Machine learning with DSP for condition monitoring system
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...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/148984 |
| _version_ | 1811685189589401600 |
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| author | Ng, Zhi Sheng |
| author2 | See Kye Yak |
| author_facet | See Kye Yak Ng, Zhi Sheng |
| author_sort | Ng, Zhi Sheng |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T04:40:34Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/148984 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:40:34Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1489842023-07-07T17:27:48Z Machine learning with DSP for condition monitoring system Ng, Zhi Sheng See Kye Yak School of Electrical and Electronic Engineering EKYSEE@ntu.edu.sg Engineering::Electrical and electronic engineering 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. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-21T12:52:09Z 2021-05-21T12:52:09Z 2021 Final Year Project (FYP) 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 https://hdl.handle.net/10356/148984 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Ng, Zhi Sheng Machine learning with DSP for condition monitoring system |
| title | Machine learning with DSP for condition monitoring system |
| title_full | Machine learning with DSP for condition monitoring system |
| title_fullStr | Machine learning with DSP for condition monitoring system |
| title_full_unstemmed | Machine learning with DSP for condition monitoring system |
| title_short | Machine learning with DSP for condition monitoring system |
| title_sort | machine learning with dsp for condition monitoring system |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/148984 |
| work_keys_str_mv | AT ngzhisheng machinelearningwithdspforconditionmonitoringsystem |