Research on leak location method of water supply pipeline based on negative pressure wave technology and VMD algorithm

Liu, Boxiang; Jiang, Zhidi; Nie, Wei; Ran, Yijian; Hao, Lin

doi:10.1016/j.measurement.2021.110235

Cited by 27 publications

(6 citation statements)

References 30 publications

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“…A noisy signal with SNR of 6.800 dB is obtained by mixing Gaussian white noise into the signals s1(t) and s2(t). The noisy signals are denoised using wavelet, EMD, SNR-EMD [33], ADM-VMD [34] and our proposed method, respectively. Among them, the ADM-VMD method searches parameter K with the minimum sample entropy as the target by fixing parameter α as 2000.…”

Section: Simulation Analysismentioning

confidence: 99%

Research on Noise Reduction Method for Leakage Signal of Water Supply Pipeline

Jiang,

Wang,

Yang

et al. 2024

IEEE Access

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The negative pressure wave (NPW) signal caused by leakage of water supply pipeline contains a lot of noise due to the influence of water flow state and circuit noise, which will adversely affect the accuracy of leakage detection and leak location. To solve this problem, a novel pipeline pressure signal denoising method based on variational mode decomposition (VMD) is proposed in the paper. Firstly, the key parameters which affect the performance of VMD method: IMFs K and penalty factor α are optimized by genetic algorithm (GA) without prior knowledge. At the same time, different parameters are combined to form different reconstructed signals based on the correlation coefficient (CC). Secondly, the optimal combination of parameters is adaptively determined by using a fitness evaluation function based on the information entropy (IE). Thirdly, based on the optimal parameter combination, reconstruct the signal to achieve noise reduction. Finally, the denoised signal will be used for leak detection and leak location calculation. In order to verify the effectiveness of the proposed method, simulation analysis and laboratory experiments are carried out. Simulation analysis results show that the noise suppression effect of our method is better than that of wavelet, empirical mode decomposition (EMD) and VMD. The highest SNR obtained by our method is 16.187. The laboratory experiment results showed that the NPW signal denoised by proposed method had less error and more stable results in location, with an average relative error of 2.97%.

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Section: Simulation Analysismentioning

confidence: 99%

Research on Noise Reduction Method for Leakage Signal of Water Supply Pipeline

Jiang,

Wang,

Yang

et al. 2024

IEEE Access

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“…The photoacoustic signals collected by the Sagnac fiber optic sound sensing system are preprocessed into the signal recognition system. Firstly, the optical sound signal preprocessing is completed and sufficient sound signals are selected as training signals for feature extraction using the VMD algorithm [12,13] and MFCC [14]. The extracted features are used in a classification model based on BP neural network to complete the signal classification recognition and output the sound recognition results to be detected.…”

Section: Optical and Acoustic Signal Recognition Algorithm Designmentioning

confidence: 99%

Research on Multi-Source Simultaneous Recognition Technology Based on Sagnac Fiber Optic Sound Sensing System

Zheng,

Tang,

Wang

et al. 2023

Photonics

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To solve the problem of multiple sound recognition in the application of Sagnac optical fiber acoustic sensing system, a multi-source synchronous recognition algorithm was proposed, which combined the VMD (variational modal decomposition) algorithm and MFCC (Mel-frequency cepstral coefficient algorithm) algorithm to pre-process the photoacoustic sensing signal, and uses BP neural network to recognize the photoacoustic sensing signal. The modal analysis and feature extraction theory of photoacoustic sensing signal based on the VMD and MFCC algorithms were presented. The signal recognition theory analysis and system recognition program design were completed based on the BP neural network. Signal acquisition of different sounds and verification experiments of the recognition system have been carried out in a laboratory environment based on the Sagnac fiber optic sound sensing system. The experimental results show that the proposed optical fiber acoustic sensing signal recognition algorithm has a simultaneous recognition rate better than 96.5% for six types of sounds, and the optical acoustic signal recognition takes less than 5.3 s, which has the capability of real-time sound detection and recognition, and provides the possibility of further application of the Sagnac-based optical fiber acoustic sensing system.

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“…denotes the instantaneous amplitude of the th q IMF, () q t  denotes the instantaneous frequency of the th q IMF. And then, the f IMF contained blades biofouling feature is selected by the maximum correlation coefficient [15] between IMFs and instantaneous frequency rv () ft .…”

Section: A Stator Current Pre-processing Based On Ht and Vmdmentioning

confidence: 99%

An entropy clustering method for blades biofouling detection of marine current turbine under variable marine current speeds

Xu,

Wang,

Xie

et al. 2023

2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)

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Marine current turbine (MCT) attracts extensive attention as a renewable energy power generation equipment. However, accurate and reliable blades biofouling detection for MCT remains a significant challenge, especially under variable marine current speed. This paper proposes an entropy clustering method to improve the detection accuracy of blades biofouling for MCT under variable marine current speed. Firstly, the stator current signal is decomposed based on variational mode decomposition (VMD) to enlarge the feature of blades biofouling. Secondly, to eliminate the influence of swell effect, fluctuating features caused by swell effect are divided into each subspace based on the proposed entropy clustering method. At the last stage, principal component analysis models (PCA) are established in each feature subspace to detect blades biofouling. To verify the effectiveness of the proposed method, experiments are carried out on a 230W MCT platform. The results show that the proposed method has satisfactory performance for blades biofouling detection under variable marine current speed.

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Research on leak location method of water supply pipeline based on negative pressure wave technology and VMD algorithm

Cited by 27 publications

References 30 publications

Research on Noise Reduction Method for Leakage Signal of Water Supply Pipeline

Research on Noise Reduction Method for Leakage Signal of Water Supply Pipeline

Research on Multi-Source Simultaneous Recognition Technology Based on Sagnac Fiber Optic Sound Sensing System

An entropy clustering method for blades biofouling detection of marine current turbine under variable marine current speeds

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