• Title/Summary/Keyword: AC Solenoid Valve

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Acoustic Noise Characteristics Improvement of Solenoid Valve by the Shading Coil Application (쉐이딩 코일의 추가에 의한 솔레노이드 밸브의 소음 특성 개선)

  • Jung, Tae-Uk
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.7
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    • pp.1175-1180
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    • 2008
  • Recently agriculture has been intelligenced and automatized because the number of agricultural population is reduced, and the various agricultural machine is developed and utilized actively, In these agricultural automation system, the solenoid valve is widely used for the supply of water and fertilizer to the plant and soil. In this solenoid valve system, AC excitation solenoid valve is widely used because of economic merit and simple system scheme. However, the instantaneous chattering vibration and noise of plunger caused by the alternative MMF variation is very important performance characteristics. In order to reduce vibration the DC excitation solenoid valve is sometimes applied for the high-end applications. In this case, the control circuit is essential to control DC excitation current. It may causes the cost increase and system complexity and it is not suitable for the outdoor agricultural machine. In this paper, the electromagnetic structural improvement of AC solenoid valve is studied to reduce the dynamic vibration and noise. As an economical solution, the shading coil is additionally implemented to the conventional solenoid valve. As a result of this study, the vibration and acoustic noise is largely reduced by the compensating MMF of shading coil and it is verified by the test of prototype.

Design and Characteristic of the AC Solenoid Valve (AC 솔레노이드 밸브의 설계 및 특성)

  • Kim, Dong-Soo;Jeon, Yong-Sik
    • Proceedings of the KSME Conference
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    • 2007.05b
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    • pp.3056-3061
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    • 2007
  • The technology of AC solenoid valves is now considered as a core technology in the fields of the production line of semi-conductor chips and the micro fluid chips for medical applications. And AC solenoid valves, which operate by compressed air, are characterized by high speed response, great repeatability and that the pressure on the cross sectional area of poppet is kept constant regardless of the fluctuation of the pressure exerted on the ports. In this study, AC solenoid valves that posses the high-speed responsibility and the high rate of flow have designed and analyzed through the law of equivalent magnetic circuit and Finite Element Method (FEM) respectively. In case of poppet, Flow field characteristic was analyzed by the variation of poppet and it was able to display flow field by changing the location of the poppet. Also, we verified possibility of the design through the static and dynamic pressure and the 3D distribution curve of the force by working the front poppet.

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Fault state detection and remaining useful life prediction in AC powered solenoid operated valves based on traditional machine learning and deep neural networks

  • Utah, M.N.;Jung, J.C.
    • Nuclear Engineering and Technology
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    • v.52 no.9
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    • pp.1998-2008
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    • 2020
  • Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.