Transfer learning based industrial steel plates fault diagnosis using industrial fault signals
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.
| প্রধান লেখক: | , , |
|---|---|
| অন্যান্য লেখক: | |
| বিন্যাস: | গবেষণাপত্র |
| ভাষা: | English |
| প্রকাশিত: |
Brac University
2024
|
| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | http://hdl.handle.net/10361/23652 |
| id |
10361-23652 |
|---|---|
| record_format |
dspace |
| spelling |
10361-236522024-07-03T21:00:41Z Transfer learning based industrial steel plates fault diagnosis using industrial fault signals Mizan, Mubasshira Nilo, Laila Sumiya Khan Tuli, Mosrika Momin Uddin, Jia Nahim, Nabuat Zaman Department of Computer Science and Engineering, Brac University Transfer learning Image processing Image classifi cation Image segmentation Image enhancement Image assessment Deep learning Cognitive learning theory Image processing--Digital techniques. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 34-35). Transfer learning (TL) has shown its great advantage to solve small-training-sample issues utilizing information learned from existing large data with deep learning tech- niques. Transfer learning has been e ectively applied in many deep learning net- works where su cient training samples are not accessible; it still experiences es- sential problems for image processing. Image processing technology has become an interesting eld in medics as image processing plays avital role in the discovery of the diseases in the early stages, which facilitates the treatment of these diseases. Image processing divides into numerous scopes. For case, image classi cation, image seg- mentation, image enhancement and image assessment. In this thesis, we will review the existing industrial fault diagnosis models and will propose an image-based deep learning model to detect or predict industrial faults. In order to do that we will convert 1D sensor's fault signals to 2D images. After that, we will extract deep fea- tures using a deep learning model for training and testing the classi er. To validate our model, we will use an industrial fault dataset. As programming tools, we will use Python and MATLAB. Mubasshira Mizan Laila Sumiya Khan Nilo Mosrika Momin Tuli B.Sc. in Computer Science 2024-07-03T05:24:43Z 2024-07-03T05:24:43Z 2021 2021-09 Thesis ID 17301074 ID 17301022 ID 17301037 http://hdl.handle.net/10361/23652 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 35 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Transfer learning Image processing Image classifi cation Image segmentation Image enhancement Image assessment Deep learning Cognitive learning theory Image processing--Digital techniques. |
| spellingShingle |
Transfer learning Image processing Image classifi cation Image segmentation Image enhancement Image assessment Deep learning Cognitive learning theory Image processing--Digital techniques. Mizan, Mubasshira Nilo, Laila Sumiya Khan Tuli, Mosrika Momin Transfer learning based industrial steel plates fault diagnosis using industrial fault signals |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021. |
| author2 |
Uddin, Jia |
| author_facet |
Uddin, Jia Mizan, Mubasshira Nilo, Laila Sumiya Khan Tuli, Mosrika Momin |
| format |
Thesis |
| author |
Mizan, Mubasshira Nilo, Laila Sumiya Khan Tuli, Mosrika Momin |
| author_sort |
Mizan, Mubasshira |
| title |
Transfer learning based industrial steel plates fault diagnosis using industrial fault signals |
| title_short |
Transfer learning based industrial steel plates fault diagnosis using industrial fault signals |
| title_full |
Transfer learning based industrial steel plates fault diagnosis using industrial fault signals |
| title_fullStr |
Transfer learning based industrial steel plates fault diagnosis using industrial fault signals |
| title_full_unstemmed |
Transfer learning based industrial steel plates fault diagnosis using industrial fault signals |
| title_sort |
transfer learning based industrial steel plates fault diagnosis using industrial fault signals |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/23652 |
| work_keys_str_mv |
AT mizanmubasshira transferlearningbasedindustrialsteelplatesfaultdiagnosisusingindustrialfaultsignals AT nilolailasumiyakhan transferlearningbasedindustrialsteelplatesfaultdiagnosisusingindustrialfaultsignals AT tulimosrikamomin transferlearningbasedindustrialsteelplatesfaultdiagnosisusingindustrialfaultsignals |
| _version_ |
1814307088994664448 |