Multi resolution analysis for bearing fault diagnosis

K. Yavanarani, G. Raj, S. Christabel, J. Vijayaraghavan
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引用次数: 3

Abstract

A wavelet-based vibration analysis was done for Defense Applications. Vibration measurements were carried out in MSL Engine test bed in order to verify that it meets the specifications at different load conditions. Such measurements are often carried out in connection with troubleshooting in order to determine whether vibration levels are within acceptable limits at given engine speeds and maneuvers. A State-of-the-art portable Vibration Data Recorder is used for data acquisition of real-world signals. This paper is intended to take the reader through the various stages in a signal processing of the vibration data using modern digital technology. Vibration signals are post-analyzed using Wavelet Transform for data mining of the vibration signal observed from accelerometers. Wavelet Transform (WT) techniques are applied to decipher vibration characteristics due to Engine excitation to diagnose the faulty bearing. The Time-Scale analysis by WT achieves a comparable accuracy than Fast Fourier Transform (FFT) while having a lower computational cost with fast predictive capability. The result from wavelet analysis is validated using the LabVIEW software.
轴承故障诊断的多分辨率分析
基于小波的振动分析方法应用于国防领域。在MSL发动机试验台上进行了振动测试,验证了其在不同载荷条件下的性能。这种测量通常用于故障排除,以确定在给定的发动机转速和操作下振动水平是否在可接受的范围内。最先进的便携式振动数据记录仪用于实际信号的数据采集。本文旨在带读者了解利用现代数字技术对振动数据进行信号处理的各个阶段。利用小波变换对加速度计观测到的振动信号进行后置分析。采用小波变换技术对发动机励磁引起的振动特征进行解码,以诊断故障轴承。基于小波变换的时间尺度分析具有与快速傅里叶变换(FFT)相当的精度,同时具有较低的计算成本和快速的预测能力。利用LabVIEW软件对小波分析结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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