Intelligent control system for rotational molding process of buoy

Abstract

The invention relates to the technical field of intelligent control, in particular to a buoy rotational molding process intelligent control system which comprises a material injection data detection module, a material injection data analysis module, a temperature detection module, a temperature analysis module, a rotating speed control module, an appearance data detection module, an appearance data analysis module and a management database. According to the system, the material injection conformity degree of each roller mold is obtained through material injection data analysis of each roller mold, then the material injection data is adjusted, the regulation and control rotating speed of each roller mold is obtained by combining the temperature uniformity degree of the inner wall of each roller mold and raw material quantity analysis, and then the rotating speed of each roller mold is regulated and controlled; the appearance qualification degree of the finished buoy is obtained through analysis according to the appearance data of the finished buoy, then the qualification condition of the finished buoy is obtained through analysis and fed back to the system, the condition that the product quality does not reach the standard can be found in time, the defective rate can be reduced, the product percent of pass is improved, and the quality risk is reduced.

Description

Technical Field

[0001] The invention relates to the field of intelligent control technology, in particular to an intelligent control system for a buoy rotational molding process. Background Art

[0002] A buoy is a hollow device with buoyancy, commonly used in water facilities such as ships, docks, pontoons, and floating docks. It plays the role of supporting objects so that they can float on the water. Buoys are usually made of plastic, rubber, metal and other materials and have good buoyancy and durability.

[0003] In practical applications, buoys are widely used in the fields of navigation assistance, aquaculture, water entertainment, etc. Buoys of different materials and structures are suitable for use in different environments and requirements, such as seawater buoys, freshwater buoys, high-strength buoys, etc.

[0004] Buoy rotational molding is a commonly used plastic product production process, mainly used to manufacture buoy products of various sizes and shapes, such as water buoys, ship buoys, fishing buoys, etc. This molding process is usually completed by heating and melting plastic particles, injecting them into the molding mold, and then cooling and solidifying them.

[0005] The patent name is a technical solution published in a Chinese patent entitled "A rotational molding system and its processing technology" (patent number is 202110560539.2). This solution realizes the fully automatic process of the rotational molding system from the initial weighing, feeding, and secondary feeding of powder materials by setting a feeding mechanism and a feeding mechanism on the mold, avoiding the problem of large weight error of powder materials and low efficiency caused by manual weighing each time. However, there are still some shortcomings, which are specifically manifested in the following aspects: First, this solution only involves the weighing and feeding of powder materials, and ignores the attention to the injection speed and injection time during the injection process, which may lead to deviations from the same standard, resulting in unstable product quality and affecting product performance and service life.

[0006] Second, the solution does not involve the link of controlling the rotation speed of the roller mold according to the amount of raw materials. Different amounts of raw materials may require different roller mold rotation speeds to ensure the best molding effect. The lack of this link may lead to unstable molding quality and product quality problems. Summary of the invention

[0007] In order to overcome the shortcomings of the background technology, an embodiment of the present invention provides an intelligent control system for a float rotational molding process, which can effectively solve the problems involved in the above-mentioned background technology.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides an intelligent control system for a float rotational molding process, including: an injection data detection module for detecting the injection data of each roller mold, the injection data including the injection speed and the injection time.

[0009] The injection data analysis module is used to obtain the injection compliance degree of each roller mold according to the injection data analysis of each roller mold, and then adjust the injection data of each roller mold with unqualified injection.

[0010] The temperature detection module is used to scan each roller mold through thermal imaging to obtain a thermal map of each area of ​​the inner wall of each roller mold, and then obtain the temperature of each pixel point in each area of ​​the inner wall of each roller mold.

[0011] The temperature analysis module is used to obtain the temperature uniformity of the inner wall of each roller mold by analyzing the temperature of each pixel point in each area of ​​the inner wall of each roller mold.

[0012] The speed control module is used to detect the amount of raw materials in each roller mold, and analyze the temperature uniformity of the inner wall of each roller mold to obtain the control speed of each roller mold, and thereby control the speed of the roller mold.

[0013] The appearance data detection module is used to detect the appearance data of the finished float, and the appearance data includes size conformity, smoothness, and bubble density.

[0014] The appearance data analysis module is used to analyze the appearance data of the finished buoy to obtain the appearance qualification of the finished buoy, and then analyze the qualification of the finished buoy and feed it back to the system.

[0015] A management database is used to store the color categories to which each chromaticity value range belongs.

[0016] Preferably, the specific analysis method of the injection data detection module is: monitor the injection time of each roller mold respectively, and record it as t f , where f represents the number of the fth roller mold, f = 1, 2, ..., g, the injection time of each roller mold is divided into several equal-length monitoring periods according to the set time, and the weight of the material injected into each roller mold in each monitoring period is weighed by a weight sensor, recorded as λ fx , where x represents the number of the xth monitoring period, x=1,2,...,y, and the set duration is recorded as t', through the formula Get the injection speed v of each roller mold f .

[0017] Preferably, the specific analysis method of the injection data analysis module is: respectively read the injection speed v of each roller mold f, injection time t f , substituting it into the formula Get the injection conformity degree α of each roller mold f , where v0 and t0 represent the set standard values ​​of injection speed and injection time respectively, φ1 and φ2 represent the weight factors of the set injection speed and injection time respectively, and e is a natural constant, which is compared with the preset injection compliance threshold. If the injection compliance of a roller mold is greater than or equal to the preset injection compliance threshold, it means that the injection compliance of the roller mold meets the standard. On the contrary, it means that the injection compliance of the roller mold does not meet the standard. The injection data of the roller mold needs to be adjusted, and all roller molds whose injection compliance does not meet the standard are counted and recorded as roller molds with unqualified injection.

[0018] Preferably, the specific method for adjusting the injection data of the roller mold is: reading the injection speed and injection time of each roller mold, and screening out the injection speed and injection time of each roller mold with unqualified injection, which are recorded as v and v respectively. j ,t j , where j represents the number of the jth roller mold with unqualified injection, j = 1, 2, ..., c, through the formula Δv j =v0-v j , Δt j =t0-t j The injection speed and injection time adjustment values ​​of each roller mold with unqualified injection are obtained, so as to adjust the injection data of each roller mold with unqualified injection.

[0019] Preferably, the specific analysis process of the temperature detection module is as follows: In the first step, the inner wall of the roller mold is divided into a number of regions of equal area, and each region of the inner wall of each roller mold is scanned by a thermal imaging camera, which is recorded as a heat map of each region of the inner wall of each roller mold, and the color category to which each chromaticity value range belongs is extracted from the management database, and at the same time, the chromaticity value of each pixel point of the heat map of each region of the inner wall of each roller mold is detected, which is recorded as the chromaticity value ε of each pixel point of the heat map of each region of the inner wall of each roller mold. fim , i represents the number of the i-th area, i=1,2,...,n, m represents the number of the m-th pixel, m=1,2,...,q, and matches it with the color category of each chromaticity value range to obtain the color category of each pixel point in each area of ​​the inner wall of each roller mold.

[0020] The second step is to use the formula Get the average chromaticity value of the thermal map of the inner wall of each roller mold Where q represents the number of pixels, n represents the number of regions, and the pixels are matched with the color categories of each chromaticity value range to obtain the color category of the average chromaticity value of the heat map of the inner wall of each roller mold, and further compared with the color category of the chromaticity value of each pixel in the heat map of each region of the inner wall of each roller mold, and the pixels whose chromaticity value belongs to the same color category as the average chromaticity value of the heat map of the inner wall of the corresponding roller mold are screened and recorded as pixels of the same color category. The heat map of each region of the inner wall of each roller mold is binarized, and the temperature of the pixel points of the same color category is recorded as 1, and the temperature of the remaining pixel points is recorded as 0. The temperature of each pixel point in each region of the inner wall of each roller mold is counted and recorded as δ fim .

[0021] Preferably, the specific analysis method of the temperature analysis module is: reading the temperature δ of each pixel point in each area of ​​the inner wall of each roller mold fim , the temperature of the inner wall of each roller mold is obtained by taking the average temperature of each pixel point in each area of ​​the inner wall of each roller mold, which is recorded as Substituting this into the formula Get the temperature uniformity of the inner wall of each roller mold ρ f , where q represents the number of pixels and n represents the number of regions, substituting it into the formula Get the influence degree of temperature uniformity of the inner wall of each roller mold μ f , where ρ0 represents the preset temperature uniformity threshold.

[0022] Preferably, the specific analysis method of the speed control module is: reading the weight of the material injected into each roller mold in each monitoring period, and accumulating it to obtain the injection amount of each roller mold, which is recorded as M f , substituting it into the formula Get the required speed v' of the roller mold f , where Δv represents the preset material unit weight corresponding to the roller mold speed, M0 represents the preset injection amount reference value, and any point on the outer edge of each roller mold is selected as the measurement point A, and at the same time, a point on the base of each roller mold is selected as the measurement point B. The number of times the measurement point A passes through the measurement point B within the set time is detected, and recorded as the number of rotations of each roller mold within the set time. The actual speed of each roller mold is obtained by dividing the number of rotations of each roller mold within the set time by the set time, which is recorded as v f , and read the influence of the temperature uniformity of the inner wall of each roller mold μ f , through the formula Δv f =(v' f -v f )*μ f Get the control speed Δv of each roller mold f, and then control the rotation speed of each roller mold.

[0023] Preferably, the specific analysis process of the appearance data detection module is as follows: the first step is to select a set number of floats from the rotationally molded float products as test samples, which are recorded as float samples, and to detect the outer diameter, length and thickness of each float sample, which are recorded as r x , l x d x , where x represents the number of the xth float sample, x = 1, 2, ..., y, and substitute it into the formula The size conformity τ of the finished float is obtained, where r0, l0, d0 represent the standard values ​​of the set outer diameter, length, and thickness, η1, η2, η3 represent the weight factors of the set outer diameter, length, and thickness, and y represents the number of float samples.

[0024] In the second step, a number of equally spaced measurement points are taken on the surface of each buoy sample at set intervals, and each measurement point of each buoy sample is irradiated with a light source of set intensity, and the light reflected from each measurement point of each buoy sample is received and its intensity is recorded as the reflected light source intensity p' xa , where a represents the number of the ath measurement point, a=1,2,...,b, and substitute it into the formula Get the light reflection uniformity β of each buoy sample x , and then through the formula The smoothness γ of the finished float is obtained, where β0 represents the preset uniformity of light reflection and y represents the number of float samples.

[0025] In the third step, each buoy sample is divided into several sub-areas of equal area, recorded as each sub-area of ​​each buoy sample, and each buoy sample is completely immersed in water to observe the number of bubbles generated in each sub-area of ​​each buoy sample, recorded as the number of bubbles in each sub-area of ​​each buoy sample. The bubble density of each sub-area of ​​each buoy sample is obtained by dividing the number of bubbles in each sub-area of ​​each buoy sample by the area of ​​the sub-area, recorded as σ xs , where s represents the number of the s-th sub-region, s = 1, 2, ..., k, and substitute it into the formula Get the bubble density of the finished float Where k represents the number of sub-regions and y represents the number of float samples.

[0026] Preferably, the specific analysis method of the appearance qualification of the finished float is: reading the size conformity τ, smoothness γ, bubble density of the finished float By formula The appearance qualification degree χ of the finished float is obtained, where w1, w2, and w3 represent the weight factors of the set size conformity, smoothness, and bubble density, respectively, and e is a natural constant.

[0027] Preferably, the specific analysis method of the appearance data analysis module is: comparing the appearance qualification degree of the finished buoys with a preset appearance qualification degree threshold; if the appearance qualification degree of the finished buoys is greater than or equal to the preset appearance qualification degree threshold, it indicates that the batch of finished buoys has passed the inspection; if the appearance qualification degree of the finished buoys is less than the preset appearance qualification degree threshold, it indicates that the batch of finished buoys has failed the inspection, and feedback is given to the system.

[0028] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention obtains the injection compliance degree of each roller mold based on the injection data analysis of each roller mold, and then adjusts the injection data of each roller mold with unqualified injection, which can avoid the production line shutdown and production rework caused by this, and improve the production efficiency and stability of the production line.

[0029] 2. The present invention analyzes the temperature of each pixel point in each area of ​​the inner wall of the roller mold to obtain the temperature uniformity of the inner wall of the roller mold, which can promptly discover the problem of temperature unevenness, help optimize the production process, and ensure stable product quality.

[0030] 3. The present invention detects the amount of raw materials in the roller mold, and analyzes the influence of the temperature uniformity of the inner wall of each roller mold to obtain the control speed of each roller mold, and controls the speed of the roller mold accordingly. Reasonable control of the speed of the roller mold can ensure the matching of the raw material amount and the uniformity of the inner wall temperature with the speed, thereby improving the stability of product quality and reducing the defective rate.

[0031] 4. The present invention obtains the appearance qualification degree of the finished buoy according to the appearance data of the finished buoy, and then analyzes the qualification of the finished buoy and feeds it back to the system. Accurate analysis of the appearance qualification degree of the finished buoy can timely discover the situation where the product quality does not meet the standard, which helps to reduce the defective rate, improve the product qualification rate and reduce quality risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0033] Figure 1 This is a system module connection diagram of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] See also Figure 1 As shown, an intelligent control system for a buoy rotational molding process includes an injection data detection module, an injection data analysis module, a temperature detection module, a temperature analysis module, a rotation speed control module, an appearance data detection module, an appearance data analysis module, and a management database.

[0036] The management database is connected to the temperature analysis module, the injection data analysis module, the speed control module, and the appearance data analysis module; the temperature analysis module is connected to the temperature detection module; the injection data analysis module is connected to the injection data detection module; and the appearance data analysis module is connected to the appearance data detection module.

[0037] The injection data detection module is used to detect the injection data of each roller mold, and the injection data includes the injection speed and the injection time.

[0038] The specific analysis method of the injection data detection module is: monitor the injection time of each roller mold respectively, and record it as t f , where f represents the number of the fth roller mold, f = 1, 2, ..., g, the injection time of each roller mold is divided into several equal-length monitoring periods according to the set time, and the weight of the material injected into each roller mold in each monitoring period is weighed by a weight sensor, recorded as λ fx , where x represents the number of the xth monitoring period, x=1,2,...,y, and the set duration is recorded as t', through the formula Get the injection speed v of each roller mold f ; It can help better control production parameters, adjust production strategies in time, and ensure the stability and efficiency of the production process.

[0039] The injection data analysis module is used to obtain the injection compliance degree of each roller mold according to the injection data analysis of each roller mold, and then adjust the injection data of each roller mold with unqualified injection.

[0040] The specific analysis method of the injection data analysis module is: read the injection speed v of each roller mold respectively f , injection time t f , substituting it into the formula Get the injection conformity degree α of each roller mold f, where φ1 and φ2 represent the weight factors of the set injection speed and injection time respectively, and e is a natural constant, which is compared with the preset injection compliance threshold. If the injection compliance of a roller mold is greater than or equal to the preset injection compliance threshold, it means that the injection compliance of the roller mold meets the standard. On the contrary, it means that the injection compliance of the roller mold does not meet the standard. The injection data of the roller mold needs to be adjusted, and all roller molds whose injection compliance does not meet the standard are counted and recorded as roller molds with unqualified injection. Automatic identification of unqualified roller molds can quickly locate problems in production, make timely adjustments, reduce wasted resources and time in production, and improve production efficiency.

[0041] It should be noted that, in one embodiment, φ1 can be set to 0.5, and φ2 can be set to 0.5. An injection speed that is too fast may cause the gas in the mold to be discharged too quickly, resulting in voids or bubbles; an injection speed that is too slow may cause uneven filling, short material, and other problems; an injection time that is too long may cause the material to be overheated in the mold, resulting in a decrease in melt quality or even thermal decomposition; an injection time that is too short may lead to insufficient filling of the mold, resulting in short material or thermal cracks, and other problems. Therefore, the weights corresponding to the injection speed and injection time are equal.

[0042] The specific method for adjusting the injection data of the roller mold is: reading the injection speed and injection time of each roller mold, and selecting the injection speed and injection time of each roller mold with unqualified injection, which are respectively recorded as v j ,t j , where j represents the number of the jth roller mold with unqualified injection, j = 1, 2, ..., c, through the formula Δv j =v0-v j , Δt j =t0-t j The injection speed and injection time adjustment values ​​of each roller mold with unqualified injection are obtained, so as to adjust the injection data of each roller mold with unqualified injection; timely adjustment of the injection data of unqualified roller molds is helpful to improve product quality and reduce the defective rate, and also provides a useful data reference for the continuous improvement of the production process.

[0043] The temperature detection module is used to scan each roller mold through thermal imaging to obtain a thermal map of each area of ​​the inner wall of each roller mold, and then obtain the temperature of each pixel point in each area of ​​the inner wall of each roller mold.

[0044] The specific analysis process of the temperature detection module is as follows: In the first step, the inner wall of the roller mold is divided into several areas of equal area, and each area of ​​the inner wall of each roller mold is scanned by a thermal imaging camera, which is recorded as a heat map of each area of ​​the inner wall of each roller mold. The color category to which each chromaticity value range belongs is extracted from the management database, and the chromaticity value of each pixel point of the heat map of each area of ​​the inner wall of each roller mold is detected, which is recorded as the chromaticity value ε of each pixel point of the heat map of each area of ​​the inner wall of each roller mold. fim , i represents the number of the i-th area, i=1,2,...,n, m represents the number of the m-th pixel, m=1,2,...,q, and matches it with the color category of each chromaticity value range to obtain the color category of each pixel point in each area of ​​the inner wall of each roller mold; this helps to detect the temperature distribution of the roller in real time and improve production efficiency.

[0045] The second step is to use the formula Get the average chromaticity value of the thermal map of the inner wall of each roller mold Where q represents the number of pixels, n represents the number of regions, and the pixels are matched with the color categories of each chromaticity value range to obtain the color category of the average chromaticity value of the heat map of the inner wall of each roller mold, and further compared with the color category of the chromaticity value of each pixel in the heat map of each region of the inner wall of each roller mold, and the pixels whose chromaticity value belongs to the same color category as the average chromaticity value of the heat map of the inner wall of the corresponding roller mold are screened and recorded as pixels of the same color category. The heat map of each region of the inner wall of each roller mold is binarized, and the temperature of the pixel points of the same color category is recorded as 1, and the temperature of the remaining pixel points is recorded as 0. The temperature of each pixel point in each region of the inner wall of each roller mold is counted and recorded as δ fim By counting and analyzing pixels of the same color category, we can understand the temperature distribution of the product, discover problems and trends in a timely manner, and help optimize product quality management.

[0046] The temperature analysis module is used to obtain the temperature uniformity of the inner wall of each roller mold by analyzing the temperature of each pixel point in each area of ​​the inner wall of each roller mold.

[0047] The specific analysis method of the temperature analysis module is: reading the temperature δ of each pixel point in each area of ​​the inner wall of each roller mold fim , the temperature of the inner wall of each roller mold is obtained by taking the average temperature of each pixel point in each area of ​​the inner wall of each roller mold, which is recorded as Substituting this into the formula Get the temperature uniformity of the inner wall of each roller mold ρ f , where q represents the number of pixels and n represents the number of regions, substituting it into the formula Get the influence degree of temperature uniformity of the inner wall of each roller mold μ f, where ρ0 represents the preset temperature uniformity threshold; by calculating and comparing the temperature uniformity, the processing quality of the product can be evaluated, the problem of temperature unevenness can be discovered in time, and measures can be taken to optimize it and improve product quality.

[0048] The speed control module is used to detect the amount of raw materials in each roller mold, and analyze the temperature uniformity of the inner wall of each roller mold to obtain the control speed of each roller mold, and thereby control the speed of the roller mold.

[0049] The specific analysis method of the speed control module is: reading the weight of the material injected into each roller mold in each monitoring period, and accumulating it to obtain the injection amount of each roller mold, which is recorded as M f , substituting it into the formula Get the required speed v' of the roller mold f , where Δv represents the preset material unit weight corresponding to the roller mold speed, M0 represents the preset injection amount reference value, and any point on the outer edge of each roller mold is selected as the measurement point A, and at the same time, a point on the base of each roller mold is selected as the measurement point B. The number of times the measurement point A passes through the measurement point B within the set time is detected, and recorded as the number of rotations of each roller mold within the set time. The actual speed of each roller mold is obtained by dividing the number of rotations of each roller mold within the set time by the set time, which is recorded as v f , and read the influence of the temperature uniformity of the inner wall of each roller mold μ f , through the formula Δv f =(v' f -v f )*μ f Get the control speed Δv of each roller mold f , and then control the rotation speed of each roller mold; by monitoring and accumulating the weight of injected materials, the injection situation of the roller mold can be mastered in real time, and the material consumption in the production process can be effectively managed and controlled.

[0050] The appearance data detection module is used to detect the appearance data of the finished float, and the appearance data includes size conformity, smoothness, and bubble density.

[0051] The specific analysis process of the appearance data detection module is as follows: In the first step, a set number of floats are randomly selected from the rotationally molded float products as test samples, which are recorded as float samples. The outer diameter, length and thickness of each float sample are respectively tested, which are recorded as r x , l x d x , where x represents the number of the xth float sample, x = 1, 2, ..., y, and substitute it into the formula The dimensional conformity τ of the finished buoy is obtained, where r0, l0, d0 represent the standard values ​​of the set outer diameter, length, and thickness respectively, η1, η2, η3 represent the weight factors of the set outer diameter, length, and thickness respectively, and y represents the number of buoy samples; by detecting and calculating the outer diameter, length, and thickness of the buoy samples, the dimensional conformity of the finished buoy can be obtained, which is helpful to evaluate the dimensional quality of the product and promptly discover dimensional deviations and problems.

[0052] It should be noted that, in one embodiment, η1 can be set to 0.4, η2 can be set to 0.3, and η3 can be set to 0.3. The outer diameter is usually the most intuitive dimensional feature of the finished float, and has an important impact on the appearance and structural stability of the product. Therefore, the weight corresponding to the outer diameter is relatively large.

[0053] In the second step, a number of equally spaced measurement points are taken on the surface of each buoy sample at set intervals, and each measurement point of each buoy sample is irradiated with a light source of set intensity, and the light reflected from each measurement point of each buoy sample is received and its intensity is recorded as the reflected light source intensity p' xa , where a represents the number of the ath measurement point, a=1,2,...,b, and substitute it into the formula Get the light reflection uniformity β of each buoy sample x , and then through the formula The finish γ of the finished float is obtained, where β0 represents the preset uniformity of light reflection and y represents the number of float samples;

[0054] In the third step, each buoy sample is divided into several sub-areas of equal area, recorded as each sub-area of ​​each buoy sample, and each buoy sample is completely immersed in water to observe the number of bubbles generated in each sub-area of ​​each buoy sample, recorded as the number of bubbles in each sub-area of ​​each buoy sample. The bubble density of each sub-area of ​​each buoy sample is obtained by dividing the number of bubbles in each sub-area of ​​each buoy sample by the area of ​​the sub-area, recorded as σ xs , where s represents the number of the s-th sub-region, s = 1, 2, ..., k, and substitute it into the formula Get the bubble density of the finished float Where k represents the number of sub-areas, and y represents the number of float samples. By measuring the reflection intensity of the light source and calculating the uniformity of light reflection, the smoothness of the float can be evaluated, which helps to inspect the surface flatness and quality of the product.

[0055] The appearance data analysis module is used to analyze the appearance data of the finished buoy to obtain the appearance qualification of the finished buoy, and then analyze the qualification of the finished buoy and feed it back to the system.

[0056] The specific analysis method of the appearance qualification of the finished float is to read the size conformity τ, smoothness γ, and bubble density of the finished float. By formula The appearance qualification degree χ of the finished float product is obtained, where w1, w2, and w3 represent the weight factors of the set size conformity, smoothness, and bubble density, respectively, and e is a natural constant; this helps to comprehensively evaluate the appearance quality of the product and ensure that the product appearance meets the requirements.

[0057] It should be noted that, in one embodiment, w1 can be set to 0.4, w2 can be set to 0.3, and w3 can be set to 0.3. The dimensional conformity is directly related to the appearance and overall shape of the product, and has an important impact on the assembly and use of the product. It is usually regarded as a key factor in appearance quality, so the corresponding weight is higher.

[0058] The specific analysis method of the appearance data analysis module is: comparing the appearance qualification degree of the finished buoy with the preset appearance qualification threshold. If the appearance qualification degree of the finished buoy is greater than or equal to the preset appearance qualification threshold, it means that the batch of finished buoys has passed the inspection. If the appearance qualification degree of the finished buoy is less than the preset appearance qualification threshold, it means that the batch of finished buoys has failed the inspection and feedback is given to the system. Timely discovery and processing of unqualified products can reduce the scrap rate, improve production efficiency and resource utilization, and reduce production costs.

[0059] A management database is used to store the color categories to which each chromaticity value range belongs.

[0060] This system obtains the injection conformity of each roller mold through injection data analysis of each roller mold, and then adjusts the injection data. It obtains the control speed of each roller mold by combining the temperature uniformity of the inner wall of each roller mold and the amount of raw materials, and then adjusts the rotation speed of the roller mold. The appearance conformity of the finished buoy is obtained according to the appearance data of the finished buoy, and then the conformity of the finished buoy is analyzed and fed back to the system. It can timely discover the situation that the product quality does not meet the standard, which helps to reduce the defective rate, improve the product qualification rate and reduce quality risks.

[0061] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still covered by the protection scope of the present invention.

Claims

1. An intelligent control system for buoy rotational molding process, characterized in that: The system specifically includes the following modules: The injection data detection module is used to detect the injection data of each roller mold, and the injection data includes injection speed and injection time; The injection data analysis module is used to analyze the injection data of each roller mold to obtain the injection compliance degree of each roller mold, and then adjust the injection data of each roller mold with unqualified injection; The temperature detection module is used to scan each roller mold by thermal imaging to obtain a thermal map of each area of ​​the inner wall of each roller mold, and then obtain the temperature of each pixel point in each area of ​​the inner wall of each roller mold; A temperature analysis module, used to obtain the temperature uniformity of the inner wall of each roller mold by analyzing the temperature of each pixel point in each area of ​​the inner wall of each roller mold; The speed control module is used to detect the amount of raw materials in each roller mold, and analyze the temperature uniformity of the inner wall of each roller mold to obtain the control speed of each roller mold, and control the speed of the roller mold accordingly; Appearance data detection module, used to detect the appearance data of each buoy finished product, including the size conformity 、 Finish 、 Bubble density; The appearance data analysis module is used to analyze the appearance data of each buoy finished product to obtain the appearance qualification of the buoy finished product, and then analyze the qualification of the buoy finished product and feed it back to the system; A management database is used to store the color categories to which each chromaticity value range belongs.

2. The intelligent control system for buoy rotational molding process according to claim 1 is characterized in that: The specific analysis method of the injection data detection module is: The injection time of each roller mold is monitored and recorded as t f , where f represents the number of the f-th roller mold, f = 1, 2, ..., g, the injection time of each roller mold is divided into several equal-length monitoring periods according to the set time, and the weight of the material injected into each roller mold in each monitoring period is weighed by a weight sensor, recorded as λ fx , where x represents the number of the xth monitoring period, x=1,2,...,y, and the set duration is recorded as t', through the formula Get the injection speed v of each roller mold f .

3. The intelligent control system for buoy rotational molding process according to claim 2 is characterized in that: The specific analysis method of the injection data analysis module is: Read the injection speed v of each roller mold separately f , injection time t f , substituting it into the formula Get the injection conformity degree α of each roller mold f , where v0 and t0 represent the set standard values ​​of injection speed and injection time respectively, φ1 and φ2 represent the weight factors of the set injection speed and injection time respectively, and e is a natural constant, which is compared with the preset injection compliance threshold. If the injection compliance of a roller mold is greater than or equal to the preset injection compliance threshold, it means that the injection compliance of the roller mold meets the standard. On the contrary, it means that the injection compliance of the roller mold does not meet the standard. The injection data of the roller mold needs to be adjusted, and all roller molds whose injection compliance does not meet the standard are counted and recorded as roller molds with unqualified injection.

4. The intelligent control system for buoy rotational molding process according to claim 3 is characterized in that: The specific method for adjusting the injection data of the roller mold is: Read the injection speed and injection time of each roller mold, and select the injection speed and injection time of each roller mold with unqualified injection, which are recorded as v j ,t j , where j represents the number of the jth roller mold with unqualified injection, j = 1, 2, ..., c, through the formula Δv j =v0-v j , Δt j =t0-t j The injection speed and injection time adjustment values ​​of each roller mold with unqualified injection are obtained, so as to adjust the injection data of each roller mold with unqualified injection.

5. The intelligent control system for buoy rotational molding process according to claim 1 is characterized in that: The specific analysis process of the temperature detection module is as follows: In the first step, the inner wall of the roller mold is divided into several areas of equal area. The thermal imaging camera is used to scan each area of ​​the inner wall of each roller mold, which is recorded as the heat map of each area of ​​the inner wall of each roller mold. The color category to which each chromaticity value range belongs is extracted from the management database. At the same time, the chromaticity value of each pixel point of the heat map of each area of ​​the inner wall of each roller mold is detected, which is recorded as the chromaticity value ε of each pixel point of the heat map of each area of ​​the inner wall of each roller mold. fim , i represents the number of the i-th region, i=1,2,...,n, m represents the number of the m-th pixel, m=1,2,...,q, and matches it with the color category of each chromaticity value range to obtain the color category of each pixel point in each region of the inner wall of each roller mold; The second step is to use the formula Get the average chromaticity value of the thermal map of the inner wall of each roller mold Where q represents the number of pixels, n represents the number of regions, and the pixels are matched with the color categories of each chromaticity value range to obtain the color category of the average chromaticity value of the heat map of the inner wall of each roller mold, and further compared with the color category of the chromaticity value of each pixel in the heat map of each region of the inner wall of each roller mold, and the pixels whose chromaticity value belongs to the same color category as the average chromaticity value of the heat map of the inner wall of the corresponding roller mold are screened and recorded as pixels of the same color category. The heat map of each region of the inner wall of each roller mold is binarized, and the temperature of the pixel points of the same color category is recorded as 1, and the temperature of the remaining pixel points is recorded as 0. The temperature of each pixel point in each region of the inner wall of each roller mold is counted and recorded as δ fim .

6. The intelligent control system for buoy rotational molding process according to claim 5, characterized in that: The specific analysis method of the temperature analysis module is: Read the temperature of each pixel point in each area of ​​the inner wall of each roller mold fim , the temperature of the inner wall of each roller mold is obtained by taking the average temperature of each pixel point in each area of ​​the inner wall of each roller mold, which is recorded as Substituting this into the formula Get the temperature uniformity of the inner wall of each roller mold ρ f , where q represents the number of pixels and n represents the number of regions, substituting it into the formula Get the influence degree of temperature uniformity of the inner wall of each roller mold μ f , where ρ0 represents the preset temperature uniformity threshold.

7. The intelligent control system for buoy rotational molding process according to claim 6, characterized in that: The specific analysis method of the speed control module is: Read the weight of the material injected into each roller mold during each monitoring period, and add them up to get the injection amount of each roller mold, recorded as M f , substituting it into the formula Get the required speed v' of the roller mold f , where Δv represents the preset material unit weight corresponding to the roller mold speed, M0 represents the preset injection amount reference value, and any point on the outer edge of each roller mold is selected as the measurement point A, and at the same time, a point on the base of each roller mold is selected as the measurement point B. The number of times the measurement point A passes through the measurement point B within the set time is detected, and recorded as the number of rotations of each roller mold within the set time. The actual speed of each roller mold is obtained by dividing the number of rotations of each roller mold within the set time by the set time, which is recorded as v f , and read the influence of the temperature uniformity of the inner wall of each roller mold μ f , through the formula Δv f =(v' f -v f )*μ f Get the control speed Δv of each roller mold f , and then control the rotation speed of each roller mold.

8. The intelligent control system for buoy rotational molding process according to claim 1, characterized in that: The specific analysis process of the appearance data detection module is as follows: In the first step, a set number of floats are selected from the rotationally molded float products as test samples, which are recorded as each float sample. The outer diameter, length and thickness of each float sample are tested respectively, which are recorded as r x , l x d x , where x represents the number of the xth float sample, x = 1, 2, ..., y, and substitute it into the formula The size conformity τ of the finished float is obtained, where r0, l0, d0 represent the standard values ​​of the set outer diameter, length, and thickness, η1, η2, η3 represent the weight factors of the set outer diameter, length, and thickness, and y represents the number of float samples; In the second step, a number of equally spaced measurement points are taken on the surface of each buoy sample at set intervals, and each measurement point of each buoy sample is irradiated with a light source of set intensity, and the light reflected from each measurement point of each buoy sample is received and its intensity is recorded as the reflected light source intensity p' xa , where a represents the number of the ath measurement point, a=1,2,...,b, and substitute it into the formula Get the light reflection uniformity β of each buoy sample x , and then through the formula The finish γ of the finished float is obtained, where β0 represents the preset uniformity of light reflection and y represents the number of float samples; In the third step, each buoy sample is divided into several sub-areas of equal area, recorded as each sub-area of ​​each buoy sample, and each buoy sample is completely immersed in water to observe the number of bubbles generated in each sub-area of ​​each buoy sample, recorded as the number of bubbles in each sub-area of ​​each buoy sample. The bubble density of each sub-area of ​​each buoy sample is obtained by dividing the number of bubbles in each sub-area of ​​each buoy sample by the area of ​​the sub-area, recorded as σ xs , where s represents the number of the s-th sub-region, s = 1, 2, ..., k, and substitute it into the formula Get the bubble density of the finished float Where k represents the number of sub-regions and y represents the number of float samples.

9. The intelligent control system for buoy rotational molding process according to claim 8, characterized in that: The specific analysis method for the appearance qualification of the finished buoy is as follows: Read the dimensional conformity τ, smoothness γ and bubble density of the finished float By formula The appearance qualification degree χ of the finished float is obtained, where w1, w2, and w3 represent the weight factors of the set size conformity, smoothness, and bubble density, respectively, and e is a natural constant.

10. The intelligent control system for buoy rotational molding process according to claim 9, characterized in that: The specific analysis method of the appearance data analysis module is: The appearance qualification degree of the finished buoys is compared with the preset appearance qualification degree threshold. If the appearance qualification degree of the finished buoys is greater than or equal to the preset appearance qualification degree threshold, it means that the batch of finished buoys has passed the inspection. If the appearance qualification degree of the finished buoys is less than the preset appearance qualification degree threshold, it means that the batch of finished buoys has failed the inspection and feedback is given to the system.

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