Evaluating Gas Turbine Performance Using Machine Generated Data: Quantifying Degradation and Impacts of Compressor Washing

Show simple item record

dc.contributor.author Igie, Uyioghosa
dc.contributor.author Diez-Gonzalez, Pablo
dc.contributor.author Giraud, Antoine
dc.contributor.author Minervino, Orlando
dc.date.accessioned 2016-07-06T10:40:08Z
dc.date.available 2016-07-06T10:40:08Z
dc.date.issued 2016
dc.identifier.citation Igie, U. et al. (2016) Evaluating Gas Turbine Performance Using Machine Generated Data: Quantifying Degradation and Impacts of Compressor Washing, Journal of Engineering for Gas Turbines and Power, Vol. 138, Iss. 2, pp. 122601-1 - 122601-18 en_UK
dc.identifier.issn 0742-4795
dc.identifier.uri http://dx.doi.org/10.1115/1.4033748
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/10097
dc.description.abstract Gas turbine operators are often met with the challenge of utilizing and making meaning of the vast measurement data collected from machine sensors during operation. This can easily be about 576 million data points of gas path measurements for one machine in a base load operation in a year, if the width of the data is 20 columns of measured and calculated parameters. This study focuses on the utilisation of large data in the context of quantifying the degradation that is mostly related to compressor fouling, in addition to investigations on the impact of off-line and on-line compressor washing. To achieve this, 4 gas turbine engines operating for about 3.5 years with 51 off-line washes and 1,184 occasions of on-line washes have been examined. This investigation includes different wash frequency, liquid concentration and one engine operation without on-line washing (only off-line). This study has involved correcting measurement data, not just with compressor inlet temperatures and pressures, but also relative humidity. TURBOMATCH: an in-house gas turbine performance simulation software has been implemented to obtain non-dimensional factors for the corrections. All of the data visualization and analysis have been conducted using Tableau analytics software, which facilitates the investigation of global and local events within an operation. The concept of using of handles and filters is proposed in this study, and it demonstrates the level of insight to the data and forms the basis of the outcomes obtained. This work shows that during operation, the engine performance is mostly deteriorating, though to varying degrees. On-line washing also showed an influence on this, reducing the average degradation rate each hour by half, when compared to the engine operating only with off-line washing. Hourly marginal improvements were also observed with an increased average wash frequency of 9 hours and a similar outcome obtained when the washing solution is 2.3 times more concentrated. Clear benefits of off-line washes is also presented, alongside the typical obtainable values of increased power output after a wash, also in relation to the number of operating hours before a wash. en_UK
dc.language.iso en en_UK
dc.publisher ASME en_UK
dc.subject Gas turbine performance en_UK
dc.subject Machine data en_UK
dc.subject Sensors en_UK
dc.subject Degradation en_UK
dc.subject Fouling en_UK
dc.subject Compressor washing en_UK
dc.subject Analytics en_UK
dc.title Evaluating Gas Turbine Performance Using Machine Generated Data: Quantifying Degradation and Impacts of Compressor Washing en_UK
dc.type Article en_UK


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search CERES


Browse

My Account

Statistics