Wavelet Enveloped Power Spectrum and Optimal Filtering For Fault Diagnosis in Gear
نویسندگان
چکیده
The methodology of vibration based condition monitoring technology has been developing at a rapid stage in the recent years suiting to the maintenance of sophisticated and complicated machines. The ability of wavelet analysis to efficiently detect non-stationary, non-periodic, transient features of the vibration signal makes it a demanding tool for condition monitoring. In this paper, the vibration condition monitoring based on Laplace and Morlet wavelet enveloped power spectrum analysis to detect the faults in gears is presented. The experimental studies were conducted on the gear testing apparatus to obtain the vibration signal from a healthy gear and a faulty gear. The vibration signals obtained were filtered to enhance the signal components before the application of wavelet analysis. A study detailing features of fault characterization is also given in order to understand the effectiveness of signal processing methods. Keywords-Continuous wavelet transform, Envelope power spectrum, Wavelet, Filtering.
منابع مشابه
Fault Detection and Diagnosis Ingears Using Wavelet Enveloped Power Spectrum and Ann
Abstract In this work, automatic detection and diagnosis of gear condition monitoring technique is presented. The vibration signals in time domain wereobtained from a fault simulator apparatus from a healthy gear and an induced faulty gear. These time domain signals were processed using Laplace and Morlet wavelet based enveloped power spectrum to detect the faults in gears. The vibration signal...
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 کاملGear Fault Diagnostics using Wavelet Transform
Due to industrial importance of gears in power transmission systems, fault detection and diagnosis of gear transmission systems have attracted considerable attention in recent years, there is constant pressure to improve measuring techniques and tools for early detection and diagnosis of gearbox faults. The time and frequency localization properties of continuous wavelet transform offers a viab...
متن کاملUsing PCA with LVQ, RBF, MLP, SOM and Continuous Wavelet Transform for Fault Diagnosis of Gearboxes
A new method based on principal component analysis (PCA) and artificial neural networks (ANN) is proposed for fault diagnosis of gearboxes. Firstly the six different base wavelets are considered, in which three are from real valued and other three from complex valued. Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared...
متن کاملData Fusion and Multi-fault Classification Based On Support Vector Machines
As a new general machine-learning tool based on structural risk minimization principle, Support Vector Machines (SVM) has the advantageous characteristic of good generalization. For this reason, the application of SVM in fault diagnosis field has becomes one growing reach focus. In this paper, data fusion strategy based on multi-class SVMs is proposed to diagnose the gear fault. The fault featu...
متن کامل