A Study on Characteristics of Leak Signals of Pipeline Using Acoustic Emission Technique

2006 ◽  
Vol 110 ◽  
pp. 79-88 ◽  
Author(s):  
Min Rae Lee ◽  
Joon Hyun Lee
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Circular Hole ◽  
Frequency Component ◽  
Acoustic Emission Technique ◽  
Acoustic Parameters ◽  
Arrival Times ◽  
Time Frequency ◽  
Aerodynamic Model ◽  
Simulation Results

This study presents an approach to leak detection of pipeline review in terms of theoretical analysis such as acoustics and hydromechanics that should be accompanied by explanation of leakage. The acoustic emission signals during leak from circular hole of different geometries were studied both analytically and experimentally. The relationships between acoustic parameters and fluid mechanical parameters also were derived analytically. A quadrupole aerodynamic model was applied for the analysis of leak from the circular hole. Computer simulation results demonstrate the effectiveness of the proposed approach. In addition, it was confirmed that the wavelet transform (WT) was an effective tool to determine source location. That is, arrival times of each frequency component needed in the velocity calculation could be determined from the peak of the magnitude of wavelet transform data on the time-frequency plane.

Leak Detection of the Pipeline Using Acoustic Emission Technique

2004 ◽  
Author(s):  
Min-Rae Lee ◽  
Joon-Hyun Lee
Keyword(s):  
Computer Simulation ◽  
Acoustic Emission ◽  
Wavelet Transform ◽  
Circular Hole ◽  
Leak Detection ◽  
Mechanical Parameters ◽  
Acoustic Emission Technique ◽  
Acoustic Parameters ◽  
Aerodynamic Model ◽  
Simulation Results

This paper presents an approach to leak detection of pipeline review in term of theoretical analysis such as acoustics and hydromechanics that should be accompanied by explanation of leakage. The acoustic emission signals during leak from a circular hole of different geometries were studied both analytically and experimentally. The relationships between acoustic parameters and fluid mechanical parameters also were derived analytically. A quadrupole aerodynamic model was applied in the analysis of leak form the circular hole. Computer simulation results demonstrate the effectiveness of the proposed approach. In addition, the leak source location results are also presented by employing the wavelet transform.

scholarly journals Acoustic Emission Wavelet Analysis of Filament Wound Composite Tube Fatigue Damage Process

2015 ◽  
Vol 9 (1) ◽  
pp. 214-219 ◽  
Author(s):  
Su Hua ◽  
Chang Cheng
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Fatigue Damage ◽  
Frequency Band ◽  
Low Frequency ◽  
High Signal ◽  
Wave Form ◽  
Radial Compression ◽  
Time Frequency ◽  
Emission Signal

This paper performed a radial compression fatigue test on glass fiber winding composite tubes, collected acoustic emission signals at different fatigue damages stages, used time frequency analysis techniques for modern wavelet transform, and analyzed the wave form and frequency characteristics of fatigue damaged acoustic emission signals. Three main frequency bands of acoustic emission signal had been identified: 80-160 kHz (low frequency band), 160-300 kHz (middle frequency band), and over 300kHz (high frequency band), corresponding to the three basic damage modes: the fragmentation of matrix resin, the layered damage of fiber and matrix, and the fracture of cellosilk respectively. The usage of wavelet transform enabled the separation of fatigue damaged acoustic emission signals from interference wave, and the access to characteristics of high signal-noise-ratio fatigue damage.

scholarly journals Laser Ultrasound Inspection Based on Wavelet Transform and Data Clustering for Defect Estimation in Metallic Samples

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 573 ◽  
Author(s):  
Hossam Selim ◽  
Miguel Delgado Prieto ◽  
José Trull ◽  
Luis Romeral ◽  
Crina Cojocaru
Keyword(s):  
Wavelet Transform ◽  
Spatial Clustering ◽  
Clustering Algorithms ◽  
Ultrasonic Waves ◽  
Internal Defects ◽  
Destructive Testing ◽  
Arrival Times ◽  
Time Frequency ◽  
Ultrasonic Methods ◽  
Ultrasound Inspection

Laser-generated ultrasound is a modern non-destructive testing technique. It has been investigated over recent years as an alternative to classical ultrasonic methods, mainly in industrial maintenance and quality control procedures. In this study, the detection and reconstruction of internal defects in a metallic sample is performed by means of a time-frequency analysis of ultrasonic waves generated by a laser-induced thermal mechanism. In the proposed methodology, we used wavelet transform due to its multi-resolution time frequency characteristics. In order to isolate and estimate the corresponding time of flight of eventual ultrasonic echoes related to internal defects, a density-based spatial clustering was applied to the resulting time frequency maps. Using the laser scan beam’s position, the ultrasonic transducer’s location and the echoes’ arrival times were determined, the estimation of the defect’s position was carried out afterwards. Finally, clustering algorithms were applied to the resulting geometric solutions from the set of the laser scan points which was proposed to obtain a two-dimensional projection of the defect outline over the scan plane. The study demonstrates that the proposed method of wavelet transform ultrasonic imaging can be effectively applied to detect and size internal defects without any reference information, which represents a valuable outcome for various applications in the industry.

Development of Novel Optical Fiber AE Sensor with Multi-Sensing Function

2006 ◽  
Vol 321-323 ◽  
pp. 71-76 ◽  
Author(s):  
Hideo Cho ◽  
Takashi Naruse ◽  
Takuma Matsuo ◽  
Mikio Takemoto
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Optical Fiber ◽  
Monitoring System ◽  
Continuous Wavelet Transform ◽  
Steel Plate ◽  
Continuous Wavelet ◽  
Arrival Times ◽  
Resonance Frequencies ◽  
Different Diameters

A novel optical fiber acoustic emission (AE) system with multi-sensing function in single long fiber was developed and utilized for the estimation of AE sources of model steel plate and jointed pipes. Multi-sensing function was achieved by dividing the single sensing fiber into several sensor portions with different resonance frequencies. The resonance frequencies were provided by winding the sensing fiber around the solid rods (sensor holders) with different diameters. The monitoring system with three sensors in a 10 m long fiber was demonstrated to detect three wave packets with different frequencies and correctly estimate the source locations of AEs from artificial (Nelson-Sue) sources on a 0.9 wide x 1.8 m long steel plate. Here the arrival times of AEs for the source location were determined by the continuous wavelet transform. Source locations on the steel plate were determined within a distance error of 53 mm. The system also makes the location of the pipe with damage possible.

scholarly journals Improvement of Accuracy in Damage Localization Using Frequency Slice Wavelet Transform

2012 ◽  
Vol 19 (4) ◽  
pp. 585-596 ◽  
Author(s):  
Xinglong Liu ◽  
Zhongwei Jiang ◽  
Zhonghong Yan
Keyword(s):  
Wavelet Transform ◽  
Damage Identification ◽  
Lamb Waves ◽  
Group Velocity Dispersion ◽  
Propagation Distance ◽  
Primary Objective ◽  
Frequency Resolution ◽  
Damage Localization ◽  
Arrival Times ◽  
Time Frequency

Damage localization is a primary objective of damage identification. This paper presents damage localization in beam structure using impact-induced Lamb wave and Frequency Slice Wavelet Transform (FSWT). FSWT is a new time-frequency analysis method and has the adaptive resolution feature. The time-frequency resolution is a vital factor affecting the accuracy of damage localization. In FSWT there is a unique parameter controlling the time-frequency resolution. To improve the accuracy of damage localization, a generalized criterion is proposed to determine the parameter value for achieving a suitable time-frequency resolution. For damage localization, the group velocity dispersion curve (GVDC) of A0Lamb waves in beam is first accurately estimated using FSWT, and then the arrival times of reflection wave from the crack for some individual frequency components are determined. An average operation on the calculated propagation distance is then performed to further improve the accuracy of damage localization.

Time Frequency Analysis of Dispersive Waves by Means of Wavelet Transform

1995 ◽  
Vol 62 (4) ◽  
pp. 841-846 ◽  
Author(s):  
Kikuo Kishimoto ◽  
Hirotsugu Inoue ◽  
Makoto Hamada ◽  
Toshikazu Shibuya
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Gabor Wavelet ◽  
Flexural Wave ◽  
Lateral Impact ◽  
Dispersive Waves ◽  
Time Frequency Analysis ◽  
Arrival Times ◽  
Time Frequency ◽  
Wide Range

A new approach is presented for investigating the dispersive character of structural waves. The wavelet transform is applied to the time-frequency analysis of dispersive waves. The flexural wave induced in a beam by lateral impact is considered. It is shown that the wavelet transform using the Gabor wavelet effectively decomposes the strain response into its time-frequency components. In addition, the peaks of the time-frequency distribution indicate the arrival times of waves. By utilizing this fact, the dispersion relation of the group velocity can be accurately identified for a wide range of frequencies.

Rail crack monitoring based on Tsallis synchrosqueezed wavelet entropy of acoustic emission signals: A field study

2017 ◽  
Vol 17 (6) ◽  
pp. 1410-1424 ◽  
Author(s):  
Dan Li ◽  
Kevin Sze Chiang Kuang ◽  
Chan Ghee Koh
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Time Window ◽  
Field Tests ◽  
Local Variation ◽  
Monitoring Strategy ◽  
Wavelet Entropy ◽  
Time Frequency ◽  
Crack Monitoring ◽  
Synchrosqueezed Wavelet Transform

This article focuses on the rail crack monitoring using acoustic emission technique in the field typically with complex cracking conditions and high operational noise. A novel crack monitoring strategy based on Tsallis synchrosqueezed wavelet entropy was developed, where synchrosqueezed wavelet transform was introduced to explore the time–frequency characteristics of acoustic emission signals and Tsallis entropy was adopted to quantify the local variation of acoustic emission wavelet coefficients more accurately. The mother wavelet of synchrosqueezed wavelet transform and three key parameters of time-Tsallis synchrosqueezed wavelet entropy, including characteristic frequency band, non-extensive parameter, and time window length, were appropriately determined. The performance of the strategy was validated through field tests with an incipient rail crack and trains running at operating speeds. Time-Tsallis synchrosqueezed wavelet entropy efficiently detected and located the crack by extracting the crack-related transients in acoustic emission signals that were easily submerged in the operational noise. Synchrosqueezed wavelet transform further helped to analyze the mechanisms of these crack-related transients, which were distinguished to be either crack propagation or impact. The experimental results demonstrated that the crack monitoring strategy proposed is able to detect both surface and internal rail cracks even in the noisy environment, highlighting its potential for field applications.

Reflection technique in time‐frequency domain using multicomponent acoustic emission signals and application to geothermal reservoirs

Geophysics ◽  
2002 ◽  
Vol 67 (3) ◽  
pp. 928-938 ◽  
Author(s):  
Nobukazu Soma ◽  
Hiroaki Niitsuma ◽  
Roy Baria
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Frequency Domain ◽  
Random Noise ◽  
Spherical Shape ◽  
Source Distribution ◽  
S Wave ◽  
Spectral Matrix ◽  
Time Frequency ◽  
Reflected Wave

We have developed a reflection technique for estimating deep geothermal reservoir structures using acoustic emission signals as a source, which is useful when there is no proper estimating technique because of high temperature, high pressure, and great depth. Because its resolution is not high enough for comparison with methods such as well logging, we have enhanced the technique by developing a time–frequency‐domain analysis of multicomponent acoustic emission signals using a wavelet transform. The reflected wave is separated from an incoherent coda by analyzing the shape of a 3‐D hodogram: a linear shape indicates the arrival of a coherent signal such as a reflected wave, and an incoherent signal such as a coda makes a spherical shape. We construct a spectral matrix of 3‐D particle motion using a wavelet transform, as is done in a time–frequency domain. We evaluate the linearity of the 3‐D hodogram for each time and frequency by using the eigenvalues of the spectral matrix. Three‐dimensional inversion of the distribution of hodogram linearity in the time–frequency domain lets us image the deep subsurface structure. The inversion is based on the diffraction stack. We reduce the uncertainties by investigating S‐wave polarization direction, and we compensate for inhomogeneous source distribution to get reliable estimates with high resolution. We then evaluate our methods with synthetic signals. We discriminate a coherent wave from incoherent random noise in the presence of an S/N ratio of −3.7 dB and detect reflectors at correct depths with a small number of detectors. We apply the method to data from the European hot, dry rock site in Soultz‐sous‐Forêts, France, and compare our estimates with those from a number of borehole observations. The detected reflectors agree with the location of fracture zones. We demonstrate the feasibility of the method for detecting reflectors at great depths.

scholarly journals Wavelet application in acoustic emission signal detection of wire related events in pipeline

2021 ◽  
Author(s):  
Ran Wu
Keyword(s):  
Signal Processing ◽  
Acoustic Emission ◽  
Wavelet Transform ◽  
Signal Detection ◽  
Time Scale ◽  
Inspection Time ◽  
Time Frequency ◽  
Pipeline Inspection ◽  
Ae Signal ◽  
Thesis Work

This thesis establishes an automatic classification program for the signal detection work in pipeline inspection. Time-scale analysis provides the basic methodology of this thesis work. The wavelet transform is implemented in the program for filtering out the majority of noise and detect needed signals. As a popular nondestructive test, acoustic emission (AE) testing has been widely used in many physical and engineering fields such as leak detection and pipeline inspection. Among those applied AE tests, a common problem is to extract the physical features of the ideal events, so as to detect similar signals. In acoustic signal processing, those features can be represented as joint time frequency distribution. However, classical signal processing methods only give global information on either time or frequency domain, while local information is lots. Although the short-time Fourier transform (STFT) is developed to analyze time and frequency details simultaneously, it can only achieve limited precision. Other time-frequency methods are also applied in AE signal processing, but they all have the problem of resolution and time consuming. Wavelet transform is a time-scale technique with adaptable precision, which makes better feature extraction and detail detection. This thesis is an application of wavelet transform in AE signal detection where various noise exists. The wavelet transform with Morelet wavelet as the mother wavelet provides the basis of the program for auto classification in this thesis work. Finally the program is tested with two industrial projects to verify the workability of wavelet transforms and the reliability of the developed auto classifiers.

A new acoustic emission damage localization method using synchrosqueezed wavelet transforms picker and time-order method

2020 ◽  
pp. 147592172097704
Author(s):  
Jingkai Wang ◽  
Linsheng Huo ◽  
Chunguang Liu ◽  
Gangbing Song
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Damage Localization ◽  
Order Method ◽  
Time Difference Of Arrival ◽  
Localization Method ◽  
Time Frequency ◽  
Steel Bar ◽  
Time Order ◽  
Synchrosqueezed Wavelet Transform

Acoustic emission technique, as a passive structural health monitoring technique, has been widely applied to detecting and locating the structural damage. The time difference of arrival and the wave velocity are the key factors in most of the acoustic emission localization methods, and the accuracy of these two factors will affect the accuracy of damage localization. To improve the accuracy of damage localization, this article proposes a new damage localization method based on the synchrosqueezed wavelet transform picker and the time-order method. The synchrosqueezed wavelet transform picker, which picks the time–frequency similar point based on time–frequency similarity theory in the low-noise interval of time–frequency matrix, can improve the accuracy and robustness of calculating time difference of arrival. Meanwhile, the time-order method not only measures the wave velocity in real time but also reduces the computing time by appropriately arranging the distribution of acoustic emission sensors. These advantages improve the accuracy and robustness of acoustic emission localization, which was verified by experiments. Furthermore, the new localization method was employed to study the energy distribution in the embedded section of steel bar during the pull-out test of steel bar and concrete, and the results show the types of resistance between steel bar and concrete.

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