Intelligent heat preservation system and method for printing machine
By integrating detection, preprocessing, trend prediction, and adaptive control units into the printing press, the problem of lag in response of traditional temperature control systems has been solved, enabling precise adjustment and stabilization of printing press temperature, thereby improving printing quality and equipment efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHONGQING KEXIN PLASTIC
- Filing Date
- 2024-11-27
- Publication Date
- 2026-05-29
AI Technical Summary
Traditional printing press temperature control systems lack the ability to respond in real time to changes in the external environment and equipment status, resulting in lagging temperature control adjustment and difficulty in accurately responding to complex temperature control needs, which affects printing quality and equipment operating efficiency.
The system employs a detection unit, a preprocessing unit, an adaptive trend prediction unit, an adaptive control unit, and a control unit. It collects temperature and environmental parameters in real time through a sensor network, uses preprocessing and regression models to predict temperature change trends, and combines a decision tree model to dynamically adjust the heater and cooling device to ensure that the temperature remains stable within the target range.
It improves temperature control accuracy and response speed, reduces the impact of temperature fluctuations on printing quality, avoids energy waste, and achieves stability and high efficiency in printing press operation.
Smart Images
Figure CN122111142A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of printing presses, and more specifically to an intelligent heat preservation system and method for printing presses. Background Technology
[0002] Printing presses require high temperature stability during operation, and the performance of the temperature control system directly affects print quality and equipment efficiency. Suitable and stable temperature conditions during printing not only ensure good ink adhesion and uniform distribution but also reduce changes in material properties caused by temperature fluctuations. Traditional printing press insulation methods typically employ simple temperature control techniques, such as using heaters of fixed power or basic temperature control devices to regulate the equipment temperature. While this method can meet temperature control requirements to some extent, it has significant drawbacks: On the one hand, traditional systems lack the ability to respond in real time to changes in the external environment and equipment status, resulting in a lag in temperature control. For example, when the ambient temperature and humidity change or the equipment operating conditions fluctuate, traditional temperature control systems cannot adapt quickly, which may cause problems such as excessively high or low temperatures, affecting printing quality.
[0003] On the other hand, traditional insulation systems typically rely on simple on / off control using preset thresholds, making it difficult to accurately respond to complex temperature control requirements. Therefore, to address these issues, an intelligent insulation system and method for printing presses are needed. Summary of the Invention
[0004] This invention addresses the shortcomings of existing technologies by proposing an intelligent heat preservation system and method for printing presses. The specific technical solution is as follows: One specific technical solution for an intelligent heat preservation system for printing presses is as follows: A smart heat preservation system for printing presses, characterized in that: It includes a detection unit, a preprocessing unit, an adaptive trend prediction unit, an adaptive control unit, and a control unit; The acquisition end of the detection unit is connected to the input end of the prediction unit via a data bus; the output end of the preprocessing unit is connected to the adaptive trend prediction unit via a data bus; the output end of the adaptive trend prediction unit is connected to the adaptive control unit via a data bus; and the adaptive control unit is connected to the control unit via a data bus. The detection unit collects the temperature and environmental parameters of the printing press in real time through a sensor network. The preprocessing unit is used to preprocess the data collected by the detection unit to obtain effective temperature characteristics. The adaptive trend prediction unit is used to predict the temperature change trend of the printing press over a period of time based on the temperature features extracted by the preprocessing unit, and to generate a heat balance index. The adaptive control unit is used to determine whether the temperature of the printing press deviates from the target range based on the effective temperature characteristics and thermal balance index, and to generate an adjustment command when it deviates from the preset range. The control unit is used to receive the adjustment command and dynamically adjust the heater power and the operating status of the cooling device to keep the temperature stable within the set range.
[0005] To better realize the present invention, the detection unit may further include a thermocouple sensor and a temperature and humidity sensor; The thermocouple sensors are arranged on the heating assembly and the printing roller to monitor the internal temperature of the heater and the surface temperature of the roller. The ambient temperature and humidity sensor is used to collect ambient temperature and relative humidity in real time.
[0006] Furthermore, the adaptive control unit includes a decision tree model. Based on real-time temperature characteristics and thermal balance state estimates, the adaptive control unit constructs an adaptive control decision tree model. The root node of the decision tree model takes the real-time effective temperature characteristics and thermal balance state estimates as inputs, serving as the initial judgment basis for the control logic. The branch nodes of the decision tree model, based on temperature control logic rules, determine whether the temperature deviates from the target range layer by layer, and generate specific adjustment instructions based on the node judgment results to guide the control unit to adjust the operating state of the printing press.
[0007] The specific technical solution for the working method of an intelligent heat preservation system for printing presses is as follows: A control method for an intelligent heat preservation system for a printing press, characterized in that: Includes the following steps: S1: The detection unit monitors the temperature of the heating component and the printing cylinder through a thermocouple sensor, and at the same time collects the temperature and humidity parameters of the environment around the printing press through a temperature and humidity sensor to form raw data; S2: The preprocessing unit preprocesses the raw data to generate usable temperature feature values, and stores the processed temperature feature values in the database. S3: The trend prediction unit receives the preprocessed temperature feature value, uses a regression model to predict the temperature change trend of the printing press in the future time period, and generates a thermal balance state index, which is simultaneously stored in the database. S4: The decision tree model within the adaptive control unit combines real-time temperature feature values and thermal balance state indicators to determine whether the current temperature state deviates from the target range according to set rules. If the decision tree model determines that adjustment is needed, proceed to S5 to generate the corresponding adjustment instruction; If the decision tree model determines that no adjustment is needed, proceed to S7 and maintain the current operating state; S5: The adaptive control unit generates specific instructions according to the control logic and sends them to the control unit until the environment stabilizes within the target range; S6: The control unit adjusts the power output of the heater and the operating status of the cooler in real time according to the received adjustment command to ensure that the printing press temperature reaches and is maintained within the target range; S7: The control unit maintains the system in its current state.
[0008] Furthermore: In S3, the trend prediction unit is equipped with a regression model. The trend prediction unit receives preprocessed temperature feature values and uses the regression model to predict the temperature change trend of the printing press over a future period of time, generating a thermal balance state index.
[0009] Furthermore: at the root node of the decision tree model, the decision tree model determines whether the temperature of the current printing press will deviate from the target range over a period of time based on the input data, and selects the subsequent path based on the determination result; If the temperature deviates from the target range, the decision tree model further splits into multiple sub-nodes, evaluates the system state and operating parameters layer by layer, and determines the optimal control scheme based on the threshold conditions of each node. As the decision tree model refines the judgment layer by layer along the branch path, it generates specific control instructions to adjust the power of the heater or the operating status of the cooling device. If the temperature is determined to be within the target range, the decision tree model will maintain the current system operating state and will not perform any additional adjustments.
[0010] Furthermore: the detection unit collects temperature and humidity parameters of the environment surrounding the printing press via a temperature and humidity sensor, forming raw data D:
[0011] in, This refers to the sampling time point; For time The collected temperature values; For time The collected humidity values; The preprocessing unit preprocesses the original data D to generate a usable input feature vector F:
[0012] in: To use the feature fusion function Extracted comprehensive feature values; The preprocessing unit stores the input feature vector F in the value database; The trend prediction unit receives preprocessed input feature values F, and uses the following regression model to predict the predicted temperature value at time point t:
[0013] in, The predicted temperature for time t; Input feature values; , , , These are the parameters to be estimated for the model; The regression model utilizes the input features F from historical data and minimizes the error function. To determine the parameters:
[0014] The trend prediction unit uses a regression model to predict the temperature over a period of time t, thus obtaining a set of predicted temperature values for that time period. , These are discrete time points in the future.
[0015] The trend prediction unit calculates the average of these predicted temperature values as an indicator of thermal equilibrium. :
[0016] The trend prediction unit will use the thermal balance state index Save to the database.
[0017] The beneficial effects of this invention are as follows: The overall structure is simple. By setting up several modules including a detection unit, a preprocessing unit, an adaptive trend prediction unit, an adaptive control unit, and a control unit, the detection unit collects the temperature and environmental parameters of the printing press in real time through a sensor network. The preprocessing unit extracts effective data, and combined with the regression model of the trend prediction unit, the system can predict future temperature change trends and generate thermal balance state indicators, providing data for subsequent control. This significantly improves temperature control accuracy, ensures stable printing press operation, and reduces the impact of temperature fluctuations on printing quality. By introducing trend prediction and decision tree logic analysis, the system can dynamically adjust the heater power and cooler status according to the operating environment. It can quickly analyze data and formulate control schemes, thereby significantly improving the system response speed, ensuring the real-time and efficient nature of temperature control, and avoiding energy waste or temperature control failure due to response lag. Attached Figure Description
[0018] Figure 1 This is a framework diagram of the present invention; Figure 2 This is a flowchart of the process of the present invention. Detailed Implementation
[0019] 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.
[0020] like Figure 1 As shown: A printing press intelligent heat preservation system includes a detection unit, a preprocessing unit, an adaptive trend prediction unit, an adaptive control unit, and a control unit.
[0021] The acquisition end of the detection unit is connected to the input end of the prediction unit via a data bus. The output end of the preprocessing unit is connected to the adaptive trend prediction unit via a data bus. The output end of the adaptive trend prediction unit is connected to the adaptive control unit via a data bus. The adaptive control unit is connected to the control unit via a data bus. The detection unit collects the temperature parameters and environmental parameters of the printing press in real time through a sensor network.
[0022] Specifically, the detection unit includes a thermocouple sensor and a temperature and humidity sensor. The thermocouple sensor is arranged on the heating assembly and the printing cylinder to monitor the internal temperature of the heater and the surface temperature of the cylinder, respectively. The ambient temperature and humidity sensor is arranged in key areas around the printing press to collect ambient temperature and relative humidity in real time, thereby capturing the influence of the external environment on the thermal balance of the printing press.
[0023] The preprocessing unit includes a data filtering module and a feature extraction module. The data filtering module performs denoising and smoothing on the acquired raw data to filter out noise signals caused by electromagnetic interference or sensor errors. The feature extraction module uses a preset algorithm to extract key temperature feature parameters from the denoised data, including the temperature gradient of the roller surface and the rate of change of ambient temperature.
[0024] The adaptive trend prediction unit, based on the temperature features extracted by the preprocessing unit and combined with a regression model, dynamically predicts the temperature change trend of the printing press over a future period and generates a thermal balance index that reflects the current state of the system, providing a reference for subsequent control logic.
[0025] The adaptive control unit is used to determine whether the temperature of the printing press deviates from the target range based on the effective temperature characteristics and thermal balance index, and to generate an adjustment command when it deviates from the preset range. Specifically, the adaptive control unit includes a decision tree model. The root node of the decision tree model uses real-time effective temperature characteristics and thermal balance state estimates as the initial judgment basis for the control logic, and further combines historical temperature control data to optimize the node branches. Branch nodes judge whether the temperature deviates from the target range layer by layer according to the temperature control logic rules; each branch path generates specific adjustment instructions based on empirical rules and statistical learning, including heater power adjustment values or cooling device operating mode switching parameters, etc.
[0026] The control unit includes an actuator control module. After receiving the adjustment command, the actuator control module adjusts the heater power output or the operating status of the cooling device in real time to ensure that the printing press temperature is stable within the target range.
[0027] like Figure 2 As shown, the specific technical solution for the operation of an intelligent heat preservation system for a printing press is as follows: A control method for an intelligent heat preservation system for a printing press includes the following steps: S1: The detection unit monitors the temperature of the heating component and the printing cylinder through a thermocouple sensor, and at the same time collects the temperature and humidity parameters of the environment around the printing press through a temperature and humidity sensor to form raw data; S2: The preprocessing unit preprocesses the raw data to generate usable temperature feature values, and stores the processed temperature feature values in the database. S3: The trend prediction unit receives the preprocessed temperature feature values, uses a regression model to predict the temperature change trend of the printing press over a future period, and generates a thermal balance state index, which is simultaneously stored in the database.
[0028] Specifically, in S3, the trend prediction unit is equipped with a regression model. The trend prediction unit receives preprocessed temperature feature values and uses the regression model to predict the temperature change trend of the printing press over a future period of time, generating a thermal balance state index.
[0029] The detection unit collects temperature and humidity parameters of the environment surrounding the printing press via a temperature and humidity sensor, forming raw data D:
[0030] in, This refers to the sampling time point; For time The collected temperature values; For time The collected humidity values; The preprocessing unit preprocesses the original data D to generate a usable input feature vector F:
[0031] in: To use the feature fusion function Extracted comprehensive feature values; The preprocessing unit stores the input feature vector F in the value database; The trend prediction unit receives preprocessed input feature values F, and uses the following regression model to predict the predicted temperature value at time point t:
[0032] in, The predicted temperature for time t; Input feature values; , , , These are the parameters to be estimated for the model; The regression model utilizes the input features F from historical data and minimizes the error function. To determine the parameters:
[0033] The trend prediction unit uses a regression model to predict the temperature over a period of time t, thus obtaining a set of predicted temperature values for that time period. , These are discrete time points in the future.
[0034] The trend prediction unit calculates the average of these predicted temperature values as an indicator of thermal equilibrium. :
[0035] The trend prediction unit will use the thermal balance state index Save to the database.
[0036] S4: The decision tree model in the adaptive control unit combines real-time temperature feature values and thermal balance state indicators to determine whether the current temperature state deviates from the target range according to the set rules. Specifically, at the root node of the decision tree model, the decision tree model determines whether the temperature of the printing press will deviate from the target range over a period of time based on the input data, and selects the subsequent path based on the judgment result. If the temperature deviates from the target range, the decision tree model further splits into multiple sub-nodes, evaluates the system state and operating parameters layer by layer, and determines the optimal control scheme based on the threshold conditions of each node. As the decision tree model refines the judgment layer by layer along the branch path, it generates specific control instructions to adjust the power of the heater or the operating status of the cooling device. If the temperature is determined to be within the target range, the decision tree model will maintain the current system operating state and will not perform any additional adjustments.
[0037] If the decision tree model determines that adjustment is needed, proceed to S5 to generate the corresponding adjustment instruction; If the decision tree model determines that no adjustment is needed, proceed to S7 and maintain the current operating state; S5: The adaptive control unit generates specific instructions according to the control logic and sends them to the control unit until the environment stabilizes within the target range; S6: The control unit adjusts the power output of the heater and the operating status of the cooler in real time according to the received adjustment command to ensure that the printing press temperature reaches and is maintained within the target range.
[0038] S7: The control unit maintains the system in its current state.
[0039] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.
[0040] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.
Claims
1. An intelligent heat preservation system for a printing press, characterized in that: It includes a detection unit, a preprocessing unit, an adaptive trend prediction unit, an adaptive control unit, and a control unit; The acquisition end of the detection unit is connected to the input end of the prediction unit via a data bus; the output end of the preprocessing unit is connected to the adaptive trend prediction unit via a data bus; the output end of the adaptive trend prediction unit is connected to the adaptive control unit via a data bus; and the adaptive control unit is connected to the control unit via a data bus. The detection unit collects the temperature and environmental parameters of the printing press in real time through a sensor network. The preprocessing unit is used to preprocess the data collected by the detection unit to obtain effective temperature characteristics. The adaptive trend prediction unit is used to predict the temperature change trend of the printing press over a period of time based on the temperature features extracted by the preprocessing unit, and to generate a heat balance index. The adaptive control unit is used to determine whether the temperature of the printing press deviates from the target range based on the effective temperature characteristics and thermal balance index, and to generate an adjustment command when it deviates from the preset range. The control unit is used to receive the adjustment command and dynamically adjust the heater power and the operating status of the cooling device to keep the temperature stable within the set range.
2. The intelligent heat preservation system for a printing press according to claim 1, characterized in that: The detection unit includes a thermocouple sensor and a temperature and humidity sensor; The thermocouple sensors are arranged on the heating assembly and the printing roller to monitor the internal temperature of the heater and the surface temperature of the roller. The ambient temperature and humidity sensor is used to collect ambient temperature and relative humidity in real time.
3. The intelligent heat preservation system for a printing press according to claim 2, characterized in that: The adaptive control unit includes a decision tree model. Based on real-time temperature characteristics and thermal balance state estimates, the adaptive control unit constructs an adaptive control decision tree model. The root node of the decision tree model takes the real-time effective temperature characteristics and thermal balance state estimates as inputs, serving as the initial judgment basis for the control logic. The branch nodes of the decision tree model, based on temperature control logic rules, judge whether the temperature deviates from the target range layer by layer, and generate specific adjustment instructions based on the node judgment results to guide the control unit to adjust the operating state of the printing press.
4. The control method of the intelligent heat preservation system for a printing press as described in claim 3, characterized in that: Includes the following steps: S1: The detection unit monitors the temperature of the heating component and the printing cylinder through a thermocouple sensor, and at the same time collects the temperature and humidity parameters of the environment around the printing press through a temperature and humidity sensor to form raw data; S2: The preprocessing unit preprocesses the raw data to generate usable input feature values, and stores the processed input feature values in the database. S3: The trend prediction unit receives the preprocessed input feature values, uses a regression model to predict the temperature change trend of the printing press over a future period, and generates a thermal balance state index, which is simultaneously stored in the database. S4: The decision tree model within the adaptive control unit combines real-time temperature feature values and thermal balance state indicators to determine whether the current temperature state deviates from the target range according to set rules. If the decision tree model determines that adjustment is needed, proceed to S5 to generate the corresponding adjustment instruction; If the decision tree model determines that no adjustment is needed, proceed to S7 and maintain the current operating state; S5: The adaptive control unit generates specific instructions according to the control logic and sends them to the control unit until the environment stabilizes within the target range; S6: The control unit adjusts the power output of the heater and the operating status of the cooler in real time according to the received adjustment command to ensure that the printing press temperature reaches and is maintained within the target range; S7: The control unit maintains the system in its current state.
5. The control method for an intelligent heat preservation system for a printing press according to claim 4, characterized in that: In S3, the trend prediction unit is equipped with a regression model. The trend prediction unit receives preprocessed temperature feature values and uses the regression model to predict the temperature change trend of the printing press over a future period of time, generating a thermal balance state index.
6. The control method for an intelligent heat preservation system for a printing press according to claim 5, characterized in that: At the root node of the decision tree model, the decision tree model determines whether the temperature of the current printing press will deviate from the target range over a period of time based on the input data, and selects the subsequent path based on the determination result; If the temperature deviates from the target range, the decision tree model further splits into multiple sub-nodes, evaluates the system state and operating parameters layer by layer, and determines the optimal control scheme based on the threshold conditions of each node. As the decision tree model refines the judgment layer by layer along the branch path, it generates specific control instructions to adjust the power of the heater or the operating status of the cooling device. If the temperature is determined to be within the target range, the decision tree model will maintain the current system operating state and will not perform any additional adjustments.
7. The control method for an intelligent heat preservation system for a printing press according to claim 6, characterized in that: The detection unit collects temperature and humidity parameters of the environment surrounding the printing press via temperature and humidity sensors, forming raw data D: in, This refers to the sampling time point; For time The collected temperature values; For time The collected humidity values; The preprocessing unit preprocesses the original data D to generate a usable input feature vector F: in: To use the feature fusion function Extracted comprehensive feature values; The preprocessing unit stores the input feature vector F in the value database; The trend prediction unit receives preprocessed input feature values F, and uses the following regression model to predict the predicted temperature value at time point t: in, The predicted temperature for time t; Input feature values; , , , These are the parameters to be estimated for the model; The regression model utilizes the input features F from historical data and minimizes the error function. To determine the parameters: The trend prediction unit uses a regression model to predict the temperature over a period of time t, thus obtaining a set of predicted temperature values for that time period. , These are discrete time points in the future.
8. The trend prediction unit calculates the average of these predicted temperature values as an indicator of thermal equilibrium state. : The trend prediction unit will use the thermal balance state index Save to the database.