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- W3092146769 abstract "The state of industrial safety at explosion and fire hazardous and chemically hazardous production facilities is largely determined by pump-and-compressor equipment technical state. Due to the high danger of chemicals circulating in the enterprises technological cycles, pump-and-compressor equipment failure can lead to emergency situations accompanied by significant economic and environmental damage. The paper presents the results of experimental studies of the interrelation between the operating modes and pump-and-compressor equipment characteristic damages of explosion and fire hazardous and chemically hazardous production facilities with higher harmonic components of currents and voltages parameters generated by electric drive motors. To ensure the electrically driven pump-and-compressor equipment technical state and predict its safe operation life, we developed the software and hardware system, the principle of which is based on the parameter sets generated by the electric drive motor of currents and voltages harmonic components and by using the artificial neural networks method. For training an artificial neural network the theory of experimental design is used, which allows us to create the necessary database for training with a significant decrease in the training experiments number. An important advantage of the developed software and hardware system is that it allows us to diagnose operating equipment and perform remote monitoring. Defects detection on operating equipment at an early stage of their development not only prevents a sudden stop of production as a result of an accident, but also significantly reduces the repairing cost of equipment and increases its service life." @default.
- W3092146769 created "2020-10-15" @default.
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- W3092146769 date "2020-09-01" @default.
- W3092146769 modified "2023-09-27" @default.
- W3092146769 title "Software and Hardware System Development for Determining Pump-and-Compressor Equipment Technical State" @default.
- W3092146769 cites W1541776468 @default.
- W3092146769 cites W2156066228 @default.
- W3092146769 doi "https://doi.org/10.1109/uralcon49858.2020.9216283" @default.
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