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Method and system for predicting diffusion of pollutants

A prediction method and prediction system technology, applied in the direction of image data processing, special data processing applications, instruments, etc., can solve the problems of low accuracy of Gaussian diffusion model, difficult data acquisition, unsatisfactory prediction effect, etc., to reduce the difficulty of acquisition , to achieve the effect of tracing the source and narrowing the scope

Pending Publication Date: 2019-01-01
浙江航天恒嘉数据科技有限公司
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Problems solved by technology

In addition, the formula derived from the existing Gaussian diffusion model requires a lot of data, and the data acquisition is difficult. The accuracy of the Gaussian diffusion model is low, and the actual prediction effect is not ideal.

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  • Method and system for predicting diffusion of pollutants
  • Method and system for predicting diffusion of pollutants
  • Method and system for predicting diffusion of pollutants

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Embodiment Construction

[0055] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

[0056] In the prior art, Gaussian diffusion models have different forms according to different diffusion conditions.

[0057] Diffusion of continuous point sources: Continuous point sources generally refer to chimneys, discharge pipes, vents, etc. that discharge large amounts of pollutants. The outlet placed on the ground is called a ground point source, and the one at a high altitude is called an elevated point source.

[0058] The following two Gaussian diffusion models are introduced in detail:

[0059] 1. Large space point source diffusion

[0060] For point source diffusion in large space, the establishment of Gaussian diffusion model has the following assumptions: ① the average wind flow field is stable, the w...

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Abstract

The invention relates to a method and a system for predicting the diffusion of pollutants. The method comprises the following steps: S1, constructing a Gaussian diffusion model of flue gas dischargedfrom a target flue gas discharge port according to the diffusion condition; S2, collecting an image of the smoke emitted from the target smoke discharge outlet, and performing image processing on theimage to obtain a trajectory equation of the smoke emitted from the target smoke discharge outlet; S3, predicting the spatial concentration distribution of the flue gas discharged from the target fluegas discharge outlet according to the trajectory equation, and correcting the Gaussian diffusion model by comparing the collected real value of the flue gas discharged from the target flue gas discharge outlet; S4, predicting the trajectory diffusion of pollutants in the flue gas discharged from the target flue gas discharge outlet by using the modified Gaussian diffusion model and the association rule algorithm. The method of the invention is based on the Gaussian diffusion model and the image recognition technology, can effectively reduce the difficulty of data acquisition and can optimizethe prediction effect.

Description

technical field [0001] The invention relates to the field of pollutant diffusion prediction, in particular to a pollutant diffusion prediction method and system. Background technique [0002] In the prior art, a Gaussian diffusion model is usually used to predict the diffusion of pollutants. However, the existing Gaussian diffusion model is based on many ideal assumptions. The required assumptions are: ①The average flow field of the wind is stable, the wind speed is uniform, and the wind direction is straight; ②The concentration of pollutants in y, z The axial direction conforms to a normal distribution; ③The mass of pollutants is conserved in the transport and diffusion; ④The source intensity of pollution sources is uniform and continuous. In addition, the formula derived from the existing Gaussian diffusion model requires a lot of data, and the data acquisition is difficult. The accuracy of the Gaussian diffusion model is low, and the actual prediction effect is not ideal...

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Application Information

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IPC IPC(8): G06F17/50G06T7/00
CPCG06T7/0004G06F30/20
Inventor 宋春红刘浩
Owner 浙江航天恒嘉数据科技有限公司
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