Bearing Signature Analysis as a Medium for Fault Detection: A Review

2007 ◽  
Vol 130 (1) ◽  
Author(s):  
M. S. Patil ◽  
Jose Mathew ◽  
P. K. RajendraKumar
Keyword(s):  
Fault Detection ◽  
Vibration Measurement ◽  
Signature Analysis ◽  
Rolling Element Bearings ◽  
Bearing Defects ◽  
Rolling Element ◽  
Vibration Signature ◽  
Recent Trends ◽  
Bearing Vibration ◽  
Detection And Diagnosis

Rolling element bearings find widespread domestic and industrial application. Defects in bearing unless detected in time may lead to malfunctioning of the machinery. Different methods are used for detection and diagnosis of the bearing defects. This paper is intended as a tutorial overview of bearing vibration signature analysis as a medium for fault detection. An explanation for the causes for the defects is discussed. Vibration measurement in both time domain and frequency domain is presented. Recent trends in research on the detection of the defects in bearings have been included.

An Automated Edge Computing-Based Condition Health Monitoring System: With an Application on Rolling Element Bearings

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Niklas Tritschler ◽  
Andrew Dugenske ◽  
Thomas Kurfess
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Vibration Signal ◽  
Vibration Sensor ◽  
Vibration Measurement ◽  
Rolling Element Bearings ◽  
Health Monitoring System ◽  
Vibration Data ◽  
Rolling Element ◽  
Vibration Signature

Abstract A failure of rolling element bearings is a frequent cause of machine breakdowns and results in a production loss due to the sudden failure. A regular condition health monitoring and an associated detection of bearing defects in the early stages can be used to predict such sudden failures. To monitor the bearing's condition, the generated vibration signature can be analyzed, since rotating machines have, in most instances, a unique vibration signature that relates to their health status. Presently, bearing analysis of many machines results in significant cost and complexity due to a large amount of vibration data that must be analyzed. A condition health monitoring system (CMS) was developed to automate and simplify the whole process from the vibration measurement to the analysis results. Additionally, the CMS is embedded into an Internet of Things (IoT) architecture. Thereby, a location-independent control of the CMS, the vibration data, and the analysis results is possible. The embedding of sensors can cause communication problems from the sensor to the cloud due to the low bandwidth of sensors and the amount of data that must be transmitted. To overcome this issue, an edge device that acts as a gateway between the vibration sensor and the cloud is the core of the CMS. It measures the vibration signal locally, analyzes it automatically, and publishes a feedback as to the bearing condition to the cloud.

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