Nondestructive Evaluation of In-Isolation Pile Shaft Integrity by Wigner-Ville Distribution

2007 ◽  
Vol 23 (1) ◽  
pp. 15-21 ◽  
Author(s):  
S.-H. Ni ◽  
J.-J. Charng ◽  
K.-F. Lo
Keyword(s):  
Nondestructive Evaluation ◽  
Frequency Domain ◽  
Frequency Domain Analysis ◽  
Analysis Tool ◽  
Signal Process ◽  
Time Frequency ◽  
Concrete Piles ◽  
Integrity Testing ◽  
Signal Characteristics ◽  
Cast Concrete

AbstractThe Wigner-Ville Distribution is a new numerical analysis tool for signal process technique in the time-frequency domain and it can offer assistance and enhance signal characteristics for better resolution both easily and quickly. Time-frequency transform can describe how a spectrum of signals changes with time owing to defects and boundary conditions. In this study, five single pre-cast concrete piles have been tested and evaluated by both sonic echo method and Wigner-Ville distribution (WVD). The appropriateness of time-frequency domain analysis is discussed. Furthermore, two difficult problems in nondestructive evaluation problems are discussed and solved: the first one is with a pile with slight defect, whose necking area percentage is less than 10%, and the other is a pile with multiple defects. The results show that WVD can not only recognize the characteristics easily, but also locate the defects more clearly than the traditional pile integrity testing method.

NONDESTRUCTIVE INTEGRITY EVALUATION OF PC PILE USING WIGNER-VILLE DISTRIBUTION METHOD

2008 ◽  
Vol 22 (11) ◽  
pp. 959-964
Author(s):  
SHENG-HUOO NI ◽  
KUO-FENG LO ◽  
YAN-HONG HUANG
Keyword(s):  
Nondestructive Evaluation ◽  
Spectral Response ◽  
Structural Features ◽  
Analysis Tool ◽  
Signal Process ◽  
Distribution Method ◽  
Time Frequency ◽  
Concrete Piles ◽  
Integrity Testing ◽  
Cast Concrete

Nondestructive evaluation (NDE) techniques have been used for years to provide a quality control of the construction for both drilled shafts and driven concrete piles. This trace is typically made up of transient pulses reflected from structural features of the pile or changes in its surrounding environment. It is often analyzed in conjunction with the spectral response, mobility curve, arrival time, etc. The Wigner-Ville Distribution is a new numerical analysis tool for signal process technique in the time-frequency domain and it can offer assistance and enhance signal characteristics for better resolution both easily and quickly. In this study, five single pre-cast concrete piles have been tested and evaluated by both sonic echo method and Wigner-Ville distribution (WVD). Furthermore, two difficult problems in nondestructive evaluation problems are discussed and solved: the first one is with a pile with slight defect, whose necking area percentage is less than 10%, and the other is a pile with multiple defects. The results show that WVD can not only recognize the characteristics easily, but also locate the defects more clearly than the traditional pile integrity testing method.

A Portable Detecting and Analytic Instrument of Vibration Signal

2012 ◽  
Vol 442 ◽  
pp. 305-308
Author(s):  
Jian Wei Li ◽  
Ling Wang ◽  
Hong Mei Zhang
Keyword(s):  
Frequency Domain ◽  
Virtual Instrument ◽  
Vibration Signal ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Time Frequency ◽  
Notebook Computer ◽  
Usb Bus ◽  
Data Acquisition Card

It is often needed in engineering that detecting and analyzing vibration signal of some equipment. To meet the requirement, a portable detecting and analytic instrument was designed using virtual instrument concept. In the instrument, notebook computer was used as the platform of hardware. Vibration signal was obtained by integrated piezoelectric acceleration sensor (DTS0104T), and was transferred to a notebook computer through data acquisition card (NI USB-6210) based on USB bus. The software, running on the notebook computer, was developed under LabVIEW. Vibration signal could be displayed on screen, recorded in disk or printed by printer, retrieved, and analyzed. The analysis functions of the instrument include: time-domain analysis, frequency-domain analysis, time-frequency domain analysis, and correlation analysis. The instrument is compact, portable, powerful, and with friendly interfaces, has broad application prospects.

scholarly journals A Fault Diagnosis Method of Rolling Mill Bearing at Low Frequency and Overload Condition Based on Integration of EEMD and GA-DBN

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiang Ji ◽  
Chen Zhao ◽  
Yongqin Wang ◽  
Tuanmin Zhao ◽  
Xinyou Zhang
Keyword(s):  
Fault Diagnosis ◽  
Frequency Domain ◽  
Rolling Mill ◽  
Rolling Force ◽  
Low Frequency ◽  
Frequency Domain Analysis ◽  
Fault Classification ◽  
Low Speed ◽  
Time Frequency ◽  
Diagnosis Method

To solve the problems of difficult fault signal recognition and poor diagnosis effect of different damage in the same position in rolling mill bearing at low speed, a fault diagnosis method of rolling mill bearing based on integration of EEMD and DBN was proposed. The vibration signals in horizontal, axial, and vertical directions were decomposed and reconstructed by EEMD, and frequency domain analysis was carried out by using refined spectrum. Then, the signal's time-frequency domain index, rolling force, and torque component feature vector were input into genetic algorithm (GA) to optimize DBN model classification. In order to verify the effectiveness of the method, the experimental study was carried out on the two-high experimental rolling mill. The results show that EEMD combined with thinning spectrum can solve the problem of fault feature extraction well. Compared with time-frequency domain characteristic input, the prediction accuracy of DBN model is obviously improved. And the accuracy of GA-DBN model is higher, and the accuracy is 98.3%, and the time taken to diagnose is significantly reduced. Finally, the fault classification of different parts of bearings and the fault diagnosis of different damage in the same part are realized, which provides a good theoretical basis for the fault diagnosis of low-speed bearings and has important engineering significance.

scholarly journals OPTIMAL ACCURACY PERFORMANCE IN MUSIC-BASED EEG SIGNAL USING MATTHEW CORRELATION COEFFICIENT ADVANCED (MCCA)

2021 ◽  
Vol 83 (6) ◽  
pp. 53-61
Author(s):  
Mahfuzah Mustafa ◽  
Zarith Liyana Zahari ◽  
Rafiuddin Abdubrani
Keyword(s):  
Feature Extraction ◽  
Frequency Domain ◽  
Correlation Coefficient ◽  
Frequency Domain Analysis ◽  
Index Formula ◽  
Eeg Signal ◽  
Time Frequency ◽  
Matthew Correlation Coefficient ◽  
Accuracy Performance ◽  
Arousal And Valence

The connection between music and human are very synonyms because music could reduce stress. The state of stress could be measured using EEG signal, an electroencephalogram (EEG) measurement which contains an arousal and valence index value. In previous studies, it is found that the Matthew Correlation Coefficient (MCC) performance accuracy is of 85±5%. The arousal indicates strong emotion, and valence indicates positive and negative degree of emotion. Arousal and valence values could be used to measure the accuracy performance. This research focuses on the enhance MCC parameter equation based on arousal and valence values to perform the maximum accuracy percentage in the frequency domain and time-frequency domain analysis. Twenty-one features were used to improve the significance of feature extraction results and the investigated arousal and valence value. The substantial feature extraction involved alpha, beta, delta and theta frequency bands in measuring the arousal and valence index formula. Based on the results, the arousal and valance index is accepted to be applied as parameters in the MCC equations. However, in certain cases, the improvement of the MCC parameter is required to achieve a high accuracy percentage and this research proposed Matthew correlation coefficient advanced (MCCA) in order to improve the performance result by using a six sigma method. In conclusion, the MCCA equation is established to enhance the existing MCC parameter to improve the accuracy percentage up to 99.9% for the arousal and valence index.

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