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    Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller

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    TEKNIK_PROSIDING_Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller.pdf (903.4Kb)
    Date
    2017
    Author
    SANTOSO, E. E.
    CHAFID, A. C.
    SIREGAR, R. L.
    SYAI'IN, M.
    ADHITYA, R.Y.
    HERIJONO, B.
    SUBIYANTO, L.
    ENDRASMONO, J.
    SARENA, S. T.
    SOEPRIJANTO, A.
    KALOKO, B. S.
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    Abstract
    One Chemical Company is a state-owned factory engaged in the production of fertilizers. Especially in factory which is a supporter of air needs for line to line needs in Plant Air Receiver. The air requirement is supplied by three air compressors using an electric power. Air is accommodated on a large tube that is called D923 Plant Air Receiver tube. After meet the required air pressure, air will be channeled to the Plant Air Receiver line. However, three compressors still use manual systems where the operator goes down to the plant to turn off and turn on the compressor and the compressor is still running independently. If the compressor burns continuously in hot conditions then the compressor lifetime will shorten. With the above problems, the researcher tries to create a system of air pressure plant automation receiver by using microcontroller, as a main control of the system are using ELM and NN. Both of them are used for controlling the air valve filling and air pressure measurement process using MPX5500DP sensor and compressor temperature measurement using DS18B20 to make two compressors as main compressor and backup compressor. It is expected to be used to assist in the process of control and monitoring of air filling so it can be controlled through control room.
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    https://repository.unej.ac.id/xmlui/handle/123456789/108222
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    • LSP-Conference Proceeding [1877]

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    Indonesia DSpace Group :

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