Research of the Power Harmonic Detection Method Based on Wavelet Packet Transform

2010 ◽  
Author(s):  
Xia Yang ◽  
Weicheng Xie
Keyword(s):  
Detection Method ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Harmonic Detection

A Detection Method for Friction Vibration Based on Harmonic Wavelet Packet Transform and Cross-Correlation Analysis

2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Pengfei Xing ◽  
Guobin Li ◽  
Ting Liu ◽  
Hongtao Gao ◽  
Guoyou Wang
Keyword(s):  
Steady State ◽  
Correlation Analysis ◽  
Cross Correlation ◽  
Detection Method ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Mean Square ◽  
Vibration Signals ◽  
Cross Correlation Analysis ◽  
Harmonic Wavelet

Running-in wear experiments were conducted on a spherical-on-disk tester. The vibration signals collected in the experiments were detected by a combination of harmonic wavelet packet transform (HWPT) and cross-correlation analysis (CCA) methods. Experimental results show that the friction vibration signals detected in tangential and normal directions have the characteristics of no time delay and strong correlation. Their root-mean-square (RMS) values gradually reduce and enter a steady-state of fluctuation with the experiments time, which are consistent with the variation of friction coefficient and reflect the change of wear states from the running-in wear to the stable wear. Therefore, the detection of friction vibration can be realized by a combination of HWPT and CCA methods.

scholarly journals Nonlinear Ultrasonic Detection Method for Delamination Damage of Lined Anti-Corrosion Pipes Using PZT Transducers

2018 ◽  
Vol 8 (11) ◽  
pp. 2240 ◽  
Author(s):  
Xiaobin Hong ◽  
Yuan Liu ◽  
Xiaohui Lin ◽  
Zongqiang Luo ◽  
Zhenwei He
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Wavelet Packet ◽  
Nonlinear Coefficient ◽  
Wavelet Packet Transform ◽  
Third Order ◽  
Ultrasonic Detection ◽  
Hilbert Huang Transform ◽  
Nonlinear Ultrasonic ◽  
Delamination Damage

Lined anti-corrosion pipes are widely used in oil and gas, petrochemical, pharmaceutical industries. However, defects, especially delamination, may occur in the production and service of pipes which result in safety accidents. Based on nonlinear ultrasonic theory, this paper studied the delamination detection method using the nonlinear harmonics for lined anti-corrosion pipes. The response characteristics of the anti-corrosion pipe were obtained through a sweep sine response experiment and the preferred excitation frequency was determined. The Wavelet Packet transform and Hilbert–Huang transform is applied for signal process and feature extraction. Then, a series of experiments were carried out and the results were analyzed and discussed. The results showed that a second-order and third-order nonlinear coefficient increased with the delamination damage. The amplitude of second-harmonic is much stronger than the third-order one. The mean squared error of the nonlinear coefficient, which was processed by Wavelet Packet transform and Hilbert–Huang transform, is smaller than wavelet packet transform and Discrete Fourier transform or processed only Hilbert–Huang transform. The higher harmonics can describe the change of delamination damage, which means that the nonlinear ultrasonic detection method could use for damage detection of anti-corrosion pipe. The nonlinear higher-harmonic is sensitive to delamination damage. The nonlinear ultrasonic method has the potential for damage detection for lined anti-corrosion pipes.

Looseness condition feature extraction of viscoelastic sandwich structure using dual-tree complex wavelet packet-based deep autoencoder network

2019 ◽  
Vol 19 (3) ◽  
pp. 873-884
Author(s):  
Yue Si ◽  
Zhousuo Zhang ◽  
Chuiqing Kong ◽  
Shujuan Li ◽  
Guigeng Yang ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Sandwich Structure ◽  
Detection Method ◽  
Sandwich Structures ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Vibration Response ◽  
Permutation Entropy ◽  
Response Signal ◽  
Complex Wavelet

It is significant to perform looseness condition detection of viscoelastic sandwich structures to avoid serious accidents. Due to the multilayer characteristic of the viscoelastic sandwich structure, the vibration response signal of such structures is nonlinear and nonstationary. Furthermore, the looseness condition feature signal contained in the vibration response signal is very puny. Condition feature extraction has become a challenging task in the looseness condition detection of viscoelastic sandwich structures. Therefore, a novel method called dual-tree complex wavelet packet-based deep autoencoder network is proposed for this task. First, the vibration response signal of the viscoelastic sandwich structure is decomposed by dual-tree complex wavelet packet transform and the sub-band signals which contain rich energy are extracted. Then, the energies of the extracted sub-band signals are calculated to form a feature set. Finally, a deep autoencoder network is established to fuse the feature set, and the fused feature is viewed as the detection index to detect the looseness condition of the viscoelastic sandwich structure. The proposed method is applied to the connecting bolt looseness condition detection of the viscoelastic sandwich structure to validate its effectiveness. Compared with the detection method based on dual-tree complex wavelet packet transform and energy and the detection method based on dual-tree complex wavelet packet transform and permutation entropy, the results indicate that the effectiveness of the proposed method in this article is more superior to that of the other two methods.

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