Acoustic emission (AE) based small leak detection of galvanized steel pipe due to loosening of screw thread connection

A leak detection system using acoustic emission methods is developed. For this, an experimental rig to detect leak was built using 8” galvanized steel pipe. The length of the pipe is 2 meters. A leak was made with 3 mm diameter and located in 1 meter from the end pipe. The pipe was filled with water and compressed until certain pressure reached. An acoustic emission transducer from Brüel and Kjær type 8313 is mounted on the pipe wall and connected to digital oscilloscope to detect AE signal. The experiment conducted by placing a sensor at a distance of 15 cm, 30 cm, 45 cm, 60 cm, and 75 cm from the position of the leak. Measurements were also performed with the variation of the pressure 3 bar, 4 bars, 5 bars, 6 bars, and 7 bar for those points.Considering acoustic emission wave travelling on pipe is plane wave, leak detection using energy attenuation emission become possible that is different from the method commonly used. Propagation constant is thus required and obtained based on experimental result where the amplitude varies with the spatial and pressure. It is found that for the case considered here. Subsequently, distance of leak location can be determined by the propagation constant and the ratio of energy. Using this method, the error of prediction is about 15.8 %.

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Leak detection for galvanized steel pipes due to loosening of screw thread connections based on acoustic emission and neural networks

Journal of Vibration and Control ◽

10.1177/1077546317720319 ◽

2017 ◽

Vol 24 (18) ◽

pp. 4122-4129 ◽

Cited By ~ 7

Author(s):

YJ Song ◽

SZ Li

Keyword(s):

Neural Networks ◽

Acoustic Emission ◽

Engineering Application ◽

Leak Detection ◽

Identification Accuracy ◽

Galvanized Steel ◽

Screw Thread ◽

Ann Model ◽

Pipe System ◽

Steel Pipes

Galvanized steel pipes with screw thread connections are widely used in indoor gas transportation. In contrast with the failure of pipe tubes, leakage in this system is prone to occur in the screw thread connections. Aiming at this specific engineering application, a method based on acoustic emission (AE) and artificial neural networks (ANNs) is proposed to detect small gas leaks. Experiments are conducted on a specifically designed galvanized steel pipe system with the manipulated leak occurring in the screw thread connection to acquire the raw AE data. The features in the time and frequency domains are extracted and selected to establish an ANN model for leak detection. It has been validated that the developed ANN-based leak detector can achieve an identification accuracy of over 98%. It is also verified that the proposed model is effective even when the AE signals due to a small leak pass over two screw thread connections or an elbow connection.

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Experimental validation of gas leak detection in screw thread connections of galvanized pipe based on acoustic emission and neural network

Structural Control and Health Monitoring ◽

10.1002/stc.2460 ◽

2019 ◽

Vol 27 (1) ◽

Author(s):

Chenyang Gong ◽

Suzhen Li ◽

Yanjue Song

Keyword(s):

Neural Network ◽

Acoustic Emission ◽

Experimental Validation ◽

Leak Detection ◽

Screw Thread ◽

Gas Leak

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Acoustic Emission-Based Small Leak Detection of Propulsion System Pipeline of Sounding Rocket

Shock and Vibration ◽

10.1155/2020/8875939 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Lin Gao ◽

Lili Dong ◽

Jianguo Cao ◽

Shaofeng Wang ◽

Wenjing Liu

Keyword(s):

Acoustic Emission ◽

Leak Detection ◽

Average Frequency ◽

Kernel Functions ◽

Estimation Accuracy ◽

Support Vector ◽

Pipeline System ◽

Small Leak ◽

Pipe Joints ◽

Pipe Joint

For pipes connected by pipe joints, leaks in the pipeline system are likely to occur at the pipe joints as opposed to the tube itself. Thus, early detection is critical to ensure the safety of the pipeline system. Based on acoustic emission (AE) techniques, this paper presents an experimental research on small leak detection in gas distribution pipelines due to loosening of the pipe joint connection. Firstly, the acoustic characteristics of leak signals are studied; then, features of signals are extracted. Finally, a classifier based on the support vector machine (SVM) technology is established, and the qualified features are selected to detect the leak. It is verified that the main frequency of the AE small leak signal due to the failure of the pipe joint is focused in the range of 33–45 kHz, and the algorithms based on SVM with kernel functions all can reach a better estimation accuracy of 98% using the feature “envelope area” or the feature set {standard deviation (STD), root mean square (RMS), energy, average frequency}.

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Development of Corrosion Depth Evaluation Method in Steel Pipe by Acoustic Emission Method

Zairyo-to-Kankyo ◽

10.3323/jcorr.70.40 ◽

2021 ◽

Vol 70 (2) ◽

pp. 40-46

Author(s):

Takuya Kurihara ◽

Matsuo Takuma ◽

Taro Kono ◽

Kaori Numata

Keyword(s):

Acoustic Emission ◽

Evaluation Method ◽

Steel Pipe ◽

Acoustic Emission Method ◽

Emission Method ◽

Corrosion Depth

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Theorical Analysis of Leakage in High Pressure Pipe Using Acoustic Emission Method

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.445.917 ◽

2012 ◽

Vol 445 ◽

pp. 917-922 ◽

Cited By ~ 3

Author(s):

Saman Davoodi ◽

Amir Mostafapour

Keyword(s):

High Pressure ◽

Acoustic Emission ◽

Degrees Of Freedom ◽

Oil And Gas ◽

Pipe Wall ◽

Leak Detection ◽

Stress Waves ◽

Motion Equation ◽

Non Linear ◽

Acoustic Emission Test

Leak detection is one of the most important problems in the oil and gas pipelines. Where it can lead to financial losses, severe human and environmental impacts. Acoustic emission test is a new technique for leak detection. Leakage in high pressure pipes creates stress waves resulting from localized loss of energy. Stress waves are transmitted through the pipe wall which will be recorded by using acoustic sensor or accelerometer installed on the pipe wall. Knowledge of how the pipe wall vibrates by acoustic emission resulting from leakage is a key parameter for leak detection and location. In this paper, modeling of pipe vibration caused by acoustic emission generated by escaping of fluid has been done. Donnells non linear theory for cylindrical shell is used to deriving of motion equation and simply supported boundary condition is considered. By using Galerkin method, the motion equation has been solved and a system of non linear equations with 6 degrees of freedom is obtained. To solve these equations, ODE tool of MATLAB software and Rung-Kuta numerical method is used and pipe wall radial displacement is obtained. For verification of this theory, acoustic emission test with continues leak source has been done. Vibration of wall pipe was recorded by using acoustic emission sensors. For better analysis, Fast Fourier Transform (FFT) was taken from theoretical and experimental results. By comparing the results, it is found that the range of frequencies which carried the most amount of energy is same which expresses the affectivity of the model.

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