CN117347598A - Water paint production detection analysis system based on Internet of things - Google Patents
Water paint production detection analysis system based on Internet of things Download PDFInfo
- Publication number
- CN117347598A CN117347598A CN202311662822.1A CN202311662822A CN117347598A CN 117347598 A CN117347598 A CN 117347598A CN 202311662822 A CN202311662822 A CN 202311662822A CN 117347598 A CN117347598 A CN 117347598A
- Authority
- CN
- China
- Prior art keywords
- water
- paint
- based paint
- time point
- pigment
- 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
- 239000003973 paint Substances 0.000 title claims abstract description 220
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 156
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 66
- 238000001514 detection method Methods 0.000 title claims abstract description 47
- 238000004458 analytical method Methods 0.000 title claims abstract description 25
- 239000000049 pigment Substances 0.000 claims abstract description 125
- 239000011248 coating agent Substances 0.000 claims abstract description 44
- 238000000576 coating method Methods 0.000 claims abstract description 44
- 239000000463 material Substances 0.000 claims abstract description 37
- 238000002156 mixing Methods 0.000 claims abstract description 21
- 238000005259 measurement Methods 0.000 claims abstract description 9
- 230000007613 environmental effect Effects 0.000 claims abstract description 7
- 238000002474 experimental method Methods 0.000 claims description 95
- 238000005286 illumination Methods 0.000 claims description 95
- 238000003756 stirring Methods 0.000 claims description 63
- 238000000034 method Methods 0.000 claims description 49
- 238000007792 addition Methods 0.000 claims description 40
- 230000008569 process Effects 0.000 claims description 30
- 230000008859 change Effects 0.000 claims description 28
- 238000012360 testing method Methods 0.000 claims description 25
- 230000004992 fission Effects 0.000 claims description 13
- 238000012937 correction Methods 0.000 claims description 12
- 230000003044 adaptive effect Effects 0.000 claims description 11
- 238000005187 foaming Methods 0.000 claims description 9
- 239000000758 substrate Substances 0.000 claims description 9
- 238000011156 evaluation Methods 0.000 claims description 8
- 238000002360 preparation method Methods 0.000 claims description 7
- 238000013441 quality evaluation Methods 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 6
- 230000015572 biosynthetic process Effects 0.000 claims description 5
- 239000002245 particle Substances 0.000 claims description 3
- 239000002994 raw material Substances 0.000 claims description 3
- 230000006855 networking Effects 0.000 claims 1
- 230000007547 defect Effects 0.000 abstract description 3
- 239000000047 product Substances 0.000 description 31
- 238000012544 monitoring process Methods 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 5
- 239000003086 colorant Substances 0.000 description 4
- 238000001035 drying Methods 0.000 description 4
- 239000011521 glass Substances 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 239000002023 wood Substances 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000919 ceramic Substances 0.000 description 1
- 239000011362 coarse particle Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000012467 final product Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/26—Oils; Viscous liquids; Paints; Inks
- G01N33/32—Paints; Inks
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N11/00—Investigating flow properties of materials, e.g. viscosity, plasticity; Analysing materials by determining flow properties
- G01N11/10—Investigating flow properties of materials, e.g. viscosity, plasticity; Analysing materials by determining flow properties by moving a body within the material
- G01N11/14—Investigating flow properties of materials, e.g. viscosity, plasticity; Analysing materials by determining flow properties by moving a body within the material by using rotary bodies, e.g. vane
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N17/00—Investigating resistance of materials to the weather, to corrosion, or to light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N17/00—Investigating resistance of materials to the weather, to corrosion, or to light
- G01N17/004—Investigating resistance of materials to the weather, to corrosion, or to light to light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Health & Medical Sciences (AREA)
- Pathology (AREA)
- Immunology (AREA)
- General Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Ecology (AREA)
- Environmental & Geological Engineering (AREA)
- Environmental Sciences (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Engineering & Computer Science (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Paints Or Removers (AREA)
Abstract
The invention belongs to the field of water paint production quality detection, and particularly discloses a water paint production detection analysis system based on the Internet of things, which comprises the following components: the color difference of the water-based paint is obtained, the types of the compensating pigments are screened, the blending content of the types of the compensating pigments is calculated, the deviation color of the paint is timely adjusted, and the consistency of the color of the water-based paint in the production process is ensured. The water-based paint is properly stirred to obtain the dry consistency and uniformity of the water-based paint, so that the form conformity of the finished product of the water-based paint is analyzed, and the defect problem hidden in the solution is prevented from affecting the accuracy of the measurement result. The weather resistance index of the water-based paint is detected by coating the water-based paint on experimental boards and various base materials in various environments, so that the performance of the paint under various environmental conditions can be ensured, and guiding suggestions are provided for determining the application field of the paint.
Description
Technical Field
The invention belongs to the field of water paint production quality detection, and relates to a water paint production detection analysis system based on the Internet of things.
Background
By strictly controlling links such as production process, finished product detection and the like in the production flow of the water-based paint, the quality stability of the product can be improved, and the defective rate can be reduced, so that the quality of the water-based paint product is ensured to meet the standard and customer requirements, and therefore, the production and manufacturing management of the water-based paint plays an important role in the paint industry.
The water-based paint product is widely applied to the fields of buildings, furniture, automobiles and the like, different customers have different requirements on colors, and the individual requirements of the customers are met through color manufacturing control management, so that the customer satisfaction can be improved. The existing preparation link of the water-based paint production process lacks an adjustment mechanism in the aspect of color deviation monitoring after pigment addition, the color of the water-based paint is closely related to pigment addition, pigment components of different batches are different, and the color output result of the water-based paint is easy to have deviation conditions, so that corresponding compensation adjustment is required to be carried out according to the deviation degree of the deviation color, and the color of the water-based paint product meets the expected requirement.
The quality of the final product can be ensured to meet the standard by carrying out targeted performance detection based on different batches and different formulas of the water-based paint, the existing quality monitoring mode is only limited to collecting static images after the water-based paint is processed, the monitoring mode cannot collect abnormal conditions possibly existing in the solution, the monitoring environment is single, and the performance change condition of the water-based paint under various environments is not considered, so that the monitoring result lacks accuracy.
Disclosure of Invention
In view of this, in order to solve the problems set forth in the above background art, a water-based paint production detection and analysis system based on the internet of things is proposed.
The aim of the invention can be achieved by the following technical scheme: the invention provides a water-based paint production detection analysis system based on the Internet of things, which comprises: the preparation flow management and control module: the method is used for collecting a production image of the water-based paint, carrying out color recognition on the production image to obtain paint color difference, obtaining a paint compensation color card, screening out various compensation pigments, calculating the blending content of the various compensation pigments, analyzing the process parameter execution error rate of each pigment adding step, and feeding back the process parameter execution error rate.
And a finished product detection management and control module: the method is used for properly stirring the water-based paint to obtain the dry consistency and uniformity of the water-based paint, and further analyzing the form conformity of the finished product of the water-based paint。
Environmental test detection module: the method is used for taking a small amount of paint to coat on the experimental board, and carrying out corresponding performance detection on experimental parameters in various environments.
The material test detection module: the method is used for coating the water-based paint on various base materials, analyzing the adaptability strength of the water-based paint on various base materials, and further evaluating the weather resistance index of the water-based paint。
Production batch quality evaluation module: the method is used for evaluating the quality grade of the batch of water-based paint by combining the form conformity and weather resistance index of the finished product of the water-based paint.
Management library: the method is used for storing paint compensation color cards, standard production images, water paint finished product form standard images and various coating fission images under various formulated addition parameters, foaming characteristics, edge breach characteristics and mold generation characteristics in humidity experiment board images, and various index reference values of various base materials and quality excellent coefficient ranges corresponding to various quality grades.
Illustratively, the blending content of the various compensating pigments is calculated as follows: and obtaining the formulated addition parameters of the pigment production of the batch, extracting each pigment addition step and the standard pigment type and standard addition content of each pigment addition step from the formulated addition parameters, and obtaining the standard production image of the water-based paint under the formulated addition parameters from a management library.
Comparing the manufactured image of the water-based paint with a standard production image to obtain a paint color difference value, calculating the paint color difference degree based on the paint color difference value, and extracting various compensation pigments corresponding to the paint color difference value and the basic compensation duty ratio of the various compensation pigments from a paint compensation color card，/>To compensate for the numbering of the pigment classes +.>。
From analytical formulasObtaining the blended content of various compensating pigments, wherein +.>Color difference of paint>Adding total amount of pigment->To set the deviation control amount, e is a natural constant.
Illustratively, the procedure parameter execution error rate acquisition mode of each pigment adding step is as follows: and (3) extracting a production video of the raw material adding process, identifying the pigment types and the content corresponding to each pigment adding step from the production video, and comparing the pigment types corresponding to each pigment adding step with the standard pigment types corresponding to the pigment adding step to obtain each error adding step.
Extracting standard process parameters of each pigment adding step from the formulated adding parameters, wherein the standard process parameters comprise stirringComparing each pigment adding step with each error adding step, and if a pigment adding step is an error adding step, recording the process parameter execution error rate of the pigment adding step as。
Otherwise, the stirring and mixing time and stirring speed of the pigment adding step are obtained and recorded asCalculating the process parameter execution error rate of the pigment addition step +.>Wherein->Indicating maximum and minimum values of the proper range of stirring speed corresponding to the pigment adding step, +.>Indicating maximum and minimum values of the proper range of the pigment addition step corresponding to the stirring and mixing time period, +.>Respectively indicates that the stirring and mixing time is smaller than the minimum value of the proper range and is larger than the set time deviation allowable value corresponding to the maximum value of the proper range,respectively indicating the allowable value of the set speed deviation corresponding to the stirring speed being larger than the maximum value of the proper range and smaller than the minimum value of the proper range, ">Indicating the deviation correction ratio of the setting>Is a logical and sign.
Counting to obtain the working procedure parameters of each pigment adding stepExecution error rate，/>，/>Step number is added to the pigment,/->。
Illustratively, the analyzing the finished form compliance content of the aqueous coating includes: setting stirring time and properly stirring the water-based paint at a set speed, installing a force sensing device on a stirring device to detect the measured resistance of each stirring time point in the set stirring time, and analyzing to obtain the dry consistency of the water-based paint。
Collecting state change images of the water-based paint at each stirring time point within a set stirring time period, extracting form standard images of the water-based paint finished product from a management warehouse, comparing to obtain color degree coincidence coefficients of the water-based paint finished product form corresponding to each stirring time point, obtaining the number of coarse paint particles at each stirring time point, and analyzing to obtain uniformity of the water-based paint。
Analysis of the finished form compliance of Water-based paintWherein->Respectively setting reference values corresponding to the dry consistency and the uniformity of the water-based paint, < >>Respectively setting the weight of the water-based paint corresponding to the dry consistency and the uniformity of the water-based paint>And (5) correcting the factor for the set product form conformity deviation.
Illustratively, the environmental test detection module content includes: and C1, uniformly coating the set water-based paint on a plurality of experimental boards, uniformly dividing the experimental boards to obtain each illumination experimental board and each humidity experimental board, and setting the observation time of the experimental boards.
And C2, carrying out ultraviolet irradiation on each illumination experiment plate according to different illumination intensities, and analyzing to obtain the change index of each illumination experiment plate at the illumination threshold time point.
C3, placing each humidity experiment board in an environment without humidity value, obtaining the foaming size, edge breach width and mould generation amount of each humidity experiment board at each observation time point, and respectively marking as，/>Number of humidity test board>，/>Number indicating observation time point, +.>Analysis of the index of variation of each humidity test panel at each observation time point +.>WhereinReference variation values are set corresponding to the bubble size, edge breach width and mold formation amount between two observation time points, respectively, < >>Respectively represent +.>Bubble size, edge breach width and mold formation of individual humidity test panels at initial observation time point, +.>To set the deviation correction coefficient.
The change index analysis mode of each illumination experiment board at the illumination threshold time point is as follows: measuring and obtaining the chromaticity of the water-based paint at each observation time point corresponding to each illumination experiment board, comparing the chromaticity with the chromaticity of the initial observation time point corresponding to the corresponding illumination experiment board to obtain the illumination threshold time point corresponding to each illumination experiment board, and extracting the chromaticity of the illumination threshold time point corresponding to each illumination experiment board，/>Number of the light experiment plate is shown, and ∈>。
Detecting whether a coating fission condition exists at a time point corresponding to the illumination threshold value of each illumination experiment plate, when the coating fission condition exists at the time point corresponding to the illumination threshold value of a certain illumination experiment plate, acquiring the total length of the coating cracks of the illumination experiment plate corresponding to the time point corresponding to the illumination threshold value, and counting to obtain the total length of the coating cracks of each illumination experiment plate corresponding to the time point corresponding to the illumination threshold valueAnalyzing the change index of each illumination experiment plate at the illumination threshold time point>Wherein->Indicating the corresponding set reference value of the crack length of the coating +.>Indicating that the crack length of the coating corresponds to the influence evaluation factor, < +.>Indicate->Chromaticity of each light experiment panel at the initial time point.
Illustratively, the steps corresponding to analyzing the adaptive strength of the aqueous coating on various substrates are: coating the water-based paint on various base materials according to the same thickness, obtaining various index measurement values of the water-based paint on various base materials, and comparing the index measurement values with corresponding index reference values of corresponding base materials in a management library to obtain the adaptability strength of the water-based paint on various base materials.
Illustratively, the weather resistance index of the aqueous coating is evaluated in the following specific ways: the interval time between the corresponding illumination threshold time point and the initial observation time point of each illumination experiment board is recorded as the tolerance time of each illumination experiment board。
Comparing the change index of each humidity experiment board at each observation time point with the change index limiting value of the corresponding humidity experiment board, and counting to obtain the humidity threshold time point of each humidity experiment board, thereby obtaining the tolerance time of each humidity experiment board。
Substituting the change index of each illumination experiment board at the illumination threshold time pointAnd the adaptive Strength of Water-based paint on various substrates +.>Evaluation of the weather resistance index of the aqueous coating materials +.>Wherein->Respectively representing the set reference tolerance time length and the +.>Number indicating the kind of substrate->，/>Indicates the number of substrate types, ">Indicating the number of the light experiment plates->Indicating the number of humidity experimental boards>Indicating the value of the adaptive intensity setting versus.
Illustratively, the evaluation of the quality grade of the batch of water-borne paint is as follows: will be、/>Substituting the formula to calculate the quality excellent coefficient of the water-based paint of the batch +.>，/>，/>And (3) evaluating the correction coefficient for the quality-improving coefficient correspondence, further comparing the quality-improving coefficient of the batch of water-based paint with the quality-improving coefficient range corresponding to each quality grade in the management library, and screening to obtain the quality grade of the batch of water-based paint.
Compared with the prior art, the invention has the following beneficial effects: (1) According to the invention, the pigment color difference degree of the water-based paint is obtained, the types of the compensating pigments are screened, the blending content of the types of the compensating pigments is calculated based on the misoperation in the pigment adding process, the deviation color of the paint is adjusted in time, the types and the content of the pigment to be added can be rapidly determined, the consistency of the colors of the water-based paint in the production process is ensured, and the production quality of products is improved.
(2) According to the invention, the water-based paint is properly stirred to obtain the dry consistency and uniformity of the water-based paint, so that the form conformity of the finished product of the water-based paint is analyzed, the influence of the flaw problem hidden in the solution on the measurement result is avoided, the monitoring precision is increased, the state characteristics of the paint can be better known, the product defects and the failure rate are reduced, and the production and use processes of the paint are effectively controlled.
(3) According to the invention, the water-based paint is coated on experimental boards and various base materials in various environments, and the weather resistance index of the water-based paint is detected, so that the performance of the paint in various environmental conditions is ensured, the quality and reliability of the water-based paint can be more accurately evaluated, and the application of the paint in different fields can be guided according to the characteristics and application requirements of the paint.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the system module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a water-based paint production detection and analysis system based on the internet of things, which comprises: the system comprises a preparation flow control module, a finished product detection control module, an environment test detection module, a material test detection module, a production batch quality evaluation module and a management library. The preparation flow control module is connected with the finished product detection control module, the finished product detection control module is connected with the environment test detection module, the environment test detection module is connected with the material test detection module, the material test detection module is connected with the production batch quality evaluation module, and the management library is respectively connected with the preparation flow control module, the finished product detection control module, the environment test detection module, the material test detection module and the production batch quality evaluation module.
The preparation flow management and control module is used for collecting a production image of the water-based paint, carrying out color recognition on the production image to obtain paint color difference degree, obtaining a paint compensation color card, screening out various compensation pigments, calculating the blending content of the various compensation pigments, analyzing the process parameter execution error rate of each pigment adding step, and feeding back the process parameter execution error rate.
In a specific embodiment of the invention, the blending content of various compensating pigments is calculated by the following steps: and obtaining the formulated addition parameters of the pigment production of the batch, extracting each pigment addition step and the standard pigment type and standard addition content of each pigment addition step from the formulated addition parameters, and obtaining the standard production image of the water-based paint under the formulated addition parameters from a management library.
The formulated addition parameters comprise each pigment addition step, standard pigment types and standard addition contents of each pigment addition step and standard working procedure parameters of each pigment addition step.
Comparing the manufactured image of the water-based paint with a standard production image by using an image processing technology to obtain a paint color difference valueCalculating a paint color difference degree based on the paint color difference value>，/>Indicating the set allowable value of the color difference of the paint,representing a set deviation correction factor corresponding to the paint color difference value, comparing the paint color difference value with a preset paint color difference value threshold, extracting various compensation pigments corresponding to the paint color difference value from a paint compensation color card when the paint color difference value is larger than the preset paint color difference value threshold, and extracting basic compensation duty ratio of various compensation pigments corresponding to the paint color difference value from the paint compensation color card>，/>To compensate for the numbering of the pigment classes +.>
The paint compensation color card comprises various compensation pigments corresponding to various paint color difference value ranges and basic compensation duty ratios of the various compensation pigments.
From analytical formulasObtaining blended contents of various compensating pigments, whereinColor difference of paint>Adding total amount of pigment->To set the deviation control amount, e is a natural constant. The total pigment addition amount is obtained by summing the pigment addition contents corresponding to the pigment addition steps.
In another embodiment of the present invention, the process parameter execution error rate obtaining manner of each pigment adding step is as follows: and (3) extracting a production video of the raw material adding process, identifying each pigment adding step and the pigment type and content corresponding to each pigment adding step from the production video, comparing the pigment type corresponding to each pigment adding step with the standard pigment type corresponding to the pigment adding step, and if the pigment type corresponding to a certain pigment adding step is different from the standard pigment type corresponding to the pigment adding step, obtaining each error adding step by the pigment adding step, and further carrying out early warning feedback on each error adding step.
Extracting standard process parameters of each pigment adding step from the formulated adding parameters, wherein the standard process parameters comprise a proper stirring and mixing time length range and a proper stirring speed range, comparing each pigment adding step with each error adding step, and if a certain pigment adding step is an error adding step, recording the process parameter execution error rate of the pigment adding step as。
Otherwise, the stirring and mixing time and stirring speed of the pigment adding step are obtained and recorded asCalculating the process parameter execution error rate of the pigment addition step +.>Wherein->Indicating the maximum and minimum values of the pigment addition step corresponding to the proper range of the stirring speed,indicating the maximum and minimum values of the appropriate ranges for the pigment addition step corresponding to the stirring and mixing time period,respectively indicates the deviation allowable value of the set time length corresponding to the stirring and mixing time length smaller than the minimum value of the proper range and larger than the maximum value of the proper range,>respectively indicating the allowable value of the set speed deviation corresponding to the stirring speed being larger than the maximum value of the proper range and smaller than the minimum value of the proper range, ">Indicating the deviation correction ratio of the setting>Is a logical and sign.
Counting to obtain the execution error rate of the working procedure parameters of each pigment adding step，/>And further, the error rate of the process parameter execution of each pigment adding step is displayed in a feedback manner.
The stirring and mixing time length of each pigment adding step is the video time length corresponding to the pigment adding step, and the pigment adding step is obtained by extracting production videos.
The stirring speed of each pigment adding step is set by a speed control device mounted on the stirring device.
In the pigment stirring process, the higher the stirring speed is, the more uniform the pigment is dispersed, but if the stirring speed is too high, the dispersing time is too short, and the pigment may not be completely dispersed or generate more bubbles; if the stirring speed is too slow, the dispersing time is too long, the pigment cannot be sufficiently wetted and dispersed uniformly, and the production efficiency may be affected.
According to the invention, the pigment color difference degree of the water-based paint is obtained, the types of the compensating pigments are screened, the blending content of the types of the compensating pigments is calculated based on the misoperation in the pigment adding process, the deviation color of the paint is adjusted in time, the types and the content of the pigment to be added can be rapidly determined, the consistency of the colors of the water-based paint in the production process is ensured, and the production quality of products is improved.
The finished product detection management and control module is used for properly stirring the water-based paint to obtain the dry consistency and uniformity of the water-based paint, so as to analyze the form conformity of the finished product of the water-based paint。
In a specific embodiment of the present invention, the analysis of the product form compliance content of the water-based paint includes: setting stirring time and properly stirring the water-based paint at a set speed, and arranging a force sensing device on a stirring device to detect the measured resistance of each stirring time point in the set stirring timeAnalyzing to obtain the dry consistency of the water-based paintWherein->Indicates the set resistance reference value, < >>Setting deviation compensation factor corresponding to the measured resistance, < ->For stirring time point number, +.>，/>The number of stirring time points was defined.
Collecting state change images of the water-based paint at each stirring time point within a set stirring time period, extracting form standard images of finished water-based paint from a management library, and identifying the contrast of paint colors at each stirring time point from the initial state images of the water-based paint collected at each stirring time point by using an image identification technologyAnd saturation->And the number of coarse coating particles at each stirring time point +.>Obtaining the standard contrast of the paint color in the water paint finished product form standard image according to the same identification technology>And standard saturation->The color degree coincidence coefficient of the water-based paint finished product form corresponding to each stirring time point is obtained by comparisonWherein->Respectively representing the set deviation ratio of contrast and saturation>Respectively represent contrast +.>Analyzing the set deviation value corresponding to the saturation to obtain uniformity of the water-based paint>Wherein->For the maximum number of coarse particles of the coating material, +.>For setting the reference coarse grain quantity->To set a uniformity deviation correction factor.
Analysis of the finished form compliance of Water-based paintWherein->Respectively setting reference values corresponding to the dry consistency and the uniformity of the water-based paint, < >>Respectively setting the weight of the water-based paint corresponding to the dry consistency and the uniformity of the water-based paint>And (5) correcting the factor for the set product form conformity deviation.
According to the invention, the water-based paint is properly stirred to obtain the dry consistency and uniformity of the water-based paint, so that the form conformity of the finished product of the water-based paint is analyzed, the influence of the flaw problem hidden in the solution on the measurement result is avoided, the monitoring precision is increased, the state characteristics of the paint can be better known, the product defects and the failure rate are reduced, and the production and use processes of the paint are effectively controlled.
The environment test detection module is used for taking a small amount of paint to coat on the experimental board and carrying out corresponding performance detection on experimental parameters under various environments.
In a specific embodiment of the present invention, the content of the environmental test detection module includes: and C1, uniformly coating the set water-based paint on a plurality of experimental boards, uniformly dividing the experimental boards to obtain each illumination experimental board and each humidity experimental board, and setting the observation time of the experimental boards.
And C2, carrying out ultraviolet irradiation on each illumination experiment plate according to different illumination intensities, and analyzing to obtain the change index of each illumination experiment plate at the illumination threshold time point.
C3, placing each humidity experiment board in an environment without humidity value, collecting characteristic images of each humidity experiment board at each observation time point, acquiring the foaming size, edge breach width and mold generation amount of each humidity experiment board at each observation time point from the characteristic images of each humidity experiment board at each observation time point by adopting an image recognition technology based on foaming characteristics, edge breach characteristics and mold generation characteristics in the humidity experiment board images stored in a management library, and respectively marking as，/>Number of humidity test board>，/>A number indicating the point in time of observation,analyzing the change index of each humidity experiment board at each observation time pointWherein->Reference variation values are set corresponding to the bubble size, edge breach width and mold formation amount between two observation time points, respectively, < >>Respectively represent +.>Bubble size, edge breach width and mold formation of individual humidity test panels at initial observation time point, +.>To set the deviation correction coefficient.
The foaming size of each humidity experiment board at each observation time point is specifically as follows: based on foaming characteristics in humidity experiment board images stored in a management library, acquiring each sub-bubble of each humidity experiment board at each observation time point from characteristic images of each humidity experiment board at each observation time point by adopting an image recognition technology, extracting each sub-bubble size of each humidity experiment board at each observation time point, and summing to obtain the bubble size of each humidity experiment board at each observation time point.
In another embodiment of the present invention, the analysis mode of the change index of each illumination experiment board at the illumination threshold time point is as follows: measuring the color of each illumination experiment board by using a colorimeter to obtain the chromaticity of the water-based paint at each observation time point corresponding to each illumination experiment board, comparing the chromaticity with the chromaticity of the initial observation time point corresponding to the corresponding illumination experiment board, extracting the minimum chromaticity change value exceeding the set chromaticity change value when the chromaticity change value of a certain illumination experiment board at a certain observation time point exceeds the set chromaticity change value, acquiring the observation time point corresponding to the minimum chromaticity change value, recording the observation time point as an illumination threshold time point, counting the illumination threshold time point corresponding to each illumination experiment board, and extracting the chromaticity of the illumination threshold time point corresponding to each illumination experiment board，/>Number of the light experiment plate is shown, and ∈>。
Detecting corresponding illumination threshold value of each illumination experiment boardIf the coating fission condition exists at the time point, when the coating fission condition exists at the time point corresponding to the illumination threshold value of a certain illumination experiment plate, the total length of the coating cracks of the illumination experiment plate corresponding to the illumination threshold value time point is obtained, and the total length of the coating cracks of each illumination experiment plate corresponding to the illumination threshold value time point is obtained through statisticsAnalyzing the change index of each illumination experiment plate at the illumination threshold time point>Wherein->Indicating the corresponding set reference value of the crack length of the coating +.>Indicating that the crack length of the coating corresponds to the influence evaluation factor, < +.>Indicate->Chromaticity of each light experiment panel at the initial time point.
The detection method for detecting whether the coating fission condition exists at the time point corresponding to the illumination threshold value of each illumination experiment plate comprises the following steps: and (3) collecting plate images of the illumination experiment plates corresponding to the illumination threshold time points, comparing the plate images with various coating fission images in the management library, and if a local image exists in the plate image of the illumination experiment plate corresponding to the illumination threshold time points and the coating fission image of the management library is the same, allowing the illumination experiment plate corresponding to the illumination threshold time points to have coating fission conditions.
The material test detection module is used for coating the water-based paint on various base materials, analyzing the adaptability strength of the water-based paint on various base materials, and further evaluating the weather resistance index of the water-based paint。
In a specific embodiment of the invention, the steps for analyzing the adaptive strength of the water-based paint on various base materials are as follows: coating the water-based paint on various base materials according to the same thickness, wherein the base material type comprises wood, metal, glass and ceramic tile, obtaining various index measurement values of the water-based paint on various base materials, comparing the index measurement values with corresponding index reference values of corresponding base materials in a management library to obtain deviation values of various base materials corresponding to various indexes, and calculating the average value to obtain the average value of the deviation of the corresponding indexes of various base materialsTo obtain the adaptability strength of the water-based paint on various base materials>Wherein->For setting the index deviation reference to be a value, +.>To set the adaptive intensity bias compensation coefficient.
The index items of the wood comprise permeability, drying time and the like; the index items of the metal comprise drying time, corrosion resistance and the like; index items of the glass include transparency, drying time length and the like; the index items of the tile include wear resistance, drying time, and the like.
In another embodiment of the invention, the weather resistance index of the water-based paint is evaluated by the following specific modes: the interval time between the corresponding illumination threshold time point and the initial observation time point of each illumination experiment board is recorded as the tolerance time of each illumination experiment board。
Comparing the change index of each humidity experiment board at each observation time point with the change index limiting value of the corresponding humidity experiment board, and when the humidity experiment board changes at a certain observation time pointWhen the index is larger than the variation index limit value of the corresponding humidity experiment plate, acquiring the minimum variation index larger than the variation index limit value, recording the observation time point corresponding to the minimum variation index as the humidity threshold time point of the humidity experiment plate, counting to obtain the humidity threshold time points of the humidity experiment plates, and further recording the interval time between the humidity threshold time points of the humidity experiment plates and the initial observation time points as the tolerance time of the humidity experiment plates。
Substituting the change index of each illumination experiment board at the illumination threshold time pointAnd the adaptive Strength of Water-based paint on various substrates +.>Evaluation of weather resistance index of Water-based paintWherein->Respectively representing the set reference tolerance time length and the +.>Number indicating the kind of substrate->，/>Indicates the number of substrate types, ">Indicating the number of the light experiment plates->Indicating the number of humidity experimental boards>Indicating the value of the adaptive intensity setting versus.
According to the invention, the water-based paint is coated on experimental boards and various base materials in various environments, and the weather resistance index of the water-based paint is detected, so that the performance of the paint in various environmental conditions is ensured, the quality and reliability of the water-based paint can be more accurately evaluated, and the application of the paint in different fields can be guided according to the characteristics and application requirements of the paint. For example, in the construction, automotive, furniture, and other industries.
The production batch quality evaluation module is used for evaluating the quality grade of the batch of water-based paint by combining the form conformity and weather resistance index of the finished product of the water-based paint.
In a specific embodiment of the invention, the process of evaluating the quality grade of the batch of water-based paint comprises the following steps: will be、/>Substituting the formula to calculate the quality excellent coefficient of the water-based paint of the batch +.>，/>，/>And (3) evaluating the correction coefficient for the quality-improving coefficient correspondence, further comparing the quality-improving coefficient of the batch of water-based paint with the quality-improving coefficient range corresponding to each quality grade in the management library, and screening to obtain the quality grade of the batch of water-based paint.
According to the invention, the quality grade of the water-based paint in the batch is evaluated by combining the form conformity and weather resistance index of the finished product of the water-based paint, and parameters and conditions in the production process can be better controlled by combining the evaluation result, so that the quality of the paint meets the requirements, the production cost is reduced, and the production and the formula of the paint can be optimized to improve the quality and the performance of the paint.
The management library is used for storing paint compensation color cards, standard production images, water paint finished product form standard images and various coating fission images under various formulated addition parameters, foaming characteristics, edge breach characteristics and mold generation characteristics in humidity experiment board images, and various index reference values of various base materials and quality excellent coefficient ranges corresponding to various high-quality grades.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (9)
1. The utility model provides a water paint production detects analytic system based on thing networking which characterized in that, this system includes:
the preparation flow management and control module: the method comprises the steps of collecting a manufacturing image of the water-based paint, carrying out color recognition on the manufacturing image to obtain paint color difference, obtaining a paint compensation color card, screening out various compensation pigments, calculating the blending content of the various compensation pigments, analyzing the process parameter execution error rate of each pigment adding step, and feeding back the process parameter execution error rate;
and a finished product detection management and control module: the method is used for properly stirring the water-based paint to obtain the dry consistency and uniformity of the water-based paint, and further analyzing the form conformity of the finished product of the water-based paint；
Environmental test detection module: the method is used for coating a small amount of paint on an experimental plate and carrying out corresponding performance detection on experimental parameters in various environments;
the material test detection module: for applying aqueous paint to various substrates and analyzing the aqueous paintThe adaptive strength of the coating on various substrates is evaluated, and the weather resistance index of the water-based coating is further evaluated；
Production batch quality evaluation module: the method is used for evaluating the quality grade of the batch of water-based paint by combining the form conformity and weather resistance index of the finished product of the water-based paint;
management library: the method is used for storing paint compensation color cards, standard production images, water paint finished product form standard images and various coating fission images under various formulated addition parameters, foaming characteristics, edge breach characteristics and mold generation characteristics in humidity experiment board images, and various index reference values of various base materials and quality excellent coefficient ranges corresponding to various quality grades.
2. The water-based paint production detection and analysis system based on the internet of things according to claim 1, wherein: the blending content of various compensating pigments is calculated, and the concrete process is as follows:
acquiring formulated addition parameters of pigment production of the batch, extracting each pigment addition step and standard pigment types and standard addition contents of each pigment addition step from the formulated addition parameters, and acquiring standard production images of the water-based paint under the formulated addition parameters from a management library;
comparing the manufactured image of the water-based paint with a standard production image to obtain a paint color difference value, calculating the paint color difference degree based on the paint color difference value, and extracting various compensation pigments corresponding to the paint color difference value and the basic compensation duty ratio of the various compensation pigments from a paint compensation color card，/>To compensate for the numbering of the pigment classes +.>；
From analytical formulasObtaining the blended content of various compensating pigments, wherein +.>Color difference of paint>Adding total amount of pigment->To set the deviation control amount, e is a natural constant.
3. The water paint production detection analysis system based on the internet of things according to claim 2, wherein: the procedure parameter execution error rate acquisition mode of each pigment adding step is as follows:
extracting a production video of a raw material adding procedure, identifying pigment types and content corresponding to each pigment adding step from the production video, and comparing the pigment types corresponding to each pigment adding step with standard pigment types corresponding to the pigment adding step to obtain each error adding step;
extracting standard process parameters of each pigment adding step from the formulated adding parameters, wherein the standard process parameters comprise a proper stirring and mixing time length range and a proper stirring speed range, comparing each pigment adding step with each error adding step, and if a certain pigment adding step is an error adding step, recording the process parameter execution error rate of the pigment adding step as；
Otherwise, the stirring and mixing time and stirring speed of the pigment adding step are obtained and recorded asCalculating the process parameter execution error rate of the pigment addition step +.>Wherein->Indicating the maximum and minimum values of the pigment addition step corresponding to the proper range of the stirring speed,indicating the maximum and minimum values of the appropriate ranges for the pigment addition step corresponding to the stirring and mixing time period,respectively indicates the deviation allowable value of the set time length corresponding to the stirring and mixing time length smaller than the minimum value of the proper range and larger than the maximum value of the proper range,>respectively indicating the allowable value of the set speed deviation corresponding to the stirring speed being larger than the maximum value of the proper range and smaller than the minimum value of the proper range, ">Indicating the deviation correction ratio of the setting>Is a logical AND symbol;
counting to obtain the execution error rate of the working procedure parameters of each pigment adding step，/>，/>Step number is added to the pigment,/->。
4. The water-based paint production detection and analysis system based on the internet of things according to claim 1, wherein: the analysis of the finished product form conformity content of the water-based paint comprises the following steps:
setting stirring time and properly stirring the water-based paint at a set speed, installing a force sensing device on a stirring device to detect the measured resistance of each stirring time point in the set stirring time, and analyzing to obtain the dry consistency of the water-based paint；
Collecting state change images of the water-based paint at each stirring time point within a set stirring time period, extracting form standard images of the water-based paint finished product from a management warehouse, comparing to obtain color degree coincidence coefficients of the water-based paint finished product form corresponding to each stirring time point, obtaining the number of coarse paint particles at each stirring time point, and analyzing to obtain uniformity of the water-based paint；
Analysis of the finished form compliance of Water-based paintWherein->Respectively setting reference values corresponding to the dry consistency and the uniformity of the water-based paint, < >>Respectively setting the weight of the water-based paint corresponding to the dry consistency and the uniformity of the water-based paint>For setting the shape conformity degree deviation of the finished productAnd a difference correction factor.
5. The water-based paint production detection and analysis system based on the internet of things according to claim 1, wherein: the environment test detection module comprises the following components:
c1, uniformly coating a set water-based paint on a plurality of experimental boards, uniformly dividing the experimental boards to obtain each illumination experimental board and each humidity experimental board, and setting the observation time of the experimental boards;
carrying out ultraviolet irradiation on each illumination experiment plate according to different illumination intensities, and analyzing to obtain the change index of each illumination experiment plate at the illumination threshold time point;
c3, placing each humidity experiment board in an environment without humidity value, obtaining the foaming size, edge breach width and mould generation amount of each humidity experiment board at each observation time point, and respectively marking as，/>Number of humidity test board>，/>Number indicating observation time point, +.>Analysis of the index of variation of each humidity test panel at each observation time point +.>WhereinRespectively represent the bubble size and edge between two observation time pointsSetting reference variation value corresponding to the gap width and mold generation amount, < >>Respectively represent +.>Bubble size, edge breach width and mold formation of individual humidity test panels at initial observation time point, +.>To set the deviation correction coefficient.
6. The water paint production detection analysis system based on the internet of things according to claim 5, wherein: the change index analysis mode of each illumination experiment plate at the illumination threshold time point is as follows:
measuring and obtaining the chromaticity of the water-based paint at each observation time point corresponding to each illumination experiment board, comparing the chromaticity with the chromaticity of the initial observation time point corresponding to the corresponding illumination experiment board to obtain the illumination threshold time point corresponding to each illumination experiment board, and extracting the chromaticity of the illumination threshold time point corresponding to each illumination experiment board，/>The number of the light experiment plate is shown,；
detecting whether a coating fission condition exists at a time point corresponding to the illumination threshold value of each illumination experiment plate, when the coating fission condition exists at the time point corresponding to the illumination threshold value of a certain illumination experiment plate, acquiring the total length of the coating cracks of the illumination experiment plate corresponding to the time point corresponding to the illumination threshold value, and counting to obtain the total length of the coating cracks of each illumination experiment plate corresponding to the time point corresponding to the illumination threshold valueAnalyzing the change index of each illumination experiment plate at the illumination threshold time point>Wherein->Indicating the corresponding set reference value of the crack length of the coating +.>Indicating that the crack length of the coating corresponds to the influence evaluation factor, < +.>Indicate->Chromaticity of each light experiment panel at the initial time point.
7. The water-based paint production detection and analysis system based on the internet of things according to claim 6, wherein: the method for analyzing the adaptive strength of the water-based paint on various base materials comprises the following steps of: coating the water-based paint on various base materials according to the same thickness, obtaining various index measurement values of the water-based paint on various base materials, and comparing the index measurement values with corresponding index reference values of corresponding base materials in a management library to obtain the adaptability strength of the water-based paint on various base materials.
8. The water-based paint production detection and analysis system based on the internet of things according to claim 7, wherein: the weather resistance index of the water-based paint is evaluated in the following specific modes:
the interval time between the corresponding illumination threshold time point and the initial observation time point of each illumination experiment board is recorded as the tolerance time of each illumination experiment board；
Comparing the change index of each humidity experiment board at each observation time point with the change index limiting value of the corresponding humidity experiment board, and counting to obtain the humidity threshold time point of each humidity experiment board, thereby obtaining the tolerance time of each humidity experiment board；
Substituting the change index of each illumination experiment board at the illumination threshold time pointAnd the adaptive Strength of Water-based paint on various substrates +.>Evaluation of the weather resistance index of the aqueous coating materials +.>Wherein->Respectively representing the set reference tolerance time length and the +.>Number indicating the kind of substrate->，/>Indicates the number of substrate types, ">Indicating the number of the light experiment plates->Indicating the number of humidity experimental boards>Indicating the value of the adaptive intensity setting versus.
9. The water-based paint production detection and analysis system based on the internet of things according to claim 1, wherein: the quality grade of the batch of water-based paint is evaluated, and the process is as follows: will be、/>Substituting the formula to calculate the quality excellent coefficient of the water-based paint of the batch +.>，/>，/>And (3) evaluating the correction coefficient for the quality-improving coefficient correspondence, further comparing the quality-improving coefficient of the batch of water-based paint with the quality-improving coefficient range corresponding to each quality grade in the management library, and screening to obtain the quality grade of the batch of water-based paint.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311662822.1A CN117347598A (en) | 2023-12-06 | 2023-12-06 | Water paint production detection analysis system based on Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311662822.1A CN117347598A (en) | 2023-12-06 | 2023-12-06 | Water paint production detection analysis system based on Internet of things |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117347598A true CN117347598A (en) | 2024-01-05 |
Family
ID=89365408
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311662822.1A Pending CN117347598A (en) | 2023-12-06 | 2023-12-06 | Water paint production detection analysis system based on Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117347598A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103119923A (en) * | 2010-01-19 | 2013-05-22 | 阿克佐诺贝尔国际涂料股份有限公司 | Method and system for determining colour from an image |
| CN111761955A (en) * | 2020-07-02 | 2020-10-13 | 深圳当纳利印刷有限公司 | Standardized color management method and device for packaging printing paper |
| CN116977116A (en) * | 2023-08-09 | 2023-10-31 | 湖北宇晴防水科技有限公司 | Waterproof material production intelligent monitoring management system based on intelligent manufacturing factory |
-
2023
- 2023-12-06 CN CN202311662822.1A patent/CN117347598A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103119923A (en) * | 2010-01-19 | 2013-05-22 | 阿克佐诺贝尔国际涂料股份有限公司 | Method and system for determining colour from an image |
| CN111761955A (en) * | 2020-07-02 | 2020-10-13 | 深圳当纳利印刷有限公司 | Standardized color management method and device for packaging printing paper |
| CN116977116A (en) * | 2023-08-09 | 2023-10-31 | 湖北宇晴防水科技有限公司 | Waterproof material production intelligent monitoring management system based on intelligent manufacturing factory |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20090157212A1 (en) | System and method of determining paint formula having a effect pigment | |
| CN109030335A (en) | Titanium dioxide primary product weatherability evaluation method | |
| JP2010536046A5 (en) | ||
| EP1975609A1 (en) | Methods for predicting dimensional stability of a wood product based on differential characteristics | |
| CN106501188A (en) | Coating covering power detection method and control methods | |
| CN116977116A (en) | Waterproof material production intelligent monitoring management system based on intelligent manufacturing factory | |
| US8208148B2 (en) | Method for determining a characteristic parameter of a CRP specimen | |
| CA2716927A1 (en) | Method of monitoring a mixture of at least two components | |
| CN117347598A (en) | Water paint production detection analysis system based on Internet of things | |
| CN113546874B (en) | SMT PCB ink color classification method | |
| CN209541904U (en) | The colour photometer of the accurate measurement color of automatic compensation is realized based on environmental change | |
| CN109342335B (en) | Building facing material chromatic aberration analysis method | |
| CN115439437B (en) | Printing and dyeing equipment production data monitoring and analyzing system based on Internet of things | |
| CN112393803B (en) | Method for detecting color sand chromatic aberration | |
| Lyu et al. | Gauge capability studies for attribute data | |
| CN112748141A (en) | Method for detecting selenium element in soda-lime-silica glass | |
| CN109738364B (en) | Method for detecting dispersibility of carbon black | |
| KR20130020868A (en) | The quantitative analysis method of polycarbonate in polycarbonate / acrylonitirle-stryrene-acrylrubber blend polymer using attenuated total reflectance | |
| CN118032678B (en) | Color-changing quality inspection method and system for ink printed matter | |
| EP1864820A2 (en) | Method for controlling print quality | |
| CN111721415A (en) | Color measuring instrument and method for realizing automatic compensation and accurate color measurement based on environmental change | |
| CN112730159B (en) | Method for rapidly and quantitatively detecting color paste bleeding of water-based polymer wall coating material | |
| CN103935120A (en) | Method for setting quality control parameter standards for printing enterprises | |
| KR102660681B1 (en) | Apparatus for measuring oil film thickness of coil strip | |
| CN111091153B (en) | Soft measurement method for bulk of paper sheet |
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 |