Flame stability and burner condition monitoring through optical sensing and digital imaging

This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for flame stability and burner condition monitoring on fossil-fuel-fired furnaces. A review of methodologies and technologies for the monitoring of flame stability and

burner condition is given, together with the discussions of existing problems and technical requirements in their applications. A technical strategy, incorporating optical sensing, digital imaging, digital signal/image processing and soft computing techniques, is proposed. Based on this strategy, a prototype flame imaging system is developed. The system consists of a rigid optical probe, an optical-bearn-splitting unit, an embedded photodetector and signal-processing board, a digital camera, and a mini-motherboard with associated application software. Detailed system design, implementation, calibration and evaluation are reported. A number of flame characteristic parameters are extracted from flame images and radiation signals. Power spectral density, oscillation frequency, and a proposed universal flame stability index are used for the assessment of flame stability. Kernel-based soft computing techniques are employed for burner condition monitoring. Specifically, kernel principal components analysis is used for the detection of abnormal conditions in a combustion process, whilst support vector machines are used for the prediction of NO x emission and the identification of flame state. Extensive experimental work was conducted on a 9MW th heavy-oil-fired combustion test facility to evaluate the performance of the prototype system and developed algorithms. Further tests were carried out on a 660MWth heavy-oil-fired boiler to investigate the cause of the boiler vibration from a flame stability point of view. Results Obtained from the tests are presented and discussed.