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Fuel type on-line identification method based on support vector machine

A technology of support vector machines and fuel types, which is applied in chemical analysis by combustion and photometry by electric radiation detectors, etc., to achieve good real-time performance, enhanced economy and safety, and reduced dimensionality

Inactive Publication Date: 2010-05-05
BEIHANG UNIV
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Problems solved by technology

However, the correct rate of this method for judging known fuel types is much lower than that of using support vector machine technology for discrimination

Method used

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  • Fuel type on-line identification method based on support vector machine
  • Fuel type on-line identification method based on support vector machine
  • Fuel type on-line identification method based on support vector machine

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Embodiment Construction

[0016] In order to enable those of ordinary skill in the art to clearly understand the technical scheme of the present invention, the specific embodiments of the present invention are now further described:

[0017] Specific implementation method:

[0018] The first step is to establish a joint probability density model of known fuel types and a support vector machine model for online identification of fuel types.

[0019] First, use three photoelectric sensors to obtain the radiation signals of a known fuel combustion flame in the infrared, visible light and ultraviolet bands, each group includes 3 signals, collect M groups, and get a total of M×3 flame radiation signals , forming a signal sample set {x(m, s)|m=1, 2, . . . , M; s=1, 2, 3}. The selection of M should make the signal in the collected sample set {x(m, s)} within a complete cycle, and can cover various working conditions of fuel combustion. For example, M=500 may be selected, that is, 500 sets of signals are col...

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Abstract

The invention discloses a fuel type on-line identification method based on a support vector machine. Three photoelectric sensors can be used for detecting radiation signals of infrared light, visible light and ultraviolet light wave bands in combustion flame of known fuel; a fuel type discriminant model is set up based on orthogonal eigen values of the radiation signals, and can be obtained by combining a joint probability density discriminant model and a support vector machine module; as the radiation signals of the fuel to be identified on the three wave bands can be obtained by the detection of the three photoelectric sensors, the obtained orthogonal eigen values is input into the set fuel type discriminant model; if the fuel to be identified is judged to be new fuel by the discriminant model, the group of orthogonal eigen values can be stored and used for completing and updating the discriminant model; and if not, the type of the fuel can be directly output by the discriminant model.

Description

【Technical field】 [0001] The invention relates to an online identification method for combustion fuel types, belonging to the technical field of industrial boiler fuel identification. 【Background technique】 [0002] The stability of combustion in the boiler is conducive to improving the utilization rate of fuel resources, reducing pollutant emissions and improving the thermal efficiency of the boiler. The change of fuel type in the boiler directly affects the detection and control of combustion, thus affecting the stability of combustion in the furnace. Due to the limitation of factors such as economy, the types of fuel in the furnace are various, and the combustion is unknown and constantly changing. Therefore, the prediction of fuel type is very important for the safety of combustion. [0003] Support Vector Machines (SVM, Support Vector Machines) is a new supervised learning method developed on the basis of statistical learning theory, which has complete theory, global ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N31/12G01J1/42
Inventor 徐立军李小路谭丞
Owner BEIHANG UNIV
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