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A new model-based approach for power plant Tube-ball mill condition monitoring and fault detection
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Guo, Shen, Wang, Jihong, Wei, Jianlin and Zachariades, Paschalis (2014) A new model-based approach for power plant Tube-ball mill condition monitoring and fault detection. Energy Conversion and Management, Volume 80 . pp. 10-19. doi:10.1016/j.enconman.2013.12.046
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Official URL: http://dx.doi.org/10.1016/j.enconman.2013.12.046
Abstract
With the fast growth in intermittent renewable power generation, unprecedented demands for power plant operation flexibility have posed new challenges to the ageing conventional power plants in the UK. Adding biomass to coal for co-fired power generation has become widely implemented practices in order to meet the emission regulation targets. These have impacted the coal mill and power plant operation safety and reliability. The Vertical Spindle mill model was developed through the authors’ work before 2007. From then, the new research progress has been made in modelling and condition monitoring for Tube-ball mills and is reported in the paper. A mathematical model for Tube-ball milling process is developed by applying engineering principles combined with model unknown parameter identifications using a computational intelligent algorithm. The model describes the whole milling process from the mill idle status, start-up to normal grinding and shut-down. The model is verified using on-site measurement data and on-line test. The on-line model is used for mill condition monitoring in two ways: (i) to compare the predicted and measured mill output pressure and temperatures and to raise alarms if there are big discrepancies; and (ii) to monitor the mill model parameter variation patterns which detect the potential faults and mill malfunctions.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) | ||||
| Divisions: | Faculty of Science > Engineering | ||||
| Library of Congress Subject Headings (LCSH): | Coal-fired power plants -- Great Britain, Genetic algorithms, Power-plants -- Great Britain | ||||
| Journal or Publication Title: | Energy Conversion and Management | ||||
| Publisher: | Elsevier Ltd | ||||
| ISSN: | 0196-8904 | ||||
| Official Date: | 2014 | ||||
| Dates: |
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| Volume: | Volume 80 | ||||
| Page Range: | pp. 10-19 | ||||
| DOI: | 10.1016/j.enconman.2013.12.046 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Open Access | ||||
| Funder: | British Coal Utilisation Research Association (BCURA), Engineering and Physical Sciences Research Council (EPSRC) | ||||
| Grant number: | 85A/B (BCURA) ; EP/G062889 (EPSRC) |
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