The complexity of changes occurring in the flame during the combustion process has a direct influence on the quantity and quality of the combustion products. The presented measurement data pertaining to the changes in flame luminosity were recorded using a specialized monitoring system. These signals from the combustion of such fuels as pulverized coal and mazout were recorded with high sampling rate. The paper presented the analysis of changes in flame luminosity for different fuels using continuous and discrete wavelet transform. The main aim of the studies was to determine the scale values, which enable differentiating between the type of combusted fuel. The results of studies were presented in the form of scalograms.


scalogram; continuous and discrete wavelet transform, diagnostics

Bi F., Li L., Zhang J., Ma T.: Source identification of gasoline engine noise based on continuous wavelet transform and EEMD–RobustICA. Applied Acoustics 100/2015, 34–42.

Białasiewicz J. T.: Falki i aproksymacje.WNT, Warszawa 2000.

Ibrahimoglu B., Yilmazoglu M. Z., Cucen A.: Numerical modeling of repowering of a thermal power plant boiler using plasma combustion systems. Energy, 103/2016, 38–48.

Jiang Y. H., Li G. X., Li H. M., Li L., Zhang G. P.: Effect of flame inherent instabilities on the flame geometric structure characteristics based on wavelet transform. International Journal of Hydrogen Energy 43(18)/2018, 9022-9035.

Komada P., Cięszczyk S., Zhirnova O., Askarova N.: Optyczna metoda diagnostyki gazu syntezowego z biomasy. Rocznik Ochrona Środowiska 18/2/2016, 271–283.

Kordylewski W.: Spalanie I paliwa. Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław 2008.

Mallat S.: A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way. Academic Press, 2008.

Miller B.G., Clean coal engineering technology. Elsevier, 251–300, 2010.

Siano D., Panza M. A., D'Agostino D.: Knock detection based on MAPO analysis, AR model and discrete wavelet transform applied to the in-cylinder pressure data: results and comparison. SAE International Journal of Engines 8(1)/2015, 1–13.

Smolarz A., Kotyra A., Wójcik W., Ballester J.: Advanced diagnostics of industrial pulverized coal burner using optical methods and artificial intelligence. Experimental Thermal and Fluid Science 43/2012, 82–89.

Wójcik W., Gromaszek K., Kotyra A., Ławicki T.: Pulverized coal combustion boiler efficient control. Przegląd Elektrotechniczny 88/11b/2012, 316–319.

Wójcik W., Gromaszek K., Shegebayeva Z., Suleimenov B., Burlibay A.: Optimal control for combustion process. Przegląd Elektrotechniczny 90/4/2014, 157–160.

Wójcik W., Gromaszek K., Smailova S.: Using optical signals for pulverised coal combustion process optimal control to increase economic efficiency of the boiler. Actual Problems of Economics 142/2013, 307–311.

Wójcik W.: Fiber-optic system for monitoring the combustion process. PAK 53/2007, 24–28.

Wójcik W.: Nowoczesne technologie paliw i spalania. Monografie Komitetu Inżynierii Środowiska PAN, Lublin 2011.

Wu J. D., Chen J. C.: Continuous wavelet transform technique for fault signal diagnosis of internal combustion engines. NDT & e International 39(4)/2006, 304–311.

Yan C., Zhang T., Sun Y., Tang H., Li H.: A hybrid variable selection method based on wavelet transform and mean impact value for calorific value determination of coal using laser-induced breakdown spectroscopy and kernel extreme learning machine. Spectrochimica Acta Part B: Atomic Spectroscopy 154/2019, 75–81.


Published : 2020-09-30

Grądz, Żaklin. (2020). SELECTED ASPECTS IN THE ANALYSIS OF THE COMBUSTION PROCESS USING WAVELET TRANSFORM. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 10(3), 52-55.

Żaklin Grądz
Lublin Univeristy of Technology, Institute of Electronics and Computer Science  Poland