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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Venkoparao, V.G. Hota, R.N. Rao, V.S. Gellaboina, M.K. |
| Copyright Year | 2009 |
| Description | Author affiliation: HTS-Research, Honeywell, Bangalore - 560076, INDIA (Venkoparao, V.G.; Hota, R.N.; Rao, V.S.; Gellaboina, M.K.) |
| Abstract | In petroleum refineries, it is a common practice to flare up the exhaust gases before releasing them to the atmosphere in order to reduce the environment pollution. The area or volume of the flare indicates the quantity of gas that is getting released in the refining process and the color of the flare at any given time is decided by the constituents of the gases in the flare and the volume of the flare indicates the quantity of gas that is released. In an indirect way, these parameters of flare indicate the performance of refining process. Presently, the flare is manually observed by the operator and doing so reliably on a 24×7 basis is a difficult job. In this paper we propose an algorithm1 to automate this effort using video analytics and provide the alarms in case of any abnormal flaring event. The flare detection is done by estimating models for foreground and background regions and the color of the flare is analyzed by using classifiers with kernel function, such as support vector machine (SVM). The performance of these algorithms is tested on various data sets collected from refineries. |
| Starting Page | 3022 |
| Ending Page | 3027 |
| File Size | 785545 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424427994 |
| DOI | 10.1109/ICIEA.2009.5138703 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Monitoring Petroleum Refining Gases Color Support vector machines Support vector machine classification Atmosphere Oil pollution Algorithm design and analysis video surveillance Object classification Feature selection One class classifier |
| Content Type | Text |
| Resource Type | Article |
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