Heating control system and method of injection molding machine

Abstract

The invention relates to the technical field of injection molding machines, and discloses a heating control system and method of an injection molding machine, and the heating control system of the injection molding machine realizes efficient, stable and safe operation of a temperature control process through accurate temperature control, intelligent self-learning, energy efficiency optimization, remote control and an efficient fault processing mechanism. The production efficiency, the product quality and the energy efficiency are obviously improved; through multiple advantages of an accurate temperature control technology, intelligent self-learning, energy efficiency optimization, safety guarantee, remote management and the like, an efficient, stable and intelligent production control scheme is provided, not only can the production quality and efficiency of the injection molding machine be improved, but also the energy consumption and the maintenance cost can be reduced, and remarkable economic benefits are brought to enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of injection molding machines, and specifically to a heating control system and method for an injection molding machine. Background Art

[0002] An injection molding machine is a machine device commonly used for plastic molding, and is widely used in the production process of plastic products. Its basic principle is to heat plastic particles to a molten state and inject the molten plastic into a closed mold by injection. After cooling, the required plastic products are obtained. The application of injection molding machines covers almost all fields of plastic products, including automotive parts, household appliance casings, medical devices, daily consumer goods, etc.

[0003] The heating control system of an injection molding machine is one of the key components to ensure the molten state of plastic and the molding quality. Its function is to heat the plastic raw materials to a temperature suitable for injection molding and maintain a constant temperature during the injection molding process, thereby ensuring the accuracy and consistency of the products. The application of the heating control system in injection molding machines is extensive and the technology is constantly developing.

[0004] Although the heating control system has been widely applied in injection molding machines, there are still some challenges in actual production. Due to the uneven heat conduction of the heating elements, the temperature distribution of the barrel or the mold may be uneven, which in turn affects the fluidity of the plastic and the molding quality. Summary of the Invention

[0005] The present invention provides a heating control system and method for an injection molding machine to solve the technical problems mentioned in the above background art.

[0006] The present invention provides the following technical solutions:

[0007] A heating control system for an injection molding machine, the system comprising:

[0008] A heating unit, the heating unit is connected to a central controller through a power module, and adjusts the heating power of the electric heater in real time to ensure that the temperatures of the mold and the molten plastic during the plastic injection molding process are maintained within an optimal range;

[0009] A temperature acquisition module, the temperature acquisition module includes a plurality of temperature sensors, and each temperature sensor is arranged at different heating areas or mold temperature control points of the injection molding machine, and is responsible for acquiring the temperature data of each area in real time;

[0010] A central controller, the central controller is the core part of the heating control system and is responsible for receiving the real-time temperature data from the temperature acquisition module;

[0011] Intelligent self-learning module. By learning historical temperature changes, load changes, and environmental changes, the intelligent self-learning module can dynamically adjust the heating strategy during the actual production process, improving temperature control accuracy and system response speed;

[0012] Energy consumption management module. The energy consumption management module monitors the power consumption of each heating area and intelligently adjusts the heating power according to the real-time temperature demand, avoiding energy consumption waste caused by overheating;

[0013] Communication module. The communication module realizes data transmission and interaction between the heating control system and external devices;

[0014] Human-machine interface. The human-machine interface provides an interface between the user and the heating control system;

[0015] Safety protection module. The safety protection module can monitor the working state of the heating system in real time and immediately send out an alarm signal and activate the protection mechanism when an abnormality occurs.

[0016] Preferably, the heating unit includes multiple heating zones, each heating zone is equipped with an independent electric heater, and independent temperature control is achieved between the heating zones.

[0017] Preferably, the central controller uses fuzzy control algorithm and PID control algorithm to dynamically adjust the temperature of each heating zone.

[0018] Preferably, the intelligent self-learning module optimizes the heating strategy based on historical temperature data, environmental temperature, and material parameters, and can dynamically update the strategy library according to the actual operation results.

[0019] Preferably, the energy consumption management module includes a current sensor and a power calculation unit for calculating the energy consumption of each heating zone and optimizing the load balance.

[0020] Preferably, the communication module supports Modbus, Ethernet, and Wi-Fi protocols, and can realize data intercommunication with the upper computer, MES system, and remote terminal.

[0021] Preferably, the human-machine interface is a touch display screen or a mobile terminal application, and has functions such as real-time temperature display, parameter setting, alarm viewing, and energy consumption report.

[0022] Preferably, the safety protection module includes functions such as over-temperature power-off protection, heater fault detection, temperature abnormality alarm, disconnection detection, and short-circuit protection.

[0023] Preferably, the system further includes a cloud management platform for centralized monitoring, statistics, and maintenance management of the heating data of multiple injection molding machines.

[0024] Heating control system and method for injection molding machine, the method is as follows:

[0025] S1: Start the heating control system of the injection molding machine. The system is connected to the central controller through the power supply module to ensure that the heating unit, temperature acquisition module, intelligent self-learning module, energy consumption management module, communication module, and safety protection module can work properly;

[0026] The system establishes a connection with external devices (such as the upper computer, MES system, and cloud management platform) through the communication module for data synchronization and status monitoring;

[0027] S2: Multiple temperature sensors of the temperature acquisition module start to work, and the temperature data of each heating area or mold temperature control point is collected in real time; the temperature data is transmitted to the central controller through the sensor and is preliminarily processed;

[0028] S3: Based on the received real-time temperature data, the central controller combines the preset heating curve and temperature control strategy, and adjusts the temperature of each heating zone through the fuzzy control algorithm and PID control algorithm; in the actual control process, the central controller adjusts the heating power of the electric heater according to the data feedback by the temperature sensor to ensure that the temperature of each heating zone is always maintained within the target temperature range;

[0029] S4: The intelligent self-learning module analyzes information such as historical temperature data, ambient temperature, and material parameters, and automatically optimizes the heating strategy according to the performance of the heating unit during the actual production process; after each production cycle ends, the intelligent self-learning module dynamically updates the heating strategy library based on the operation data to improve the temperature control accuracy and response speed of subsequent production;

[0030] S5: The energy consumption management module monitors the power consumption of each heating zone in real time through the current sensor; the load of each heating zone is balanced and optimized through the power calculation unit to ensure that the heating power meets the temperature control requirements while avoiding unnecessary energy waste and improving the energy efficiency of the system;

[0031] S6: Through the communication module, the system can transmit real-time temperature data, energy consumption information, etc. to the upper computer, MES system, or cloud management platform to achieve remote monitoring and management; users interact with the heating control system through the mobile terminal application or touch display screen to adjust temperature parameters, view alarm information, generate energy consumption reports, etc.;

[0032] S7: The safety protection module monitors the working state of the heating system in real time and conducts a comprehensive fault detection on the heating unit; when problems such as overheating, abnormal temperature, heater failure, disconnection, and short circuit occur, the safety protection module issues an alarm signal in time and starts the protection mechanism, such as power-off protection or power adjustment, to ensure the safe and stable operation of the system;

[0033] S8: According to the changes in the real-time production environment (such as load changes, environmental temperature fluctuations, etc.), the system will dynamically adjust the heating strategy to ensure that the temperature of each heating zone always remains within the most suitable range, guaranteeing the quality stability during the injection molding process; the intelligent self-learning module continuously accumulates data during each production process and optimizes the heating control strategy to further improve the performance of the system;

[0034] S9: The cloud management platform is connected to the heating control system of the injection molding machine to conduct centralized monitoring, statistics, and maintenance management of the heating data of multiple injection molding machines; users can view the working status, temperature curves, energy consumption data, etc. of all devices through the cloud platform for centralized management, remote fault diagnosis, and maintenance scheduling

[0035] The present invention has the following beneficial effects:

[0036] 1. Precise temperature control: The temperature of the mold and the molten plastic is precisely adjusted through the heating unit, avoiding uneven heating or overheating, ensuring the quality of plastic molding, and improving production efficiency and product consistency.

[0037] 2. Real-time monitoring and feedback: The temperature acquisition module monitors the temperature of each heating zone in real time through sensors distributed in different areas, ensuring that the system can quickly respond to temperature changes and avoiding local overheating or overcooling.

[0038] 3. Stable and efficient heating control: The central controller combines fuzzy control and PID algorithms to dynamically adjust the temperature of each heating zone, enhancing the adaptability and temperature control accuracy of the system, and ensuring the stability and efficiency of the temperature control process.

[0039] 4. Self-learning and optimization function: The intelligent self-learning module optimizes the heating strategy based on historical data and real-time feedback, gradually improving the temperature control accuracy and system response speed, and enhancing production efficiency and energy-saving effects.

[0040] 5. Energy efficiency improvement: The energy consumption management module monitors the power consumption of each heating zone, dynamically adjusts the power to avoid energy waste, and improves the overall energy efficiency and reduces the operating cost through load balancing optimization.

[0041] 6. Remote monitoring and control: The communication module realizes real-time data transmission and control through connection with the host computer, MES system, and remote terminal, supports remote monitoring and fault diagnosis, reduces the dependence on on-site operations, and improves management efficiency.

[0042] 7. Operational convenience: The human-machine interface provides an intuitive temperature control and alarm response interface, enhancing the convenience of operators and the system response efficiency, and reducing operation errors.

[0043] 8. System security guarantee: The security protection module monitors the system status in real time, processes abnormal situations in a timely manner, prevents equipment damage or production stagnation, and ensures production safety and continuity.

[0044] Overall, through precise temperature control, intelligent self-learning, energy efficiency optimization, remote control, and an efficient fault handling mechanism, the system realizes the efficient, stable, and safe operation of the temperature control process, significantly improving production efficiency, product quality, and energy efficiency. Brief Description of the Drawings

[0045] Figure 1 It is a schematic diagram of the system of the present invention;

[0046] Figure 2 It is a schematic flowchart of the data processing module of the present invention. Detailed Embodiments

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0051] Embodiment

[0052] Please refer to Figure 1 , the heating control system of an injection molding machine, the system includes:

[0053] A heating unit, which is connected to the central controller through a power module and adjusts the heating power of the electric heater in real time to ensure that the temperatures of the mold and the molten plastic during the plastic injection molding process are maintained within the optimal range; the heating unit is the core component of the heating control system of the injection molding machine. The goal of the heating unit is to ensure that the temperatures of the mold and the molten plastic are always maintained within the optimal working range. The heating unit can precisely control the heating state of the mold, avoid plastic molding quality problems caused by uneven heating or overheating, ensure production efficiency and product consistency, and the temperature stability directly affects the molding accuracy, surface quality, and mechanical properties of the injection molded parts.

[0054] Temperature acquisition module. The temperature acquisition module includes multiple temperature sensors, each of which is arranged at different heating areas of the injection molding machine or mold temperature control points, and is responsible for collecting the temperature data of each area in real time. The temperature sensors are responsible for collecting the temperature data of these areas in real time and feeding them back to the central controller. The real-time data acquisition of the temperature sensors can effectively monitor the temperature conditions of each heating zone, ensure that the system can respond quickly and adjust the temperature, thereby avoiding excessive or too low local temperature and ensuring the precise control of the injection molding process.

[0055] Central controller. The central controller is the core part of the heating control system, responsible for receiving the real-time temperature data from the temperature acquisition module, making corresponding temperature control decisions based on these data, and sending adjustment commands to the heating unit according to the preset heating strategy. The precise calculation and control ability of the central controller can accurately adjust the heating power according to the actual temperature change, ensure the stability and accuracy of the heating process. Its core role is to coordinate the work of all heating areas, avoid overheating or uneven heating, and improve the injection molding quality and production efficiency.

[0056] Intelligent self-learning module. By learning the historical temperature changes, load changes and environmental changes, the intelligent self-learning module can dynamically adjust the heating strategy during the actual production process, improve the temperature control accuracy and system response speed. According to the data feedback in the actual production, adjusting the heating strategy in each production cycle, the intelligent self-learning module can further improve the temperature control accuracy and system response speed through intelligent adjustment. With the accumulation of the usage process, the temperature control effect of the system will gradually improve, realizing a more efficient and energy-saving heating process.

[0057] Energy consumption management module. The energy consumption management module monitors the power consumption of each heating area and intelligently adjusts the heating power according to the real-time temperature demand, avoiding energy consumption waste caused by overheating. The energy consumption management module effectively avoids the energy consumption waste caused by overheating, improves the energy efficiency ratio. Through reasonable power distribution and dynamic adjustment, it helps to reduce the operating cost and reduce the energy consumption without affecting the heating accuracy, meeting the energy-saving requirements of modern industry.

[0058] Communication module. The communication module realizes the data transmission and interaction between the heating control system and external devices (such as the upper computer, MES system, cloud platform, etc.). The communication module ensures that the system can achieve real-time data exchange with external devices, provides basic support for remote monitoring, data storage, production scheduling, etc., enabling users to obtain production data in a timely manner, optimize the production process, and improve the management efficiency.

[0059] Human - machine interaction interface, which provides an interface between the user and the heating control system; the human - machine interaction interface enables the operator to intuitively view the system operation status and temperature curve, quickly adjust the temperature setting or respond to alarm information, improving the operation convenience and response efficiency. A good interaction interface can enhance the user experience and reduce operation errors.

[0060] Safety protection module, which can monitor the working status of the heating system in real - time and immediately send out an alarm signal and activate the protection mechanism (such as power - off, heating power adjustment, etc.) when an abnormality occurs (such as over - temperature, heater failure, temperature anomaly, wire breakage, short - circuit, etc.); the safety protection module effectively avoids equipment damage or production stagnation caused by system failures or abnormalities, ensures the safe and stable operation of the production process, prolongs the equipment service life through real - time protection and fault handling, and guarantees the continuity of the production process.

[0061] Specifically, the heating unit includes multiple heating zones, each heating zone is equipped with an independent electric heater, and independent temperature control is achieved between the heating zones; each heating zone can be managed through a separate temperature control system, equipped with a temperature sensor to monitor the temperature change in this area in real - time, and the power output of the electric heater is precisely adjusted through the central controller. The independent temperature control system enables the temperature of each area to be independently adjusted according to different production requirements, avoiding temperature non - uniformity or over - heating phenomena; the design of multiple heating zones in the heating unit provides higher flexibility, precision, and energy efficiency, enabling the injection molding machine to meet more complex production requirements and ensuring the stability and high - quality output of the production process.

[0062] Specifically, the central controller uses fuzzy control algorithm and PID control algorithm to perform dynamic temperature regulation on each heating zone; during the injection molding process, the temperature change is often affected by various factors such as the external environment, equipment aging, and raw material differences. Fuzzy control can effectively handle these uncertain factors. By setting fuzzy rules (such as "if the temperature is too high, then reduce the heating power"), the system can adaptively adjust according to the actual situation; fuzzy control can dynamically adjust the heating power based on information such as the real - time temperature deviation (e.g., the difference between the target temperature and the actual temperature) and the temperature change rate. Through the fuzzy control algorithm, the system can make a more intelligent and rapid response, avoiding excessive temperature fluctuations; fuzzy control has a high fault tolerance for temperature prediction and regulation, especially when sudden changes occur during the production process, it can effectively prevent system crashes or large - scale temperature fluctuations.

[0063] The PID (Proportional-Integral-Derivative) control algorithm is a classic feedback control algorithm widely used in various temperature control systems. The proportional control adjusts the heating power according to the current temperature deviation. The larger the deviation, the stronger the output signal, thereby increasing the heating power to shorten the time for the temperature to reach the target. The integral control mainly deals with the long-existing temperature deviation to prevent the temperature system from deviating from the target temperature for a long time. For example, the system may have a slight but continuous deviation due to equipment aging or external environmental changes. The integral term can accumulate these deviations and make corresponding compensations. The derivative control predicts the temperature change trend and reacts in advance to avoid overshoot caused by too rapid temperature changes, helping the system to cope with the dynamic situation of temperature changes and making the adjustment process smoother.

[0064] By combining the fuzzy control algorithm and the PID control algorithm, the central controller can achieve more accurate, stable, and efficient temperature regulation in the dynamically changing injection molding production process. This combined control strategy can not only enhance the system's adaptability to external environmental changes but also ensure the temperature control accuracy and energy efficiency during the injection molding process, thereby improving production efficiency and product quality.

[0065] Specifically, the intelligent self-learning module optimizes the heating strategy based on historical temperature data, ambient temperature, and material parameters, and can dynamically update the strategy library according to the actual operation results. The module continuously collects real-time data through temperature sensors, environmental monitoring devices, load sensors, etc. These data can reflect the performance of the system in different working states in real time. When a certain heating strategy performs well in actual operation, the system will add this strategy to the strategy library through the feedback mechanism. Conversely, if a certain strategy fails to achieve the ideal effect in the actual production process, the system will adjust or directly replace the strategy.

[0066] The dynamically updated strategy library enables the system to adjust the heating strategy according to the actual production conditions. For example, when the system detects that the mold temperature is continuously too high or too low for a long time, the intelligent self-learning module can automatically adjust the heating power to avoid energy waste or material damage caused by overheating. In addition, the module will also adaptively adjust the PID control parameters according to the actual operating conditions to further optimize the system performance.

[0067] By learning historical temperature data, ambient temperature, and material parameters, the intelligent self-learning module can continuously optimize the heating strategy and dynamically update the strategy library. This adaptive and intelligent temperature control mechanism not only improves the temperature control accuracy and efficiency of the injection molding machine but also enables the system to operate stably under complex and changing production conditions, thereby improving the quality, efficiency, and energy-saving effect of the production process.

[0068] Specifically, the energy consumption management module includes a current sensor and a power calculation unit, which are used to calculate the energy consumption of each heating zone and optimize the load balancing. The current sensor is arranged at the power input end of each heating zone of the heating unit to collect the current data of each heating zone in real time. Since the current is proportional to the heating power, by monitoring the change of the current, the energy consumption information of the heating zone can be obtained. The current sensor can help monitor the load condition of the heating zone. When the load of a certain heating zone increases, the increase in current directly reflects the rise in power demand. The current sensor can promptly sense these changes and transmit the data to the power calculation unit to support the adjustment of load balancing.

[0069] According to the current data and the voltage parameters of the heating zone, the power calculation unit uses the following formula for power calculation:

[0070] P = U × I

[0071] Where P represents power, U is voltage, and I is current. The power calculation unit calculates the real-time power consumption of each heating zone through the real-time monitoring of current and voltage. After calculating the power of each heating zone, the power calculation unit will evaluate whether the energy efficiency of each heating zone meets the set standards according to the temperature control requirements of the system. For example, if the power consumption of a certain heating zone exceeds the expectation, it may indicate problems such as overheating and heat waste, which need to be adjusted. The power calculation unit feeds back the calculation results to the central controller, and together with the data of the temperature acquisition module, provides a basis for load balancing and the optimization of heating strategies, which can ensure the reasonable use of energy and avoid energy waste while maintaining the temperature control accuracy.

[0072] According to the real-time power data, the energy consumption management module will evaluate the actual demands of each heating zone and dynamically adjust the heating power. The energy consumption management module will cooperate to optimize the power of all heating zones, avoid excessive work in a single heating zone, which may lead to low load in other areas and cause energy waste. By evenly distributing the load among each heating zone, the system can maximize the overall efficiency and ensure that the system completes the temperature control task under low power consumption.

[0073] Through the close cooperation of the current sensor and the power calculation unit, the energy consumption management module realizes the precise energy consumption monitoring and dynamic optimization adjustment of the heating unit. Through load balancing optimization, the system can achieve efficient energy consumption management of each heating zone, reduce energy waste, and improve the overall energy efficiency of the production process. This not only helps to improve production efficiency, but also can reduce energy consumption, reduce equipment failures and extend the equipment life, thus bringing significant economic benefits to the injection molding production process.

[0074] Specifically, the communication module supports Modbus (a communication protocol widely used in the industrial automation field), Ethernet (a standard protocol commonly used in modern industrial control systems), and Wi-Fi (which provides wireless communication capabilities for the communication module), enabling data interconnection with the host computer, MES system, and remote terminals.

[0075] The communication module supports real-time data transmission, enabling the host computer, MES system, and remote terminals to obtain real-time information such as the temperature, energy consumption, and operating status of the system. Operators and managers can access the latest data at any time to make timely adjustments and decisions, ensuring that the system operates at its best.

[0076] The communication module enables the remote terminal to monitor and control the system in real time. Operators can remotely adjust heating parameters, view alarm information, diagnose faults, etc., reducing the dependence on on-site operators and enhancing operation flexibility. Especially when an abnormality occurs during the production process, it can quickly diagnose and handle faults.

[0077] By connecting to the MES system, the communication module enables the data of the heating control system to be centrally stored and statistically analyzed. These data can be used to generate reports, conduct production trend analysis, optimize production plans and resource allocation, further improving production efficiency and energy utilization rate.

[0078] The communication module supports multiple protocols, ensuring that the injection molding machine heating control system can be easily integrated into a wider industrial automation system. For example, it can achieve seamless connection with other devices in the workshop, equipment management systems, energy management systems, etc., promoting the intelligence and automation of the entire production process. By supporting Ethernet and Wi-Fi protocols, the system can be easily extended to different production environments and requirements.

[0079] The communication module is an important part of the injection molding machine heating control system. By supporting Modbus, Ethernet, and Wi-Fi protocols, it realizes efficient data interconnection with the host computer, MES system, and remote terminals. This not only enables the heating control system to obtain the status information of external devices in real time but also supports remote monitoring, control, diagnosis, and data analysis, improving operation flexibility, production efficiency, and system integration, and ultimately enhancing the intelligence and automation level of the entire production process.

[0080] Specifically, the human-machine interaction interface is a touch display screen or a mobile terminal application, with functions of real-time temperature display, parameter setting, alarm viewing, and energy consumption report; the design of the human-machine interaction interface makes the injection molding machine heating control system more intelligent and user-friendly. Whether through the touch display screen or the mobile terminal application, users can conveniently perform functions such as real-time temperature display, parameter setting, alarm viewing, and energy consumption report. By providing an intuitive and convenient operation interface, the human-machine interaction interface significantly improves the operability, monitoring ability, and energy efficiency management of the heating control system, helping operators manage and control the heating process of the injection molding machine more efficiently.

[0081] Specifically, the safety protection module includes over-temperature power-off protection (used to prevent the temperature of the heating unit from being too high, avoiding safety hazards such as equipment damage or fire caused by overheating), heater fault detection (real-time monitoring of the working state of the heater to ensure the normal operation of the heater and prevent temperature control failure or accidents during the production process caused by faults), temperature anomaly alarm (timely detection of temperature fluctuations or abnormal conditions in the heating system to ensure that the temperature during the production process is always maintained within the ideal range), wire break detection (able to monitor whether there is a wire break in the lines of sensors, heaters, and other components in the heating system to ensure the normal operation of the system), and short-circuit protection function (preventing short-circuits in the electrical equipment in the system, which may lead to equipment damage, fire, or electrical accidents).

[0082] Through functions such as over-temperature power-off protection, heater fault detection, temperature anomaly alarm, wire break detection, and short-circuit protection, the safety protection module ensures the safe operation of the injection molding machine heating control system. Each function plays an important role in different working links, helping to prevent problems such as equipment failure, temperature control failure, overheating, or electrical accidents, thus ensuring the safety of operators and the normal operation of the equipment. At the same time, these protection functions provide multi-level safety protection for the system, making the entire production process more stable and reliable.

[0083] Specifically, the system further includes a cloud management platform for centralized monitoring, statistics, and maintenance management of the heating data of multiple injection molding machines; the cloud management platform not only provides real-time monitoring of a single injection molding machine but also enables centralized management of multiple injection molding machines to ensure the efficiency, stability, and intelligence of the entire production process.

[0084] The introduction of the cloud management platform enables the injection molding machine heating control system to achieve intelligent, remote, and centralized management, greatly improving production efficiency and the convenience of equipment maintenance. Through data statistics, analysis, and intelligent decision-making, the platform not only helps optimize the production process but also improves the reliability and energy efficiency of the equipment. Functions such as remote monitoring, alarm, and permission management ensure the safety and controllability of the production process, making the entire production process more transparent and efficient.

[0085] Heating control system and method for an injection molding machine, the method is as follows:

[0086] S1: Start the heating control system of the injection molding machine. The system is connected to the central controller through the power module to ensure that the heating unit, temperature acquisition module, intelligent self-learning module, energy consumption management module, communication module, and safety protection module can work properly; the system establishes a connection with external devices (such as a host computer, MES system, and cloud management platform) through the communication module for data synchronization and status monitoring.

[0087] S2: Multiple temperature sensors of the temperature acquisition module start to work, and the temperature data of each heating area or mold temperature control point is collected in real time; the temperature data is transmitted to the central controller through the sensor and is preliminarily processed.

[0088] S3: Based on the received real-time temperature data, the central controller combines the preset heating curve and temperature control strategy, and adjusts the temperature of each heating zone through the fuzzy control algorithm and PID control algorithm; in the actual control process, the central controller adjusts the heating power of the electric heater according to the data feedback by the temperature sensor to ensure that the temperature of each heating zone is always maintained within the target temperature range.

[0089] S4: The intelligent self-learning module analyzes information such as historical temperature data, ambient temperature, and material parameters, and automatically optimizes the heating strategy according to the performance of the heating unit during the actual production process; after each production cycle ends, the intelligent self-learning module dynamically updates the heating strategy library based on the operation data to improve the temperature control accuracy and response speed of subsequent production.

[0090] S5: The energy consumption management module monitors the power consumption of each heating zone in real time through the current sensor; the load of each heating zone is balanced and optimized through the power calculation unit to ensure that the heating power meets the temperature control requirements while avoiding unnecessary energy waste and improving the energy efficiency of the system.

[0091] S6: Through the communication module, the system can transmit real-time temperature data, energy consumption information, etc. to the host computer, MES system, or cloud management platform to achieve remote monitoring and management; users interact with the heating control system through the mobile terminal application or touch display screen to adjust temperature parameters, view alarm information, generate energy consumption reports, etc.

[0092] S7: The safety protection module monitors the working state of the heating system in real time and conducts a comprehensive fault detection on the heating unit; when problems such as over-temperature, abnormal temperature, heater failure, disconnection, short circuit, etc. occur, the safety protection module issues an alarm signal in time and starts the protection mechanism, such as power-off protection or power adjustment, to ensure the safe and stable operation of the system.

[0093] S8: According to the changes in the real-time production environment (such as load changes, environmental temperature fluctuations, etc.), the system will dynamically adjust the heating strategy to ensure that the temperature of each heating zone always remains within the most suitable range, guaranteeing the quality stability during the injection molding process; the intelligent self-learning module continuously accumulates data during each production process and optimizes the heating control strategy to further improve the system performance.

[0094] S9: The cloud management platform is connected to the heating control system of the injection molding machine to conduct centralized monitoring, statistics, and maintenance management of the heating data of multiple injection molding machines; users can view the working status, temperature curves, energy consumption data, etc. of all devices through the cloud platform for centralized management, remote fault diagnosis, and maintenance scheduling.

[0095] The injection molding machine heating control system and method provide an efficient, flexible, and safe solution through the comprehensive application of modern control theory, intelligent learning, and energy management technologies. Its advantages are as follows:

[0096] Precise temperature control performance: By adopting fuzzy control algorithm and PID control algorithm in the central controller, it can accurately adjust the temperature of each heating zone. Whether in the case of rapid temperature changes or when the load of the heating unit changes, the system can ensure that the temperature of each heating zone always remains within the optimal range, thus guaranteeing the quality stability of the plastic injection molding process.

[0097] Intelligent self-learning and dynamic optimization: The introduction of the intelligent self-learning module enables the system to continuously optimize the heating strategy based on historical temperature data, environmental temperature, and material parameters. This dynamic learning and self-optimization ability can improve the temperature control accuracy and response speed. As the production cycle progresses, the system will become more and more accurate, significantly enhancing the efficiency and quality of subsequent production.

[0098] Energy efficiency optimization and load balancing: The use of the energy consumption management module enables the system to maintain good temperature control accuracy while being able to monitor and optimize the energy consumption of each heating zone in real time. Through the power calculation unit for load balancing, it ensures the reasonable distribution of heating power, avoiding energy waste caused by overheating, thereby greatly improving the energy utilization rate of the system and reducing the operating cost.

[0099] Remote monitoring and centralized management: Through the connection of the communication module with the upper computer, MES system, and cloud management platform, the system can achieve remote monitoring and centralized management of the heating data of multiple injection molding machines. Users can view temperature data, energy consumption reports, alarm information, etc. in real time through mobile terminal applications or touch display screens for remote control and optimization adjustment. This not only improves the transparency of the production process but also greatly enhances the efficiency of production management.

[0100] Comprehensive safety protection mechanism: The safety protection module monitors the heating system in real time, enabling it to promptly detect and handle issues such as heater failures, abnormal temperatures, wire breaks, and short circuits. Through means such as power-off protection and power regulation, the system can respond quickly in case of a failure, avoid safety accidents, and ensure the stability and safety of the production process.

[0101] Real-time adjustment and strong adaptability: The system can dynamically adjust the heating strategy according to changes in the real-time production environment (such as load changes, ambient temperature fluctuations, etc.). This high adaptability ensures that the system can cope with different production conditions, maintain the temperature of each heating zone within an appropriate range at all times, and improve the stability and quality of the injection molding process.

[0102] Maintenance management and remote diagnosis: The introduction of the cloud management platform enables users to conveniently conduct centralized management of equipment, remote fault diagnosis, and maintenance scheduling. Through the platform, managers can view the working status, temperature curves, energy consumption data, etc. of each injection molding machine, and perform maintenance and scheduling in a timely manner, thereby reducing downtime and extending the service life of the equipment.

[0103] Data-driven decision support: Through the accumulation and analysis of historical data, the cloud management platform can provide data-driven decision support for managers. The system helps managers optimize production plans, save energy, and improve the operating efficiency of the equipment by statistically analyzing production data, energy consumption data, and equipment health status.

[0104] Enhanced user experience: The design of the human-machine interface makes operation more convenient and intuitive. Users can easily adjust the temperature, set parameters, and view alarm information through the touch screen or mobile device. Through the friendly interface design, operators and managers can quickly respond and adjust various parameters in production, improving the overall production efficiency.

[0105] High scalability and flexibility: The system has high scalability due to its compatibility with a variety of external devices (such as host computers, MES systems, cloud platforms) through standardized communication protocols. As the production scale expands, more devices can be conveniently connected to the system for unified management and monitoring to meet the needs of different-scale production.

[0106] This heating control system and method provide an efficient, stable, and intelligent production control solution through various advantages such as precise temperature control technology, intelligent self-learning, energy efficiency optimization, safety guarantee, and remote management. This method can not only improve the production quality and efficiency of injection molding machines but also reduce energy consumption and maintenance costs, bringing significant economic benefits to enterprises.

[0107] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0108] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. The heating control system of an injection molding machine, characterized in that the system Including: A heating unit, which is connected to a central controller through a power supply module and adjusts the heating power of the electric heater in real time to ensure that the temperatures of the mold and the molten plastic during the plastic injection molding process are maintained within the optimal range; A temperature acquisition module, which includes multiple temperature sensors, and each temperature sensor is arranged at different heating areas or mold temperature control points of the injection molding machine and is responsible for acquiring the temperature data of each area in real time; A central controller, which is the core part of the heating control system and is responsible for receiving the real-time temperature data from the temperature acquisition module; An intelligent self-learning module, which can dynamically adjust the heating strategy during the actual production process by learning the historical temperature changes, load changes, and environmental changes, so as to improve the temperature control accuracy and the system response speed; An energy consumption management module, which monitors the power consumption of each heating area and intelligently adjusts the heating power according to the real-time temperature demand to avoid energy consumption waste caused by overheating; A communication module, which realizes the data transmission and interaction between the heating control system and external devices; A human-machine interaction interface, which provides an interface between the user and the heating control system; A safety protection module, which can monitor the working state of the heating system in real time and immediately send out an alarm signal and start the protection mechanism when an abnormality occurs.

2. The heating control system of the injection molding machine according to claim 1, characterized in that: The heating unit includes multiple heating zones, each heating zone is equipped with an independent electric heater, and independent temperature control is realized between the heating zones.

3. The heating control system of the injection molding machine according to claim 2, wherein: The central controller uses a fuzzy control algorithm and a PID control algorithm to perform dynamic temperature regulation on each heating zone.

4. The heating control system of the injection molding machine according to claim 1, characterized in that: The intelligent self-learning module optimizes the heating strategy based on historical temperature data, ambient temperature, and material parameters, and can dynamically update the strategy library according to the actual operation results.

5. The heating control system of the injection molding machine according to claim 1, characterized in that: The energy consumption management module includes a current sensor and a power calculation unit, which are used to calculate the energy consumption of each heating zone and optimize the load balance.

6. The heating control system of the injection molding machine according to claim 1, wherein: The communication module supports Modbus, Ethernet, and Wi-Fi protocols and can realize data intercommunication with the upper computer, MES system, and remote terminal.

7. The heating control system of the injection molding machine according to claim 1, characterized in that: The human-machine interaction interface is a touch display screen or a mobile terminal application, and has functions such as real-time temperature display, parameter setting, alarm viewing, and energy consumption report.

8. The heating control system of the injection molding machine according to claim 1, wherein: The safety protection module includes functions such as over-temperature power-off protection, heater fault detection, temperature abnormality alarm, wire break detection, and short-circuit protection.

9. The heating control system of the injection molding machine according to any one of claims 1 to 8, characterized in that: The system further includes a cloud management platform, which is used for centralized monitoring, statistics, and maintenance management of the heating data of multiple injection molding machines.

10. The heating control system and method of the injection molding machine according to claims 1 to 9, characterized in that, The method is as follows: S1: Start the heating control system of the injection molding machine. The system is connected to the central controller through the power supply module to ensure that the heating unit, temperature acquisition module, intelligent self-learning module, energy consumption management module, communication module, and safety protection module can work normally; The system establishes a connection with external devices (such as the upper computer, MES system, and cloud management platform) through the communication module for data synchronization and status monitoring; S2: Multiple temperature sensors of the temperature acquisition module start to work, and the temperature data of each heating area or mold temperature control point are collected in real time; the temperature data are transmitted to the central controller through the sensors and are preliminarily processed; S3: Based on the received real-time temperature data, the central controller combines the preset heating curve and temperature control strategy, and adjusts the temperature of each heating zone through the fuzzy control algorithm and the PID control algorithm; in the actual control process, the central controller adjusts the heating power of the electric heater according to the data feedback by the temperature sensor to ensure that the temperature of each heating zone is always maintained within the target temperature range; S4: The intelligent self-learning module analyzes information such as historical temperature data, ambient temperature, and material parameters, and automatically optimizes the heating strategy according to the performance of the heating unit during the actual production process; after each production cycle ends, the intelligent self-learning module dynamically updates the heating strategy library based on the operation data to improve the temperature control accuracy and response speed of subsequent production; S5: The energy consumption management module monitors the power consumption of each heating zone in real time through the current sensor; the load of each heating zone is balanced and optimized through the power calculation unit to ensure that the heating power meets the temperature control requirements while avoiding unnecessary energy waste and improving the energy efficiency of the system; S6: Through the communication module, the system can transmit real-time temperature data, energy consumption information, etc. to the upper computer, MES system or cloud management platform to achieve remote monitoring and management; users interact with the heating control system through the mobile terminal application or touch display screen to adjust temperature parameters, view alarm information, generate energy consumption reports, etc.; S7: The safety protection module monitors the working state of the heating system in real time and conducts a comprehensive fault detection on the heating unit; when problems such as over-temperature, abnormal temperature, heater failure, disconnection, short circuit, etc. occur, the safety protection module issues an alarm signal in time and activates the protection mechanism, such as power-off protection or power adjustment, etc., to ensure the safe and stable operation of the system; S8: According to the changes in the real-time production environment (such as load changes, ambient temperature fluctuations, etc.), the system dynamically adjusts the heating strategy to ensure that the temperature of each heating zone is always maintained within the most suitable range, and guarantees the quality stability during the injection molding process; the intelligent self-learning module continuously accumulates data during each production process and optimizes the heating control strategy to further improve the performance of the system; S9: The cloud management platform is connected to the heating control system of the injection molding machine to conduct centralized monitoring, statistics, and maintenance management of the heating data of multiple injection molding machines; users can view the working state, temperature curve, energy consumption data, etc. of all devices through the cloud platform for centralized management, remote fault diagnosis, and maintenance scheduling.

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