CN110782455A - Novel method for determining mud content of raw sand based on image processing method - Google Patents
Novel method for determining mud content of raw sand based on image processing method Download PDFInfo
- Publication number
- CN110782455A CN110782455A CN201911133336.4A CN201911133336A CN110782455A CN 110782455 A CN110782455 A CN 110782455A CN 201911133336 A CN201911133336 A CN 201911133336A CN 110782455 A CN110782455 A CN 110782455A
- Authority
- CN
- China
- Prior art keywords
- image
- mud content
- sand
- raw sand
- color space
- 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.)
- Granted
Links
- 239000004576 sand Substances 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000003672 processing method Methods 0.000 title claims abstract description 9
- 239000007788 liquid Substances 0.000 claims abstract description 9
- 238000013178 mathematical model Methods 0.000 claims abstract description 9
- 238000012360 testing method Methods 0.000 claims abstract description 9
- 238000007781 pre-processing Methods 0.000 claims abstract description 4
- 238000005406 washing Methods 0.000 claims description 11
- 238000006243 chemical reaction Methods 0.000 claims description 10
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 4
- 238000005303 weighing Methods 0.000 claims description 4
- 239000012153 distilled water Substances 0.000 claims description 3
- 239000011521 glass Substances 0.000 claims description 2
- 238000010606 normalization Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 claims description 2
- 238000003756 stirring Methods 0.000 claims description 2
- 238000005259 measurement Methods 0.000 abstract description 3
- 238000004140 cleaning Methods 0.000 abstract 1
- 238000005266 casting Methods 0.000 description 5
- 239000003110 molding sand Substances 0.000 description 5
- 238000005520 cutting process Methods 0.000 description 2
- 238000001035 drying Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 239000010802 sludge Substances 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000009835 boiling Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 238000004062 sedimentation Methods 0.000 description 1
- 230000035945 sensitivity Effects 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
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
- G01N15/075—Investigating concentration of particle suspensions by optical means
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
- G01N2015/0687—Investigating concentration of particle suspensions in solutions, e.g. non volatile residue
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
Landscapes
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Dispersion Chemistry (AREA)
- Quality & Reliability (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Spectrometry And Color Measurement (AREA)
Abstract
The invention discloses a method for measuring the mud content of raw sand based on an image processing method, and belongs to the field of measurement of the mud content of the raw sand. The invention solves the problem that the existing method for measuring the mud content of the raw sand has complex and fussy process, and the flow of the invention is shown in figure 1. The method comprises the following steps: s1, cleaning the raw sand; s2, obtaining a turbid liquid image of the raw sand, and preprocessing the image; s3, converting the RGB color model into a Lab color model; s4, extracting the brightness component of the image to obtain a characteristic value; s5, constructing a mathematical model of mud content and characteristic values; s6, calculating the mud content of the to-be-measured raw sand sample according to a pre-constructed mathematical model of the mud content and the characteristic value; s7, calculating the mud content of the to-be-measured raw sand sample according to a pre-constructed mathematical model of the mud content and the characteristic value; and S8, inputting the test turbid liquid sample into the program for accuracy test. The method enables the determination of the mud content of the raw sand to be simpler and more efficient, and enables the determination efficiency to be improved. The invention is suitable for measuring the mud content of the raw sand.
Description
Technical Field
The invention belongs to the field of measuring the mud content of raw sand, and particularly relates to a novel method for measuring the mud content of the raw sand based on an image processing method.
Background
The raw sand is the "aggregate" of the molding sand, which has a great influence on the properties of the molding sand, and therefore, the quality of the raw sand needs to be controlled. The mud content is one of important indexes for representing the quality of the raw sand, and influences the performance of the molding sand and even the performance of a casting, for example, the too high mud content can cause the molding sand to become brittle, the casting is easy to generate insufficient air hole casting and other defects; too low a content of sludge causes a large increase in the sensitivity of the molding sand to moisture and an excessively rough surface of the casting. Therefore, the mud content of the raw sand or the used sand must be known in the production. Therefore, the method has important significance for detecting and controlling the mud content of the raw sand and controlling the quality of the casting.
The current measurement of the mud content of the raw sand is a standard measurement method, and the sedimentation velocity of particles in water is calculated according to a Stokes formula and the specified water temperature and standing time according to the principle of the method, so that the position where sand grains should be settled is obtained. The fine fraction above this point is then of the mud fraction. The method needs boiling, vortex washing, multiple siphoning, drying, weighing and other steps, has multiple and complicated steps, has poor repeatability, and correspondingly improves errors caused by human factors due to excessive human participation. In this information and automation era, too many manual operations alone add many problems to production and life, and therefore, the most fundamental object of the present invention is to solve these problems, i.e., to reduce too many human involvement and simplify the measurement procedure.
Disclosure of Invention
A new method for measuring the mud content of raw sand based on an image processing method is characterized by comprising the following steps:
s1, weighing 50g of raw sand containing 2g, 3g, 3.5g and 4g of mud by using an electronic balance, then respectively preparing 600ml of turbid liquid with distilled water, pouring the turbid liquid into a sand washing cup, washing sand for 15min by using a vortex-washing sand washer, then placing the sand washing cup into a dark room, uniformly stirring the sand by using a glass rod, and standing the sand for one minute;
s2, collecting the image of the turbid liquid to be detected through an image collecting device, and carrying out normalization processing on the collected image, wherein the resolution of the image is a multiplied by b;
s3, performing image preprocessing including filtering and the like on each image;
s4, converting the image to be detected from the RGB color model into a Lab color model;
s5, extracting the brightness component of the image to obtain a characteristic value;
s6, constructing a mathematical model of mud content and characteristic values;
s7, calculating the mud content of the to-be-measured raw sand sample according to a pre-constructed mathematical model of the mud content and the characteristic value;
and S8, inputting the test sample into the program for accuracy test.
The method according to claim 1, wherein the color model conversion in step four is performed, and the specific principle and steps of performing color conversion on the image are as follows:
the color model S41 and Lab mode is a color model independent of equipment and based on physiological characteristics, and the LAB color model is composed of three elements: l (luminance), two color channels a and b; wherein the value range of L is [0,100], which represents pure black to pure white; the value range of a is [ -128, -127], representing from dark green (low brightness value) to gray (medium brightness value) to bright pink red (high brightness value); b ranges from bright blue (low luminance value) to gray (medium luminance value) to yellow (high luminance value);
s42, converting RGB into a Lab color mode, wherein the RGB color space cannot be directly converted into the Lab color space, and the RGB color space is converted into an XYZ color space by means of the XYZ color space and then is converted into the Lab color space from the XYZ color space;
the RGB and XYZ color space conversion formula is as follows:
(1)
the formula for converting the XYZ color space to Lab is as follows: generally, Yn, Xn and Zn are all 1;
wherein:
in the above expression, the value ranges of the variables X, Y, Z and t are all [0,1 ];
and S43, performing color model conversion on the image by using a self-contained function rgb2lab in Matlab.
Compared with the prior art, the invention has the advantages and positive effects that:
according to the method, on the basis of reflection difference of particles and distilled water to light, through characteristic value analysis obtained by extracting brightness components from a Lab color mode of a measured turbid liquid image based on an image processing method, the complex and tedious processes of repeated sand washing, filtering, drying, weighing and the like after sand washing in the conventional method for measuring the mud content of the raw sand are solved, the participation of manual operation is reduced, the test time is reduced from hours to half an hour, and the mud content of the raw sand is rapidly measured.
Drawings
FIG. 1 is a flow chart of a new method for determining the mud content of raw sand based on an image processing method;
FIG. 2 is a turbidity chart of the mud content of the raw sand to be measured;
FIG. 3 is a graph showing the relationship between the sludge content and the water content;
fig. 4 is a graph of the effects of data fitting.
Detailed Description
The process of the invention is further illustrated below with reference to the accompanying drawings and specific examples: referring to the attached figure 1, a new method for measuring the mud content of raw sand based on an image processing method;
s1, collecting the detected solution through a detection device, recording a video, preparing 4 turbid solutions (mud is 2g, 3g, 3.5g and 4g respectively) with different concentrations, and recording each concentration for 10 minutes;
s2, cutting the obtained video into images and cutting the images, wherein the resolution of the images is 150 x 100, as shown in figure 2;
s3, image preprocessing such as median filtering is adopted for each image;
s4, converting the image to be detected through a color model, extracting a brightness component, and obtaining a characteristic value;
s41, converting the image from rgb to lab by applying the self-contained conversion function rgb2lab of matlab;
s5, extracting the brightness component of the image to obtain a characteristic value;
s6, fitting a curve to construct a mathematical model according to the characteristic value and the true value, wherein the x axis is the mud content and the y axis is the characteristic value as shown in the attached figures 3 and 4;
s7, calculating the mud content of the to-be-measured raw sand sample according to a pre-constructed mathematical model of the mud content and the characteristic value;
and S8, inputting the test sample into the program for accuracy test.
Claims (2)
1. A new method for measuring the mud content of raw sand based on an image processing method is characterized by comprising the following steps:
s1, weighing by using an electronic balance: 50g of raw sand with mud content of 2g, 3g, 3.5g and 4g respectively, then preparing 600ml of turbid liquid with distilled water respectively, pouring the turbid liquid into a sand washing cup, washing sand for 15min by using a vortex washing type sand washer, then placing the sand washing cup into a dark room, uniformly stirring the sand by using a glass rod, and standing the sand for one minute;
s2, collecting the image of the turbid liquid to be detected through an image collecting device, and carrying out normalization processing on the collected image, wherein the resolution of the image is a multiplied by b;
s3, performing image preprocessing including filtering and the like on each image;
s4, converting the image to be detected from the RGB color model into a Lab color model;
s5, extracting the brightness component of the image to obtain a characteristic value;
s6, constructing a mathematical model of mud content and characteristic values;
s7, calculating the mud content of the to-be-measured raw sand sample according to a pre-constructed mathematical model of the mud content and the characteristic value;
and S8, inputting the test sample into the program for accuracy test.
2. The method according to claim 1, wherein the color model conversion in step four is performed, and the specific method and steps for performing color conversion on the image are as follows:
the color model S41 and Lab mode is a color model independent of equipment and based on physiological characteristics, and the LAB color model is composed of three elements: l (luminance), two color channels a and b; wherein the value range of L is [0,100], which represents pure black to pure white; the value range of a is [ -128, -127], representing from dark green (low brightness value) to gray (medium brightness value) to bright pink red (high brightness value); b ranges from bright blue (low luminance value) to gray (medium luminance value) to yellow (high luminance value);
s42, converting RGB into a Lab color mode, wherein the RGB color space cannot be directly converted into the Lab color space, and the RGB color space is converted into an XYZ color space by means of the XYZ color space and then is converted into the Lab color space from the XYZ color space;
the RGB and XYZ color space conversion formula is as follows:
the RGB and XYZ color space conversion formula is as follows:
(1)
the formula for converting the XYZ color space to Lab is as follows: generally, Yn, Xn and Zn are all 1;
wherein:
in the above expression, the value ranges of the variables X, Y, Z and t are all [0,1 ];
and S43, performing color model conversion on the image by using a self-contained function rgb2lab in Matlab.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911133336.4A CN110782455B (en) | 2019-11-19 | 2019-11-19 | Novel method for determining mud content of raw sand based on image processing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911133336.4A CN110782455B (en) | 2019-11-19 | 2019-11-19 | Novel method for determining mud content of raw sand based on image processing method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110782455A true CN110782455A (en) | 2020-02-11 |
| CN110782455B CN110782455B (en) | 2021-10-08 |
Family
ID=69392083
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911133336.4A Active CN110782455B (en) | 2019-11-19 | 2019-11-19 | Novel method for determining mud content of raw sand based on image processing method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110782455B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112748079A (en) * | 2020-12-23 | 2021-05-04 | 中山艾尚智同信息科技有限公司 | Method for measuring mud content of natural sand for building |
| CN112816475A (en) * | 2021-01-13 | 2021-05-18 | 太原市玉磊预拌混凝土有限公司 | Natural sand mud content detection device based on image scanning |
| CN115343228A (en) * | 2022-07-22 | 2022-11-15 | 深圳大学 | Method, device and equipment for determining sand and stone mud content |
| CN115409741A (en) * | 2022-11-01 | 2022-11-29 | 长江勘测规划设计研究有限责任公司 | Machine vision recognition algorithm for measuring sediment content by using river surface color difference |
| CN116678885A (en) * | 2023-08-03 | 2023-09-01 | 福建南方路面机械股份有限公司 | Deep learning-based detection control method and device for mud content of water-washed coarse aggregate |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104853168A (en) * | 2015-05-25 | 2015-08-19 | 三峡大学 | Intelligent monitoring system for gravel aggregate quality |
| US9401030B2 (en) * | 2014-04-25 | 2016-07-26 | Tazco Soil Service Co. | Image processing system for soil characterization |
| CN108918328A (en) * | 2018-04-10 | 2018-11-30 | 哈尔滨理工大学 | A kind of automatic device and method based on constant volume method measurement roughing sand clay content |
| CN110349123A (en) * | 2019-06-11 | 2019-10-18 | 东南大学 | A kind of quantitative evaluation method of apparent mass of clear concrete |
-
2019
- 2019-11-19 CN CN201911133336.4A patent/CN110782455B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9401030B2 (en) * | 2014-04-25 | 2016-07-26 | Tazco Soil Service Co. | Image processing system for soil characterization |
| CN104853168A (en) * | 2015-05-25 | 2015-08-19 | 三峡大学 | Intelligent monitoring system for gravel aggregate quality |
| CN108918328A (en) * | 2018-04-10 | 2018-11-30 | 哈尔滨理工大学 | A kind of automatic device and method based on constant volume method measurement roughing sand clay content |
| CN110349123A (en) * | 2019-06-11 | 2019-10-18 | 东南大学 | A kind of quantitative evaluation method of apparent mass of clear concrete |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112748079A (en) * | 2020-12-23 | 2021-05-04 | 中山艾尚智同信息科技有限公司 | Method for measuring mud content of natural sand for building |
| CN112816475A (en) * | 2021-01-13 | 2021-05-18 | 太原市玉磊预拌混凝土有限公司 | Natural sand mud content detection device based on image scanning |
| CN115343228A (en) * | 2022-07-22 | 2022-11-15 | 深圳大学 | Method, device and equipment for determining sand and stone mud content |
| CN115409741A (en) * | 2022-11-01 | 2022-11-29 | 长江勘测规划设计研究有限责任公司 | Machine vision recognition algorithm for measuring sediment content by using river surface color difference |
| CN116678885A (en) * | 2023-08-03 | 2023-09-01 | 福建南方路面机械股份有限公司 | Deep learning-based detection control method and device for mud content of water-washed coarse aggregate |
| CN116678885B (en) * | 2023-08-03 | 2023-12-19 | 福建南方路面机械股份有限公司 | Deep learning-based detection control method and device for mud content of water-washed coarse aggregate |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110782455B (en) | 2021-10-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110782455B (en) | Novel method for determining mud content of raw sand based on image processing method | |
| CN106991679A (en) | One kind quantifies recognition methods based on cloud platform urine test paper physical signs | |
| CN104251861A (en) | Intelligent terminal-based liquid detection analyzer and detection method using the same | |
| CN113945556A (en) | Water quality fluoride detection method based on digital image colorimetric analysis | |
| CN110132916B (en) | Accurate quantitative analysis method for metal elements | |
| US20200271590A1 (en) | Rapid joint detection device and detection method for deterioration degree of fried oil | |
| CN109323999A (en) | A kind of spectrophotometric detecting method based on image values analysis | |
| CN111751376A (en) | Rice nitrogen nutrition estimation method based on canopy image feature derivation | |
| CN111103338B (en) | Multi-mode automatic pH measuring instrument based on network and measuring method thereof | |
| CN112595711A (en) | Titration end point determination device | |
| CN109030755A (en) | The detection device and method of grain moisture content, mass of 1000 kernel and bulk density based on image processing techniques | |
| CN108827962B (en) | Egg maturity detection method based on light transmission method | |
| CN103063674A (en) | Detection method for copper grade of copper block, and detection system thereof | |
| CN105651739B (en) | Contents of many kinds of heavy metal ion nanocomposite optical detection device and method based on Stripping Voltammetry | |
| CN102226755A (en) | On-line analyzer for monitoring silicate concentration or phosphate concentration in water | |
| CN114994069B (en) | Method and system for detecting pollution components and content of insulator based on hyperspectrum | |
| CN106485257A (en) | The washing detergency objective evaluation device and method that view-based access control model is perceived | |
| CN114152557B (en) | Image analysis-based blood cell counting method and system | |
| CN2705791Y (en) | Grain fatty acid value detector | |
| CN116559162B (en) | Sand MB value rapid judging method based on image recognition technology | |
| CN105987866A (en) | Heterogeneous liquid settlement automatic-monitoring method and device | |
| CN101592644B (en) | Method for detecting barium ions in oil field water | |
| Iacono et al. | pH strip reader for beer samples based on image analysis | |
| CN204044085U (en) | A kind of foreign matter detection system based on light spectrum image-forming | |
| CN116681992B (en) | Ammonia nitrogen detection method based on neural network |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |