Copper clad plate production process ice machine intelligent control system

Abstract

The present application belongs to the technical field of refrigeration energy saving, and discloses an intelligent control system for ice machines in a copper-clad plate production process, which comprises a temperature zone distribution management module, which collects cooling demand parameters of each process on a copper-clad plate production line, sets different temperature zones according to the cooling demand parameters, and divides the main refrigeration output into temperature zone water supply circuits to meet different process demands; and a cold source response distribution module, which is used for evaluating the refrigeration response capacity and real-time load change of each temperature zone water supply circuit, determining the differences in the refrigeration response capacity of each temperature zone water supply circuit according to the evaluation results, and generating corresponding cold distribution instructions; thus, accurate distribution, smooth regulation and efficient utilization of cold are realized, and the temperature control precision and energy efficiency level of the copper-clad plate production process are improved.

Description

Technical Field

[0001] This invention relates to the field of refrigeration and energy-saving technology, and more specifically, to an intelligent control system for an ice machine in the copper-clad laminate production process. Background Technology

[0002] Copper clad laminates (CCLs) are a key basic material in the electronics industry and occupy an indispensable position in the modern electronics and information industry. Throughout the entire CCL production process, the chiller plays a crucial role. In the production processes of some high-end products where the dimensional accuracy and performance stability of CCLs are extremely demanding, the stable low-temperature environment provided by the chiller is indispensable, directly affecting whether the product can meet stringent quality standards.

[0003] The existing intelligent control system for the copper clad laminate production process mainly has the following problems:

[0004] Existing ice machines and cooling systems used in copper-clad laminate (CCL) production processes or similar industrial settings generally suffer from slow response and insufficient adjustment accuracy in multi-temperature zone environments. Traditional systems typically rely on set temperatures or average loads for overall control, failing to fully consider the dynamic and time-varying characteristics of cooling loads in each temperature zone. This results in untimely responses to changes in cooling demand, and the temperature control accuracy is insufficient to meet production process requirements. Particularly in CCL production, different processes have significantly different cooling water temperature requirements. If the control strategy fails to dynamically adapt to the load variation characteristics of each temperature zone, an imbalance between cooling supply and demand can easily occur, leading to overcooling or undercooling in some zones.

[0005] Furthermore, the load change rate and thermal inertia differ significantly across temperature zones. Traditional control methods based on fixed setpoints or proportional allocation cannot adaptively adjust to these differences, easily leading to imbalances in cooling capacity distribution. Some temperature zones experience energy waste due to over-supply of cooling capacity, while others suffer from temperature fluctuations due to insufficient cooling capacity, ultimately resulting in frequent start-ups and shutdowns of the ice machine, increased system energy consumption, and decreased equipment operational stability. Existing cooling systems lack quantitative models of the cooling response capabilities of each temperature zone, making it impossible to assess the sensitivity of each zone to cooling capacity adjustments in real time or scientifically determine its cooling potential. Cooling capacity allocation relies solely on experience or fixed proportional allocation methods, significantly reducing the controllability and economy of system operation.

[0006] Meanwhile, existing refrigeration systems generally suffer from irrational cooling capacity allocation strategies. Traditional methods fail to dynamically and accurately allocate cooling capacity based on the actual cooling response capacity of the water supply loops in each temperature zone, and lack a mechanism to adjust the allocation ratio according to load change trends. Because the thermal inertia and cooling capacity release delay characteristics of heat exchange equipment are not considered, cooling capacity allocation often lags behind actual load changes, making it difficult to achieve coordinated control between multiple temperature zones, resulting in low cooling capacity utilization and limited overall operating efficiency.

[0007] Especially in systems equipped with plate heat exchangers, traditional control strategies generally neglect their thermal inertia characteristics and temperature response hysteresis during the phase change cold storage phase. Plate heat exchangers exhibit significant nonlinear heat transfer relationships during cold storage and release. If the cooling output relies solely on direct regulation without introducing an inertial compensation mechanism, a phase delay can easily occur between the cooling output curve and the load change curve. This not only weakens the real-time performance of the cooling response but also causes frequent start-ups and shutdowns of the refrigeration equipment within a short period, increasing energy consumption and shortening equipment lifespan.

[0008] In view of this, the present invention proposes an intelligent control system for ice machines in the copper clad laminate production process to solve the above problems. Summary of the Invention

[0009] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: an intelligent control system for an ice machine in the copper clad laminate production process, comprising:

[0010] The temperature zone flow management module collects the cooling demand parameters of each process on the copper clad laminate production line, sets different temperature zones according to the cooling demand parameters, and divides the main unit's cooling output into temperature zone water supply loops to meet the different process requirements.

[0011] The cold source response allocation module is used to evaluate the cooling response capability and real-time load changes of the water supply circuit in each temperature zone, determine the differences in cooling response capability of each temperature zone water supply circuit based on the evaluation results, and generate corresponding cooling capacity allocation instructions.

[0012] The plate heat exchanger double-layer temperature control module is used to receive cold energy distribution commands, construct a cold energy storage inertia compensation function based on the phase change cold storage characteristics of the preset plate heat exchanger, evaluate the cold energy response inertia of the preset plate heat exchanger and calculate the compensation amount; perform inertia compensation on the cold energy distribution command based on the compensation amount, and then correct the cold energy output.

[0013] The cooling process monitoring module uses a graphical interface to display the real-time operating status of the water supply circuits in each temperature zone, and provides visualized control over the cooling capacity distribution and inertia compensation process.

[0014] Preferably, the cooling requirement parameters include workshop air conditioning temperature control parameters, water washing tower absorbent temperature control parameters, adhesive liquid temperature control parameters for the mixing process, fluid heat exchange parameters, and dynamic control auxiliary parameters.

[0015] Preferably, the method for setting different temperature zones according to cooling requirement parameters includes:

[0016] The cooling requirements of each process in the copper clad laminate production line are analyzed and clustered. Based on the differences in temperature control accuracy and cooling intensity of different processes, processes with similar cooling requirements are grouped into the same temperature zone. Each temperature zone represents a group of process areas with similar cooling characteristics.

[0017] Preferably, the method for dividing the temperature zone water supply circuit includes:

[0018] The cooling output of the main unit is divided into several temperature zone water supply loops according to the cooling needs of different temperature zones. Each temperature zone water supply loop corresponds to a specific process step. The chilled water circulation flow rate and supply water temperature of each temperature zone water supply loop are independently adjusted by valve groups and variable frequency pumps, thereby realizing independent control and supply of cooling capacity for different temperature zones.

[0019] Preferably, the method for evaluating the cooling response capability and real-time load changes of the water supply circuits in each temperature zone includes:

[0020] Real-time data collection of water supply circuits in each temperature zone, including water supply temperature, return water temperature, chilled water circulation flow rate and temperature control deviation parameters, is used to calculate the instantaneous cooling load. By calculating the difference in instantaneous cooling load between adjacent sampling times and dividing it by a preset sampling time interval, the load change rate is obtained, thereby obtaining the real-time load change of each temperature zone's water supply circuit.

[0021] Based on temperature control deviation, real-time load change, and loop thermal inertia, a cooling response characteristic function is constructed, and the cooling response potential parameters of the water supply loop in each temperature zone are calculated. Based on the real-time load change and cooling response potential parameters, the cooling response capability and real-time load change of the water supply loop in each temperature zone are evaluated.

[0022] Preferably, the method for determining the differences in cooling response capabilities of water supply circuits in each temperature zone includes:

[0023] The cooling response potential parameters are normalized, and the cooling response potential parameters of each temperature zone water supply circuit are mapped to cooling response weights using the Sigmoid function, thereby characterizing the cooling response capability of each temperature zone water supply circuit. Based on the cooling response weights and the current total cooling output of the ice machine, the cooling capacity allocation of each temperature zone water supply circuit is generated.

[0024] Preferably, the method for generating the corresponding cooling capacity allocation instruction includes:

[0025] The system statistically analyzes the cooling capacity distribution of the water supply circuits in each temperature zone and generates corresponding cooling capacity distribution instructions. The cooling capacity distribution instructions include the target water supply temperature and cooling capacity output ratio for each temperature zone. The cooling capacity distribution instructions are then transmitted to the intelligent control terminal of the ice machine to adjust the cooling capacity output of the water supply circuits in each temperature zone in real time, so that the cooling effect of different temperature zones matches the load changes of the corresponding water supply circuits.

[0026] Preferably, the method for calculating and obtaining the compensation amount includes:

[0027] The system receives the cooling capacity allocation command and parses out the corresponding target water supply temperature and cooling capacity output ratio. Based on the physical parameters of the preset plate heat exchanger and the phase change cooling storage characteristics, it constructs a cooling storage inertia compensation function to evaluate the cooling capacity response inertia of the preset plate heat exchanger under the condition of cooling capacity change per unit time, and then calculates and obtains the compensation amount.

[0028] Preferably, the method for correcting the cooling output includes:

[0029] The compensation amount is superimposed on the original cooling output ratio in the cooling distribution command to dynamically correct the cooling output. When the heat load of the temperature zone increases, the cooling output is immediately output through the plate heat exchanger pre-installed on the water supply circuit of the temperature zone. When the heat load of the temperature zone decreases, the plate heat exchanger begins to absorb the cooling output to achieve energy balance and keep the water temperature stable within the preset temperature control range.

[0030] Preferably, the method for visually controlling the cooling capacity distribution and inertia compensation process includes:

[0031] After synchronizing and caching the real-time monitoring data of the water supply circuits in each temperature zone according to the timestamp, the data is mapped to the graphical interface and displayed in the form of a topology map. The current water supply temperature change trend and cooling output level are displayed intuitively through color, curves and numerical labels.

[0032] The display effect is adjusted according to the result of dynamic correction of cooling output. When the cooling output is in the state, the color of the line representing the corresponding temperature zone water supply circuit in the topology diagram gradually darkens. When the cooling absorption is in the state, the color of the line representing the corresponding temperature zone water supply circuit in the topology diagram gradually lightens, thereby realizing the visual control of cooling distribution and inertia compensation process.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] This invention continuously monitors the supply and return water temperatures, chilled water circulation flow rates, and temperature control deviation parameters of each temperature zone, enabling real-time calculation and tracking of the changing trends in cooling demand in the water supply loops of each temperature zone. This accurately reflects the instantaneous cooling load characteristics of different process stages. Compared with previous control methods that relied on fixed set temperatures or empirical parameters, this invention achieves dynamic quantification and accurate identification of cooling demand.

[0035] By constructing a cooling response characteristic function, the cooling response capability of each temperature zone water supply loop can be effectively characterized, and the cooling response potential parameter can be accurately calculated. This allows for a better assessment of the cooling response potential of each temperature zone water supply loop under different conditions, which is beneficial for more refined and efficient control of the cooling system and avoids the problem of relying on experience or fixed proportions for cooling capacity distribution in traditional systems.

[0036] By introducing real-time load change and cooling response capability assessment, high-load or lag-response temperature zones can be identified in advance, enabling feedforward allocation and coordinated control of cooling capacity, thereby reducing problems such as frequent start-stop of the ice machine and compressor overload operation.

[0037] By normalizing the cooling response potential parameters and mapping them to cooling response weights using the Sigmoid function, and then combining this with the total cooling output of the ice machine for cooling capacity allocation, precise cooling capacity allocation can be achieved based on the actual cooling response capacity of the water supply circuits in each temperature zone. This ensures that each temperature zone receives the required cooling capacity, avoiding waste or insufficiency, and also effectively adapts to the dynamically changing cooling demands of each temperature zone, guaranteeing the stability and accuracy of temperature control.

[0038] By defining a cold storage inertia compensation function and combining it with the phase change cold storage characteristics of plate heat exchangers, a quantifiable energy response inertia model was established. This enables the system to perform feedforward compensation based on the trend of cold load changes, eliminating cold load response lag. The cold load distribution command is dynamically corrected through the cold storage inertia compensation function, ensuring coordinated cold load output from plate heat exchangers in different temperature zones. This allows for adaptive adjustment of the cold load supply ratio when the production line's heat load distribution changes, ensuring that the temperature in each zone remains stable within the preset range. Through coordinated control of the plate heat exchanger and the absorbent temperature in the water washing tower, the cooling water temperature and absorbent temperature remain stable within the process requirements. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the intelligent control system for an ice machine in the copper clad laminate production process provided by the present invention;

[0040] Figure 2 This is a schematic diagram of a method for intelligent control of an ice machine in the copper clad laminate production process provided by the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example 1

[0042] Please see Figure 1 As shown in the figure, this embodiment provides an intelligent control system for ice machines in the copper clad laminate production process, which specifically includes the following:

[0043] In the copper clad laminate (CCL) production process, the cooling system is a core component ensuring product quality and production stability. It needs to adapt to the varying temperature zones required for multiple processes, including core fabric impregnation, hot-press curing, and cutting. However, current mainstream cooling systems and their control strategies in multi-temperature environments still have significant technical limitations, failing to meet the high requirements of CCL production for temperature control accuracy, energy efficiency, and equipment stability. Specific problems include the following:

[0044] Significant lag exists in the response to cooling demand in multiple temperature zones: existing cooling systems rely heavily on fixed temperature thresholds or average load calculations for multi-temperature zone control, failing to fully capture the dynamic characteristics and time-varying patterns of cooling load in each zone. In copper-clad laminate production, the cooling load of each process changes in real time with adjustments to production rate, fluctuations in material throughput, and changes in equipment operating status. However, traditional systems only output cooling capacity based on preset temperatures or historical average loads, failing to match the dynamic changes in load in real time, resulting in a time lag between cooling supply and actual demand.

[0045] Insufficient load adaptability leads to a series of operational problems: Significant differences exist in the load change rate and thermal inertia across different temperature zones in copper-clad laminate production. The core fabric impregnation process, due to direct contact with low-temperature cooling water, has low thermal inertia and a rapid load change rate; while the cutting and forming process, due to its large equipment size and long heat dissipation path, has high thermal inertia and a slow load change rate. Traditional control strategies employ a uniform adjustment logic without dynamically adapting to these differences. When a sudden load increase occurs in a certain temperature zone, the system may excessively increase the overall cooling output, leading to over-supply of cooling in other temperature zones with higher thermal inertia, causing condensation on the equipment. Conversely, if the system reduces cooling output due to a decrease in the load in a certain temperature zone, it may result in insufficient cooling in temperature zones with rapidly changing loads.

[0046] The lack of scientific basis and insufficient precision in cooling capacity allocation: Existing refrigeration systems cannot quantitatively assess the sensitivity of cooling capacity adjustment in each temperature zone, nor can they monitor the cooling response potential of each temperature zone in real time. This lack of information leads to a lack of scientific support in the cooling capacity allocation process, relying solely on operator experience or allocation according to fixed proportions (such as the power ratio of equipment in each temperature zone). This extensive allocation method is difficult to adapt to the dynamically changing cooling demands of each temperature zone: when a temperature zone needs to increase its cooling capacity supply due to process adjustments, the system may not be able to allocate sufficient cooling capacity in a timely manner due to fixed proportion limitations; conversely, when the load in a temperature zone decreases, it is impossible to accurately transfer redundant cooling capacity to other demanding temperature zones, resulting in excess cooling capacity in some temperature zones and insufficient cooling capacity in others, severely restricting the overall operating efficiency and temperature control effect of the refrigeration system.

[0047] Static control methods ignore thermal inertia and phase change delay, exacerbating phase differences: Traditional refrigeration systems often use static control methods based on fixed thresholds or proportional valves for cooling capacity distribution. This fails to consider the thermal inertia characteristics of plate heat exchangers in copper-clad laminate (CCL) production cooling systems, as well as the phase change delay effect in the cold storage stage. This results in a significant phase delay between cooling capacity output and actual heat load changes on the production line. When the production line's heat load has decreased, the system may still be outputting high cooling capacity, leading to oversupply; conversely, when the heat load has increased, the system's cooling capacity cannot keep up, resulting in undersupply. This phase difference not only further reduces temperature control accuracy but also causes the ice machine to fall into a cycle of over-adjustment and reverse correction, exacerbating frequent equipment start-ups and shutdowns, increasing energy consumption and equipment fatigue, and making it difficult to smoothly cope with sudden load changes in CCL production.

[0048] Against this backdrop, the present invention proposes an intelligent control system for ice machines in the copper clad laminate production process, specifically comprising:

[0049] The temperature zone flow management module collects the cooling demand parameters of each process on the copper clad laminate production line, sets different temperature zones according to the cooling demand parameters, and divides the main unit's cooling output into temperature zone water supply loops to meet the different process requirements.

[0050] The cold source response allocation module is used to evaluate the cooling response capability and real-time load changes of the water supply circuit in each temperature zone, determine the differences in cooling response capability of each temperature zone water supply circuit based on the evaluation results, and generate corresponding cooling capacity allocation instructions.

[0051] The plate heat exchanger double-layer temperature control module is used to receive cold energy distribution commands, construct a cold energy storage inertia compensation function based on the phase change cold storage characteristics of the preset plate heat exchanger, evaluate the cold energy response inertia of the preset plate heat exchanger and calculate the compensation amount; perform inertia compensation on the cold energy distribution command based on the compensation amount, and then correct the cold energy output.

[0052] The cooling process monitoring module uses a graphical interface to display the real-time operating status of the water supply circuits in each temperature zone, and provides visualized control over the cooling capacity distribution and inertia compensation process.

[0053] Cooling requirements parameters include workshop air conditioning temperature control parameters, water washing tower absorbent temperature control parameters, adhesive mixing process adhesive temperature control parameters, fluid heat exchange parameters, and dynamic control auxiliary parameters.

[0054] The temperature control parameters of the workshop air conditioning reflect the impact of the overall production environment on the load of the water supply circuit and are used in the calculation of the cooling capacity demand of the workshop air conditioning, including ambient temperature, relative humidity, temperature difference between air conditioning supply and return air and air conditioning supply volume.

[0055] The temperature control parameters of the absorbent liquid in the water washing tower are used to describe the cooling requirements of the liquid medium in the water washing tower during the cleaning process of copper clad laminate production, including the inlet and outlet temperatures of the absorbent liquid, the circulation flow rate and heat exchange efficiency of the absorbent liquid, and the level and concentration of the absorbent liquid.

[0056] The temperature control parameters of the resin solution in the mixing process are used to reflect the exothermic reaction characteristics and cooling requirements of the resin mixing process, including the reaction temperature and target maintenance temperature parameters, the reaction exothermic rate parameters, the stirring power and the cooling water flow rate.

[0057] Fluid heat exchange parameters include the supply water temperature, return water temperature, chilled water circulation flow rate, and temperature control deviation parameters of each temperature zone's water supply circuit, which are used to evaluate the cooling response capability and real-time load changes of each temperature zone's water supply circuit; dynamic control auxiliary parameters include the temperature zone number and water supply circuit topology information.

[0058] Methods for setting different temperature zones based on cooling requirement parameters include:

[0059] Feature analysis (statistical analysis) and k-means clustering were performed on the cooling demand parameters of each process in the copper clad laminate production line. Based on the differences in temperature control accuracy and cooling intensity among different processes, processes with similar cooling demands (the difference in cooling demand between two processes reaches a preset cooling demand difference threshold) were grouped into the same temperature zone. Each temperature zone represents a group of process areas with similar cooling characteristics. For example, processes with high temperature control accuracy requirements and frequent load changes were set up as independent temperature zones; while processes with similar temperature control requirements and relatively stable load changes could be combined and set up into the same temperature zone.

[0060] The methods for dividing temperature zone water supply circuits include:

[0061] The cooling output of the main unit is divided into several temperature zone water supply loops according to the cooling needs of different temperature zones. Each temperature zone water supply loop corresponds to a specific process step. The chilled water circulation flow rate and supply water temperature of each temperature zone water supply loop are independently adjusted by valve groups and variable frequency pumps, thereby realizing independent control and supply of cooling capacity for different temperature zones. This not only ensures the stability of temperature control in each process, but also improves the energy efficiency of the overall refrigeration system.

[0062] Methods for evaluating the cooling response capability and real-time load changes of water supply circuits in each temperature zone include:

[0063] Real-time acquisition of operational data from the water supply circuits in each temperature zone, including supply water temperature, return water temperature, chilled water circulation flow rate, and temperature control deviation parameters, to calculate instantaneous cooling load. ;in, Indicates the first Each temperature zone water supply circuit is in Instantaneous cooling load at any given moment; Indicates the density of chilled water; This indicates the specific heat capacity of chilled water; Indicates the first Each temperature zone water supply circuit is in The chilled water circulation flow rate at any given time; Indicates the first Each temperature zone water supply circuit is in The return water temperature at any given time; Indicates the first Each temperature zone water supply circuit is in The water supply temperature at any given time; Indexes representing water supply circuits in different temperature zones; An index representing time;

[0064] By calculating the instantaneous cooling load difference between adjacent sampling times and dividing it by a preset sampling time interval to obtain the load change rate, the real-time load change of each temperature zone's water supply circuit can be obtained. ;in, This indicates the preset sampling time interval; Indicates the time interval between preset sampling times. Within, the rate of change of cooling load over time in each temperature zone water supply circuit;

[0065] To characterize the cooling response capability of the water supply loops in each temperature zone, a cold source response potential function is introduced: a cooling response characteristic function is constructed based on temperature control deviation, real-time load change, and loop thermal inertia, and the cooling response potential parameters of the water supply loops in each temperature zone are calculated. ;in, Indicates the first Each temperature zone water supply circuit is in Cooling response potential parameters at any given time; Indicates the first The response gain coefficient of each temperature zone water supply loop is used to characterize the amplification capability of the temperature zone water supply loop to the cooling output under heat load changes. The response gain coefficient is obtained by monitoring the deviation between the target supply water temperature and the return water temperature of the temperature zone and calculating the proportional relationship between the temperature difference change and the cooling output change. Indicates the first The target temperature for each temperature zone water supply circuit; Indicates the first The inertial regulation coefficient of each temperature zone water supply loop is used to reflect the lag and regulation speed of the cooling capacity change in the temperature zone water supply loop. The inertial regulation coefficient is determined by calculating the time delay ratio of the cooling capacity response by statistically analyzing the response time of the cooling capacity output signal.

[0066] The following technical problems of the existing technology have been solved: In multi-temperature zone environments, existing ice machines or cooling systems are usually controlled only based on the set temperature or average load, which fails to fully consider the dynamic and time-varying characteristics of the cooling load changes in each temperature zone, resulting in a lag in the system's response to changes in cooling demand and difficulty in meeting actual needs in terms of temperature control accuracy.

[0067] Because there are significant differences in the load change rate and thermal inertia of different temperature zones, traditional control strategies are difficult to dynamically adjust these differences, which can easily lead to oversupply or undersupply of cooling capacity in some temperature zones, resulting in frequent start-ups and shutdowns of the chiller, increased energy consumption, and reduced equipment operating stability.

[0068] Existing refrigeration systems cannot quantify the sensitivity of different temperature zones to cooling capacity adjustment, nor can they assess their cooling response potential in real time. This results in a lack of scientific basis for cooling capacity allocation, which can only rely on experience or be allocated according to a fixed ratio.

[0069] Compared with existing technologies, the advantages are: by continuously monitoring the supply and return water temperatures, chilled water circulation flow rates, and temperature control deviation parameters of each temperature zone, the cooling demand of each temperature zone's water supply circuit can be calculated and tracked in real time, thereby accurately reflecting the instantaneous cooling load characteristics of different process links. Compared with the previous control methods that relied on fixed set temperatures or empirical parameters, dynamic quantification and accurate identification of cooling demand have been achieved.

[0070] By constructing a cooling response characteristic function, the cooling response capability of each temperature zone water supply loop can be effectively characterized, and the cooling response potential parameter can be accurately calculated. This allows for a better assessment of the cooling response potential of each temperature zone water supply loop under different conditions, which is beneficial for more refined and efficient control of the cooling system and avoids the problem of relying on experience or fixed proportions for cooling capacity distribution in traditional systems.

[0071] By introducing real-time load change and cooling response capability assessment, high-load or lag-response temperature zones can be identified in advance, enabling feedforward allocation and coordinated control of cooling capacity, thereby reducing problems such as frequent start-stop of the ice machine and compressor overload operation.

[0072] Methods for determining the differences in cooling response capabilities of water supply circuits in different temperature zones include:

[0073] The cooling response potential parameters are normalized, and the sigmoid function is used to map the cooling response potential parameters of each temperature zone water supply loop to cooling response weights, thereby characterizing the cooling response capability of each temperature zone water supply loop. Based on the cooling response weights and the current total cooling output of the ice machine, the cooling capacity allocation of each temperature zone water supply loop is generated. ;in, Indicates the first Each temperature zone water supply circuit is in Cooling distribution at any given time; Indicates the first Each temperature zone water supply circuit is in The weight of the cooling response at any given moment; Indicates in Total cooling output of the ice machine at all times; This represents the weighted sum of the cooling response weights of all temperature zone water supply circuits, used to ensure that the total cooling capacity distribution equals the current total cooling output of the ice machine;

[0074] The following technical problems of the existing technology have been solved: The existing technology is unreasonable in terms of cooling capacity distribution. For example, it cannot dynamically and accurately distribute cooling capacity according to the actual cooling response capacity of the water supply circuit of each temperature zone, resulting in excess or insufficient cooling capacity in some temperature zones, which affects the overall operating efficiency and temperature control effect of the refrigeration system; it also lacks a reasonable method to guide the distribution of cooling capacity, which makes the distribution of cooling capacity lack a scientific basis and difficult to adapt to the dynamically changing cooling needs of each temperature zone.

[0075] Compared to existing technologies, the advantages are as follows: By normalizing the cooling response potential parameters and mapping them to cooling response weights using the Sigmoid function, and then combining this with the total cooling output of the ice machine for cooling capacity allocation, precise cooling capacity allocation can be achieved based on the actual cooling response capacity of the water supply circuit in each temperature zone. This ensures that each temperature zone receives the cooling capacity required to meet its needs, avoiding waste or insufficient cooling capacity, and also adapts well to the dynamically changing cooling demands of each temperature zone, ensuring the stability and accuracy of temperature control.

[0076] Methods for generating corresponding cooling capacity allocation instructions include:

[0077] The system statistically analyzes the cooling capacity distribution of the water supply circuits in each temperature zone and generates corresponding cooling capacity distribution instructions. The cooling capacity distribution instructions include the target water supply temperature and cooling capacity output ratio for each temperature zone. The cooling capacity distribution instructions are then transmitted to the intelligent control terminal of the ice machine to adjust the cooling capacity output of the water supply circuits in each temperature zone in real time, so that the cooling effect of different temperature zones matches the load changes of the corresponding water supply circuits.

[0078] Methods for calculating and obtaining compensation amounts include:

[0079] The system receives the cooling capacity allocation command and parses out the corresponding target water supply temperature and cooling capacity output ratio. Based on the physical parameters of the preset plate heat exchanger and the phase change cooling storage characteristics, it constructs a cooling storage inertia compensation function to evaluate the cooling capacity response inertia of the preset plate heat exchanger under the condition of cooling capacity change per unit time, and then calculates and obtains the compensation amount.

[0080] The cold storage inertia compensation function is: ;in, Indicates the first Each temperature zone The compensation amount at time t; indicating the compensation amount at time t; Ice storage tanks in various temperature zones Energy storage ratio at any given time; Indicates the first The temperature gradient of the phase change layer in each temperature zone is calculated by the ratio of the temperature difference between the upper and lower parts of the phase change layer to the layer thickness. Represents the weighting function of the cold storage layer response; The phase change response coefficient reflects the thermal conductivity and heat exchange rate of the cold storage material. The larger the value, the faster the cold energy is released.

[0081] Phase change cold storage characteristics include the heat transfer efficiency, latent heat release rate, and ice layer thickness variation law of plate heat exchangers during the phase change cold storage stage, which are used to characterize the energy response inertia of a pre-set plate heat exchanger under changes in cooling capacity.

[0082] This solution addresses the following technical problems of existing technologies: Traditional refrigeration systems often employ static methods based on fixed thresholds or proportional valve control for cold energy distribution, neglecting the thermal inertia characteristics and temperature response hysteresis effect of plate heat exchangers during the phase change cold storage phase. This results in a significant phase delay between cold energy output and changes in the production line's heat load. Traditional cold energy control strategies do not consider the phase change delay characteristics and nonlinear heat transfer relationship of the cold storage system. Cold energy output is often directly adjusted, making it difficult to smoothly respond to sudden load changes, leading to frequent start-ups and shutdowns of ice machines, increased energy consumption, and equipment fatigue.

[0083] The advantages over existing technologies are as follows: By defining a cold storage inertia compensation function and combining it with the phase change cold storage characteristics of plate heat exchangers, a quantifiable energy response inertia model is established, enabling the system to perform feedforward compensation based on the trend of cold load changes, thus eliminating cold load response lag. The cold load distribution command is dynamically corrected through the cold storage inertia compensation function, ensuring that the cold load output of plate heat exchangers in different temperature zones is coordinated. This allows for adaptive adjustment of the cold load supply ratio when the heat load distribution of the production line changes, ensuring that the temperature in each temperature zone remains stable within the preset range. Through the coordinated control of the plate heat exchanger and the absorbent temperature of the water washing tower, the cooling water temperature and absorbent temperature remain stable within the process requirements.

[0084] Methods for correcting cooling output include:

[0085] The compensation amount is superimposed on the original cooling output ratio in the cooling distribution command to dynamically correct the cooling output. When the heat load of the temperature zone increases, the cooling output is immediately output through the plate heat exchanger pre-installed on the water supply circuit of the temperature zone. When the heat load of the temperature zone decreases, the plate heat exchanger begins to absorb the cooling output to achieve energy balance and keep the water temperature stable within the preset temperature control range.

[0086] Methods for visualizing and coordinating the cooling capacity distribution and inertia compensation processes include:

[0087] After synchronizing and caching the real-time monitoring data of the water supply circuits in each temperature zone according to the timestamp, the data is mapped to the graphical interface and displayed in the form of a topology map. The current water supply temperature change trend and cooling output level are displayed intuitively through color, curve and numerical labels. Maintenance personnel can quickly identify the temperature control stability and load distribution of each temperature zone through the graphical interface.

[0088] The display effect is adjusted according to the result of dynamic correction of cooling output. When the cooling output is in the state, the color of the line representing the corresponding temperature zone water supply circuit in the topology diagram gradually darkens. When the cooling absorption is in the state, the color of the line representing the corresponding temperature zone water supply circuit in the topology diagram gradually lightens, reflecting the process of cooling release and absorption, thereby realizing the visual control of cooling distribution and inertial compensation process.

[0089] In this embodiment, by continuously monitoring the supply and return water temperatures, chilled water circulation flow rates, and temperature control deviation parameters of each temperature zone, the cooling demand change trend of each temperature zone's water supply circuit can be calculated and tracked in real time, thereby accurately reflecting the instantaneous cooling load characteristics of different process links. Compared with the previous control methods that relied on fixed set temperatures or empirical parameters, dynamic quantification and accurate identification of cooling demand have been achieved.

[0090] By constructing a cooling response characteristic function, the cooling response capability of each temperature zone water supply loop can be effectively characterized, and the cooling response potential parameter can be accurately calculated. This allows for a better assessment of the cooling response potential of each temperature zone water supply loop under different conditions, which is beneficial for more refined and efficient control of the cooling system and avoids the problem of relying on experience or fixed proportions for cooling capacity distribution in traditional systems.

[0091] By introducing real-time load change and cooling response capability assessment, high-load or lag-response temperature zones can be identified in advance, enabling feedforward allocation and coordinated control of cooling capacity, thereby reducing problems such as frequent start-stop of the ice machine and compressor overload operation.

[0092] By normalizing the cooling response potential parameters and mapping them to cooling response weights using the Sigmoid function, and then combining this with the total cooling output of the ice machine for cooling capacity allocation, precise cooling capacity allocation can be achieved based on the actual cooling response capacity of the water supply circuits in each temperature zone. This ensures that each temperature zone receives the required cooling capacity, avoiding waste or insufficiency, and also effectively adapts to the dynamically changing cooling demands of each temperature zone, guaranteeing the stability and accuracy of temperature control.

[0093] By defining a cold storage inertia compensation function and combining it with the phase change cold storage characteristics of plate heat exchangers, a quantifiable energy response inertia model was established. This enables the system to perform feedforward compensation based on the trend of cold load changes, eliminating cold load response lag. The cold load distribution command is dynamically corrected through the cold storage inertia compensation function, ensuring coordinated cold load output from plate heat exchangers in different temperature zones. This allows for adaptive adjustment of the cold load supply ratio when the production line's heat load distribution changes, ensuring that the temperature in each zone remains stable within the preset range. Through coordinated control of the plate heat exchanger and the absorbent temperature in the water washing tower, the cooling water temperature and absorbent temperature remain stable within the process requirements. Example 2

[0094] Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A method for intelligent control of an ice machine in the copper clad laminate production process is provided, including:

[0095] S1. Collect the cooling demand parameters of each process on the copper clad laminate production line, set different temperature zones according to the cooling demand parameters, and divide the main unit cooling output into temperature zone water supply loops to meet different process requirements.

[0096] S2 is used to evaluate the cooling response capability and real-time load changes of the water supply circuit in each temperature zone, determine the differences in cooling response capability of each temperature zone water supply circuit based on the evaluation results, and generate corresponding cooling capacity allocation instructions.

[0097] S3 is used to receive the cold energy distribution command, construct the cold energy storage inertia compensation function based on the phase change cold energy storage characteristics of the preset plate heat exchanger, evaluate the cold energy response inertia of the preset plate heat exchanger and calculate the compensation amount; perform inertia compensation on the cold energy distribution command based on the compensation amount, and then correct the cold energy output.

[0098] S4. A graphical interface is used to display the real-time operating status of the water supply circuits in each temperature zone, and the cooling capacity distribution and inertia compensation process are visualized and controlled.

[0099] Since the electronic device described in this embodiment is the electronic device used in implementing the intelligent control system for an ice machine in a copper-clad laminate production process as described in this application, those skilled in the art can understand the specific implementation methods and various variations of the electronic device in this embodiment based on the intelligent control system for an ice machine in a copper-clad laminate production process described in this application. Therefore, how the electronic device implements the method in this application will not be described in detail here. Any electronic device used by those skilled in the art in implementing the intelligent control system for an ice machine in a copper-clad laminate production process as described in this application falls within the scope of protection of this application.

[0100] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0101] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for users of ordinary technical skills, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. An intelligent control system for an ice machine in the copper clad laminate production process, characterized in that, include: The temperature zone flow management module collects the cooling demand parameters of each process on the copper clad laminate production line, sets different temperature zones according to the cooling demand parameters, and divides the main unit's cooling output into temperature zone water supply loops to meet the different process requirements. The cold source response allocation module is used to evaluate the cooling response capability and real-time load changes of the water supply circuit in each temperature zone, determine the differences in cooling response capability of each temperature zone water supply circuit based on the evaluation results, and generate corresponding cooling capacity allocation instructions. The method for evaluating the cooling response capability and real-time load changes of the water supply circuits in each temperature zone includes: Real-time data collection of water supply circuits in each temperature zone, including water supply temperature, return water temperature, chilled water circulation flow rate and temperature control deviation parameters, is used to calculate the instantaneous cooling load. By calculating the difference in instantaneous cooling load between adjacent sampling times and dividing it by a preset sampling time interval, the load change rate is obtained, thereby obtaining the real-time load change of each temperature zone's water supply circuit. Instantaneous cooling load ;in, Indicates the first Each temperature zone water supply circuit is in Instantaneous cooling load at any given moment; Indicates the density of chilled water; This indicates the specific heat capacity of chilled water; Indicates the first Each temperature zone water supply circuit is in The chilled water circulation flow rate at any given time; Indicates the first Each temperature zone water supply circuit is in The return water temperature at any given time; Indicates the first Each temperature zone water supply circuit is in The water supply temperature at any given time; Indexes representing water supply circuits in different temperature zones; An index representing time; Real-time load changes of water supply circuits in each temperature zone ;in, Indicates the preset sampling time interval; Indicates the time interval between preset sampling times. Within, the rate of change of cooling load over time in each temperature zone water supply circuit; Based on temperature control deviation, real-time load change and loop thermal inertia, a cooling response characteristic function is constructed, and the cooling response potential parameters of the water supply loop in each temperature zone are calculated. Based on the real-time load change and cooling response potential parameters, the cooling response capability and real-time load change of the water supply loop in each temperature zone are evaluated. Cooling response potential parameters ;in, Indicates the first Each temperature zone water supply circuit is in Cooling response potential parameters at any given time; Indicates the first The response gain coefficient of each temperature zone water supply loop is used to characterize the amplification capability of the temperature zone water supply loop to the cooling output under heat load changes. The response gain coefficient is obtained by monitoring the deviation between the target supply water temperature and the return water temperature of the temperature zone and calculating the proportional relationship between the temperature difference change and the cooling output change. Indicates the first The target temperature for each temperature zone water supply circuit; Indicates the first The inertial adjustment coefficient of the water supply circuit in each temperature zone; The method for determining the differences in cooling response capabilities of water supply circuits in different temperature zones includes: The cooling response potential parameters are normalized, and the cooling response potential parameters of each temperature zone water supply circuit are mapped to cooling response weights using the Sigmoid function, thereby characterizing the cooling response capability of each temperature zone water supply circuit; based on the cooling response weights and the current total cooling output of the ice machine, the cooling capacity allocation of each temperature zone water supply circuit is generated. Cooling distribution ;in, Indicates the first Each temperature zone water supply circuit is in Cooling distribution at any given time; Indicates the first Each temperature zone water supply circuit is in The weight of the cooling response at any given moment; Indicates in Total cooling output of the ice machine at all times; This represents the weighted sum of the cooling response weights of all temperature zone water supply circuits, used to ensure that the total cooling capacity distribution equals the current total cooling output of the ice machine; The plate heat exchanger double-layer temperature control module is used to receive cold energy distribution commands, construct a cold energy storage inertia compensation function based on the phase change cold storage characteristics of the preset plate heat exchanger, evaluate the cold energy response inertia of the preset plate heat exchanger and calculate the compensation amount; perform inertia compensation on the cold energy distribution command based on the compensation amount, and then correct the cold energy output. The cooling process monitoring module uses a graphical interface to display the real-time operating status of the water supply circuits in each temperature zone, and provides visualized control over the cooling capacity distribution and inertia compensation process.

2. The intelligent control system for the ice machine in the copper clad laminate production process according to claim 1, characterized in that, The cooling requirements parameters include workshop air conditioning temperature control parameters, water washing tower absorbent temperature control parameters, adhesive mixing process adhesive temperature control parameters, fluid heat exchange parameters, and dynamic control auxiliary parameters.

3. The intelligent control system for the ice machine in the copper clad laminate production process according to claim 2, characterized in that, The method for setting different temperature zones based on cooling demand parameters includes: The cooling requirements of each process in the copper clad laminate production line are analyzed and clustered. Based on the differences in temperature control accuracy and cooling intensity of different processes, processes with similar cooling requirements are grouped into the same temperature zone. Each temperature zone represents a group of process areas with similar cooling characteristics.

4. The intelligent control system for the ice machine in the copper clad laminate production process according to claim 3, characterized in that, The method for dividing the temperature zone water supply circuit includes: The cooling output of the main unit is divided into several temperature zone water supply loops according to the cooling needs of different temperature zones. Each temperature zone water supply loop corresponds to a specific process step. The chilled water circulation flow rate and supply water temperature of each temperature zone water supply loop are independently adjusted by valve groups and variable frequency pumps, thereby realizing independent control and supply of cooling capacity for different temperature zones.

5. The intelligent control system for the ice machine in the copper clad laminate production process according to claim 4, characterized in that, The method for generating the corresponding cooling capacity allocation instruction includes: The system statistically analyzes the cooling capacity distribution of the water supply circuits in each temperature zone and generates corresponding cooling capacity distribution instructions. The cooling capacity distribution instructions include the target water supply temperature and cooling capacity output ratio for each temperature zone. The cooling capacity distribution instructions are then transmitted to the intelligent control terminal of the ice machine to adjust the cooling capacity output of the water supply circuits in each temperature zone in real time, so that the cooling effect of different temperature zones matches the load changes of the corresponding water supply circuits.

6. The intelligent control system for the ice machine in the copper clad laminate production process according to claim 5, characterized in that, The method for calculating and obtaining the compensation amount includes: The system receives the cooling capacity allocation command and parses out the corresponding target water supply temperature and cooling capacity output ratio. Based on the physical parameters of the preset plate heat exchanger and the phase change cooling storage characteristics, it constructs a cooling storage inertia compensation function to evaluate the cooling capacity response inertia of the preset plate heat exchanger under the condition of cooling capacity change per unit time, and then calculates and obtains the compensation amount.

7. The intelligent control system for the ice machine in the copper clad laminate production process according to claim 6, characterized in that, The method for correcting the cooling output includes: The compensation amount is superimposed on the original cooling output ratio in the cooling distribution command to dynamically correct the cooling output. When the heat load of the temperature zone increases, the cooling output is immediately output through the plate heat exchanger pre-installed on the water supply circuit of the temperature zone. When the heat load of the temperature zone decreases, the plate heat exchanger begins to absorb the cooling output to achieve energy balance and keep the water temperature stable within the preset temperature control range.

8. The intelligent control system for the ice machine in the copper clad laminate production process according to claim 7, characterized in that, The method for visualizing and controlling the cooling capacity distribution and inertia compensation process includes: After synchronizing and caching the real-time monitoring data of the water supply circuits in each temperature zone according to the timestamp, the data is mapped to the graphical interface and displayed in the form of a topology map. The current water supply temperature change trend and cooling output level are displayed intuitively through color, curves and numerical labels. The display effect is adjusted according to the result of dynamic correction of cooling output. When the cooling output is in the state, the color of the line representing the corresponding temperature zone water supply circuit in the topology diagram gradually darkens. When the cooling absorption is in the state, the color of the line representing the corresponding temperature zone water supply circuit in the topology diagram gradually lightens, thereby realizing the visual control of cooling distribution and inertia compensation process.

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