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Method for real time extraction of TDLAS gas absorption spectrum absorbance by BP neural network

A BP neural network and gas absorption technology, applied in the direction of color/spectral characteristic measurement, etc., can solve the problems that are not easy to meet, and achieve the effect of wide application range and good robustness

Active Publication Date: 2015-04-22
SOUTHEAST UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

For industrial application environments, especially in unstable combustion flow fields, it is difficult to meet this condition

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  • Method for real time extraction of TDLAS gas absorption spectrum absorbance by BP neural network
  • Method for real time extraction of TDLAS gas absorption spectrum absorbance by BP neural network
  • Method for real time extraction of TDLAS gas absorption spectrum absorbance by BP neural network

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Embodiment 1

[0035] The method for real-time extraction of the TDLAS gas absorption spectrum absorbance by the BP neural network of the present embodiment is specifically realized by the following steps:

[0036] Step 1) In the TDLAS measurement system, the signal source generates the current control signal of the semiconductor laser to modulate the laser, and the modulated optical signal sent by the laser is split into two paths, one path passes through the gas to be measured, and after being absorbed by the gas to be measured, then is received by a photodetector to produce a transmitted signal V abp , the other path is directly received by the photodetector without passing through the gas to be measured, and generates a reference signal V ref .

[0037] Step 2) For the transmission signal V of step 1) abp and reference signal V refPerform normalization processing, transform the amplitude of the transmission signal and the reference signal to [0.1,0.95] through linear function transfor...

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Abstract

The invention discloses a method for real time extraction of the TDLAS gas absorption spectrum absorbance by a BP neural network. The method comprises the following steps: 1, laser emitted by a laser in a TDLAS measuring system is modulated by a current control signal generated by a signal source to form two beams, one beam of laser traverses through a gas to be measured and irradiates to one photoelectric detector to obtain a transmission signal Vabp, and the other beam of laser directly irradiates to another photoelectric detector to obtain a reference signal Vref; and 2, the transmission signal Vabp and the reference signal Vref are normalized to obtain a normalized transmission signal Vabp_norm and a normalized reference signal Vref_norm, the normalized transmission signal Vabp_norm and the normalized reference signal Vref_norm are input to the BP neural network, and the BP neural network extracts the absorption spectrum absorbance of the output gas. The method for real time extraction of the gas absorption spectrum absorbance in a TDLAS gas measuring technology by the BP neural network of FPGA has the advantages of good robustness wide application range and real time calculation.

Description

technical field [0001] The invention relates to a method for real-time extraction of TDLAS gas absorption spectrum absorbance by BP neural network, more specifically, a method for real-time extraction of tunable semiconductor laser gas absorption spectrum absorbance by BP neural network, belonging to the technical field of analytical instrument algorithms . Background technique [0002] With the rapid development of my country's economy and the continuous increase of the industrialization process, a large amount of harmful gases are emitted into the atmosphere during the production of coal-fired power plants, metallurgy and municipal waste incineration, mainly CO, CO 2 , NO X , SO 2 Gas and dust, etc., cause many problems such as high energy consumption and serious environmental pollution. The country pays more and more attention to environmental protection. Therefore, improving combustion efficiency and reducing the emission of harmful combustibles have a great impact on ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/39
Inventor 卢荣军杜倩倩
Owner SOUTHEAST UNIV