An intelligent reconfiguration approach based on fuzzy partitioning in PV arrays

Karaköse, Mehmet; Bayğın, Mehmet; Baygin, Nursena; Murat, Kagan; Akın, Erhan

doi:10.1109/inista.2014.6873644

Cited by 18 publications

(6 citation statements)

References 14 publications

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“…The proposed method, was operated by a train watching with 16km/h. On the acquired images, Sobel edge extraction algorithm and Hough transformation are applied and rail component detection has done [16], [17].…”

Section: Numbers Of Matching >Threshold Valuementioning

confidence: 99%

A New Computer Vision Based Method for Rail Track Detection and Fault Diagnosis in Railways

Karaköse¹,

Yaman²,

Bayğın³

et al. 2017

IJMERR

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Computer vision-based condition monitoring methods, the methods are increasingly used on railway systems. Rail condition monitoring process can be performed using data obtained with the help of computers using these methods. In this study, a computer-based visual rail condition monitoring is proposed. By means of a camera placed on top of the train the rail that the train is on and the neighbor rail images are taken. On these images, the edge and feature extraction methods are applied to determine the rails. The resulting several faults between railways were studied to determine if there is a failure. The results obtained are given at the end of the study. Experimental results show that the proposed method is examined, it is observed that a healthy and effective results.  Index Terms-condition monitoring, railway systems, image processing, fault diagnosis interests are image processing, fault diagnosis, computer vision, railway inspection systems and fuzzy systems.

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Section: Numbers Of Matching >Threshold Valuementioning

confidence: 99%

A New Computer Vision Based Method for Rail Track Detection and Fault Diagnosis in Railways

Karaköse¹,

Yaman²,

Bayğın³

et al. 2017

IJMERR

Self Cite

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“…Therefore, this step in the reconfiguration approach can provide a higher amount of power. For this step, an efficiency and applicable fuzzy partitioning method solution is used for less complexity in the calculations 20,21,22,23 . The proposed system is a single-input single-output fuzzy structure.…”

Section: B Fuzzy Measurement With Adaptive Valuesmentioning

confidence: 99%

Fuzzy Based Reconfiguration Method Using Intelligent Partial Shadow Detection in PV Arrays*

Karaköse¹,

Bayğın²,

Murat³

et al. 2016

IJCIS

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Photovoltaic (PV) systems are the most commonly used methods. PV systems have the most potential and efficiency between the species of renewable energy. However, this method can be subjected to a loss of energy gain when shading occurs on the PV panels. To overcome this negative situation, a reconfiguration process in the PV systems has been developed. Through this method, the power losses caused by the shading of the panel on the system are attempting to be minimized . Without any change in the physical location of the pre-shading panels, the panels are co nfigured with electrical connectors. In this study, a new efficient and intelligent reconfiguration method is proposed. The short-circuit current values of the PV panels are detected using current sensors. Shortcircuit current values vary in proportion to the shadings that occur on the panels. A fuzzy calculation is carried out taking the current values into account as the system input parameters. The optimal connection structure is detected by using the fuzzy output values. The result is then applied to the system by switching the matrix circuit. The proposed method has been tested in different shadowing conditions and has been seen as a gain ratio. Experiments performed in real-time availability have confirmed the suitability of the method for different sized systems.

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“…In the literature fuzzy logic based reconfiguration study uses I values, that are inputs to the switch module that depend on PV array system, in order to perform the best panel reconfiguration [9]. In another study, for PV arrays, a genetic algorithm based reconfiguration method that processes to find the maximum energy production from the panels that are not shaded is presented [10].…”

Section: Shadow Detetion Algorithmmentioning

confidence: 99%

A shadow detection approach based on fuzzy logic using images obtained from PV array

Karaköse

Firildak

2015

2015 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)

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Shadows on PV arrays influence the energy production performance negatively. There are many methods in the literature related to the detection of these shadows and reconfiguration of arrays. The methods proposed in the literature generally aim at reconfiguration of arrays and detecting shadow regions by using current (I), voltage (V) and power (P) information. In the process of reconfiguration it is quite difficult to measure to use P, V, I information. In this paper, in order to use in the reconfiguration processes for the detection of the shadow region on PV arrays, a new fuzzy logic based computer vision method is presented. The proposed method, firstly, performs object detection with background subtraction. Then, detects the edge of the object regions. Finally, it detects shadow regions with the help of fuzzy logic decision making system. Experimental results are provides effective performance for detecting of shaded areas on PV arrays.

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An intelligent reconfiguration approach based on fuzzy partitioning in PV arrays

Cited by 18 publications

References 14 publications

A New Computer Vision Based Method for Rail Track Detection and Fault Diagnosis in Railways

A New Computer Vision Based Method for Rail Track Detection and Fault Diagnosis in Railways

Fuzzy Based Reconfiguration Method Using Intelligent Partial Shadow Detection in PV Arrays*

A shadow detection approach based on fuzzy logic using images obtained from PV array

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