CN114778246A - Kaolin preparation device based on Internet of things and control method - Google Patents
Kaolin preparation device based on Internet of things and control method Download PDFInfo
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- CN114778246A CN114778246A CN202210407043.6A CN202210407043A CN114778246A CN 114778246 A CN114778246 A CN 114778246A CN 202210407043 A CN202210407043 A CN 202210407043A CN 114778246 A CN114778246 A CN 114778246A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
- G01N1/286—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q involving mechanical work, e.g. chopping, disintegrating, compacting, homogenising
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J19/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J19/0053—Details of the reactor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J19/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J19/0053—Details of the reactor
- B01J19/0066—Stirrers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J19/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J19/0053—Details of the reactor
- B01J19/0073—Sealings
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- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J19/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J19/18—Stationary reactors having moving elements inside
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N19/00—Investigating materials by mechanical methods
- G01N19/04—Measuring adhesive force between materials, e.g. of sealing tape, of coating
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- 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
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Abstract
The invention relates to a kaolin preparation device based on the Internet of things and a control method, belonging to the technical field of kaolin preparation. When the kaolin coating is prepared, the image information in the preparation process is collected, the image is identified, and when the identification result meets the preset identification result, the kaolin coating is detected, so that whether the coating meets the preset condition or not is judged, if not, the kaolin coating is stirred again, the condition that the kaolin coating does not meet the requirement is effectively avoided being prepared in the preparation process, and the industrialization of the preparation of the kaolin coating is facilitated.
Description
Technical Field
The invention relates to the technical field of kaolin preparation, in particular to a kaolin preparation device based on the Internet of things and a control method.
Background
The kaolin is clay mineral with kaolinite as main component, commonly called as "porcelain clay", and includes kaolinite, nacrite, dickite, halloysite and other minerals. Crystal chemistry of kaoliniteIs of the formula Al4 [ Si4O10］(OH)8It is a 1: 1 type of phyllosilicate mineral whose crystal structure is composed of a silicon-oxygen tetrahedral layer and an aluminum-oxygen octahedral layer, which are connected by hydrogen-oxygen bonds. China has abundant kaolin reserves, 21 hundred million t of ascertained resources account for 9.46 percent of the ascertained resources in the world, is second only to America and India, and is third in the world, and is mainly distributed in Guangdong, Shaanxi, Fujian, Jiangxi, Guangxi and the like. They can be classified into hard kaolin, soft kaolin and sandy kaolin according to their texture, plasticity and sand, and coal-based kaolin and non-coal-based kaolin according to their cause. The kaolin coating is a solid film which is coated on the surface of an object and has certain adhesive force, hardness and flatness, and the solid film is called as a coating film, a coating layer and the like, and is widely used for decoration engineering in the aspect of buildings due to the characteristics of attractive appearance, fire prevention and the like. The current common coating is composed of resin and high molecular compounds, has the characteristics of good viscosity and the like, but can generate harmful gas on the coating to cause harm to human bodies. Meanwhile, the addition of an auxiliary agent containing a volatile organic compound in the preparation process improves the performance of the coating and can generate irritant gas. The inorganic coating has the characteristics of high hardness, high temperature resistance, water resistance, corrosion resistance, good flame retardance and the like, can resist the high temperature of 400-1000 ℃, and is a research hotspot of high-temperature coatings.
However, many problems still exist in the preparation process of the kaolin coating at present, such as poor adhesion of the prepared kaolin coating, easy occurrence of pores on the surface of a coating when the prepared kaolin is coated on a material, and influence on the brushing effect and the service performance of the coating.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a kaolin preparation device based on the Internet of things and a control method.
In order to achieve the purpose, the invention adopts the technical scheme that:
the invention provides a kaolin preparation device based on the Internet of things, which comprises a preparation box body, a mixing module and a testing module, wherein the mixing module comprises a driving motor arranged at the bottom of the preparation box body, the output end of the driving motor is communicated with a first gear, the first gear is at least meshed with two groups of second gears, the second gears are communicated with a rotating shaft, a sealing ring is arranged on the rotating shaft, the sealing ring is arranged on the preparation box body, a plurality of rotating blades are arranged on the rotating shaft, and magnetic coils are arranged on the rotating blades;
the test module comprises a supporting seat arranged on the side part of the preparation box body, a first hydraulic cylinder and a second hydraulic cylinder are arranged on the supporting seat and are arranged in parallel, the output ends of the first hydraulic cylinder and the second hydraulic cylinder are both connected with a detection platform, and a plurality of grooves are formed in the detection platform;
the top of preparation box still is provided with a plurality of linear guide rails, be provided with first telescopic link on the linear guide rail, one of first telescopic link is served and is provided with the test briquetting, be provided with pressure sensor on the test briquetting, with pass through pressure sensor acquires the pressure value that receives to whether the kaolin in the preparation box reaches the predetermined standard according to the pressure value that receives.
Further, in a preferred embodiment of the present invention, a central line of the groove of the detection platform faces a center of the test pressure block, and the test pressure block is provided with a plurality of scraping sheets.
Further, in a preferred embodiment of the present invention, a second telescopic rod is further disposed on the linear sliding rail, a telescopic portion of the second telescopic rod is disposed inside the outer casing, and the inside of the second telescopic rod is a hollow structure.
Further, in a preferred embodiment of the present invention, one end of the second telescopic rod is further connected to a vacuum suction block, and one end of the vacuum suction block is connected to an air duct.
Further, in a preferred embodiment of the present invention, the vacuum suction block is provided with a plurality of through holes and a cavity portion, the through holes are all collected in the cavity portion, and the cavity portion is provided with channels, and the channels are spirally distributed on the upper portion of the vacuum suction block in a vertical direction so as to connect the air guide tube through the channels.
Further, in a preferred embodiment of the present invention, an infrared imager is further disposed on a side portion of the preparation box, so as to obtain image information in the preparation box through the infrared imager, and start the test module and the mixing module according to the image information.
Further, in a preferred embodiment of the present invention, the air duct penetrates through the inside of the second telescopic rod, and the air duct is communicated with an external air pump.
Further, in a preferred embodiment of the present invention, the top of the preparation box body is provided with a plurality of solution tanks, one end of each solution tank is connected with a control valve, and the other end of each control valve is communicated with the injection pipe.
The invention provides a control method of a kaolin preparation device based on the Internet of things, which is applied to any one of the kaolin preparation devices based on the Internet of things and comprises the following steps:
acquiring an image in the preparation box body through an infrared imager;
establishing an image recognition model based on a neural network, and importing a pre-trained image into the recognition model to obtain a trained image recognition model;
leading the image in the preparation box body into the trained image recognition model to obtain a recognition result;
comparing the recognition result with a preset recognition result to obtain a deviation rate;
and judging whether the deviation rate is greater than a preset deviation rate threshold value or not, and if so, starting the test module.
Further, in a preferred embodiment of the present invention, the control method for the internet-of-things-based kaolin preparation device is characterized by further comprising the following steps:
acquiring a pressure value to which a test pressing block bears when scraping off a kaolin coating on a detection platform through a pressure sensor;
recording the pressure values, establishing a removed data model, and leading the pressure values of the test pressure into the removed data model to obtain a plurality of test pressure values from which preset data are removed;
calculating an average test pressure value based on the test pressure value without the preset data, and taking the average test pressure value as a coating adhesion test value;
and judging whether the coating adhesion force test value is smaller than a preset adhesion force value, and if so, sending a control signal to start the mixing system.
The invention solves the defects in the background art, and has the following beneficial effects:
the kaolin coating preparation device is provided with the testing module, the image is identified by collecting image information in the preparation process when the kaolin coating is prepared, and the kaolin coating is detected when the identification result meets the preset identification result, so that whether the coating meets the preset condition is judged, and if not, the kaolin coating is stirred again, so that the preparation of the kaolin coating which does not meet the requirement in the preparation process can be effectively avoided, the preparation efficiency is improved, and the kaolin coating preparation industrialization is facilitated. The invention is provided with the mixing module, can fully mix the reacted substances, is provided with the plurality of rotating blades, can drive the plurality of rotating blades by utilizing one driving motor, has simple design, can achieve better mixing effect, improves the utilization efficiency of the driving motor, and is beneficial to the heat dissipation of the driving motor because the driving motor and the sealing ring are arranged at the outer side of the preparation box body, thereby prolonging the service life of the driving motor and meeting the use requirement of the driving motor for long-time work. And the invention is provided with the infrared imager, can obtain the image information in the preparation course through the infrared imager, thus judge whether the picture in the test course has obvious space on the detection platform, if there is not long enough to explain the time of stirring, need to carry on longer stirring time, make the coating mix more evenly, improve and brush the back coating and more level and better performance.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that drawings of other embodiments can be obtained according to the drawings without creative efforts.
Fig. 1 shows a schematic overall structure diagram of a kaolin preparation device based on the internet of things;
FIG. 2 shows a schematic diagram of the internal structure of a kaolin preparation device based on the Internet of things;
FIG. 3 shows a schematic diagram of a partial structure of a test module;
FIG. 4 shows a schematic diagram of a partial structure of a kaolin preparation device based on the Internet of things;
FIG. 5 shows a schematic of the structure of a test compact;
FIG. 6 illustrates a schematic cross-sectional view of a portion of an Internet of things-based kaolin preparation device;
FIG. 7 is a partial schematic view of a hybrid module;
FIG. 8 is a schematic cross-sectional view of a seal ring;
FIG. 9 illustrates a method flow diagram of a method of controlling an Internet of things-based kaolin preparation device;
fig. 10 shows a partial method flowchart of a control method of an internet of things-based kaolin preparation device.
In the figure:
1. the method comprises the steps of preparing a box body, 2, a mixing module, 3, a testing module, 201, a driving motor, 202, a first gear, 203, a second gear, 204, a rotating shaft, 205, a sealing ring, 206, a rotating blade, 301, a supporting seat, 302, a first hydraulic cylinder, 303, a second hydraulic cylinder, 304, a detection platform, 401, a linear sliding rail, 402, a first telescopic rod, 403, a testing pressing block, 404, a pressure sensor, 405, a scraping sheet, 406, a second telescopic rod, 407, an outer shell, 408, a vacuum suction block, 409, an air duct, 410, an infrared imager, 411, a solution box, 412, a control valve, 413 and an injection tube.
Detailed Description
In order that the above objects, features and advantages of the present invention may be more clearly understood, the present invention will be further described in detail with reference to the accompanying drawings and detailed description, which are simplified in illustration only for the purpose of illustrating the basic structure of the present invention and thus only show the structure related to the present invention, and it should be noted that the embodiments and features of the embodiments may be combined with each other in the present application without conflict.
In the description of the present application, it is to be understood that the terms "central," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship indicated in the drawings for convenience in describing the present application and to simplify the description, but are not intended to indicate or imply that the device or element so referred to must have a particular orientation, be constructed in a particular orientation, and be operated in a particular manner, and thus are not to be construed as limiting the scope of the present application. Furthermore, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the invention, the meaning of "a plurality" is two or more unless otherwise specified.
In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art through specific cases.
To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
The invention provides a kaolin preparation device based on the Internet of things, which comprises a preparation box body 1, a mixing module 2 and a testing module 3, wherein the mixing module 2 comprises a driving motor 201 arranged at the bottom of the preparation box body 1, the output end of the driving motor 201 is communicated with a first gear 202, the first gear 202 is meshed and connected with at least two groups of second gears 203, the second gears 203 are communicated with a rotating shaft 204, a sealing ring 205 is arranged on the rotating shaft 204, the sealing ring 205 is arranged on the preparation box body 1, a plurality of rotating blades 206 are arranged on the rotating shaft 204, and magnetic coils are arranged on the rotating blades 206;
it should be noted that the driving motor 201 is used to drive the first gear 202, and the first gear 203 can be meshed with the plurality of second gears 203, so that the second gears 203 drive the rotating shaft 204, and the rotating blades 206 arranged on the rotating shaft 204 can rotate, so that the driving motor 201 can be used to drive the plurality of rotating blades 206 to prepare the kaolin coating in the preparation box 1, thereby improving the mixing effect in the preparation process, and the driving motor can be used to drive the plurality of rotating blades 206, as shown in the figure, the second gear 203 can be further connected to the side end of the second gear 203, and so on, so that the utilization efficiency of the driving motor 201 can be fully utilized. On the other hand, since the driving motor 201 is disposed outside the preparation box 1, heat dissipation of the driving motor 201 is facilitated, and thus the service life of the driving motor 201 is prolonged. And this device is provided with sealing washer 205, can avoid preparing the condition that the inside kaolin coating of box 1 leaked effectively and appear, in addition, be provided with magnetic coil on rotating vane 206, magnetic coil can be heat energy with electric energy conversion to can heat the inside kaolin coating of preparation box 1, owing to set up a plurality of rotating vane 206, make the heat can evenly and carry out the heat exchange with the inside kaolin coating of preparation box 1 fast, thereby improve the speed of heat exchange, make the reaction rate between the reactant increase, thereby improve the preparation efficiency of kaolin coating.
The test module 3 comprises a support base 301 arranged on the side part of the preparation box body 1, a first hydraulic cylinder 302 and a second hydraulic cylinder 303 are arranged on the support base 301, the first hydraulic cylinder 302 and the second hydraulic cylinder 303 are arranged in parallel, the output ends of the first hydraulic cylinder 302 and the second hydraulic cylinder 303 are both connected with a detection platform 304, and a plurality of grooves are arranged on the detection platform 304;
it should be noted that, on one hand, the first hydraulic cylinder 302 and the second hydraulic cylinder 303 may be used to communicate with the detection platform 304, and the first hydraulic cylinder 302 and the second hydraulic cylinder 303 may be used to drive, so that the test operation may be performed alternately, and the actual condition of the coating on the detection platform 304 may be measured for multiple times, at this time, the image information of the coating on the detection platform coated in the groove of the detection platform 304 may be obtained by the infrared imager, at this time, the coating image in the groove may be compared with the preset coating image, and the process may be identified by the neural network, for example, a convolutional neural network, a deep learning algorithm, a machine learning algorithm, etc. may be used to identify whether there is an obvious pore surface layer in the coating image, where the preset coating image is a normal surface layer without obvious pores, and when the coating image is a surface layer with obvious pores, the insufficient time in the process of preparing the kaolin coating can be judged, so that a control system (such as a computer) is used for sending a continuous mixing instruction, and a mixing module 2 is continuously started. When the water content is not in accordance with the water content, more pores can be remained on the coating surface of the coating, and the styrene-acrylic emulsion is used as a manufacturing material, so that the pores are remained on the coating surface, and the styrene-acrylic emulsion has good film forming property, so that bubbles can not float upwards and break in the stirring process, the pores are generated on the coating surface after coating, the coating effect and the service performance of the coating are influenced, the detection function is added in the manufacturing process, the coating can be stirred continuously in time, and the generation of the pores generated on the coating surface after coating is effectively reduced, so that the coating is in accordance with the use in the fields of building production, industrial production and the like.
The top of the preparation box body 1 is also provided with a plurality of linear guide rails 401, a first telescopic rod 402 is arranged on the linear guide rails 401, one end of the first telescopic rod 402 is provided with a test pressing block 403, a pressure sensor 404 is arranged on the test pressing block 403, so that the pressure sensor 404 can obtain the pressure value received by the pressure sensor 404, and whether the kaolin in the preparation box body 1 reaches the preset standard or not can be judged according to the pressure value received by the pressure sensor 404.
Further, in a preferred embodiment of the present invention, a plurality of solution tanks 411 are disposed on the top of the preparation tank 1, one end of each solution tank 411 is connected to a control valve 412, and the other end of each control valve 412 is connected to a flow injection pipe 413.
It should be noted that, under the action of the linear guide 401, the second telescopic rod 406 moves to a predetermined position, and the detection platform 304 may be provided with a displacement sensor, so that the second telescopic rod 406 can move to the predetermined position, and therefore, the vacuum suction block 408 is used to suck a part of the paint in the preparation box 1, and the vacuum suction block 408 is moved to a designated position on the detection platform 304 to place the sucked paint on the detection platform 304, so that the arc-shaped side portion of the vacuum suction block 408 faces the detection platform 304The coating on the detection platform 304 is uniformly coated in the groove of the detection platform 304, after the coating is kept still for a period of time, after the coating is dried, the first telescopic rod 402 is used for extending and moving to a coating position on the detection platform, the distance between the coating surface and the scraping sheet 405 is smaller than a preset standard distance, and the distance between the contact surface between the coating surface and the scraping sheet 405 is inconsistent, so that the scraping force applied to the coating is inconsistent, that is, the pressure applied to the pressure sensor is inconsistent, so as to determine whether the adhesive force of the kaolin coating attached to the preset material meets the preset adhesive force according to the pressure value, when the control system determines that the adhesive force of the kaolin coating attached to the preset material does not meet the preset adhesive force, the water content in the preparation process of the kaolin coating is insufficient or excessive, therefore, according to the actual condition of the adhesive force, water is injected into the water solution in the solution tank 411 by opening the control valve 412 through the injection pipe 413, and the adhesive force strength of the prepared kaolin coating attached to the preset material is in accordance with the actual requirement. Wherein the adhesive force intensity can be calculated according to a formula
And calculating to obtain the adhesive force, wherein K is the adhesive force strength, F is the actual value tested by the pressure sensor, H is the thickness of the coating, and S is the area value of the vacuum suction block when the vacuum suction block is in contact with the detection platform.
Further, in a preferred embodiment of the present invention, the center line of the groove of the detecting platform 304 is opposite to the center of the testing press block 403, and a plurality of scraping sheets 405 are disposed on the testing press block 403.
It should be noted that the central line of the groove of the detection platform 304 is directly opposite to the center of the test pressing block 403, which is beneficial to that the test pressing block 403 can move to a designated position area each time, and an alignment basis is provided for detection.
Further, in a preferred embodiment of the present invention, the linear sliding rail 401 is further provided with a second telescopic rod 406, the telescopic portion of the second telescopic rod 406 is disposed inside the outer housing 407, and the inside of the second telescopic rod 406 is a hollow structure.
Further, in a preferred embodiment of the present invention, one end of the second telescopic rod 406 is further connected to a vacuum suction block 408, and one end of the vacuum suction block 408 is connected to an air duct 409.
Further, in a preferred embodiment of the present invention, the vacuum suction block 408 is provided with a plurality of through holes and a cavity portion, the through holes are collected in the cavity portion, and the cavity portion is provided with a channel, and the channel is spirally distributed on the upper portion of the vacuum suction block in the vertical direction so as to connect the air duct 409 through the channel.
It should be noted that, an external air pump is used to suck air in the vacuum suction block 408, so that a negative pressure relationship is formed between the vacuum suction block 408 and the pressure inside the preparation tank 1, the vacuum suction block 408 is used to suck a part of the coating from the preparation tank 1, the coating enters the cavity portion through the through hole, since the through hole is spirally distributed on the upper portion of the vacuum suction block 408 in the vertical direction, and the proximity sensor can be arranged in the channel, when the proximity sensor detects that the coating exists in the channel, the air pump keeps a certain air pump amount, so that a certain amount of coating can be sucked into the cavity portion each time, when the coating is coated on the detection platform 304, the coating in the cavity portion flows out from the through hole and is placed on the groove surface of the detection platform 304, and the coating on the groove surface is uniformly coated in the groove by the arc surface of the vacuum suction block 408, therefore, the kaolin coating can be detected in real time in the process of preparing the kaolin coating, and when the property of the prepared kaolin does not meet the preset standard, the kaolin coating is adjusted according to actual conditions, such as insufficient water content, short stirring time and the like, so that the preparation process in the preparation of the kaolin coating can be optimized, the preparation quality of the kaolin coating is ensured, the incomplete preparation condition is effectively avoided, the condition of re-processing is avoided, the preparation time is saved, and the preparation efficiency is improved.
Further, in a preferred embodiment of the present invention, an infrared imager 410 is further disposed on a side of the preparation box, so as to obtain image information in the preparation box 1 through the infrared imager 410, and to start the test module 3 and the mixing module 2 according to the image information.
It should be noted that, on the other hand, the image in the preparation box is obtained by the infrared imager 410, for example, it can be identified whether there is an obvious pore surface layer in the coating image by using the convolutional neural network, the deep learning algorithm, the machine learning algorithm, etc., when the identification result meets the standard for detecting the coating, the result can be identified by the above method, for example, the coating in the shot image has no obvious bubble phenomenon, no obvious pore on the coating surface, etc., when the result is identified, the test module is started, at this time, the external air pump is used to suck the air in the vacuum suction block 408, so that the vacuum suction block 408 and the pressure inside the preparation box 1 form a negative pressure relationship, the vacuum suction block 408 is used to suck a part of the coating from the preparation box 1, the coating enters the cavity through the through hole, when the coating is painted on the detection platform, and (3) the paint of the cavity part flows out of the through hole and is placed on the groove surface of the detection platform, and the paint of the groove surface is uniformly coated in the groove of the detection platform by utilizing the arc-shaped surface of the vacuum suction block.
Further, in a preferred embodiment of the present invention, the air duct 409 penetrates through the inside of the second telescopic rod 406, and the air duct 409 is connected to an external air pump.
The invention provides a control method of a kaolin preparation device based on the Internet of things, which is applied to any one of the kaolin preparation devices based on the Internet of things, and comprises the following steps:
s102, acquiring an image in the preparation box body through an infrared imager;
s104, establishing an image recognition model based on a neural network, and importing a pre-trained image into the recognition model to obtain a trained image recognition model;
s106, importing the images in the preparation box body into the trained image recognition model to obtain a recognition result;
s108, comparing the identification result with a preset identification result to obtain a deviation ratio;
and S110, judging whether the deviation rate is greater than a preset deviation rate threshold value, and if so, starting the test module.
It should be noted that, the image in the preparation box is obtained by the infrared imager, for example, it can be identified whether there is an obvious pore surface layer in the coating image by using convolutional neural network, deep learning algorithm, machine learning algorithm, etc., when the identification result meets the standard for detecting the coating, the result can be identified by the above method, for example, the coating in the shot image has no obvious bubble phenomenon, no obvious pore on the coating surface, etc., when the result is identified, the test module is started, the air in the vacuum suction block is sucked by the external air pump, so that the vacuum suction block and the pressure inside the preparation box form a negative pressure relationship, the vacuum suction block sucks part of the coating from the preparation box, the coating enters the cavity through the through hole, when the coating is coated on the detection platform, the coating in the cavity flows out from the through hole and is placed on the groove surface of the detection platform, the arc-shaped surface of the vacuum suction block is used for uniformly coating the coating on the surface of the groove in the groove of the detection platform, the image information of the coating coated on the detection platform in the groove of the detection platform can be acquired through an infrared imager, the coating image in the groove can be compared with a preset coating image, the process can be identified through a neural network, for example, whether an obvious pore surface layer exists in the coating image can be identified through a convolutional neural network, a deep learning algorithm, a machine learning algorithm and the like, the preset coating image is a normal surface layer without obvious pores, when the coating image is a surface layer with the obvious pores, the insufficient time in the process of preparing the kaolin coating can be judged, a control system is used for sending a continuous mixing instruction, a mixing module is continuously started, and the mode can effectively avoid the phenomena of rough particles in the preparation of the kaolin and the phenomena of coating on the preset material The generation of the pore phenomenon ensures that the preparation quality of the coating is higher in the process of preparing the kaolin coating, and the coating which is coated on the preset material by the kaolin coating is smoother and has better performance.
Further, in a preferred embodiment of the present invention, the control method for the kaolin preparation apparatus based on the internet of things is characterized by further comprising the following steps:
s202, acquiring a pressure value to which a test pressing block is subjected when a kaolin coating on a detection platform is scraped through a pressure sensor;
s204, recording the pressure values, establishing a removed data model, and introducing the pressure values subjected to the test pressure into the removed data model to obtain a plurality of test pressure values from which preset data are removed;
s206, calculating an average test pressure value based on the test pressure value without the preset data, and taking the average test pressure value as a coating adhesion test value;
and S208, judging whether the coating adhesion force test value is smaller than a preset adhesion force value, and if so, sending a control signal to start a mixing system.
It should be noted that the elimination data model includes a trend removing algorithm, drift nodes can be removed by using the trend removing algorithm, the drift nodes can be understood as detection nodes with a large deviation from experimental data, so as to obtain effective test pressure values, and since the vacuum suction block can suck the same amount of paint each time, the test pressure values obtained by testing can be always close to each other, and multiple groups of detection can be performed once, so that the accuracy of testing the paint can be improved, an average test pressure value can be calculated according to the effective test pressure values, and the adhesive force strength can be calculated according to a calculation formula
Is calculated to obtain whereinKIn order to enhance the adhesive strength,Ffor the actual value measured by the pressure sensor,Hin order to be the thickness of the coating,Sthe area value of the vacuum suction block when the vacuum suction block is contacted with the detection platform. When the coating adhesion test value is less than the preset adhesion strengthAt the moment, the mixing system is continuously started, the driving motor is utilized to drive the first gear, the first gear can be meshed with the plurality of second gears, the second gears drive the rotating shaft, the rotating blades arranged on the rotating shaft can rotate, the driving motor can be used to drive the plurality of rotating blades to continuously prepare the kaolin coating in the preparation box body, the scraping force applied to the coating is inconsistent because the distance between the surface of the coating and the contact surface between the scraping blades is inconsistent, namely the pressure applied to the pressure sensor is inconsistent, so that whether the adhesive force of the kaolin coating attached to the preset material meets the preset adhesive force or not is determined according to the pressure value, and when the control system determines that the adhesive force of the kaolin coating attached to the preset material does not meet the preset adhesive force, the water content in the preparation process of the kaolin coating is insufficient or excessive, therefore, water is injected into the water with proper amount through the flow injection pipe by opening the control valve through the water solution in the solution tank according to the actual condition of the adhesive force, so that the adhesive force strength of the prepared kaolin coating attached to the preset material is in line with the actual requirement.
In summary, on one hand, the kaolin coating preparation method is provided with the test module, the image is identified by collecting the image information in the preparation process when the kaolin coating is prepared, and when the identification result meets the preset identification result, the kaolin coating is detected, so that whether the coating meets the preset condition is judged, and if not, the kaolin coating is stirred again, so that the preparation of the kaolin coating which does not meet the requirement in the preparation process can be effectively avoided, the preparation efficiency is improved, and the industrialization of the kaolin coating preparation is facilitated.
On the other hand, the mixing module is arranged, the reaction substances can be fully mixed, the rotating blades are arranged, one driving motor can be used for driving the rotating blades, the design is simple, a better mixing effect can be achieved, the utilization efficiency of the driving motor is improved, and on the other hand, the driving motor and the sealing ring are arranged on the outer side of the preparation box body, so that the heat dissipation of the driving motor is facilitated, the service life of the driving motor can be prolonged, and the use requirement of the driving motor for long-time work can be met. The infrared imager is arranged, and image information in the preparation process can be acquired through the infrared imager, so that whether obvious gaps exist in the image in the test process on the detection platform or not is judged, if the obvious gaps exist, the stirring time is not long enough, and longer stirring time is needed, so that the coating is mixed more uniformly, and the smoothness and better performance of the coated coating are improved.
Furthermore, it should be understood that although the present specification describes embodiments, not every embodiment includes only a single embodiment, and such description is for clarity purposes only, and it is to be understood that all embodiments may be combined as appropriate by one of ordinary skill in the art to form other embodiments as will be apparent to those of skill in the art from the description herein.
While the preferred embodiments of the present invention have been described, it will be apparent to those skilled in the art from this disclosure that various changes and modifications can be made without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and the technology must be determined in accordance with the scope of the claims.
Claims (10)
1. A kaolin preparation device based on the Internet of things comprises a preparation box body, a mixing module and a testing module, and is characterized in that the mixing module comprises a driving motor arranged at the bottom of the preparation box body, the output end of the driving motor is communicated with a first gear, the first gear is at least meshed with two groups of second gears, the second gears are communicated with a rotating shaft, a sealing ring is arranged on the rotating shaft, the sealing ring is arranged on the preparation box body, a plurality of rotating blades are arranged on the rotating shaft, and magnetic coils are arranged on the rotating blades;
the test module comprises a supporting seat arranged on the side part of the preparation box body, a first hydraulic cylinder and a second hydraulic cylinder are arranged on the supporting seat and are arranged in parallel, the output ends of the first hydraulic cylinder and the second hydraulic cylinder are both connected with a detection platform, and a plurality of grooves are formed in the detection platform;
the top of preparation box still is provided with a plurality of linear guide rails, be provided with first telescopic link on the linear guide rail, one of first telescopic link is served and is provided with the test briquetting, be provided with pressure sensor on the test briquetting, in order to pass through pressure sensor acquires the pressure value that receives to whether the kaolin in the preparation box reaches the preset standard according to the pressure value that receives.
2. The internet-of-things-based kaolin preparation device according to claim 1, wherein a groove center line of the detection platform is opposite to the center of the test pressing block, and the test pressing block is provided with a plurality of scraping sheets.
3. The kaolin preparation device based on the Internet of things as claimed in claim 1, wherein a second telescopic rod is further arranged on the linear sliding rail, the telescopic portion of the second telescopic rod is arranged inside the outer shell, and the inside of the second telescopic rod is of a hollow structure.
4. The kaolin preparation device based on the Internet of things as claimed in claim 3, wherein one end of the second telescopic rod is further connected with a vacuum suction block, and one end of the vacuum suction block is connected with an air guide tube.
5. The kaolin preparation device based on the Internet of things according to claim 4, wherein the vacuum suction block is provided with a plurality of through holes and a cavity part, the through holes are collected in the cavity part, the cavity part is provided with a channel, and the channel is spirally distributed on the upper part of the vacuum suction block in the vertical direction so as to be connected with the air guide tube through the channel.
6. The internet-of-things-based kaolin preparation device according to claim 1, wherein an infrared imager is further arranged on the side of the preparation box body, so that image information in the preparation box body can be acquired through the infrared imager, and the test module and the mixing module can be started according to the image information.
7. The Internet of things-based kaolin preparation device according to claim 4, wherein the air guide tube penetrates through the inside of the second telescopic rod, and the air guide tube is communicated with an external air pump.
8. The internet-of-things-based kaolin preparation device according to claim 5, wherein a plurality of solution tanks are arranged at the top of the preparation tank body, one end of each solution tank is connected with a control valve, and the other end of each control valve is communicated with an injection pipe.
9. The control method of the kaolin preparation device based on the Internet of things is characterized by being applied to the kaolin preparation device based on the Internet of things as claimed in any one of claims 1 to 8, and comprising the following steps:
acquiring an image in the preparation box body through an infrared imager;
establishing an image recognition model based on a neural network, and importing a pre-trained image into the recognition model to obtain a trained image recognition model;
leading the image in the preparation box body into the trained image recognition model to obtain a recognition result;
comparing the recognition result with a preset recognition result to obtain a deviation rate;
and judging whether the deviation rate is greater than a preset deviation rate threshold value or not, and if so, starting the test module.
10. The control method for the kaolin preparation device based on the internet of things according to claim 9, further comprising the steps of:
acquiring a pressure value to which a test pressing block bears when scraping off a kaolin coating on a detection platform through a pressure sensor;
recording the pressure values, establishing a removed data model, and introducing the pressure values subjected to the test pressure into the removed data model to obtain a plurality of test pressure values from which preset data are removed;
calculating an average test pressure value based on the test pressure value after the preset data are removed, and taking the average test pressure value as a coating adhesion test value;
and judging whether the coating adhesion force test value is smaller than a preset adhesion force value, and if so, sending a control signal to start a mixing system.
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