Research on a small-noise reduction method based on EMD and its application in pipeline leakage detection

Lu, Wenqing; Zhang, Laibin; Liang, Wei; Yu, Xuchao

doi:10.1016/j.jlp.2016.02.017

Cited by 49 publications

(10 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…11 In Tao et al, 12 a fault detection method via the EMD based on local characteristic time scales of the analyzed signal. In Lu et al, 13 an improved EMD method is used to recognize leak feature extraction of a fluid pipeline.…”

Section: Introductionmentioning

confidence: 99%

Pipeline leak detection based on empirical mode decomposition and deep belief network

Yan

Yuan

et al. 2022

Measurement and Control

View full text Add to dashboard Cite

Leak detection of an oil pipeline can prevent environmental and financial losses. A method for the cyber-physical system of pipeline leak detection is proposed based on the empirical mode decomposition (EMD) and deep belief network (DBN). Experiment data are acquired from an oil pipeline company. The EMD is suitable for noise removal and signal reconstruction from raw pressure signals, and the reconstructed signals are used to establish a DBN model of pipeline leakage. Our proposed method obtains higher-recognition-accuracy results (98% accuracy) and can more effectively identify leak detection than the twin support vector machine (TWSVM), support vector machine (SVM), and back-propagation neural network (BPNN).

show abstract

Section: Introductionmentioning

confidence: 99%

Pipeline leak detection based on empirical mode decomposition and deep belief network

Yan

Yuan

et al. 2022

Measurement and Control

View full text Add to dashboard Cite

show abstract

“…The method of leak location based on the negative pressure wave (NPW) has become one of the research hotspots [7][8][9]. When the pipeline leaks, the pressure at the leakage point will drop rapidly, and this pressure drop named the NPW inflection point will propagate to both sides of the leakage point in the form of a negative pressure wave.…”

Section: Introductionmentioning

confidence: 99%

Research on Leakage Location of Pipeline Based on Module Maximum Denoising

Zhang

Jiang

2022

Applied Sciences

View full text Add to dashboard Cite

Leak detection and location of water supply pipelines is an important area of research, and it is especially important to find the leakage location in time and repair them. In view of the problem, that a large amount of noise is mixed in the detection signal when the pipeline leaks, it will inevitably affect the detection and positioning effect. In this paper, a denoising algorithm based on improved module maximum is proposed. Firstly, a discrete binary wavelet transform is carried out on the noisy signal, and the module maximum point corresponding to the wavelet transform coefficients, on each scale, is obtained. Secondly, different thresholds are used for the module maximum of different scale layers and the wavelet coefficients are reconstructed according to the retained module maximum and their extremums. Thirdly, the alternative projection algorithm is used to effectively suppress the false oscillations in the reconstructed signal, improve the quality of the reconstructed signal, and obtain the noise reduction signal. Finally, according to the theory of the negative pressure wave, the inflection point of the negative pressure wave is identified by the wavelet decomposition method, and the location of leakage point is determined. In order to verify the effectiveness of the proposed algorithm, a leakage simulation experiment system of water supply pipeline is built. The analysis of the results shows that, compared with the wavelet denoising method and the EMD-based method, the method proposed in this paper achieves a better denoising effect, obtains a smoother pressure signal, retains the signal waveform characteristics, and identifies the obvious inflexion point of the negative pressure wave. The minimum relative error of leakage point location is 0.9%, and the maximum relative error is 2.5%.

show abstract

“…The real-time detection technology can monitor the pipeline status online with high efficiency. NPW is the preferred technology among them [13], and it has an excellent application prospect in the leakage detection of water supply pipelines.…”

Section: Introductionmentioning

confidence: 99%

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

2021

View full text Add to dashboard Cite

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%.

show abstract

Research on a small-noise reduction method based on EMD and its application in pipeline leakage detection

Cited by 49 publications

References 28 publications

Pipeline leak detection based on empirical mode decomposition and deep belief network

Pipeline leak detection based on empirical mode decomposition and deep belief network

Research on Leakage Location of Pipeline Based on Module Maximum Denoising

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

Contact Info

Product

Resources

About