Md Sani, Zamani (2007) Intelligent Rock Vertical Shaft Impact Crusher Local Database System. International Journal of Computer Science and Network Security . pp. 57-62. ISSN 1738-7906
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Abstract
Aggregates are one of the major components in the concrete production. The aggregates output from the Rock Vertical Shaft Impact Crusher (RoR VSI), had been classified to six groups of shapes then divided further into two categories namely the high quality aggregates and the low quality aggregates. The characteristics of the aggregates such as shape, size and color, do play an important roles in the development of high strength concrete. In order to produce high quality aggregates, the system would need to be monitored and maintained continuously by analyzing the past and current data. Presently, there is no database system to store the images for the classified data. The conventional method of the aggregates is done manually which is slow, highly subjective and laborious. Therefore, a local database system is proposed to store information could help to overcome this problem. The images and aggregates’ recognition and classification data will be kept in order and it will have a simple and easy way of storing and retrieving information. The machine performance can be retrieved for any period of time by calculating the output for high quality aggregates out of total of agggregates produced. The shapes break down for all six recognizable shapes also can be displayed. These could help the engineer to monitor the system on output performance with continuous analysis, with shorter time. Other than that, the strength of the concrete can be determined by counting the number and the percentage of good quality of aggregate being used.
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Electrical Engineering > Department of Mechatronics Engineering |
| Depositing User: | En Zamani Md. Sani |
| Date Deposited: | 18 Nov 2013 04:26 |
| Last Modified: | 28 May 2015 04:09 |
| URI: | http://eprints.utem.edu.my/id/eprint/10202 |
| Statistic Details: | View Download Statistic |
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