You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
19 August 2014Identification of biomass co-combustion operating point using image processing
Thermal power and excess air coefficient are one of key parameters that characterize operating point of combustion
process. In practice, they are hard to determine directly. The k-nearest neighbor (k-NN) regression algorithm was applied where some flame image geometric parameters were used as predictors. The model was assessed by carrying out several combustion tests for nine different settings of the laboratory combustion facility. Thermal power and excess air coefficient were kept constant and set independently for known biomass content.
The alert did not successfully save. Please try again later.
Andrzej Kotyra, Waldemar Wójcik, Aigul Iskakova, Sarsenbek Zhussupbektov, "Identification of biomass co-combustion operating point using image processing," Proc. SPIE 9291, 13th International Scientific Conference on Optical Sensors and Electronic Sensors, 929108 (19 August 2014); https://doi.org/10.1117/12.2070057