JP2009068970A - Simulating apparatus of dust diffusion into atmosphere, diffusion simulating method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To enhance the simulating precision of dust diffusion into the atmosphere. <P>SOLUTION: At least one fixedly installed camera 200 is used to continuously record the time series image of the smoke from the chimney present in a measuring target region at a definite time interval, the brightness in the time direction of the same pixel coordinates of the continuous image is subjected to Fourier transform to calculate the time series of the power spectrum of a screen, the power spectrum of an isotropic turbulent flow is calculated from the power spectrum of the screen, the vibration frequency caused by a Karman vortex is calculated from the difference between the power spectrum of the screen and the power spectrum of the isotropic turbulent flow. A Storrow-Hull number is calculated from the vibration frequency caused by the Karman vortex, wind velocity and the diameter of the chimney, a vortex diffusion coefficient and diffusion width are calculated using the relation between the Storrow-Hull number and a Reynolds number, the diffusion width is decomposed into a horizontal component and a vertical component using the image in the ejection direction of the smoke from the chimney and the diffusion of dust is simulated by the analysis of a numerical value using the horizontal component of the diffusion width, the vertical component of the diffusion width, a weather condition and a dust condition. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a dust atmospheric diffusion simulation apparatus, method, and program for determining the diffusion of dust into the atmosphere, and in particular, accurately and inexpensively diffuses dust from a factory having a chimney or a coal storage to the atmosphere. Related to what you want.

  Dust diffused from factories and coal storage sites causes troubles such as soiling laundry and automobiles in the surrounding area, so it is indispensable to monitor the diffusion of dust and minimize the amount of dust. . Therefore, conventionally, when monitoring the diffusion state of dust to the surrounding area, a large number of dust diffusion amount measuring devices are installed and monitoring is performed based on the measured values.

  Patent Document 1 discloses a device that monitors the diffusion of dust by reducing the number of dust diffusion amount measurement points by using numerical simulation. As shown in FIG. 14, stability stage classifications A to G are obtained from the wind speed, the amount of solar radiation, and the like using a Pasquill stability stage classification table (see Table 1). Then, using the stability stage classifications A to G and the distance from the dust source, from the Pasquill-Gifford diagram (see FIGS. 15 and 16), the vertical component σz of the diffusion width and the horizontal component σy of the diffusion width. Ask for. Thereafter, the dust diffusion distribution is obtained by numerical analysis from the obtained diffusion width, the measured dust diffusion amount, the wind direction, and the like.

Japanese Patent Laid-Open No. 2-64437

  However, the conventional method of monitoring the diffusion state with a large number of dust diffusion amount measuring devices has to increase the number of relatively expensive measuring devices in order to improve the monitoring accuracy, and is not economical. There is a point. In addition, the diffusion state other than the measurement points can only be interpolated from the data of the measurement points.

  Further, the simulation method disclosed in Patent Document 1 has only seven stages as Pasquill stability stage classifications obtained from observed values of weather conditions, and may not match the actual situation, and the numerical simulation analysis accuracy is poor. There was a problem. For example, in the clear sky after noon, the amount of solar radiation is large, the Pasquill stability classification categories are A and B, and the Pasquill-Gifford diagram shows a large value for the horizontal component σy of the diffusion width. . However, when the actual phenomenon is observed, there is a discrepancy that only the smoke rises and the horizontal component σy of the diffusion width is small.

  The present invention has been made in view of the above points, and an object thereof is to improve the simulation accuracy of the diffusion of dust into the atmosphere.

The inventors of the present application have determined the diffusion width directly by paying attention to the smoke generated from the chimney as a method for accurately obtaining the diffusion width of the dust in the atmosphere. The gist of the present invention will be described below.
The dust diffusion simulation apparatus of the present invention is a dust diffusion simulation apparatus for determining the diffusion of dust into the atmosphere, and is present in the measurement target area using one or more stationary cameras. Means for continuously recording time-series images of smoke from the chimney at regular time intervals, and means for obtaining a time series of the power spectrum of the screen by Fourier transforming the luminance in the time direction at the same pixel coordinates of the continuous images. And a means for obtaining an isotropic turbulent power spectrum from the screen power spectrum, a vibration frequency caused by the Karman vortex from the difference between the screen power spectrum and the isotropic turbulent power spectrum, and a vibration caused by the Karman vortex. A means for obtaining the Strouhal number from the frequency, wind speed and chimney diameter, and obtaining the eddy diffusion coefficient and diffusion width using the relationship between the Strouhal number and the Reynolds number; Using the image of the direction in which smoke is emitted from the air and separating the diffusion width into a horizontal component and a vertical component, and the numerical analysis using the horizontal component of the diffusion width and the vertical component of the diffusion width, the meteorological condition, and the dust condition. And means for simulating the diffusion of.
The method for simulating the diffusion of dust in the atmosphere of the present invention is a method for simulating the diffusion of dust in the atmosphere to determine the diffusion of the dust into the atmosphere, and is present in the measurement target area using one or more stationary cameras. A step of continuously recording a time series image of smoke from a chimney at a certain time interval, and a step of obtaining a time series of a power spectrum of the screen by Fourier transforming the luminance in the time direction at the same pixel coordinates of the continuous image. Calculating the power spectrum of isotropic turbulence from the power spectrum of the screen, determining the vibration frequency due to Karman vortex from the difference between the power spectrum of the screen and the power spectrum of isotropic turbulence, and vibration due to Karman vortex Obtain the Strouhal number from the frequency, wind speed, and chimney diameter, and obtain the eddy diffusion coefficient and diffusion width using the relationship between the Strouhal number and the Reynolds number. Using the image of the step and the direction of smoke emission from the chimney, decomposing the diffusion width into a horizontal component and a vertical component, using the horizontal component of the diffusion width and the vertical component of the diffusion width, weather conditions, and dust conditions And a step of simulating the diffusion of dust by numerical analysis.
The program of the present invention is a program for simulating the diffusion of dust into the atmosphere to determine the diffusion of dust into the atmosphere, and is present in the measurement target area using one or more cameras with a stationary computer. Means for continuously recording time-series images of smoke from the chimney at regular time intervals, means for obtaining a time series of the power spectrum of the screen by Fourier transforming the luminance in the time direction at the same pixel coordinates of the continuous images; A means of obtaining a power spectrum of isotropic turbulence from the power spectrum of the screen, a vibration frequency caused by Karman vortex from a difference between the power spectrum of the screen and the power spectrum of isotropic turbulence, and a vibration frequency caused by Karman vortex The Strouhal number from the wind speed and chimney diameter, the vortex diffusion coefficient and the diffusion width using the relationship between the Strouhal number and the Reynolds number, By means of numerical analysis using the image of the direction of smoke emission from the bump, the means for decomposing the diffusion width into a horizontal component and a vertical component, the horizontal component of the diffusion width and the vertical component of the diffusion width, weather conditions, and dust conditions It functions as a means for simulating the diffusion of dust.

  According to the present invention, since the simulation accuracy of the diffusion of dust into the atmosphere can be improved, the action of measures for suppressing the diffusion of dust can be executed quickly, and the environment for suppressing the amount of dust that diffuses in the surrounding area, etc. Improvement can be promoted.

Preferred embodiments of the present invention will be described below with reference to the accompanying drawings.
FIG. 1 shows a functional configuration of a dust diffusion simulation apparatus for determining the diffusion of dust into the atmosphere in the present embodiment. Connected to the atmospheric diffusion simulation apparatus 100 is a camera 200 for continuously recording time-series images of smoke from a chimney existing in the measurement target area at regular time intervals. Although only one camera 200 is shown in FIG. 1, a plurality of cameras may be provided. FIG. 2 shows a flowchart of a dust diffusion simulation method for dust in the present embodiment for obtaining diffusion of dust into the atmosphere.

  The recording unit 101 continuously records time-series images of smoke from a chimney existing in the measurement target area at regular time intervals using one or more stationary cameras 200 (step S101 in FIG. 2).

  The power spectrum calculation unit 102 Fourier-transforms the luminance in the time direction at the same pixel coordinates of the continuous image to obtain a time series of the power spectrum of the screen (step S102 in FIG. 2).

  The vibration frequency calculation unit 103 obtains the power spectrum of the isotropic turbulent flow from the power spectrum of the screen, and obtains the vibration frequency caused by the Karman vortex from the difference between the power spectrum of the screen and the power spectrum of the isotropic turbulent flow (FIG. 2). Step S103).

  The eddy diffusion counting / diffusion width calculation unit 104 obtains the Strouhal number from the vibration frequency due to Karman vortex, the wind speed, and the chimney diameter, and obtains the eddy diffusion coefficient and the diffusion width using the relationship between the Strouhal number and the Reynolds number ( Step S104 in FIG.

  The diffusion width decomposition unit 105 decomposes the diffusion width into a horizontal component and a vertical component using an image in the direction of smoke emission from the chimney (step S105 in FIG. 2).

  The simulation unit 106 simulates the diffusion of dust by numerical analysis using the horizontal component of the diffusion width, the vertical component of the diffusion width, the weather condition, and the dust condition (step S106 in FIG. 2).

  As shown in FIG. 3, since the smoke image from the chimney changes with time, the time series image of the smoke from the chimney existing in the measurement target area is displayed at fixed time intervals using one or more stationary cameras 200. To record continuously. FIG. 3 shows a photograph taken by the camera 200.

As shown in FIGS. 4A and 4B, luminance p (x, y, i) in the time direction at the same pixel coordinates (x, y) of the continuous image (time-series image) 2 (i = 0, 2,..., 2N-1) is Fourier-transformed using equation (1) to obtain the power spectrum E _{P of the} screen. 2N is the number of integrated images, and Δt is a time step. In FIG. 4A, 3 represents a time series of luminances in the time direction of the same pixel coordinates of a continuous image.

When the relationship between the power spectrum E _{P of the} screen and the frequency f is a logarithmic graph, it is as shown in FIG. 5, and the power spectrum E _{P of the} screen decreases downward. The power spectrum E _T of isotropic turbulence is proportional to the frequency f raised to the power of T (constant) and a (constant), and is expressed by the equation (2). As shown in FIG. 5, a straight line in contact with the lower side of the curve of the power spectrum E _P of the screen is obtained, and constants T and a are obtained from the slope of the straight line and arbitrary points on the straight line. By subtracting the power spectrum E _T of isotropic turbulent flow from the power spectrum E _{P of the} screen, the dominant frequency (the peak frequency in the distribution) is obtained. As shown in equation (3), let E ₁ be the difference between the power spectrum E _{P of the} screen and the power spectrum E _T of isotropic turbulent flow, and E ₁ is the peak frequency of the E ₁ distribution. the frequency showing the maximum value and the dominant frequency f _O of the power spectrum of the fluidic oscillator, the dominant frequency f _O of the power spectrum of the fluid vibration and the vibration frequency f of the Karman vortex caused.

  The Strouhal number St is defined by the equation (4), and is obtained from the vibration frequency f caused by the Karman vortex, the wind speed u of the wind blowing toward the chimney, and the chimney diameter D. The Strouhal number St and the Reynolds number Re are approximated by an approximate expression (b is a constant) shown in the equation (5), and the Reynolds number Re is obtained from this equation. The vortex diffusion coefficient Κ and the Reynolds number Re have a relationship shown in the equation (6), and the vortex diffusion coefficient Κ is obtained. Between the diffusion coefficient K and the diffusion width σ, there is a relationship of the expression (7), and the diffusion width σ is obtained.

In order to simulate the diffusion of dust, it is necessary to decompose the diffusion width σ into its horizontal component σy and vertical component σz. As shown in FIGS. 12 (a) and 12 (b), the combined result of the horizontal diffusion and vertical diffusion of the powder is considered to be the ejection direction of the smoke image. When V is ev, the vertical unit vector is ev, the horizontal unit vector is eh, the diffusion width σ, the horizontal component of the diffusion width σ is σy, and the vertical component of the diffusion width σ is σz, the diffusion width is expressed by Equations (8) and (9). σ can be obtained. In FIG. 12, 1 represents a chimney. FIG. 12B shows a photograph taken by the camera 200.
σy = σ (V · eh) (8)
σz = σ (V · ev) (9)

  Dust diffusion distribution is obtained by numerical analysis from the obtained diffusion width σ and the measured dust diffusion amount and weather conditions. In this way, it was possible to provide an apparatus for directly calculating the relationship between the diffusion coefficient from the observation value of the weather condition and the time-series image of the smoke from the chimney. As a result, the relationship between the observed values of the weather conditions and the diffusion width is determined more finely and quantitatively than the seven-level atmospheric stability category, and it has become possible to improve the simulation accuracy of the diffusion of dust into the atmosphere. .

(Example)
An embodiment of the present invention will be described with reference to FIGS. 3 and 5 to 11. First, using one or more cameras in which time-series images of smoke from a chimney existing in the calculation target area are placed, recording is continuously performed at regular time intervals as shown in FIG.

The luminance in the time direction at the same pixel coordinates of the continuous image is Fourier-transformed using equation (1) to obtain a screen power spectrum E _P as shown in FIG. Here, the time increment Δt = 1 second and the number of integrated images 2N = 64.

In order to obtain the dominant frequency of the power spectrum of fluid vibration, the difference E ₁ between the power spectrum E _{P of the} screen and the power spectrum E _T of isotropic turbulence is obtained. The power spectrum E _T of the isotropic turbulent flow is obtained by examining the slope T of the log-log graph with the frequency of the power spectrum E _P of the screen, and T = −1. The power spectrum E _T of isotropic turbulence is considered to be proportional to the frequency −1 to the first power, and is expressed by equation (2), where a is a constant. The difference E ₁ between the power spectrum E _{P of the} screen represented by the expression (3) and the power spectrum E _T of isotropic turbulence indicates the power spectrum of the fluid vibration, and indicates the maximum value of the distribution of E _1. frequency peak is dominant frequency, the dominant frequency f _O of the power spectrum of the fluid vibration and the vibration frequency f of the Karman vortex caused.

  From the vibration frequency f caused by Karman vortex shown in FIG. 7, the wind speed u of the wind blowing toward the chimney shown in FIG. 6, and the chimney diameter D using the equation (4), the Strouhal number shown in FIG. Obtain the time series of St.

  Between the Strouhal number St and the Reynolds number Re, there is a relational expression of a curve as shown in FIG. 9, but this apparatus approximates a straight line as shown in FIG. The Reynolds number Re is obtained from the equation (5), and the eddy diffusion coefficient K shown in FIG. 10 is obtained using the equation (6). The diffusion width σ is obtained from the equation (7), and the diffusion width σ is decomposed into its horizontal component σy and vertical component σz using the direction of ejection of the smoke image as shown in FIG.

  Dust diffusion distribution is obtained by numerical analysis from the obtained diffusion width σ and the measured dust diffusion amount and weather conditions.

  FIG. 11 shows the vertical component of the diffusion width at a point of 100 mm from the dust source determined by the method using the present invention and the conventional Pasquill-Gifford diagram. FIG. 11 is a characteristic diagram showing the relationship between time and vertical diffusion width. The results according to the present invention show changes over time, and the results with the conventional apparatus show results when the Pasquill stability stage classification is C, D, E, F. When both are compared, the values are in the same order, but it can be seen that the values change continuously in time series in the present invention, whereas they change discretely in the conventional method.

  Since the present invention obtains the diffusion width directly from the observation value of the weather condition and the time-series image of the smoke from the chimney, the relationship between the observation value of the weather condition and the diffusion coefficient is finer than the conventional method of seven stages, and becomes high accuracy, In addition, the cost can be reduced.

  FIG. 13 shows a hardware configuration example of a computer that can function as the atmospheric diffusion simulation apparatus of the present invention. The computer includes a CPU 51 that is a central processing unit that controls the entire apparatus, a display unit 52 that displays various input conditions, analysis results, and the like, and a storage unit 53 such as a hard disk that stores analysis results and the like. Further, it has a ROM (Read Only Memory) 54 for storing a control program, various application programs, data and the like. The CPU 51 includes a RAM (Random Access Memory) 55 which is a work area used when the CPU 51 performs processing while controlling each unit based on the control program, and an input unit 56 such as a keyboard and a mouse.

  The object of the present invention can also be achieved by supplying a storage medium storing software program codes for realizing the functions of the above-described embodiments to a system or apparatus. In this case, the computer (or CPU or MPU) of the system or apparatus reads and executes the program code stored in the storage medium.

  In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the program code itself and the storage medium storing the program code constitute the present invention. As a storage medium for supplying the program code, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

It is a figure which shows the function structure of the atmospheric diffusion simulation apparatus of the dust for calculating | requiring the spreading | diffusion of the dust in air | atmosphere in this embodiment. It is a flowchart of the atmospheric | air-diffusion simulation method of the dust for calculating | requiring the spreading | diffusion of the dust in air | atmosphere in this embodiment. It is a figure which shows the time-sequential image of the smoke from a chimney. It is a diagram for explaining how to determine the power spectrum E _P of the screen, a diagram, (b) is a characteristic diagram showing the concept of a continuous image (a). It is a characteristic view which shows the relationship between the power spectrum E _{P of the} screen and the frequency f. It is a characteristic view which shows the time series of the wind speed u of the wind which blows toward a chimney. It is a characteristic view which shows the time series of the vibration frequency f resulting from Karman vortex. It is a characteristic view which shows the time series of the Strouhal number St. It is a characteristic view which shows the relationship between Strouhal number St and Reynolds number Re. It is a characteristic view showing a time series of the eddy diffusion coefficient K. It is a figure for demonstrating the comparison with this invention and the conventional method, and is a characteristic view which shows the time series of a perpendicular | vertical diffusion width. It is a figure for demonstrating decomposition | disassembly into the horizontal component of (sigma) y and the vertical component (sigma) z of the spreading | diffusion width (sigma), (a) is the relationship between the unit vector V of the advancing direction of smoke, the vertical unit vector ev, and the horizontal unit vector eh. FIG. 4B is a diagram showing an image of smoke generated from the chimney. It is a figure which shows the hardware structural example of the computer which can function as an atmospheric diffusion simulation apparatus of this invention. It is a figure for demonstrating the atmospheric diffusion simulation by the method using the Pasquill-Gifford diagram. It is a characteristic figure of the horizontal component of the diffusion width in a Pasquill-Gifford diagram. It is a characteristic view of the vertical component of the diffusion width in the Pasquill-Gifford diagram.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Recording part 102 Power spectrum calculating part 103 Vibration frequency calculating part 104 Eddy diffusion count / diffusion width calculating part 105 Diffusion width decomposing part 106 Simulation part

Claims (3)

An apparatus for simulating the diffusion of dust into the atmosphere to determine the diffusion of dust into the atmosphere,
Means for continuously recording time-series images of smoke from a chimney existing in the measurement target area at fixed time intervals using one or more stationary cameras;
Means for Fourier transforming the luminance in the time direction at the same pixel coordinates of the continuous image to obtain a time series of the power spectrum of the screen;
A means for obtaining a power spectrum of isotropic turbulence from the power spectrum of the screen, and obtaining a vibration frequency caused by the Karman vortex from a difference between the power spectrum of the screen and the power spectrum of the isotropic turbulence;
A means for obtaining the Strouhal number from the vibration frequency and wind speed caused by the Karman vortex and the diameter of the chimney, and obtaining the eddy diffusion coefficient and the diffusion width using the relationship between the Strouhal number and the Reynolds number,
Means for decomposing the diffusion width into a horizontal component and a vertical component using an image of the direction of smoke emission from the chimney;
An apparatus for simulating the diffusion of dust in the atmosphere, comprising means for simulating the diffusion of dust by numerical analysis using a horizontal component of the diffusion width, a vertical component of the diffusion width, weather conditions, and dust conditions. A method for simulating the diffusion of dust into the atmosphere to determine the diffusion of dust into the atmosphere,
Using a fixed one or more cameras, continuously recording a time-series image of smoke from a chimney existing in a measurement target area at regular time intervals;
Fourier transforming the luminance in the time direction at the same pixel coordinates of the continuous image to obtain a time series of the power spectrum of the screen;
Obtaining a power spectrum of isotropic turbulence from the power spectrum of the screen, obtaining a vibration frequency caused by the Karman vortex from the difference between the power spectrum of the screen and the power spectrum of the isotropic turbulence;
Obtaining the Strouhal number from the vibration frequency, wind speed and chimney diameter caused by the Karman vortex, obtaining the vortex diffusion coefficient and diffusion width using the relationship between the Strouhal number and the Reynolds number;
Decomposing the diffusion width into a horizontal component and a vertical component using an image of the direction of smoke emission from the chimney;
A method for simulating the diffusion of dust in the atmosphere, comprising the step of simulating the diffusion of dust by numerical analysis using a horizontal component of the diffusion width, a vertical component of the diffusion width, weather conditions, and dust conditions. A program for simulating the diffusion of dust into the atmosphere to determine the diffusion of dust into the atmosphere,
Computer
Means for continuously recording time-series images of smoke from a chimney existing in the measurement target area at fixed time intervals using one or more stationary cameras;
Means for Fourier transforming the luminance in the time direction at the same pixel coordinates of the continuous image to obtain a time series of the power spectrum of the screen;
A means for obtaining a power spectrum of isotropic turbulence from the power spectrum of the screen, and obtaining a vibration frequency caused by the Karman vortex from a difference between the power spectrum of the screen and the power spectrum of the isotropic turbulence;
A means for obtaining the Strouhal number from the vibration frequency and wind speed caused by the Karman vortex and the diameter of the chimney, and obtaining the eddy diffusion coefficient and the diffusion width using the relationship between the Strouhal number and the Reynolds number,
Means for decomposing the diffusion width into a horizontal component and a vertical component using an image of the direction of smoke emission from the chimney;
A program for functioning as a means of simulating the diffusion of dust by numerical analysis using the horizontal component of the diffusion width and the vertical component of the diffusion width, weather conditions, and dust conditions.

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