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Leak Detection In Flowlines Using Machine Learning - Education - Nairaland

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Leak Detection In Flowlines Using Machine Learning by eduproject(m): 4:16pm On Mar 03
CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Transport of fluids and gases through pipe is widely used in the industry, including the iron ore beneficiation processes. Because these materials that eventually can cause environmental damage or injury persons, it is essential to monitor these pipes in order to prevent disasters and losses. As a result, several leakage detection techniques have been developed over the last thirty years (Datta and Sarkar, 2016).
The detection of leaks is a crucial issue in today’s world, as it has the potential to affect the environment, human safety, and result in economic losses. Leaks of water, gas, electricity, and oil can occur in various forms, and hence, the detection of leaks is crucial in industrial, commercial, and residential areas. The objective of leak detection is to detect and control leaks in a timely manner to create a safe environment and minimize losses. Leak detection technologies can be broadly classified into physical and electronic methods. Physical methods are traditional and require experienced professionals, making them labor-intensive, time-consuming, and costly. Electronic methods, on the other hand, use modern technologies such as sensor technology, data analytics, and artificial intelligence (AI) to detect and analyze leaks.

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