## 1 Introduction
### Related Work
#### 1.1.1 Fault Detection in Pipelines
\begin{table}
\begin{tabular}{c c} \hline \hline
**Hardware-Based Method** & **Software-Based Method** \\ \hline
**Optical method**: This method relies on optical technologies, such as lidar (light detection and ranging), laser diodes, thermal imaging, and spectral imaging. These techniques use light or electromagnetic radiation to detect and analyze objects or phenomena. & **Signal processing-based method**: Signal processing techniques are employed to analyze data collected from sensors placed along the pipeline. Signal processing algorithms, such as filtering, noise reduction, and feature extraction, are used to identify anomalies in the collected data. Deviations from normal operating conditions, such as sudden pressure drops or irregular flow patterns, can trigger alerts for potential pipeline faults. \\ \hline
**Acoustic method**: Hardware-based acoustic methods involve the use of sound waves, acoustic emissions, ultrasonic waves, and sonar for detection and analysis. They are often used in applications like underwater sonar systems and structural health monitoring. & **Real-time model-based method**: Real-time models of pipeline systems are developed using mathematical and computational techniques. These models simulate the expected behavior of the pipeline under various operating conditions. During pipeline operation, the software continuously compares real-time sensor data with the predictions from the model. Any significant deviation between observed data and model predictions can indicate a fault in the pipeline. For example, a sudden drop in pressure that is not predicted by the model may suggest a leak or blockage. \\ \hline
**T \begin{table}
\begin{tabular}{c c} \hline \hline
**Blockage Detection Techniques** & **Leakage Detection Techniques** \\ \hline
**Vibration analysis**: This technique involves monitoring the vibrations in pipes to identify potential blockages. Changes in vibrations can indicate flow issues. & **Negative pressure wave-based leak detection system**: This technique is based on the detection of negative pressure waves generated by leaks in pipes. \\ \hline
**Pulse echo methodology leak detection**: This technique uses ultrasonic pulses to detect leaks in pipes. The reflection of pulses can reveal the presence of leaks. & **Negative pressure wave-based leak detection system**: This technique is based on the detection of negative pressure waves generated by leaks in pipes. \\ \hline
**Acoustic reflectometry**: It relies on the emission and detection of acoustic waves to locate blockages in pipes. The reflection of waves can indicate obstructions. & **Support vector machine-based pipeline leakage detection**: This technique employs machine learning algorithms like support vector machines to identify patterns related to leaks. \\ \hline
**Transient wave blockage interaction and blockage detection**: This technique utilizes transient waves to detect blockages in pipes. Changes in wave propagation can signal blockages. & **Support vector machine-based pipeline leakage detection**: This technique employs machine learning algorithms like support vector machines to identify patterns related to leaks. \\ \hline
**Stochastic successive linear estimator**: It is based on mathematical and statistical models to estimate the presence of blockages in pipes. & **Filter diagonalization method**: This method utilizes signal processing techniques to identify noise patterns related to leaks. \\ \hline  & **Harmonic wavelet analysis**: This method focuses on decomposing acoustic signals into harmonic components to detect leaks. \\ \hline  & **Genetic algorithm in combination with the inverse** **transient method**: This method combines genetic algorithms with modeling techniques to detect and locate leaks. \\ \hline  & **Computational fluid dynamic simulation**: This method uses numerical simulations to predict and detect leaks based on fluid flow behavior in pipes. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Main technologies for pipe blockage/leakage detection.