An intelligent prognostic model for electrolytic capacitors health monitoring: A design of experiments approach

Author:

Bhargava Cherry12ORCID,Banga Vijay Kumar3,Singh Yaduvir4

Affiliation:

1. Department of Electronics and Communication Engineering, I.K. Gujral Punjab Technical University, Jalandhar, India

2. Department of Electronics and Communication Engineering, Lovely Professional University, Phagwara, India

3. Electronics and Communication Engineering, Amritsar College of Engineering and Technology, Amritsar, India

4. Department of Electrical Engineering, Harcourt Butler Technical University, Kanpur, India

Abstract

In the world of fast-growing technology, the electronic gadgets become obsolete with the invention of advanced technology. Reuse of electronic components is a philosophy now being applied to all manufacturing industries to achieve the goal of reuse technology. The accurate assessment of residual life is of great significance for reuse as well as the successful operation of the application. The prediction of failure before it occurs will, in turn, reduce the repairing cost and strengthen the reputation of the manufacturer in real-time market. This article reports a novel technique to explore the residual life of electrolytic capacitor and validates it, using accelerated life testing. The optimization and evaluation of proposed technology are accomplished using design of experiments methodology, that is, Taguchi’s approach to designing the experiments. Prediction of residual life of capacitor is done using regression and artificial neural networks technique. A decision support system is prepared using fuzzy logic, which monitors the current health status of the capacitor and directs the user accordingly. Using six environmental stress and electrical parameters, the actual lifetime of the electrolytic capacitor is accessed, which has been proven as a valid and accurate technique, exhibiting error rate of 2.99%.

Publisher

SAGE Publications

Subject

Mechanical Engineering

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