Heat preservation furnace preheating system and method for die casting production

Abstract

The invention discloses a heat-preserving furnace preheating system and method for die-casting production. The heat-preserving furnace preheating system for die-casting production comprises a four-layer framework including sensing, execution, control and application and is matched with a four-step preheating method. The sensing layer monitors temperature and stress in a full-dimension mode, the execution layer is provided with a partition composite heat source and two-stage waste heat recovery, the control layer is regulated and controlled through digital twinning and AI, and the application layer achieves visual management and factory data interaction. Under the synergistic effect of the system, the furnace temperature control precision is high, and the uniformity is good; graded waste heat recovery and an intelligent preheating curve reduce energy consumption; thermal stress monitoring prediction and accurate operation and maintenance prolong the service life of the furnace lining and reduce the cost; the efficiency is improved through cooperation of preheating and production and rapid fault response; full-process visualization and factory system interconnection upgrading intelligentization are achieved, the target of quality improvement, energy conservation, cost reduction, efficiency improvement and intelligence integration is finally achieved, and the die-casting production line is adapted to a modern die-casting production line.

Description

Technical Field

[0001] This invention belongs to the technical field of die casting production equipment, specifically a preheating system and method for a holding furnace used in die casting production. Background Technology

[0002] In die casting production, the preheating quality of the holding furnace has a critical impact on the stability of the melt temperature, the product qualification rate, and the equipment operation and maintenance costs. Currently, the preheating systems commonly used in the industry suffer from several core technical bottlenecks: traditional single heat sources (such as pure electromagnetic heating and resistance heating) are difficult to match the differentiated heat demands of the entire process of feeding, melting, and discharging in the holding furnace, resulting in radial temperature gradients in the melt contact area often exceeding ±30℃, leading to product defects such as shrinkage cavities and cracks; during intermittent production processes (such as mold changes and waiting for materials), due to the lack of an effective heat buffering mechanism, the energy consumption during system reheating from room temperature accounts for more than 30% of the total energy consumption; frequent preheating also causes the furnace lining to bear significant thermal stress due to drastic temperature differences between the inside and outside, exacerbating microcrack propagation, and the existing systems lack stress monitoring and control mechanisms, resulting in an average furnace lining lifespan of only 800-1000 preheating cycles.

[0003] In addition, existing digital twin models fail to incorporate operating parameters such as heat loss and preheating frequency in actual die-casting batches, resulting in temperature field prediction deviations exceeding 10%, which cannot effectively support accurate preheating decisions. In terms of maintenance, furnace lining health assessment still relies solely on usage time and fails to correlate preheating frequency with the cumulative effect of thermal stress, which can easily lead to over-maintenance or sudden failures.

[0004] In view of the above problems, the industry urgently needs to develop an intelligent preheating system and method that integrates multiple algorithms and is adapted to the actual working conditions of die casting, so as to achieve the comprehensive goals of precise temperature control, energy saving and consumption reduction, extended furnace lining life and support for intelligent maintenance. Summary of the Invention

[0005] The purpose of this invention is to provide a preheating system and method for a holding furnace in die casting production, so as to solve the problems of poor temperature uniformity, high energy consumption, short furnace lining life and inaccurate maintenance in the existing die casting holding furnace preheating system mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A preheating system for a holding furnace used in die casting production, comprising: The sensing layer includes K-type thermocouples and micro-strain sensors arranged on the inner wall, outer wall and middle layer of the die-casting heat preservation furnace lining, a non-contact infrared thermometer set in the center of the furnace, and flow sensors and power sensors respectively installed in the waste heat recovery fluid circuit and the heat source power supply circuit. The execution layer includes at least three partitioned composite heat source modules distributed along the furnace body axis, and two-stage waste heat recovery modules connected in series. The partitioned composite heat source modules include medium-frequency electromagnetic induction coils, infrared radiation tubes, and cooling fans. The two-stage waste heat recovery modules include a high-temperature section finned copper heat exchanger and a combination of a medium-temperature section spiral tube heat exchanger and a phase change material PCM heat storage tank. The control layer includes a digital twin model and an AI predictive control unit that match the die-casting production process; the digital twin model integrates multi-physics simulation of temperature field, stress field and flow field; the AI ​​predictive control unit includes a preheating curve generation module that is linked to the start and stop of the die-casting machine, a furnace lining thermal stress prediction module and a model self-optimization module; The application layer includes a local control unit with functions such as temperature field visualization, energy consumption statistics, furnace lining health assessment and fault alarm, as well as a factory-level interface that supports data interaction with the die-casting plant's MES system.

[0007] A preheating method for a holding furnace used in die casting production, the preheating method comprising the following steps: S1: System initialization, complete sensor calibration and testing, digital twin model parameter initialization and loading, and heating unit communication link testing. According to the furnace lining type, call the material database and generate a multi-segment heating rate curve by combining the die-casting machine start-up time and electricity price peak and valley periods. S2: Coordinated preheating, controlling the medium frequency electromagnetic induction coil to operate stably at the preset initial power, and using infrared radiation tubes to dynamically compensate for the temperature difference in each zone of the furnace in real time, and triggering the start of the two-stage waste heat recovery modules according to the furnace temperature change, so as to realize the coordinated operation of heat source supply and waste heat recovery. S3: Constant temperature maintenance. When the furnace temperature fluctuation exceeds the ±2℃ threshold, the output power of each heat source module is automatically adjusted. At the same time, the PCM heat storage tank is controlled to release heat and control the temperature as needed. Simultaneously, the furnace lining stress state is monitored in real time through micro-strain sensors, and key parameter data during the preheating process are fully recorded. S4: Cooling maintenance. The cooling process is smoothly controlled according to the preset gradient cooling curve. Based on the thermal stress accumulation data during the entire preheating cycle, the quantitative score of furnace lining health is updated, and targeted maintenance suggestions are output to achieve precise management of furnace lining operation and maintenance.

[0008] According to the above technical solution, the partitioned composite heat source module is configured with a power complementary linkage algorithm, specifically: the AI ​​predictive control unit collects the temperature difference ΔTᵢ between the inside and outside of the i-th partition detected by the K-type thermocouple every 2 seconds, where ΔTᵢ is: When ΔTᵢ≤8℃, maintain the initial power P of the intermediate frequency electromagnetic induction coil. 电磁0 With the initial power P of the infrared radiator 红外0 When ΔTᵢ>8℃, follow P电磁新 =P 电磁0 ×(1-k1), P infrared new = P infrared 0 × (1+k2) adjust power, where k1 is 0.1~0.15 and k2 is 0.2~0.25; If ΔTᵢ is still greater than 8℃ after adjustment, then proceed according to P. 电磁迭代 =P 电磁新 ×(1-0.5k1), P 红外迭代 =P 红外新 ×(1+0.5k2) iterative correction until ΔTᵢ≤8℃, controlling the radial temperature gradient in the contact area of ​​the die-casting melt within ±2℃.

[0009] According to the above technical solution, the two-stage waste heat recovery module is configured with an intermittent heat buffering algorithm, specifically: when the outlet exhaust gas temperature T of the medium-temperature section heat exchanger... 余热 When the phase transition temperature of PCM is ≥, the recoverable heat Q is calculated using the formula: in, For the specific heat capacity of the exhaust gas, For the quality of exhaust gas, ; The exhaust gas mass flow rate is expressed in kg / s. For the recovery time, The outlet exhaust gas temperature of the medium-temperature section heat exchanger. The phase transition temperature of the PCM; like ≤PCM maximum heat storage If the heat is fully recoverable, all recoverable heat will be stored in the PCM heat storage tank; otherwise, it will be stored in the PCM heat storage tank first. After reaching the PCM heat storage tank, the remaining heat is used to heat the circulating water; during the die-casting interval, the furnace lining temperature... Calculate the required additional heat when the temperature is <300℃. Specifically: in, For the specific heat capacity of the furnace lining, For the quality of the furnace lining, This refers to the furnace lining temperature during the intermittent period. like ≤PCM thermal storage tank residual heat storage Then the heat release from the PCM will meet the heat replenishment requirement. > Heat is first released through the PCM heat storage tank. The insufficient portion is supplemented by an auxiliary electric heating module, thereby effectively reducing the energy consumption cost of the first preheating after the interval period.

[0010] According to the above technical solution, the digital twin model is configured with a dynamic correction algorithm for die-casting conditions. Specifically, in the temperature field simulation, a heat loss coefficient of the molten contact zone based on N batches of historical die-casting data is introduced. Specifically: in, Temperature of the molten metal contact zone detected by an infrared thermometer Let the initial simulation temperature be the temperature of the i-th batch of digital twin models, and then... Correcting the temperature field; In the stress field simulation process, a preheating frequency correction coefficient is introduced. Specifically: Where n is the number of times it has been preheated, The actual stress value detected by the micro-strain sensor during the nth preheating. The initial simulation stress value of the digital twin model during the nth preheating is given, and it is calculated according to... The stress field simulation results were corrected, and the remaining life of the furnace lining was calculated by combining the material σ-N curve. Ntotal represents the total fatigue life of the material, used to reduce life prediction errors.

[0011] According to the above technical solution, the furnace lining is a composite structure of functionally graded material (FGM) and phase change material (PCM) microcapsules. A material-heat flux adaptation algorithm is configured, and the algorithm executes the following steps: Temperature difference acquisition: The temperature difference ΔT between the inside and outside of the furnace lining is acquired in real time through a K-type thermocouple in the middle layer of the furnace lining, with a sampling frequency of 1Hz, and the real-time power output data of the zoned composite heat source module is acquired simultaneously. Dynamic matching of thermal conductivity coefficient: Based on the gradient characteristics of FGM, when ΔT>15℃, the algorithm automatically increases the thermal conductivity coefficient λ(x) of the inner layer of FGM, while decreasing the thermal conductivity coefficient λ(x) of the outer layer; when ΔT<5℃, the algorithm reverses the adjustment of λ(x), so that the inner layer λ(x) returns to the baseline value and the outer layer λ(x) increases. PCM latent heat release regulation: Combining ΔT and heat source power data, when ΔT>15℃, the algorithm controls the latent heat release rate of PCM microcapsules to increase, helping to smooth the temperature difference; when ΔT<5℃, the latent heat release rate is reduced to avoid excessive heat release leading to temperature fluctuations.

[0012] According to the above technical solution, in step S1, the multi-segment heating rate curve is generated by the die-casting production adaptation algorithm, specifically: the total remaining preheating time is calculated based on the planned start time of the die-casting machine and the current time. , according to The total duration has been adjusted to allow for time for temperature stabilization. For safety reasons, the preheating process is divided into low-temperature, medium-temperature, and high-temperature sections; the rate in the medium-temperature section is fixed at 0.8~0.9℃ / min. By reverse-engineering the rates v1 in the low-temperature section and v3 in the high-temperature section, we can ensure that the melt temperature matches the die-casting requirements upon completion of preheating; among which... =(300℃-T 当前 / v1), v2 = 0.8 to 0.9℃ / min, =(T 目标 -800℃) / v3.

[0013] According to the above technical solution, the monitoring of furnace lining thermal stress in step S2 is achieved through a multi-parameter coupling algorithm, specifically: first, the basic thermal stress is calculated, as shown in the following formula: Where E is the elastic modulus of the furnace lining, α is the coefficient of thermal expansion, and ΔT is the temperature difference between the inside and outside of the furnace lining; a preheating frequency correction coefficient is then introduced. With furnace lining aging coefficient ,in , Where n is the number of preheating cycles, To round down, t is used as the number of days the furnace lining has been used, calculated as follows: Calculate the total thermal stress; when ≥0.7× When the heating rate is reduced, a level 1 warning is triggered. ≥0.9× : Suspend preheating and trigger a level-two warning to ensure the safety of the furnace lining structure.

[0014] According to the above technical solution, the factory-level interface is configured with a preheating-die-casting closed-loop interaction algorithm, specifically: transmitting the preheating completion time t to the MES system via the OPCUA protocol. 预热完成 Die casting machine start-up time t 压铸启动 Actual temperature of the melt T 熔液实际 With the required temperature T 熔液要求 The time matching degree Mt is calculated as follows: When |t 预热完成 -t 压铸启动 When |T ≤ 5min, Mt = 100%, and for every 1min exceeding 5min, Mt decreases by 10%; the temperature matching degree MT is calculated as follows: when |T 熔液实际 -T 熔液要求 When the temperature is ≤±5℃, MT=100%; for every 1℃ increase above this temperature, MT decreases by 20%. Press M 综合=0.6Mt+0.4MT to calculate the overall matching degree: when M 综合 Maintain parameters when ≥90%, and ≤70% for M. 综合 If <90%, adjust the preheating start time or target temperature for the next batch. 综合 When the temperature drops below 70%, the preheating curve algorithm is reactivated to reduce the waiting time in die casting production.

[0015] According to the above technical solution, the furnace lining health score in step S4 is calculated using a die-casting preheating correlation algorithm, specifically as follows: First, calculate the heat loss rate as 1 - (P). 有效 / P 总输入 ) Calculate the heat loss of the furnace lining, where P 有效 P is the effective preheating power, i.e., the power actually used to raise the furnace temperature; 总输入 This represents the total input power of the heat source. Then, according to the rate of decrease in thermal insulation performance = (η) 初始 -η 当前 ) / η 初始 Calculate the degree of thermal insulation performance degradation by multiplying by 100%; where P 有效 For preheating effective power, P 总输入 For the total input power, η 初始 For initial insulation efficiency, η 当前 =1 - heat loss rate; Then press health = 100 - (σ) 累计 / (σ 屈服 ×10 4 The quantification score is calculated as (σ × 50) - (insulation performance degradation rate × 50), where σ 累计 For each batch of preheating process σ 总修正 The integral value changes with the preheating time; when the health score is >60, it can be used normally and the furnace lining can be used normally. When the health score is 40 < and the furnace lining is ≤60, it is recommended to repair the furnace lining locally. When the health score is ≤40, it is recommended to replace the entire furnace lining. This achieves precise maintenance related to the preheating frequency of die casting.

[0016] Compared with the prior art, the present invention has the following beneficial effects: In this invention, through the synergistic effect of full-dimensional temperature and stress monitoring at the sensing layer, zoned composite heat sources and two-stage waste heat recovery at the execution layer, digital twin and AI predictive regulation at the control layer, and visualized management and factory-level data interaction at the application layer, multiple comprehensive technical effects are achieved: Firstly, it significantly improves the accuracy and uniformity of furnace temperature control (constant temperature fluctuation ≤ ±2℃, eliminating local temperature differences); secondly, it reduces energy consumption through graded waste heat recovery (significantly improving waste heat utilization rate) and intelligent preheating curves linked to the die-casting machine and electricity prices; thirdly, it extends the furnace lining life and reduces maintenance costs through real-time monitoring and prediction of furnace lining thermal stress and precise operation and maintenance based on full-cycle data; fourthly, it improves production efficiency through deep collaboration between preheating and production processes and rapid fault response; and fifthly, it upgrades intelligent management through full-process data visualization and interconnection with the factory MES system, ultimately achieving the integrated goals of quality improvement, energy saving, cost reduction, efficiency enhancement, and intelligence, adapting to the high requirements of modern die-casting production lines. Attached Figure Description

[0017] Figure 1 This is a flowchart of the preheating method of the preheating system of the present invention. Detailed Implementation

[0018] 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.

[0019] Example 1 This system comprises a perception layer, an execution layer, a control layer, and an application layer. These layers work together to achieve precise preheating and intelligent control. The specific structure is as follows: The sensing layer is used to collect key physical parameters during the preheating process of the holding furnace in real time, providing data support for the control layer, including: Temperature sensing components: 3-5 sets of K-type thermocouples (measuring range 0-1200℃, accuracy ±0.5%FS), embedded in the inner wall of the furnace lining (molten contact area, 5mm from the inner wall surface), the middle layer (half the furnace lining thickness), and the outer wall (3mm from the outer wall surface); one non-contact infrared thermometer (measuring range 200-1000℃, resolution 1℃), fixed in the center of the furnace (100mm from the molten liquid surface), used to correct thermocouple measurement deviations.

[0020] Stress sensing components: 2-3 sets of micro-strain sensors (range 0-5000με, sensitivity 1με / V) are attached to the middle layer of the furnace lining (uniformly distributed along the axial direction) to monitor changes in thermal stress in the furnace lining.

[0021] Energy and fluid sensing components: One electromagnetic flowmeter (measuring range 0.1-10 m³ / h, accuracy ±0.2%), installed in the waste heat recovery fluid loop (heat exchanger inlet pipe); one power sensor (measuring range 0-100 kW, accuracy ±0.1%), connected in series in the heat source power supply loop (medium frequency electromagnetic induction coil power supply terminal), to monitor the waste heat fluid flow and heat source power respectively.

[0022] The execution layer executes the instructions of the control layer to achieve heat source output regulation and waste heat recovery, including: Zoned composite heat source module: 3-4 zones are distributed along the furnace body axis (upper, middle, lower). Each zone contains 1 set of medium frequency electromagnetic induction coils (rated power 30-60kW, frequency 1-10kHz), 1 set of infrared radiation tubes (rated power 10-20kW, wavelength 2-5μm), and 1 cooling fan (air volume 500-1500m³ / h). The medium frequency electromagnetic induction coils are used for deep heating of the furnace lining, the infrared radiation tubes are used for surface temperature compensation, and the cooling fan is used for emergency cooling (such as when stress exceeds the standard).

[0023] Two-stage waste heat recovery module: installed in series at the exhaust gas outlet of the preheating system, including: High-temperature section: Finned copper heat exchanger (fin spacing 5-8mm, heat exchange area 1.5-3㎡, operating temperature 300-500℃), used to recover the sensible heat of high-temperature waste gas; Medium-temperature section: A combination of spiral tube heat exchanger (tube diameter 20-30mm, spiral number 10-15 turns) and phase change material (PCM) heat storage tank (volume 0.5-2m³, PCM uses NaNO2-KNO3 eutectic salt, phase change temperature 270℃, latent heat 150-200kJ / kg) is used to recover and store the latent heat of medium-temperature waste gas (200-300℃).

[0024] The control layer is the core of the system, used to implement multi-physics coupled control, including: Digital twin model: built on the ANSYS multiphysics simulation platform, integrating temperature field, stress field, and flow field simulation. Temperature field: Solving the heat conduction equation using the finite element method: in, Where c is the furnace lining density and c is the specific heat capacity of the furnace lining. Let q be the thermal conductivity and q be the heat flux density of the heat source. The rate of change of furnace lining temperature with respect to time. This is a heat conduction term, describing the spatial transfer of heat within the furnace lining. The heat flux density of the heat source.

[0025] Stress field: Based on thermoelastic theory, the temperature field calculation results are used as loads to solve the stress equations. in, Let D be the thermal stress generated within the furnace lining, and D be the elastic matrix of the furnace lining material. For the total strain of the furnace lining, The thermal strain of the furnace lining is caused solely by temperature changes. in, The coefficient of thermal expansion is This refers to the temperature difference between the inside and outside of the furnace lining.

[0026] Flow field: The flow of waste heat fluid was simulated using the CFD method, the Navier-Stokes equations were solved, and the structural parameters of the heat exchanger were optimized.

[0027] AI Predictive Control Unit: Built on an edge computing gateway (quad-core 2.0GHz CPU, 4GB memory), it contains 3 core modules: Preheating curve generation module: Communicates with the die-casting machine PLC via Modbus protocol, and generates a multi-segment heating curve by combining peak and valley electricity price data (obtained from the factory power monitoring system); Furnace lining thermal stress prediction module: Based on LSTM neural network, input parameters such as historical stress data and preheating frequency to predict stress changes in the next 10 batches of preheating; Model self-optimization module: After every 50 batches of preheating, the parameters of the digital twin model, such as thermal conductivity and elastic modulus E, are corrected based on the measured data to ensure that the simulation deviation is ≤3%.

[0028] The application layer implements human-computer interaction and factory-level data integration, including: Local control unit: Equipped with a 10-inch touch screen (1280×800 resolution) and an industrial computer, featuring temperature field visualization (color cloud map display), energy consumption statistics (daily / weekly / monthly reports), furnace lining health assessment (numerical scoring and level display), and fault alarm (audible and visual alarm + SMS push) functions; Factory-level interface: Adopting the OPC UA protocol, it supports data interaction with the die-casting factory's MES system. Transmitted parameters include preheating completion time, melt temperature, energy consumption data, etc., with a data transmission frequency of 1Hz.

[0029] This method is based on the above system and includes four steps: system initialization (S1), coordinated preheating (S2), constant temperature maintenance (S3), and cooling maintenance (S4). Each step combines a dedicated algorithm to achieve precise control, as detailed below: Step S1: System initialization.

[0030] Sensor testing: Zero-point calibration of type K thermocouples (based on ice-water mixture, correction deviation ≤0.1℃), no-load testing of micro-strain sensors (to ensure stable output signal), and range calibration of flow sensors and power sensors; Model parameter loading: The digital twin model loads the current furnace lining material parameters (retrieved from the material database, such as for high-alumina furnace linings). =2800kg / m³, c=1100J / (kg·℃), =1.5W / (m·℃)\), E=80GPa, =9×10 -6 / ℃.

[0031] Communication test: Establish communication connections between the control layer, execution layer, and application layer, and ensure that the instruction response delay is ≤100ms.

[0032] Preheating curve generation: A multi-segment heating rate curve is generated using a die-casting production adaptation algorithm. The algorithm formula is as follows: Calculate the total remaining preheating time: in, The planned start time for the die-casting machine (obtained from the MES system). This is the system initialization completion time, in minutes.

[0033] Total adjustment time (with time reserved for temperature stabilization): in, For a safety margin, a value of 1.1 to 1.2 is used, such as... =1.15, =360min, then =360 / 1.15≈313min.

[0034] Divide the preheating stage and deduce the rate: Preheating is divided into a low-temperature section (T) 当前 (300℃ to 300℃), medium temperature range (300℃ to 800℃), high temperature range (800℃ to T) 目标 ),in: The rate is fixed in the intermediate temperature range: v2 = 0.8 to 0.9℃ / min, for example, v2 = 0.85℃ / min, duration =500℃ / v2.

[0035] Duration of low temperature phase: =(300℃-T 当前 / v1), where T 当前 v1 represents the initial furnace temperature and v2 represents the rate of the low-temperature section.

[0036] Duration of high-temperature period: =(T 目标 -800℃) / v3, where T 目标 v3 represents the high-temperature section rate, which is the required temperature for the die-casting melt.

[0037] Rate constraint: when T 目标 =700℃, eliminate the high-temperature section, and divide the preheating into a low-temperature section (T 当前 From 300℃ to 700℃, the rate remains 0.8~0.9℃ / min in the medium temperature range. Reverse-engineering v1, =(700-800) / v3, where v3 takes a negative value to indicate cooling, and the absolute value of the rate is controlled at 1-2℃ / min.

[0038] Step S2: Collaborative preheating.

[0039] Heat source coordinated control: The medium frequency electromagnetic induction coil is controlled according to P. 电磁0 (Initial power, e.g., 50kW) During operation, the infrared radiation tube monitors the temperature difference between the inside and outside of the furnace lining zones in real time (data collected by thermocouples on the inner wall). When the temperature of a certain zone is 2℃ lower than the target value, the infrared radiation tube compensation is activated (power P). 红外0 =15kW).

[0040] Waste heat recovery startup: Two-stage waste heat recovery is started according to the furnace temperature; when the exhaust gas temperature in the furnace is ≥500℃, the high-temperature section finned heat exchanger is started; when the exhaust gas temperature in the furnace is ≥300℃, the medium-temperature section spiral tube heat exchanger and PCM heat storage tank are started.

[0041] Dynamic power adjustment: Power output is optimized through a complementary linkage algorithm of partitioned composite heat sources. The algorithm formula is as follows: First, calculate the temperature difference between the inside and outside of the zone: in, Let be the temperature of the inner wall of the furnace lining in the i-th zone (°C). Let be the temperature of the outer wall of the furnace lining in the i-th zone (°C), i = 1, 2, ..., n, where n is the number of zones.

[0042] Then adjust the power according to the power adjustment rules: Iterative correction: If after adjustment If the temperature is >8℃, then iterate according to the following formula: Until ≤8℃, ultimately controlling the radial temperature gradient in the contact zone of the die-casting melt within ±2℃.

[0043] when ≤8℃ (normal temperature difference): Maintain. ; when >8℃ (Inner wall overheating): , Where, k1 = 0.1 to 0.15 (electromagnetic power reduction coefficient, such as k1 = 0.12, k2 = 0.2 to 0.25 (infrared power enhancement coefficient, such as k2 = 0.23).

[0044] Step S3: Maintain constant temperature.

[0045] Temperature fluctuation control: When the furnace temperature fluctuates beyond ±2℃, the control layer outputs a power adjustment command (e.g., if the temperature is too high, reduce the electromagnetic power by 5%-10%; if the temperature is too low, increase the infrared power by 10%-15%). Simultaneously, the PCM heat storage tank releases heat and controls the temperature according to an intermittent heat buffering algorithm. The algorithm formula is as follows: Calculate recoverable heat (preheating stage): in, The specific heat capacity of exhaust gas (air at 270°C) =1.05kJ / (kg·℃), For the quality of exhaust gas, ,in, The exhaust gas mass flow rate is expressed in kg / s. For the recovery time, The outlet exhaust gas temperature (°C) of the medium-temperature section heat exchanger. This is the PCM phase transition temperature.

[0046] Heat storage rules: Heat replenishment during the interval (when changing molds in the die-casting machine): in, For the specific heat capacity of the furnace lining, For the quality of the furnace lining, Temperature of the furnace lining during the intermittent period (°C).

[0047] Calorie replenishment rules: If Q 回收 ≤Q 储 (Q) 储 (For the maximum heat storage capacity of the PCM, such as 500kJ): all heat is stored in the PCM heat storage tank; If Q 回收 >Q 储 Storage Q 储 Afterwards, the remaining heat (Q) 回收 -Q 储 It is used to heat circulating water (for use by other equipment in the plant).

[0048] If (Q) 补 ≤Q 剩余 (Q) 剩余 (For the remaining heat storage of the PCM): it is supplemented by heat release from the PCM heat storage tank; If Q 补 >Q 剩余 PCM heat release Q 剩余 Afterwards, the remaining heat (Q) 补 -Q 剩余 The energy consumption for the first preheating after the intermittent period is reduced by more than 35% by supplementing the auxiliary electric heating (power 20kW).

[0049] Stress monitoring: Micro-strain sensors collect furnace lining stress data once per second, and simultaneously record parameters such as preheating time and power output to provide data for subsequent health assessment.

[0050] Step S4: Cooling maintenance.

[0051] Gradient cooling: Control the cooling fan and waste heat recovery system according to the cooling curve (rate 0.5-1℃ / min) to avoid excessive thermal stress on the furnace lining due to rapid cooling.

[0052] Health assessment: The furnace lining health score is calculated using a die-casting preheating correlation algorithm. The algorithm formula is as follows: Calculate the rate of decrease in thermal insulation performance: Calculate the cumulative thermal stress: in, The total corrected stress for each batch of preheating (calculated by a multi-parameter coupling algorithm). Total preheating time (s).

[0053] Health rating: in, The yield strength of the furnace lining material (e.g., 300 MPa). This is the stress accumulation threshold coefficient (derived from 10,000 batches of preheating life experiments).

[0054] The maintenance recommendation rules are as follows: The heat loss rate is calculated using the following formula: in, This refers to the effective power used for preheating, specifically the power used to raise the temperature. in, To dissipate heat and reduce power loss due to radiation, This represents the total input power of the heat source.

[0055] Thermal insulation efficiency is calculated using the following formula: in, Indicates the heat loss rate. This indicates the current insulation efficiency.

[0056] The rate of decrease in thermal insulation performance is calculated using the following formula: in, This refers to the initial insulation efficiency of the furnace lining.

[0057] Health score > 60: Normal use, no maintenance required.

[0058] 40 points < Health score ≤ 60 points: It is recommended to repair the furnace lining locally (such as applying high-temperature resistant ceramic adhesive to the cracks in the inner wall).

[0059] Health score ≤ 40: It is recommended to replace the entire furnace lining to avoid sudden damage during production.

[0060] Data update: Upload the temperature, stress, and energy consumption data of this preheating to the digital twin model and update the material parameters (e.g., if the thermal conductivity decreases by 5% due to aging, it will be corrected to 1.425W / (m・℃) in the model).

[0061] The formula used to correct for discrepancies between the simulation results of the temperature and stress fields is as follows: Temperature field correction: Where N represents the number of historical die-casting batches. The measured temperature (°C) of the contact zone of the molten metal in the i-th batch. Let be the initial simulation temperature (°C) for the i-th batch. The initial simulation temperature (°C) for the current batch is used, and the corrected simulation deviation is ≤3%.

[0062] Stress field correction: Where n is the number of preheating cycles, The measured stress (MPa) is the stress during the nth preheating. The initial simulated stress (MPa) for the nth preheating. The initial simulation stress (MPa) for the current batch. The total fatigue life of the furnace lining material. For the remaining lifetime, the corrected lifetime prediction error is ≤10%.

[0063] The furnace lining material-heat flux adaptation algorithm is used to dynamically adjust the thermal conductivity of the functional graded material (FGM) and the latent heat release rate of the PCM, as shown in the following formula: Temperature difference data collection: (Temperature difference between inside and outside the furnace lining, °C), sampling frequency 1Hz; Adjustment of thermal conductivity: When the temperature exceeds 15℃ (too large a temperature difference): When <5℃ (temperature difference is too small): in, The reference thermal conductivity of the inner layer of FGM is given. The reference thermal conductivity is the outer layer of the FGM.

[0064] PCM latent heat release rate adjustment: When >15℃: When <5℃: in, The PCM reference latent heat release rate.

[0065] A multi-parameter coupled algorithm for furnace lining thermal stress is used to calculate the total corrected thermal stress, as shown in the following formula: Basic thermal stress: Where E is the elastic modulus of the furnace lining (70~90GPa). The coefficient of thermal expansion is (8~10×10⁻) 6 / ℃), The temperature difference (°C) between the inside and outside of the furnace lining.

[0066] Correction factor calculation: Preheating frequency correction factor: in This is the floor function. This is the preheating frequency correction factor, where n is the total number of preheating cycles completed for the furnace lining. Furnace lining aging coefficient: in This refers to the cumulative actual number of working days since the furnace lining was installed.

[0067] Total corrected thermal stress: Warning rules: when ≥0.7× Reduce the heating rate by 20% to 30% and trigger a Level 1 warning; when ≥0.9× : Pause preheating and trigger a level 2 warning; prediction error ≤ 8%.

[0068] The preheating-die-casting closed-loop interaction algorithm is used to optimize the linkage between preheating and die-casting machines. The formula is as follows: The time matching degree is used to evaluate the synchronization between the preheating completion time and the die-casting machine start-up time. The calculation formula is a piecewise function: in, This indicates the time it takes for the preheating system to complete the entire preheating process; This indicates the actual start time of the die-casting machine; when M t ≥0% (when the time difference exceeds 15 minutes, M) t Set the value to 0%, triggering a forced recalculation of the preheating curve.

[0069] Temperature matching degree is used to evaluate the consistency between the actual temperature of the melt and the temperature required by the die-casting process. The calculation formula is a piecewise function: in, This indicates the temperature at the center of the melt as measured by an infrared thermometer after preheating, in °C, with a precision of [missing information]. This indicates the process temperature determined based on the material of the die-cast product; constraints: ≥0% When the temperature difference exceeds 10℃, take 0% to trigger the melt reheating process.

[0070] The overall matching degree takes into account the weights of time and temperature (time weight 0.6, temperature weight 0.4, set based on the actual need in die-casting production to prioritize time synchronization over small temperature deviations), and the calculation formula is as follows: The adjustment rules are as follows: when ≥90%: Maintain current preheating parameters; When 70%≤ <90%: Fine-tune the parameters for the next batch (if the time difference is too large, advance / delay the preheating start by 5-10 minutes; if the temperature difference is too large, correct the target temperature by ±2-3℃). when <70%: Reactivate the preheating curve generation algorithm to reduce die casting production waiting time by more than 20%.

[0071] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0072] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A preheating system for a holding furnace used in die casting production, characterized in that: include: The sensing layer includes K-type thermocouples and micro-strain sensors arranged on the inner wall, outer wall and middle layer of the die-casting heat preservation furnace lining, a non-contact infrared thermometer set in the center of the furnace, and flow sensors and power sensors respectively installed in the waste heat recovery fluid circuit and the heat source power supply circuit. The execution layer includes at least three partitioned composite heat source modules distributed along the furnace body axis, and two-stage waste heat recovery modules connected in series. The partitioned composite heat source modules include medium-frequency electromagnetic induction coils, infrared radiation tubes, and cooling fans. The two-stage waste heat recovery modules include a high-temperature section finned copper heat exchanger and a combination of a medium-temperature section spiral tube heat exchanger and a phase change material PCM heat storage tank. The control layer includes a digital twin model and an AI predictive control unit that match the die-casting production process; the digital twin model integrates multi-physics simulation of temperature field, stress field and flow field; the AI ​​predictive control unit includes a preheating curve generation module that is linked to the start and stop of the die-casting machine, a furnace lining thermal stress prediction module and a model self-optimization module; The application layer includes a local control unit with functions such as temperature field visualization, energy consumption statistics, furnace lining health assessment and fault alarm, as well as a factory-level interface that supports data interaction with the die-casting plant's MES system.

2. A method for preheating a holding furnace in die-casting production, characterized in that: Based on the preheating system described in claim 1, the preheating method includes the following steps: S1: System initialization, complete sensor calibration and testing, digital twin model parameter initialization and loading, and heating unit communication link testing. According to the furnace lining type, call the material database and generate a multi-segment heating rate curve by combining the die-casting machine start-up time and electricity price peak and valley periods. S2: Coordinated preheating, controlling the medium frequency electromagnetic induction coil to operate stably at the preset initial power, and using infrared radiation tubes to dynamically compensate for the temperature difference in each zone of the furnace in real time, and triggering the start of the two-stage waste heat recovery modules according to the furnace temperature change, so as to realize the coordinated operation of heat source supply and waste heat recovery. S3: Constant temperature maintenance. When the furnace temperature fluctuation exceeds the ±2℃ threshold, the output power of each heat source module is automatically adjusted. At the same time, the PCM heat storage tank is controlled to release heat and control the temperature as needed. Simultaneously, the furnace lining stress state is monitored in real time through micro-strain sensors, and key parameter data during the preheating process are fully recorded. S4: Cooling maintenance. The cooling process is smoothly controlled according to the preset gradient cooling curve. Based on the thermal stress accumulation data during the entire preheating cycle, the quantitative score of furnace lining health is updated, and targeted maintenance suggestions are output to achieve precise management of furnace lining operation and maintenance.

3. The preheating method for a holding furnace in die-casting production according to claim 2, characterized in that: The partitioned composite heat source module is configured with a power complementary linkage algorithm, specifically: the AI ​​predictive control unit collects the temperature difference ΔTᵢ between the inside and outside of the i-th partition detected by the K-type thermocouple every 2 seconds, where ΔTᵢ is: When ΔTᵢ≤8℃, maintain the initial power P of the intermediate frequency electromagnetic induction coil. 电磁0 With the initial power P of the infrared radiator 红外0 When ΔTᵢ>8℃, follow P 电磁新 =P 电磁0 ×(1-k1), P infrared new = P infrared 0 × (1+k2) adjust power, where k1 is 0.1~0.15 and k2 is 0.2~0.25; If ΔTᵢ is still greater than 8℃ after adjustment, then proceed according to P. 电磁迭代 =P 电磁新 ×(1-0.5k1), P 红外迭代 =P 红外新 ×(1+0.5k2) iterative correction until ΔTᵢ≤8℃, controlling the radial temperature gradient in the contact area of ​​the die-casting melt within ±2℃.

4. The preheating method for a holding furnace in die-casting production according to claim 3, characterized in that: The two-stage waste heat recovery module is configured with an intermittent heat buffering algorithm, specifically: when the exhaust gas temperature T at the outlet of the intermediate temperature section heat exchanger... 余热 When the phase transition temperature of PCM is ≥, the recoverable heat Q is calculated using the formula: in, For the specific heat capacity of the exhaust gas, For the quality of exhaust gas, ; The exhaust gas mass flow rate is expressed in kg / s. For the recovery time, The outlet exhaust gas temperature of the medium-temperature section heat exchanger. The phase transition temperature of the PCM; like ≤PCM maximum heat storage If the heat is fully recoverable, all recoverable heat will be stored in the PCM heat storage tank; otherwise, it will be stored in the PCM heat storage tank first. After reaching the PCM heat storage tank, the remaining heat is used to heat the circulating water; during the die-casting interval, the furnace lining temperature... Calculate the required additional heat when the temperature is <300℃. Specifically: in, For the specific heat capacity of the furnace lining, For the quality of the furnace lining, This refers to the furnace lining temperature during the intermittent period. like ≤PCM thermal storage tank residual heat storage Then the heat release from the PCM will meet the heat replenishment requirement. > Heat is first released through the PCM heat storage tank. The insufficient portion is supplemented by an auxiliary electric heating module, thereby effectively reducing the energy consumption cost of the first preheating after the interval period.

5. A preheating method for a holding furnace in die-casting production according to claim 4, characterized in that: The digital twin model is configured with a dynamic correction algorithm for die-casting conditions. Specifically, in the temperature field simulation, a heat loss coefficient of the molten contact zone based on N batches of historical die-casting data is introduced. Specifically: in, Temperature of the molten metal contact zone detected by an infrared thermometer Let the initial simulation temperature be the temperature of the i-th batch of digital twin models, and then... Correcting the temperature field; In the stress field simulation process, a preheating frequency correction coefficient is introduced. Specifically: Where n is the number of times it has been preheated, The actual stress value detected by the micro-strain sensor during the nth preheating. The initial simulation stress value of the digital twin model during the nth preheating is given, and it is calculated according to... The stress field simulation results were corrected, and the remaining life of the furnace lining was calculated by combining the material σ-N curve. Ntotal represents the total fatigue life of the material, used to reduce life prediction errors.

6. The preheating method for a holding furnace in die-casting production according to claim 5, characterized in that: The furnace lining is a composite structure of functionally graded material (FGM) and phase change material (PCM) microcapsules. A material-heat flux adaptation algorithm is configured, and the algorithm executes the following steps: Temperature difference acquisition: The temperature difference ΔT between the inside and outside of the furnace lining is acquired in real time through a K-type thermocouple in the middle layer of the furnace lining, with a sampling frequency of 1Hz, and the real-time power output data of the zoned composite heat source module is acquired simultaneously. Dynamic matching of thermal conductivity coefficient: Based on the gradient characteristics of FGM, when ΔT>15℃, the algorithm automatically increases the thermal conductivity coefficient λ(x) of the inner layer of FGM, while decreasing the thermal conductivity coefficient λ(x) of the outer layer; when ΔT<5℃, the algorithm reverses the adjustment of λ(x), so that the inner layer λ(x) returns to the baseline value and the outer layer λ(x) increases. PCM latent heat release regulation: Combining ΔT and heat source power data, when ΔT>15℃, the algorithm controls the latent heat release rate of PCM microcapsules to increase, helping to smooth the temperature difference; when ΔT<5℃, the latent heat release rate is reduced to avoid excessive heat release leading to temperature fluctuations.

7. A preheating method for a holding furnace in die-casting production according to claim 6, characterized in that: In step S1, the multi-segment heating rate curve is generated using a die-casting production adaptation algorithm, specifically based on the planned start-up time of the die-casting machine. With current time Calculate the total remaining preheating time , according to The total duration has been adjusted to allow for time for temperature stabilization. For safety reasons, the preheating process is divided into low-temperature, medium-temperature, and high-temperature sections; the rate in the medium-temperature section is fixed at 0.8~0.9℃ / min. By reverse-engineering the rates v1 in the low-temperature section and v3 in the high-temperature section, we can ensure that the melt temperature matches the die-casting requirements upon completion of preheating; among which... =(300℃-T 当前 / v1), v2 = 0.8 to 0.9℃ / min, = (T 目标 -800℃) / v3.

8. The preheating method for a holding furnace in die-casting production according to claim 1, characterized in that: In step S2, the monitoring of furnace lining thermal stress is achieved through a multi-parameter coupling algorithm, specifically: first, the basic thermal stress is calculated, as shown in the following formula: Where E is the elastic modulus of the furnace lining, α is the coefficient of thermal expansion, and ΔT is the temperature difference between the inside and outside of the furnace lining; a preheating frequency correction coefficient is then introduced. With furnace lining aging coefficient ,in , Where n is the number of preheating cycles, To round down, t is used as the number of days the furnace lining has been used, calculated as follows: Calculate the total thermal stress; when ≥0.7× When the heating rate is reduced, a level 1 warning is triggered. ≥0.9× : Suspend preheating and trigger a level-two warning to ensure the safety of the furnace lining structure.

9. A preheating method for a holding furnace in die-casting production according to claim 1, characterized in that: The factory-level interface configuration preheating-die-casting closed-loop interaction algorithm is as follows: The preheating completion time t is transmitted to the MES system via the OPC UA protocol. 预热完成 Die casting machine start-up time t 压铸启动 Actual temperature of the melt T 熔液实际 With the required temperature T 熔液要求 The time matching degree Mt is calculated as follows: When |t 预热完成 -t 压铸启动 When Mt is ≤5 min, Mt = 100%; for every 1 min exceeding 5 min, Mt decreases by 10%. Calculate the temperature matching degree MT, specifically: when |T 熔液实际 -T 熔液要求 When the temperature is ≤±5℃, MT=100%; for every 1℃ increase above this temperature, MT decreases by 20%. Press M 综合 =0.6Mt+0.4MT to calculate the overall matching degree: when M 综合 Maintain parameters when ≥90%, and ≤70% for M. 综合 If <90%, adjust the preheating start time or target temperature for the next batch. 综合 When the temperature drops below 70%, the preheating curve algorithm is reactivated to reduce the waiting time in die casting production.

10. A preheating method for a holding furnace in die-casting production according to claim 1, characterized in that: In step S4, the furnace lining health score is calculated using a die-casting preheating correlation algorithm, specifically as follows: First, calculate the heat loss rate as 1 - (P). 有效 / P 总输入 ) Calculate the heat loss of the furnace lining, where P 有效 P is the effective preheating power, i.e., the power actually used to raise the furnace temperature; 总输入 This represents the total input power of the heat source. Then, according to the rate of decrease in thermal insulation performance = (η) 初始 -η 当前 ) / η 初始 Calculate the degree of thermal insulation performance degradation by multiplying by 100%; where P 有效 For preheating effective power, P 总输入 For the total input power, η 初始 For initial insulation efficiency, η 当前 =1 - heat loss rate; Then press health = 100 - (σ) 累计 / (σ 屈服 ×10 4 The quantification score is calculated as (σ × 50) - (insulation performance degradation rate × 50), where σ 累计 For each batch of preheating process σ 总修正 The integral value changes with the preheating time; when the health score is >60, it can be used normally and the furnace lining can be used normally. When the health score is 40 < and the furnace lining is ≤60, it is recommended to repair the furnace lining locally. When the health score is ≤40, it is recommended to replace the entire furnace lining. This achieves precise maintenance related to the preheating frequency of die casting.

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