CN113192050A - Slime water online monitoring device and method and electronic equipment - Google Patents
Slime water online monitoring device and method and electronic equipment Download PDFInfo
- Publication number
- CN113192050A CN113192050A CN202110539287.5A CN202110539287A CN113192050A CN 113192050 A CN113192050 A CN 113192050A CN 202110539287 A CN202110539287 A CN 202110539287A CN 113192050 A CN113192050 A CN 113192050A
- Authority
- CN
- China
- Prior art keywords
- coal slime
- image
- slime water
- binary
- binary image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 103
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000012806 monitoring device Methods 0.000 title claims description 18
- 239000003245 coal Substances 0.000 claims abstract description 100
- 239000002245 particle Substances 0.000 claims abstract description 34
- 238000012544 monitoring process Methods 0.000 claims abstract description 31
- 238000001514 detection method Methods 0.000 claims abstract description 24
- 238000009826 distribution Methods 0.000 claims abstract description 18
- 238000011010 flushing procedure Methods 0.000 claims description 33
- 238000012545 processing Methods 0.000 claims description 22
- 230000015654 memory Effects 0.000 claims description 19
- 230000007246 mechanism Effects 0.000 claims description 16
- 230000009466 transformation Effects 0.000 claims description 10
- 238000010586 diagram Methods 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 7
- 230000000877 morphologic effect Effects 0.000 claims description 6
- 239000011248 coating agent Substances 0.000 claims description 4
- 238000000576 coating method Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 4
- 239000000126 substance Substances 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 239000006185 dispersion Substances 0.000 claims description 2
- 239000003250 coal slurry Substances 0.000 description 8
- 239000010419 fine particle Substances 0.000 description 6
- 238000003860 storage Methods 0.000 description 5
- 230000000903 blocking effect Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000011176 pooling Methods 0.000 description 3
- 238000003556 assay Methods 0.000 description 2
- 239000011153 ceramic matrix composite Substances 0.000 description 2
- 238000009833 condensation Methods 0.000 description 2
- 230000005494 condensation Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000003973 paint Substances 0.000 description 2
- 230000035699 permeability Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 239000002002 slurry Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000008187 granular material Substances 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000009533 lab test Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000005406 washing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration by the use of histogram techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/155—Segmentation; Edge detection involving morphological operators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
Abstract
The application discloses an online coal slime particle concentration measuring device, which comprises computing equipment, a light source and an acquisition device, wherein the acquisition device comprises a pipe body and a camera device arranged in the pipe body, a shooting window is arranged at the end part of the pipe body, the computing equipment is electrically connected with the camera device, and a detection area is formed between the shooting window and the light source; the camera device collects images of the coal slime water in the detection area through the shooting window, and the computing equipment computes the particle size distribution of the coal slime water according to the images of the coal slime water. The application also discloses an online coal slime particle concentration measuring method and electronic equipment. The method and the device can monitor the particle distribution condition of the coal slime water in real time, and improve monitoring timeliness.
Description
Technical Field
The application relates to the technical field of coal slime collection, in particular to a coal slime water online monitoring device and method and electronic equipment.
Background
The key parameters such as the concentration and the granularity of the coal slime particles are generally laboratory test analysis steps such as coal slime water sampling, screening and measuring. Due to the influence of assay analysis, the assay result of the previous day can be obtained only the next day, and the reference value of the method has very little guiding significance on industrial process control. The requirements of the coal slime concentration process on the particle size and the concentration of the coal slime are high, and the existing method cannot meet the requirements.
Therefore, there is a need to design a device, a method and an electronic device for on-line monitoring of coal slime water.
Disclosure of Invention
The application aims to overcome the defects of the prior art, and provides the coal slime water online monitoring device, the coal slime water online monitoring method and the electronic equipment, which can monitor the particle distribution condition of the coal slime water in real time and improve the monitoring timeliness.
The technical scheme of the application provides a slime water on-line monitoring device, including computing equipment, light source and collection system, collection system includes body and the camera device of setting in the body, the tip of body has the shooting window, computing equipment with the camera device electricity is connected, form detection area between shooting window and the light source;
the camera device collects images of the coal slime water in the detection area through the shooting window, and the computing equipment computes the particle size distribution of the coal slime water according to the images of the coal slime water.
Preferably, the coal slime water detection device further comprises a splitter for collecting or dispersing the coal slime water, and the splitter is arranged below the detection area.
Preferably, the riffler comprises any one of a pooling device or a dividing device;
the collecting device is provided with a first channel with the diameter which is changed from large to small along the flow direction of the slime water;
the dispersion device is provided with a second channel with a diameter which is smaller and larger along the flow direction of the coal slime water.
Preferably, the camera further comprises a transparent cover plate covering the shooting window, and hydrophilic paint is arranged on the transparent cover plate.
Preferably, the shooting device further comprises a flushing mechanism, wherein the flushing mechanism is arranged outside the pipe body, and the flushing direction of the flushing mechanism faces the shooting window.
Preferably, the flushing mechanism comprises a flushing pipe and a pipe clamp valve clamped on the flushing pipe and used for controlling the opening and closing of the flushing pipe.
The invention also discloses a slime water parameter online monitoring method, which comprises the following steps:
collecting an image of slime water as an original image;
carrying out gray level transformation on the original image to obtain a gray level image of the original image;
carrying out binarization processing on the gray-scale image to obtain a first binary image and a second binary image;
performing morphological processing on the first binary image and performing distance conversion to obtain a converted gray image after the distance conversion;
taking coordinates corresponding to the local extreme point of the transformed gray level image as watershed dam bottom coordinates, taking points corresponding to coordinates in the second binary image, which are the same as the watershed dam bottom coordinates, as the watershed dam bottom of the second binary image, and performing watershed operation on the watershed dam bottom based on the second binary image in the second binary image to obtain a binary connected image;
carrying out connected domain extraction on the binary connected graph to obtain a size fraction distribution result of coarse coal slime particles;
and carrying out exclusive OR processing on the second binary image and the binary connected image to obtain a particle size distribution result of medium-fine coal slime particles.
Preferably, the watershed operation based on the second binary image at the watershed dam bottom to obtain a binary connected image specifically includes:
and increasing the target area marks of the coal slime particles by adopting a method of controlling the markers, and stopping when the watershed damming edge meets the edge of the second binary image.
Preferably, the binarizing the grayscale image to obtain the first binary image and the second binary image specifically includes:
calculating the maximum inter-class variance of the samples of the statistical histogram of the gray-scale image to obtain a first threshold th 1;
setting a second threshold th2, said second threshold being smaller than said first threshold;
obtaining a ternary image according to the first threshold value and the second threshold value, and carrying out binarization processing on the ternary image, wherein the point of the ith row and the jth column in the ternary image
Determining the value of the point with the same coordinate in the first binary image and the second binary image according to the value of each point in the ternary image, wherein:
point of ith row and jth column in first binary image
Point of ith row and jth column in second two-value diagram
The present invention also discloses an electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to at least one of the processors; wherein the content of the first and second substances,
the memory stores instructions executable by at least one of the processors, and the instructions are executed by at least one of the processors to enable the at least one of the processors to execute the above-mentioned coal slurry parameter online monitoring method.
After adopting above-mentioned technical scheme, have following beneficial effect:
the invention can monitor the coal slime water on line, carry out photographing analysis processing on the coal slime particles in the coal slime water, realize the on-line measurement of the particle size distribution condition of the coal slime water and improve the monitoring efficiency.
Drawings
The disclosure of the present application will become more readily understood by reference to the drawings. It should be understood that: these drawings are for illustrative purposes only and are not intended to limit the scope of the present application. In the figure:
FIG. 1 is a schematic structural diagram of an on-line monitoring device for slime water according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the construction of a pooling device in one embodiment of the present invention;
FIG. 3 is a schematic diagram of the construction of a dispersing apparatus according to one embodiment of the present invention;
FIG. 4 is a schematic flow chart of a method for monitoring coal slurry water parameters on line according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a hardware structure of an electronic device according to the present invention.
Reference symbol comparison table:
a computing device 10;
a light source 20;
the pipe body 30: a shooting window 301;
the imaging device 40: an industrial camera 401, a telecentric mirror 402;
a splitter 50;
the flushing mechanism 60: a flush line 601, a pinch valve 602;
a processor 701, a memory 702, an input device 703, a display device 704.
Detailed Description
Embodiments of the present application are further described below with reference to the accompanying drawings.
It is easily understood that according to the technical solutions of the present application, those skilled in the art can substitute various structures and implementations without changing the spirit of the present application. Therefore, the following detailed description and the accompanying drawings are merely illustrative of the technical solutions of the present application, and should not be construed as limiting or restricting the technical solutions of the present application in their entirety.
The terms of orientation of up, down, left, right, front, back, top, bottom, and the like referred to or may be referred to in this specification are defined relative to the configuration shown in the drawings, and are relative terms, and thus may be changed correspondingly according to the position and the use state of the device. Therefore, these and other directional terms should not be construed as limiting terms. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Throughout the description of the present application, it is to be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "coupled" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two components can be directly connected or indirectly connected through an intermediate medium, and the two components can be communicated with each other. The foregoing is to be understood as belonging to the specific meanings in the present application as appropriate to the person of ordinary skill in the art.
The invention discloses a slime water online monitoring device in one embodiment, as shown in fig. 1, the slime water online monitoring device comprises a computing device 10, a light source 20 and a collecting device, wherein the collecting device comprises a tube body 30 and a camera device arranged in the tube body 30, the end part of the tube body 30 is provided with a shooting window 301, the computing device 10 is electrically connected with the camera device, and a detection area is formed between the shooting window 301 and the light source 20;
the camera device collects images of the coal slime water in the detection area through the shooting window 301, and the calculation device 10 calculates the particle size distribution of the coal slime water according to the images of the coal slime water.
In the device, the shooting window 301 is arranged in flowing coal slime water, the irradiation light beam emitted by the light source 20 is perpendicular to the shooting window 301, the light source 20 is used for improving irradiation when the coal slime water passes through the detection area, and the shooting device 40 is used for shooting the coal slime water in the detection area. The shooting device 40 transmits the shot images of the coal slime water to the computing equipment 10, and the computing equipment 10 calculates the current particle size distribution of the coal slime water according to the images.
In one embodiment of the present invention, a splitter 50 for collecting or dispersing the coal slurry water is further included, and the splitter 50 is disposed below the detection region.
Can adjust the concentration of the coal slime water of the detection area of flowing through splitter 50, select different splitters 50 according to the concentration condition of current coal slime water, guarantee that the coal slime water of different concentrations can both keep in suitable detected concentration when passing through the detection area to improve the accuracy and the uniformity of monitoring.
In one embodiment of the present invention, the splitter 50 comprises either a pooling device or a splitting device;
the collecting device is provided with a first channel with the diameter changing from large to small along the flow direction of the slime water;
the dispersing device has a second passage with a diameter that becomes smaller and larger in the flow direction of the slime water.
Wherein, as shown in fig. 2, the upper end of the collecting device is an outlet, the lower end is an inlet, and the channel of the collecting device is from bottom to top from big to small, so that the concentration of the coal slime flowing through the collecting device can be improved, and the device is suitable for the condition that the whole concentration of the coal slime is lower. The inner wall of the channel of the collecting device is a cambered surface, so that the flow velocity of the slime water in the channel can be increased.
As shown in figure 3, the upper end of the dispersing device is an outlet, the lower end of the dispersing device is an inlet, and the channel of the dispersing device is enlarged from bottom to top, so that the concentration of the coal slime water flowing through the collecting device can be reduced, and the dispersing device is suitable for the condition of high overall concentration of the coal slime water. The inner wall of the channel of the dispersing device is an inclined plane, so that the coal slime water is prevented from generating turbulence in the channel.
The entrance and exit of the collecting device and the dispersing device are provided with blocking plates, the blocking plates are made of ceramic matrix composite materials, certain permeability exists in high-speed flowing liquid, and fine particles below 100nm can be blocked, so that the fine particles in the coal slime water can be blocked, and the interference of the fine particles in the coal slime water on monitoring is avoided.
In one embodiment of the present invention, the camera further comprises a transparent cover plate covering the shooting window 301, and the transparent cover plate is provided with a hydrophilic paint. Through setting up hydrophilic coating can make the difficult condensation of bubble on transparent cover plate to influence the monitoring result.
In one embodiment of the present invention, the imaging device comprises an industrial camera 401 and a telecentric mirror 402, the industrial camera 401 being coupled to the telecentric mirror 402. Through telecentric mirror 402 combining with industrial camera 401, the phenomenon that the accuracy of monitoring is affected due to obvious geometric distortion caused by defocusing of the shot slime water photo can be avoided.
In one embodiment of the present invention, the device further includes a flushing mechanism 60, the flushing mechanism 60 is disposed outside the tube 30, and a flushing direction of the flushing mechanism 60 faces the shooting window 301. Can wash by water to shooting window 301 through washing mechanism 60, avoid the coal slime granule adhesion in the coal slime aquatic to influence the accuracy of monitoring on shooting window 301.
In one embodiment of the present invention, the flushing mechanism 60 comprises a flushing pipe 601 and a pinch valve 602 clamped on the flushing pipe 601 and used for controlling the opening and closing of the flushing pipe 601.
The pipe clamp valve 602 is a pneumatic pipe clamp valve, and the opening and closing of the flushing pipe 601 can be intermittently controlled through the pneumatic pipe clamp valve, so that the flushing pipe 601 can intermittently flush the shooting window 301.
The invention also discloses a slime water parameter online monitoring method, which comprises the following steps:
collecting an image of slime water as an original image;
carrying out gray level transformation on the original image to obtain a gray level image of the original image;
carrying out binarization processing on the gray-scale image to obtain a first binary image and a second binary image;
performing morphological processing on the first binary image and performing distance conversion to obtain a converted gray image after the distance conversion;
taking coordinates corresponding to the local extreme point of the transformed gray level image as watershed dam bottom coordinates, taking points corresponding to the coordinates in the second binary image, which are the same as the watershed dam bottom coordinates, as the watershed dam bottom of the second binary image, and performing watershed operation on the watershed dam bottom based on the second binary image in the second binary image to obtain a binary connected image;
carrying out connected domain extraction on the binary connected graph to obtain a size fraction distribution result of coarse coal slime particles;
and carrying out exclusive OR processing on the second binary image and the binary connected image to obtain a particle size distribution result of medium-fine coal slime particles.
In one embodiment of the present invention, performing watershed operations on a watershed dam bottom based on a second binary image to obtain a binary connected image specifically includes:
and increasing the target area marks of the coal slime particles by adopting a method of controlling the markers, and stopping when the watershed damming edge meets the edge of the second binary image.
In one embodiment of the present invention, the binarizing the grayscale image to obtain the first binary image and the second binary image specifically includes:
calculating the maximum inter-class variance of the samples of the statistical histogram of the gray-scale image to obtain a first threshold th 1;
setting a second threshold th2, the second threshold being smaller than the first threshold;
obtaining a ternary image according to the first threshold value and the second threshold value, and carrying out binarization processing on the ternary image, wherein the point of the ith row and the jth column in the ternary image
Determining the value of the point with the same coordinate in the first binary image and the second binary image according to the value of each point in the ternary image, wherein:
point of ith row and jth column in first binary image
Point of ith row and jth column in second two-value diagram
In one embodiment of the present invention, the statistical histogram of the gray scale map is represented by equation (3):
where n is the total number of pixels, nq is the number of pixels with a gray level of q, and L is all possible gray levels in the image, 255;
the maximum inter-class variance is:
wherein, P1(k) Is the ratio of the number of first type samples to the total number of samples, P2(k) Is the ratio of the number of the second type samples to the total number of the samples, m1(k) Is the mean of the first class samples, m2(k) Is the mean value of the second type of samples, mGAn overall mean;
wherein, the first threshold th1 is a division value of the maximum inter-class variance;
the second threshold th2 is set to 0.9.
In one embodiment of the present invention, the performing morphological processing and distance conversion on the first binary image to obtain a distance-converted grayscale image P3 specifically includes:
and performing morphological processing on the first binary image, corroding coal slime particles by adopting a 3 x 3 square structural element, and performing distance transformation on the second binary image to obtain a transformed gray image after the distance transformation.
The present invention also discloses an electronic device, comprising:
at least one processor 701; and the number of the first and second groups,
a memory 702 communicatively coupled to the at least one processor 701; wherein the content of the first and second substances,
the memory 702 stores instructions executable by the at least one processor 701, and the instructions are executable by the at least one processor 701 to enable the at least one processor 701 to perform the above-mentioned coal slurry parameter online monitoring method.
Example 1:
the embodiment discloses a coal slime water on-line monitoring device, as shown in fig. 1, the coal slime water on-line monitoring device comprises a computing device 10, a light source 20 and a collecting device, wherein the collecting device comprises a pipe body 30 and a camera device arranged in the pipe body 30, a shooting window 301 is arranged at the end part of the pipe body 30, a transparent cover plate is arranged on the shooting window 301, so that the inside and the outside of the pipe body 30 are separated, the shooting window 301 is arranged in flowing coal slime water, the light source 20 is arranged at one side of the shooting window 301, a detection area is formed between the light source 20 and the shooting window 301, and light rays perpendicular to the shooting window 301 are emitted by the light source 20 to provide illumination required by shooting for the camera device.
The camera device is electrically connected with the computing device 10, the camera device shoots the slime water flowing through the detection area through the shooting window 301, the shot pictures are transmitted to the computing device 10, and the computing device 10 calculates the current particle size distribution condition of the slime water according to the images.
In this embodiment, the slurry water flows from the lower end to the upper end of the illustration and through the detection zone. The coal slime water on-line monitoring device is also provided with a splitter 50, the splitter 50 is arranged below the detection area, the coal slime water enters the detection area after passing through the splitter 50, and the splitter 50 is used for collecting or dispersing the coal slime water, so that the concentration of the coal slime water flowing through the detection area is adjusted.
Specifically, in the present embodiment, the splitter 50 includes any one of a collecting device or a dispersing device. As shown in fig. 2, the upper end of the collecting device is an outlet, the lower end of the collecting device is an inlet, and the diameter of a channel of the collecting device is reduced along the flowing direction of the coal slime water, so that the concentration of the coal slime water flowing through the collecting device can be improved, and the collecting device is suitable for the condition that the overall concentration of the coal slime water is low. The inner wall of the channel of the collecting device is a cambered surface, so that the flow velocity of the slime water in the channel can be increased.
As shown in figure 3, the upper end of the dispersing device is an outlet, the lower end of the dispersing device is an inlet, and the diameter of the channel of the dispersing device is increased along the flowing direction of the coal slime water, so that the concentration of the coal slime water flowing through the collecting device can be reduced, and the dispersing device is suitable for the condition that the integral concentration of the coal slime water is high. The inner wall of the channel of the dispersing device is an inclined plane, so that the coal slime water is prevented from generating turbulence in the channel.
The entrance and exit of the collecting device and the dispersing device are provided with blocking plates, the blocking plates are made of ceramic matrix composite materials, certain permeability exists in high-speed flowing liquid, and fine particles below 100nm can be blocked, so that the fine particles in the coal slime water can be blocked, and the interference of the fine particles in the coal slime water on monitoring is avoided.
In this embodiment, be equipped with hydrophilic coating on transparent cover plate, can make the difficult condensation of bubble on transparent cover plate through setting up hydrophilic coating to influence the monitoring result.
In this embodiment, the image pickup apparatus includes an industrial camera 401 and a telecentric mirror 402, and the industrial camera 401 is connected to the telecentric mirror 402. Through telecentric mirror 402 combining with industrial camera 401, the phenomenon that the accuracy of monitoring is affected due to obvious geometric distortion caused by defocusing of the shot slime water photo can be avoided.
In this embodiment, the coal slime water on-line monitoring device further comprises a flushing mechanism 60, wherein the flushing mechanism 60 comprises a flushing pipeline 601 and a pneumatic pipe clamp valve clamped on the flushing pipeline 601, and the opening and closing of the flushing pipeline 601 can be intermittently controlled through the pneumatic pipe clamp valve, so that the flushing pipeline 601 can intermittently flush the shooting window 301, and the coal slime particles in the coal slime water are prevented from adhering to the shooting window 301 to affect the monitoring accuracy.
In the device, flowing coal slime water is collected or dispersed by a splitter 50 and enters a detection area, a shooting device 40 shoots the coal slime water in the detection area through a shooting window 301 and transmits the shot image to a computing device 10, and the computing device 10 processes and analyzes the image, so that the current particle size distribution condition of the coal slime water is obtained through calculation.
Example 2:
the embodiment discloses a method for monitoring coal slime water parameters on line, which comprises the following steps as shown in FIG. 4:
s1: collecting an image of slime water as an original image;
s2: carrying out gray level transformation on the original image to obtain a gray level image of the original image;
s3: carrying out binarization processing on the gray-scale image to obtain a first binary image and a second binary image;
s4: performing morphological processing and distance transformation on the first binary image P1 to obtain a transformed gray image P3 after distance transformation;
s5: taking coordinates corresponding to the local extreme point of the transformed gray-scale image P3 as watershed dam bottom coordinates, taking points corresponding to the same coordinates as the watershed dam bottom coordinates in the second binary image P2 as the watershed dam bottom of the second binary image P2, and performing watershed operation in the second binary image P2 based on the watershed dam bottom of the second binary image P2 to obtain a binary connected image P4;
s6: carrying out connected domain extraction on the binary connected graph P4 to obtain a size fraction distribution result of coarse coal slime particles;
s7: and carrying out exclusive OR processing on the second binary image P2 and the binary connected image P4 to obtain a particle size distribution result of medium-fine coal slime particles.
In the present embodiment, step S3 includes the following steps:
s3.1: calculating the maximum inter-class variance of the samples of the statistical histogram of the gray-scale image to obtain a first threshold th 1;
s3.2: setting a second threshold th2, the second threshold th2 being less than the first threshold th 1;
s3.3: obtaining a three-value graph according to a first threshold th1 and a second threshold th2, and performing binarization processing on the three-value graph, wherein points in the ith row and the jth column in the three-value graph
Determining the value of the point with the same coordinate in the first binary image and the second binary image according to the value of each point in the ternary image, wherein:
point of ith row and jth column in first binary image
Point of ith row and jth column in second two-value diagram
Wherein, step S3.1 specifically includes:
the statistical histogram of the gray scale map is expressed by equation (3):
where n is the total number of pixels, nq is the number of pixels with a gray level of q, and L is all possible gray levels in the image, 255;
the maximum inter-class variance is:
wherein, P1(k) Is the ratio of the number of first type samples to the total number of samples, P2(k) Is the ratio of the number of the second type samples to the total number of the samples, m1(k) Is the mean of the first class samples, m2(k) Is the mean value of the second type of samples, mGOverall mean.
The first threshold th1 is a division value of the maximum inter-class variance.
In step S3.2, the second threshold th2 is set to 0.9;
in this embodiment, step S4 specifically includes:
and (3) morphologically processing the binary image P1, corroding the coal slime particles by adopting 3 × 3 square structural elements, and performing distance transformation on the binary image P1 to obtain a gray image P3 after distance transformation.
In this embodiment, step S5 specifically includes:
coordinates (P) corresponding to local extreme point Pk of transformed gray scale map P3kx，Pky) And performing watershed operation on the second binary image P2 as watershed dam bottom coordinates, increasing the marks of the coal slime particle target areas by adopting a method of controlling the marks in order to prevent the watershed from being over-segmented, and stopping when the edge of the watershed dam meets the edge of the second binary image P2.
Example 3:
fig. 5 is a schematic diagram of a hardware structure of an electronic device according to the present invention, which includes:
at least one processor 701; and the number of the first and second groups,
a memory 702 communicatively coupled to the at least one processor 701; wherein the content of the first and second substances,
the memory 702 stores instructions executable by the at least one processor 701, and the instructions are executed by the at least one processor 701 to enable the at least one processor 701 to perform the above coal slurry parameter on-line monitoring method
In fig. 5, one processor 701 is taken as an example.
The electronic device may further include: an input device 703 and a display device 704.
The processor 701, the memory 702, the input device 703 and the display device 704 may be connected by a bus or other means, and are illustrated as being connected by a bus.
The memory 702, serving as a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions/modules corresponding to the coal slime water parameter online monitoring method in the embodiment of the present application, for example, the method flow shown in fig. 4. The processor 701 executes various functional applications and data processing by running nonvolatile software programs, instructions and modules stored in the memory 702, so as to implement the method for monitoring the coal slurry water parameter online in the foregoing embodiment.
The memory 702 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area can store data and the like created according to the use of the coal slime water parameter online monitoring method. Further, the memory 702 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 702 may optionally include a memory remotely located from the processor 701, and these remote memories may be connected via a network to a device that performs the method for on-line monitoring of coal slurry parameters. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 703 may receive input user clicks and generate signal inputs related to user settings and functional control of the slurry water parameter on-line monitoring method. Display device 704 may include a display screen or the like.
The coal slurry water parameter on-line monitoring method in any of the method embodiments described above is performed when the one or more modules are stored in the memory 702 and executed by the one or more processors 701.
The foregoing is considered as illustrative only of the principles and preferred embodiments of the application. It should be noted that, for a person skilled in the art, several other modifications can be made on the basis of the principle of the present application, and these should also be considered as the scope of protection of the present application.
Claims (10)
1. The coal slime water online monitoring device is characterized by comprising a computing device (10), a light source (20) and a collecting device, wherein the collecting device comprises a pipe body (30) and a camera device arranged in the pipe body (30), a shooting window (301) is arranged at the end part of the pipe body (30), the computing device (10) is electrically connected with the camera device, and a detection area is formed between the shooting window (301) and the light source (20);
the camera device penetrates through the shooting window (301) to collect images of the coal slime water in the detection area, and the calculation equipment (10) calculates the particle size distribution of the coal slime water according to the images of the coal slime water.
2. The coal slime water on-line monitoring device according to claim 1, further comprising a splitter (50) for collecting or dispersing the coal slime water, wherein the splitter (50) is arranged below the detection area.
3. The coal slime water on-line monitoring device according to claim 2, wherein the splitter (50) comprises any one of a collecting device or a splitting device;
the collecting device is provided with a first channel with the diameter which is changed from large to small along the flow direction of the slime water;
the dispersion device is provided with a second channel with a diameter which is smaller and larger along the flow direction of the coal slime water.
4. The coal slime water on-line monitoring device according to claim 1, further comprising a transparent cover plate covering the shooting window (301), wherein a hydrophilic coating is arranged on the transparent cover plate.
5. The coal slime water on-line monitoring device of claim 1, further comprising a flushing mechanism (60), wherein said flushing mechanism (60) is disposed outside said pipe body (30) and the flushing direction of said flushing mechanism (60) faces said shooting window (301).
6. The coal slime water on-line monitoring device according to claim 5, wherein the flushing mechanism (60) comprises a flushing pipeline (601) and a pipe clamp valve (602) clamped on the flushing pipeline (601) and used for controlling the opening and the closing of the flushing pipeline (601).
7. A coal slime water parameter online monitoring method is characterized by comprising the following steps:
collecting an image of slime water as an original image;
carrying out gray level transformation on the original image to obtain a gray level image of the original image;
carrying out binarization processing on the gray-scale image to obtain a first binary image and a second binary image;
performing morphological processing on the first binary image and performing distance conversion to obtain a converted gray image after the distance conversion;
taking coordinates corresponding to the local extreme point of the transformed gray level image as watershed dam bottom coordinates, taking points corresponding to coordinates in the second binary image, which are the same as the watershed dam bottom coordinates, as the watershed dam bottom of the second binary image, and performing watershed operation on the watershed dam bottom based on the second binary image in the second binary image to obtain a binary connected image;
carrying out connected domain extraction on the binary connected graph to obtain a size fraction distribution result of coarse coal slime particles;
and carrying out exclusive OR processing on the second binary image and the binary connected image to obtain a particle size distribution result of medium-fine coal slime particles.
8. The coal slime water parameter online monitoring method of claim 7, wherein the watershed operation is performed at the watershed dam bottom based on the second binary image to obtain a binary connected image, and specifically comprises:
and increasing the target area marks of the coal slime particles by adopting a method of controlling the markers, and stopping when the watershed damming edge meets the edge of the second binary image.
9. The coal slime water parameter online monitoring method according to claim 7, wherein the binarizing processing is performed on the gray map to obtain a first binary map and a second binary map, and specifically comprises:
calculating the maximum inter-class variance of the samples of the statistical histogram of the gray-scale image to obtain a first threshold th 1;
setting a second threshold th2, said second threshold being smaller than said first threshold;
obtaining a ternary image according to the first threshold value and the second threshold value, and carrying out binarization processing on the ternary image, wherein the point of the ith row and the jth column in the ternary image
Determining the value of the point with the same coordinate in the first binary image and the second binary image according to the value of each point in the ternary image, wherein:
point of ith row and jth column in first binary image
Point of ith row and jth column in second two-value diagram
10. An electronic device, comprising:
at least one processor (701); and the number of the first and second groups,
a memory (702) communicatively coupled to at least one of the processors (701); wherein the content of the first and second substances,
the memory (702) stores instructions executable by at least one of the processors (701), the instructions being executable by the at least one of the processors (701) to enable the at least one of the processors (701) to perform the coal slime water parameter on-line monitoring method as set forth in any one of claims 7 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110539287.5A CN113192050A (en) | 2021-05-18 | 2021-05-18 | Slime water online monitoring device and method and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110539287.5A CN113192050A (en) | 2021-05-18 | 2021-05-18 | Slime water online monitoring device and method and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113192050A true CN113192050A (en) | 2021-07-30 |
Family
ID=76982373
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110539287.5A Pending CN113192050A (en) | 2021-05-18 | 2021-05-18 | Slime water online monitoring device and method and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113192050A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115155788A (en) * | 2022-08-04 | 2022-10-11 | 华电电力科学研究院有限公司 | Heavy medium sorting and medium adding system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1793839A (en) * | 2005-12-12 | 2006-06-28 | 苏州科技学院 | Automatic monitoring device of active sludge multiparameter |
| US20140125801A1 (en) * | 2012-03-16 | 2014-05-08 | Tongji University | On-line tunnel deformation monitoring system based on image analysis and its application |
| KR101799680B1 (en) * | 2016-06-10 | 2017-11-22 | 조선대학교산학협력단 | A method for brain image segmentation using a combination of expectation maximization algorithm and watershed transform |
| CN210071670U (en) * | 2018-10-17 | 2020-02-14 | 兖煤菏泽能化有限公司 | Coal slime tailing ash content measuring device based on machine vision |
| CN111047555A (en) * | 2019-11-13 | 2020-04-21 | 鞍钢集团矿业有限公司 | Ore image granularity detection algorithm based on image processing technology |
| US20200193212A1 (en) * | 2016-09-07 | 2020-06-18 | Malvern Panalytical Limited | Particle boundary identification |
| CN112330653A (en) * | 2020-11-16 | 2021-02-05 | 鞍钢集团矿业有限公司 | Online ore granularity detection method based on image recognition technology |
-
2021
- 2021-05-18 CN CN202110539287.5A patent/CN113192050A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1793839A (en) * | 2005-12-12 | 2006-06-28 | 苏州科技学院 | Automatic monitoring device of active sludge multiparameter |
| US20140125801A1 (en) * | 2012-03-16 | 2014-05-08 | Tongji University | On-line tunnel deformation monitoring system based on image analysis and its application |
| KR101799680B1 (en) * | 2016-06-10 | 2017-11-22 | 조선대학교산학협력단 | A method for brain image segmentation using a combination of expectation maximization algorithm and watershed transform |
| US20200193212A1 (en) * | 2016-09-07 | 2020-06-18 | Malvern Panalytical Limited | Particle boundary identification |
| CN210071670U (en) * | 2018-10-17 | 2020-02-14 | 兖煤菏泽能化有限公司 | Coal slime tailing ash content measuring device based on machine vision |
| CN111047555A (en) * | 2019-11-13 | 2020-04-21 | 鞍钢集团矿业有限公司 | Ore image granularity detection algorithm based on image processing technology |
| CN112330653A (en) * | 2020-11-16 | 2021-02-05 | 鞍钢集团矿业有限公司 | Online ore granularity detection method based on image recognition technology |
Non-Patent Citations (4)
| Title |
|---|
| ZHU BING-LI ET AL.: "Comprehensive applying watershed algorithm in segmentation of CT brain images", 《2011 6TH IEEE JOINT INTERNATIONAL INFORMATION TECHNOLOGY AND ARTIFICIAL INTELLIGENCE CONFERENCE》 * |
| 吴冰;赵成安;: "井下料位图像采集方法研究", 河南理工大学学报(自然科学版), no. 04 * |
| 周健;余荣传;贾敏才;: "基于数字图像技术的砂土模型试验细观结构参数测量", 岩土工程学报, no. 12 * |
| 蔡改贫;李龙茂;姜志宏;: "基于图像处理的矿石粒度检测系统设计", 冶金自动化, no. 06 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115155788A (en) * | 2022-08-04 | 2022-10-11 | 华电电力科学研究院有限公司 | Heavy medium sorting and medium adding system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110414334B (en) | Intelligent water quality identification method based on unmanned aerial vehicle inspection | |
| CN102297660B (en) | Measuring method of shield tunnel lining segment seam open width and apparatus thereof | |
| Radice et al. | Solid transport measurements through image processing | |
| CN105758345B (en) | A kind of x-ray fluorescence imaging device of on-line measurement strip coating thickness | |
| CN109074033A (en) | For optimizing cohesion and/or flocculated method and system in water treatment procedure | |
| CN108416287A (en) | A kind of pedestrian detection method excavated based on omission negative sample | |
| CN101029863B (en) | Method and apparatus for on-line measuring microparticle in water | |
| CN108956484A (en) | A kind of method and apparatus of integration tracking pollution sources | |
| WO2021126346A1 (en) | In-situ, real-time detection of particulate defects in a fluid | |
| CN109876569A (en) | A kind of bag filter purification gas index on-line measuring device, system and method | |
| CN113192050A (en) | Slime water online monitoring device and method and electronic equipment | |
| Cauteruccio et al. | Experimental evidence of the wind-induced bias of precipitation gauges using particle image velocimetry and particle tracking in the wind tunnel | |
| US20120293795A1 (en) | Defect inspection device and method of inspecting defect | |
| CN113012195A (en) | Method for estimating river surface flow velocity based on optical flow calculation and readable storage medium | |
| WO2020119600A1 (en) | Image acquisition device and detection apparatus for particulate matter in liquid | |
| CN109711313B (en) | Real-time video monitoring method for identifying sewage poured into river channel | |
| O'Brien et al. | An experimental study of the dynamics of saltation within a three-dimensional framework | |
| WO2014026999A1 (en) | Method for determining the size spectra and the concentration of particles in a multi-phase liquid flow and cavitation channel | |
| CN103258433B (en) | Intelligent clear display method for number plates in traffic video surveillance | |
| CN104010165B (en) | Precipitation particles shadow image automatic acquisition device | |
| KR100633649B1 (en) | Method and device for measuring fine particles in ultrapure water | |
| Abbaszadeh et al. | A new bubbly flow detection and quantification procedure based on optical laser-beam scattering behavior | |
| KR101897232B1 (en) | Apparatus of image detector for detecting particulate in liquid | |
| TWI662509B (en) | Development of a disdrometer and particle tracking process thereof | |
| SE515950C2 (en) | Method and apparatus for measuring the log surface profile of a log |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |