Makeen Mohd Amin creator author. text abstract or summary my 2018 2018 monographic eng

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xii, 81 pages : illustrations (some color), charts ; 30 cm. + 1 CD-ROM Nowadays, there are many approaches to the methods for detecting pipeline’s feature either from external or internal. The only argument is which method will deliver the most effective result with the advantage of time-saving and human-friendly. The results were influenced by the surrounding noise either from inner or the outer pipeline networks. This thesis mainly focuses on the detection features in pipeline network using Ensemble Empirical Mode Decomposition Method (EEMD). The objectives of this thesis are to study and analyse data by using EEMD method for leakage detection in the pipeline system and identify and compare the leakage position between the measured distance and analysed distance. Therefore, the test rig was built by using 56m polyethene pipe with the leak as the main feature. Solenoid valve is used to create water hammering phenomenon. The water hammering phenomenon will generate a transient wave inside the pipe. The data was collected using DASYLab software and analysed using MATLAB software. The leakage and outlet position were determined by undergoing intrinsic mode function analysis (IMF) and later analysed by their respective instantaneous frequency analysis (IF) using EEMD method. The experiment was runs in two situations, firstly by closing the leakage valve and the other one by opening the valve to create leakage. The analysed results show that the position of the outlet is almost similar to the measured distance with 0.55% and 6% of percentage error. The analysed leakage location is also determined and compared to the measured distance. It indicates that only 3.21% of error between the measured distance and analysed distance and analysed distance. It can be concluded that the EEMD analysis is one of the best methods to be the approach in leak detection of either underground or above ground piping system. In addition, this method can be said as low in cost and energy saving. specialized Makeen Mohd Amin Faculty of Mechanical Engineering Thesis (Master of Engineering (Mechanical)) -- Universiti Malaysia Pahang – 2018 Includes bibliographical references Faculty of Mechanical Engineering Dissertations Universities and colleges Disertations Theses THE0005254(Local) UMP 180927 20251117113405.0 vtls000105329 eng