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All Journal Journal of Applied Engineering and Technological Science (JAETS)
A. Malligarjun
Scholar, Department of Artificial Intelligence and Data Science, Erode Sengunthar Engineering College, Erode, Tamilnadu, India.
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Life Time Prediction of an Electromagnet Relay using Clustering based Principal Component Analysis with Hybrid Deep Learning Model T. Maris Murugan; C. Reeda Lenus; S. Sridharan; A. Malligarjun
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.5891

Abstract

The estimation of the electromagnet relay remaining useful life is highly crucial to maintain reliability and avoid unscheduled breakdowns in various applications. The objective of this research work will be to design a model with much higher precision and efficiency utilizing PCA coupled with a hybrid deep learning architecture of Bi-LSTM along with Bi-GRU. The C-MAPSS dataset was of reduced dimensionality, since PCA has been applied to eliminate data redundancy while retaining crucial characteristics, and then K-means clustering is applied to classify the data; afterwards, the Bi-LSTM and Bi-GRU models are implemented for RUL relay prediction. The proposed method in comparison with typical deep learning models has a Mean Absolute Error of 0.021 and an R² of 0.996. Results developed reflect how the model can produce some very powerful prediction, however; what it really shows is great potential for this approach with respect to predictive maintenance of electromagnet relays. PCA may well amalgamate with Bi-LSTM and Bi-GRU models to achieve great scalability according to the maintenance engineering, which offers practical applications in improving the lifetime of the electromagnet relays.
Co-Authors C. Reeda Lenus S. Sridharan T. Maris Murugan