Intelligent Multi-Sensor Process Condition Monitoring
A Master of Science Thesis in Mechatronics Submitted by Firas Hammad Entitled, "Intelligent Multi-Sensor Process Condition Monitoring," December 2007. Available are both Soft and Hard Copies of the Thesis.
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | doctoralThesis |
| منشور في: |
2007
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/122 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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| _version_ | 1864513442815148032 |
|---|---|
| author | Hammad, Firas |
| author_facet | Hammad, Firas |
| author_role | author |
| dc.contributor.none.fl_str_mv | Deiab, Ibrahim |
| dc.creator.none.fl_str_mv | Hammad, Firas |
| dc.date.none.fl_str_mv | 2007-12 2011-03-10T12:43:47Z 2011-03-10T12:43:47Z |
| dc.format.none.fl_str_mv | application/pdf application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2007.05 http://hdl.handle.net/11073/122 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | Mechatronics Testing Machinery Monitoring Manufacturing processes Automation |
| dc.title.none.fl_str_mv | Intelligent Multi-Sensor Process Condition Monitoring |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
| description | A Master of Science Thesis in Mechatronics Submitted by Firas Hammad Entitled, "Intelligent Multi-Sensor Process Condition Monitoring," December 2007. Available are both Soft and Hard Copies of the Thesis. |
| format | doctoralThesis |
| id | aus_e9decd7f5c6bff3c651468a1ed8ea86d |
| identifier_str_mv | 35.232-2007.05 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/122 |
| publishDate | 2007 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Intelligent Multi-Sensor Process Condition MonitoringHammad, FirasMechatronicsTestingMachineryMonitoringManufacturing processesAutomationA Master of Science Thesis in Mechatronics Submitted by Firas Hammad Entitled, "Intelligent Multi-Sensor Process Condition Monitoring," December 2007. Available are both Soft and Hard Copies of the Thesis.Loss of production and machine breakdown are critical challenges facing modern machining. The main objective of this work is to develop an intelligent multi-sensor process condition monitoring that is able to predict the wear propagation in the cutting tool using information obtained from the analysis of cutting force and acoustic emission (AE) signals generated during turning of steel. The time domain for cutting forces and AE signals are processed for relevant features about fresh and worn tools. Principal component analysis (PCA) is used to eliminate redundant and irrelevant features. The most relevant features are used as inputs for the two classifier used in this investigation, namely, back propagation neural network (BPNN) and polynomial classifier (PC). The classifiers parameters are optimized to achieve faster computations and better predictions. To improve accuracy, leave-one-out (LOO) method is used to train both classifiers. LOO uses all the data samples for training the system. Classifiers training is modeled by correlating the extracted features with the actual measured tool wear. Comparing to BPNN, PC shows a dramatic reduction in training and prediction time. The results show the effectiveness of PCA in selecting feature that retains as much as possible of the variation in the original data. Such a system is of vital importance to the automation of manufacturing facilities. Also the use of features enhances the accuracy of both method in comparison to the use of raw data.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR)Deiab, Ibrahim2011-03-10T12:43:47Z2011-03-10T12:43:47Z2007-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdf35.232-2007.05http://hdl.handle.net/11073/122en_USoai:repository.aus.edu:11073/1222025-06-26T12:29:08Z |
| spellingShingle | Intelligent Multi-Sensor Process Condition Monitoring Hammad, Firas Mechatronics Testing Machinery Monitoring Manufacturing processes Automation |
| status_str | publishedVersion |
| title | Intelligent Multi-Sensor Process Condition Monitoring |
| title_full | Intelligent Multi-Sensor Process Condition Monitoring |
| title_fullStr | Intelligent Multi-Sensor Process Condition Monitoring |
| title_full_unstemmed | Intelligent Multi-Sensor Process Condition Monitoring |
| title_short | Intelligent Multi-Sensor Process Condition Monitoring |
| title_sort | Intelligent Multi-Sensor Process Condition Monitoring |
| topic | Mechatronics Testing Machinery Monitoring Manufacturing processes Automation |
| url | http://hdl.handle.net/11073/122 |