Detection of Intelligent Machine Fault using Deep Learning Classification

Detection of Intelligent Machine Fault using Deep Learning Classification

Publication Date : 2023-12-10
Author(s) :

S. Sridevi, Pidatala Ravitej, N. Janaki

           
Article Name :

Detection of Intelligent Machine Fault using Deep Learning Classification

Abstract :

Researchers have long been interested in developing fault detection methods for rotating machinery, and engineers and scientists are increasingly focusing on artificial intelligence-based approaches. When using other signal processing techniques to extract fault characteristics or categorize fault features, artificial neural networks especially deep learning-based techniques—are widely employed. The methodologies and these studies are closely related. This deep learning classification to detect intelligent machine errors. This developed a deep learning algorithm’s technique for the classification of machine faults. To facilitate the process, the input dataset is pre-processed. Researching the observed data is part of the data analysis process known as data pre-processing. The dataset is fed into the segmentation block following pre-processing. K-value to precisely identify the size and shape of the faults, morphological operations are employed in conjunction with segmentation for image segmentation. It attempts to maintain as much difference between the clusters as well as much similarity between the intra-cluster data points. The deep learning method includes the classifications of long-short-term memory networks (LSTM). When it comes to fault diagnosis in that area, LSTM classifier is designed to categorize faults according to their type.

No. of Downloads :

9