Underground Network Research Articles

AUTONOMOUS ROBOTIC SYSTEMS FOR PIPE INSPECTION USING MAPPING AND NONDESTRUCTIVE TESTING

This paper presents the development of a mapping and nondestructive technique (NDT) for the assessment of concrete pipeline networks. It focuses on the inspection of open-end culverts and storm drain systems using sensor networks. The network consists of 3D Lidar/3D camera/radar with NDT sensors. These sensors are mounted on autonomous vehicles that are set to reduce the extent of human operator involvement through intelligent control algorithms. More accurate remote monitoring is achieved by using smart robots and sensor networks equipped with advanced AI-based techniques. In the systems, ground robots are used with onboard sensing to enable environmental observation. The ground robots have the capability of remote communication, teleoperation, and the transmission of collected data. Effective automated mapping requires the flexibility to allow real-time changes in planning to accommodate unmodeled/unexpected uncertainties and disturbances. The autonomous system can be used repeatedly with reduced cost, primarily for maintenance. In addition, making the process autonomous can reduce the risk to human inspectors and save time during inspections. Also, it can be operated by personnel who require less training to obtain the data than standard inspection processes. The developed technology is demonstrated by actual field and lab testing. It provides accurate assessment tools for underground pipeline networks.

Study on analytical model of gas diffusion in underground pipe network

Through the analysis of gas pipeline leakage causes and gas leakage diffusion model, the preventive measures for gas leakage accidents are put forward, which is of great significance for the harm of gas leakage and explosion accidents. In this paper, the mathematical model of gas leakage is established through hydrodynamics and pipeline gas motion equation, and the leakage process is analyzed by means of numerical simulation, the change law of gas dynamic leakage is obtained from the aspects of gas leakage conditions, gas movement and diffusion law.

Manhole Quality Management and Sensing Using IOT

'A novel design of a model method of quality management of manholes in metropolitan cities that can improve the efficiency of civic bodies in an urban and technology driven country'. In these recent times, aging and outdated public sewers and underground networks and facilities have caused increased needs for systems that support the robust maintenance and management of social infrastructure. There are dire needs for measure regarding manholes involved in water, sewage, gas and electric facilities, including the supplementary countermeasures to prevent the covers from being subjected to damaged or displaced due to ill manner of maintenance, aging or torrential rainfall that exceeds its drainage capacity. There is also concern regarding covers being stolen or manholes being used in acts of terrorism, and efforts to solve the problems caused by manholes are required so that people can live in a safe environment and are not subjected to any freak accidents or unfortunate mishaps. This social concern can be monitored and solved with the integration of Internet of Things (IoT) will enable us to effectively solve the problems regarding underground network of sewers. Internet of Things (IoT) consists of real-life objects, communication devices attached to sensor networks in order to provide communication and automated actions between real world and information and data driven world.

3D MODELLING OF TRAM TUNNEL FROM TLS POINT CLOUDS FOR TECHNICAL DOCUMENTATION AND EXTRACTION OF CHARACTERISTIC LINES

Abstract. The Strasbourg tramway has only one tunnel 1400 m long built in 1994. It grants the operation of two lines of the transportation network. It also houses the only underground station "Gare centrale" and is the only tunnel operated by the CTS (Compagnie des Transports Strasbourgeois). Due to new guidelines for georeferencing of underground networks, the CTS had to know the precise planimetric and altimetric position of the tunnel, considered as a sensitive network located in urban areas. The regulations also set the criteria for precision which for this specific case requires an accuracy of less than 40 cm. This project on behalf of and in partnership with the CTS therefore aims to set up a method allowing the 3D survey of the tunnel considering the specific constraints of urban transport networks and then to propose different 2D or 3D deliverables allowing the management of the tunnel. Initially, the project focused on extracting the shape of the tunnel characteristic lines, which corresponds to the line tangent to the points of higher altitude and the extreme points of each cross-section, along the axis of the tunnel. In a second step, a 2D plan containing all the technical elements present in the tunnel was realized, as well as a 3D modelling of a significative part of the infrastructure. A video was also derived from the point cloud to inspect the entire tunnel from different points of views. In the future, more advanced 3D models or BIM models could be considered. This would require information on the structure of the walls, the construction materials, or the links between the different elements. A project to survey and model the underground station will make it possible in the future to perfect the acquisition and knowledge of the underground infrastructures belonging to the transport company.

AUTOMATING THE UNDERGROUND CADASTRAL SURVEY: A PROCESSING CHAIN PROPOSAL

Abstract. In order to ensure the proper functioning and evolution of underground networks (water, gas, etc.) over time, municipal services need to maintain accurate and up-to-date maps. Such maps are generally updated using traditional data acquisition methods (total station or GNSS), which are time-consuming, expensive, and require several teams of surveyors in the field. In this context, an important topic of research is the automation of the updating of the underground cadastre in order to save time, money, and human effort. In this paper, we present a new method that we developed ranging from the choice of the acquisition system, the tests carried out in the field to the detection of objects and the automatic segmentation in a 3D point cloud. We have chosen to use a convolutional neural network on images for the detection of objects that are part of the underground cadastre. As the next step, objects are projected to obtain a 3D point cloud segmented based on the object type. The vectorization step is still under development so that objects can be converted to vector format and therefore be used for updating the cadastre. The results based on excavation sites with well-represented objects in our training database are excellent, approaching 96% accuracy. However, the detection of rare objects is much less good and thus remains a topic for future research. Overall, the complete processing chain allowing to automate as much as possible the update of an underground cadastre is presented in this paper.

Energy-Efficient Deterministic Approach for Coverage Hole Detection in Wireless Underground Sensor Network: Mathematical Model and Simulation

Wireless underground sensor networks (WUSNs) are being used in agricultural applications, in border patrol, and in the monitoring of remote areas. Coverage holes in WUSNs are an issue which needs to be dealt with. Coverage holes may occur due to random deployment of nodes as well as the failure of nodes with time. In this paper, a mathematical approach for hole detection using Delaunay geometry is proposed which divides the network region into Delaunay triangles and applies the laws of triangles to identify coverage holes. WUSNs comprise static nodes, and replacing underground nodes is a complex task. A simplistic algorithm for detecting coverage holes in static WSNs/WUSNs is proposed. The algorithm was simulated in the region of interest for the initially randomly deployed network and after energy depletion of the nodes with time. The performance of the algorithm was evaluated by varying the number of nodes and the sensing radius of the nodes. Our scheme is advantageous over other schemes in the following aspects: (1) it builds a mathematical model and polynomial-time algorithm for detecting holes, and (2) the scheme does not work on centralized computation and therefore provides better scalability, (3) is energy-efficient, and (4) provides a cost-effective solution to detect holes with great accuracy and a low detection time. The algorithm takes less than 0.1 milliseconds to detect holes in a 100 m × 100 m-size network with 100 sensor nodes having a sensing radius of 8 m. The detection time shows only a linear change with an increase in the number of nodes in the network, which makes the algorithm applicable for every network size from small to large.

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation.

Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m3/m3). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs.

Application of GPR Underground Pipeline Detection Technology in Urban Complex Geological Environments

In the process of the continuous construction of underground pipelines, underground pipe network systems have become increasingly complex, which puts forward higher requirements for normal operation and maintenance. To address different kinds of complex conditions, this experiment in the present paper takes ground penetrating radar as the research basis and uses a self-correction and screening algorithm to innovatively detect underground pipelines. The results show that urban underground pipeline detection technology based on ground penetrating radar (GPR) can obtain a highly reliable number of pipelines and track predefined pipelines when detecting different numbers of verification pipelines. When detecting underground pipelines in different sections, the vertical and horizontal errors are no more than 0.199 m and 0.248 m, respectively, which means that the detection technology of urban underground pipelines based on GPR has high detection accuracy and can be performed on high-level detection tasks under various complex conditions. This research applies bottom detection radar to urban underground pipeline detection technology under complex conditions for the first time, innovatively uses the action mechanism of bottom detection radar, integrates its high precision and high efficiency into underground pipeline detection technology, and ensures the effectiveness of the detection work.

THE IFC FILE FORMAT AS A MEANS OF INTEGRATING BIM AND GIS: THE CASE OF THE MANAGEMENT AND MAINTENANCE OF UNDERGROUND NETWORKS

Abstract. The construction sector is undergoing an important digital revolution. The integration between Building Information Modeling (BIM) and Geographical Information System (GIS) is a key component of this revolution and is increasingly discussed. Although benefits are already recognised, several challenges still remain. The purpose of this paper is to present the method proposed by the GEOBIMM project to overcome the existing barriers towards the integration between BIM and GIS domains and to present the first results applied to the maintenance of underground networks. The results are a set of guidelines essential for the integration of BIM files in GIS platforms within the GEOBIMM domain, to ensure: the appropriate geometric description of the elements; the correct georeferencing; the geospatial semantic and topological interoperability between the two systems; the appropriate definition of the information parameters. These pillars are further used to develop a guideline for planners and construction companies supporting them in developing compliant BIM models.

Influence of geological discontinuities on the groundwater flow of the Serra Geral Fractured Aquifer System

Groundwater circulation in fractured aquifer systems is a topic of worldwide interest as they are heterogeneous and peculiar environments. In Brazil, little is known about the groundwater flow within fractured rocks. This knowledge gap motivated the investigation of (1) the statistical variance of the exploited discharges and their relationship with the directions of geological lineaments, (2) the analyzes of the relationship between of the groundwater flow with the different characteristics of the discontinuities and (3) the correlation between the acting stresses with the fracturing geometries that present groundwater flow. To reach these objectives, this paper is circumscribed within the following methods: frequency graphs, normality assumptions test, non-parametric homogeneity tests, multiple correspondence analysis, scanline profiles, and in situ stress analysis. This study was carried out in the Serra Geral Fractured Aquifer System, in Caxias do Sul, Rio Grande do Sul, Brazil. The results showed that most the exploited water wells are associated with the NW-SE and NE-SW lineament directions. There was a predominance of four sets of subvertical fractures (S1, S2, S3, and S4) and one sub-horizontal (S5). Sets of fractures S3, S4, and S5 showed the greatest persistence of fractures and presence of exudation. The tension axes σ1 and σ3 were identified in the (310°; 113°–141°) and (218°; 020°–051°) directions, respectively. The groundwater circulation in sets of fractures S3 and S4 is related to tensions σ1 and σ3 and the most exploited lineament directions NW-SE and NE-SW, while S5 is correlated to tension σ2 and behaves as a facilitator of the groundwater circulation in the underground flow network.

Along the hidden Timavo. 90° Congresso della Società Geologica Italiana - Trieste, 14-16 settembre 2021. Pre congress Field Trip T2

Almost 200 years after the first studies on the Timavo River, researchers are still carrying out their investigations, thanks in part to European projects, aiming to improve the knowledge on the Reka/Timavo cross-border aquifer in order to protect the groundwater resource through quantitative and qualitative monitoring of the underground waters. The Classical Karst Region is, in fact, home to what is generically called the underground Timavo network, a set of underground drainage paths developed well below sea level. The waters flow both in large conduits and in small fractures characterizing the rock mass. Water is the engine that created all these hypogean features and the surface karst morphotypes thanks to the chemical (dissolution) and physical (erosion) processes. The topographical surface is studded with thousands of dolines. Throughout the territory, more than 5.000 caves have been explored, of which more than 150 have a development exceeding a hundred meters. Out of all of them, only less than a dozen reach the water base level (Timavo caves) and others are crossed by water during floods. In this framework is the field trip proposed in the guide book designed as an accompaniment for visitors and participants in the 90° SGI Congress. The excursion goes along the underground path of the Reka/Timavo River, starting from Slovenia, visiting the Škocjan caves in which the river disappears underground (UNESCO world heritage site since 1986). The excursion moves on to the Grotta Gigante cave with another stop at the surface dissolution laboratory and the museum, after which visitors will take part in the excellent sightseeing to be found at Doberdò Lake and at the Timavo Springs where freshwaters meet the salty Adriatic Sea.

Multi‐hoped cooperative communication‐based wireless underground sensor network design

SummaryDeepwater utilization and underwater sound communication with inadequate bandwidth, elongated propagation interruption, signal failure issues, and sensor node malfunction due to ecological circumstances are the limitations of the underwater wireless sensor network. Further, the challenges in underground wireless sensor network (WSN) include superior bandwidth, high power expenses, information handling, and cross‐layer design. On the other hand, cooperative communications facilitate competent employment of communication resources, by permitting nodes in a network to work together in information communication. As wireless sensor networks adapt to multi‐hop transmission in high data traffic, there is a high demand for achieving energy efficiency. Moreover, in the course of proximity nodes to the sink, an energy hole is started for the extended network lifetime. This paper proposes the design of multi‐hoped cooperative communication‐based wireless underground sensor networks that guarantees energy efficiency in a hostile environment. In addition, network coverage and connectivity improvement are also improved by this proposed design.

AI-Based Efficient WUGS Network Channel Modeling and Clustered Cooperative Communication

Wireless underground sensor networks (WUSNs) are sub-ground-surface sensor node networks designed to establish real-time tracking capacities in diverse underground ecosystems composed of soil, water, oil, and other materials. The contact medium is the key distinction between USNs and terrestrial wireless sensor networks. The communication properties of electromagnetic (EM) waves in underwater resources like mud, water, oil, and other materials, as well as major variations between propagation in air, make classification of the underground wireless channel difficult. From the transmission of data, the channels modelling is involved to remove the noise and reduce the energy. After that Multi-driven Clustering Algorithm (MCA) method is used to cluster the channel based on the EDT method (Energy, Distance, and Time). Completing the transmission, the data can be transmitted to the destination. The experimental portion of the proposed method is analyzed by varying parameters such as energy, throughput, channel response, and time duration of the data transmission. From the experimental analysis, it is observed that 55% and 45% more energy levels can be saved with the proposed MCA method than with the LEACH methods for DR and SW media methods, respectively. The throughput of the proposed method is proven with 45% and 42% improvement over the time horizon in the median under the frequency for soil of the LEACH and LEACH-CO2 methods, correspondingly.

Improvement of the electric energy quality in underground electric networks in highly productive coal mines

One of the main factors for the effective functioning of the power supply system in highly productive coal mines is the uninterrupted power supply of underground consumers for the entire process cycle at sufficient amount of electric energy at a high level of quality and performance. The analysis of electric energy consumption in highly productive coal mine has shown that about 57 % of electric energy consumers are located in underground workings. Consumers can be divided into the following areas of basic technological process of coal production: production areas (13 %); conveyor transport areas (13 %); preparation areas (8 %), and areas of auxiliary processes of coal production: mine drainage (23 %). The increase in the share of controlled-velocity electric drives in the total power balance of fully-mechanized longwalls leads to factors previously atypical of underground power networks. Such factors include changes to the harmonic composition of the network, arising higher current and voltage harmonics, affecting the supplying network and causing heating of electrical equipment, power and electric energy losses. Therefore, the most pressing issues are to improve electric energy quality in underground electric networks of highly productive coal mines. The study has developed a technique for experimental investigations of quality indicators of electric energy (presented in the form of algorithm) in respect to specific conditions of highly productive coal mines. These include dangerous facilities in terms of sudden gas/dust outbursts. This technique was tested at a number of coal mines of JSC SUEK-Kuzbass. The study also presents the results of experimental investigations to determine the actual level of total harmonic distortion (factor) in underground electric networks of fully-mechanized longwalls of coal mines. Of greater importance is justification of higher harmonic filter parameters. To this end a calculation algorithm based on the developed technique has been proposed. Research has shown that application of forward and inverse Clarke transformations for calculating the harmonic filter parameters is applicable for all voltage levels. The simulation model of power supply system of a coal mine fully-mechanized longwall allows conditions of higher harmonics damping to be studied by means of a device for improvement of electric energy quality. Applying the proposed technical solutions to improve the quality of electric energy based on the simulation modeling allowed the successful damping of higher harmonics to be achieved. For example, the total harmonic components voltage (THD (U)) was reduced from 9.07 to 1.77 %.

Addressing the Directionality Challenge through RSSI-Based Multilateration Technique, to Localize Nodes in Underwater WSNs by Using Magneto-Inductive Communication

The deployment and efficient use of wireless sensor networks (WSNs) in underwater and underground environments persists to be a difficult task. In addition, the localization of a sensor Rx node in WSNs is an important aspect for the successful communication with the aforementioned environments. To overcome the limitations of electromagnetic, acoustic, and optical communication in underwater and underground wireless sensor networks (UWSNs), magneto-inductive (MI) communication technology emerged as a promising alternative for usage in UWSNs with a wide range of applications. To make the magneto-inductive underwater wireless sensor networks (MI-UWSNs) more efficient, recently, various research studies focused on the optimization of the physical layer, MAC layer, and routing layer, but none of them has taken into account the effect of directionality. Despite the directionality issue posed by the physical nature of a magnetic field, the unique qualities of MI communication open up a gateway for several applications. The directionality issue of MI sensors is a critical challenge that must be taken into account while developing any WSN protocol or localization algorithm. This paper highlights and discusses the severity and impact of the directionality issue in designing a localization algorithm for magneto-inductive wireless sensor networks (MI-WSNs). A received signal strength indicator (RSSI)-based multilateration localization algorithm is presented in this paper, where a minimum of 2 and maximum of 10 anchor Tx nodes are used to estimate the position of the sensor Rx nodes, which are deployed randomly in a 15 m × 15 m simulation environment. This RSSI-based multilateration technique is the most suitable option that can be used to quantify the impact of directionality on the localization of a sensor Rx node.

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.

The DARPA Subterranean Challenge: A Synopsis of the Circuits Stage

Complex underground environments present significant challenges for the autonomy, perception, networking, and mobility of robots operating in time-sensitive disaster response scenarios. In 2017, DARPA created the Subterranean Challenge to stimulate innovation and investment in solutions that can rapidly map, navigate, and search complex environments, including human-made tunnel systems, urban underground, and natural cave networks. The program is hosting a series of evaluations, namely, the three Circuit Events and the Final Event, which assess each competing team’s approaches in representative subterranean environments. This paper provides an overview of the program and the results from the Circuits Stage of the competition

CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge

Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems, as underground settings present key challenges that can render robot autonomy hard to achieve. This problem has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In response, we present the CERBERUS system-of-systems, as a unified strategy for subterranean exploration using legged and flying robots. Our proposed approach relies on ANYmal quadraped as primary robots, exploiting their endurance and ability to traverse challenging terrain. For aerial robots, we use both conventional and collision-tolerant multirotors to explore spaces too narrow or otherwise unreachable by ground systems. Anticipating degraded sensing conditions, we developed a complementary multimodal sensor-fusion approach, utilizing camera, LiDAR, and inertial data for resilient robot pose estimation. Individual robot pose estimates are refined by a centralized multi-robot map-optimization approach to improve the reported location accuracy of detected objects of interest in the DARPA-defined coordinate frame. Furthermore, a unified exploration path-planning policy is presented to facilitate the autonomous operation of both legged and aerial robots in complex underground networks. Finally, to enable communication among team agents and the base station, CERBERUS utilizes a ground rover with a high-gain antenna and an optical fiber connection to the base station and wireless “breadcrumb” nodes deployed by the legged robots. We report results from the CERBERUS system-of-systems deployment at the DARPA Subterranean Challenge’s Tunnel and Urban Circuit events, along with the current limitations and the lessons learned for the benefit of the community.

Shift Scheduling Optimization: A Real-Life Underground Transportation Example

Personnel scheduling is basically a type of scheduling that determines which employee will work and when, taking into account the needs of the industry and employees. Personnel scheduling is intertwined with shift scheduling problems in shift systems. In many industries, the assignment of employees to shifts during the day, the determination of relief breaks and meal breaks are an important factor for shift scheduling while meeting the changing workforce needs. The main purpose of this study is to schedule the shifts of the machinists of Ankaray, which is one of the underground transportation networks of Ankara, the capital of Turkey, in the transportation sector where people serve people. In the study, shift scheduling models in the literature were examined and Aykin's optimal shift scheduling with multiple break windows was taken as a basis. The model divides the working hours into two shifts during the day and finds the number of employees required for each shift. In addition, it also determines the relief break and lunch break times for each employee. As a result, the current situation was analyzed and a comparison was made with the results on the established optimization model. Cost minimization is at the root of the problem, so it is concretely shown how this model will contribute in real life.

Prosthetic Symbiosis

Prosthetic Symbiosis