Sensor-based autonomous pipeline monitoring robotic system

The field of robotics applications continues to advance. This dissertation addresses the computational challenges of robotic applications and translations of actions using sensors. One of the most challenging fields for robotics applications is pipeline-based applications which have become an indispensable part of life. Proactive monitoring and frequent inspections are critical in maintaining pipeline health. However, these tasks are highly expensive using traditional maintenance systems, knowing that pipeline systems can be largely deployed in an inaccessible and hazardous environment. Thus, we propose a novel cost effective, scalable, customizable, and autonomous sensor-based robotic system, called SPRAM System (Sensor-based Autonomous Pipeline Monitoring Robotic System). It combines robot agent based technologies with sensing technologies for efficiently locating health related events and allows active and corrective monitoring and maintenance of the pipelines. The SPRAM System integrates RFID systems with mobile sensors and autonomous robots. While the mobile sensor motion is based on the fluid transported by the pipeline, the fixed sensors provide event and mobile sensor location information and contribute efficiently to the study of health history of the pipeline. In addition, it permits a good tracking of the mobile sensors. Using the output of event analysis, a robot agent gets command from the controlling system, travels inside the pipelines for detailed inspection and repairing of the reported incidents (e.g., damage, leakage, or corrosion). The key innovations of the proposed system are 3-fold: (a) the system can apply to a large variety of pipeline systems; (b) the solution provided is cost effective since it uses low cost powerless fixed sensors that can be setup while the pipeline system is operating; (c) the robot is autonomous and the localization technique allows controllable errors. In this dissertation, some simulation experiments described along with prototyping activities demonstrate the feasibility of the proposed system

Application of software and hardware-based technologies in leaks and burst detection in water pipe networks: a literature review

With the rise of smart water cities, water resource management has become increasingly important. The increase in the use of intelligent leak detection technologies in the water, gas, oil, and chemical industries has led to a significant improvement in safety, customer, and environmental results, and management costs. The aim of this review article is to provide a comprehensive overview of the application of software and hardware-based technologies in leak detection and bursts in water pipeline networks. This review aims to investigate the existing literature on the subject and to analyse the key leak detection systems in the water industry. The novelty of this review is the comprehensive analysis of the literature on software and hardware-based technologies for leak and burst detection in water pipe networks. Overall, this review article contributes to understanding the latest developments and challenges in the application of software- and hardware-based technologies for leak and burst detection in water pipe networks, and serves as a valuable resource for researchers, engineers, and practitioners working in the field of water distribution systems

Acoustic signal-based underwater oil leak detection and localization

Underwater Wireless Sensor Networks (UWSNs) have been becoming popular for exploring offshore, natural resource development, geological oceanography, and monitoring the underwater environment. The acoustic channel characteristics in underwater impose challenges, including limited bandwidth, signal attenuation, and propagation delay that limits UWSN utilization. The marine environment is under threat from pollution, which impacts human life and activities. Compared to other pollution types, the oil leak is a significant threat to the marine ecosystem. When the leaked oil or other petroleum products mix with water in the ocean, significant biological and economic impacts could result. Although much research has focused on improving the reception and processing of acoustic signals, increasing performance, and reducing packet delay, no significant research results have been reported on finding an effective early-stage leak detection method using acoustic signal processing. Accurate information about oil spill location and its characteristics is much needed for oil spill containment and cleanup operations. Developing an efficient under- water oil leak detection and localization algorithm is still challenging in UWSNs because of the impairments of the acoustic channel. In this thesis, we propose a technique that detects the presence of an oil leak in the underwater environment at an early stage. We also propose a localization algorithm that determines the approximate location of the oil leak. Firstly, we review the propagation properties of acoustic signals to understand acoustic communication in the marine environment better. We then discuss the transmission of sound in terms of reflection and refraction. We propose a leak detection technique based on the range estimation method to detect oil leak at an early stage before reaching the ocean sur- face. We perform a two-dimensional analysis for evaluating the performance of the proposed detection technique. To investigate the proposed technique, we perform evaluation with different network sizes and topologies. We discuss the detection ratio, network scalability, power and intensity of the received signal. We then perform a three-dimensional analysis to evaluate the performance of the proposed technique. We conduct theoretical analysis to investigate the proposed technique in terms of detection ratio, network scalability, power and intensity of the received signal. We assess the efficiency of the proposed detection method by considering an oil leak at different ocean levels. Finally, we propose a cooperative localization algorithm for localizing the leak in the UWSN. We then evaluate the proposed localization algorithm for two different topologies. Our results show that our proposed technique works well for an underwater network with concentric hexagonal topology. We can extend the proposed method for other types of targets with different shapes and sizes

PipeProbe: A Mobile Sensor Droplet for Mapping Hidden Pipeline

Abstract This paper presents PipeProbe, a mobile sensor system for determining the spatial topology of hidden water pipelines behind walls. PipeProbe works by dropping a tiny wireless sensor capsule into the source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatio-temporal analysis on the sensor readings, our algorithm locates all turning points in the pipelines and maps their 3D spatial topology. We evaluated the PipeProbe system by developing a prototype and using data collected in our experimental testbed. Results show that the PipeProbe system successfully located and estimated 90% of all pipe tube lengths within 8-cm accuracy on average tube lengths of 76 cm. PipeProbe also successfully located 90% of all turning points within 15-cm accuracy on average length paths of 335cm