Density, Distillation, FT-IR and FIA for Rapid Determination of Adulterant Kerosene in Gasoline and Diesel
Chebii Paul1, Munyendo Were2, Kiprop Ambrose3, Mitei Yulita Cheruiyot4, Joseph Barmao5
1Chebii Paul, Department of Chemistry and Biochemistry, Moi University, Eldoret, Kenya.
2Munyendo Were, Department of Chemistry and Biochemistry, Moi University, Eldoret, Kenya.
3Kiprop Ambrose, Department of Chemistry and Biochemistry, Moi University, Eldoret, Kenya.
4Mitei Yulita Cheruiyot, Department of Chemistry, University of Eldoret, Eldoret, Kenya.
5Joseph Barmao, Department of Chemistry and Biochemistry, Moi University, Eldoret, Kenya.
Manuscript received on February 12, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on February 25, 2016. | PP: 20-29 | Volume-4 Issue-3, February 2016. | Retrieval Number: C1057024316
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The paper concerns the design of a new methodology for diagnosis by Luneberger Observer using the Bond Graph. The observer design provides a state estimated from the model and inputs and outputs measurements. Furthermore, we have exploited the architectural of the Bond Graph to generate the diagnostic condition based on Luenberger observers. Furthermore, the performance of the proposed diagnosis system is studied by these residuals to the certainties and faults. The research results have been applied to an industrial process RODS (Reverse Osmosis Desalination System) of Research and Technology Center of Energy Borj Cedria. In this context, the proposed method was operated from the modeling step to the diagnosis system step
Keywords: Diagnosis, Lunberger Observer, Bond Graph, Reverse Osmosis Desalination System.