Isolation heat dissipation control method and system for high-low temperature magnetic drive pump

Abstract

The invention discloses an isolation heat dissipation control method and system of a high-low temperature magnetic drive pump, and relates to the technical field of heat dissipation control of magnetic drive pumps, and the method comprises the following steps: carrying out physical characteristic analysis on transmission liquid, and establishing a physical characteristic representation space; constructing an over-temperature thermodynamic diagram; and establishing a thermal power-energy consumption relationship of the high-low temperature magnetic drive pump, and performing heat dissipation parameter search on the isolation heat dissipation equipment by combining the overtemperature thermal power diagram and taking minimization of pump operation energy consumption and maximization of liquid transmission performance as multiple targets to obtain a heat dissipation control strategy. According to the method, the technical problems that in the prior art, high-low temperature magnetic drive pump isolation heat dissipation parameter optimization lacks pertinence, and pump operation energy consumption control and liquid transmission performance stability are difficult to consider at the same time are solved, and accurate optimization of high-low temperature magnetic drive pump isolation heat dissipation parameters is achieved; and the operation energy consumption of the pump and the performance stability of liquid transmission are optimized.

Description

Technical Field

[0001] This invention relates to the field of magnetic pump heat dissipation control technology, specifically to a method and system for isolating and controlling the heat dissipation of high and low temperature magnetic pumps. Background Technology

[0002] In industrial production, high and low temperature magnetic drive pumps are widely used in high and low temperature media transfer scenarios in fields such as chemical engineering, refrigeration, and energy due to their characteristics of no shaft seal and low leakage risk. However, the core technical pain points in their operation restrict their effectiveness: on the one hand, the electromagnetic induction between the high-speed rotation of the external magnetic rotor and the isolation sleeve easily generates eddy current heating, and the impeller friction and medium flow resistance inside the pump also generate heat. If heat dissipation is not timely, the temperature of the transferred liquid can easily exceed the suitable range, causing a sudden change in liquid viscosity and a decrease in chemical stability, which in turn affects the transfer efficiency and may even damage the pump components. On the other hand, existing isolation and heat dissipation control schemes mostly adopt fixed power heat dissipation or start-stop control based on a single temperature threshold, lacking precise consideration of the physical characteristics of the transferred liquid and the thermal differences in different areas inside the pump, and cannot meet the dual requirements of magnetic drive pump operation stability and energy consumption control under complex working conditions.

[0003] Existing technologies lack targeted optimization of isolation and heat dissipation parameters for high and low temperature magnetic pumps, making it difficult to simultaneously address the technical issues of pump operation energy consumption control and stable liquid transfer performance. Summary of the Invention

[0004] This application provides a method and system for isolating and dissipating heat control of high and low temperature magnetic pumps, which is used to address the technical problem that the optimization of isolation and heat dissipation parameters of high and low temperature magnetic pumps in the prior art is not targeted, and it is difficult to balance the control of pump operation energy consumption and the stability of liquid transfer performance.

[0005] In view of the above problems, this application provides a method and system for isolating and controlling heat dissipation of high and low temperature magnetic pumps.

[0006] The first aspect of this application provides a method for isolating and controlling the heat dissipation of a high and low temperature magnetic pump, the method comprising: The physical properties of the transported liquid are analyzed to establish a physical property characterization space, which includes physical properties, time series, temperature change gradient, and temperature constraint threshold. Based on the physical property characterization space, the overtemperature distribution information of the transported liquid is identified, and an overtemperature thermogram is constructed. The thermodynamic-energy consumption relationship of the high and low temperature magnetic pump is established. Combined with the overtemperature thermogram, the heat dissipation parameters of the isolation and heat dissipation equipment are searched with the multiple objectives of minimizing pump operating energy consumption and maximizing the performance of the transported liquid, and a heat dissipation control strategy is obtained.

[0007] A second aspect of this application provides an isolated heat dissipation control system for high and low temperature magnetic pumps, the system comprising: The characterization space establishment module is used to analyze the physical properties of the transported liquid and establish a physical property characterization space, including physical properties, time series, temperature change gradient, and temperature constraint threshold. The overtemperature thermal map construction module is used to identify the overtemperature distribution information of the transported liquid based on the physical property characterization space and construct an overtemperature thermal map. The control strategy acquisition module is used to establish the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump, and in conjunction with the overtemperature thermal map, to search for heat dissipation parameters of the isolation heat dissipation device with multiple objectives of minimizing pump operating energy consumption and maximizing the performance of the transported liquid, and obtain a heat dissipation control strategy.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: The physical properties of the transported liquid are analyzed to establish a physical property characterization space. Based on this space, the overtemperature distribution information of the transported liquid is identified, and an overtemperature thermogram is constructed. The thermodynamic-energy consumption relationship of the high- and low-temperature magnetic pump is established. Combining this overtemperature thermogram, and with the multiple objectives of minimizing pump operating energy consumption and maximizing transported liquid performance, the heat dissipation parameters of the isolation and heat dissipation equipment are searched to obtain a heat dissipation control strategy. This achieves precise optimization of the isolation and heat dissipation parameters of the high- and low-temperature magnetic pump, improving both pump operating energy consumption and the stability of transported liquid performance. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A schematic flowchart of the isolation and heat dissipation control method for a high and low temperature magnetic pump provided in an embodiment of this application; Figure 2 This is a schematic diagram of the isolation and heat dissipation control system for a high and low temperature magnetic pump provided in an embodiment of this application.

[0011] Figure labeling: Characterization space establishment module 10, superheated thermal map construction module 20, control strategy acquisition module 30. Detailed Implementation

[0012] This application provides a method and system for isolating and controlling the heat dissipation of high and low temperature magnetic pumps, which addresses the technical problem that existing technologies lack targeted optimization of isolation and heat dissipation parameters for high and low temperature magnetic pumps, making it difficult to balance pump operation energy consumption control with stable liquid transfer performance.

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0014] Example 1, as Figure 1 As shown, this application provides an isolation and heat dissipation control method for high and low temperature magnetic pumps, the method comprising: Step S100: Analyze the physical properties of the transported liquid and establish a physical property characterization space, including physical properties, time series, temperature change gradient, and temperature constraint threshold.

[0015] Specifically, for specific liquids transported by high and low temperature magnetic pumps, such as chemical media and coolants, a relationship between temperature and physical properties, namely viscosity, density, and chemical stability, is established. This clarifies the target transport temperature range necessary for the liquid's intended use, such as media transport or heat exchange. For example, a certain coolant needs to be maintained at -20℃ to 50℃ to ensure fluidity and heat dissipation. Then, combining the internal transport channel structure of the magnetic pump, such as the impeller, isolation sleeve, and flow channel dimensions, and the pump's operating state model, such as changes in speed, flow rate, and load, a simulation space for the transport process is constructed. The established temperature-physical property relationship is embedded within this space, and the transport of the liquid within the pump is simulated through simulation. Throughout the process, dynamic changes in physical properties over different time series are acquired, such as viscosity changes over time and temperature gradients, as well as transport simulation features including the rate of temperature rise and fall at different locations within the flow channel. Finally, based on the target transport temperature range, corresponding temperature constraint thresholds are extracted, such as the lower limit threshold of -20℃ and the upper limit threshold of 50℃ for the aforementioned coolant. Temperature data exceeding or approaching these thresholds are marked in the transport simulation features. Ultimately, the four core dimensions of physical properties, time series, temperature gradient, and temperature constraint thresholds are integrated to form a complete physical property characterization space, providing data support for subsequent over-temperature identification and heat dissipation control.

[0016] Step S200: Based on the physical characteristics of the space, identify the overheating distribution information of the transported liquid and construct an overheating thermogram.

[0017] Specifically, based on the physical characteristics of the temperature constraint thresholds defined in the space, such as the upper limit threshold of 50℃ and the lower limit threshold of -20℃ for a certain transported liquid, multiple warning lines are set, such as a mild over-temperature warning line of 45℃ / -15℃ and a severe over-temperature warning line of 48℃ / -18℃, to refine the over-temperature risk level. Subsequently, based on the real-time temperature field data obtained from the transport simulation in the space, which includes temperature values ​​at different time series and different flow channel locations, the temperature is compared with the warning lines one by one according to grid units, such as dividing the flow channel inside the pump into several small grids. The degree of over-temperature in each grid unit is calculated, such as the difference between the actual temperature and the threshold, the duration of over-temperature, such as the duration of temperature exceeding the warning line, and the rate of temperature change, such as the temperature per unit time. The rise / fall amplitude is calculated; then, by weighted fusion of the square root of the over-temperature amplitude, the duration of over-temperature, and the rate of temperature change, the thermal risk index of each grid cell is obtained, and risk levels such as safe zone, observation zone, warning zone, and danger zone are divided accordingly to complete the quantification of over-temperature distribution; finally, according to the spatial location of the temperature field, such as the impeller area inside the pump, the area near the isolation sleeve, the outlet flow channel area, and the temporal relationship, the quantified over-temperature amount, over-temperature time point, and risk level are converted into a visual heat map. The over-temperature distribution state of different areas and times is intuitively presented with color gradients, such as blue representing the safe zone, yellow representing the warning zone, and red representing the danger zone, forming a complete over-temperature heat map that clearly reflects the key over-temperature areas and temporal patterns of the transported liquid inside the pump.

[0018] Step S300: Establish the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump. Combined with the above-temperature thermogram, with the goal of minimizing pump operating energy consumption and maximizing liquid transfer performance, search for heat dissipation parameters of the isolation heat dissipation equipment to obtain a heat dissipation control strategy.

[0019] Specifically, starting from the multiphysics mechanism of magnetic pumps, an electromagnetic-thermal-fluid multiphysics coupling analysis framework is constructed to quantify the correlation between external magnetic rotor parameters and eddy current heating of the isolation sleeve. A fluid-thermal coupling transport model is established to describe the interaction between medium flow and heat transfer, and a mechanical-thermal effect model is used to analyze the impact of thermal deformation on efficiency. After integrating the three models, the energy relationship is coupled to clarify the composition of hydraulic transmission energy consumption, eddy current loss energy consumption, heat dissipation system energy consumption, and performance loss energy consumption. A complete thermodynamic-energy consumption relationship for high and low temperature magnetic pumps is established to evaluate the impact of different thermodynamic states on pump energy consumption. Then, the heat dissipation requirements of different time series and different grid regions are extracted from the over-temperature thermal map, such as the need for high-intensity heat dissipation in the danger zone. The observation area needs to be adequately cooled. By combining the thermodynamic-energy consumption relationship, the energy consumption data of each dimension under the corresponding time series are calculated to construct the energy consumption time series curve. Finally, with the dual objectives of minimizing pump operating energy consumption and maximizing the performance of the transferred liquid, the heat dissipation priority is configured according to the risk level reflected by the over-temperature thermogram. The dangerous area is given priority to ensure temperature stability, and the safe area is given priority to save energy. Energy saving target weights are assigned to different priority time series. The energy saving weight is reduced for high priority time series and increased for low priority time series. Based on the weights, an evaluation function is constructed to search for parameters such as the heat dissipation power, start and stop timing, and heat dissipation area coverage of the isolation heat dissipation equipment. The parameter combination with the optimal energy consumption evaluation and the ability to maintain the performance of the transferred liquid is selected to form the final heat dissipation control strategy.

[0020] In one possible implementation, step S100 further includes: Step S110: Establish the temperature-physical property relationship of the transported liquid and determine the target transport temperature, which is the temperature range required to maintain the physical properties of the transported liquid.

[0021] Step S120: Construct a simulation space according to the pump internal transmission structure and pump operation state model, and embed the temperature-physical property relationship into the simulation space to simulate the transmission process of the liquid and obtain transmission simulation characteristics, including the physical property changes and temperature gradient changes corresponding to the transmission time series.

[0022] Step S130: Extract the temperature constraint threshold according to the target transmission temperature, mark the temperature constraint threshold in the transmission simulation feature, and establish the physical characteristic characterization space.

[0023] Specifically, for specific liquids transported by high and low temperature magnetic pumps, such as corrosive media in chemical production, coolants in refrigeration systems, and heat transfer oils in energy transmission, physical property data of the liquid under different temperature conditions are obtained through experimental testing or industry database queries. These data include, but are not limited to, viscosity, density, thermal conductivity, and chemical stability. Based on this data, a model of the correspondence between temperature and physical properties is established. For example, the viscosity of a certain coolant is stable at 5~8 mPa·s in the range of -30℃ to 40℃, and the viscosity increases or decreases sharply outside this range. Then, combined with the intended use of the liquid, such as ensuring efficient heat dissipation and smooth pipeline transmission for coolants, and avoiding the aggravation of equipment corrosion due to temperature changes for corrosive media, a temperature range that can maintain its core physical properties and meet the usage requirements is selected and determined as the target transmission temperature. For example, the target transmission temperature of the aforementioned coolant is set to -25℃ to 35℃, ensuring that the liquid always has the appropriate physical properties during the magnetic pump transmission process.

[0024] Based on the actual internal transmission structure parameters of the high and low temperature magnetic pump, such as the flow channel diameter, the number and angle of impeller blades, the thickness and material of the isolation sleeve, and the layout of the inlet and outlet pipelines, and combined with a pre-set pump operating state model covering operating parameters such as speed, inlet and outlet pressure, and flow fluctuation range under different working conditions, a transmission process simulation space highly matched to the actual pump body is constructed in a simulation platform, such as CFD fluid simulation software. Then, the established temperature-physical property relationship of the transmitted liquid, such as the correlation model between temperature and viscosity and density, is embedded into this simulation space to ensure the regularity of the liquid's physical properties changing with temperature during the simulation process. Consistent with reality; then the simulation was started to simulate the complete transmission process of liquid from the pump inlet, through the impeller acceleration, through the isolation sleeve area, and finally out of the outlet. Data was collected and recorded in real time during the simulation, and the transmission simulation characteristics were finally obtained, including the changes in physical properties corresponding to the transmission time series, such as the viscosity curve of the liquid with the flow channel temperature during different time periods such as 0~0s and 10~20s, the temperature gradient changes, such as the temperature difference between the impeller area and the outlet pipe area, and the temperature rise and fall rate per unit length of the flow channel, etc., to provide dynamic data support for the subsequent construction of the physical property characterization space.

[0025] Based on a defined target transfer temperature, such as -10℃ to 60℃ for a certain heat transfer oil, corresponding temperature constraint thresholds are extracted. Typically, the upper and lower limits of the target temperature range are directly set as core constraint thresholds, i.e., a lower limit of -10℃ and an upper limit of 60℃. If the liquid is sensitive to temperature fluctuations, additional warning boundaries approaching the thresholds can be set, such as -12℃ and 62℃. Next, based on the acquired transfer simulation characteristics, including time-series data on changes in physical properties and temperature gradient changes, key data points exceeding or approaching the temperature constraint thresholds are screened and marked. For example, in the temperature gradient change data, a region in the flow channel where the temperature rises to 61℃ is marked. The system records the time points and corresponding locations when the temperature approaches the upper threshold, drops to -11℃ at a certain time, and approaches the lower threshold. It also records the physical properties of the liquid at these threshold points, such as the change in thermal conductivity of the heat transfer oil at 61℃ and the viscosity fluctuation at -11℃. Finally, the labeled transmission simulation features are integrated with the initial temperature-physical property relationship, target transmission temperature, and temperature constraint threshold to construct a physical property characterization space containing four core dimensions: "physical properties, time series, temperature change gradient, and temperature constraint threshold". This fully presents the property changes and temperature constraint boundaries of the transmission liquid during the transmission process in the pump, providing a structured data foundation for subsequent over-temperature identification.

[0026] In one possible implementation, step S200 further includes: Step S210: In the physical property characterization space, set upper and lower baselines based on the temperature constraint threshold, determine the temperature change data for over-temperature, and mark the over-temperature amount and over-temperature time point of the over-temperature data according to the time sequence.

[0027] Step S220: Perform heat map conversion according to the marked over-temperature amount and the distribution of over-temperature time points to construct the over-temperature heat map.

[0028] Specifically, within the constructed physical property characterization space, upper and lower baselines are set based on extracted temperature constraint thresholds, such as the lower limit threshold of -20℃ and the upper limit threshold of 50℃ for a certain transported liquid. Simultaneously, multiple warning baselines can be added according to the liquid's temperature sensitivity, such as a mild warning line of -18℃ / 48℃ and a severe warning line of -19℃ / 49℃. Then, temperature change data across all time series within the characterization space is compared with the baselines to determine over-temperature. For example, a temperature of 48℃ is considered mild over-temperature, 49℃ is considered severe over-temperature, and below -19℃ is considered low-temperature over-temperature. For data determined to be over-temperature, the over-temperature amount is further recorded and marked, such as the difference between the actual temperature and the baseline (49℃ corresponds to a severe over-temperature amount of 1℃) and the over-temperature time point (e.g., mild over-temperature first appears in the channel outlet area at 15 seconds of transport). This establishes a correlation between over-temperature data and time and spatial location.

[0029] The marked overtemperature amount and overtemperature time point data are matched with the spatial grid of the pump's internal transmission structure, such as grid cells divided by impeller, isolation sleeve, and outlet pipe, to clarify the overtemperature state of each grid cell at different time points. Then, a color mapping rule is set according to the magnitude of the overtemperature, such as yellow for mild overtemperature, red for severe overtemperature, and dark blue for low-temperature overtemperature. Combined with the temporal distribution of overtemperature time points, the discrete overtemperature data is converted into a continuous visual heat map. The heat map can present the overtemperature distribution of various regions in the pump at a specific time point, such as the grid cells near the isolation sleeve showing red (severe overtemperature) and the inlet area showing blue (safe state). It can also display the changing trend of the overtemperature area through dynamic time-series switching, such as the process of the overtemperature area spreading from the impeller to the outlet pipe. Finally, a complete overtemperature heat map is constructed, which intuitively reflects the key overtemperature areas and temporal patterns of the transmitted liquid in the pump.

[0030] In one possible implementation, step S210 further includes: Step S211: Based on the temperature constraint threshold, set multi-level warning lines.

[0031] Step S212: Based on real-time temperature field data, use the multi-level early warning line to compare the temperature field data for over-temperature, and calculate the degree of over-temperature, duration of over-temperature, and rate of temperature change for each grid cell.

[0032] Step S213: Based on the degree of overheating, duration of overheating and rate of temperature change of each grid cell, perform overheating distribution quantification, and determine the overheating time coordinates according to the time series corresponding to the overheating. Specifically, mark the overheating amount according to the overheating distribution quantification results, and mark the overheating time points according to the overheating time coordinates.

[0033] Specifically, considering the differences in heat dissipation conditions and transported liquid characteristics in different areas within the high and low temperature magnetic pump, such as the high-temperature impeller area, the eddy current heating area of ​​the isolation sleeve, and the low-temperature sensitive areas of the inlet and outlet, the determined temperature constraint thresholds are refined into zone temperature constraint thresholds by region. For example, the upper limit threshold for the impeller area is 55℃, and the upper limit threshold for the inlet and outlet areas is 50℃. Then, based on the zone thresholds, multiple warning lines are set, such as "warning line 52℃, danger line 54℃" for the impeller area, and "warning line 48℃, danger line 50℃" for the inlet and outlet areas, to adapt to the over-temperature risk level requirements of different areas.

[0034] The system acquires real-time temperature field data generated by the transmission simulation in the physical property characterization space. This data covers all preset grid units within the high- and low-temperature magnetic pump, including fine grids divided according to areas such as the flow channel, impeller, and isolation sleeve. It contains the specific temperature values ​​of each grid unit at different transmission time points. Then, based on the set multi-level warning lines for each zone, such as "warning line 52℃, danger line 54℃" for the impeller zone and "warning line 48℃, danger line 50℃" for the inlet and outlet zones, the real-time temperature of each grid unit is compared with the warning line of its corresponding area to determine whether the temperature exceeds the warning line and the corresponding warning level. For example, if the temperature of a certain grid in the impeller zone is 53℃, it is determined to exceed the warning line but not reach the danger level. The system first identifies the overheating threshold; then, for grid cells determined to be overheating, it calculates three core parameters: overheating degree, i.e., the difference between the actual temperature and the corresponding warning line, such as 1℃ for a temperature of 53℃ and the impeller area warning line of 52℃; overheating duration, i.e., the cumulative duration for which the temperature of the grid cell remains above the corresponding warning line, such as 8 seconds for continuous overheating from the 10th to the 18th second of transmission; and temperature change rate, i.e., the rate of temperature increase or decrease per unit time, such as a rate of 1℃ / s for a temperature of 51℃ at 10 seconds and 53℃ at 12 seconds. This allows for the quantitative decomposition of the overheating state of each grid cell, providing a data foundation for subsequent overheating distribution quantification and time stamping.

[0035] For each grid cell, a weighted fusion algorithm is used to process the degree and duration of overheating. The square root is taken to balance the weight of prolonged slight overheating with the rate of temperature change, resulting in a thermal risk index that comprehensively reflects the risk of overheating. Based on the index value range, the overheating distribution is quantified into four levels: safe, observation, warning, and danger. For example, an index below 0.2 is considered safe, and above 0.8 is considered dangerous. Each grid cell is then marked with the amount of overheating based on the quantification level, such as "high overheating" for the danger level and "medium overheating" for the warning level. Simultaneously, the time nodes of the first occurrence of overheating, the upgrade / downgrade of overheating level, and the end of overheating in each grid cell are extracted. These nodes are precisely correlated with the time series of the transmission process to determine the overheating time coordinates, such as "transmission from 15s to 22s, grid B in the isolation sleeve area is at the warning level of overheating, and after 22s it is downgraded to the observation level." The start, change, and end times of overheating in each grid cell are marked with overheating time points according to the coordinates, ultimately forming an overheating data system that combines the quantification degree of overheating with time series information, providing refined data support for the subsequent construction of overheating heat maps.

[0036] In one possible implementation, step S213 further includes: Step S2131: Weight and fuse the overheating amplitude, the square root of the overheating duration, and the temperature change rate to obtain the thermal risk index of each grid cell.

[0037] Step S2132: Divide the risk into multiple risk levels based on the range of thermal risk index values, including safe zone, observation zone, warning zone and danger zone.

[0038] Step S2133: Using the risk level and the corresponding thermal risk index, generate the overtemperature quantification result of the overtemperature distribution.

[0039] Specifically, for each grid cell, three core parameters are selected: overtemperature amplitude, the square root of overtemperature duration, and the rate of temperature change. Based on the operational requirements of the high and low temperature magnetic pump, if it is more sensitive to rapid heating, the weight of the rate of temperature change is increased and different weights are assigned to each parameter. For example, the weight of overtemperature amplitude is 0.4, the weight of the square root of overtemperature duration is 0.3, and the weight of the rate of temperature change is 0.3. The thermal risk index of each grid cell is calculated through the weighted summation formula, namely, thermal risk index = overtemperature amplitude × 0.4 + √(overtemperature duration × 0.3) + temperature change rate × 0.3, so as to achieve comprehensive quantification of the overtemperature state.

[0040] Next, based on the characteristics of the liquid being transferred and the safety operating standards of the magnetic pump, a range of thermal risk index values ​​is set to classify risk levels: for example, an index of 0 to 0.2 corresponds to the safe zone, meaning there is no risk of overheating and the temperature is stable within the target range; 0.2 to 0.4 corresponds to the observation zone, meaning there is slight overheating or the temperature is close to the warning line and continuous monitoring is required; 0.4 to 0.8 corresponds to the warning zone, meaning there is significant overheating and heat dissipation control is required; and above 0.8 corresponds to the danger zone, meaning there is severe overheating and powerful heat dissipation needs to be activated immediately, ensuring that the classification of levels accurately matches the actual overheating risk.

[0041] Finally, the thermal risk index of each grid cell is associated with its corresponding risk level to generate a quantitative result of the overheating distribution. This result includes the location information of the grid cell, such as the impeller area grid and the isolation sleeve grid, the corresponding thermal risk index value, such as 0.65, and the corresponding risk level, such as the warning zone. The specific composition of the overheating parameters of the grid cell is also marked, such as the overheating amplitude of 1.5℃, the overheating duration of 4s, and the temperature change rate of 0.8℃ / s. This forms structured quantitative data of overheating, providing a clear quantitative basis for the subsequent construction of overheating thermal maps and the formulation of heat dissipation strategies.

[0042] In one possible implementation, step S300 further includes: Step S310: Construct an electromagnetic-thermal-fluid multiphysics coupling analysis framework to quantify the correlation between the operating parameters of the external magnetic rotor and the eddy current heating of the isolation sleeve.

[0043] Step S320: Establish a flow-heat coupled transport model to describe the interaction mechanism between the flow of the medium and the heat transfer in the pump, and identify the influence of the high-temperature zone on the fluid viscosity and flow resistance.

[0044] Step S330: Construct a mechanical-thermal effect model to analyze the impact of thermal deformation on operating efficiency.

[0045] Step S340: Integrate the electromagnetic-thermal-fluid multiphysics field coupling analysis framework, the fluid-thermal coupling transport model, and the mechanical-thermal effect model to conduct energy relationship coupling effects and construct the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump, including hydraulic transmission energy consumption, eddy current loss energy consumption, heat dissipation system energy consumption, and performance loss energy consumption, to evaluate the influence of thermodynamic state on pump energy consumption.

[0046] Specifically, this study addresses the electromagnetic drive and heat generation mechanisms of high- and low-temperature magnetic pumps by integrating three major modules: electromagnetic simulation, heat conduction analysis, and fluid flow simulation. This forms a multiphysics coupled analysis framework encompassing electromagnetic, thermal, and fluid dynamics. The electromagnetic module, based on Maxwell's equations, simulates the magnetic field distribution and electromagnetic induction intensity of the external magnetic rotor under different operating parameters, such as rotational speed, input current, and magnetic field frequency. The thermal module, combining Fourier's law of heat conduction, calculates the eddy current density generated by the isolation sleeve under electromagnetic induction, thereby deriving the eddy current heating power and heat distribution. The fluid module simulates the flow state of the liquid transported within the pump, analyzing the effect of liquid flow on the heat transfer of the isolation sleeve. The effect of eddy currents is used to couple energy and physical quantities between electromagnetic, thermal, and fluid forces. For example, eddy current heat is transferred to the liquid through heat conduction, and the liquid flow in turn affects the temperature distribution of the isolation sleeve. Based on this framework, multiple sets of simulation experiments are conducted by controlling variables, such as fixing the magnetic field frequency and changing the speed of the external magnetic rotor. Data such as the eddy current heating power, heating area, and maximum temperature of the isolation sleeve under different operating parameters are recorded. Finally, the operating parameters of the external magnetic rotor are established and quantified, such as the correspondence between the increase of X% in the eddy current heat generation of the isolation sleeve for every 100 r / min increase in speed and the eddy current heating characteristics of the isolation sleeve, clarifying the generation law and influencing factors of the core heat source.

[0047] Based on computational fluid dynamics (CFD) and heat transfer theory, a flow-heat coupled transport model is constructed. This model first divides the computational grid and sets boundary conditions, such as inlet flow rate, outlet pressure, and wall heat dissipation coefficient, according to the actual flow channel structure of the high and low temperature magnetic pump, such as impeller blade angle, isolation sleeve clearance, and inlet and outlet pipe dimensions. Then, the thermophysical property parameters of the transported liquid are embedded into the model, such as thermal conductivity and specific heat capacity as a function of temperature. At the same time, heat source data such as isolation sleeve eddy current heating and impeller friction heating are associated to realize bidirectional coupled calculation of flow field and thermal field. That is, the flow of medium will drive heat diffusion, and the heat distribution will change the physical properties of the medium, thereby affecting the flow state. Through model simulation, on the one hand, the interaction mechanism between the flow of the medium and the heat transfer in the pump can be clearly described, such as the forced convection heat dissipation effect of high-speed fluid on the surface of the isolation sleeve, and the local temperature rise caused by heat accumulation in the dead zone of the flow channel; on the other hand, the high-temperature zone, such as the influence of the periphery of the isolation sleeve and the vicinity of the impeller hub on the fluid characteristics, can be monitored and quantified. For example, by comparing simulation data at different temperatures, it can be identified that the viscosity of the liquid in the high-temperature zone decreases with the increase of temperature, such as the viscosity decreasing by 20% when the temperature rises from 40℃ to 60℃, which leads to a decrease in flow resistance, or the destructive effect of local vaporization of the liquid on the flow stability under extreme high temperatures. This provides data support for the subsequent construction of the thermodynamic-energy relationship at the flow-heat coupling level.

[0048] This study focuses on key components of high- and low-temperature magnetic pumps, such as impellers, isolation sleeves, pump casings, and bearings. It combines material thermophysical properties, such as coefficients of thermal expansion and elastic moduli, with data on the temperature field distribution within the pump, derived from the thermodynamic results of multiphysics coupling analysis, to construct a mechanical-thermal effect model. This model first simulates the deformation of components due to thermal expansion and contraction under different temperature conditions using a thermal stress calculation module. Examples include the radial expansion of the isolation sleeve at high temperatures and the axial displacement of the impeller due to temperature differences. Then, it combines mechanical dynamics and fluid dynamics theories to analyze the impact of these thermal deformations on the core fit and flow field characteristics within the pump. For instance, the radial expansion of the isolation sleeve reduces the gap between it and the inner magnetic rotor, potentially increasing frictional resistance; axial deformation of the impeller may disrupt the sealing fit with the pump casing, causing fluid backflow; and thermal deformation of the bearings may lead to decreased rotational accuracy and increased mechanical losses. Finally, by comparing pump operating parameters before and after deformation, such as flow rate, head, and shaft power, the efficiency loss caused by thermal deformation is quantified. For example, under certain operating conditions, impeller thermal deformation leads to a 5% decrease in pump hydraulic efficiency and a 3% increase in mechanical loss. The mechanism by which thermal state indirectly affects pump operating efficiency through component deformation is clarified, providing mechanical data support for the subsequent integration and construction of a complete thermodynamic-energy relationship.

[0049] With energy flow and conversion as the core theme, this study deeply integrates an electromagnetic-thermal-fluid multiphysics coupling analysis framework, a fluid-thermal coupling transport model, and a mechanical-thermal effect model. The electromagnetic-thermal-fluid framework provides fundamental data on eddy current loss energy consumption, such as the heat energy loss from eddy current conversion in isolation sleeves. The fluid-thermal coupling model supports the calculation of hydraulic transport energy consumption, such as the energy consumption of the medium overcoming resistance during flow. The mechanical-thermal effect model quantifies performance loss energy consumption, such as the efficiency reduction and additional energy consumption caused by component thermal deformation. Then, through energy coupling algorithms, the study analyzes the mutual influence between different energy consumption types, such as how increased eddy current loss leads to temperature rise, which in turn causes changes in fluid viscosity, indirectly... Increase hydraulic transmission energy consumption; thermal deformation of components caused by high temperature will further aggravate performance loss energy consumption. Clarify the thermal state, such as the quantitative correlation between different over-temperature levels, heat source distribution and various types of energy consumption; finally, construct a high and low temperature magnetic pump thermodynamic-energy consumption relationship covering hydraulic transmission energy consumption, i.e., core energy consumption of medium transportation, eddy current loss energy consumption, i.e. key electromagnetic induction loss, heat dissipation system energy consumption, i.e. energy consumption of subsequent heat dissipation equipment operation, and performance loss energy consumption, i.e. additional losses caused by thermal deformation, etc. This relationship can intuitively reflect the composition and change law of the pump's total energy consumption under different thermal states, and provide a quantitative evaluation basis for subsequent optimization of heat dissipation parameters and balancing energy consumption and heat dissipation effect by combining over-temperature thermograms.

[0050] In one possible implementation, step S300 further includes: Step S350: Extract the time-series heat dissipation requirements based on the aforementioned overheat thermal map.

[0051] Step S360: Based on the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump, and combined with the pump operating parameters for the time-series heat dissipation demand, perform energy consumption calculations in various dimensions to construct an energy consumption time-series curve.

[0052] Step S370: With the goal of minimizing the energy consumption of the high and low temperature pump and with the constraints of maintaining the target temperature stability and performance of the transported liquid, the heat dissipation parameters are searched according to the energy consumption time series curve to obtain the optimal combination of heat dissipation control parameters based on the energy consumption evaluation results, and the heat dissipation control strategy is generated.

[0053] Specifically, based on the spatial over-temperature distribution presented by the over-temperature heat map, such as the danger zone of the isolation sleeve, the warning zone of the impeller, and the time sequence change patterns, such as the expansion of the over-temperature area or the upgrading of the thermal risk level during a certain period, the heat dissipation requirements are broken down according to the time sequence. For example, during the 10th to 15th second of transmission, high-intensity heat dissipation needs to be provided for the danger zone of the isolation sleeve, and during the 15th to 20th second, gradient heat dissipation needs to be taken into account for both the warning zone of the impeller and the isolation sleeve area. At the same time, the heat dissipation priority of each time segment is marked, such as the danger zone corresponding to high priority and the warning zone corresponding to medium priority, forming a time sequence heat dissipation requirement list.

[0054] Next, based on the established thermodynamic-energy consumption relationship, and combined with the current operating parameters of the high and low temperature magnetic pump, such as speed, flow rate, and inlet and outlet pressure, the energy consumption of each dimension is calculated for the heat dissipation target of each time period in the time-series heat dissipation demand, such as reducing the temperature of the danger zone from 55℃ to 50℃. This includes the energy consumption of the heat dissipation system required to meet the heat dissipation target, the change in hydraulic transmission energy consumption during the heat dissipation process, and the fluctuation value of performance loss energy consumption. The total energy consumption data of each time period is integrated in chronological order. Total energy consumption = hydraulic transmission energy consumption + eddy current loss energy consumption + heat dissipation system energy consumption + performance loss energy consumption. An energy consumption time series curve is constructed to intuitively reflect the energy consumption change trend corresponding to meeting the heat dissipation demand in different time periods, such as the energy consumption peak during high-priority heat dissipation periods and the energy consumption trough during low-priority heat dissipation periods.

[0055] With minimizing the total energy consumption of high and low temperature pumps as the core objective, and taking the stability of the target temperature of the transported liquid and the maintenance of liquid performance as constraints, multiple sets of searches and simulations were conducted on key parameters of the isolation and heat dissipation equipment, such as heat dissipation power, heat dissipation area coverage, and start-up and shutdown timing, based on energy consumption time-series curves. For example, the energy consumption and temperature control effect corresponding to 800W and 1000W heat dissipation power were tested for high-priority periods, and the energy consumption difference between intermittent heat dissipation and continuous low-power heat dissipation was tested for low-priority periods. By constructing an evaluation function, the optimal parameter combination for energy consumption evaluation results was selected by considering energy consumption cost, temperature deviation, and performance loss cost. For example, 1000W directional heat dissipation was used for high-priority periods, and 500W intermittent heat dissipation was used for low-priority periods. Finally, a heat dissipation control strategy that takes into account both energy consumption optimization and heat dissipation effect was generated.

[0056] In one possible implementation, step S330 further includes: Step S331: Align the timing heat dissipation requirements with the energy consumption timing curve according to the timing relationship.

[0057] Step S332: Configure the heat dissipation priority for timing heat dissipation requirements based on the target temperature of the liquid being transferred and performance maintenance constraints.

[0058] Step S333: Based on the heat dissipation priority, assign weights to the corresponding time-series energy-saving targets, construct an evaluation function based on the energy-saving weight allocation results, and use it to evaluate the targets in the strategy search and select the best combination of heat dissipation parameters.

[0059] Specifically, based on the transmission time axis, the extracted time-series heat dissipation requirements are precisely aligned with the constructed energy consumption time-series curve to ensure that the heat dissipation requirements of each time period match the energy consumption characteristics of that time period, providing a time-series correlation basis for subsequent targeted optimization.

[0060] Next, based on the target temperature range of the transmitted liquid, such as -20℃ to 50℃, and performance maintenance requirements, such as viscosity stability of 5 to 8 mPa·s, the aligned time-series heat dissipation requirements are prioritized: If over-temperature data shows that the liquid temperature is close to or exceeds the target range during a certain period, such as the temperature in the isolation sleeve area reaching 54℃ in the 10th to 15th second, exceeding the upper limit threshold by 4℃, causing a sharp drop in liquid viscosity and destruction of chemical stability, then the heat dissipation requirement for that period is configured as high priority; if the temperature is only within the warning range during a certain period, such as the temperature in the impeller area reaching 48℃ in the 15th to 20th second, close to the upper limit but not exceeding it, the liquid performance is not affected for the time being, and only continuous monitoring is required, then it is configured as medium priority; if the temperature is within the safe range, such as the temperature in all areas being below 40℃ in the 20th to 25th second, and only basic heat dissipation is required, then it is configured as low priority.

[0061] Finally, weights are assigned to the energy-saving targets for different time periods based on different heat dissipation priorities: For high-priority periods, "ensuring temperature and performance stability" is the primary principle, so the weight of the energy-saving target is reduced, for example, the energy-saving weight is set to 0.3, prioritizing heat dissipation needs; for medium-priority periods, heat dissipation and energy saving are balanced, and the energy-saving weight is set to 0.5; for low-priority periods, "minimizing energy consumption" is the core, and the energy-saving weight is increased to 0.8. Based on this weight allocation, a comprehensive evaluation function is constructed, consisting of weight × energy cost + temperature deviation penalty × penalty coefficient + performance loss cost × cost coefficient. In subsequent heat dissipation parameter searches, this function is used to calculate the evaluation score for each parameter combination, ultimately selecting the optimal parameter combination with the highest score that balances heat dissipation and energy-saving needs across different time periods.

[0062] In one possible implementation, step S333 further includes: When heat dissipation priority is low, energy saving is the primary optimization goal, energy saving targets are given high weight, and temperature control tolerance is relaxed.

[0063] When the heat dissipation priority is medium, balance the energy saving target and the heat dissipation target, and configure the energy saving target with a balanced weight.

[0064] When heat dissipation priority is high, the primary optimization goal is to regulate the temperature of the transported liquid, and the energy-saving target is configured with a low weight.

[0065] Specifically, when the heat dissipation priority is low, the temperature of the liquid being transported in the pump is within a safe range, such as being far below the upper limit of the target temperature or above the lower limit, and there is no risk of fluctuation in the physical properties of the liquid, such as viscosity and chemical stability. In this case, energy saving is the primary optimization goal, and the weight of the energy saving goal is set to the highest, such as 0.8~0.9. At the same time, the temperature control tolerance is appropriately relaxed, such as allowing the temperature to fluctuate within ±3℃~±5℃ within the target range. It is not necessary to strictly maintain it within a fixed range. Low-power heat dissipation modes are preferred, such as intermittent heat dissipation, low-flow heat dissipation medium supply, or extended start-stop intervals of heat dissipation equipment, to minimize the energy consumption of the heat dissipation system and the total energy consumption of the pump. It is only necessary to ensure that the temperature does not exceed the safe boundary.

[0066] When the heat dissipation priority is medium, the corresponding liquid temperature is in the warning range. If it is close to the upper / lower limit of the target temperature but not exceeded, and the physical properties of the liquid fluctuate slightly but do not affect the transmission function, it is necessary to balance the energy-saving target and the heat dissipation target. The weight of the energy-saving target should be configured to a balanced level, such as 0.4~0.6. At the same time, the temperature control tolerance should be tightened, such as reducing the allowable fluctuation range to ±1℃~±2℃. Under the premise of meeting the basic heat dissipation requirements and preventing the temperature from approaching the threshold further, parameters that take into account both energy consumption and heat dissipation effect should be selected, such as medium-power continuous heat dissipation and targeted coverage of the over-temperature risk area, to avoid excessive heat dissipation leading to energy waste and to prevent insufficient heat dissipation from causing risk escalation.

[0067] When heat dissipation priority is high, the corresponding liquid temperature is close to or slightly exceeds the target temperature threshold, or there is a rapid heating / cooling trend, causing drastic changes in the liquid's physical properties, such as a sudden increase / decrease in viscosity or chemical decomposition, affecting transmission safety and pump operation stability. In this case, the primary optimization goal is to regulate the temperature of the transmitted liquid and restore it to a safe state. The weight of the energy-saving target is set to the lowest, such as 0.1~0.3. At the same time, the temperature deviation is strictly controlled, requiring the temperature to be quickly brought back to the target range, with the deviation less than ±1℃. High-intensity heat dissipation schemes are prioritized, such as full-power heat dissipation, increasing the flow rate of the heat dissipation medium, and expanding the coverage of the heat dissipation area. Even if energy consumption increases in the short term, it is necessary to ensure that the temperature is quickly controlled and the liquid performance is stable to avoid the risk of escalating and causing damage to the pump body or transmission process.

[0068] Example 2, based on the same inventive concept as the isolation and heat dissipation control method for the high and low temperature magnetic pump in the foregoing examples, such as... Figure 2 As shown, this application provides an isolated heat dissipation control system for high and low temperature magnetic pumps. The system and method embodiments in this application are based on the same inventive concept. The system includes: The characterization space establishment module 10 is used to analyze the physical properties of the transported liquid and establish a physical property characterization space, which includes physical properties, time series, temperature change gradient, and temperature constraint threshold.

[0069] The supertemperature thermal map construction module 20 is used to characterize the space based on the physical properties, identify the supertemperature distribution information of the transported liquid, and construct a supertemperature thermal map.

[0070] The control strategy acquisition module 30 is used to establish the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump. Combined with the over-temperature thermogram, the module searches for heat dissipation parameters of the isolation heat dissipation device with multiple objectives of minimizing pump operating energy consumption and maximizing liquid transfer performance, and obtains the heat dissipation control strategy.

[0071] Furthermore, the system is also used to implement the following functions: A temperature-physical property relationship for the transported liquid is established, and a target transport temperature is determined. The target transport temperature is the temperature range required to maintain the physical properties of the transported liquid. A simulation space is constructed according to the pump's internal transport structure and pump operating state model, and the temperature-physical property relationship is embedded in the simulation space to simulate the transport process of the transported liquid, obtaining transport simulation features, including changes in physical properties and temperature gradients corresponding to the transport time series. A temperature constraint threshold is extracted based on the target transport temperature, and the temperature constraint threshold is marked in the transport simulation features to establish the physical property characterization space.

[0072] Furthermore, the system is also used to implement the following functions: In the physical property characterization space, upper and lower baselines are set with the temperature constraint threshold, and the temperature change data is judged to exceed the temperature limit. The temperature exceedance data is marked with the temperature exceedance amount and the temperature exceedance time point according to the time sequence relationship. The heat map is converted according to the marked temperature exceedance amount and the distribution of temperature exceedance time points to construct the temperature exceedance heat map.

[0073] Furthermore, the system is also used to implement the following functions: Based on the temperature constraint threshold, a multi-level early warning line is set; based on real-time temperature field data, the temperature field data is compared for over-temperature using the multi-level early warning line, and the degree of over-temperature, duration of over-temperature, and rate of temperature change of each grid cell are calculated; based on the degree of over-temperature, duration of over-temperature, and rate of temperature change of each grid cell, the over-temperature distribution is quantified, and the over-temperature time coordinate is determined according to the time series corresponding to the over-temperature, wherein the over-temperature amount is marked according to the over-temperature distribution quantization result, and the over-temperature time point is marked according to the over-temperature time coordinate.

[0074] Furthermore, the system is also used to implement the following functions: The thermal risk index of each grid cell is obtained by weighting and fusing the square root of the overtemperature amplitude, the overtemperature duration, and the temperature change rate. Multiple risk levels are divided according to the numerical range of the thermal risk index, including safe zone, observation zone, early warning zone, and danger zone. The overtemperature distribution is quantified using the risk level and the corresponding thermal risk index.

[0075] Furthermore, the system is also used to implement the following functions: An electromagnetic-thermal-fluid multiphysics coupling analysis framework was constructed to quantify the correlation between the operating parameters of the external magnetic rotor and the eddy current heating of the isolation sleeve. A fluid-thermal coupling transport model was established to describe the interaction mechanism between the flow of the medium and heat transfer within the pump, and to identify the influence of the high-temperature zone on fluid viscosity and flow resistance. A mechanical-thermal effect model was constructed to analyze the impact of thermal deformation on operating efficiency. The electromagnetic-thermal-fluid multiphysics coupling analysis framework, the fluid-thermal coupling transport model, and the mechanical-thermal effect model were integrated to conduct energy relationship coupling effects and construct the thermodynamic-energy consumption relationship of high and low temperature magnetic pumps, including hydraulic transmission energy consumption, eddy current loss energy consumption, heat dissipation system energy consumption, and performance loss energy consumption, to evaluate the influence of thermodynamic state on pump energy consumption.

[0076] Furthermore, the system is also used to implement the following functions: Based on the ultra-high temperature thermogram, the time-series heat dissipation requirements are extracted; based on the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump, and combined with the pump operating parameters, the time-series heat dissipation requirements are evaluated, and energy consumption calculations are performed in various dimensions to construct an energy consumption time-series curve; with the goal of minimizing the energy consumption of the high and low temperature pump, and with the constraints of maintaining the target temperature stability and performance of the transported liquid, the heat dissipation parameters are searched according to the energy consumption time-series curve to obtain the optimal combination of heat dissipation control parameters for energy consumption evaluation results, and the heat dissipation control strategy is generated.

[0077] Furthermore, the system is also used to implement the following functions: The time-series heat dissipation requirements are aligned with the energy consumption time-series curve according to the time sequence relationship; the heat dissipation priority is configured for the time-series heat dissipation requirements based on the target temperature of the transported liquid and performance maintenance constraints; the energy-saving targets for the corresponding time sequence are weighted based on the heat dissipation priority, and an evaluation function is constructed according to the energy-saving weight allocation result, which is used to evaluate the targets in the strategy search and select the best combination of heat dissipation parameters.

[0078] Furthermore, the system is also used to implement the following functions: When the heat dissipation priority is low, energy saving is the primary optimization goal, and the energy saving goal is configured with a high weight, while the temperature control tolerance is relaxed; when the heat dissipation priority is medium, the energy saving goal and the heat dissipation goal are balanced, and the energy saving goal is configured with a balanced weight; when the heat dissipation priority is high, the regulation of the temperature of the transported liquid is the primary optimization goal, and the energy saving goal is configured with a low weight.

[0079] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0080] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0081] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for isolating and controlling the heat dissipation of a high and low temperature magnetic pump, characterized in that, include: The physical properties of the transported liquid are analyzed, and a physical property characterization space is established, including physical properties, time series, temperature change gradient, and temperature constraint threshold. Based on the physical characteristics of the space, identify the overheating distribution information of the transported liquid and construct an overheating thermogram; The thermodynamic-energy consumption relationship of high and low temperature magnetic pumps is established. Combined with the aforementioned overtemperature thermogram, the heat dissipation parameters of the isolation heat dissipation equipment are searched with the multiple objectives of minimizing pump operating energy consumption and maximizing liquid transfer performance, so as to obtain a heat dissipation control strategy.

2. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 1, characterized in that, The process of analyzing the physical properties of the transported liquid and establishing a physical property characterization space includes: Establish the temperature-physical property relationship of the transported liquid, and determine the target transport temperature, which is the temperature range required to maintain the physical properties of the transported liquid. Based on the pump internal transmission structure and pump operation state model, a simulation space is constructed, and the temperature-physical property relationship is embedded in the simulation space to simulate the transmission process of the transmitted liquid and obtain transmission simulation characteristics, including the physical property changes and temperature gradient changes corresponding to the transmission time series. Based on the target transmission temperature, a temperature constraint threshold is extracted, and the temperature constraint threshold is marked in the transmission simulation features to establish the physical characteristic characterization space.

3. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 2, characterized in that, Based on the physical characteristics characterizing the space, the superheated distribution information of the transported liquid is identified, and a superheated thermal map is constructed, including: In the physical property characterization space, upper and lower baselines are set with the temperature constraint threshold, and the temperature change data is judged to exceed the temperature limit. The temperature exceedance data is marked with the temperature exceedance amount and temperature exceedance time point according to the time sequence relationship. The heat map is constructed by converting the marked over-temperature amount and the distribution of over-temperature time points.

4. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 3, characterized in that, Using the aforementioned temperature constraint threshold to set upper and lower baselines, temperature change data is used to determine over-temperature conditions, and the over-temperature data is marked with over-temperature amount and over-temperature time point according to the time sequence, including: Based on the aforementioned temperature constraint threshold, multiple warning levels are set; Based on real-time temperature field data, the multi-level early warning line is used to compare the temperature field data for over-temperature, and the degree of over-temperature, duration of over-temperature, and rate of temperature change of each grid cell are calculated. Based on the degree of overheating, duration of overheating, and rate of temperature change of each grid cell, the overheating distribution is quantified, and the overheating time coordinates are determined according to the time series corresponding to the overheating. Specifically, the overheating amount is marked according to the overheating distribution quantization results, and the overheating time point is marked according to the overheating time coordinates.

5. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 4, characterized in that, The quantification of overheat distribution based on the overheating degree, overheating duration, and temperature change rate of each grid cell includes: The thermal risk index of each grid cell is obtained by weighting and fusing the square root of the overheating amplitude, the overheating duration, and the temperature change rate. Based on the range of thermal risk index values, multiple risk levels are divided, including safe zone, observation zone, warning zone, and danger zone; By utilizing the risk level and the corresponding thermal risk index, the overtemperature distribution is quantified.

6. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 1, characterized in that, Establish the thermodynamic-energy consumption relationship of high and low temperature magnetic pumps, including: An electromagnetic-thermal-fluid multiphysics coupling analysis framework was constructed to quantify the correlation between the operating parameters of the external magnetic rotor and the eddy current heating of the isolation sleeve; A flow-heat coupled transport model was established to describe the interaction mechanism between the medium flow and heat transfer within the pump, and to identify the influence of the high-temperature zone on fluid viscosity and flow resistance. A mechanical-thermal effect model was constructed to analyze the impact of thermal deformation on operating efficiency; An integrated electromagnetic-thermal-fluid multiphysics field coupling analysis framework, a fluid-thermal coupling transport model, and a mechanical-thermal effect model are used to investigate the energy relationship coupling effect and construct the thermodynamic-energy consumption relationship of high and low temperature magnetic pumps, including hydraulic transmission energy consumption, eddy current loss energy consumption, heat dissipation system energy consumption, and performance loss energy consumption, which are used to evaluate the influence of thermodynamic state on pump energy consumption.

7. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 6, characterized in that, Obtain heat dissipation control strategies, including: Based on the aforementioned over-temperature thermal map, extract the time-series heat dissipation requirements; Based on the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump, and combined with the pump operating parameters, the energy consumption is calculated in various dimensions to construct the energy consumption time series curve. With the goal of minimizing the energy consumption of the high and low temperature pumps and the constraints of maintaining the target temperature stability and performance of the transported liquid, the heat dissipation parameters are searched based on the energy consumption time series curve to obtain the optimal combination of heat dissipation control parameters for energy consumption evaluation, and the heat dissipation control strategy is generated.

8. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 7, characterized in that, With the goal of minimizing the energy consumption of high and low temperature pumps, and constrained by maintaining the target temperature stability and performance of the transferred liquid, a search for heat dissipation parameters is performed based on the energy consumption time series curve, including: Align the timing-series heat dissipation requirements with the energy consumption timing curve according to the timing relationship; Prioritize heat dissipation requirements based on the target temperature of the liquid being transferred and performance maintenance constraints; Based on heat dissipation priority, energy-saving targets corresponding to the time sequence are weighted and assigned. An evaluation function is constructed based on the energy-saving weight assignment results and used to evaluate the targets in the strategy search and select the best combination of heat dissipation parameters.

9. The isolation and heat dissipation control method for high and low temperature magnetic pumps according to claim 8, characterized in that, Based on heat dissipation priority, energy-saving targets corresponding to the time sequence are weighted and allocated, including: When heat dissipation priority is low, energy saving is the primary optimization goal, energy saving targets are assigned a high weight, and temperature control tolerance is relaxed. When the heat dissipation priority is medium, balance the energy saving target and the heat dissipation target, and configure the energy saving target with a balanced weight. When heat dissipation priority is high, the primary optimization goal is to regulate the temperature of the transported liquid, and the energy-saving target is configured with a low weight.

10. An isolation and heat dissipation control system for a high and low temperature magnetic pump, characterized in that, The system is used to implement the isolation and heat dissipation control method for a high and low temperature magnetic pump according to any one of claims 1-9, the system comprising: The characterization space establishment module is used to analyze the physical properties of the transported liquid and establish a physical property characterization space, which includes physical properties, time series, temperature change gradient, and temperature constraint threshold. The superheated thermal map construction module is used to characterize the space based on the physical properties, identify the superheated distribution information of the transported liquid, and construct a superheated thermal map. The control strategy acquisition module is used to establish the thermodynamic-energy consumption relationship of the high and low temperature magnetic pump. Combined with the over-temperature thermogram, the module searches for heat dissipation parameters of the isolation heat dissipation equipment with multiple objectives of minimizing pump operating energy consumption and maximizing liquid transfer performance, and obtains the heat dissipation control strategy.

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