Urban Gas Pipeline Research Articles

An intelligent monitoring approach for urban natural gas pipeline leak using semi-supervised learning generative adversarial networks

Traditional gas pipeline leak monitoring methods are subjected to the long response times and high false alarm rates. Deep learning can enhance the accuracy and real-time performance of pipeline leak monitoring. This paper develops an intelligent monitoring approach for urban gas pipeline leaks based on a semi-supervised learning Generative Adversarial Network (SGAN). First, the Isolation Forest algorithm is used to classify anomalies in the collected process parameter data of urban natural gas pipelines. One-Hot Encoding is used to label a small amount of sample data of pipeline leak. Second, both the labeled and unlabeled data are input into SGAN model for semi-supervised learning and classification to monitor the state of urban gas pipeline leak. The methodology addresses the imbalance between pipeline leak status data and normal data. The comparison with GAN and MLP shows that the methodology reaches the highest values in all evaluation metrics (precision = 94.1%, accuracy = 95.63%, recall = 93.93%, F1 score = 94.32%). The superior performance and accuracy make it more effective for urban natural gas pipeline leak monitoring.

A Risk Assessment Model of Gas Pipeline Leakage Based on a Fuzzy Hybrid Analytic Hierarchy Process

Given the rising urban demand for gas, it has emerged as a primary energy source for urban activities and daily life. However, China’s urban gas pipeline network has witnessed a surge in accidents, leading to significant losses and disasters. Therefore, it is particularly necessary to study the disaster risk assessment model caused by urban gas pipeline leakage. There are some problems in the previous evaluation methods, such as less consideration of the influence relationships between disaster factors. To redress this issue, a novel fuzzy hybrid analytic hierarchy process evaluation methodology is proposed. First, a hybrid hierarchical risk assessment model is developed by combining the analytic hierarchy process and the network analytic hierarchy process. Membership matrices and impact matrices are utilized to calculate comprehensive factor weights. This approach enhances the understanding of relationships between risk factors within the hierarchical structure model. Subsequently, employing a fuzzy evaluation method, the risk level matrix is derived by using multiplication and bounded operators to ascertain the risk level state. This solves the problem of the fuzzy boundaries when measuring the index factors of the gas pipeline network. Finally, experimental analysis is carried out on the gas pipeline network in the central area of a city and validates the model’s accuracy in practical applications.

Real-time detection of urban gas pipeline leakage based on machine learning of IoT time-series data

China is advancing urban gas pipeline safety through the strategic deployment of methane detectors. This study introduces a systematic approach for identifying underground gas leaks, and overcoming challenges such as biogas interference and environmental factors. Abnormal methane sequences, defined by expert experience, undergo data preprocessing, including cleansing, compressing, and extracting rising segments. Feature engineering is performed on these rising segments across three dimensions: temporal, volatility, and temperature features. Different classification algorithms, including K-nearest neighbor, decision tree, and support vector machine, are employed for gas leakage recognition. The decision tree proves most effective, achieving a 92.86% recall rate for methane leakage segments. Additionally, feature importance ranking from the decision tree model highlights the maximum value of preprocessed methane concentration time series and the fitting slope of the rising segment as crucial features for methane leakage detection.

Prediction of the residual lifetime of bitumen coatings on urban gas pipelines from the change in their mechanical characteristics during thermal-oxidative aging

Residual life of bitumen insulation is an important parameter of urban gas pipelines. Its fast and reliable estimation is necessary for timely health monitoring and coating restoration. In this study, we propose to define lifespan of bitumen insulation in situ from the mechanical characteristics measured during its thermal-oxidative aging. For evaluation of elastic and viscous properties, micro-impact dynamic indentation was applied. We determined the values of activation energy under thermal destruction and the dependence of transient electrical resistance on the critical values of coating's mechanical properties. Obtained experimental data foster real-time estimation of service time of insulation without coating removal.

Research on generation paths of production safety accidents in urban gas pipeline networks: A fuzzy set qualitative Comparative analysis (fsQCA) based on Chinese data

The production safety accidents in urban gas pipeline networks of China have shown a frequent trend in recent years, which has become the main obstacle to the high-quality development of urban gas industry. In this paper, based on 38 typical accidents that occurred in mainland China from 2012 to 2022, the fuzzy set Qualitative Comparative Analysis (fsQCA) method was applied to explore the accident generation paths. We identified seven condition variables and one result variable, then six condition configurations were derived through the fsQCA method to classify the accident generation paths into four types: "illegal operation", "Equipment failure", "third-party activities damage", and "multiple risk coupling". The results show that: (1) Interrupting the generation paths of accidents caused by illegal operation and multiple risk coupling not only requires local governments and regulatory departments to strengthen safety supervision, but also requires gas enterprises to improve their safety management organizational structures and safety production management systems; (2) Strengthening daily inspection, maintenance, and risk monitoring of urban gas pipeline networks is the core of curbing accidents caused by equipment failure; (3) Deepening cooperation between gas enterprises and third-party units is the key to prevent and control accidents caused by third-party activities damage; (4) Local governments and gas enterprises should strengthen cooperation to improve the effectiveness of accident prevention and control by building the risk synergetic governance model. This study provides theoretical guidance for preventing production safety accidents in urban gas pipeline networks of China.

A defect contour imaging method of small diameter pipeline based on self-made three-dimensional magnetic sensor

PurposeThe purpose of this paper is to use the corresponding magnetic sensor and detection method to detect and image the defects of small diameter pipelines. Urban gas pipeline is an energy transportation tool for urban industrial production and social life, which is closely related to urban safety. Preventing the occurrence of urban gas pipeline transportation accidents and carrying out pipeline defect detection are of great significance for the urban economic and social stability. To perform pipeline defect detection, the magnetic flux leakage internal detection method is generally used in the detection of large-diameter long-distance oil and gas pipelines. However, in terms of the internal detection of small-diameter pipelines, due to the heavy weight, large structure of the detection device and small pipe diameter, the detection is more difficult.Design/methodology/approachIn order to solve the above matters, self-made three-dimensional magnetic sensor and three-dimensional magnetic flux leakage imaging direct method are proposed for studying the defect identification. Firstly, for adapting to the diameter range of small-diameter pipelines, and containing the complete information of the defect, a self-made three-dimensional magnetic sensor is made in this paper to improve the accuracy of magnetic flux leakage detection. And on the basis of it, a small diameter pipeline defect detection system is built. Secondly, as detection signal may be affected by background magnetic field interference and the jitter interference, the complete ensemble empirical mode decomposition with adaptive noise method is utilized to screen the detected signal. As a result, the useful signal is reconstructed and the interference signal is removed. Finally, the defect contour inversion imaging of detection is realized based on the direct method of three-dimensional magnetic flux leakage imaging, which includes three-dimensional magnetic flux leakage detection data and data segmentation recognition.FindingsThe three-dimensional magnetic flux leakage imaging experimental results shown that, compared to the actual defects, the typical defects, irregular defects and crack groove defects can be analyzed by the magnetic flux leakage defect contour imaging method in qualitative and quantitative way respectively, which provides a new idea for the research of defect recognition.Originality/valueA three-dimensional magnetic sensor is made to adapt the diameter range of small diameter pipeline, and based on it, a small-diameter pipeline defect detection system is built to collect and display the magnetic flux leakage signal.

Research on the vibration response characteristics of PE gas pipeline aimed for third-party damage monitoring

Third-party damage (TPD) incidents account for over 73% in China, becoming the primary cause of urban buried gas pipeline disruption. Therefore, real-time monitoring of TPD holds significance. This passage introduces a novel method for third-party damage monitoring of urban gas pipeline networks without excavation. The approach involves installing acoustic sensors in the pipeline to detect abnormal signals caused by construction activities. While the effectiveness of this method has been confirmed for buried steel pipelines, the propagation patterns, frequency characteristics, and the impact of fluid flow within PE pipelines remain unclear. To this end, this study explores these issues through experiments and simulations. According to the research, sound waves are the primary mode of signal propagation. The impact of gas pressure can be disregarded, but if the flow is reversed, the signal will weaken by 26%. The signal energy is concentrated in the 0–2 kHz range, decreasing exponentially as the distance increases. Moreover, a positive linear correlation exists between the signal energy and the load size to the power of 0.1. This research provides theoretical support for studying third-party damage monitoring technology and identifying and localizing damage types.

A probabilistic analysis method for evaluating the safety & resilience of urban gas pipeline network

Urban gas pipeline networks (UGPN) provide important support for high-quality urbanization. Therefore, it is imperative to analyze and assess the potential failures of UGPN. A novel probabilistic analysis method is proposed for assessing the safety and resilience of UGPN. Firstly, Bow-Tie analysis is used to identify faults. Then, a four-dimensional resilience assessment network is developed. Bayesian network is utilized to model the relationship between the variables, while dynamic Bayesian network is used to consider the dynamic nature of the system. The results of the study show that the proposed model can accurately estimate faults, consequences, and influence paths. Furthermore, the resilience analysis shows that monitoring the objective conditions is crucial and that the initial failure probability of the UGPN decreases from 0.03767 % to 0.01435 % when connected to a resilience network, indicating that considering resilience can effectively improve the reliability and safety of the UGPN. Two application examples are presented in the paper to validate the functionality of the proposed model. The proposed model can be used to set the state of UGPN to predict the probability of occurrence of a specific event and its consequences and to simulate the improvement trend of UGPN based on the direction of focus of future work.

Temporal dynamics of urban gas pipeline risks

Urban gas pipelines pose significant risks to public safety and infrastructure integrity, necessitating thorough risk assessment methodologies to mitigate potential hazards. This study investigates the dynamics of population distribution, demographic characteristics, and building structures to assess the risk associated with gas pipelines. Using geospatial analysis techniques, we analyze population distribution patterns during both day and night periods. Additionally, we conduct an in-depth vulnerability assessment considering multiple criteria maps, highlighting areas of heightened vulnerability in proximity to gas pipelines and older buildings. This study incorporated the concept of individual risk and the intrinsic parameters of gas pipelines to develop a hazard map. Hazard analysis identifies areas with elevated risks, particularly around main pipeline intersections and high-pressure zones. Integrating hazard and vulnerability assessments, we generate risk maps for both day and night periods, providing valuable insights into spatial risk distribution dynamics. The findings underscore the importance of considering temporal variations in risk assessment and integrating demographic and structural factors into hazard analysis for informed decision-making in pipeline management and safety measures.

Feature extraction and pattern recognition of gas pipeline flow noise signals in a strong noisy background.

The purpose of this study is to put forward a feature extraction and pattern recognition method for the flow noise signal of natural gas pipelines in view of the complex situation brought by the rapid development and expansion of urban natural gas infrastructure in China, especially in the case that there are active and abandoned pipelines, metal and nonmetal pipelines, and natural gas, water and power pipelines coexist in the underground of the city. Because the underground situation is unknown, gas leakage incidents caused by natural gas pipeline rupture occur from time to time, posing a threat to personal safety. Therefore, the motivation of this study is to provide a feasible method to accelerate the aging, renewal and transformation of urban natural gas pipelines to ensure the safe operation of urban natural gas pipeline network and promote the high-quality development of urban economy. Through the combination of experimental test and numerical simulation, this study establishes a database of urban natural gas pipeline flow noise signals, and uses principal component analysis (PCA) to extract the characteristics of flow noise signals, and develops a mathematical model for feature extraction. Then, a classification and recognition model based on backpropagation neural network (BPNN) is constructed, which realizes the detection and recognition of convective noise signals. The research results show that the theoretical method based on acoustic feature analysis provides guidance for the orderly and safe construction of urban natural gas pipeline network and ensures its safe operation. The research conclusion shows that through the simulation analysis of 75 groups of gas pipeline flow noise under different working conditions. Combined with the experimental verification of ground flow noise signals, the feature extraction and pattern recognition method proposed in this study has a recognition accuracy of up to 97% under strong noise background, which confirms the accuracy of numerical simulation and provides theoretical basis and technical support for the detection and recognition of urban gas pipeline flow noise.

Leakage Diffusion Modeling of Key Nodes of Gas Pipeline Network Based on Leakage Concentration

In order to achieve the prediction and early warning of city gas pipe network leakage accidents, as well as to provide rapid and precise support for emergency response to such accidents, this study focuses on a Gaussian diffusion model applied to a large urban gas pipeline network. Specifically, it investigates the gas gate wells, which are key nodes in the pipeline network, to develop a leakage model. The objective is to analyze the variation in internal gas concentration in the gate wells and determine the range of danger posed by external gas diffusion from the gate wells. In addition, Fluent simulation is utilized to compare the accuracy of the model’s calculations. The findings of this study indicate that the gas concentration inside the gate well, as predicted by the model fitting results and Fluent simulation, exhibit a high level of agreement, with coefficient of determination (R2) values exceeding 0.99. Moreover, when predicting the hazardous distance of gas leakage outside the gate well, the model’s results show an average relative error of 0.15 compared to the Fluent simulation results. This demonstrates that the model is highly accurate and meets the practical application requirements.

Research on Deflagration Hazard and Its Influencing Factors on Urban Gas Pipeline

Abstract In this paper, the hazard criteria for thermal radiation and shock wave overpressure applicable to the deflagration of urban gas pipelines have been proposed. The phast software is used to analyze the hazard intensity and degree of pipeline deflagration. Based on the hazard criteria, the situation of personnel and object damage is determined, and targeted risk control points are proposed. The influence of the parameters of wind speed, atmospheric stability, air humidity, and operating pressure on the deflagration hazard is studied. The work presented in this paper can provide a reference for the disaster assessment and safety management of urban gas pipelines.

Identification and Number Prediction of Natural Gas Heating Users in a Company in Chengdu

Nowadays, more and more residents in Sichuan and Chongqing area choose to use gas for heating in winter, and the demand for gas is increasing. Therefore, it is necessary to improve the refined management of residential gas consumption. Firstly, this paper uses K-means clustering according to the gas consumption data from 2017 to 2021 provided by a company in Chengdu, so as to obtain the regulation of residents’ gas consumption. According to the different users’ gas consumption habits, the gas heating users in 2017 are identified. Then, a better SVM model is selected in SVM, KNN and logistic regression to classify the gas consumption data in 2018-2021. Finally, according to the classification results, the grey model is used to predict the number of gas heating users in the next two years, and compared with the real data in 2022, the results shows that the model effect is good. This study provides strong theoretical and technical support for gas companies to rationally plan gas consumption and optimize the operation of urban gas pipeline network.

Dynamic risk investigation of urban natural gas pipeline accidents using Stochastic Petri net approach

The safety of urban gas pipelines is challenged by a series of adverse factors, and the unexpected accidents may pose a catastrophic threat to humans, the environment and assets. The existing studies mainly focused on causation investigation of natural gas pipeline accident, the dynamic evolution process of urban natural gas pipeline accident is still challenging task for accident prevention. To find out the unfavorable factors that cause accidents, this study presents a dynamic risk modeling of urban natural gas pipeline accidents using Stochastic Petri net (SPN). An SPN model of an accident evolution process is constructed based on the discrete events in an accident flowchart, and the critical places and transitions are evaluated through this model. Considering the slow development of the early events leading to accidents, the delay time of the transitions at this stage cannot be determined, Bayesian theory is used to dynamically update SPN model. Critical accident nodes and their occurrence probabilities are estimated, which are used to support the efficient risk management strategies. The gas explosion accident in Shiyan, Hubei, as a representative case is investigated, and the results show that pipeline corrosion, ignition sources, inefficient information feedback and unreasonable solutions are critical accident causations. The probabilities of critical accident nodes increase over time, which means that these factors need to be managed efficiently to prevent the accidents. The application shows that the model can be used as a tool for gas companies and governments to investigate urban gas pipeline accidents.

Data-Driven Urban Gas Pipeline Integrity Detection and Evaluation Technology System

At present, PE pipelines are widely used in urban gas pipeline networks. As pipeline safety is of great importance to the gas supply, this paper focuses on the safety and reliability of PE pipes during service. First of all, this paper analyzes the aging factors of PE materials and the failure forms and mechanisms of PE pipes. Second, the performance testing methods of PE pipelines are summarized, including pipeline pressure tests, pipeline condition inspections, welded joint inspections, mechanical performance tests, and physical performance tests. In addition, life prediction methods for PE pipelines are introduced and analyzed. The methods and applicability of tensile experiments and DSC experiments based on thermal oxygen aging are both analyzed, and the corresponding experiments are also carried out. On the basis of the above research, the technical system of the integrity detection and evaluation of urban gas pipelines is finally established. The system includes the integrity detection method of urban gas pipelines and the applicability evaluation and determination of retest cycles, which can provide a reference for the safe operation of urban gas pipeline networks.

Study on Noise Source Analysis and Control Method of Gas Station

With the rapid development of economy, environmental issues have attracted more and more attention from all walks of life. As a new type of efficient energy, urban gas plays a vital role in promoting the healthy development of cities and mitigating urban air pollution. As the hub of urban gas, gas stations play the role of gas distribution, peak regulation and pressure regulation, and are necessary facilities for the safe and stable operation of urban gas pipeline network. With the increase of the number of urban gas stations, the noise problem generated by the stations is becoming increasingly prominent, which seriously affects the quality of people’s life and social environment. Based on the analysis of the causes of gas station noise, this paper analyzes the noise control strategy of gas station.

Application of Intelligent and Automation Technology in Operation and Management of Urban Gas Pipeline Network

Application of Intelligent and Automation Technology in Operation and Management of Urban Gas Pipeline Network

Analysis of the Causes and Countermeasures of Emergency Disposal Failure of Urban Gas Pipeline Leakage Accident

Analysis of the Causes and Countermeasures of Emergency Disposal Failure of Urban Gas Pipeline Leakage Accident

Interchangeability of Hydrogen Injection in Zhejiang Natural Gas Pipelines as a Means to Achieve Carbon Neutrality

The blending of hydrogen gas into natural gas pipelines is an effective way of achieving the goal of carbon neutrality. Due to the large differences in the calorific values of natural gas from different sources, the calorific value of natural gas after mixing with hydrogen may not meet the quality requirements of natural gas, and the quality of natural gas entering long-distance natural gas and urban gas pipelines also has different requirements. Therefore, it is necessary to study the effect of multiple gas sources and different pipe network types on the differences in the calorific values of natural gas following hydrogen admixing. In this regard, this study aimed to determine the quality requirements and proportions of hydrogen-mixed gas in natural gas pipelines at home and abroad, and systematically determined the quality requirements for natural gas entering both long-distance natural gas and urban gas pipelines in combination with national standards. Taking the real calorific values of the gas supply cycle of seven atmospheric sources as an example, the calorific and Wobbe Index values for different hydrogen admixture ratios in a one-year cycle were calculated. The results showed that under the requirement of natural gas interchangeability, there were great differences in the proportions of natural gas mixed with hydrogen from different gas sources. When determining the proportion of hydrogen mixed with natural gas, both the factors of different gas sources and the factors of the gas supply cycle should be considered.

Small-Diameter Tube Wall Damage-Detection Method Based on TE01 Mode Microwave.

Accidents occur frequently in urban gas pipelines, and pipeline damage detection is an important means of ensuring pipeline safety. Aiming at the problem that the small diameter pipeline is difficult to detect, this paper proposes a detection method for the inner wall damage of a small-diameter pipeline based on the TE01 mode microwave and uses the TE01 mode to detect the inner wall damage of the pipeline by the terminal short-circuit reflection method. By analyzing the transition of microwave propagation mode at the defect, based on the Maxwell equation and the field distribution equation of the TE01 mode microwave in the pipe and the pipe wall current equation, the microwave reflection coefficient at the defect is established when the microwave distortion modes at the defect are TE and TM modes. A small-diameter pipeline simulation model is established, and the influence of the electric field, magnetic field, wall current distribution, and reflected wave reflection coefficient in the pipeline when inner wall defects of different widths are analyzed using the finite integral theory during microwave detection of the TE01 mode. An experimental platform for the microwave detection of small-diameter pipes was built to detect defects on the inner walls of pipes with different widths. The results show that the inner wall defect causes the electric field, magnetic field, current propagation period, and energy distribution of the TE01 mode microwave propagated in the pipe to be distorted, and the microwave reflection coefficient and return loss exhibit a significant frequency shift with the change in the defect width. The experimental and simulation results had a good consistency.