Application Research of PLC Technology in Automatic Control of Electrical Equipment

Contact resistance is an essential cause of electrical equipment joint heating. An experimental platform was built to measure and compare temperature and contact resistance of memory alloy spring washers and ordinary spring washers when heated by taking the same heavy current, on condition that both of the counterparts had the same initial contact resistance and temperature. Results showed that memory alloy washer were more helpful to limit the joint temperature rise by reducing contact resistance from their features of tempting to restore to original shape when heated to a high temperature. Therefore, the memory alloy washers were proved to have remarkable effect on ensuring safety of electric power equipments and reducing energy loss.

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AUTOMATIC CONTROL IN ELECTRICAL EQUIPMENT MONITORING BY USING PLC PROGRAMMING TECHNOLOGY

International Journal of Mechatronics and Applied Mechanics ◽

10.17683/ijomam/issue8.56 ◽

2020 ◽

Vol i (8) ◽

Keyword(s):

Automatic Control ◽

Electrical Equipment ◽

Equipment Monitoring ◽

Plc Programming

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Deep Neural Networks with Application to Transformer Failure Diagnosis

10.5753/eniac.2018.4424 ◽

2018 ◽

Author(s):

Hugo Riviere S. Moraes ◽

Adriana Rosa Garcez Castro

Keyword(s):

Neural Networks ◽

Deep Neural Networks ◽

Power Transformer ◽

Electrical Equipment ◽

Failure Diagnosis ◽

Oil Analysis ◽

Application Research ◽

Dissolved Gas ◽

Incipient Faults ◽

Testing Data

This paper presents the outcomes of an application research of deep neural networks to diagnosis incipient faults in power transformer through dissolved gas-in-oil analysis (DGA). Two models was proposed, first, using a Stacked Autoencoder Network and later a Convolucional Neural Network. To the development of the system was used the database TC10 which contains data of faults usually found in electrical equipment in service. This database are described in norm IEC 60599. The outcomes achieved, considering the testing data was 100% and 96,5% of accuracy, showed that this models containing a wide applicability to the problem.

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