Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148984
Title: Machine learning with DSP for condition monitoring system
Authors: Ng, Zhi Sheng
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Ng, Z. S. (2021). Machine learning with DSP for condition monitoring system. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148984
Abstract: Condition monitoring is the process of monitoring a parameter of condition in a system in order to identify a significant change which is indicative of a developing fault. It has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure. Using machine learning techniques, the big data gathered around a system can be analysed as a single coherent whole to draw conclusions about its current state of health. This project will develop a condition monitoring method using machine learning to detect defects on a real life system. A test jig will be used to mimic a real life system to collect sufficient data for machine learning. A DSP will be used to implement the machine learning algorithm.
URI: https://hdl.handle.net/10356/148984
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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