Fast pattern recognition inspection system (FPRIS) for machine vibration

被引:0
作者
Se-do Oh
Young-jin Kim
Tae-hwi Lee
机构
[1] Kyung Hee University,Department of Industrial & Management Engineering
[2] Psylogic,undefined
来源
Journal of Mechanical Science and Technology | 2014年 / 28卷
关键词
Pattern recognition; Machine vibration; Diagnostics; Automatic inspection; FPRIS;
D O I
暂无
中图分类号
学科分类号
摘要
It is difficult to analyze the raw vibration signals of complex vibrating machines because these signals have complicated patterns. An appropriate preprocessing method has to be applied to enhance the signal resolution. In most cases, these preprocessed data are also difficult to inspect, however, because distributions of these data may have non-parametric and multi-modal distributions. If we apply the currently available methodologies to these data, we will encounter problems such as low accuracy, long delay times, and so on. To overcome these limitations, we developed the FPRIS (fast pattern recognition inspection system). FPRIS guarantees high diagnosis accuracy with fast running time, and the usefulness of FPRIS is demonstrated through the learning of sampled data.
引用
收藏
页码:437 / 444
页数:7
相关论文
共 32 条
[1]  
Heng R B W(1998)Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition Applied Acoustics 53 211-226
[2]  
Nor M J M(2002)A DSPbased FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis Instrumentation and Measurement 51 1316-1322
[3]  
Betta G(1996)Applications of time-frequency analysis to signals from manufacturing and machine monitoring sensors Proceedings of the IEEE 84 1319-1329
[4]  
Liguori C(1994)Application of cyclostationary and time-frequency signal analysis to car engine diagnosis Acoustics, Speech, and Signal Processing 4 19-22
[5]  
Paolillo A(2006)Continuous wavelet transform technique for fault signal diagnosis of internal combustion engines NDT & E International 39 304-311
[6]  
Pietrosanto A(2002)Vibration signal analysis and feature extraction based on reassigned wavelet scalogram Journal of Sound and Vibration 253 1087-1100
[7]  
Atlas L E(2000)Fault diagnosis of rotating machinery through visualisation of sound signals Mechanical Systems and Signal Processing 14 229-241
[8]  
Bernard G D(2010)Gear fault detection with Wigner-Viller distribution based cepstrum approach Computer Engineering and Technology (ICCET, 2010 2nd International Conference on 1 500-502
[9]  
Narayanan S B(2011)Diagnostic system for crashing and damping signals in engine-assembly line KSME (A) 35 965-970
[10]  
Konig D(2013)Development of moving average prediction diagnostic module for vibration parameter influenced by environmental factors KSME (A) 37 797-804