Rolling Bearing Fault Diagnosis Based on AIS

Yao Bin Hu; Xia Yue; Chun Liang Zhang

doi:10.4028/www.scientific.net/AMR.139-141.2569

Paper Titles

Research and Application on Chlorophyll Fluorescence On-Line Monitoring Technology
p.2550

De-Noising of Damage Signal in Wire Rope Based on Adaptive Lifting Wavelet
p.2556

Steam Turbine Blade MMM Testing and Failure Analysis
p.2561

The Remote Monitor for Smart Motion Device by Using VPN Technology
p.2565

Rolling Bearing Fault Diagnosis Based on AIS
p.2569

Curvature Mode Characteristics of the Simple Beam with a Local Damaged Crack
p.2574

One Method to Determine the Optimal Maintenance Time Based on Selective Attrition
p.2578

A Method of Simulating Computation for the Fatigue Life Prediction
p.2582

Engineering Machinery Engine System Reliability Analysis
p.2587

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 139-141Rolling Bearing Fault Diagnosis Based on AIS

Rolling Bearing Fault Diagnosis Based on AIS

Abstract:

In this paper, an approach of rolling bearing fault diagnosis based on artificial immune system (AIS) is presented. The features extracted from vibration signals are normalized as the original antigens, and an advanced clone selection algorithm (CSA) is applied to train the antibodies. Then use the antibody set to recognize the faults online. The experiments on rolling bearing show the approach is effective and feasible.