Back Pressure Monitoring of Power Plant Condenser Using Multiple Adaptive Regression Spline
| dc.contributor.author | Pani, Ajaya Kumar | |
| dc.date.accessioned | 2021-10-07T12:27:38Z | |
| dc.date.available | 2021-10-07T12:27:38Z | |
| dc.date.issued | 2020-02 | |
| dc.description.abstract | This research work involves the application of multivariate adaptive regression spline (MARS) for estimating back pressure (p) created in a condenser of a coal-fired thermal power plant. MARS employs the plant load (L) and temperature of cooling water (T) as input variables. The output of the MARS is condenser back pressure p^. The designed MARS-based model gives equations for determination of p. Further, the MARS-generated objective function is optimized by randomized search cross validation. Simulation study shows that the accuracy of the reported MARS model is quite satisfactory for the prediction of back pressure. | en_US |
| dc.identifier.uri | https://link.springer.com/chapter/10.1007/978-981-15-0135-7_1 | |
| dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/2651 | |
| dc.language.iso | en | en_US |
| dc.publisher | Springer | en_US |
| dc.subject | Chemical Engineering | en_US |
| dc.subject | Fault Detection | en_US |
| dc.subject | Modelling | en_US |
| dc.subject | Multivariate adaptive regression spline | en_US |
| dc.title | Back Pressure Monitoring of Power Plant Condenser Using Multiple Adaptive Regression Spline | en_US |
| dc.type | Other | en_US |
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