Flying dust concentration detection device and flying dust detection method

A technology for concentration detection and detection method, which is applied in measurement devices, suspension and porous material analysis, particle suspension analysis, etc., and can solve the problems of low civil use, high cost, limited measurement effect and accuracy

Pending Publication Date: 2020-06-19
山东诺蓝信息科技有限公司
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Problems solved by technology

[0003] In order to reduce the hazards of dust in specific occasions, it is necessary to be able to detect the concentration of dust in the atmosphere in

Method used

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  • Flying dust concentration detection device and flying dust detection method
  • Flying dust concentration detection device and flying dust detection method
  • Flying dust concentration detection device and flying dust detection method

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[0037] This patent uses the combination of SSD (single shot multibox detector) algorithm and SAPD (soft anchor-point object dectection) algorithm to measure

[0038] In the SSD algorithm, VGG16 is used as the basic model, and then a convolutional layer is added on the basis of VGG16 to obtain more feature maps for detection.

[0039] The network structure of the improved SSD algorithm used in this patent is as follows: Figure 14 As shown, multi-scale feature maps are used to achieve the goal of detection.

[0040] This patent uses VGG16 as the basic model, and converts the fully connected layers fc6 and fc7 of VGG16 into 3×3 convolutional layers conv6 and 1×1 convolutional layers conv7 respectively, and the pooling layer pool5 is changed from the original 2×2-s2 becomes 3×3-s1.

[0041] Further, in order to expand the field of view of convolution exponentially without increasing the complexity of parameters and model, conv6 adopts dilated convolution or atrous convolution, ...

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Abstract

The invention relates to a flying dust concentration detection device and flying dust detection method based on deep learning, belongs to the technical field of air quality detectors, and solves the problems of flying dust concentration detection cost, long recognition time and poor measurement effect in the prior art. The invention comprises an air collection device, an air transmission device,n a paper feeding device and a measuring device. The method comprises the following steps: the air collection device acquires real-time sample air collected in a detection field environment; the air transmission device is used for internally transmitting the sample air through a negative pressure machine; the paper feeding device automatically replaces background paper used for shooting after shooting is completed, and the measuring device detects an object through an artificial neural network after shooting sample gas. The sizes of the flying dust particles can be effectively detected, thedifferent particles are recognized and detected by means of a deep learning algorithm of target detection, and the concentrations of the different particles in the flying dust can be accurately detected in real time.

Description

technical field [0001] The present invention mainly relates to the field of air quality detection, in particular to a dust detection device and a dust detection method based on deep learning measurement technology. Background technique [0002] Flying dust is an open pollution source that enters the atmosphere due to the dust on the ground being driven by wind, man-made or other drives, and is an important part of the total suspended particulate matter in the ambient air. When the powder is subjected to the induced air flow, the flowing air caused by indoor ventilation, and the air flow generated by the rotation of the moving parts of the equipment during the transportation and processing of the powder, the fine dust in the powder will be separated from the powder first and then fly away. The diffusion of dust is caused by the flow of indoor air, thus completing the process from dust generation to diffusion. Flying dust can pollute the air, affect the environment, and cause...

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Application Information

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IPC IPC(8): G01N15/06
CPCG01N15/06G01N2015/0693
Inventor 潘红光车昕马论论樊永森王利平孙大明
Owner 山东诺蓝信息科技有限公司
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