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

E. E. Santoso; A. C. Chafid; R. L. Stregar; M. Syai'In; R. Y. Adhitya; B. Herijono; L. Subiyanto; J. Endrasmono; S. T. Sarena; A. Soeprijanto; B. S. Kaloko

doi:10.1109/ISESD.2017.8253307

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

E. E. Santoso, A. C. Chafid, R. L. Stregar, M. Syai'In, R. Y. Adhitya, B. Herijono, L. Subiyanto, J. Endrasmono, S. T. Sarena, A. Soeprijanto, B. S. Kaloko

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	2017 International Symposium on Electronics and Smart Devices, ISESD 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	67-72
Number of pages	6
ISBN (Electronic)	9781538627785
DOIs	https://doi.org/10.1109/ISESD.2017.8253307
Publication status	Published - 1 Jul 2017
Event	2nd International Symposium on Electronics and Smart Devices, ISESD 2017 - Yogyakarta, Indonesia Duration: 17 Oct 2017 → 19 Oct 2017

Publication series

Name	2017 International Symposium on Electronics and Smart Devices, ISESD 2017
Volume	2018-January

Conference

Conference	2nd International Symposium on Electronics and Smart Devices, ISESD 2017
Country/Territory	Indonesia
City	Yogyakarta
Period	17/10/17 → 19/10/17

Keywords

DS18B20
ELM
MPX5500DP sensor
NN
microcontroller
plant air receiver

Access to Document

10.1109/ISESD.2017.8253307

Cite this

Santoso, E. E., Chafid, A. C., Stregar, R. L., Syai'In, M., Adhitya, R. Y., Herijono, B., Subiyanto, L., Endrasmono, J., Sarena, S. T., Soeprijanto, A., & Kaloko, B. S. (2017). Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller. In 2017 International Symposium on Electronics and Smart Devices, ISESD 2017 (pp. 67-72). (2017 International Symposium on Electronics and Smart Devices, ISESD 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISESD.2017.8253307

Santoso, E. E. ; Chafid, A. C. ; Stregar, R. L. et al. / Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller. 2017 International Symposium on Electronics and Smart Devices, ISESD 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 67-72 (2017 International Symposium on Electronics and Smart Devices, ISESD 2017).

@inproceedings{1c3e24d79e074cac9418d6c4aa2d3815,

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

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.",

keywords = "DS18B20, ELM, MPX5500DP sensor, NN, microcontroller, plant air receiver",

author = "Santoso, {E. E.} and Chafid, {A. C.} and Stregar, {R. L.} and M. Syai'In and Adhitya, {R. Y.} and B. Herijono and L. Subiyanto and J. Endrasmono and Sarena, {S. T.} and A. Soeprijanto and Kaloko, {B. S.}",

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year = "2017",

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doi = "10.1109/ISESD.2017.8253307",

language = "English",

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Santoso, EE, Chafid, AC, Stregar, RL, Syai'In, M, Adhitya, RY, Herijono, B, Subiyanto, L, Endrasmono, J, Sarena, ST, Soeprijanto, A & Kaloko, BS 2017, Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller. in 2017 International Symposium on Electronics and Smart Devices, ISESD 2017. 2017 International Symposium on Electronics and Smart Devices, ISESD 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 67-72, 2nd International Symposium on Electronics and Smart Devices, ISESD 2017, Yogyakarta, Indonesia, 17/10/17. https://doi.org/10.1109/ISESD.2017.8253307

Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller. / Santoso, E. E.; Chafid, A. C.; Stregar, R. L. et al.
2017 International Symposium on Electronics and Smart Devices, ISESD 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 67-72 (2017 International Symposium on Electronics and Smart Devices, ISESD 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller

AU - Santoso, E. E.

AU - Chafid, A. C.

AU - Stregar, R. L.

AU - Syai'In, M.

AU - Adhitya, R. Y.

AU - Herijono, B.

AU - Subiyanto, L.

AU - Endrasmono, J.

AU - Sarena, S. T.

AU - Soeprijanto, A.

AU - Kaloko, B. S.

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AB - 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.

KW - DS18B20

KW - ELM

KW - MPX5500DP sensor

KW - NN

KW - microcontroller

KW - plant air receiver

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BT - 2017 International Symposium on Electronics and Smart Devices, ISESD 2017

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Santoso EE, Chafid AC, Stregar RL, Syai'In M, Adhitya RY, Herijono B et al. Comparison of Extreme Learning Machine and Neural Network Methods on Automatic Pressure Application of Plant Air Receiver Based on Microcontroller. In 2017 International Symposium on Electronics and Smart Devices, ISESD 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 67-72. (2017 International Symposium on Electronics and Smart Devices, ISESD 2017). doi: 10.1109/ISESD.2017.8253307

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

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Keywords

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