A method for online monitoring of environmental dust based on image denoising

Abstract

The present invention discloses an online monitoring method for environmental dust based on image denoising, and relates to the technical field of dust monitoring. The present invention includes a processing unit, a background layer, a mobile terminal, a wireless module and a visual terminal, the visual terminal includes a controller, a rotating device, a brightness sensor, a camera, a fill light module and a distance measurement module, the brightness sensor obtains brightness information and transmits it to the controller, the controller sends a fill light instruction to the fill light module, the fill light module starts to fill light, the controller sends a distance measurement instruction to the distance measurement module, the distance measurement module obtains the distance information between the camera and the background layer position and feeds back to the controller, the controller sends a steering instruction to the camera, and the camera rotates along the vertical direction of the background layer. The present invention realizes low-cost construction investment by installing a visual terminal in a tunnel, and is conducive to identifying dust in an image by setting a background layer and adjusting the focal length of the camera.

Description

Technical Field

[0001] The invention relates to the technical field of dust monitoring, and in particular to an environmental dust online monitoring method based on image denoising. Background Art

[0002] Tunnel dust monitoring is to ensure the air quality during tunnel construction and operation, prevent dust from harming the health of construction workers, and also to ensure visibility in the tunnel and avoid safety accidents caused by obstructed vision. Tunnel dust mainly comes from drilling, blasting, slag loading, concrete spraying and other operations during construction. These activities will generate a lot of dust. If not controlled and monitored, it will have a serious impact on the environment in the tunnel. In actual application, tunnel dust monitoring technology mainly includes the use of dust detectors for real-time monitoring, which are deployed and fixed in the tunnel. The dust detector uses a light scattering dust sensor based on the principle of light scattering to measure the total dust and respirable dust concentration. It is usually equipped with an exhaust system and data processing technology, which can convert dust concentration into numbers within a certain range and display it in real time on a display screen.

[0003] Dust monitors rely on light scattering dust sensors or dust concentration sensors. The cost of deploying monitoring equipment in every area of ​​the tunnel is too high. Dust monitoring equipment based on image analysis technology can greatly reduce the construction investment cost in the tunnel and is more conducive to the economy of project construction. However, the current image analysis technology is not perfect. The dark light environment in the tunnel will cause many noise points when collecting image information. Too much noise points will affect the analysis results of the dust environment in the tunnel. Therefore, using image denoising to analyze the dust environment in the tunnel without increasing additional construction investment is a technical problem that technical personnel in this field need to solve. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an online monitoring method for environmental dust based on image denoising, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an online monitoring method for environmental dust based on image denoising, which is implemented based on a processing unit, a background layer, a mobile terminal, a wireless module and a visual terminal, wherein the visual terminal includes a controller, a rotating device, a brightness sensor, a camera, a fill light module and a distance measurement module, wherein the brightness sensor obtains brightness information of the area where the visual terminal is located and transmits it to the controller, the controller sends a fill light instruction to the fill light module, the fill light module starts to fill light the area where the visual terminal is located, the controller sends a distance measurement instruction to the distance measurement module, the distance measurement module obtains the distance information between the camera and the intersection position of the camera facing the background layer and feeds it back to the controller, the controller sends a steering instruction to the camera, the camera rotates in the vertical direction along the background layer, and the camera obtains image information and transmits it to the controller;

[0006] The controller transmits the obtained brightness information, distance information and image information to the processing unit through the wireless module, and the processing unit analyzes and processes the brightness information, distance information and image information to obtain the dust condition of the environment in the area where the visual terminal is located, and the mobile terminal establishes a data connection with the processing unit through the wireless module;

[0007] The camera, brightness sensor, fill light module, and ranging module are all fixed to one side of the rotating device, and the controller is fixed to the other side of the rotating device. The rotating device is arranged on one side of the top symmetry line in the tunnel. The background layer is a long strip structure, and the background layer is arranged on the other side of the top symmetry line in the tunnel. The background layer extends downward from the top symmetry line of the inner surface of the tunnel to the angle between the wall and the ground.

[0008] The following steps are involved:

[0009] Step 1: Measure, deploy and install. Measure the parameters of the monitoring area in the tunnel. Use a mobile terminal to upload the parameter data to the processing unit. The processing unit determines the number of visual terminals and the installation point interval according to the received parameter data and sends them to the mobile terminal. The processing unit also determines the background layer width and sends it to the mobile terminal. The construction personnel install the visual module and background layer according to the data received by the mobile terminal.

[0010] Step 2: Brightness analysis, the controller sends a rotation command to the rotating device, and the rotating device rotates on one side to drive the brightness sensor to rotate intermittently. The rotation area is from the visual terminal to the top to the bottom of the background layer. Each rotation angle is one degree, and it stays for 300 milliseconds after each rotation is completed. The brightness sensor obtains the brightness information corresponding to the rotation angle in the interval between each rotation stop and transmits it to the controller, and the controller calculates the brightness average of all angles;

[0011] Step 3: Initial distance measurement, the controller sends a rotation command to the rotating device again, and one side of the rotating device rotates in the opposite direction to drive the distance measurement module to rotate intermittently. The rotation area is from the bottom to the top of the background layer toward the visual terminal, and the rotation angle is half a degree each time. After each rotation is completed, it stays for 500 milliseconds. The distance measurement module obtains the distance information of the intersection of the camera direction and the background layer in the interval between each rotation stop, and the distance measurement module transmits the obtained distance information to the controller;

[0012] Step 4: Analyze the rotation angle. The controller calculates and analyzes the equivalent space in the area where the visual terminal is located, and calculates the angle information that the camera needs to rotate according to the equivalent space;

[0013] Step 5: ranging, focusing, and filling-in-light shooting. The controller executes a filling-in-light camera program. The controller controls the filling-in-light module to fill in the light of the area where the visual terminal is located. The camera focal length is adjusted according to the distance information obtained by the ranging module. The camera obtains image information and transmits it to the controller. The controller transmits the obtained image information to the processing unit through the wireless module. Focusing can improve the clarity of the image information obtained by the camera and reduce the probability of image noise.

[0014] Step 6: Image denoising analysis. The processing unit executes a denoising program to denoise the image information of each equivalent space in each visual terminal. The processing unit comprehensively analyzes the denoised image information of each visual terminal to obtain the dust density of each turning area and straight area in the tunnel. When the dust density exceeds a preset threshold, the processing unit pushes an alarm message to the mobile terminal of the construction personnel through the wireless module to monitor the dust in the tunnel.

[0015] Furthermore, the specific steps of the deployment and installation are as follows:

[0016] Step 11: Manual measurement: Construction workers use a tape measure to measure the total length L of the tunnel in the dust monitoring area and the height of the tunnel at the same time. , tunnel width w and tunnel top radius , construction workers use theodolite to measure the deflection angle of each turning area of ​​the tunnel and the length of the centerline of the turning area ,The arc top radius can be obtained by calculation, that is, the tunnel width is divided by two, and the construction personnel manually record the measured values;

[0017] Step 12: Manually input parameters. Construction personnel use mobile terminals to manually input the total length L of the tunnel and the height of the tunnel. , tunnel width w, tunnel top radius , deflection angle and the length of the centerline of the turning area In the input processing unit, the construction personnel mark each turning area with a number through the mobile terminal, and the mark number is transmitted to the processing unit through the wireless module;

[0018] Step 13: Calculate the number of visual terminal deployments and installation spacing, and the processing unit uses the formula Calculate the curvature C of each turning area of ​​the tunnel;

[0019] The processing unit is based on the formula Calculate the number of visual terminals deployed in each turning area ,in and is the weight coefficient, and the specific value is determined according to the actual flatness of the inner wall of the tunnel and the difficulty of construction. The processing unit is based on the number of visual terminals deployed in the turning area. Calculate the installation spacing q of the visual terminals in the corresponding turning area, and the processing unit deploys the number of visual terminals in each turning area , the installation spacing q and the marking number correspond one to one;

[0020] The processing unit is based on the formula Calculate the number of visual terminals deployed in the straight area of ​​the tunnel without turning The processing unit deploys the number of visual terminals in the straight area And the number of visual terminals deployed in all tunnel turning areas The total number is accumulated to get the number of visual terminals that need to be deployed in the tunnel as a whole , in the formula The length of the centerline of all tunnel turning areas The sum of It is represented as the straight tunnel length excluding all turning areas in the tunnel. The processing unit is based on the number of visual terminals deployed in the straight area. Calculate the installation spacing e of the visual terminals in the straight line area;

[0021] Step 14: Calculate the background layer width. The background layer width in the straight area of ​​the tunnel is a constant. The processing unit divides the tunnel width w by the number of visual terminals deployed in the straight area. Get the background layer width value of the straight line area;

[0022] In different turning areas in the tunnel, the processing unit calculates the curvature degree C and the number of visual terminals deployed in each turning area. The product of the background layer width of the turning area, the curvature C and the number of visual terminals deployed in the turning area are obtained. They are all proportional to the width of the background layer;

[0023] Step 15: The processing unit sets the number of visual terminals , the number of visual terminals deployed in the turning area corresponding to each marked number turning area , the corresponding installation spacing q of the visual terminals in the turning area, the installation spacing e of the visual terminals in the straight area, the background layer width value of the straight area and the background layer width value corresponding to each marked numbered turning area are transmitted to the mobile terminal through the wireless module. The construction personnel deploy and install the visual module and background layer in the tunnel according to the data received by the mobile terminal.

[0024] Furthermore, the analyzing the rotation angle specifically comprises the following steps:

[0025] Step 41: the controller sends a fill light instruction to the fill light module, the fill light module starts to fill light the area where the visual terminal is located, the brightness sensor obtains brightness information and transmits it to the controller, the controller divides the average brightness value without fill light by the brightness value after fill light, and multiplies the result by one thousandth by the cube of the average value of all distances obtained in step 3 to obtain the equivalent space value;

[0026] Step 42: the controller sends a shooting instruction to the camera, the camera acquires image information and transmits it to the controller, and the controller sends a distance measurement instruction to the distance measurement module, the distance measurement module measures the distance information between the camera and the background layer at the current angle and transmits it to the controller, and the controller calculates the width value of the background layer by combining the distance information and the image information of the background layer in the image;

[0027] Step 43: The controller divides the equivalent space value obtained in step 41 by the background layer width value to obtain the area that the camera needs to scan vertically. The controller then obtains the angle value that each equivalent space rotation device needs to rotate according to the area of ​​the camera's vertical scanning and the distance information measured at each angle.

[0028] Furthermore, the fill light camera program specifically includes the following steps:

[0029] Step 51: the controller sends a rotation instruction to the rotating device according to the angle value obtained in step 43, and the rotating device rotates on one side to drive the camera, brightness sensor, fill light module, and distance measurement module to rotate;

[0030] Step 52: In each equivalent space, when the rotation angle of the rotating device reaches half of the corresponding angle value of the equivalent space, that is, the angle bisector of the rotation angle of the equivalent space, the controller sends a distance measurement instruction to the distance measurement module, and the distance measurement module obtains the distance information between the current camera direction and the background layer and transmits it to the controller. The controller adjusts the focal length of the camera according to the received distance information so that the camera focus falls on the background layer, thereby completing the distance measurement and focusing of the camera;

[0031] Step 53: the controller sends a fill light instruction to the fill light module, and the fill light module starts to fill light the area where the visual terminal is located. At the same time, the controller controls the camera to start, and the camera captures the image information of the current angle and transmits it to the controller.

[0032] Furthermore, the noise reduction procedure specifically includes the following steps:

[0033] Step 61: The processing unit takes half of the angle value in the equivalent spatial image information as a reference, selects an area within one degree of the reference as an analysis area, and the analysis area is closest to the focus point of the camera and has the highest definition, so it is used as a reference for image information analysis. The areas corresponding to the remaining angle values ​​are divided into equal proportions according to a proportion of 5%, and the image information after division is sorted from high to low according to the grayscale value;

[0034] Step 62: The processing unit further divides the analysis area into rectangles of equal area, and classifies each divided rectangular image by calculating the histogram of the image. The processing unit randomly extracts a rectangular image from each classified category to count the number of dust particles, and assigns the statistical number of dust particles to the remaining rectangular images in the same category. The processing unit accumulates and sums the number of dust particles in all rectangular images in the analysis area, and then divides the sum by the area of ​​the analysis area to obtain the dust density corresponding to the analysis area.

[0035] Step 63: the processing unit divides the areas corresponding to the remaining angle values ​​after the segmentation into equal proportions, determines the segmentation ratio according to the sorting method in step 61, and removes noise from the sorted image by using a mean filter;

[0036] Step 64: the processing unit compares the grayscale histogram of the denoised image information with the analysis area in step 61, compares the similarity of the grayscale distribution of the images, assigns the dust density of each denoised image according to the dust density of the analysis area multiplied by the similarity ratio, counts the dust density of all image information, and completes the analysis and calculation of the dust density in a single equivalent space;

[0037] Step 65: The processing unit repeats the above steps, step 61 to step 64, until all equivalent spaces have completed analysis and calculation, and the dust density analysis of the area where a single visual terminal is located is completed.

[0038] A register is integrated into a controller and a processing unit respectively, and a computer program or instruction for execution by the controller or the processing unit is stored in the register. When the computer program or instruction is executed, the method in the above content is implemented.

[0039] The present invention has the following beneficial effects:

[0040] 1. By installing visual terminals in the tunnel, low-cost construction investment can be achieved. Combined with the fill light and denoising of image information, the computing pressure of the processing unit on image information is reduced, and dust monitoring in the tunnel can be realized simply and quickly.

[0041] 2. By setting the background layer, the contrast of dust in the image information can be improved, which is convenient for identification and statistics. By adjusting the focal length of the camera, the clarity of the image information obtained by the camera can be improved, and the noise information of the image can be further reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0043] Figure 1 A block diagram of an online environmental dust monitoring method based on image denoising according to the present invention;

[0044] Figure 2 It is a structural schematic diagram of the camera of the present invention.

[0045] In the accompanying drawings, the components represented by the reference numerals are listed as follows:

[0046] In the picture: 1- camera, 2- background layer. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] See also Figure 1-2 The present invention provides a technical solution: an online monitoring method for environmental dust based on image denoising, please refer to Figure 1, realized by a processing unit, a background layer 2, a mobile terminal, a wireless module and a visual terminal, wherein the visual terminal includes a controller, a rotating device, a brightness sensor, a camera 1, a fill light module and a distance measurement module, wherein the brightness sensor obtains brightness information of the area where the visual terminal is located and transmits it to the controller, the controller sends a fill light instruction to the fill light module, the fill light module starts to fill light the area where the visual terminal is located, the controller sends a distance measurement instruction to the distance measurement module, the distance measurement module obtains the distance information between the camera 1 and the intersection position of the camera 1 toward the background layer 2 and feeds it back to the controller, the controller sends a steering instruction to the camera 1, the camera 1 rotates toward the vertical direction along the background layer 2, and the camera 1 obtains image information and transmits it to the controller;

[0049] The controller transmits the obtained brightness information, distance information and image information to the processing unit through the wireless module. The processing unit analyzes and processes the brightness information, distance information and image information to obtain the dust condition of the environment in the area where the visual terminal is located. The mobile terminal establishes a data connection with the processing unit through the wireless module.

[0050] See also Figure 2 The camera 1, the brightness sensor, the fill light module, and the distance measurement module are all fixed on one side of the rotating device, and the controller is fixed on the other side of the rotating device. The rotating device is arranged on one side of the top symmetry line in the tunnel. The background layer 2 is a long strip structure. The background layer 2 is arranged on the other side of the top symmetry line in the tunnel. The background layer 2 extends downward from the top symmetry line of the inner surface of the tunnel to the angle between the wall and the ground. Figure 2 The arrows in the middle point to the highest and lowest points in the range of image information acquired by camera 1. Local analysis can be used to infer the overall situation. By analyzing and calculating the dust density in the area scanned by camera 1, the overall dust density in the tunnel can be intuitively determined.

[0051] The following steps are involved:

[0052] Step 1: Measure, deploy and install. Measure the parameters of the monitoring area in the tunnel. Use a mobile terminal to upload the parameter data to the processing unit. The processing unit determines the number of visual terminals and the installation point interval based on the received parameter data and sends it to the mobile terminal. The processing unit also determines the width of the background layer 2 and sends it to the mobile terminal. The construction personnel install the visual module and background layer 2 according to the data received by the mobile terminal.

[0053] Step 2: Brightness analysis. The controller sends a rotation command to the rotating device. The rotation of one side of the rotating device drives the brightness sensor to rotate intermittently. The rotation area is from the visual terminal to the top to the bottom of the background layer 2. Each rotation angle is one degree. After each rotation is completed, it stays for 300 milliseconds. The brightness sensor obtains the brightness information corresponding to the rotation angle in the interval between each rotation stop and transmits it to the controller. The controller calculates the average brightness of all angles.

[0054] Step 3: Initial distance measurement, the controller sends a rotation command to the rotating device again, and one side of the rotating device rotates in the opposite direction to drive the ranging module to rotate intermittently. The rotation area is from the bottom to the top of the visual terminal toward the background layer 2. The rotation angle is half a degree each time, and it stays for 500 milliseconds after each rotation is completed. The ranging module obtains the distance information of the intersection of the camera 1 and the background layer 2 in the interval between each rotation stop, and the ranging module transmits the obtained distance information to the controller;

[0055] Step 4: Analyze the rotation angle. The controller calculates and analyzes the equivalent space in the area where the visual terminal is located, and calculates the angle information that the camera 1 needs to rotate according to the equivalent space.

[0056] Step 5: ranging, focusing, and filling-in-light shooting. The controller executes the filling-in-light camera program. The controller controls the filling-in-light module to fill in the light of the area where the visual terminal is located. The focal length of the camera 1 is adjusted according to the distance information obtained by the ranging module. The camera 1 obtains image information and transmits it to the controller. The controller transmits the obtained image information to the processing unit through the wireless module.

[0057] Step 6: Image denoising analysis. The processing unit executes the denoising program to denoise the image information of each equivalent space in each visual terminal. The processing unit comprehensively analyzes the denoised image information of each visual terminal to obtain the dust density of each turning area and straight area in the tunnel. When the dust density exceeds the preset threshold, the processing unit pushes an alarm message to the mobile terminal of the construction personnel through the wireless module to realize the monitoring of dust in the tunnel.

[0058] The specific steps for deployment and installation are as follows:

[0059] Step 11: Manual measurement: Construction workers use a tape measure to measure the total length L of the tunnel in the dust monitoring area and the height of the tunnel at the same time. , tunnel width w and tunnel top radius , construction workers use theodolite to measure the deflection angle of each turning area of ​​the tunnel and the length of the centerline of the turning area The theodolite is an existing measuring instrument. The specific measuring steps are not repeated here. The turning area is a non-linear deflection area in the tunnel, including the up-down direction and the left-right direction. The arc top radius can be obtained by calculation, that is, the tunnel width is divided by two. The construction personnel manually record the measured values;

[0060] Step 12: Manually input parameters. Construction personnel use mobile terminals to manually input the total length L of the tunnel and the height of the tunnel. , tunnel width w, tunnel top radius , deflection angle and the length of the centerline of the turning area In the input processing unit, the construction personnel mark each turning area with a number through the mobile terminal, and the mark number is transmitted to the processing unit through the wireless module;

[0061] The mobile terminal is a handheld wireless terminal with Internet function. The construction personnel input the collected tunnel dimension data into the processing unit through the mobile terminal, and the processing unit calculates and analyzes the number of visual terminals to be deployed and the installation positions. Any wireless terminal on the market that can meet the input parameters and communication functions can be used as the mobile terminal of the construction personnel in this embodiment, and the specific model of the mobile terminal is not limited;

[0062] Step 13: Calculate the number of visual terminal deployments and installation spacing, and the processing unit according to the formula Calculate the curvature C of each turning area of ​​the tunnel;

[0063] Processing units according to the formula Calculate the number of visual terminals deployed in each turning area ,in and is the weight coefficient, and the specific value is determined according to the actual flatness of the tunnel inner wall and the difficulty of construction. The processing unit determines the number of visual terminals deployed in the turning area. Calculate the installation spacing q of the visual terminals in the corresponding turning area, and the processing unit will deploy the number of visual terminals in each turning area , the installation spacing q and the marking number correspond one to one;

[0064] It should be noted that the greater the curvature C, the smaller the area to be monitored, indicating that fewer visual terminals need to be deployed, and the greater the width w, the larger the monitoring range of the visual terminal radiation, indicating that fewer visual terminals need to be deployed, and the greater the tunnel height and the length of the centerline of the turning area The larger the value, the larger the monitoring area in the tunnel needs to be. To ensure the rationality of the monitoring data, the number of visual terminals deployed also needs to be increased.

[0065] Processing units according to the formula Calculate the number of visual terminals deployed in the straight area of ​​the tunnel without turning areas , the processing unit deploys the number of visual terminals in the straight area And the number of visual terminals deployed in all tunnel turning areas The total number is accumulated to get the number of visual terminals that need to be deployed in the tunnel. , in the formula The length of the centerline of all tunnel turning areas The sum of It is expressed as the straight tunnel length excluding all turning areas in the tunnel. The processing unit is based on the number of visual terminals deployed in the straight area. Calculate the installation spacing e of the visual terminals in the straight line area;

[0066] Step 14: Calculate the width of background layer 2. The width of the straight area of ​​background layer 2 in the tunnel is a constant. The processing unit divides the tunnel width w by the number of visual terminals deployed in the straight area. Get the width value of the background layer 2 in the straight line area;

[0067] In different turning areas in the tunnel, the processing unit calculates the degree of curvature C in each turning area and the number of visual terminals deployed in the turning area. The product of the width of the background layer 2 in the turning area, the curvature C and the number of visual terminals deployed in the turning area are obtained. They are all proportional to the width of background layer 2;

[0068] Step 15: The processing unit will be the number of visual terminals , the number of visual terminals deployed in the turning area corresponding to each marked number turning area , the corresponding installation spacing q of the visual terminals in the turning area, the installation spacing e of the visual terminals in the straight area, the width value of the background layer 2 in the straight area and the width value of the background layer 2 corresponding to each marked numbered turning area are transmitted to the mobile terminal through the wireless module. The construction personnel deploy and install the visual module and background layer 2 in the tunnel according to the data received by the mobile terminal.

[0069] The analysis of the rotation angle specifically includes the following steps:

[0070] Step 41: The controller sends a fill light instruction to the fill light module, and the fill light module starts to fill light the area where the visual terminal is located. The brightness sensor obtains brightness information and transmits it to the controller. The controller divides the average brightness value without fill light by the brightness value after fill light, and multiplies the result by one thousandth by the cube of the average value of all distances obtained in step 3 to obtain the equivalent space value;

[0071] The light in the tunnel is uneven, so it is necessary to fill the scanning area in the tunnel to avoid excessive noise information generated during image acquisition. At the same time, in order to ensure that the volume of each scanning area is the same when the camera 1 rotates and scans, it is convenient for the processing unit to use as a reference when analyzing, and the spatial variables are controlled by controlling different rotation angles;

[0072] Step 42: The controller sends a shooting instruction to the camera 1, the camera 1 obtains the image information and transmits it to the controller, at which point the controller sends a distance measurement instruction to the distance measurement module, the distance measurement module measures the distance information between the camera 1 and the background layer 2 at the current angle and transmits it to the controller, and the controller calculates the width value of the background layer 2 by combining the distance information and the image information of the background layer 2 in the image;

[0073] Step 43: The controller divides the equivalent space value obtained in step 41 by the width value of the background layer 2 to obtain the area that the camera 1 needs to scan vertically. The controller then obtains the angle value that each equivalent space rotation device needs to rotate according to the area of ​​the vertical scan of the camera 1 and the distance information measured at each angle.

[0074] The fill light camera procedure specifically includes the following steps:

[0075] Step 51: The controller sends a rotation instruction to the rotating device according to the angle value obtained in step 43, and the rotating device rotates on one side to drive the camera 1, the brightness sensor, the fill light module, and the distance measurement module to rotate;

[0076] Step 52: In each equivalent space, when the rotation angle of the rotating device reaches half of the corresponding angle value of the equivalent space, that is, the angle bisector of the rotation angle of the equivalent space, the controller sends a distance measurement instruction to the distance measurement module, and the distance measurement module obtains the distance information between the current direction of the camera 1 and the background layer 2 and transmits it to the controller. The controller adjusts the focal length of the camera 1 according to the received distance information so that the focus of the camera 1 falls on the background layer 2, and the distance measurement and focusing of the camera 1 are completed;

[0077] If the camera 1 collects too much image data, it will increase the computing pressure of the processing unit. Therefore, the space in the tunnel area is divided by an equivalent space method, and then the camera 1 focuses and shoots images at a specific angle. This image information collection method can reduce the computing pressure of the processing unit and the data transmission pressure of the wireless module, reduce the construction investment cost, and also improve the response speed of the entire monitoring system. The processing unit can monitor the dust in the tunnel environment by analyzing the dust density on the background layer 2 in the image information. The surface of the background layer 2 is frosted and has a single dark color. On the one hand, it is beneficial for the processing unit to denoise the image information, and on the other hand, it is beneficial to increase the contrast of dust in the image information, which is convenient for the processing unit to identify;

[0078] Step 53: The controller sends a fill light instruction to the fill light module, and the fill light module starts to fill light the area where the visual terminal is located. At the same time, the controller controls the camera 1 to start, and the camera 1 captures the image information of the current angle and transmits it to the controller.

[0079] The noise reduction procedure specifically includes the following steps:

[0080] Step 61: The processing unit takes half of the angle value in the equivalent space image information as the reference, selects the area within one degree of the reference as the analysis area, and divides the area corresponding to the remaining angle values ​​into equal proportions according to a proportion of 5%, and sorts the image information after segmentation from high to low according to the grayscale value;

[0081] Step 62: The processing unit further divides the analysis area into rectangles of equal area, and the processing unit classifies each divided rectangular image by calculating the histogram of the image. The processing unit randomly extracts a rectangular image from each classified category to count the number of dust particles, and assigns the statistical number of dust particles to the remaining rectangular images in the same category. The processing unit accumulates and sums the number of dust particles in all rectangular images in the analysis area, and then divides the sum by the area of ​​the analysis area to obtain the dust density corresponding to the analysis area.

[0082] The principle of image histogram technology is to traverse and count each pixel in the image, and subdivide the possible grayscale range or color range according to the set grayscale level, usually divided into 0 to 255 grayscale levels, record the number of times each specific value appears, and realize the judgment of similarity between images;

[0083] Step 63: The processing unit divides the area corresponding to the remaining angle values ​​after segmentation into equal proportions, and determines the segmentation ratio according to the sorting method in step 61. The sorting is 5%, 7%, 9%, and so on from high to low. The segmentation ratio increases by 2% for each subsequent position in the sorting. The higher the sorting position, the smaller the area segmentation ratio, which means that the image information is less denoised. The processing unit denoises the sorted image by using a mean filter.

[0084] Mean filter denoising uses the average value of pixels in the image information to replace the value of the central pixel to achieve the technical method of removing image noise;

[0085] Step 64: The processing unit compares the grayscale histogram of the denoised image information with the analysis area in step 61, compares the similarity of the grayscale distribution of the images, assigns the dust density of each denoised image according to the dust density of the analysis area multiplied by the similarity ratio, counts the dust density of all image information, and completes the analysis and calculation of the dust density in a single equivalent space;

[0086] Step 65: The processing unit repeats the above steps, step 61 to step 64, until all equivalent spaces have completed analysis and calculation, and the dust density analysis of the area where a single visual terminal is located is completed.

[0087] A register is integrated into a controller and a processing unit respectively. The register stores a computer program or instruction for execution by the controller or the processing unit. When the computer program or instruction is executed, the method in the above embodiment is implemented.

[0088] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An online monitoring method for environmental dust based on image denoising, characterized in that: The following steps are involved: Step 1: measurement, deployment and installation, measuring parameters of the monitoring area in the tunnel, using a mobile terminal to upload parameter data to a processing unit, the processing unit determines the number of visual terminals and the installation point interval based on the received parameter data and sends them to the mobile terminal, determines the width of the background layer (2), and installs the visual module and the background layer (2) according to the data received by the mobile terminal; Step 2: Brightness analysis: the controller sends a rotation command to the rotating device. The rotating device rotates on one side to drive the brightness sensor to rotate intermittently. The brightness sensor obtains brightness information during each rotation stop interval and transmits it to the controller to calculate the average brightness of all angles. Step 3: Initial distance measurement, the controller sends a rotation instruction to the rotating device again, and one side of the rotating device rotates in the opposite direction to drive the distance measurement module to rotate intermittently. The distance measurement module obtains distance information during each rotation stop interval and transmits the obtained distance information to the controller; Step 4: Analyze the rotation angle. The controller calculates and analyzes the equivalent space in the area where the visual terminal is located, and calculates the angle information that the camera (1) needs to rotate according to the equivalent space. Step 5: Distance measurement, focusing, fill-in-light shooting, executing the fill-in-light shooting program, and transmitting the obtained image information to the processing unit through the wireless module; Step 6: Image denoising analysis: the processing unit executes a denoising program to denoise the image information of each equivalent space in each visual terminal, and comprehensively analyzes the denoised image information of each visual terminal to obtain the dust density of each area in the tunnel. When the dust density exceeds a preset threshold, an alarm message is pushed to the mobile terminal to monitor the dust in the tunnel. The specific steps of the measurement deployment and installation are as follows: Step 11: Manual measurement: Use a tape measure to measure the total length L of the tunnel in the dust monitoring area and the height of the tunnel , width w and arc top radius , using a theodolite to measure the deflection angle of each turning area of ​​the tunnel and the length of the centerline of the turning area , record the measured value; Step 12: Manually input parameters and use the mobile terminal to manually record the total length L and height of the tunnel. , width w, arc top radius , deflection angle and the length of the centerline of the turning area In the input processing unit, each turning area is marked with a number through the mobile terminal, and the marked number is transmitted to the processing unit through the wireless module; Step 13: Calculate the number of visual terminal deployments and installation spacing according to the formula Calculate the curvature C of each turning area of ​​the tunnel; According to the formula Calculate the number of visual terminals deployed in each turning area ,in and is the weight coefficient, based on the number of visual terminals deployed in the turning area Calculate the installation spacing q of the visual terminals in the corresponding turning area, and the number of visual terminals deployed in each turning area , the installation spacing q and the marking number correspond one to one; According to the formula Calculate the number of visual terminals deployed in the straight area of ​​the tunnel , deploy the number of visual terminals in the straight area And the number of visual terminals deployed in all tunnel turning areas The total number is accumulated to get the number of visual terminals that need to be deployed in the tunnel as a whole , in the formula is the centerline length of all tunnel turning areas The sum of the number of visual terminals deployed in the straight area Calculate the installation spacing e of the visual terminals in the straight line area; Step 14: Calculate the width of the background layer (2), where the width of the background layer (2) in the straight area of ​​the tunnel is a constant value, and divide the tunnel width w by the number of visual terminals deployed in the straight area Get the width value of the straight line area background layer (2); In different turning areas in the tunnel, calculate the curvature degree C and the number of visual terminals deployed in each turning area. The product of gets the width value of the background layer (2) in the turning area; Step 15: The processing unit sets the number of visual terminals , the number of visual terminals deployed in the turning area corresponding to each marked number turning area , the installation spacing q of the turning area, the installation spacing e of the straight area, the width value of the background layer (2) of the straight area and the width value of the background layer (2) of each marking number in the turning area are transmitted to the mobile terminal via the wireless module, and the visual module and the background layer (2) are deployed and installed in the tunnel according to the data received by the mobile terminal; The analysis of the rotation angle specifically comprises the following steps: Step 41: the controller sends a fill light instruction to the fill light module, the fill light module starts to fill light the area where the visual terminal is located, the brightness sensor obtains brightness information and transmits it to the controller, the average brightness value without fill light is divided by the brightness value after fill light, and the result is multiplied by one thousandth by the cube of the average value of all distances obtained to obtain the equivalent space value; Step 42: the controller sends a shooting instruction to the camera (1), the camera (1) acquires image information and transmits it to the controller, and the controller then sends a distance measurement instruction to the distance measurement module, the distance measurement module measures the distance information between the camera (1) and the background layer (2) at the current angle and transmits it to the controller, and calculates the width value of the background layer (2) by combining the distance information and the image information of the background layer (2) in the image; Step 43: The controller divides the obtained equivalent space value by the width value of the background layer (2) to obtain the area that the camera (1) needs to vertically scan, and then obtains the angle value that each equivalent space rotation device needs to rotate according to the area of ​​the vertical scanning of the camera (1) and the distance information measured at each angle; The fill light camera program specifically includes the following steps: Step 51: the controller sends a rotation instruction to the rotation device according to the obtained angle value, and the rotation device rotates on one side to drive the camera (1), the brightness sensor, the fill light module, and the distance measurement module to rotate; Step 52: In each equivalent space, when the rotation angle of the rotating device reaches half of the angle value, the controller sends a distance measurement instruction to the distance measurement module, and the distance measurement module obtains the distance information between the current direction of the camera (1) and the background layer (2) and transmits it to the controller, and adjusts the focal length of the camera (1) according to the received distance information so that the focus of the camera (1) falls on the background layer (2), thereby completing the distance measurement and focusing of the camera (1); Step 53: the controller sends a fill light instruction to the fill light module, and the fill light module starts to fill light the area where the visual terminal is located. At the same time, the controller controls the camera (1) to start, and the camera (1) captures image information of the current angle and transmits it to the controller; The noise reduction procedure specifically includes the following steps: Step 61: The processing unit takes half of the angle value in the equivalent space image information as a reference, selects an area within one degree of the reference as an analysis area, and divides the area corresponding to the remaining angle values ​​into equal proportions, and sorts the image information after division from high to low according to the grayscale value; Step 62: The processing unit further divides the analysis area into equal-area rectangles, and classifies each divided rectangular image by calculating the histogram of the image. A rectangular image is randomly selected from each classified category to count the number of dust particles, and the statistical number of dust particles is assigned to the remaining rectangular images in the same category. The dust particles of all rectangular images in the analysis area are accumulated and summed, and then divided by the area of ​​the analysis area to obtain the dust density corresponding to the analysis area. Step 63: the processing unit divides the areas corresponding to the remaining angle values ​​after the division into equal proportions, determines the division ratio according to the sorting method, and uses a mean filtering method to denoise the sorted image; Step 64: The processing unit compares the grayscale histogram of the denoised image information with the analysis area, compares the similarity of the grayscale distribution of the images, assigns the dust density of each denoised image according to the dust density of the analysis area multiplied by the similarity ratio, counts the dust density of all image information, and completes the analysis and calculation of the dust density in a single equivalent space; Step 65: The processing unit repeats the above steps until all equivalent spaces have completed analysis and calculation, and the dust density analysis of the area where a single visual terminal is located is completed.

2. A register, characterized in that: The registers are integrated into the controller and the processing unit respectively, and computer programs or instructions for execution by the controller or the processing unit are stored in the registers. When the computer programs or instructions are executed, the method according to claim 1 is implemented.

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