Preventive Maintenance of Rotating Machines using Signal Processing Techniques
A. Ganguly1, Manoj K. Kowar2, H. Chandra3
1Prof. M. K. Kowar, Director,. BIT Durg, India.
2Manoj K. Kowar, Bhilai Institute of Technology Durg, India.
3H. Chandra, Bhilai Institute of Technology Durg, India.
Manuscript received on April 15, 2012. | Revised Manuscript received on April 20, 2012. | Manuscript published on May 05, 2012. | PP: 35-40 | Volume-2 Issue-2, May 2012 . | Retrieval Number: B0501032212/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents a method for analyzing the vibration signals of rotating machines and diagnoses preventive maintenance requirements using Vibration Signature Analysis Technique. The concept of Vibration Signature Analysis of Rotating Machines lies on the fact that all rotating machines in good condition have a fairly stable vibration pattern, which can be considered its ‘Signature’. Under any anomalous condition of working of such machines, the vibration pattern gets changed. The amount of variation can be detected and the nature of anomalies can be analyzed to get an idea about the malfunctioning of the rotating machine. In order to develop the technique to be applied, it is proposed to simulate the vibration signals of a rotating machines using MATLAB to store the signature of rotating machines under healthy conditions. Deformation can now be introduced in the signature or can be acquired from other sources. Such deformed signals are to be processed in order to know the type of defect the rotating parts of the machine is suffering from. Based on the type of defect, preventive maintenance schedule can be proposed. This paper also aims at overcoming the limitations of traditional Vibration Signature Analysis techniques.
Keywords: Vibration Signals, Signature Analysis, Signal Processing, Rotating machines, Preventive Maintenance.