Improvement of Cepstrum Analysis for the Purpose to Detect Leak, Feature and Its Location in Water Distribution System based on Pressure Transient Analysis / Hanafi.M.Yusop ...[et al.]

Nowadays, pipeline system is one of the powerful technologies to be implemented in the real world. It is very essential for transporting fluid especially water from one point to the next point. But the pipeline system will also defect as leaks due to many reasons. Pressure Transient signal is a newly developed method to detect and localize leak phenomena since the signal has information about that phenomenon .The basic principal is the fact of water spouting out of a leak in pressurized pipe that generates a signal, and the signal may contain information to whether a leak exists and where it is located. To extract this signal, many signal analysis methods were implemented by researchers such as cross-correlation, genetic algorithm, and wavelets transform. Cepstrum analysis is proposed as a method to extract leak and pipe feature information from pressure transient signal by considering this method to analyse non-stationary data. Since in the real test, the originality and pure data are hard to be captured due to noise generated from environment and the noise level ratio is very low, pre-processing method as a filtering technique is implemented to analyse the real signal before the signal goes through cepstrum analysis as post-processing method. This research focused on the improvement of cepstrum analysis in order to extract information about the leak, pipe feature, and its location. In this research, cepstrum analysis was proposed as Post-Processing method. Discrete Wavelets Transform (DWT) and Principal Component Analysis (PCA) were proposed as Pre-Processing Methods. The pressure Transient signal was analysed using Matlab software. The results satisfactorily predicted the leak location as the comparison analysis using theoretical calculation and experimental results were just 0.4% to 3.8%. Therefore, PCA and DWT were recommended as data pre-processing methods to improve cepstrum analysis result.