scholarly journals Study on Vibration Characteristics of Natural Gas Pipeline Explosion Based on Improved MP-WVD Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Huayuan Ma ◽  
Yuan Long ◽  
Xinghua Li ◽  
Mingshou Zhong ◽  
Jianyuan Wu ◽  
...  
Keyword(s):  
Natural Gas ◽  
Frequency Distribution ◽  
Gas Pipeline ◽  
Frequency Resolution ◽  
Time Frequency ◽  
Natural Gas Pipeline ◽  
Precise Analysis ◽  
Nature Gas ◽  
Control State ◽  
Time Frequency Distribution

In order to meet the requirement of precise analysis of nature gas pipeline explosion, authors combined MP algorithm and WVD distribution to improve the time-frequency resolution and to solve the problem of cross-terms interference. The HHT algorithm was applied to the data preprocessing of MP algorithm to reduce the computational complexity of the MP algorithm. It improved the computing efficiency and laid the foundation for big data analysis. In this paper, authors carried out a full-size pipeline explosion experiment at the CNPC pipeline fracture control State Key Laboratory. Advantages of the improved MP-WVD algorithm were taken to obtain the time-frequency distribution characteristics of the pipeline explosion vibration. The research provided a new algorithm for the time-frequency distribution of nonstationary random vibration, and the result provided a reference for the safe operation and construction of natural gas pipeline.

Detection Method of Nature Gas Pipeline Leakage Based on Pattern Recognition

2011 ◽  
Vol 403-408 ◽  
pp. 3144-3148
Author(s):  
Shuai Wang ◽  
Jian Jun Yu ◽  
Ming Qing Yan ◽  
Shu Ying Xiao
Keyword(s):  
Pattern Recognition ◽  
Natural Gas ◽  
Safety Management ◽  
Gas Pipeline ◽  
Actual Condition ◽  
Pipeline Network ◽  
Natural Gas Pipeline ◽  
Detection Technology ◽  
Continuous Progress ◽  
Nature Gas

Natural gas pipeline network is one of the most important city lifeline. Because of the complex process of pipeline operation, there has not an authoritative and reliable way to detect leakage. Taking into account the current continuous progress of pipeline network simulation and mature of gas SCADA system, the fault of natural gas pipeline network can be diagnosed by pattern recognition method. The method takes full advantage of the existing detection technology and the actual condition of the pipe network. It is very useful for pipeline safety management and maintenance.

scholarly journals Experimental and Numerical Simulation Study on the Shock and Vibration Effect of OD1422-X80 Mainline Natural Gas Pipeline Explosion

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Huayuan Ma ◽  
Mingshou Zhong ◽  
Xinghua Li ◽  
Quanmin Xie ◽  
You Zhou ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Natural Gas ◽  
Ground Vibration ◽  
Gas Pipeline ◽  
Experimental Results ◽  
Maximum Speed ◽  
Impact Compression ◽  
Time Frequency ◽  
Vibration Effect ◽  
Natural Gas Pipeline

In this paper, the explosion experiment of the OD1422-X80 natural gas pipeline was carried out. The phenomenon of pipeline explosion was recorded, and a large amount of data on vibration effects were obtained. The data showed that the ground vibration during the explosion was mainly caused by the physical explosion process, and the subsequent gas explosion did not produce strong vibration. Based on the ANSYS/LS-DYNA platform, a numerical calculation model of this experiment was established. The numerical results agreed well with the experimental results. Simulation and experimental results showed that when the gas pressure in the pipe was lower than 7 MPa, the pipeline cracks stop growing. The maximum speed of the pipe wall moving outward reached 50 m/s, which formed a huge impact compression effect on the surrounding soil. This state spread to distant places and gradually decayed into an elastic stress wave, which formed a ground vibration effect. Time-frequency analysis was introduced into the vibration signal processing. The analysis results showed that the main frequency of pipeline explosion vibration was distributed around 10 Hz and had a long duration. The research results provided a reference for subsequent gas pipeline explosion test and numerical simulation research.

scholarly journals A Cascaded Approach for Correcting Ionospheric Contamination with Large Amplitude in HF Skywave Radars

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Yajun Li ◽  
Yinsheng Wei ◽  
Rujiang Guo ◽  
Rongqing Xu ◽  
Zhuoqun Wang ◽  
...  
Keyword(s):  
Frequency Distribution ◽  
Large Amplitude ◽  
Gradient Algorithm ◽  
Frequency Resolution ◽  
Good Effect ◽  
Distribution Method ◽  
Phase Gradient ◽  
Time Frequency ◽  
Phase Perturbation ◽  
Time Frequency Distribution

Ionospheric phase perturbation with large amplitude causes broadening sea clutter’s Bragg peaks to overlap each other; the performance of traditional decontamination methods about filtering Bragg peak is poor, which greatly limits the detection performance of HF skywave radars. In view of the ionospheric phase perturbation with large amplitude, this paper proposes a cascaded approach based on improved S-method to correct the ionospheric phase contamination. This approach consists of two correction steps. At the first step, a time-frequency distribution method based on improved S-method is adopted and an optimal detection method is designed to obtain a coarse ionospheric modulation estimation from the time-frequency distribution. At the second correction step, based on the phase gradient algorithm (PGA) is exploited to eliminate the residual contamination. Finally, use the measured data to verify the effectiveness of the method. Simulation results show the time-frequency resolution of this method is high and is not affected by the interference of the cross term; ionospheric phase perturbation with large amplitude can be corrected in low signal-to-noise (SNR); such a cascade correction method has a good effect.

Adaptive radial sinc kernel distribution and its application in mechanical fault diagnosis

2016 ◽  
Vol 231 (3) ◽  
pp. 485-493 ◽  
Author(s):  
Zhinong Li ◽  
Ming Zhu ◽  
Fulei Chu ◽  
Xuping He
Keyword(s):  
Fault Diagnosis ◽  
Frequency Distribution ◽  
Kernel Function ◽  
Rolling Bearing ◽  
Kernel Functions ◽  
Frequency Resolution ◽  
Good Time ◽  
Time Frequency ◽  
Fixed Kernel ◽  
Time Frequency Distribution

Based on the deficiency of fixed-kernel in the traditional time–frequency distribution, which is lack of adaptability, a new adaptive kernel function, which is named as the adaptive radial sinc kernel, is proposed according to design criteria of adaptive optimal kernel. The definition and algorithm of radial sinc kernel are given, and the proposed method is compared with the tradition time–frequency distribution. The simulation results show that the proposed method is superior to the traditional fixed-kernel functions, such as Wigner–Ville distribution, Choi–Williams distribution, cone-kernel distribution and continuous wavelet transform. The adaptive radial sinc kernel can overcome the deficiency of fixed-kernel function in traditional time–frequency distribution, adopt the optimizing method to filter the cross-terms adaptively according to the signal distribution, obtain good time–frequency resolution and has extensive adaptability for an arbitrary signal. Finally, the proposed method has been applied to the fault diagnosis of rolling bearing, and the experiment result shows that the proposed method is very effective.

Method of Displacement Parameters Prediction Based on Neural Network for Natural Gas Pipeline

2011 ◽  
Vol 79 ◽  
pp. 232-236 ◽  
Author(s):  
Shu Lin Liu ◽  
Xian Ming Wang ◽  
Rui Zhang ◽  
You Fu Tang ◽  
Rui Cong
Keyword(s):  
Neural Network ◽  
Numerical Simulation ◽  
Natural Gas ◽  
Working Conditions ◽  
Gas Pipeline ◽  
Isolation Method ◽  
Natural Gas Pipeline ◽  
Nitrogen Injection ◽  
Nature Gas ◽  
The Relationship

Theoretical investigation is not enough for natural gas pipeline displacement technology of nitrogen isolation method without isolator, which makes displacement parameters hard to be controlled accurately. Therefore, the method of natural gas pipeline displacement parameters prediction based on neural network is proposed in this paper. From Fluent numerical simulation, some useful information is acquired, such as displacement parameters under the typical working conditions, the relationship between different working conditions and nitrogen injection capacity. Moreover, the samples gained by simulation are trained by neutral network which has association function. Thus the aim of forecasting process parameter for nitrogen displacement technology without isolator is attained, which provides an important reference for the production of nitrogen displacement of nature gas pipeline without isolator.

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