Gear fault diagnosis via non-stationary adaptive MARTIN distance
نویسندگان
چکیده
منابع مشابه
Gear Fault Diagnosis Using Cyclic Bispectrum
This paper introduces the theory of cyclic statistics as a powerful tool for the diagnosis of gear faults. More precisely, a new method based on the cyclic bispectrum, a third order cyclic statistical function, is used for monitoring. This estimator furnishes a valuable means of detecting and characterising non-linear coupling effects as well as any periodic correlation between different compon...
متن کاملGear Fault Diagnosis and Classification Based on Fisher Discriminant Analysis
Gears are the most essential parts in rotating machinery. So gear fault modes diagnosis and levels classification are very important in engineering practice. This paper present a novel method in gear fault recognition and identification using Fisher discriminant analysis (FDA) due to FDA can reduct dimension when analyse signal. The real data collected from a gearbox test rig is used to validat...
متن کاملFault diagnosis in gear using wavelet envelope power spectrum
In recent years, improvement has been achieved in vibration signal processing, using wavelet analysis for condition monitoring and fault diagnosis. The use of wavelet analysis has proven to be efficient to detect faults in vibration signals with nonstationary, transient characteristics/ components. An experimental data set is used to compare the diagnostic capability of the fast Fourier transfo...
متن کاملMinimum distance estimation of stationary and non-stationary ARFIMA processes
A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters. The estimator is easy to compute and is consistent and asymptotically normally distributed for fractionally integrated (FI) processes with an integratio...
متن کاملNonlinear and Non-stationary Vibration Analysis for Mechanical Fault Detection by Using EMD-FFT Method
The Hilbert-Huang transform (HHT) is a powerful method for nonlinear and non-stationary vibrations analysis. This approach consists of two basic parts of empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA). To achieve the reliable results, Bedrosian and Nuttall theorems should be satisfied. Otherwise, the phase and amplitude functions are mixed together and consequently, the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientia Iranica
سال: 2011
ISSN: 1026-3098
DOI: 10.1016/j.scient.2011.03.008