scholarly journals Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Boxiang Liu ◽  
Zhu Jiang ◽  
Wei Nie
Keyword(s):  
Negative Pressure ◽  
Pressure Wave ◽  
Inflection Point ◽  
Time Difference ◽  
Permutation Entropy ◽  
Economic Losses ◽  
Pipeline System ◽  
Denoising Method ◽  
Noise Interference ◽  
Negative Pressure Wave

Leakage problems are common in the water supply pipeline system, which will threaten the health of residents and cause economic losses. Negative pressure wave (NPW) technology calculates the time difference through the inflection point to locate the leak. However, due to the nonlinear and nonstationary characteristics of the pressure signal, it is difficult to obtain an accurate inflection point of the NPW by the traditional method. Therefore, the advantages of applying variational mode decomposition (VMD) in NPW technology are explored. Firstly, the correlation coefficient and permutation entropy (PE) are used for effective intrinsic mode function (IMF) component selection and parameter optimization. Thus, an adaptive denoising method based on VMD (AD-VMD) is presented. Then, to effectively separate the detail features of the NPW, a novel inflection point extraction method based on VMD (IPE-VMD) is proposed. Simulation and experimental results show that AD-VMD can effectively suppress noise interference and conserve the mutation characteristic of the leakage. IPE-VMD can obtain a distinct maximum peak at the inflection point and has good robustness to noise interference. This method can calculate the time difference precisely and stably. In addition, the accuracy of the leak location is verified. The average relative positioning error is 5.13%.

Pipeline Leak Detection Based on Double Sensor Negative Pressure Wave

2013 ◽  
Vol 313-314 ◽  
pp. 1225-1228 ◽  
Author(s):  
Chun Xia Hou ◽  
Er Hua Zhang
Keyword(s):  
False Alarm ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Detection System ◽  
Low Frequency ◽  
Leak Detection ◽  
Frequency Component ◽  
Economic Losses ◽  
Single Sensor ◽  
Negative Pressure Wave

Pipeline leak lead to huge economic losses and environmental pollution. Leak detection system based on single sensor negative pressure wave often causes false alarm. In this paper the double sensor method is adopted to exclude false alarm by determining the propagation direction of the pressure wave. In order to remove the inverse coherent interference caused by pump running, the phase difference of primary low frequency component is used to identify the sign of the time delay between the double sensors. The experiment shows the mothod is effective.

Research on Leak Monitoring Technology for Product Oil Pipeline

2012 ◽  
Author(s):  
Dongliang Yu ◽  
Bin Xu ◽  
Likun Wang ◽  
Dongjie Tan ◽  
Hongchao Wang ◽  
...  
Keyword(s):  
Acoustic Wave ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Mechanical Damage ◽  
Pipeline System ◽  
Accident Risk ◽  
Long Distance ◽  
Chemical Corrosion ◽  
Oil Pipeline ◽  
Negative Pressure Wave

As an important tool for the long-distance transportation of product oil, pipeline construction has being developed rapidly in recent years in the world. In the long-term running, leak will occur occasionally and seriously endanger the operation safety of the pipeline system, which may be caused by internal & external factors including pipe aging, mechanical damage, chemical corrosion, and natural disaster, etc. In order to timely find out and accurately locate the leakage, and reduce the economic loss and the accident risk, it is necessary to research into leak monitoring techniques and apply them in field. Compared with crude oil pipeline, due to multi-batch transportation, multi-distribution operation and frequent regulation, leak monitoring for product oil pipeline is much more difficult. Once leak occurs, the oil loss at the leakage point induces an oil pressure drop, causing negative pressure wave as well as acoustic wave. Through analyzing negative pressure wave signals and acoustic wave signals acquired by sensors, it can find out and locate the leakage. For interference signals like background noises in the product oil pipeline, wavelet packet decomposition technology is used to denoise the acquired negative pressure wave signals and acoustic wave signals, and extract the feature signals. Meanwhile, the signal velocity in product oil is calculated dynamically to improve the location accuracy. Field Tests indicate that the technology combining negative pressure wave and acoustic wave is accurate and reliable, and has good performance.

Application of SOM Network in Ship Pipeline Leakage Detecting

2012 ◽  
Vol 468-471 ◽  
pp. 538-541 ◽  
Author(s):  
Hong Hao Yin ◽  
Hui Chen ◽  
Zhong Bo Peng
Keyword(s):  
Neural Network ◽  
Working Conditions ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Oil And Gas ◽  
Pipeline System ◽  
Data Sampling ◽  
Long Distance ◽  
Som Network ◽  
Negative Pressure Wave

At present, ship pipeline leakage has become a great hidden risk of safe navigation and environmental pollution, but piping detecting technology mostly focuses on long-distance oil and gas pipeline, and does a little on the complicated pipeline system, for example, ship pipeline system. The frequently-used leakage detecting of negative pressure wave method, because the frequent adjustable pump or reset valve of ship pipeline system will also produce the negative pressure wave, may easily fail to report or even misreport. In order to monitor ship pipeline leakage effectively and greatly reduce fault alarm rate and missing alarm rate, SOM network (self-organizing feature map neural network) had been used to identify leakage from different working conditions. At first, the waveform characteristics of pressure and flow signals were analyzed by kurtosis calculating to obtain condition eigenvectors. From data sampling in terms of pipe working conditions, learning samples were obtained. Accordingly, the nonlinear mapping between SOM neural network inputs and outputs were well established via training. Afterwards, ship piping leakage was detected based on input eigenve

Projective Noise Reduction Algorithm for Negative Pressure Wave Signal Processing

2008 ◽  
Author(s):  
Dongliang Yu ◽  
Laibin Zhang ◽  
Liang Wei ◽  
Zhaohui Wang
Keyword(s):  
Noise Reduction ◽  
Negative Pressure ◽  
Pressure Wave ◽  
Random Noise ◽  
Background Signal ◽  
Long Distance ◽  
Noise Component ◽  
Wave Signal ◽  
Non Linear ◽  
Negative Pressure Wave

The appearance of a rupture, leak or damage in the long-distance oil & gas pipeline, which could cause a leak, usually generates a non-linear & chaotic negative pressure wave signal. By properly interpreting the negative pressure wave signature, it is possible to detect a leak along the pipeline. Most traditional noise reduction methods are established based on the linear system, which are not in line with the actual non-linear & chaotic situation. Therefore, the weak negative pressure wave signals, generated by small leaks, are often filtered out and cause false alarm and failure alarm. In order to resolve the problem, this paper uses the non-linear projective algorithm for noise reduction. First, the weak negative pressure wave signal series would be reconstructed using delay coordinates, in the high dimensional phase space, the background signal, the negative pressure wave signal and the noise signal are separated into different sub-spaces. Through the reconstruction of sub-spaces, the weak pressure wave signal can be isolated from the background signal as well as the random noise component reduced.

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