JP2009103580A - Device, method, and program for simulating diffusion of dust in atmosphere - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a device for improving simulating diffusion of dust in the atmosphere, precisely and inexpensively determining a diffusion width and a diffusion coefficient of dust. <P>SOLUTION: The device for simulating diffusion of dust includes: a unit 101 for recording time-series iamges of smoke from a chimney stack located in an object area to be observed using one or more cameras 200 stationarily placed; a unit 102 for producing power images by Fourier-transforming intensity in the time direction for each of the same pixel coordinate of the images in the time-series; a unit 103 for determining a diffusion width at a predetermined location from a relationship in arrangement of a wind direction, cameras, and smoke, by determining the location range of smoke from the power images and determining the diffusion widths on the power images from the location range of the smoke; a unit 104 for determining the diffusion width and the diffusion coefficient at the location where simulation is performed from the diffusion width at the predetermined location; and a unit 105 for simulating the diffusion of dust with numerical analysis by using the diffusion width, the diffusion coefficient, the wind direction, and the wind speed at the locations where the simulation is performed. <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 disperses dust into the atmosphere of a factory or coal storage with a chimney, It relates to what you want cheaply.

  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. 12, using the Pasquill stability stage classification table (see Table 1), the stability stage classifications A to G are obtained from the wind speed, the amount of solar radiation, and the like. Then, using the stability stage classifications A to G and the distance from the dust source, from the Pasquill-Gifford diagram (see FIGS. 13 and 14), 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, measured dust diffusion amount, wind direction, and the like.

  Furthermore, Patent Literature 2 discloses a method for monitoring smoke by image correlation analysis. Patent Document 3 discloses a smoke monitoring method using sound waves. Patent Document 4 discloses a photo measurement method using a balloon.

Japanese Patent Laid-Open No. 2-64437 JP 2002-90471 A Japanese Patent Laid-Open No. 58-13595 JP-A-8-166400

  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, in the simulation method disclosed in Patent Document 1, there are only seven stages of Pasquill stability stage classification obtained from observed values of weather conditions, and there are cases where it does 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.

  Furthermore, in the method for monitoring smoke by the correlation analysis between images disclosed in Patent Document 2, a diffusion coefficient cannot be obtained and a dust diffusion simulation cannot be performed. Even with the smoke monitoring method using sound waves disclosed in Patent Document 3 and the photo measurement method using a balloon disclosed in Patent Document 4, a diffusion coefficient cannot be obtained, dust diffusion simulation cannot be performed, and the cost Becomes higher.

  The present invention has been made in view of the above points, so that the diffusion width and diffusion coefficient of dust in the atmosphere can be obtained accurately and at low cost, and the simulation accuracy of the diffusion of dust into the atmosphere is improved. The purpose is to let you.

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 an observation target area using one or more stationary cameras. Means for recording a time-series image of smoke from the chimney, means for generating a power image by Fourier-transforming the luminance in the time direction for each identical pixel coordinate of the time-series image, and a range of smoke from the power image And calculating a diffusion width on the power image from the smoke existing range, obtaining a diffusion width at a predetermined point from a wind direction and a positional relationship between the camera and smoke, and a simulation from the diffusion width at the predetermined point The means for obtaining the diffusion width and diffusion coefficient at the point where the simulation is performed, and the powder by numerical analysis using at least the diffusion width, the diffusion coefficient, the wind direction and the wind speed at the point where the simulation is performed Characterized by comprising a means for simulating the diffusion.
The method for simulating the diffusion of dust in the atmosphere according to 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 observation target area using one or more stationary cameras. Recording a time-series image of smoke from the chimney, generating a power image by Fourier transforming the luminance in the time direction for each identical pixel coordinate of the time-series image, and a range of smoke from the power image Obtaining a diffusion width on the power image from the smoke existing range, obtaining a diffusion width at a predetermined point from the wind direction and the arrangement relationship between the camera and smoke, and a simulation from the diffusion width at the predetermined point And at least using the diffusion width, diffusion coefficient, wind direction, and wind speed at the point where the simulation is performed. Characterized by a step of simulating the diffusion of dust by the value analysis.
The program of the present invention is a program for performing a simulation of dust diffusion in the atmosphere for determining the diffusion of dust into the atmosphere, and using one or more stationary cameras, a chimney existing in the observation target area Means for recording a time-series image of smoke from the image, means for generating a power image by Fourier transforming the luminance in the time direction for each identical pixel coordinate of the time-series image, and determining the smoke presence range from the power image , A means for obtaining a diffusion width on the power image from the smoke presence range, obtaining a diffusion width at a predetermined point from the wind direction and the relationship between the camera and smoke, and a simulation from the diffusion width at the predetermined point Diffusion of dust by numerical analysis using at least the diffusion width, diffusion coefficient, wind direction, and wind speed at the point where the simulation is carried out Causing a computer to function as simulation means.

  ADVANTAGE OF THE INVENTION According to this invention, the diffusion width and diffusion coefficient in the atmosphere of dust can be calculated | required accurately and at low cost, and the precision of the diffusion simulation to the atmosphere of dust can be improved. Thereby, the action of the countermeasure for suppressing dust diffusion can be executed quickly, and environmental improvement such as suppression of the amount of dust diffusing in the surrounding area 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 recording a time-series image (continuous image) of smoke from a chimney existing in the observation target area. 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 records a time-series image of smoke from a chimney existing in the observation target area using one or more cameras 200 that are stationary (step S101 in FIG. 2). Here, images obtained by photographing smoke from the chimney are continuously recorded at a predetermined time interval (for example, a constant time interval).

  The power image generation unit 102 generates a power image by performing Fourier transform on the luminance in the time direction for each identical pixel coordinate of the time-series image recorded by the recording unit 101 (step S102 in FIG. 2).

  The diffusion width calculation unit 103 obtains the smoke existence range from the power image generated by the power image generation unit 102, obtains the diffusion width on the power image from the smoke existence range, and arranges the wind direction, the camera 200, and the smoke 2 to obtain the diffusion width at the observation point (predetermined point) (step S103 in FIG. 2).

  The diffusion width / diffusion coefficient computing unit 104 obtains the diffusion width and the diffusion coefficient at the point (arbitrary point) where the simulation is performed from the diffusion width at the observation point obtained by the diffusion width computing unit 103 (step in FIG. 2). S104).

  The simulation unit 105 numerically uses the diffusion width, diffusion coefficient, wind direction, wind speed, dust generation intensity, and position information of the dust generation intensity measurement point at the point where the simulation is performed, which is obtained by the diffusion width / diffusion coefficient calculation unit 104. Dust diffusion is simulated by analysis (step S105 in FIG. 2).

  Hereinafter, the details of the above steps will be described. As shown in FIG. 3, since the image of the smoke from the chimney changes with time, the time series image of the smoke from the chimney existing in the observation target area is recorded using one or more stationary cameras 200. FIG. 3 illustrates a time-series image (photograph) taken by the camera 200.

As shown in FIG. 4, the luminance p (x, y, i) in the time direction at the same pixel coordinate (x, y) of the time series image 1 is Fourier-transformed using the equation (1), and the pixel coordinate is obtained. The power E _p (x, y) at (x, y) is obtained. 2N is the number of integral images. i is a number of continuous images, and is set to 0 to 2N-1. In FIG. 4, 2 represents a time series of luminances in the time direction of the same pixel coordinates of the continuous image.

A power image is defined as the power E _p (x, y) at pixel coordinates (x, y) displayed on the screen. FIG. 5 is a diagram for explaining an observation method of the diffusion width σi on the power image. FIG. 5 illustrates the image displayed on the screen. FIG. 6 is a plan view showing the positional relationship between the camera 200, the chimney, and the observation point m when the wind direction is known. The power E _p (x, y) at the pixel coordinates (x, y) differs greatly except for smoke and smoke, and here, the maximum value of the power E _p (x, y) at the pixel coordinates (x, y). The range of 1/10 or more of the smoke is the smoke presence range.

  The smoke width obtained as described above is measured and set as the diffusion width σi on the power image. When the wind direction is known, as shown in FIG. 6, the actual distance b from the camera 200 to the observation point m from the wind direction, the actual distance X ′ from the chimney to the observation point m, the actual distance a from the camera 200 to the chimney, and b. Can be calculated. In FIG. 5, using a reference length (for example, a known chimney height) L, an observation point m is considered in consideration of the scale from the reference length Li on the power image and the diffusion width σi on the power image. The diffusion width σz ′ at is obtained from equation (2). And it converts into diffusion width (sigma) z in the point which implements simulation by (3) Formula. Further, the diffusion coefficient K is obtained by the equation (4). Note that u is the wind speed of the wind blowing toward the chimney.

  Numerical analysis using the diffusion width σz, the diffusion coefficient K, the wind direction, the wind speed u, the measured dust intensity (dust diffusion amount), and the position information of the dust intensity observation point at the point where the simulation is obtained in this way. By simulating the diffusion distribution of dust.

  As described above, the relationship between the diffusion coefficient can be directly obtained 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 observation value of the weather condition and the diffusion width is determined more finely and quantitatively than the seven-stage atmospheric stability category, and it becomes possible to improve the simulation accuracy of the diffusion of dust into the atmosphere.

(Example)
Examples of the present invention will be described. First, a time series image of smoke from a chimney existing in the observation target area is recorded using one or more stationary cameras 200. Then, the luminance p (x, y, i) in the time direction at the same pixel coordinate (x, y) of the time series image is Fourier transformed using the equation (1), and the pixel coordinate (x, y) is used. Power E _p (x, y) is obtained, and a power image is obtained as shown in FIG. FIG. 7 illustrates the image displayed on the screen. Here, the time increment was 1 second, and the number of integrated images was 2N = 256.

  When the wind velocity u changes as shown in FIG. 9 as shown in FIG. 8 and the wind speed u changes as shown in FIG. 9, if the diffusion width observation direction is determined to be one direction in the leeward direction of smoke, the predetermined point becomes m point in FIG. If the reference length L = 30 m and the actual distance a = 100 m from the camera 200 to the chimney (see FIG. 6) and the like are checked in advance, the actual distance X ′ from the chimney to the observation point m will be described with reference to FIG. The actual distance b from the camera 200 to the observation point m can be obtained uniquely.

  In FIG. 5, using the reference length L, the diffusion width σz ′ at the observation point m is obtained by the equation (2) in consideration of the scale from the photograph. Then, it is converted into a diffusion width σz with X = 100 [m] or the like in the equation (3). Further, the diffusion coefficient K is obtained by the equation (4).

  FIG. 10 shows a time series of the diffusion width at a point of 100 mm from the dust generation source (chimney) obtained by the method to which the present invention is applied, and compared with the order of the diffusion width in the conventional Pasquill-Gifford diagram. When both are compared, the values are in the same order. However, it can be seen that the conventional method changes discretely, whereas the method to which the present invention is applied continuously changes in time series. This result also shows that the relationship between the observed values of the weather conditions and the diffusion width is more detailed and quantitative than the seven-step atmospheric stability category, and it is possible to improve the accuracy of the dust diffusion simulation into the atmosphere. .

  FIG. 11 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 in this embodiment. It is a flowchart of the atmospheric diffusion simulation method of dust in this embodiment. It is a figure which shows the time-sequential image of the smoke from a chimney. It is a figure which shows the concept of a time series image. It is a figure for demonstrating the observation method of the diffusion width (sigma) i on a power image. It is a top view which shows the arrangement | positioning relationship of a camera, a chimney, and an observation point when a wind direction is known. It is a figure which shows the example of a power image. 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 figure which shows the change of a wind direction. 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 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 100 Atmospheric diffusion simulation apparatus 101 Recording part 102 Power image generation part 103 Diffusion width calculating part 104 Diffusion width / diffusion coefficient calculating part 105 Simulation part 200 Camera

Claims (3)

An apparatus for simulating the diffusion of dust into the atmosphere to determine the diffusion of dust into the atmosphere,
Means for recording a time-series image of smoke from a chimney existing in the observation area using one or more stationary cameras;
Means for generating a power image by Fourier transforming the luminance in the time direction for each identical pixel coordinate of the time series image;
Means for obtaining a smoke existing range from the power image, obtaining a diffusion width on the power image from the smoke existing range, and obtaining a diffusion width at a predetermined point from a wind direction, a camera and smoke arrangement relationship;
Means for obtaining a diffusion width and a diffusion coefficient at a point where the simulation is performed from the diffusion width at the predetermined point;
An apparatus for simulating the diffusion of dust in the atmosphere, comprising: means for simulating the diffusion of dust by numerical analysis using at least a diffusion width, a diffusion coefficient, a wind direction, and a wind speed at a point where the simulation is performed. A method for simulating the diffusion of dust into the atmosphere to determine the diffusion of dust into the atmosphere,
Recording a time-series image of smoke from a chimney present in the observation area using one or more stationary cameras;
Generating a power image by Fourier transforming the luminance in the time direction for each identical pixel coordinate of the time-series image;
Obtaining a smoke presence range from the power image, obtaining a diffusion width on the power image from the smoke existence range, obtaining a diffusion width at a predetermined point from a wind direction and a camera and smoke arrangement relationship;
Obtaining a diffusion width and a diffusion coefficient at a point where the simulation is performed from a diffusion width at the predetermined point;
And simulating the diffusion of dust by numerical analysis using at least a diffusion width, a diffusion coefficient, a wind direction, and a wind speed at a point where the simulation is performed. A program for simulating the diffusion of dust into the atmosphere to determine the diffusion of dust into the atmosphere,
Means for recording a time-series image of smoke from a chimney existing in the observation area using one or more stationary cameras;
Means for generating a power image by Fourier transforming the luminance in the time direction for each identical pixel coordinate of the time series image;
Means for obtaining a smoke existing range from the power image, obtaining a diffusion width on the power image from the smoke existing range, and obtaining a diffusion width at a predetermined point from a wind direction, a camera and smoke arrangement relationship;
Means for obtaining a diffusion width and a diffusion coefficient at a point where the simulation is performed from the diffusion width at the predetermined point;
A program for causing a computer to function as means for simulating dust diffusion by numerical analysis using at least a diffusion width, a diffusion coefficient, a wind direction, and a wind speed at a point where the simulation is performed.

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