Efficient cooling and shaping system for core rod production and processing

Abstract

The invention relates to the technical field of industrial manufacturing, and discloses an efficient cooling and shaping system for core rod production and processing, comprising: a core rod cooling path design module for designing a multi-channel cooling path inside a core rod and an external spray cooling path; the temperature sensing and monitoring module is used for collecting temperature data inside and on the surface of the core rod in real time; the intelligent control module is used for dynamically generating cooling parameters based on the target temperature and the current temperature of the core rod; and the cooling execution and feedback module is used for adjusting the flow rate of the cooling liquid, the spraying pressure and the spraying direction according to the cooling parameters generated by the intelligent control module. By optimizing an internal cooling path and an external spray cooling design of the core rod, efficient and uniform cooling is realized so as to shorten the shaping time; the precise temperature control and partition cooling technology is combined, thermal stress and deformation are effectively reduced, and the machining precision is improved; and meanwhile, the operation cost is reduced through dynamic energy consumption optimization and cooling liquid circulation, and the green and energy-saving targets are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of industrial manufacturing, in particular to a high-efficiency cooling and shaping system for core rod production and processing. Background Art

[0002] During the production and processing of the core rod, a large amount of heat is often accumulated due to the need for high-temperature heating and complex molding processes. This heat must be quickly removed during the cooling stage to complete the shaping. However, traditional core rod cooling technology has many shortcomings and is difficult to meet the high requirements of modern production for efficiency, quality, energy saving and environmental protection.

[0003] At present, the common core rod cooling methods mainly include natural cooling and traditional forced cooling. Although natural cooling is simple, the cooling speed is slow, and it is difficult to ensure the uniformity of the temperature inside and outside the core rod during the cooling process, which easily causes deformation and quality problems of the core rod. The traditional forced cooling method removes heat through a single cooling path (such as internal cooling or external spraying), but it is limited by the single cooling path design and the limitations of the temperature control system, and there are many problems. On the one hand, in the traditional cooling path design, the contact area between the coolant and the core rod is limited, the heat transfer efficiency is not high, and the cooling time is too long, resulting in low cooling efficiency; on the other hand, due to the lack of real-time monitoring and dynamic adjustment of the temperature distribution inside and outside the core rod, local overcooling or overheating is prone to occur during the cooling process, increasing the risk of thermal stress and deformation. In addition, traditional cooling systems mostly adopt a constant flow and constant pressure operation mode, lack of energy consumption optimization means, resulting in high system operating costs and low energy utilization.

[0004] At the same time, the surface of the mandrel is directly exposed to the coolant and is susceptible to corrosion and wear during long-term operation, which not only reduces the service life of the mandrel, but also further affects the stability and reliability of the cooling system. Therefore, in view of the above problems, a new cooling and shaping system that can achieve efficient cooling of the mandrel, precise temperature control, energy saving and environmental protection is urgently needed to meet the modern industry's demand for high efficiency and high quality of mandrel processing. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a high-efficiency cooling and shaping system for core rod production and processing, which solves the problems of low cooling efficiency, insufficient temperature control accuracy and high energy consumption in the existing core rod cooling process.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an efficient cooling and shaping system for mandrel production and processing, comprising:

[0007] Core rod cooling path design module, used to design the multi-channel cooling path inside the core rod and the external spray cooling path;

[0008] Temperature sensing and monitoring module, used to collect real-time temperature data inside and on the surface of the core rod;

[0009] Intelligent control module for dynamically generating cooling parameters based on the mandrel target temperature and current temperature;

[0010] A cooling execution and feedback module is used to adjust the coolant flow rate, spray pressure and spray direction according to the cooling parameters generated by the intelligent control module;

[0011] Data analysis and optimization module, used to analyze data during the cooling process and optimize cooling strategies.

[0012] Preferably, the core rod cooling path design module includes:

[0013] Multi-channel internal cooling path, using spiral or tree-like structure to increase the contact area between the coolant and the inner wall of the core rod;

[0014] A spray cooling path, including an annular spray array, capable of adjusting the spray angle and pressure of the nozzle;

[0015] The surface of the core rod is covered with a high thermal conductivity coating to enhance the heat exchange efficiency between the coolant and the core rod surface.

[0016] Preferably, the heat exchange of the cooling path satisfies the following formula:

[0017] Q cool =hA contact (T surface -T fluid )

[0018] in:

[0019] Q cool : The amount of heat transferred by the cooling of the core rod per unit time;

[0020] h: heat transfer coefficient between the coolant and the inner wall of the core rod;

[0021] A contact : contact area of ​​cooling path;

[0022] T surface : core rod inner wall temperature;

[0023] T fluid : Coolant temperature.

[0024] Preferably, the temperature sensing and monitoring module includes:

[0025] Built-in thermocouple sensor to monitor the internal temperature of the mandrel;

[0026] Non-contact infrared temperature sensor, used to collect core rod surface temperature data;

[0027] The data fusion module is used to perform denoising and real-time fusion calculation on the temperature data collected by the sensor.

[0028] Preferably, the temperature measurement of the embedded thermocouple sensor satisfies the following formula:

[0029] E=α(T junction -T reference )

[0030] in:

[0031] E: potential output by the thermocouple;

[0032] α: thermoelectric coefficient of thermocouple material;

[0033] T junction : Thermocouple contact point temperature;

[0034] T reference : Thermocouple reference junction temperature.

[0035] Preferably, the intelligent control module includes:

[0036] A reinforcement learning control module to dynamically adjust the coolant flow rate and spray pressure based on a reward function;

[0037] A temperature prediction module is used to predict the future temperature distribution of the core rod based on historical temperature data;

[0038] The cooling parameter generation module is used to generate cooling parameters according to the target temperature and the predicted temperature.

[0039] Preferably, the reward function of the reinforcement learning control module is defined as:

[0040] R=-|T target -T current |-βE energy

[0041] in:

[0042] R: reward value;

[0043] T target : Mandrel target temperature;

[0044] T current : Current temperature of the mandrel;

[0045] β: energy consumption penalty coefficient;

[0046] E energy : Energy consumption of the cooling process.

[0047] Preferably, the cooling execution and feedback module includes:

[0048] A variable frequency pump control submodule, used to adjust the coolant flow rate according to cooling parameters;

[0049] A spray adjustment submodule, used to adjust the angle and pressure of the nozzle;

[0050] Heat exchangers are used to maintain a constant temperature of the coolant and to heat the subcooled liquid.

[0051] Preferably, the flow rate of the coolant satisfies the following formula:

[0052]

[0053] in:

[0054] v fluid : Coolant flow rate;

[0055] ρ: coolant density;

[0056] C p : specific heat capacity of coolant;

[0057] T inlet and T outlet : Coolant inlet and outlet temperatures.

[0058] Preferably, the data analysis and optimization module includes:

[0059] Real-time data analysis module to evaluate cooling efficiency and detect temperature control anomalies;

[0060] A historical data optimization module is used to optimize cooling parameters based on historical data of the cooling process;

[0061] Energy consumption evaluation module, used to record the energy consumption data of the cooling system and optimize the cooling strategy.

[0062] The present invention provides an efficient cooling and shaping system for core rod production and processing. It has the following beneficial effects:

[0063] 1. The present invention significantly increases the contact area between the coolant and the core rod surface by designing a multi-channel cooling path inside the core rod and an external spray cooling path, and uses a zone cooling technology to dynamically adjust different areas to ensure rapid heat removal. Combined with the application of a high thermal conductivity coating and the turbulence enhancement design of the cooling path, the cooling time of the core rod is shortened, and the heat transfer is more uniform and efficient during the entire cooling process, thereby greatly improving the efficiency of core rod production and processing.

[0064] 2. The present invention collects the temperature data inside and outside the core rod in real time through the temperature sensing and monitoring module, and combines the cooling parameters generated by the intelligent control module to achieve precise control of the coolant flow and spray pressure in the cooling path, ensuring that the temperature of each area of ​​the core rod is always kept within the set range. Through the dual mechanism of zone cooling and temperature control feedback, the thermal stress and deformation problems caused by local overcooling or overheating are effectively avoided, thereby improving the processing accuracy and quality of the core rod products.

[0065] 3. The present invention avoids the energy waste caused by the fixed mode operation in the traditional cooling system by dynamically adjusting the coolant flow rate, spray pressure and spray flow rate. At the same time, the coating optimization and coolant recycling design further reduce the coolant consumption and the heat loss of the equipment. Combined with the energy consumption optimization algorithm in the cooling process, the present invention can significantly reduce the total operating cost of the cooling system, achieve the environmental protection goal of green energy saving, and is suitable for large-scale industrial production. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a schematic diagram of the overall framework of the system in the present invention;

[0067] Figure 2 It is a schematic diagram of a core rod cooling path design module in the present invention;

[0068] Figure 3 Schematic diagram of the temperature sensing and monitoring module in the present invention;

[0069] Figure 4 is a schematic diagram of the intelligent control module in the present invention;

[0070] Figure 5 It is a schematic diagram of the cooling execution and feedback module in the present invention;

[0071] Figure 6 It is a schematic diagram of the data analysis and optimization module in the present invention. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] Example:

[0074] Please refer to the attached Figure 1 -Attached Figure 6 The embodiment of the present invention provides an efficient cooling and shaping system for mandrel production and processing, including:

[0075] 1. Core rod cooling path design module, used to design the multi-channel cooling path inside the core rod and the external spray cooling path;

[0076] 1. Internal cooling path design

[0077] 1.1. Multi-channel cooling path layout

[0078] A multi-channel cooling path is arranged inside the core rod, and the cooling path adopts a spiral or branch-like structure. Its design goal is to maximize the contact area between the coolant and the inner wall of the core rod and enhance the heat exchange efficiency between the coolant and the inner wall of the core rod. The spiral design can increase the turbulence intensity of the coolant, and the branch-like design can optimize the distribution of the cooling path.

[0079] 1.2 Heat transfer formula:

[0080] The heat exchange of the cooling path satisfies the following formula:

[0081] Q cool =hA contact (T surface -T fluid )

[0082] in:

[0083] Q cool : The heat taken away by the coolant per unit time (W).

[0084] h: heat transfer coefficient between coolant and core channel wall (W / m 2 ·K).

[0085] A contact : Contact area of ​​the inner wall of the cooling channel (m 2 ).

[0086] T surface : Temperature of the core rod channel wall (K).

[0087] T fluid : Average temperature of coolant (K).

[0088] Calculate the heat removal Q based on the actual temperature demand of each zone cool,i , satisfying the following formula:

[0089] Q cool,i =h i A contact,i (T surface,i -T fluid,i )

[0090] in:

[0091] Q cool,i : The amount of heat removed per unit time from the i-th cooling zone;

[0092] h i : heat transfer coefficient between the coolant and the inner wall of the core rod in the i-th region;

[0093] A contact,i : The contact area between the coolant and the inner wall of the core rod in the i-th cooling area;

[0094] T surface,i : The inner wall temperature of the core rod in the i-th region;

[0095] T fluid,i : The average temperature of the coolant in the ith area.

[0096] Heat transfer coefficient h i Depending on the flow state of the coolant, the turbulent or laminar state of the coolant flow can be evaluated by Reynolds number calculation.

[0097] 1.3. Partition cooling flow regulation:

[0098] The cooling path is divided into multiple zones, and different zones have independent coolant flow control. According to the temperature distribution of different zones of the mandrel, the coolant flow rate is adjusted to achieve gradient cooling.

[0099] The coolant flow rate for each cooling zone is determined by the amount of heat to be removed, Q cool,i Determine that the coolant flow rate satisfies the following formula:

[0100]

[0101] in:

[0102] v i : Flow rate of coolant in zone i (m 3 / s).

[0103] ρ: Coolant density (kg / m 3 ).

[0104] C p : Specific heat capacity of the coolant (J / kg·K).

[0105] T inlet,i and T outlet,i : Inlet and outlet temperatures of the coolant (K).

[0106] A flow control device, such as a variable frequency pump or an electromagnetic flow control valve, adjusts the coolant flow rate of each zone in real time according to the above formula to meet the heat removal requirements.

[0107] 1.4. Zone temperature control feedback:

[0108] The temperature feedback data for zone cooling comes from a distributed temperature sensor network, including:

[0109] Thermocouple sensor: arranged inside the core rod of each cooling zone to detect the wall temperature in the zone;

[0110] Coolant temperature sensor: arranged at the entrance and exit of each area to collect coolant temperature data in real time.

[0111] Based on the collected temperature data, the cooling efficiency of the current area is calculated and the coolant flow and spray parameters are dynamically adjusted to ensure that the temperature deviation is within the allowable range.

[0112] 2. Mandrel surface spray cooling design

[0113] 2.1. Annular sprayer array layout

[0114] An annular spray array is arranged on the outer surface of the core rod, and each nozzle is evenly distributed around the outer circumference of the core rod. The sprayer achieves full coverage cooling of the core rod surface by adjusting the nozzle angle, pressure and flow rate. The spray coverage satisfies the following formula:

[0115]

[0116] in:

[0117] A spray : Spray coverage area of ​​a single nozzle (m 2 );

[0118] r spray : Spray radius (m), depends on the spray pressure and nozzle diameter.

[0119] The spray path achieves uniform cooling of the core rod surface by adjusting the angle, pressure and flow of the sprayer.

[0120] 2.2. Dynamic adjustment of spray pressure

[0121] The spray pressure is dynamically adjusted according to the real-time temperature feedback of the core rod surface, and its adjustment parameters are calculated by the following formula:

[0122] P spray = k(T target -T current )

[0123] in:

[0124] P spray : spray pressure (Pa);

[0125] T target : Mandrel target cooling temperature (K);

[0126] T current : Current temperature of the mandrel surface (K);

[0127] k: control coefficient, calibrated by experiment.

[0128] 3. Optimization of mandrel surface coating

[0129] 3.1 Coating material selection

[0130] The outer surface of the core rod is coated with a high thermal conductivity material (such as graphene reinforced composite material). The coating has high thermal conductivity, wear resistance and corrosion resistance, and can significantly improve the heat exchange efficiency of the core rod surface.

[0131] 3.2. The heat transfer performance of the coating satisfies the following formula:

[0132] Q 涂层 =k coating A coating (T surface -T fluid )

[0133] in:

[0134] Q 涂层 : Heat transfer of coating per unit time (W);

[0135] k coating : Thermal conductivity of coating material (W / m·K);

[0136] A coating :Coating contact area (m 2 );

[0137] T surface : Mandrel surface temperature (K);

[0138] T fluid : Coolant temperature (K).

[0139] 4. Flow regulation of cooling path

[0140] 4.1 Dynamic Flow Control

[0141] The flow control of the cooling path is dynamically adjusted according to the real-time feedback of the temperature control system to meet the cooling requirements of different parts of the core rod. The flow rate of the coolant satisfies the following formula:

[0142]

[0143] in:

[0144] v fluid : Coolant flow rate (m / s);

[0145] Q cool : The amount of heat to be removed (W);

[0146] ρ: Coolant density (kg / m3 );

[0147] C p : specific heat capacity of coolant (J / kg·K);

[0148] T inlet , T outlet : Coolant inlet and outlet temperatures (K).

[0149] Performance advantages:

[0150] High heat transfer efficiency: Through multi-channel internal cooling and surface coating optimization, the heat transfer capacity of the cooling path is significantly improved.

[0151] Good cooling uniformity: the optimized design of zone cooling and spray coverage is adopted to ensure uniform temperature distribution inside and outside the core rod.

[0152] Strong dynamic adjustment capability: By adjusting the coolant flow and spray pressure in real time, it can adapt to the complex temperature control requirements in core rod processing.

[0153] Wide range of applications: Modular design is suitable for the production and processing of mandrels of different specifications.

[0154] Through the implementation of this module, the cooling efficiency and shaping accuracy of the core rod processing can be significantly improved, thermal stress and deformation can be reduced, and the quality and processing efficiency of the core rod products can be improved. The design of this module fully discloses the details of the internal cooling path, external spray cooling and surface coating optimization, ensuring the repeatability and practical operability of the technology.

[0155] 2. Temperature sensing and monitoring module, used to collect temperature data inside and on the surface of the core rod in real time;

[0156] In order to capture the temperature inside and outside the core rod in real time, a multi-sensor network was constructed to achieve accurate monitoring and fusion processing of temperature signals.

[0157] 1. Temperature monitoring equipment

[0158] 1.1. Internal embedded sensors:

[0159] Embedded high temperature heat-resistant thermocouples are distributed on the inner wall of the cooling channel every 10 cm.

[0160] Thermocouple temperature measurement equation:

[0161] E=α(T junction -T reference )

[0162] in:

[0163] E: The potential difference generated by the thermocouple (V).

[0164] α: Thermoelectric coefficient of the thermocouple material (V / K).

[0165] T junction : Contact point temperature (K).

[0166] T reference : Reference end temperature (K).

[0167] 1.2. Surface non-contact sensor:

[0168] An infrared temperature sensor is used to monitor the temperature of the mandrel outer surface.

[0169] Temperature calculation formula:

[0170]

[0171] in:

[0172] E measured : The radiation energy received by the infrared sensor (W / m 2 ).

[0173] σ: Stefan-Boltzmann constant (5.67×10 -8 W / m 2 ·K 4 ).

[0174] ∈: core rod surface emissivity.

[0175] 2. Data fusion and transmission

[0176] Edge computing technology is used to pre-process the data collected by the sensor, filter out noise, and generate a multi-dimensional temperature field.

[0177] 3. Intelligent control module

[0178] The intelligent control module is used to dynamically generate cooling parameters based on the core rod target temperature and current temperature.

[0179] Function: Through artificial intelligence technology, dynamically adjust cooling parameters to achieve precise temperature control.

[0180] Submodules:

[0181] Reinforcement learning control submodule:

[0182] The cooling strategy is adjusted according to the deviation between the target temperature and the actual temperature of the mandrel.

[0183] The reward function weighs temperature error against energy consumption.

[0184] Temperature prediction submodule:

[0185] Based on the historical temperature data, the LSTM neural network is used to predict the future temperature distribution of the core rod.

[0186] Optimize cooling parameters in advance.

[0187] Cooling parameter generation submodule:

[0188] Calculate coolant flow rate, spray pressure and coolant temperature in real time.

[0189] Input: target temperature, current temperature data, historical cooling data.

[0190] Output: Optimized cooling control parameters.

[0191] 1. Reinforcement Learning Control

[0192] Control objectives:

[0193] Minimize core temperature deviation |T target -T current | and energy consumption.

[0194] Reward function design:

[0195] R=-|T target -T current |-βE energy

[0196] 2. Temperature prediction model

[0197] Use LSTM (Long Short-Term Memory Network) to predict the core rod temperature change trend:

[0198] T t+1 =f LSTM (T t ,T t-1 ,...,T t-n )

[0199] The intelligent control module includes the following steps:

[0200] S1. Target temperature setting:

[0201] According to the core rod processing requirements and material properties, set the target cooling temperature T of the core rod. target and the allowable temperature deviation range ΔT;

[0202] S2. Real-time temperature acquisition: obtain the real-time temperature data of the core rod transmitted by the temperature sensing and monitoring module, including the internal temperature T of the core rod internal and surface temperature T surface , generate current temperature distribution data T current .

[0203] S3, temperature deviation calculation: according to the target temperature T target With the current temperature T currentThe temperature deviation ΔT is calculated by current :

[0204] ΔT current =T target -T current

[0205] S4. Cooling parameter calculation: based on temperature deviation ΔT current , generating coolant flow rate v fluid , spray pressure P spray and coolant temperature T fluid The optimization parameters are:

[0206] Coolant flow rate v fluid Satisfies the following formula:

[0207]

[0208] in:

[0209] Q cool The amount of heat that needs to be removed;

[0210] ρ is the coolant density;

[0211] C p is the specific heat capacity of the coolant;

[0212] T inlet , T outlet are the inlet and outlet temperatures of the coolant.

[0213] Spray pressure P spray Calculated by the following formula:

[0214] P spray = k(T target -T current )

[0215] in:

[0216] k is the spray control coefficient, which is based on experimental calibration.

[0217] S5. Temperature prediction: The temperature prediction model is used to predict the future temperature change trend of the core rod. The long short-term memory network (LSTM) is used to realize the prediction based on the historical temperature data. The prediction formula is:

[0218] T t+1 =f LSTM (T t ,T t-1 ,...,T t-n )

[0219] in:

[0220] Tt+1 Forecast temperature at a future moment;

[0221] T t ,T t-1 ,...,T t-n is the temperature data at the past n moments.

[0222] S6. Reinforcement Learning Optimization:

[0223] Using the reinforcement learning control strategy, the cooling parameters are optimized according to the temperature deviation and energy consumption, and the reward function is defined as:

[0224] R=-|T target -T current |-βE energy

[0225] in:

[0226] R is the reward value;

[0227] β is the energy consumption penalty coefficient;

[0228] E energy is the current energy consumption of the system.

[0229] S7, cooling parameter output:

[0230] The optimized coolant flow rate, spray pressure and coolant temperature parameters are output to the cooling execution and feedback module to perform real-time cooling control.

[0231] Through the above steps, the intelligent control module can realize dynamic optimization of the core rod cooling parameters, ensuring that the core rod temperature is always kept within the target range, while reducing energy consumption and improving cooling efficiency.

[0232] 4. Cooling execution and feedback module, used to adjust the coolant flow rate, spray pressure and spray direction according to the cooling parameters generated by the intelligent control module;

[0233] The module achieves real-time adjustment of cooling parameters through variable frequency pump and spray system.

[0234] 1. Coolant flow rate adjustment

[0235]

[0236] 2. Spray system adjustment

[0237] Adjust the spray angle, pressure and flow rate in real time according to temperature feedback to ensure that the spray covers the high temperature area.

[0238] 5. Data Analysis and Optimization Module

[0239] Cooling efficiency optimization and parameter adaptive adjustment are achieved through data analysis.

[0240] 1. Real-time data optimization

[0241] Kalman filtering is used to remove noise and generate accurate temperature distribution maps in real time.

[0242] 2. Historical data analysis

[0243] Use machine learning techniques (such as decision trees or clustering algorithms) to optimize cooling parameter configuration.

[0244] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Highly efficient cooling and shaping system for core rod production and processing, characterized by: include: Core rod cooling path design module, used to design the multi-channel cooling path inside the core rod and the external spray cooling path; Temperature sensing and monitoring module, used to collect real-time temperature data inside and on the surface of the core rod; Intelligent control module for dynamically generating cooling parameters based on the mandrel target temperature and current temperature; A cooling execution and feedback module is used to adjust the coolant flow rate, spray pressure and spray direction according to the cooling parameters generated by the intelligent control module; Data analysis and optimization module, used to analyze data during the cooling process and optimize cooling strategies.

2. The efficient cooling and shaping system for mandrel production and processing according to claim 1 is characterized in that: The core rod cooling path design module includes: Multi-channel internal cooling path, using spiral or tree-like structure to increase the contact area between the coolant and the inner wall of the core rod; A spray cooling path, including an annular spray array, capable of adjusting the spray angle and pressure of the nozzle; The surface of the core rod is covered with a high thermal conductivity coating to enhance the heat exchange efficiency between the coolant and the core rod surface.

3. The efficient cooling and shaping system for mandrel production and processing according to claim 1 is characterized in that: The heat exchange of the cooling path satisfies the following formula: Q cool =hA contact (T surface -T fluid ) in: Q cool : The amount of heat transferred by the cooling of the core rod per unit time; h: heat transfer coefficient between the coolant and the inner wall of the core rod; A contact : contact area of ​​cooling path; T surface : core rod inner wall temperature; T fluid : Coolant temperature.

4. The efficient cooling and shaping system for mandrel production and processing according to claim 1 is characterized in that: The temperature sensing and monitoring module comprises: Built-in thermocouple sensor to monitor the internal temperature of the mandrel; Non-contact infrared temperature sensor, used to collect core rod surface temperature data; The data fusion module is used to perform denoising and real-time fusion calculation on the temperature data collected by the sensor.

5. The efficient cooling and shaping system for mandrel production and processing according to claim 1, characterized in that: The temperature measurement of the embedded thermocouple sensor satisfies the following formula: E=α(T junction -T reference ) in: E: potential output by the thermocouple; α: thermoelectric coefficient of thermocouple material; T junction : Thermocouple contact point temperature; T reference : Thermocouple reference junction temperature.

6. The efficient cooling and shaping system for mandrel production and processing according to claim 1, characterized in that: The intelligent control module comprises: A reinforcement learning control module to dynamically adjust the coolant flow rate and spray pressure based on a reward function; A temperature prediction module is used to predict the future temperature distribution of the core rod based on historical temperature data; The cooling parameter generation module is used to generate cooling parameters according to the target temperature and the predicted temperature.

7. The efficient cooling and shaping system for mandrel production and processing according to claim 1, characterized in that: The reward function of the reinforcement learning control module is defined as: R=-|T target -T current |-βE energy in: R: reward value; T target : Mandrel target temperature; T current : Current temperature of the mandrel; β: energy consumption penalty coefficient; E energy : Energy consumption of the cooling process.

8. The efficient cooling and shaping system for mandrel production and processing according to claim 1, characterized in that: The cooling execution and feedback module includes: A variable frequency pump control submodule, used to adjust the coolant flow rate according to cooling parameters; A spray adjustment submodule, used to adjust the angle and pressure of the nozzle; Heat exchangers are used to maintain a constant temperature of the coolant and to heat the subcooled liquid.

9. The efficient cooling and shaping system for mandrel production and processing according to claim 1, characterized in that: The flow rate of the coolant satisfies the following formula: in: v fluid : Coolant flow rate; ρ: coolant density; C p : specific heat capacity of coolant; T inlet and T outlet : Coolant inlet and outlet temperatures.

10. The efficient cooling and shaping system for mandrel production and processing according to claim 1, characterized in that: The data analysis and optimization module includes: Real-time data analysis module to evaluate cooling efficiency and detect temperature control anomalies; A historical data optimization module is used to optimize cooling parameters based on historical data of the cooling process; Energy consumption evaluation module, used to record the energy consumption data of the cooling system and optimize the cooling strategy.

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