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RISS 인기검색어
- 검색키워드
- 주제어 : Parallel-connected devices (검색결과 6 건)
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Influence of Device Parameters Spread on Current Distribution of Paralleled Silicon Carbide MOSFETs
Ke, Junji,Zhao, Zhibin,Sun, Peng,Huang, Huazhen,Abuogo, James,Cui, Xiang The Korean Institute of Power Electronics 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.4
This paper systematically investigates the influence of device parameters spread on the current distribution of paralleled silicon carbide (SiC) MOSFETs. First, a variation coefficient is introduced and used as the evaluating norm for the parameters spread. Then a sample of 30 SiC MOSFET devices from the same batch of a well-known company is selected and tested under the same conditions as those on datasheet. It is found that there is big difference among parameters spread. Furthermore, comprehensive theoretical and simulation analyses are carried out to study the sensitivity of the current imbalance to variations of the device parameters. Based on the concept of the control variable method, the influence of each device parameter on the steady-state and transient current distributions of paralleled SiC MOSFETs are verified separately by experiments. Finally, some screening suggestions of devices or chips before parallel-connection are provided in terms of different applications and different driver configurations.
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Influence of Device Parameters Spread on Current Distribution of Paralleled Silicon Carbide MOSFETs
Junji Ke,Zhibin Zhao,Peng Sun,Huazhen Huang,James Abuogo,Xiang Cui 전력전자학회 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.4
This paper systematically investigates the influence of device parameters spread on the current distribution of paralleledsilicon carbide (SiC) MOSFETs. First, a variation coefficient is introduced and used as the evaluating norm for the parametersspread. Then a sample of 30 SiC MOSFET devices from the same batch of a well-known company is selected and tested underthe same conditions as those on datasheet. It is found that there is big difference among parameters spread. Furthermore,comprehensive theoretical and simulation analyses are carried out to study the sensitivity of the current imbalance to variationsof the device parameters. Based on the concept of the control variable method, the influence of each device parameter on thesteady-state and transient current distributions of paralleled SiC MOSFETs are verified separately by experiments. Finally, somescreening suggestions of devices or chips before parallel-connection are provided in terms of different applications and differentdriver configurations.
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Soh, Young-Sung,Hong, Jung-Woo The Korea Institute of Convergence Signal Processi 2015 융합신호처리학회 논문지 (JISPS) Vol.16 No.3
Connected component labeling (CCL) is a mandatory step in image segmentation where objects are extracted and uniquely labeled. CCL is a computationally expensive operation and thus is often done in parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method, modified 8 directional label selection (M8DLS) method, HYBRID1 method, and HYBRID2 method. Soh et al. showed that HYBRID2 outperforms the others and is the best so far. In this paper we propose a new hybrid parallel CCL algorithm termed as HYBRID3 that combines selective four directional label search (S4DLS) with label backtracking (LB). We show that the average percentage speedup of the proposed over M8DLS is around 60% more than that of HYBRID2 over M8DLS for various kinds of images.
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소영성,홍정우 한국융합신호처리학회 2015 융합신호처리학회 논문지 (JISPS) Vol.16 No.3
Connected component labeling (CCL) is a mandatory step in image segmentation where objects are extracted and uniquely labeled. CCL is a computationally expensive operation and thus is often done in parallel processing framework to reduce execution time. Various parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method, modified 8 directional label selection (M8DLS) method, HYBRID1 method, and HYBRID2 method. Soh et al. showed that HYBRID2 outperforms the others and is the best so far. In this paper we propose a new hybrid parallel CCL algorithm termed as HYBRID3 that combines selective four directional label search (S4DLS) with label backtracking (LB). We show that the average percentage speedup of the proposed over M8DLS is around 60% more than that of HYBRID2 over M8DLS for various kinds of images.
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An Improved Hybrid Approach to Parallel Connected Component Labeling using CUDA
Soh, Young-Sung,Ashraf, Hadi,Kim, In-Taek The Korea Institute of Convergence Signal Processi 2015 융합신호처리학회 논문지 (JISPS) Vol.16 No.1
In many image processing tasks, connected component labeling (CCL) is performed to extract regions of interest. CCL was usually done in a sequential fashion when image resolution was relatively low and there are small number of input channels. As image resolution gets higher up to HD or Full HD and as the number of input channels increases, sequential CCL is too time-consuming to be used in real time applications. To cope with this situation, parallel CCL framework was introduced where multiple cores are utilized simultaneously. Several parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method[1], modified 8 directional label selection (M8DLS) method[2], and HYBRID1 method[3]. Soh [3] showed that HYBRID1 outperforms NSZ-LE and M8DLS, and argued that HYBRID1 is by far the best. In this paper we propose an improved hybrid parallel CCL algorithm termed as HYBRID2 that hybridizes M8DLS with label backtracking (LB) and show that it runs around 20% faster than HYBRID1 for various kinds of images.
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An Improved Hybrid Approach to Parallel Connected Component Labeling using CUDA
소영성,Hadi Ashraf,김인택 한국융합신호처리학회 2015 융합신호처리학회 논문지 (JISPS) Vol.16 No.1
In many image processing tasks, connected component labeling (CCL) is performed to extract regions of interest. CCL was usually done in a sequential fashion when image resolution was relatively low and there are small number of input channels. As image resolution gets higher up to HD or Full HD and as the number of input channels increases, sequential CCL is too time-consuming to be used in real time applications. To cope with this situation, parallel CCL framework was introduced where multiple cores are utilized simultaneously. Several parallel CCL methods have been proposed in the literature. Among them are NSZ label equivalence (NSZ-LE) method[1], modified 8 directional label selection (M8DLS) method[2], and HYBRID1 method[3]. Soh [3] showed that HYBRID1 outperforms NSZ-LE and M8DLS, and argued that HYBRID1 is by far the best. In this paper we propose an improved hybrid parallel CCL algorithm termed as HYBRID2 that hybridizes M8DLS with label backtracking (LB) and show that it runs around 20% faster than HYBRID1 for various kinds of images.
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