Continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels

Abstract

The present invention belongs to the technical field of production and conveying equipment, and in particular, relates to a continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels, including a front-end double crawler, a slitting machine, a conveying roller, a preheating device, a high-pressure foaming machine, a rear-end double crawler and a conveying control system; the conveying control system integrates the molding parameters of the rock wool composite panel, and the working state parameters of the slitting machine, the conveying roller, the preheating device, the front-end double crawler and the rear-end double crawler as inputs, and outputs a matching first conveying power, a second conveying power and a third conveying power. The entire production and conveying system of the present invention adjusts the conveying speed in real time through multi-parameter monitoring to ensure that each link is carried out in the best synchronous state, ensuring the precise control of each link between the rock wool board composite panel and the double-sided flame-retardant thermal insulation composite panel during the conveying process, avoiding interruptions and delays, and maintaining the smoothness of the production process. The system can flexibly adjust the conveying power of each link to maximize the overall production efficiency.

Description

Technical Field

[0001] The invention belongs to the technical field of production and conveying equipment, and in particular relates to a continuous production and conveying system for double-sided flame-retardant and heat-insulating composite panels. Background Art

[0002] In the field of building exterior wall insulation, fire safety and energy-saving performance are two key considerations. With the increasing requirements for building fire safety, especially the strict regulations on the flame retardant standards of exterior wall materials, rock wool sandwich panels are widely used due to their excellent flame retardant properties. However, the high thermal conductivity of rock wool materials limits its efficiency in energy saving to a certain extent.

[0003] In order to solve the above problems, the existing technology combines rock wool board and polyurethane layer. Polyurethane material has extremely low thermal conductivity, which is much lower than the thermal conductivity of rock wool. By combining the polyurethane layer with the rock wool board, the thermal insulation effect can be greatly improved while maintaining the fireproof performance, so that the overall thermal insulation performance of the building exterior wall is improved and meets more stringent energy-saving standards.

[0004] In the production process for the above-mentioned products, the upper and lower steel plates of the rock wool composite board are first formed, and the longitudinal cutting, flipping, arranging, side milling and conveying of the large rock wool board are carried out simultaneously. After the upper and lower steel plates are preheated, they are combined with the middle rock wool layer by sprinkling glue on the lower steel plate and the rock wool layer, and then the rock wool composite board is made by hot pressing with double tracks. Then the rock wool composite board is cut horizontally, so that the rock wool composite board is divided into an upper and lower layer structure, and the upper and lower layers are transported forward in two ways. The lower layer moves along the horizontal roller, and the upper layer moves upward along the sloped conveying equipment through special equipment, forming a hollow space in the middle; finally, the polyurethane is foamed in the hollow space, so that the foamed polyurethane and the double-layer rock wool board are integrated, and a double-sided flame-retardant thermal insulation composite board with better integrity can be obtained. The implementation of the above process can achieve higher production efficiency, which not only increases the overall stability of the composite board, but also improves the durability. This integrated design reduces the risk of peeling between layers and ensures long-term performance.

[0005] In order to realize the above production process, there is often a need for equipment modification. The production lines of rock wool boards and polyurethane need to be adaptively modified, and after the modification, they need to be synchronously integrated and controlled to achieve precise continuous production, while ensuring production efficiency and product consistency and quality. However, during the modification process, due to communication delays and mechanical limitations, after the modification of the equipment structure, there is often a certain delay in the control of the front and rear production lines. How to solve the above delays and realize the synchronous transportation of the front and rear production lines has become the key to whether the above production process can be realized and achieve the expected performance. Summary of the invention

[0006] The present invention provides a continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels, which can effectively solve the problems in the background technology.

[0007] To achieve the above object, the technical solution of the present invention is as follows:

[0008] Double-sided flame-retardant thermal insulation composite board continuous production conveying system, including front-end double crawler, cutting machine, conveying roller, preheating device, high-pressure foaming machine, back-end double crawler and conveying control system;

[0009] The front double crawler provides the first conveying power for the rock wool composite board by pressure conveying, the cutting machine transversely cuts the formed rock wool composite board to obtain an upper and lower two-layer structure, and the conveying roller conveys the upper and lower two-layer structures to the preheating device for preheating respectively, and continues to convey after preheating; wherein, the conveying roller passively conveys the lower structure while keeping the height unchanged, and partially lifts the upper structure to a set height and supplies the second conveying power;

[0010] The high-pressure foaming machine sprays polyurethane toward the upper surface of the preheated lower structure, and the polyurethane foams between the upper and lower structures, and is formed by the subsequent double-track hot pressing to obtain a double-sided flame-retardant thermal insulation composite board;

[0011] The rear double crawler provides the third conveying power and heat for the double-sided flame-retardant thermal insulation composite board by pressure conveying, and together with the modules on both sides provides a restricted space for the polyurethane foaming molding;

[0012] The conveying control system takes the forming parameters of the rock wool composite board and the working state parameters of the cutting machine, conveying roller, preheating device, front double crawler and rear double crawler as input, and outputs the matching first conveying power, second conveying power and third conveying power.

[0013] Furthermore, the input of the conveying control system includes:

[0014] The forming speed of the rock wool composite board;

[0015] and, at least one of a tool state, a temperature, a cutting speed, and a jitter amount of the slicer;

[0016] and, the conveying speed of the conveying roller conveyor upper track, the front track double crawler and the rear track double crawler;

[0017] And, the temperature control parameters of the preheating device and the subsequent double crawler tracks.

[0018] Furthermore, the transport control system uses an adaptive adjustment algorithm to output the matched first transport power, second transport power and third transport power, the adaptive adjustment algorithm is based on a combination of fuzzy control and PID control, and the adaptive adjustment algorithm process includes:

[0019] Collecting the input real-time data;

[0020] Input the real-time data into a fuzzy control module, and output target values ​​of the first conveying power, the second conveying power, and the third conveying power;

[0021] The target value is input into a PID control module, and the first conveying power, the second conveying power and the third conveying power are adjusted according to the target value.

[0022] Furthermore, the real-time data is input into a fuzzy control module, and target values ​​of the first delivery power, the second delivery power, and the third delivery power are output, including:

[0023] In the fuzzy control module, a rule base is set based on experience or expert knowledge, wherein the rules in the rule base include a combination of multiple inputs and corresponding outputs;

[0024] Dividing each of the inputs into a number of fuzzy sets, defining a membership function for each of the fuzzy sets, and converting the real-time data into memberships of different fuzzy sets through the membership function;

[0025] Matching each rule in the rule base according to the converted membership degree to activate the rule through matching, and performing fuzzy reasoning on the activated rule according to the membership degree to calculate the membership degree of the fuzzy sets of the first transmission power, the second transmission power, and the third transmission power;

[0026] The output of the fuzzy reasoning is converted into specific numerical values ​​to obtain the target values ​​of the first conveying power, the second conveying power, and the third conveying power.

[0027] Further, the rules are activated by matching, and the activated rules are subjected to fuzzy reasoning according to the degree of membership, including:

[0028] The number of matched rules is determined. When the number of matched rules is greater than 1, an activation membership is calculated for each activated rule according to the input membership, and the activation memberships are synthesized.

[0029] Further, the activation membership is calculated based on the input membership, using a minimum method or a product method.

[0030] Furthermore, the activation memberships are synthesized, including:

[0031] Setting a smoothing coefficient for each of the rules;

[0032] Assigning a weighted coefficient to the activation membership of each rule to obtain a weighted activation membership, wherein the weighted coefficient is positively correlated with the activation membership;

[0033] According to the weighted activation membership, smoothing is performed to obtain a synthetic activation membership, and the formula is as follows:

[0034] ;

[0035] Where i is the number of each rule.

[0036] Further, the rules are activated by matching, and the activated rules are subjected to fuzzy reasoning according to the degree of membership, including:

[0037] The number of matched rules is determined, and when the number of matched rules is equal to 0, the rule closest to the current input is detected; the similarity between the input and the detection result is determined, and interpolation is performed according to the similarity to obtain the activation membership after interpolation.

[0038] Furthermore, the interpolation adopts linear interpolation or weighted average interpolation.

[0039] Furthermore, the adaptive adjustment algorithm process also includes: dynamically adjusting parameters of the PID controller based on the target value.

[0040] The technical solution of the present invention can achieve the following technical effects:

[0041] In the present invention, the entire production and conveying system adjusts the conveying speed in real time through multi-parameter monitoring, ensuring that each link is carried out in the best synchronous state, ensuring the precise control between each production link during the conveying process of the rock wool board composite board and the double-sided flame retardant thermal insulation composite board, avoiding interruptions and delays, and maintaining the smoothness of the production process; at the same time, the system can flexibly adjust the conveying power of each link to maximize the overall production efficiency while ensuring product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 It is a simplified schematic diagram of a continuous production conveying system for double-sided flame-retardant thermal insulation composite panels;

[0044] Figure 2 for Figure 1 A partial enlarged view of the middle A;

[0045] Figure 3 It is a schematic diagram of the forming of the double-sided flame-retardant thermal insulation composite panel at the rear double track;

[0046] Figure 4 It is the flow chart of adaptive adjustment algorithm;

[0047] Figure 5 A flowchart for inputting real-time data into a fuzzy control module and outputting target values ​​of a first delivery power, a second delivery power and a third delivery power;

[0048] Reference numerals: 1, front double crawler; 2, slitting machine; 3, top conveying front section; 4, bottom conveying front section; 5, preheating device; 6, top conveying rear section; 7, bottom conveying rear section; 8, high-pressure foaming machine; 9, rear double crawler;

[0049] 01. Rock wool composite board; 02. Composite board upper structure; 03. Composite board lower structure; 04. Polyurethane core layer. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0052] Double-sided flame retardant thermal insulation composite board continuous production conveying system, such as Figure 1 As shown, a simplified schematic diagram of a continuous production conveying system for double-sided flame-retardant thermal insulation composite panels is provided, including a front-end double crawler 1, a slitting machine 2, a conveying roller, a preheating device 5, a high-pressure foaming machine 8, a back-end double crawler 9 and a conveying control system;

[0053] The front double crawler 1 provides the first conveying power for the rock wool composite board 01 by pressing, and the cutter 2 cuts the formed rock wool composite board 01 transversely to obtain an upper and lower two-layer structure. The conveying roller conveys the upper and lower two-layer structures to the preheating device 5 for preheating respectively, and continues to convey after preheating; wherein, the conveying roller conveys the lower structure at a constant height for passive conveying, and partially lifts the upper structure to a set height and supplies the second conveying power;

[0054] The high-pressure foaming machine 8 sprays polyurethane on the upper surface of the preheated lower structure, and the polyurethane foams between the upper and lower structures, and is hot-pressed and formed by the subsequent double crawler 9 to obtain a double-sided flame-retardant thermal insulation composite board;

[0055] The rear double crawler 9 provides the third conveying power and heat for the double-sided flame retardant thermal insulation composite board by pressure delivery, and together with the modules on both sides provides a restricted space for polyurethane foaming molding;

[0056] The conveying control system takes the forming parameters of the integrated rock wool composite board 01, as well as the working state parameters of the cutting machine 2, the conveying roller, the preheating device 5, the front double crawler 1 and the rear double crawler 9 as input, and outputs the matching first conveying power, second conveying power and third conveying power.

[0057] In the present invention, the entire production and conveying system adjusts the conveying speed in real time through multi-parameter monitoring, ensuring that each link is carried out in the best synchronous state, ensuring the precise control between each production link during the conveying process of the rock wool board composite board and the double-sided flame retardant thermal insulation composite board, avoiding interruptions and delays, and maintaining the smoothness of the production process; at the same time, the system can flexibly adjust the conveying power of each link to maximize the overall production efficiency while ensuring product quality.

[0058] In this embodiment, the specific process of the double-sided flame retardant thermal insulation composite board can be performed according to the following process:

[0059] Rock wool board production and transportation section:

[0060] In this production line, rock wool composite board 01 is produced. In this production line, steel plates serving as surface reinforcement structures of rock wool boards are supplied through two upper and lower uncoilers respectively. Specifically, steel coils are loaded, uncoiled and coated, and respectively sent to upper and lower forming machines for adaptive forming of the ends. Then, the upper and lower steel plates are respectively sent to the double crawler entrances of the front double crawler 1. At the same time, the rock wool raw materials are transported to the foaming room after preliminary processing. In the spraying room, the upper surface of the lower steel plate and the upper surface of the rock wool are sprayed with glue respectively. Then, the rock wool and the upper and lower steel plates are simultaneously sent to the front double crawler 1 for extrusion shaping, heating and transportation. Here, the first conveying power is supplied to complete high-temperature bonding to form the rock wool composite board 01. The equipment in this part is existing equipment and will not be repeated here. In this embodiment, only the speed correlation between the front double crawler 1 and the back is concerned.

[0061] Polyurethane core layer 04 production and conveying section:

[0062] The rock wool composite board 01 is transported to the cutting machine 2, and the rock wool composite board 01 is cut horizontally by the cutting machine 2 to obtain an upper and lower two-layer structure, that is, Figure 1The composite plate upper structure 02 and the composite plate lower structure 03 shown in the figure are respectively transferred to the preheating device 5 through the top conveying front section 3 and the bottom conveying front section 4 in the conveying roller as shown in the figure; wherein, the composite plate lower structure 03 is preferably covered with non-woven fabric before being sent to the preheating device 5, and then enters the side of the rear double crawler 9 at the same time as the composite plate upper structure 02. Figure 2 As shown, the polyurethane raw material is sprayed by the high-pressure foaming machine 8 at the top conveying rear section 6 and the bottom conveying rear section 7, as well as between the composite plate upper structure 02 and the composite plate lower structure 03. The rear double crawler 9 and the two side modules next to it are together set up to form a molding space. Specifically, the thickness and width of the board are controlled by the two side modules next to the double crawler and the height of the double crawler. Finally, the polyurethane foaming and expansion between the composite plate upper structure 02 and the composite plate lower structure 03 reaches the point where the upper and lower plates are completely bonded, and then the double crawler is taken out, as shown in FIG. Figure 3 As shown, the boards are cut into specified lengths and then placed in the cooling room for drying. After the cooling time is up, they are stacked and packaged, and the production of the entire set of boards is completed.

[0063] As a preferred embodiment of the above, the input of the conveying control system includes:

[0064] Forming speed of rock wool composite board 01;

[0065] and at least one of a tool state, a temperature, a cutting speed and a jitter amount of the slicer 2;

[0066] and the conveying speed of the conveying roller conveyor upper track, the front track double crawler 1 and the rear track double crawler 9;

[0067] And, the temperature control parameters of the preheating device 5 and the rear double crawler belt 9.

[0068] The comprehensive consideration of the above parameters can ensure that the final conveying control is more accurate and reliable. During the implementation process, the forming speed of the rock wool composite board 01 can be collected by a speed sensor, and a contact or non-contact speed sensor is installed on the production line to monitor the moving speed of the rock wool composite board 01 in real time. The conveying speed of the conveyor roller above the first track, the front track double crawler 1 and the rear track double crawler 9 can also be achieved in the above manner, which will not be repeated here.

[0069] The tool status can be achieved through a visual detection system. Specifically, by installing a camera and an image processing system, the tool status can be monitored in real time to check whether the tool is cutting normally and whether the tool is offset or damaged. The tool temperature can be collected through an infrared temperature sensor or a contact temperature sensor. The temperature control parameters of the preheating device 5 and the rear double crawler 9 can also be collected in the above manner.

[0070] The tool speed can be obtained by installing a rotary encoder on the tool drive motor to measure the tool rotation speed in real time, thereby calculating the actual cutting speed; the jitter amount can be collected by installing an accelerometer or vibration sensor on the tool holder, and by analyzing the sensor data, the tool stability and possible jitter that may occur during the cutting process can be determined.

[0071] The above-mentioned method for acquiring each parameter is only a specific example, and other acquisition methods that can achieve the corresponding purpose are also within the protection scope of the present invention.

[0072] As a preferred embodiment of the above, Figure 4 As shown, the transport control system uses an adaptive adjustment algorithm to output the matched first transport power, second transport power and third transport power. The adaptive adjustment algorithm is based on the combination of fuzzy control and PID control. The adaptive adjustment algorithm process includes:

[0073] S1: collect input real-time data;

[0074] S2: inputting the real-time data into the fuzzy control module, and outputting the target values ​​of the first conveying power, the second conveying power and the third conveying power;

[0075] S3: Input the target value into the PID control module, and adjust the first conveying power, the second conveying power and the third conveying power according to the target value.

[0076] In this preferred embodiment, the system collects equipment parameters in real time, which helps to fully understand the current state of the production process. For specific parameter types, see the above embodiments. In the implementation process, by inputting real-time data into the fuzzy control module, it is possible to handle complex and high-uncertainty situations. Fuzzy control can effectively evaluate various input states and generate reasonable target values ​​based on empirical rules. This process can adapt to changes in production conditions in real time. The target value output by the fuzzy control is input into the PID control module, allowing fine adjustment of the conveying power. The PID control can quickly respond to changes in the target value and ensure the stability of the system. By adjusting the proportional, integral and differential parameters, the first, second and third conveying powers can be accurately controlled.

[0077] As a preferred embodiment of the above, Figure 5 As shown, the real-time data is input into the fuzzy control module, and the target values ​​of the first delivery power, the second delivery power and the third delivery power are output, including:

[0078] A1: In the fuzzy control module, a rule base is set based on experience or expert knowledge. The rules in the rule base include a combination of multiple inputs and corresponding outputs.

[0079] During the implementation of this step, the rule base should be designed based on the correlation of various parameters in actual production experience and expert knowledge. For example, some parameter combinations may cause the production line speed to be too fast, thus affecting the production quality, so corresponding adjustments need to be made in such cases; each rule usually appears in the form of "if-then", for example: "If the cutting speed is 'fast' and the temperature is 'low', then the first conveying power output is 'reduced'", this method can provide clear control logic for different production states;

[0080] A2: Divide each input into several fuzzy sets, define a membership function for each fuzzy set, and convert the real-time data into the membership of different fuzzy sets through the membership function;

[0081] The input referred to here includes different parameter types, that is, each parameter type in the input is divided into several fuzzy sets, such as "low", "medium", and "high", which reflect the fuzzy state of the input; when defining the membership function for each fuzzy set, a triangular, trapezoidal or Gaussian membership function is usually used, and the membership function quantifies the degree of the input data in the fuzzy set. For example, if the cutting speed is at a high level, the degree of belonging to "high" is greater, while the degree of belonging to "low" is smaller; the real-time data is converted into a membership value through the membership function. For example, when the value of the input data is close to the fuzzy set "medium", its membership is close to 1, and vice versa.

[0082] A3: Match each rule in the rule base according to the converted membership degree to activate the rule through matching, and perform fuzzy reasoning on the activated rule according to the membership degree to calculate the membership degree of the first transmission power, the second transmission power, and the third transmission power fuzzy set;

[0083] When implementing this step, since the input value can partially belong to multiple fuzzy sets, multiple rules may be activated at the same time, and the activated rules correspond to the membership values ​​of specific output fuzzy sets; in this case, the results of multiple rules can be synthesized according to the activated membership to obtain the membership of each output fuzzy set;

[0084] A4: Convert the output of the fuzzy reasoning into specific numerical values ​​to obtain the target values ​​of the first conveying power, the second conveying power, and the third conveying power.

[0085] Defuzzification converts the results of fuzzy reasoning into specific numerical outputs. Common defuzzification methods include the centroid method or the maximum membership method. After defuzzification, the target values ​​of each transmission power are obtained as specific values, which are used to actually adjust the transmission power. These target values ​​are specific instructions for further execution of the system.

[0086] As a preferred embodiment of the above, by matching the activation rules, and performing fuzzy reasoning on the activated rules according to the membership degree, the method includes:

[0087] Determine the number of matched rules. During the implementation process, the number of matched rules may include multiple situations. Among them, when the number of matched rules is 1, a set of default output values ​​can be defined in the system as the control output when no rule is matched. These default values ​​are usually safe values ​​or neutral values ​​to ensure that the system will not become unstable due to the lack of rules. For example, the first, second, and third transmission forces can be set to "maintain" or "medium"; and as a further preference, when the number of matched rules is greater than 1, the activation membership is calculated for each activated rule based on the input membership, and the activation memberships are synthesized. Specifically, the activation membership is calculated based on the input membership, using the minimum method or the product method.

[0088] Among them, the minimum method specifically selects the minimum value of the input membership as the activation membership of the rule, which is suitable for processing multiple condition combinations; the product method specifically multiplies the membership of each input variable to obtain the activation membership of the rule, which is suitable for processing relatively independent situations between inputs; the above two methods can be selected and used according to specific needs.

[0089] In the continuous production process, the parameters of the production equipment often fluctuate slightly due to fluctuations in raw materials, changes in the machine operating state, etc. If these fluctuations are not smoothed and directly affect the control system, it will cause excessive fluctuations in the control signal, which may affect the production quality and even cause production interruption. Based on the above situation, as a preferred embodiment of the above embodiment, the activation memberships are synthesized, including:

[0090] B1: Set a smoothing coefficient for each rule; the smoothing coefficient is used to determine the sensitivity to changes in activation membership during the synthesis process. When the smoothing coefficient is high, it means that the system is less sensitive to input changes, thus maintaining a relatively stable output; when the smoothing coefficient is low, the system is more sensitive to changes and the output response is faster;

[0091] B2: Assign a weighted coefficient to the activation membership of each rule to obtain the weighted activation membership. The weighted coefficient is positively correlated with the activation membership, that is, the rules with larger activation membership will have a greater impact on the final synthesis result, ensuring that more relevant rules dominate the synthesis process;

[0092] B3: Perform smoothing according to the weighted activation membership to obtain the synthetic activation membership. The formula is as follows:

[0093] ;

[0094] Where i is the number of each rule.

[0095] According to the above formula, the weighted activation membership is calculated for each rule, and the influence of each rule on the final synthesis result is adjusted by the smoothing coefficient. The final synthesis activation membership is the weighted average of all rules. The weighted activation membership of all rules is multiplied by their corresponding smoothing coefficients and then divided by the sum of all smoothing coefficients. In this preferred embodiment, through the smoothing process when synthesizing the activation membership, the synthesis result will show a stable trend, reducing the need for frequent adjustments and improving the stability and production efficiency of the system. By calculating the weighted activation membership and applying the smoothing coefficient, the system can make more flexible adjustments according to the actual production needs while ensuring stability. For example, when encountering uneven raw materials or equipment load fluctuations, the system can quickly and smoothly adjust the conveying power to ensure high quality and high efficiency of production.

[0096] During the implementation process, the weighted mechanism makes the system pay more attention to key production links, and avoids unnecessary fluctuations through smoothing. Each link in the production process can maintain precise control, thereby ensuring the stable quality of the final product - double-sided flame-retardant thermal insulation composite panels; because the system can accurately adjust the transmission power, it avoids excessive or unnecessary heating, thereby effectively reducing energy consumption and material waste. The smoothing and weighted mechanisms help the system to respond promptly to different changes, while maintaining stable system operation, avoiding unnecessary downtime and fluctuations, and improving production efficiency.

[0097] As another case, by matching the activation rules, the activated rules are subjected to fuzzy reasoning according to the membership, including: judging the number of matched rules, and when the number of matched rules is equal to 0, detecting the rule closest to the current input; judging the similarity between the input and the detection result, and interpolating according to the similarity to obtain the activation membership after interpolation.

[0098] Based on the above optimization scheme, even if there is no completely matching rule, the system still needs to make control decisions based on the similarity of the input; in the implementation process, it is key to detect the similarity between the input and the closest rule. Specifically, methods such as Euclidean distance and cosine similarity can be used to measure the similarity between the input and the rule, and how to adjust the activation degree of the rule based on the similarity. Finally, interpolation can ensure that in the absence of a complete match of the rule, the system can still respond reasonably according to the input situation. As a preferred method, interpolation can specifically use linear interpolation or weighted average interpolation, depending on the similarity between the rules; the activation membership after interpolation is used as the new rule activation value for subsequent fuzzy reasoning.

[0099] Through the above optimization scheme, the system can respond flexibly to changing production environments. Whether it is a slight fluctuation in materials or a change in equipment status, the control parameters can be adjusted through similarity and interpolation calculations to maintain the stability and responsiveness of the system. When the number of matching rules is 0, interpolation technology is used to ensure smooth adjustment of the activation membership, avoiding excessive delivery or unnecessary energy consumption.

[0100] In traditional PID control, PID parameters Kp, Ki, and Kd are usually fixed. However, in the actual production process, due to environmental changes, these fixed parameters may not provide the best control response. As a preferred embodiment of the above embodiment, the adaptive adjustment algorithm process also includes: dynamically adjusting the parameters of the PID controller based on the target value.

[0101] Specifically, the impact of the target value on the parameters of the PID controller includes three aspects:

[0102] (1) Impact on proportional gain Kp: If the difference between the target value and the current actual value is large, that is, the error is large, the proportional gain Kp should be increased so that the system can respond quickly and reduce the error. Otherwise, the proportional gain Kp should be appropriately reduced to avoid excessive response of the system and maintain a stable state.

[0103] (2) Impact on the integral gain Ki: If the error between the target value and the current output persists, for example, long-term deviations in temperature or conveying speed, the integral gain Ki should be increased to help eliminate the steady-state error; when the error is small or the target value changes greatly, the integral gain Ki should be appropriately reduced to avoid excessive increase in the integral action, resulting in over-regulation;

[0104] (3) Impact on differential gain Kd: If the target value changes quickly, for example, due to frequent input changes in the production process, resulting in rapid changes in the error, the differential gain Kd should be increased to predict future error changes and make appropriate adjustments to avoid overshoot or system oscillation; if the target value changes slowly or the error changes little, the differential gain Kd should be appropriately reduced to avoid overreaction of the system and maintain smooth operation.

[0105] By combining fuzzy control with PID control, the target value provides significant advantages for the dynamic adjustment of the PID controller. The system can respond to various uncertainties, fluctuations and complexities in the production process more flexibly and accurately, and adjust the PID parameters in real time to ensure the stability and efficiency of production. This not only improves the adaptability and robustness of the system, but also effectively reduces energy waste, overshoot, oscillation and other problems, ultimately improving production efficiency, product quality and the stability of the production line.

[0106] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. Double-sided flame-retardant thermal insulation composite board continuous production conveying system, including front-end double crawler, cutting machine, conveying roller, preheating device, high-pressure foaming machine, back-end double crawler and conveying control system; The front double crawler provides the first conveying power for the rock wool composite board by pressure conveying, the cutting machine cuts the formed rock wool composite board transversely to obtain an upper and lower two-layer structure, and the conveying roller conveys the upper and lower two-layer structure to the preheating device for preheating respectively, and continues to convey after preheating; wherein, The conveying roller conveys the lower structure while keeping the height unchanged for passive conveying, and partially lifts the upper structure to a set height and supplies a second conveying power; The high-pressure foaming machine sprays polyurethane toward the upper surface of the preheated lower structure, and the polyurethane foams between the upper and lower structures, and is formed by the subsequent double-track hot pressing to obtain a double-sided flame-retardant thermal insulation composite board; The rear double crawler provides the third conveying power and heat for the double-sided flame-retardant thermal insulation composite board by pressure conveying, and together with the modules on both sides provides a restricted space for the polyurethane foaming molding; It is characterized in that The conveying control system takes the forming parameters of the integrated rock wool composite board and the working state parameters of the slitting machine, conveying roller, preheating device, front track double crawler and back track double crawler as input, and adopts an adaptive adjustment algorithm to output the matching first conveying power, second conveying power and third conveying power; the adaptive adjustment algorithm is based on the combination of fuzzy control and PID control, and the process includes: Collect input real-time data; Input the real-time data into a fuzzy control module, and output target values ​​of the first conveying power, the second conveying power, and the third conveying power; The target value is input into a PID control module, and the first conveying power, the second conveying power and the third conveying power are adjusted according to the target value. And dynamically adjust the parameters of the PID controller based on the target value.

2. The continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels according to claim 1 is characterized in that: The inputs to the conveyor control system include: The forming speed of the rock wool composite board; and, at least one of a tool state, a temperature, a cutting speed, and a jitter amount of the slicer; and, the conveying speed of the conveying roller conveyor upper track, the front track double crawler and the rear track double crawler; And, the temperature control parameters of the preheating device and the subsequent double crawler tracks.

3. The continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels according to claim 1 is characterized in that: The real-time data is input into a fuzzy control module, and target values ​​of the first delivery power, the second delivery power, and the third delivery power are output, including: In the fuzzy control module, a rule base is set based on experience or expert knowledge, wherein the rules in the rule base include a combination of multiple inputs and corresponding outputs; Dividing each of the inputs into a number of fuzzy sets, defining a membership function for each of the fuzzy sets, and converting the real-time data into memberships of different fuzzy sets through the membership function; Matching each rule in the rule base according to the converted membership degree to activate the rule through matching, and performing fuzzy reasoning on the activated rule according to the membership degree to calculate the membership degree of the fuzzy sets of the first transmission power, the second transmission power, and the third transmission power; The output of the fuzzy reasoning is converted into specific numerical values ​​to obtain the target values ​​of the first conveying power, the second conveying power, and the third conveying power.

4. The continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels according to claim 3 is characterized in that: The rules are activated by matching, and the activated rules are subjected to fuzzy reasoning according to the membership degree, including: The number of matched rules is determined. When the number of matched rules is greater than 1, an activation membership is calculated for each activated rule according to the input membership, and the activation memberships are synthesized.

5. The continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels according to claim 4 is characterized in that: The activation membership is calculated based on the input membership, using the minimum method or product method.

6. The continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels according to claim 4 is characterized in that: The activation memberships are synthesized, including: Setting a smoothing coefficient for each of the rules; Assigning a weighted coefficient to the activation membership of each rule to obtain a weighted activation membership, wherein the weighted coefficient is positively correlated with the activation membership; According to the weighted activation membership, smoothing is performed to obtain a synthetic activation membership, and the formula is as follows: ； Where i is the number of each rule.

7. The continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels according to claim 3 is characterized in that: The rules are activated by matching, and the activated rules are subjected to fuzzy reasoning according to the membership degree, including: The number of matched rules is determined, and when the number of matched rules is equal to 0, the rule closest to the current input is detected; the similarity between the input and the detection result is determined, and interpolation is performed according to the similarity to obtain the activation membership after interpolation.

8. The continuous production and conveying system for double-sided flame-retardant thermal insulation composite panels according to claim 7 is characterized in that: The interpolation adopts linear interpolation or weighted average interpolation.

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