SDH-FCOS:An Efficient Neural Network for Defect Detection in Urban Underground Pipelines

Urban underground pipelines are an important infrastructure in cities,and timely investigation of problems in underground pipelines can help ensure the normal operation of cities.Owing to the growing demand for defect detection in urban underground pipelines,this study developed an improved defect detection method for urban underground pipelines based on fully convolutional one-stage object detector(FCOS),called spatial pyramid pooling-fast(SPPF)feature fusion and dual detection heads based on FCOS(SDH-FCOS)model.This study improved the feature fusion component of the model network based on FCOS,introduced an SPPF network structure behind the last output feature layer of the backbone network,fused the local and global features,added a top-down path to accelerate the circulation of shallowinformation,and enriched the semantic information acquired by shallow features.The ability of the model to detect objects with multiple morphologies was strengthened by introducing dual detection heads.The experimental results using an open dataset of underground pipes show that the proposed SDH-FCOS model can recognize underground pipe defects more accurately;the average accuracy was improved by 2.7% compared with the original FCOS model,reducing the leakage rate to a large extent and achieving real-time detection.Also,our model achieved a good trade-off between accuracy and speed compared with other mainstream methods.This proved the effectiveness of the proposed model.

Building Information Modeling-Based Secondary Development System for 3D Modeling of Underground Pipelines

Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.

Research of Risk Identification and Prevention of Underground Pressure Pipelines Damage Caused by External Disturbance

External disturbance is an important cause of underground pressure pipeline damage,which leads to accidents,and it is crucial to study the risk of damage caused by external disturbance and come up with proper prevention and control measures.We reviewed literature on risk identification of underground pressure pipelines damage due to external disturbance was conducted,and a list of risk factors was formed.Based on the list of risk factors,fault tree analysis was carried out on underground pressure pipelines damage caused by external disturbances,and risk prevention and control measures were proposed through the calculation of minimum cut sets,minimum path sets,and structural importance,in hopes of providing reference for the normal operation of underground pressure pipelines.

Experimental and finite element analyses on the corrosion of underground pipelines

Underground pipelines, on which a city relies for survival and development, have become an important part of lifeline engineering. Underground pipelines are utilized for conveying liquid, gas or loose solid, pipeline leakage and damage occasionally resulting from corrosion. Corrosion monitoring of underground pipelines is aimed at ensuring their normal operation and preventing loss of life and property. In this paper, a new method to monitor corrosion of pipelines has been proposed to solve the mentioned problem. Under the influence of internal pressure and corrosion, the pipeline wall becomes thinner and the circumferential deformation increases. The method is to indirectly investigate pipeline corrosion by monitoring the circumferential deformation. Numerical simulation confirms that the circumferential strain curve of the pipeline wall measured by using the proposed method to describe the corrosion is feasible. The proposed method provides a new way for real-time and long-term monitoring and management of underground pipelines.

Discussion on applying an analytical method to optimize the anti-freeze design parameters for underground water pipelines in seasonally frozen areas

Adopting the quasi-three-dimensional （Quasi-3D） numerical method to optimize the anti-freeze design parameters of an underground pipeline usually involves heavy numerical calculations. Here, the fitting formulae between the safe con-veyance distance （SCD） of a water pipeline and six influencing factors are established based on the lowest water temper-ature （LWT） along the pipeline axis direction. With reference to the current widely used anti-freeze design approaches for underground pipelines in seasonally frozen areas, this paper first analyzes the feasibility of applying the maximum frozen penetration （MFP） instead of the mean annual ground surface temperature （MAGST） and soil water content （SWC） to calculate the SCD. The results show that the SCD depends on the buried depth if the MFP is fixed and the variation of the MAGST and SWC combination does not significantly change the SCD. A comprehensive formula for the SCD is estab-lished based on the relationships between the SCD and several primary influencing factors and the interaction among them. This formula involves five easy-to-access parameters： the MFP, buried depth, pipeline diameter, flow velocity, and inlet water temperature. A comparison between the analytical method and the numerical results based on the Quasi-3D method indicates that the two methods are in good agreement overall. The analytic method can be used to optimize the anti-freeze design parameters of underground water pipelines in seasonally frozen areas under the condition of a 1.5 safety coefficient.

Incident analyses of frost heaving failure of municipal underground gas pipelines in cold regions of northern China

In the cold regions of northern China, incidents of municipal underground gas pipeline rupture and leakage occur quite fi-equently, aaost often in winter. To prevent harm to citizen safety and property, analysis of the causes of such cracking and leakage is therefore valuable. Two incident analyses are discussed here and the reasons why most of these types of cases occur dttring winter are clarified. Fhe effects of vehicle loadings above buried pipelines are calculated and compared with the effects and calculations of frost heaving forces. We demonstrate thtit when the soil layer above a pipeline freezes rapidly, the soil generates repeated frost heaving, which exerts heaving forces on the pipeline that can result in fatigue crack propagation and ultimate pipeline failure. Therefore, the incident induced 9y frost heaving is one of the primary reasons of gas pipeline failure. Based on these analyses, we present some recommendations pertaining to the proper design, construction, and management of gas pipelines.

Location monitoring approach of underground pipelines using time-sequential images

The location monitoring of underground pipelines is of utmost significance as it helps the effective management and maintenance of the pipelines,and facilitates the planning of nearby projects,preventing damage to the pipelines.However,currently there is a serious lack of data on the locations of underground pipelines.This paper proposes an image-based approach for monitoring the locations of underground pipelines by combing deep learning and visual-based reconstruction.The proposed approach can build the monitoring model for underground pipelines and characterize their locations through their centroid curve.Its advantages are:(1)simplicity:it only requires time-sequential images of the inner walls of underground pipelines;(2)clarity:the location model and the location curve of underground pipelines can be provided quickly;(3)robustness:it can cope with some existing problems in underground pipelines,such as light variations and small viewing angles.A lightweight approach for monitoring the locations of underground pipelines is achieved.The proposed approach’s effectiveness has been validated through laboratory simulation experiments,demonstrating accuracy at the millimeter level.

Gaussian Distance Weighted Algorithm for Geometric Characteristics of Three-Dimensional Discrete Curves

Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the geometric characteristics of any point on the discrete curve, a distance-based Gaussian weighted algorithm is proposed to estimate the geometric characteristics of three-dimensional space discrete curves. According to the definition of discrete derivatives, the algorithm fully considers the relative position difference between a specific point and its neighboring points, introduces the distance weighting idea, and integrates the smoothing strategy. The experiment uses two spatial discrete curves for uniform and non-uniform sampling, and compares them with two commonly used estimation algorithms. The comparative analysis is carried out in terms of sampling density, neighborhood radius and noise resistance. The experimental results show that the Gaussian distance weighted algorithm is effective and provides an efficient algorithm for underground pipeline safety detection.

Electromagnetic Fields and Induced Voltages on Underground Pipeline in the Vicinity of AC Traction System

Various regulations, aimed at the protection of human beings and electrical equipment against possible adverse effects resulting from exposure to electromagnetic fields, have been issued in many countries. Most of them are based on safety guidelines published by international expert groups. In this paper, electric and magnetic fields are calculated in the vicinity of 25 kV traction line supplying railway traction systems. Calculation results are compared to exposure limits specified by safety guidelines and regulations. Possible countermeasures for reduction of electromagnetic fields are proposed. Also, this paper presents a method for calculation of the induced voltages to an underground gas pipeline from a neighbouring 25 kV electric traction overhead line in case of short circuit. Calculations are performed with EMTP-ATP software. Possible countermeasures for reduction of induced voltages are proposed.

Recent Research Advances in the Risk Assessment Method of an Underground Pressure Pipeline

This paper reviews the risk assessment method of an underground pressure pipeline, introduces the risk assessment method of expert grading, fuzzy integrative assessment, probabilistic risk assessment and extenics assessment in an underground pressure pipeline. Moreover, it puts forward the developing orientation of risk assessment.

Response of underground pipeline through fault fracture zone to random ground motion

It is assumed that a pipeline is laid through a vertical fault fracture zone, and is excited by seismic ground motion modelled as stationary stochastic process. For horizontal incidence of waves, the cross-PSD （Power Spectral Density） function is developed using wave propagation theory, while for vertical incidence of waves the cross-PSD function is composed by auto-PSD model, coherence model and site response model. As the seismic input, the eross-PSD function is used to calculate the the axial and lateral seismic responses of underground pipeline through the fracture zone. The results show that the incident directions of seismic waves, width and soil property of the fracture zone have great influence on underground pipeline. It is suggested that the flexible joints with appropriate stiffness should be added into the pipeline near the interfaces between the fracture zone and the surrounded media.

Underground Pipeline Surveillance with an Algorithm Based on Statistical Time-Frequency Acoustic Features

Underground pipeline networks suffer from severe damage by earth-moving devices due to rapid urbanization.Thus,designing a round-the-clock intelligent surveillance system has become crucial and urgent.In this study,we develop an acoustic signal-based excavation device recognition system for underground pipeline protection.The front-end hardware system is equipped with an acoustic sensor array,an Analog-to-Digital Converter(ADC)module(ADS1274),and an industrial processor Advanced RISC Machine(ARM)cortex-A8 for signal collection and algorithm implementation.Then,a novel Statistical Time-Frequency acoustic Feature(STFF)is proposed,and a fast Extreme Learning Machine(ELM)is adopted as the classifier.Experiments on real recorded data show that the proposed STFF achieves better discriminative capability than the conventional acoustic cepstrum features.In addition,the surveillance platform is applicable for encountering big data owing to the fast learning speed of ELM.