The Experts below are selected from a list of 39 Experts worldwide ranked by ideXlab platform
M.t. Ir. Jatmiko - One of the best experts on this subject based on the ideXlab platform.
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Perbandingan Akurasi Kwh Meter Digital Dan Kwh Meter Analog
2017Co-Authors: Muhammad Ridho Rohman Zuhri, M.t. Ir. JatmikoAbstract:Electrical energy cannot be separated from daily human needs. In modern times, we are all dependent on electricity for our communication, transportation, and more. It is especially important at home where we use it to help wash our clothes, power fans to cool us down, or give us light at night. Electrical energy used in housing is automatically calculated by PT. PLNusing a measuring instrument, like a kWh Meter for example. There are two types of kWH Meters that PT.PLN uses: the kWh Analogue Meter and the kWh digital Meter. This study aims to determine the accuracy of the kWh Meter. This will be done by installing a series of two postpaid electricity Meters with a prepaid Meter. Data will be obtained through the addition of kWh on the postpaid electricity Meter and the reduction of kWh on the prepaid electricity Meter by using a resistive load. From the results of this study, it can be concluded that the average percentage of error readings for resistive loads (cos φ=1) amounted to 11.498% contained in the digital Meter kWh. On testing in the second home, the digital kWh Meter had 5 times as many erroneous readings over 30%. In comparison, the Analogue kWh Meter on had 1 kWh reading of 8.043% and 2 kWh reading of 8.369%. To develop this research, we can use capacitive or inductive loads.
Muhammad Ridho Rohman Zuhri - One of the best experts on this subject based on the ideXlab platform.
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Perbandingan Akurasi Kwh Meter Digital Dan Kwh Meter Analog
2017Co-Authors: Muhammad Ridho Rohman Zuhri, M.t. Ir. JatmikoAbstract:Electrical energy cannot be separated from daily human needs. In modern times, we are all dependent on electricity for our communication, transportation, and more. It is especially important at home where we use it to help wash our clothes, power fans to cool us down, or give us light at night. Electrical energy used in housing is automatically calculated by PT. PLNusing a measuring instrument, like a kWh Meter for example. There are two types of kWH Meters that PT.PLN uses: the kWh Analogue Meter and the kWh digital Meter. This study aims to determine the accuracy of the kWh Meter. This will be done by installing a series of two postpaid electricity Meters with a prepaid Meter. Data will be obtained through the addition of kWh on the postpaid electricity Meter and the reduction of kWh on the prepaid electricity Meter by using a resistive load. From the results of this study, it can be concluded that the average percentage of error readings for resistive loads (cos φ=1) amounted to 11.498% contained in the digital Meter kWh. On testing in the second home, the digital kWh Meter had 5 times as many erroneous readings over 30%. In comparison, the Analogue kWh Meter on had 1 kWh reading of 8.043% and 2 kWh reading of 8.369%. To develop this research, we can use capacitive or inductive loads.
L. Abdulwahab - One of the best experts on this subject based on the ideXlab platform.
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AN ASSESSMENT OF BILLING ELECTRICITY CONSUMERS VIA Analogue MeterS IN KANO, NIGERIA, BY KANO ELECTRICITY DISTRIBUTION PLC
Bayero Journal of Pure and Applied Sciences, 2010Co-Authors: L. AbdulwahabAbstract:This paper assesses the perception of billing consumers via Analogue Meter in Kano Electricity Distribution Plc, Nigeria. Questionnaire survey was used to collect data from the consumers, frequency counts and percentages were used to analyze the generated data. The result of the study revealed that 38% of the Analogue Meters were installed between eleven to twenty one years ago; hence the need for replacement of obsolete Meters and periodic inspection of all consumers’ Meters at least once in three months for proper reading is vital in order to achieve accurate billing. The study also revealed poor and unreliable power supply and most often the bills issued for the electricity consumption are based on estimates, thus contributing to poor consumers’ response to payments of electricity bills. Some suggestions that can facilitate the improvements of the operation of the Distribution Company were offered. Keywords: Electricity Distribution, Consumers, Analogue Meter, Billing, Nigeria
Yoshihiko Hamamoto - One of the best experts on this subject based on the ideXlab platform.
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Automatic Reading of an Analogue Meter Using Image Processing Techniques
IEEJ Transactions on Electronics Information and Systems, 2009Co-Authors: Yusuke Fujita, Yoshihiko HamamotoAbstract:In this paper, we propose a system for automatic reading of an Analogue Meter using a digital image which is flexible and allows easy installation for various existing Analogue Meters. The system operates segmentation of Meter area from a image, correcting image distortion and recognition of the scale on the Meter in automatic setup phase. And it operates Meter reading in monitoring phase. In our system, the planer projective transformation is automatically applied to a distorted image using a rectangle and a circle, to correct geometric distortion. In the automatic setup phase, the graduation marks of the scale are detected and located from a acquired image. Thereby, the Meter reading can be flexibly adapted to different Meter scales during the easy process. In the monitoring phase, the needle is detected and located from a new acquired image, and the Meter reading is derived by comparing the relative position of the needle within the arrangement of the detected graduation marks. The experimental results show that the proposed system realizes automatic reading for various Analogue Meters as exactly as human observers under the controlled illuminated condition.
Koudjo M. Koumadi - One of the best experts on this subject based on the ideXlab platform.
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ISA - Intelligent Instrument Reader Using Computer Vision and Machine Learning
2018 IEEE Industry Applications Society Annual Meeting (IAS), 2018Co-Authors: Robert A. Sowah, Abdul R. Ofoli, Eugene Mensah-ananoo, Godfrey A. Mills, Koudjo M. KoumadiAbstract:A novel algorithm using computer vision and machine learning techniques have been developed in this research and applied to automate the reading of analog Meters. This approach does not rely on any prior information about the Meter being read or any human intervention during the process. High-level features of the Meter including the graduation values and angles are extracted using a cascade of image contour filters with a series of digit classifiers. The features are refined and used to train regression models that return the reading of the Analogue Meter automatically. The proposed approach was tested to read a variety of offline and live-feed images of analog pointer Meters automatically without any prior information about the Meters.