Online monitoring and early warning method and system for slurry quality of desulfurizing absorption tower

Abstract

The invention discloses a desulfurization absorption tower slurry quality online monitoring and early warning method and system, and relates to the technical field of slurry quality online monitoring, and the method comprises the following steps: collecting an absorption tower slurry image, and carrying out preprocessing; extracting slurry foams based on the edge features; calculating and extracting the area occupied by the slurry foam area, and judging; and the system selects whether to give an alarm according to a judgment result. The invention provides a desulfurization absorption tower slurry quality on-line monitoring and early warning method based on feature extraction, aiming at the problems that slurry parameters of an absorption tower of a desulfurization system of a thermal generator set at present all adopt a manual measurement mode, test is operated manually, and the slurry quality cannot be monitored in real time, and the invention provides a desulfurization absorption tower slurry quality on-line monitoring and early warning method based on feature extraction. According to the method, the slurry images can be collected in real time at the slurry outlet pipeline, the slurry foam characteristics of the collected images are extracted, and meanwhile, according to the extraction result, the slurry foaming condition is analyzed, the slurry quality is judged, and the result is fed back to an operator in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of slurry quality online monitoring, and in particular to a desulfurization absorption tower slurry quality online monitoring early warning method and system. Background Art

[0002] At present, the slurry parameters of the desulfurization system absorption tower of the thermal power generation unit are all measured manually, and the test is all done manually, and the slurry quality cannot be monitored in real time. The present invention proposes a desulfurization absorption tower slurry quality online monitoring and early warning method based on feature extraction. The method can collect slurry images in real time at the slurry outlet pipeline, and extract slurry foam features from the collected images. At the same time, according to the extracted results, the slurry foaming situation is analyzed, the slurry quality is judged, and real-time feedback is given to the operating personnel. According to the analysis results, the operating personnel can monitor the slurry quality in real time and dynamically, effectively avoid the risk of slurry quality deterioration due to untimely monitoring, and ensure the safe and stable operation of the desulfurization environmental protection system. Summary of the invention

[0003] In view of the problems existing in the existing online monitoring and early warning system of slurry quality in desulfurization absorption towers, the present invention is proposed.

[0004] Therefore, the problem to be solved by the present invention is that timely monitoring cannot be guaranteed, which easily leads to the risk of deterioration of slurry quality.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a method for online monitoring and early warning of slurry quality in a desulfurization absorption tower, which comprises the following steps:

[0007] Collect the absorption tower slurry image and perform preprocessing;

[0008] Extract slurry foam based on edge features;

[0009] Calculate the area occupied by the extracted slurry foam area and make a judgment;

[0010] Based on the judgment result, the system chooses whether to alarm.

[0011] As a preferred solution of the method for online monitoring and early warning of desulfurization absorption tower slurry quality of the present invention, the step of preprocessing the absorption tower slurry image includes:

[0012] The Brown distortion model is used to dedistort the image to remove radial distortion and tangential distortion. The Brown distortion model in the camera Cartesian coordinate system is expressed as:

[0013]

[0014] In the formula, (x c1d ,y c1d ) is the coordinate of the imaging point after distortion on the imaging plane, k c1 is the second-order distortion coefficient, k c2 is the 4th-order distortion coefficient, k c5 is the 6th order distortion coefficient, k c3 , k c4 is the tangential distortion coefficient, r is the distance from the intersection of the optical axis centerline and the imaging plane to the imaging point, and r 2 =x c1 2 +y c1 2 ;

[0015] Then, through the conversion relationship between the image coordinate system and the pixel coordinate system, the pixel coordinates (u', v') after distortion compared with the original image can be obtained as follows:

[0016]

[0017] The distorted pixel coordinate values ​​need to be interpolated, and then the interpolated pixel values ​​are assigned to the corresponding pixel coordinates after dedistortion.

[0018] As a preferred solution of the method for online monitoring and early warning of desulfurization absorption tower slurry quality of the present invention, the step of preprocessing the absorption tower slurry image also includes:

[0019] The grayscale image of the absorption tower slurry is converted into a binary image. The specific steps include:

[0020] R(x,y)=G(x,y)=B(x,y)=rR(x,y)+gG(x,y)+bB(x,y);

[0021] Where R(x,y), G(x,y), and B(x,y) are the red, green, and blue channel components of the pixel, respectively, and r, g, and b represent the red, green, and blue channel weights.

[0022] As a preferred solution of the method for online monitoring and early warning of desulfurization absorption tower slurry quality of the present invention, the step of preprocessing the absorption tower slurry image also includes:

[0023] The slurry image of the absorption tower is subjected to noise reduction processing by the Gaussian distribution formula, where the Gaussian distribution formula is expressed as:

[0024]

[0025] Where (x, y) is the coordinate of any point in the mask, (u x ,u y) are the coordinates of the center point of the Gaussian template, which are usually regarded as integers during calculations.

[0026] As a preferred solution of the method for online monitoring and early warning of slurry quality in the desulfurization absorption tower of the present invention, the step of extracting the area occupied by the slurry foam area includes:

[0027] In the foam image, for the extracted foam edge points, each point is scanned horizontally starting from the center of the image, that is, each row is scanned clockwise from left to right to obtain the foam contour of a one-dimensional dot matrix;

[0028] Perform cubic spline fitting on the obtained point matrix, and find the point with the largest absolute value of the first-order derivative of the fitting curve at the center of the image, and record it as the starting point;

[0029] Continue to perform the same operation on the fitting curve and find the coordinates corresponding to the point as the end point;

[0030] Then perform the same operation on the end point as on the starting point to obtain the coordinates of the new end point, and then perform the same operation on the new end point as on the starting point until the end points of all fitting curves are obtained;

[0031] Get the one-dimensional coordinate point on the line connecting the symmetry centers of the foam image;

[0032] The radius of the fitted circle of the foam in the corresponding binary image, the area of ​​the corresponding circle and the corresponding number of pixels are calculated through the one-dimensional coordinate points on the line connecting the symmetry centers of the foam image, and the proportion of the number of pixels occupied in the image is calculated.

[0033] As a preferred solution of the method for online monitoring and early warning of the quality of slurry in the desulfurization absorption tower of the present invention, the step of judging the occupied area includes:

[0034] When the occupied area is greater than 30% of the absorption tower slurry image area, a pre-alarm is issued;

[0035] When the occupied area is greater than 50% of the absorption tower slurry image area, an alarm is issued.

[0036] As a preferred solution of the method for online monitoring and early warning of slurry quality in the desulfurization absorption tower of the present invention, the alarm step includes:

[0037] Visual Alarm: Displays a warning message on the monitoring screen.

[0038] Audible alarm: The alarm sounds through a buzzer or speaker.

[0039] Remote notification: Notification to operators via SMS, email or APP push.

[0040] In a second aspect, an embodiment of the present invention provides an online monitoring and early warning system for the quality of slurry in a desulfurization absorption tower, which includes an image acquisition module, an image preprocessing module, an edge feature extraction module, and an alarm module;

[0041] The image acquisition module uses a high-definition camera or an industrial camera to capture images of the absorption tower slurry;

[0042] The image preprocessing module is used to perform de-distortion, de-graying and de-noising processing on the image;

[0043] The edge feature extraction module is used to extract the outline of the foam from the edge map to form a closed area;

[0044] The alarm module is used to remind the staff.

[0045] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, any step of the above-mentioned desulfurization absorption tower slurry quality online monitoring and early warning method is implemented.

[0046] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned method for online monitoring and early warning of desulfurization absorption tower slurry quality is implemented.

[0047] The beneficial effects of the present invention are as follows: in view of the problem that the slurry parameters of the absorption tower of the desulfurization system of the thermal power generating unit are all measured manually, the tests are all performed manually, and the slurry quality cannot be monitored in real time, the present invention proposes an online monitoring and early warning method for the slurry quality of the desulfurization absorption tower based on feature extraction, which can collect slurry images in real time at the slurry outlet pipeline, and extract slurry foam features from the collected images, and analyze the slurry foaming situation according to the extracted results, judge the slurry quality, and provide real-time feedback to the operating personnel. According to the analysis results, the operating personnel can monitor the slurry quality in real time and dynamically, effectively avoid the risk of slurry quality deterioration due to untimely monitoring, and ensure the safe and stable operation of the desulfurization environmental protection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0049] Figure 1The figure is a flow chart of the online monitoring and early warning method for the slurry quality in the desulfurization absorption tower.

[0050] Figure 2 This is a picture of the collected slurry for the online monitoring and early warning method of the desulfurization absorption tower slurry quality.

[0051] Figure 3 This is a dedistorted image of the collected slurry image for the online monitoring and early warning method of the desulfurization absorption tower slurry quality.

[0052] Figure 4 This is a grayscale processing diagram of the online monitoring and early warning method for the desulfurization absorption tower slurry quality.

[0053] Figure 5 This is the filtering processing diagram of the online monitoring and early warning method for the desulfurization absorption tower slurry quality.

[0054] Figure 6 This is the slurry foam edge extraction diagram for the online monitoring and early warning method of the desulfurization absorption tower slurry quality. DETAILED DESCRIPTION

[0055] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0056] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0057] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0058] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0059] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0060] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0061] Example 1

[0062] Reference Figure 1 to Figure 6 , which is the first embodiment of the present invention, provides a method for online monitoring and early warning of slurry quality in a desulfurization absorption tower, comprising the following steps:

[0063] S1. Collect the absorption tower slurry image and perform preprocessing.

[0064] The preprocessing steps for the absorber slurry image include:

[0065] The Brown distortion model is used to dedistort the image to remove radial distortion and tangential distortion. The Brown distortion model in the camera Cartesian coordinate system is expressed as:

[0066]

[0067] In the formula, (x c1d ,y c1d ) is the coordinate of the imaging point after distortion on the imaging plane, k c1 is the second-order distortion coefficient, k c2 is the 4th-order distortion coefficient, k c5 is the 6th order distortion coefficient, k c3 , k c4 is the tangential distortion coefficient, r is the distance from the intersection of the optical axis centerline and the imaging plane to the imaging point, and r 2 =x c1 2 +y c1 2 ;

[0068] Then, through the conversion relationship between the image coordinate system and the pixel coordinate system, the pixel coordinates (u', v') after distortion compared with the original image can be obtained as follows:

[0069]

[0070] It is necessary to interpolate the distorted pixel coordinates and assign the interpolated pixel values ​​to the corresponding pixel coordinates after dedistortion. The distortion of the image can be removed by traversing all pixel points, such as Figure 3 shown.

[0071] The present invention uses a Baumer industrial camera, and the size of the collected color image is 2581 (H) × 1932 (V). Each pixel contains three channels of 24-bit RGB image data, so the amount of data to be processed for each image is very large. If the original image is processed directly, the processing time will be long. In order to reduce the image processing time and improve efficiency, it is necessary to convert the image grayscale into a binary image.

[0072] Image grayscale means converting each pixel from RGB3 channels to a single channel, and grayscale the image after traversing all pixels. The grayscale value range of the grayscale image is 0 to 255, indicating a total of 256 levels from black to white. The component values ​​of the RGB3 channels of the original image are equivalently operated, that is, the value of each component is evaluated according to the specified transformation relationship;

[0073] The grayscale image of the absorption tower slurry is converted into a binary image. The specific steps include:

[0074] R(x,y)=G(x,y)=B(x,y)=rR(x,y)+gG(x,y)+bB(x,y);

[0075] In the formula, R(x,y), G(x,y), and B(x,y) are the red, green, and blue channel components of the pixel, respectively. r, g, and b represent the weights of the red, green, and blue channels. The grayscale result is as follows: Figure 4 shown.

[0076] The preprocessing step for the absorber slurry image also includes:

[0077] The slurry image of the absorption tower is subjected to noise reduction processing by the Gaussian distribution formula, where the Gaussian distribution formula is expressed as:

[0078]

[0079] Where (x, y) is the coordinate of any point in the mask, (u x ,u y) are the coordinates of the center point of the Gaussian template. They are usually regarded as integers during calculations. The coordinate values ​​at different positions are substituted into the Gaussian function for solution, and the obtained value is the template coefficient. Among the many parameters for generating the Gaussian filter template, the most important parameter is the standard deviation σ. The size of σ reflects the degree of discreteness of the data. σ is inversely proportional to the center coefficient of the template. That is, the smaller σ is, the larger the center coefficient of the template is, and the smaller the coefficient around the center of the template is, which will reduce the smoothing and denoising effect of the image; conversely, the larger σ is, the difference between the coefficients in the template is not very large, and its effect is similar to that of the mean template, which has a better smoothing effect on the image. The filtering results are as follows: Figure 5 shown.

[0080] S2. Extract slurry foam based on edge features.

[0081] The steps of extracting the area occupied by the slurry foam area include:

[0082] In the foam image, for the extracted foam edge points, each point is scanned horizontally starting from the center of the image, that is, each row is scanned clockwise from left to right to obtain the foam contour of a one-dimensional dot matrix;

[0083] Perform cubic spline fitting on the obtained point matrix, and find the point with the largest absolute value of the first-order derivative of the fitting curve at the center of the image, and record it as the starting point;

[0084] Continue to perform the same operation on the fitting curve and find the coordinates corresponding to the point as the end point;

[0085] Then perform the same operation on the end point as on the starting point to obtain the coordinates of the new end point, and then perform the same operation on the new end point as on the starting point until the end points of all fitting curves are obtained;

[0086] Get the one-dimensional coordinate point on the line connecting the symmetry centers of the foam image;

[0087] The radius of the fitted circle of the foam in the corresponding binary image, the area of ​​the corresponding circle and the corresponding number of pixels are calculated through the one-dimensional coordinate points on the line connecting the symmetric centers of the foam image, and the proportion of the number of pixels in the image is calculated, such as Figure 6 shown.

[0088] S3. Calculate the area occupied by the extracted slurry foam area and make a judgment.

[0089] The steps to judge the occupied face include:

[0090] When the occupied area is greater than 30% of the absorption tower slurry image area, a pre-alarm is issued;

[0091] When the occupied area is greater than 50% of the absorption tower slurry image area, an alarm is issued.

[0092] S4. Based on the judgment result, the system chooses whether to alarm.

[0093] The alarm step includes:

[0094] Visual Alarm: Displays a warning message on the monitoring screen.

[0095] Audible alarm: The alarm sounds through a buzzer or speaker.

[0096] Remote notification: Notification to operators via SMS, email or APP push.

[0097] In summary, in view of the problem that the slurry parameters of the desulfurization system absorption tower of the thermal power generating unit are currently measured manually, the tests are all done manually, and the slurry quality cannot be monitored in real time, the present invention proposes a desulfurization absorption tower slurry quality online monitoring and early warning method based on feature extraction, which can collect slurry images at the slurry outlet pipeline in real time, and extract slurry foam features from the collected images, and analyze the slurry foaming situation according to the extracted results, judge the slurry quality, and provide real-time feedback to the operating personnel. According to the analysis results, the operating personnel can monitor the slurry quality in real time and dynamically, effectively avoid the risk of slurry quality deterioration due to untimely monitoring, and ensure the safe and stable operation of the desulfurization environmental protection system.

[0098] Example 2

[0099] On the basis of the first embodiment, this embodiment further provides a desulfurization absorption tower slurry quality online monitoring and early warning system, including an image acquisition module, an image preprocessing module, an edge feature extraction module, and an alarm module;

[0100] The image acquisition module uses a high-definition camera or an industrial camera to capture images of the absorption tower slurry;

[0101] The image preprocessing module is used to perform de-distortion, de-graying and de-noising processing on the image;

[0102] The edge feature extraction module is used to extract the outline of the foam from the edge map to form a closed area;

[0103] The alarm module is used to remind the staff.

[0104] This embodiment also provides a computer device, which is suitable for the case of an online monitoring and early warning method for the quality of slurry in a desulfurization absorber, and includes a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the online monitoring and early warning method for the quality of slurry in a desulfurization absorber as proposed in the above embodiment.

[0105] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0106] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for online monitoring and early warning of the quality of slurry in a desulfurization absorption tower proposed in the above embodiment is implemented.

[0107] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0108] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for online monitoring and early warning of slurry quality in a desulfurization absorption tower, characterized in that: The following steps are included: Collect the absorption tower slurry image and perform preprocessing; Extract slurry foam based on edge features; Calculate the area occupied by the extracted slurry foam area and make a judgment; Based on the judgment result, the system chooses whether to alarm.

2. The method for online monitoring and early warning of slurry quality in a desulfurization absorption tower according to claim 1, characterized in that: The preprocessing steps for the absorber slurry image include: The Brown distortion model is used to dedistort the image to remove radial distortion and tangential distortion. The Brown distortion model in the camera Cartesian coordinate system is expressed as: In the formula, (x c1d ,y c1d ) is the coordinate of the imaging point after distortion on the imaging plane, k c1 is the second-order distortion coefficient, k c2 is the 4th-order distortion coefficient, k c5 is the 6th order distortion coefficient, k c3 , k c4 is the tangential distortion coefficient, r is the distance from the intersection of the optical axis centerline and the imaging plane to the imaging point, and r 2 =x c1 2 +y c1 2 ; Then, through the conversion relationship between the image coordinate system and the pixel coordinate system, the pixel coordinates (u', v') after distortion compared with the original image can be obtained as follows: The distorted pixel coordinate values ​​need to be interpolated, and then the interpolated pixel values ​​are assigned to the corresponding pixel coordinates after dedistortion.

3. The method for online monitoring and early warning of slurry quality in a desulfurization absorption tower according to claim 2, characterized in that: The preprocessing step for the absorber slurry image also includes: The grayscale image of the absorption tower slurry is converted into a binary image. The specific steps include: R(x,y)=G(x,y)=B(x,y)=rR(x,y)+gG(x,y)+bB(x,y); Where R(x,y), G(x,y), and B(x,y) are the red, green, and blue channel components of the pixel, respectively, and r, g, and b represent the red, green, and blue channel weights.

4. The method for online monitoring and early warning of slurry quality in a desulfurization absorption tower according to claim 3, characterized in that: The preprocessing step for the absorber slurry image also includes: The slurry image of the absorption tower is subjected to noise reduction processing by the Gaussian distribution formula, where the Gaussian distribution formula is expressed as: Where (x, y) is the coordinate of any point in the mask, (u x ,u y ) are the coordinates of the center point of the Gaussian template, which are usually regarded as integers during calculations.

5. The method for online monitoring and early warning of slurry quality in a desulfurization absorption tower according to claim 4, characterized in that: The steps of extracting the area occupied by the slurry foam area include: In the foam image, for the extracted foam edge points, each point is scanned horizontally starting from the center of the image, that is, each row is scanned clockwise from left to right to obtain the foam contour of a one-dimensional dot matrix; Perform cubic spline fitting on the obtained point matrix, and find the point with the largest absolute value of the first-order derivative of the fitting curve at the center of the image, and record it as the starting point; Continue to perform the same operation on the fitting curve and find the coordinates corresponding to the point as the end point; Then perform the same operation on the end point as on the starting point to obtain the coordinates of the new end point, and then perform the same operation on the new end point as on the starting point until the end points of all fitting curves are obtained; Get the one-dimensional coordinate point on the line connecting the symmetry centers of the foam image; The radius of the fitted circle of the foam in the corresponding binary image, the area of ​​the corresponding circle and the corresponding number of pixels are calculated through the one-dimensional coordinate points on the line connecting the symmetry centers of the foam image, and the proportion of the number of pixels occupied in the image is calculated.

6. The method for online monitoring and early warning of slurry quality in a desulfurization absorption tower according to claim 5, characterized in that: The steps to judge the occupied face include: When the occupied area is greater than 30% of the absorption tower slurry image area, a pre-alarm is issued; When the occupied area is greater than 50% of the absorption tower slurry image area, an alarm is issued.

7. The method for online monitoring and early warning of slurry quality in a desulfurization absorption tower according to claim 6, characterized in that: The alarm step includes: Visual Alarm: Displays a warning message on the monitoring screen. Audible alarm: The alarm sounds through a buzzer or speaker. Remote notification: Notification to operators via SMS, email or APP push.

8. A desulfurization absorption tower slurry quality online monitoring and early warning system, based on the desulfurization absorption tower slurry quality online monitoring and early warning method according to any one of claims 1 to 7, characterized in that: It includes an image acquisition module, an image preprocessing module, an edge feature extraction module, and an alarm module; The image acquisition module uses a high-definition camera or an industrial camera to capture images of the absorption tower slurry; The image preprocessing module is used to perform de-distortion, de-graying and de-noising processing on the image; The edge feature extraction module is used to extract the outline of the foam from the edge map to form a closed area; The alarm module is used to remind the staff.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for online monitoring and early warning of the quality of slurry in a desulfurization absorption tower according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for online monitoring and early warning of the quality of slurry in a desulfurization absorption tower according to any one of claims 1 to 7 are implemented.

Images