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Title

An Intelligent Autonomous System for Condition-Based Maintenance- Case Study: Control Valves

Year: 1398
COI: JR_JIST-7-2_005
Language: EnglishView: 100
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Authors

Hamidreza Naseri - Department of Computer, Faculty of Engineering, Islamic Azad University, Qom Branch, Qom, Iran
Ali Shahidinejad - Department of Computer, Faculty of Engineering, Islamic Azad University, Qom Branch, Qom, Iran
Mostafa Ghobaei-Arani - Department of Computer, Faculty of Engineering, Islamic Azad University, Qom Branch, Qom, Iran

Abstract:

Maintenance process generally plays a vital role to achieve more benefits to the enterprises. Undoubtedly, this process has a high value-added in oil and gas industries. Process owner expectations and new technology acquisition have been changing the mindset of domain experts to the new maintenance approaches and different newer methods such as condition-based maintenance models for improving the reliability and decreasing the cost of maintenance. Because of the high dynamic behavior of the gas and the instability of the input parameters, the need to apply a model with self-healing behavior is a serious demand in the gas industry. However, to the best of our knowledge, despite its importance, there is not any comprehensive study in the literature. In this paper, we present a new neuro-fuzzy model and a self-management control loop using real world data to meet the mentioned targets for a specified control valve in a gas refinery. ANFIS model is employed for the reasoning process which has six inputs (Inlet/outlet Pressures, temperature, flow rate, controller output and valve rod displacement), and one output that is a type of failure of the control valve and the most failures are considered based on domain expert knowledge. A suitable control loop is used to unceasingly monitor, analyze, plan and finally execute the process of prediction of failures. Due to undertaken improvement, there is a considerable change in reliability and financial indices. Moreover, the proposed approach is compared with two different methods. The results show that our proposed model comprehensively improves accuracy by ۲۴%.

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This Paper COI Code is JR_JIST-7-2_005. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/1142413/

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Naseri, Hamidreza and Shahidinejad, Ali and Ghobaei-Arani, Mostafa,1398,An Intelligent Autonomous System for Condition-Based Maintenance- Case Study: Control Valves,https://civilica.com/doc/1142413

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The specifications of the publisher center of this Paper are as follows:
Type of center: Azad University
Paper count: 2,372
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