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UNMANNED ROBOTIC VEHICLE FOR PIPELINE INSPECTION USING COMPUTER VISION
Abstract:
The maintenance and inspection of pipelines play a crucial role in ensuring the integrity and efficiency of industrial infrastructures. This research proposes the design and implementation of an unmanned robotic vehicle equipped with advanced computer vision technology for the purpose of pipeline inspection. The autonomous nature of the robotic system allows for efficient and cost-effective inspection, reducing human intervention and operational risks.
The robotic vehicle integrates computer vision algorithms to analyze visual data captured by onboard cameras, enabling the detection and identification of potential issues such as cracks, corrosion, and leaks along the pipeline. The implementation of real-time image processing enhances the vehicle’s ability to navigate and respond to dynamic environmental conditions, ensuring comprehensive and accurate inspection results.
Furthermore, the unmanned vehicle incorporates intelligent path-planning algorithms, enabling it to autonomously navigate through complex pipeline networks with minimal human intervention. The system aims to enhance inspection speed, coverage, and accuracy, thereby reducing downtime and improving overall safety in industrial settings.
This research contributes to the ongoing advancement of robotics in industrial applications, particularly in the domain of infrastructure inspection. The proposed unmanned robotic vehicle offers a reliable and efficient solution for pipeline inspection, leveraging state-of-the-art computer vision technology to address the challenges associated with traditional inspection methods. The outcomes of this study have implications for industries reliant on pipeline infrastructures, promoting proactive maintenance and minimizing the risks associated with unforeseen issues in critical pipelines.
CHAPTER ONE:
INTRODUCTION
1.1 Background of the Study
The inspection and maintenance of pipelines are critical for ensuring the integrity and efficient operation of various industries, including oil and gas, water supply, and chemical processing. Traditionally, pipeline inspections have been conducted manually, involving human inspectors navigating through the pipelines, which can be time-consuming, costly, and pose safety risks. With advancements in technology, Unmanned Robotic Vehicles (URVs) equipped with Computer Vision systems have emerged as a promising solution for automating and enhancing the pipeline inspection process.
Pipelines are the safest means by which oil, gases and other fluids such as chemicals are transported and distributed. however, structural issues often arise such as cracks and corrosion which causes progressive degradation and disintegration over time (Kiran et al., 2017). This progressive deterioration also increases the probability of failure (fatigue cracking). In an effort to prevent structural failure, companies are required to perform periodic inspections of all critical facilities (Kamsu-Foguem, 2016). Existing inspection method often involved physical evaluation by skilled personnel, high inspection cost (Oyekola, Mohamed, et al., 2019) for inspection of structures in high risk locations such as working at height, confined spaces, toxic environment etc. this therefore makes inspection a painful and enduring task which also affects work flow. Additionally, exact and solid assessment of pipelines are sometimes required for more stringent controls and escalated financial weight (Casal, 2017).
In an effort to find a solution of this existing inspection technology, companies now seek for solution which would not affect or interfere with regular operational run. Additionally, adequately dependable and accurate examination results can only be gotten by direct contact or access to the inspection surface and if this isn’t plausible from an external perspective, there will need for internal inspection. Sometimes, physical access to these structures might not be possible due to sizing constraint. However, a pipe inspection robot is a welcome development in the field of robotics which provides answers for inaccessible pipeline systems (Oyekola, Lambrache, et al., 2019).
Robotics is a robust developing engineering fields as they provide solutions which surpasses human limitations such as fatigue, stress ability to function in toxic environments, tight spaces etc. (Lattanzi & Miller, 2017). The utilization of robot is more normal these days than at any other time and it is not, at this point only utilized by heavy production industries given that integrity threats form serious safety concerns which are often required to be addressed on time.
In mitigating these threats, there is a need for an internal inspection tool which is capable of incorporating relevant technologies and sensors in order to effectively detect these anomalies (Xie et al., 2018).
Robots versatile mechanical frameworks are discovering their way into a wide range of situations into which past frameworks couldn’t venture. Portable robots have the ability to perform different investigation errands in a given domain without being settled to one area (Seeja et al., 2018). An ever-increasing number of versatile mechanical frameworks are supplanting difficult, hazardous, or bulky duties that were previously done by human workers. This is on the grounds that innovation, for example, robot vision, discernment, detecting and instrumentation keeps on enhancing with technology on a daily basis due to an exponential development in computing power especially on mobile computers.
In this research, both the study of pipe inspection robots and design of such robots to inspect pipes, checking pipe integrity and detecting cracks is carried out. This study will also be useful for inspection of water pipelines, plumbing, sewer inspection, etc.
1.2 Statement of the Problem
The conventional methods of pipeline inspection face challenges such as limited accessibility to remote or hazardous areas, high costs, and potential safety risks to human inspectors. These challenges underscore the need for innovative approaches that leverage Unmanned Robotic Vehicles and Computer Vision technologies to improve the efficiency, accuracy, and safety of pipeline inspections.
1.3 Objectives of the Study
The primary objectives of this research are:
To design and develop an Unmanned Robotic Vehicle for pipeline inspection.
To implement Computer Vision algorithms for real-time image and video analysis during pipeline inspections.
To assess the performance of the Unmanned Robotic Vehicle in terms of inspection accuracy, efficiency, and safety.
To explore the potential applications and benefits of integrating Computer Vision in pipeline inspection processes.
1.4 Research Questions
To guide the investigation, the following research questions are formulated:
How can an Unmanned Robotic Vehicle be designed and developed for efficient pipeline inspection?
What Computer Vision algorithms can be implemented for real-time image and video analysis during pipeline inspections?
What is the performance of the Unmanned Robotic Vehicle in terms of inspection accuracy, efficiency, and safety?
What are the potential applications and benefits of integrating Computer Vision in pipeline inspection processes?
1.5 Significance of the Study
The study’s significance lies in its potential contributions to the fields of robotics, computer vision, and pipeline inspection. The development of an Unmanned Robotic Vehicle equipped with Computer Vision capabilities could significantly improve the accuracy and efficiency of pipeline inspections, reducing costs and enhancing safety. The findings of this research may have broader implications for industries relying on extensive pipeline networks.
1.6 Scope of the Study
This research focuses on the design, development, and evaluation of an Unmanned Robotic Vehicle specifically tailored for pipeline inspection. The study also involves the implementation of Computer Vision algorithms to analyze images and videos captured during the inspection process. The geographical scope of application may vary, encompassing pipelines in different industries and environments.
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