PM2.5 concentration detection method and device based on neural network

A neural network and concentration detection technology, applied in biological neural network models, measurement devices, suspension and porous material analysis, etc. Effect

Active Publication Date: 2017-06-20
NORTHEASTERN UNIV LIAONING
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Problems solved by technology

[0007] Aiming at the defects of the prior art, the present invention provides a method and device for detecting PM2.5 concentration based on a neural network, which overcomes the shortcomings of low automation of the PM2.5 concentration detection method in the prior art, and can realize repeated detection, detection High precision and easy calculation

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  • PM2.5 concentration detection method and device based on neural network
  • PM2.5 concentration detection method and device based on neural network
  • PM2.5 concentration detection method and device based on neural network

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[0049] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0050] figure 1 A schematic flow chart of the neural network-based PM2.5 concentration detection method provided in the first embodiment of the present invention is shown, as figure 1 As shown, the method of this embodiment is as follows.

[0051] 101. Establish a laser detection system based on the principle of Fraunhofer diffraction.

[0052] In this step, the laser detection system includes: a power supply unit, a He-Ne laser, a filter lens, a beam expander lens, an air pump, an air chamber, a signal receiving unit, a detection unit and a calculation unit;

[0053] Wherein, the power supply unit is used to provide power for the He-Ne laser, the air pump, the detectio...

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Abstract

The invention provides a method and device for detecting PM2.5 concentration based on a neural network. First, a laser detection system is established based on the principle of Fraunhofer diffraction, and then according to the digital signal of light intensity collected by the laser detection system, based on Fraunhofer Based on the principle of diffraction, it is verified that there is a corresponding functional relationship between the light intensity digital signal and the PM2.5 concentration value, and the light intensity digital signal is used as an input to establish a regularized neural network model to output the PM2.5 concentration value. The shortcomings of the low automation degree of the PM2.5 concentration detection method in the prior art are overcome, and repeated detection can be realized, the detection accuracy is high, and the calculation is simple and convenient.

Description

[0001] Technical field: [0002] The invention relates to the field of concentration detection, in particular to a neural network-based PM2.5 concentration detection method and device. [0003] Background technique: [0004] In recent years, severe smog and polluted air have appeared in the central and eastern regions of my country, and related studies have shown that PM2.5 is the chief culprit of smog. PM2.5 refers to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm in the atmosphere, also known as particulate matter that can enter the lungs. Compared with coarser atmospheric particles, PM2.5 has a smaller particle size and is rich in a large number of toxic and harmful substances And the residence time in the atmosphere is long, the transportation distance is long, pollutes the atmospheric environment, and will pose a serious threat to people's health. [0005] The existing PM2.5 concentration detection methods mostly use manual gravimetric method...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N15/06G06N3/02
Inventor 徐林关天一李砚浓郑文婧
Owner NORTHEASTERN UNIV LIAONING
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