Papers by Keyword: Morlet Wavelet

Abstract: Application of Fast Fourier Transform (FFT) in machinery faults detection is known to be only effective if fault is of repetitive in nature and considering severe. While minor and transient faults are usually remain undetected based on vibration spectrum analysis. Wavelet analysis is relatively new technique which is still suffered from inadequately in its time-frequency resolution. In this paper, ahmedrabak_time wavelet is proposed based on the wavelet reassignment technique for Morlet mother wavelet. The proposed wavelet analysis is compared to the conventional wavelet analysis for machinery faults detection based on simulated signal. The results showed that the proposed wavelet has a better resolution than conventional wavelet analysis which could clearly indicate the presence and the location of the fault.

Abstract: Signals with multiple transients are often encountered with much noise in engineering. The transient feature extraction has always been the key issue for signal analysis. A new signal de-noising method combining sparse representation and Morlet wavelet basis is proposed for signal de-noising and feature extraction. Simulation study concerning multiple transients signal shows the effectiveness of this method in transient feature extraction. The efficiency of this de-noising method is also verified by its application to extract fault signature for gearbox.

Abstract: This paper presents the convenient wavelet family for the fatigue strain signal analysis based on the wavelet coefficients. This study involves the Morlet and Daubechies wavelet coefficients using both the Continuous and Discrete Wavelet Transforms, respectively. The signals were collected from a front lower suspension arm of a passenger car by placing strain gauges at the highest stress locations. The car was driven over public road surfaces, i. e. pavé, highway and UKM roads. In conclusion, the Daubechies wavelet was the convenient wavelet family for the analysis. It was because the wavelet gave the higher wavelet coefficient values indicating that the resemblance between the wavelet and the signals was stronger, closer and more similar.

Abstract: Direct Sequence Spread Spectrum (DSSS) Communication has been widely applied in Personal communications network, WLAN, the third-generation mobile communications, satellite communications systems, military tactics communications and etc, thanks to the DSSS signals’ strong anti-interference ability, low probability of being intercepted and outstanding multi-access communication ability. At the same time, the Problem of estimating Signals has been of great research interest with the development of wind-band weak signals processing and communication antagonism. A new effective detection method of DSSS is proposed, combined the method of wavelet transformation with cycle spectral correlation approach, from the perspective of jamming in non-cooperation condition, and a simulation result of signals--BPSK is given.

Abstract: Wavelet analysis, as a new kind of time-frequency representation technique, has made great progress recently and been applied widely in different engineering practice. To solve the problem of full-wave Fourier algorithm which is disable to filter decaying DC component and has worse frequency characteristic, it is presented an improved algorithm depending on the combination of subtraction filter and full-wave Morlet complex wavelet, to get out the fundamental wave amplitude of the current in the distribution line, by studying each parameter’s influence on the performances of Morlet complex wavelet algorithm. It can filter decaying DC component efficiently and has better frequency characteristic.

Abstract: This paper describes a quantitative damage identification method for CF/EP composite laminates based on Lamb waves excited by distributed PZT wafers. The fundamental symmetric mode S0 is considered to detect defects (hole) in the plate. The Morlet wavelet and the cross-correlation analysis are introduced as signal processing tools for determining the time-of-flight (ToF) of Lamb wave. Considering the difference of Lamb wave velocities in different directions in a composite plate, the relationship of Lamb wave velocity in a unidirectional fibre reinforced laminate is studied and validated experimentally and numerically. In addition, a defect identification approach is revealed based on a regular arrangement of PZT wafers. Then, on the basis of the relationship of the wave velocity and the ToF, the location of a hole is identified by proposed method. Results demonstrate that the method is feasible in quantitative diagnosis of composite structures.

Abstract: Based on the wavelet scalogram obtained by Morlet wavelet transform and hard threshold de-noising filtering for typical acoustic emission signals, region segmented location method is introduced to get the number and accurate values of the characteristic frequencies, therefore the error induced by misjudgment and misreading can be avoided effectively. Then considering the weakness of large characteristic frequency error in Morlet wavelet scalogram, the feature extraction accuracy has been improved by combing region segmented location method and reassigned wavelet scalogram. Simulation results show that the proposed method has the merits of well rapidity, high reliability and briefness, hence can realize high precision feature extraction and has great practical value.

Abstract: A method of vibration analysis for mechanical fault detection based on adaptive noise canceling(ANC) and envelope analysis was presented. The adaptive filtering was used for noise canceling and feature extraction from vibration signal measured for the detection. The envelope analysis based on analytic wavelet was also used for the fault detection. Experiment shows that the method proposed in this paper is very effective for reducing noise, and for vibration analysis to discriminating the fault types with a high accuracy.

Abstract: This paper deals with a new scheme for prognostics of ball bearing based on Self-Organizing Map (SOM), back propagation neural-network and complex Morlet Wavelet methods. It uses complex Morlet wavelet-based envelope to extract successfully the characteristic frequencies of ball bearing. Then the minimum quantization error (MQE) indicator deriving from SOM is used for performance degradation assessment. Based on Weight Application to Failure Times (WAFT) technology, which deriving from back propagation neural networks, a prognostics model of ball bearing is developed successfully. And the experimental results show that the proposed methods are greatly superior to the currently used L10 bearing life prediction.