead to widely use of renewable energy sources in form of microgrid. The intermittent nature of the microgrid's sources and the altering behaviors of loads result to unstable of the system's voltage and frequency as well as the system reliability. The purpose of this paper is to develop real-time control based decentralizing technique for handling the challenging issues of the microgrid. Two levels distributed control is proposed. A modify droop control and frequency restoration is implemented as low-level control. The upper-level, a multiagent system is developed and it is the main control method in the research. The agents are implemented using Boris based on C#.NET language. The multiagent system consists of four main agents such as CONTROL agent, DER Agent, RENEW agent and LOAD agent. To evaluate the control performance, the microgrid testbed has been built. The results prove the effectiveness of real-time control to stabilize, monitor, improve system reliability and provide the microgrid intelligent operation.
{"title":"Multi-agent system based real-time control for standalone microgrid","authors":"D. Leng, Kittichot Soontorntaweesub, S. Polmai","doi":"10.1109/ISITIA.2017.8124066","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124066","url":null,"abstract":"The energy crisis and environmental concern lead to widely use of renewable energy sources in form of microgrid. The intermittent nature of the microgrid's sources and the altering behaviors of loads result to unstable of the system's voltage and frequency as well as the system reliability. The purpose of this paper is to develop real-time control based decentralizing technique for handling the challenging issues of the microgrid. Two levels distributed control is proposed. A modify droop control and frequency restoration is implemented as low-level control. The upper-level, a multiagent system is developed and it is the main control method in the research. The agents are implemented using Boris based on C#.NET language. The multiagent system consists of four main agents such as CONTROL agent, DER Agent, RENEW agent and LOAD agent. To evaluate the control performance, the microgrid testbed has been built. The results prove the effectiveness of real-time control to stabilize, monitor, improve system reliability and provide the microgrid intelligent operation.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128143341","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124098
A. N. Rumaksari, S. Sumpeno, A. Wibawa
Many applications of computer vision, motion captures nowadays are an active research field. Supported by camera innovation in high definition technology and high-speed processing unit technology make higher degree on object detection standard. We can see it from the increasing number of new methods that have improvement in accuracy. In automatic vehicle surveillance area, Spatial Mixture Gaussian model becomes well-known moving based object detection via background subtraction technique in this decades. This method models particular pixel as mixture of Gaussians distribution with regard to pixel's higher probability of occurrences and variance of each Gaussians in the mixture model. Although, this model has threshold to control the sensitivity of object's motion, it has problem with separating an object from its shadow. This is happening because the shadow attaches to the object. Since they always move in tandem, as the result, detected object area will merge and shadow and object will form into a single unity that is difficult to separate. In accordance with detection, occluded object because of a shadow will decrease detector's accuracy. Therefore, we need to remove shadow, in order to maintain detector's quality of accuracy. Challenge in doing so is there is exist dynamic illumination condition which resulting a nonuniform shadow pixel value. This can cause failure of threshold-based linear shadow casting technique. To solve above-mentioned problem, we need a shadow filter that can adapt to the illumination changes. In this experiment, we have successfully implemented an adaptive shadow filter based on DSD algorithm to improve background subtraction method. Our proposed method has a stable result in outdoor environment dataset and it is proven to be able applied to traffic surveillance video application.
{"title":"Background subtraction using spatial mixture of Gaussian model with dynamic shadow filtering","authors":"A. N. Rumaksari, S. Sumpeno, A. Wibawa","doi":"10.1109/ISITIA.2017.8124098","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124098","url":null,"abstract":"Many applications of computer vision, motion captures nowadays are an active research field. Supported by camera innovation in high definition technology and high-speed processing unit technology make higher degree on object detection standard. We can see it from the increasing number of new methods that have improvement in accuracy. In automatic vehicle surveillance area, Spatial Mixture Gaussian model becomes well-known moving based object detection via background subtraction technique in this decades. This method models particular pixel as mixture of Gaussians distribution with regard to pixel's higher probability of occurrences and variance of each Gaussians in the mixture model. Although, this model has threshold to control the sensitivity of object's motion, it has problem with separating an object from its shadow. This is happening because the shadow attaches to the object. Since they always move in tandem, as the result, detected object area will merge and shadow and object will form into a single unity that is difficult to separate. In accordance with detection, occluded object because of a shadow will decrease detector's accuracy. Therefore, we need to remove shadow, in order to maintain detector's quality of accuracy. Challenge in doing so is there is exist dynamic illumination condition which resulting a nonuniform shadow pixel value. This can cause failure of threshold-based linear shadow casting technique. To solve above-mentioned problem, we need a shadow filter that can adapt to the illumination changes. In this experiment, we have successfully implemented an adaptive shadow filter based on DSD algorithm to improve background subtraction method. Our proposed method has a stable result in outdoor environment dataset and it is proven to be able applied to traffic surveillance video application.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123040613","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124056
Trisna Wati, R. S. Wibowo, O. Penangsang
Economic Dispatch (ED) is an important aspect in any power system. The conventional methods for solving ED include Lambda-Iterative, Newton-Raphson, Quadratic programming (QP), etc. However, conventional method cannot solved non quadratic function. The input-output characteristics of a generator produced highly non-linear leading so its challenging non-convex and non-smooth optimization problem. In this paper, combine QP and Particle Swarm Optimization (PSO) to solve economic dispatch with valve point effect. The initial PSO population is obtained from the QP. The convergence of QP-PSO has a good performance and near global minimum.
{"title":"Hybrid QP-PSO for solving economic dispatch with valve point effect","authors":"Trisna Wati, R. S. Wibowo, O. Penangsang","doi":"10.1109/ISITIA.2017.8124056","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124056","url":null,"abstract":"Economic Dispatch (ED) is an important aspect in any power system. The conventional methods for solving ED include Lambda-Iterative, Newton-Raphson, Quadratic programming (QP), etc. However, conventional method cannot solved non quadratic function. The input-output characteristics of a generator produced highly non-linear leading so its challenging non-convex and non-smooth optimization problem. In this paper, combine QP and Particle Swarm Optimization (PSO) to solve economic dispatch with valve point effect. The initial PSO population is obtained from the QP. The convergence of QP-PSO has a good performance and near global minimum.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127862435","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124107
Adi Dwi Irwan Falih, W. A. Dharma, S. Sumpeno
The wheelchair is still a mobility aids commonly used by patients with muscle weakness or stroke patients. Some stroke patients, having constraints in moving a joystick or controlling an electric wheelchair due to muscle limitations of their hands Myo-armband, as wearable device that have an Electromyogram sensor can be used as an alternative in controlling the electric device like wheelchair more easily. The Electromyography Research (EMG) on feature of particular muscle activation pattern which has correlation with a motion contributes inspiration to be applied as motion control media on electric wheelchair. Classification process of EMG will be a new alternative to control wheelchair movement for user or patient who hasn't latitude to move their limb and just able to do easy motion using their forearm. The stages of this project is detecting signal in the muscle using EMG, extracting feature of muscle response in time domain base, and be classified by Naïve Bayes, the dataset classification is pinned in raspberry and output to arduino controller to be used as output motion in motor of electric wheelchair. The result of this research is classification of MAV feature, Peak number, RMS and Gradient Magnitude in 275 stream of muscle data show that detected and correctly can be discriminate 90.18%, thus, a sum of 248 instances and wrongly 9.8182% a sum of 27 instances.
{"title":"Classification of EMG signals from forearm muscles as automatic control using Naive Bayes","authors":"Adi Dwi Irwan Falih, W. A. Dharma, S. Sumpeno","doi":"10.1109/ISITIA.2017.8124107","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124107","url":null,"abstract":"The wheelchair is still a mobility aids commonly used by patients with muscle weakness or stroke patients. Some stroke patients, having constraints in moving a joystick or controlling an electric wheelchair due to muscle limitations of their hands Myo-armband, as wearable device that have an Electromyogram sensor can be used as an alternative in controlling the electric device like wheelchair more easily. The Electromyography Research (EMG) on feature of particular muscle activation pattern which has correlation with a motion contributes inspiration to be applied as motion control media on electric wheelchair. Classification process of EMG will be a new alternative to control wheelchair movement for user or patient who hasn't latitude to move their limb and just able to do easy motion using their forearm. The stages of this project is detecting signal in the muscle using EMG, extracting feature of muscle response in time domain base, and be classified by Naïve Bayes, the dataset classification is pinned in raspberry and output to arduino controller to be used as output motion in motor of electric wheelchair. The result of this research is classification of MAV feature, Peak number, RMS and Gradient Magnitude in 275 stream of muscle data show that detected and correctly can be discriminate 90.18%, thus, a sum of 248 instances and wrongly 9.8182% a sum of 27 instances.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132740808","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 : 2017-08-01DOI: 10.1109/ISITIA.2017.8124071
N. Tung, Nguyễn Quang Việt
In the context of development quickly in recent period, electric power system in Viet Nam, with the power system load increases fastly, this resulted in the phenomenon of increased short circuit current value (NM) on grid. The fast development of the power source in recent period and the increasing power system load have led to rapid rising of short circuit current value on the grid. It existed already many points on the grid where short circuit current values exceed the allowed value. [1]. This article aims at searching, giving out the solutions for limiting the short circuit current on Viet Nam grid by installing a Resistive Fault Current Limiter (R-FCL) into neutral conductor of the transformer. This solution is carried out with the following steps: (1)establishing calculating method for installed resistant value, (2) Simulating grid involved resistive current fault limiter, (3) installing limiter apparatus on the real grid with the Resistant product provided by Bolid manufacturer[2], (4) Comparing the experimental result with the simulating results with the simulating results. This would give out the solution for limiting short circuit current applied in a case on Viet Nam grid-110 Kv Binh An transformer substation. The results have shown high effectiveness of applying R-FCL on Viet Nam grid.
{"title":"Effect on fault current lever reduction by using resistive fault current limiter in 110 kV Binh an substation","authors":"N. Tung, Nguyễn Quang Việt","doi":"10.1109/ISITIA.2017.8124071","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124071","url":null,"abstract":"In the context of development quickly in recent period, electric power system in Viet Nam, with the power system load increases fastly, this resulted in the phenomenon of increased short circuit current value (NM) on grid. The fast development of the power source in recent period and the increasing power system load have led to rapid rising of short circuit current value on the grid. It existed already many points on the grid where short circuit current values exceed the allowed value. [1]. This article aims at searching, giving out the solutions for limiting the short circuit current on Viet Nam grid by installing a Resistive Fault Current Limiter (R-FCL) into neutral conductor of the transformer. This solution is carried out with the following steps: (1)establishing calculating method for installed resistant value, (2) Simulating grid involved resistive current fault limiter, (3) installing limiter apparatus on the real grid with the Resistant product provided by Bolid manufacturer[2], (4) Comparing the experimental result with the simulating results with the simulating results. This would give out the solution for limiting short circuit current applied in a case on Viet Nam grid-110 Kv Binh An transformer substation. The results have shown high effectiveness of applying R-FCL on Viet Nam grid.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133436361","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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