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Predictive Maintenance of Air Conditioning Systems Using Supervised Machine Learning | IEEE Conference Publication | IEEE Xplore

Predictive Maintenance of Air Conditioning Systems Using Supervised Machine Learning


Abstract:

Various types of faults can occur in an air conditioner resulting in a decrease in efficiency, a rise in energy consumption, and increasing maintenance costs. Hence predi...Show More

Abstract:

Various types of faults can occur in an air conditioner resulting in a decrease in efficiency, a rise in energy consumption, and increasing maintenance costs. Hence predictive maintenance becomes important. In this paper, the two most common types of faults - gas leakage and capacitor malfunction have been detected using the decision tree machine learning algorithm. The data for faulty and operating air conditioners have been collected using distributed sensors, microcontroller, and dedicated circuitry and analyzed using MATLAB Classification App Learner Toolbox. The results obtained by the decision tree for fault detection and diagnosis and load monitoring were then compared with results obtained by support vector machine and the prediction accuracy for the decision tree was found to be higher. The presented research work can identify the air conditioner which is faulty as well as predicts the type of fault at an early stage to do maintenance beforehand.
Date of Conference: 10-14 December 2019
Date Added to IEEE Xplore: 16 April 2020
ISBN Information:
Conference Location: New Delhi, India

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