Soft Computational Technique to Estimate Inflow for Fault Detection in Control Valve

K. V. Santhosh, Bhagya R. Navada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A sensor less flow measurement technique is proposed in this paper. The objective of the proposed work is to design an observer which can estimate the inflow to the control valve by soft computation techniques, so as to detect the faults in the control valve. Orifice flow meter is placed at the outlet of the control valve for measurement of outflow. By analyzing the behavior of control valve for different input signal, in flow to the control valve is estimated. Control valve works on the principle of regulating the inflow based on the control signal. Performance of the control valve can be established by measuring outflow, by knowing input signal and estimation of inflow to the control valve. To estimate the inflow, neural network based model is incorporated in the proposed work. Designed estimator is compared with the standard signal to evaluate the performance. The root mean square of percentage error of 0.91 shows successful design of estimator.

Original languageEnglish
Title of host publication2nd International Conference on Energy, Power and Environment
Subtitle of host publicationTowards Smart Technology, ICEPE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647691
DOIs
Publication statusPublished - 04-03-2019
Event2nd International Conference on Energy, Power and Environment, ICEPE 2018 - Shillong, Meghalaya, India
Duration: 01-06-201802-06-2018

Publication series

Name2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018

Conference

Conference2nd International Conference on Energy, Power and Environment, ICEPE 2018
CountryIndia
CityShillong, Meghalaya
Period01-06-1802-06-18

Fingerprint

Computational Techniques
Fault Detection
Fault detection
Estimate
Estimator
Flow Measurement
Measurement Techniques
Signal Control
Flow measurement
Mean Square
Orifices
Percentage
Observer
Fault
Roots
Neural Networks
Sensor
Neural networks
Evaluate
Sensors

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Energy Engineering and Power Technology
  • Computer Networks and Communications
  • Renewable Energy, Sustainability and the Environment

Cite this

Santhosh, K. V., & Navada, B. R. (2019). Soft Computational Technique to Estimate Inflow for Fault Detection in Control Valve. In 2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018 [8658834] (2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EPETSG.2018.8658834
Santhosh, K. V. ; Navada, Bhagya R. / Soft Computational Technique to Estimate Inflow for Fault Detection in Control Valve. 2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018. Institute of Electrical and Electronics Engineers Inc., 2019. (2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018).
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abstract = "A sensor less flow measurement technique is proposed in this paper. The objective of the proposed work is to design an observer which can estimate the inflow to the control valve by soft computation techniques, so as to detect the faults in the control valve. Orifice flow meter is placed at the outlet of the control valve for measurement of outflow. By analyzing the behavior of control valve for different input signal, in flow to the control valve is estimated. Control valve works on the principle of regulating the inflow based on the control signal. Performance of the control valve can be established by measuring outflow, by knowing input signal and estimation of inflow to the control valve. To estimate the inflow, neural network based model is incorporated in the proposed work. Designed estimator is compared with the standard signal to evaluate the performance. The root mean square of percentage error of 0.91 shows successful design of estimator.",
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Santhosh, KV & Navada, BR 2019, Soft Computational Technique to Estimate Inflow for Fault Detection in Control Valve. in 2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018., 8658834, 2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018, Institute of Electrical and Electronics Engineers Inc., 2nd International Conference on Energy, Power and Environment, ICEPE 2018, Shillong, Meghalaya, India, 01-06-18. https://doi.org/10.1109/EPETSG.2018.8658834

Soft Computational Technique to Estimate Inflow for Fault Detection in Control Valve. / Santhosh, K. V.; Navada, Bhagya R.

2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018. Institute of Electrical and Electronics Engineers Inc., 2019. 8658834 (2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - A sensor less flow measurement technique is proposed in this paper. The objective of the proposed work is to design an observer which can estimate the inflow to the control valve by soft computation techniques, so as to detect the faults in the control valve. Orifice flow meter is placed at the outlet of the control valve for measurement of outflow. By analyzing the behavior of control valve for different input signal, in flow to the control valve is estimated. Control valve works on the principle of regulating the inflow based on the control signal. Performance of the control valve can be established by measuring outflow, by knowing input signal and estimation of inflow to the control valve. To estimate the inflow, neural network based model is incorporated in the proposed work. Designed estimator is compared with the standard signal to evaluate the performance. The root mean square of percentage error of 0.91 shows successful design of estimator.

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Santhosh KV, Navada BR. Soft Computational Technique to Estimate Inflow for Fault Detection in Control Valve. In 2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018. Institute of Electrical and Electronics Engineers Inc. 2019. 8658834. (2nd International Conference on Energy, Power and Environment: Towards Smart Technology, ICEPE 2018). https://doi.org/10.1109/EPETSG.2018.8658834