A rare earth magnet intelligent sintering production line and control system

Abstract

This invention relates to the field of intelligent sintering technology, and discloses an intelligent sintering production line and control system for rare earth magnets. The system includes a temperature data acquisition module, a temperature gradient evaluation module, a temperature change rate fitting module, a heating power adjustment module, a directional thermal energy compensation module, and an optimized heating command generation module. The system acquires temperature distribution information within the sintering furnace; evaluates real-time temperature gradients at different locations within the sintering furnace and compares these real-time temperature gradients with preset gradient thresholds to identify abnormal temperature regions within the sintering furnace; fits the temperature change rate of the abnormal temperature regions; adjusts the heating power of the abnormal temperature regions by combining the material phase transformation critical parameters of the rare earth magnets at the current sintering stage; performs directional thermal energy compensation on the abnormal temperature regions to obtain a power compensation amount; and superimposes the power compensation amount with the reference power of the sintering furnace to generate optimized heating commands. This invention can improve the intelligent sintering control efficiency of rare earth magnets.

Description

Technical Field

[0001] This invention relates to the field of sintering temperature control technology, and in particular to an intelligent sintering production line and control system for rare earth magnets. Background Technology

[0002] In the field of rare earth magnet sintering temperature control technology, traditional sintering control systems lack effective data purification mechanisms in the temperature data acquisition stage, making them susceptible to interference and unable to generate accurate temperature distribution information reflecting the magnet's heating environment. Furthermore, the methods for assessing the temperature gradient within the sintering furnace are relatively simplistic, failing to comprehensively correlate position coordinates with temperature values. This results in inaccurate real-time temperature gradient judgments and difficulty in quickly identifying abnormal temperature areas at risk of cracking, posing potential risks to magnet sintering quality.

[0003] Existing technologies, in the process of adjusting heating power, do not fully consider the critical parameters of material phase transformation at different sintering stages of rare earth magnets, but only adjust the power based on simple temperature data, resulting in insufficient adjustment accuracy. In addition, the lack of a targeted thermal energy compensation mechanism makes it impossible to accurately supplement heat according to the specific location and volume of temperature anomaly areas, resulting in poor temperature uniformity within the sintering furnace. This not only reduces the sintering efficiency of rare earth magnets, but also affects the consistency and stability of magnet performance. Summary of the Invention

[0004] This invention provides an intelligent sintering production line and control system for rare earth magnets to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides an intelligent sintering control system for rare earth magnets, characterized in that the system includes a temperature data acquisition module, a temperature gradient evaluation module, a temperature change rate fitting module, a heating power adjustment module, a directional thermal energy compensation module, and an optimized heating command generation module, wherein:

[0006] The temperature data acquisition module is used to collect real-time temperature data of rare earth magnets at different locations in the sintering furnace, so as to generate temperature distribution information reflecting the heating environment of rare earth magnets in the sintering furnace.

[0007] The temperature gradient assessment module is used to assess the real-time temperature gradient at different locations within the sintering furnace based on the temperature distribution information, and compare the real-time temperature gradient with a preset gradient threshold to identify abnormal temperature regions within the sintering furnace that pose a risk of cracking.

[0008] The temperature change rate fitting module is used to fit the temperature change rate of the temperature anomaly region based on the continuous temperature data sequence of the temperature anomaly region.

[0009] The heating power adjustment module is used to adjust the heating power in the temperature abnormal region based on the temperature change rate and the material phase transformation critical parameters of the rare earth magnet in the current sintering stage.

[0010] The directional thermal energy compensation module is used to perform directional thermal energy compensation on the temperature abnormal area based on the heating power, so as to obtain the power compensation amount of the sintering furnace.

[0011] The optimized heating command generation module is used to superimpose the power compensation amount and the reference power of the sintering furnace to generate the optimized heating command for the sintering furnace.

[0012] In a preferred embodiment, when the temperature data acquisition module collects real-time temperature data of the rare earth magnet at different locations within the sintering furnace to generate temperature distribution information reflecting the heating environment of the rare earth magnet within the sintering furnace, it is specifically used for:

[0013] The real-time temperature data of rare earth magnets at corresponding locations is collected by temperature sensors installed inside the sintering furnace.

[0014] By removing outlier data from the real-time temperature dataset, a clean temperature dataset for the sintering furnace is obtained.

[0015] Based on the location information in the clean temperature dataset, the clean temperature dataset is integrated to generate temperature distribution information reflecting the heating environment of the rare earth magnets inside the sintering furnace.

[0016] In a preferred embodiment, when the temperature gradient assessment module evaluates the real-time temperature gradient at different locations within the sintering furnace based on the temperature distribution information and compares the real-time temperature gradient with a preset gradient threshold to identify temperature anomaly regions within the sintering furnace that pose a risk of cracking, it is specifically used for:

[0017] Integrate the temperature values ​​and coordinates corresponding to different locations in the temperature distribution information to establish a location-temperature association dataset for the sintering furnace;

[0018] Based on the location temperature association dataset, the temperature difference between adjacent locations in the sintering furnace is determined, and the temperature difference set of the sintering furnace is obtained.

[0019] Based on the set of temperature differences, the temperature gradient state corresponding to different locations in the sintering furnace is defined, and the real-time temperature gradient in the sintering furnace is obtained.

[0020] The real-time temperature gradient is compared with the preset gradient threshold one by one to mark the location range in the sintering furnace that exceeds the preset gradient threshold, thereby obtaining the temperature anomaly area in the sintering furnace.

[0021] In a preferred embodiment, when the temperature gradient assessment module performs the task of defining the temperature gradient state corresponding to different locations within the sintering furnace based on the set of temperature differences to obtain the real-time temperature gradient within the sintering furnace, it is specifically used for:

[0022] Based on the set of temperature differences and the location temperature association dataset, the adjacent position pairs corresponding to the temperature differences are determined to generate the difference position correspondence table in the sintering furnace;

[0023] The internal spatial layout parameters of the sintering furnace are mapped to the difference position correspondence table to obtain the spatial spacing attribute of the adjacent position pairs, so as to generate the spacing difference association data in the sintering furnace.

[0024] The spacing difference correlation data is matched with the preset gradient state division standard to obtain the temperature gradient state corresponding to different positions in the sintering furnace.

[0025] Based on the temperature gradient state, the temperature gradient attributes corresponding to different locations within the sintering furnace are determined to obtain the real-time temperature gradient within the sintering furnace.

[0026] In a preferred embodiment, when the temperature change rate fitting module performs the task of fitting the temperature change rate of the temperature anomaly region based on a continuous temperature data sequence of the temperature anomaly region, it is specifically used for:

[0027] By associating the temperature anomaly area with the temperature sensor inside the sintering furnace, the temperature sensor corresponding to the temperature anomaly area is determined.

[0028] Using a fixed sliding window, the temperature sensor collects temperature data of the temperature anomaly area at different time points to form the original temperature data sequence of the temperature anomaly area.

[0029] After removing the pulse interference data from the original temperature data sequence, a stable temperature data sequence for the temperature anomaly region is obtained.

[0030] Add corresponding timestamps to the temperature data in the stable temperature data sequence to obtain a continuous temperature data sequence of the temperature anomaly region.

[0031] Observe the continuous temperature data sequence and record the correspondence between temperature changes at adjacent time points and time intervals;

[0032] Based on the aforementioned correspondence, the rate of temperature change in the temperature anomaly region is fitted.

[0033] In a preferred embodiment, the formula for calculating the rate of temperature change is as follows:

[0034] ;

[0035] In the formula, This indicates the rate of temperature change. This indicates the number of data points in the continuous temperature data sequence within a fixed sliding window. This indicates the first continuous temperature data sequence. The timestamp of each data point This indicates the first continuous temperature data sequence. Temperature values ​​for each data point.

[0036] In a preferred embodiment, when the heating power adjustment module adjusts the heating power in the temperature anomaly region based on the temperature change rate and the material phase transformation critical parameters of the rare earth magnet at the current sintering stage, it is specifically used for:

[0037] Based on the critical value of thermal stress of the rare earth magnet, the critical parameters of material phase transformation of the rare earth magnet in the current sintering stage are determined.

[0038] The difference between the temperature change rate and the critical phase transformation parameter of the material is compared to obtain the comparison result between the temperature change rate and the critical phase transformation parameter of the material;

[0039] Based on the comparison results, the heating power adjustment amount for the temperature anomaly area is determined;

[0040] Adjust the heating power of the temperature abnormal area according to the heating power adjustment amount.

[0041] In a preferred embodiment, when the directional thermal energy compensation module performs directional thermal energy compensation on the temperature anomaly region based on the heating power to obtain the power compensation amount of the sintering furnace, it is specifically used for:

[0042] The three-dimensional coordinates and volume of the temperature anomaly region within the sintering furnace were determined.

[0043] Based on the three-dimensional coordinates, determine the heating equipment inside the sintering furnace corresponding to the temperature anomaly region;

[0044] The adjusted heating power and the thermal radiation efficiency of the heating equipment are weighted and fused to obtain the initial compensation power of the sintering furnace;

[0045] Based on the historical temperature data of the sintering furnace, the temperature equalization standard of the sintering furnace is determined, and the current temperature of the sintering furnace is compared with the temperature equalization standard to obtain the temperature deviation result of the sintering furnace.

[0046] Based on the temperature deviation, the initial compensation power is adjusted to obtain the power compensation amount of the sintering furnace.

[0047] In a preferred embodiment, when the optimized heating command generation module performs the superposition of the power compensation amount and the reference power of the sintering furnace to generate the optimized heating command for the sintering furnace, it is specifically used for:

[0048] According to the sintering process specifications corresponding to the sintering furnace, the reference power of the sintering furnace during the sintering stage is obtained;

[0049] Based on the compensation direction of the power compensation amount, the reference power is adjusted by increasing or decreasing the compensation amount to obtain the target heating power of the sintering furnace;

[0050] The location information of the temperature anomaly area is retrieved, and the target heating power is bound to the location information to obtain the heating area corresponding to the target heating power;

[0051] According to a predetermined instruction protocol format, the target heating power and the corresponding location information are integrated into the optimized heating instruction for the sintering furnace.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] 1. This invention generates a clean temperature dataset by removing abnormal data through a temperature data acquisition module, and combines the location coordinates and temperature values ​​with a temperature gradient assessment module to accurately define the real-time temperature gradient and identify abnormal areas with the risk of cracking. The heating power adjustment module can also adjust the power based on the material phase transformation critical parameters of the rare earth magnet at the current sintering stage to avoid magnet cracking due to abnormal temperature gradient or improper power, thus effectively ensuring sintering quality.

[0054] 2. This invention determines the power compensation amount based on the three-dimensional coordinates of the abnormal area, the thermal radiation efficiency of the heating equipment, and historical temperature data. It optimizes the heating command generation module by superimposing the reference power to generate accurate commands, thereby achieving directional heat compensation. This not only reduces heat energy waste and improves the efficiency of intelligent sintering control, but also ensures uniform temperature inside the furnace and guarantees stable and consistent performance of rare earth magnets. Attached Figure Description

[0055] Figure 1 This is a system architecture diagram of a rare earth magnet intelligent sintering control system provided in an embodiment of the present invention;

[0056] Figure 2 This is a schematic diagram of the composition structure of a rare earth magnet intelligent sintering production line according to an embodiment of the present invention.

[0057] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 belong to some, but not all, embodiments of the present invention. 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.

[0059] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “said” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0060] Depending on the context, the word "if" or "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0061] Furthermore, the timing of the steps in the following method embodiments is merely an example and not a strict limitation.

[0062] In practice, the server-side equipment deployed in a rare earth magnet intelligent sintering control system may consist of one or more devices. This rare earth magnet intelligent sintering control system can be implemented as: a business instance, a virtual machine, or hardware devices. For example, this rare earth magnet intelligent sintering control system can be implemented as a business instance deployed on one or more devices in a cloud node. Simply put, this rare earth magnet intelligent sintering control system can be understood as software deployed on a cloud node, used to provide a rare earth magnet intelligent sintering control system to various user terminals. Alternatively, this rare earth magnet intelligent sintering control system can also be implemented as a virtual machine deployed on one or more devices in a cloud node. This virtual machine contains application software for managing various user terminals. Alternatively, this rare earth magnet intelligent sintering control system can also be implemented as a server composed of numerous identical or different types of hardware devices, with one or more hardware devices configured to provide a rare earth magnet intelligent sintering control system to various user terminals.

[0063] In terms of implementation, the intelligent sintering control system for rare earth magnets and the user terminal are mutually compatible. That is, if the intelligent sintering control system for rare earth magnets is implemented as an application installed on a cloud service platform, then the user terminal is implemented as a client that establishes a communication connection with the application; or if the intelligent sintering control system for rare earth magnets is implemented as a website, then the user terminal is implemented as a webpage; or if the intelligent sintering control system for rare earth magnets is implemented as a cloud service platform, then the user terminal is implemented as a mini-program in an instant messaging application.

[0064] like Figure 1 The figure shown is a system architecture diagram of a rare earth magnet intelligent sintering control system provided in an embodiment of the present invention.

[0065] The intelligent sintering control system 100 for rare earth magnets described in this invention can be located on a cloud server. In terms of implementation, it can function as one or more service devices, or as an application installed on the cloud (e.g., a mobile service operator's server, server cluster, etc.), or it can be developed into a website. Depending on the functions implemented, the intelligent sintering control system 100 for rare earth magnets may include a temperature data acquisition module 101, a temperature gradient evaluation module 102, a temperature change rate fitting module 103, a heating power adjustment module 104, a directional thermal energy compensation module 105, and an optimized heating command generation module 106. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the system processor and perform a fixed function, stored in the system's memory.

[0066] In this embodiment of the invention, in a rare earth magnet intelligent sintering control system, each of the above-mentioned modules can be implemented independently and can be called by other modules. Here, "calling" can be understood as one module connecting to multiple modules of another type and providing corresponding services to those connected modules. In the rare earth magnet intelligent sintering control system provided by this embodiment of the invention, without modifying the program code, the applicable scope of the rare earth magnet intelligent sintering control system architecture can be adjusted by adding modules and directly calling them, achieving cluster-based horizontal expansion to quickly and flexibly expand the rare earth magnet intelligent sintering control system. In practical applications, the above-mentioned modules can be set in the same device or different devices, or they can be set in a virtual device, such as a service instance in a cloud server.

[0067] The following describes, with reference to specific embodiments, each component and its specific workflow of a rare-earth magnet intelligent sintering control system:

[0068] The temperature data acquisition module 101 is used to acquire real-time temperature data of rare earth magnets at different locations in the sintering furnace, so as to generate temperature distribution information reflecting the heating environment of rare earth magnets in the sintering furnace.

[0069] In this embodiment of the invention, when the temperature data acquisition module collects real-time temperature data of the rare earth magnet at different locations within the sintering furnace to generate temperature distribution information reflecting the heating environment of the rare earth magnet within the sintering furnace, it is specifically used for:

[0070] The real-time temperature data of rare earth magnets at corresponding locations is collected by temperature sensors installed inside the sintering furnace.

[0071] By removing outlier data from the real-time temperature dataset, a clean temperature dataset for the sintering furnace is obtained.

[0072] Based on the location information in the clean temperature dataset, the clean temperature dataset is integrated to generate temperature distribution information reflecting the heating environment of the rare earth magnets inside the sintering furnace.

[0073] Temperature sensors are uniformly deployed along the inner wall of the sintering furnace and at different heights and horizontal positions within the furnace. The sensor deployment completely covers the area where the rare earth magnets are placed in the furnace, including their top, bottom, sides, and center positions. Each temperature sensor is assigned a unique location identifier, which corresponds one-to-one with the specific placement position of the rare earth magnet, ensuring that subsequent data acquisition can be accurately linked to the corresponding location of the rare earth magnet. After the sintering furnace is started and enters a stable operating state, all temperature sensors continuously capture temperature values ​​at their corresponding locations at fixed time intervals. Each captured temperature value is simultaneously recorded along with the corresponding location identifier and acquisition time, forming a raw data record containing three core elements: temperature value, location information, and acquisition time. As the sintering process progresses, all generated raw data records are continuously aggregated, ultimately forming a complete real-time temperature dataset.

[0074] First, based on the standard temperature range required for the rare earth magnet sintering process and the rated operating temperature range of the sintering furnace, the normal range of temperature data is determined. This normal range is a temperature range that has been verified through multiple sintering tests and can guarantee the sintering quality of rare earth magnets. Temperature data exceeding this range will be initially judged as abnormal data. Then, each data record in the real-time temperature dataset is checked one by one. First, it is checked whether the temperature value of each data record is within the preset normal range. If the temperature value exceeds this range, the data record is directly marked as abnormal data. Next, consecutive data records corresponding to the same location marker are checked, and the temperature value change range of adjacent data records is observed. If the change range far exceeds the maximum normal temperature rise and fall range in the sintering process, i.e., it does not conform to the gradual temperature change pattern during sintering, the data record with abnormal change range is marked as abnormal data. Simultaneously, the datasets corresponding to all sensors are checked. If all data records corresponding to a certain location marker have no temperature value output, or the output temperature value remains constant and significantly different from the temperature values ​​corresponding to adjacent location markers, it indicates that the sensor is faulty, and all its corresponding data records are marked as abnormal data. After marking all abnormal data, these marked records are completely removed from the real-time temperature dataset. The remaining data records that have been verified and confirmed to be without abnormalities are then compiled to form a clean temperature dataset.

[0075] First, all data records in the cleanroom temperature dataset are categorized and organized according to their location information. Data records with the same location identifier are grouped together, forming several dataset groups centered on location identifiers. Each group contains all temperature values ​​corresponding to different acquisition times during the sintering process at that location. Then, the temperature values ​​within each dataset group are integrated. All temperature values ​​within the group are summed, and the sum is divided by the total number of temperature values ​​within the group. This method calculates the average temperature value corresponding to each location identifier, ensuring that the temperature at each location is accurately reflected through the average temperature value. Finally, each location identifier is associated with its corresponding average temperature value to generate a location-average temperature correspondence table, which clearly presents the temperature situation at each specific location within the furnace. Finally, combining the physical structure of the sintering furnace and the actual placement of rare earth magnets inside the furnace, the information in the position-average temperature correspondence table is mapped onto the three-dimensional physical space of the sintering furnace. The average temperature values ​​corresponding to adjacent positions are connected and integrated. Through this spatial mapping and connection process, information that can intuitively reflect the temperature distribution of rare earth magnets in different areas and positions within the sintering furnace is formed. This information reflects the temperature distribution of the heating environment of the rare earth magnets and can clearly show the spatial distribution differences of temperature within the furnace, providing data support for subsequent optimization of the sintering process and ensuring the sintering quality of the magnets.

[0076] The beneficial effects are as follows: by rationally deploying temperature sensors within the sintering furnace, accurate acquisition of temperature data at corresponding locations of rare earth magnets is achieved, ensuring the integrity and location correlation of the real-time temperature dataset; through clear abnormal data judgment criteria and rejection processes, invalid data in the real-time temperature dataset is effectively removed, ensuring the accuracy and reliability of the clean temperature dataset; based on location information, the clean temperature dataset is classified, average temperature is calculated, and spatial mapping is integrated, generating temperature distribution information that can truly reflect the heating environment of rare earth magnets within the sintering furnace, providing accurate data basis for optimizing and adjusting the sintering process and improving the sintering quality of rare earth magnets. Furthermore, the entire process is clearly defined, highly repeatable, and meets the practical application needs in industrial production.

[0077] The temperature gradient assessment module 102 is used to assess the real-time temperature gradient at different locations in the sintering furnace based on the temperature distribution information, and compare the real-time temperature gradient with a preset gradient threshold to identify abnormal temperature areas in the sintering furnace that have a risk of cracking.

[0078] In this embodiment of the invention, when the temperature gradient assessment module evaluates the real-time temperature gradient at different locations within the sintering furnace based on the temperature distribution information and compares the real-time temperature gradient with a preset gradient threshold to identify temperature anomaly regions within the sintering furnace that pose a risk of cracking, it is specifically used for:

[0079] Integrate the temperature values ​​and coordinates corresponding to different locations in the temperature distribution information to establish a location-temperature association dataset for the sintering furnace;

[0080] Based on the location temperature association dataset, the temperature difference between adjacent locations in the sintering furnace is determined, and the temperature difference set of the sintering furnace is obtained.

[0081] Based on the set of temperature differences, the temperature gradient state corresponding to different locations in the sintering furnace is defined, and the real-time temperature gradient in the sintering furnace is obtained.

[0082] The real-time temperature gradient is compared with the preset gradient threshold one by one to mark the location range in the sintering furnace that exceeds the preset gradient threshold, thereby obtaining the temperature anomaly area in the sintering furnace.

[0083] When the temperature gradient assessment module performs the operation of defining the temperature gradient state corresponding to different locations within the sintering furnace based on the set of temperature differences, and obtaining the real-time temperature gradient within the sintering furnace, it is specifically used for:

[0084] Based on the set of temperature differences and the location temperature association dataset, the adjacent position pairs corresponding to the temperature differences are determined to generate the difference position correspondence table in the sintering furnace;

[0085] The internal spatial layout parameters of the sintering furnace are mapped to the difference position correspondence table to obtain the spatial spacing attribute of the adjacent position pairs, so as to generate the spacing difference association data in the sintering furnace.

[0086] The spacing difference correlation data is matched with the preset gradient state division standard to obtain the temperature gradient state corresponding to different positions in the sintering furnace.

[0087] Based on the temperature gradient state, the temperature gradient attributes corresponding to different locations within the sintering furnace are determined to obtain the real-time temperature gradient within the sintering furnace.

[0088] All temperature values ​​from the temperature distribution information are extracted, and the corresponding location coordinates for each temperature value are precisely extracted. These location coordinates must fully reflect the three-dimensional spatial position of that temperature within the sintering furnace, ensuring a unique correspondence between each temperature value and its location. During extraction, existing location identifiers in the temperature distribution information are used for precise verification to avoid mismatches between temperature values ​​and location coordinates. Each extracted temperature value is then individually bound to its corresponding location coordinates. After binding, all the binding relationships between temperature values ​​and location coordinates are arranged sequentially according to the spatial arrangement within the sintering furnace, forming a structured dataset. This dataset is the location-temperature association dataset, which fully contains the coordinate information of each spatial location within the sintering furnace and the corresponding temperature value, achieving a precise association between temperature and location information.

[0089] All location coordinates and corresponding temperature values ​​are extracted from the location-temperature association dataset. Based on the physical structure of the sintering furnace and the spatial distribution of location coordinates, a clear criterion for determining adjacent locations is established: two spatially closest locations without any other obstructions are considered adjacent. This criterion ensures that the definition of adjacent locations conforms to the actual physical scenario of temperature conduction within the sintering furnace. Following this criterion, all locations in the location-temperature association dataset are examined one by one to identify all combinations of adjacent locations that meet the criteria. For each group of adjacent locations, the temperature values ​​corresponding to the two locations are retrieved from the location-temperature association dataset. The higher temperature value is subtracted from the lower temperature value to obtain the temperature difference between the adjacent locations. Each temperature difference value is uniquely associated with its corresponding combination of adjacent locations. All temperature difference values ​​corresponding to combinations of adjacent locations are collected and summarized to form a set containing information on the temperature differences between all adjacent locations within the sintering furnace; this set is the temperature difference set.

[0090] Based on the temperature uniformity requirements of rare earth magnet sintering processes and considering the influence of temperature gradients on the microstructure and magnetic properties of magnets during sintering, a standard for defining temperature gradient states was established. This standard divides temperature differences into three distinct intervals, each corresponding to a different temperature gradient state: a smaller interval corresponds to a gentle temperature gradient, a medium interval to a moderate temperature gradient, and a larger interval to a steep temperature gradient. Each interval division was verified through multiple sintering experiments to ensure it meets actual production requirements. Each temperature difference in the set is compared one by one with the three intervals in the definition standard to determine its corresponding interval and temperature gradient state. Each temperature gradient state is then associated with its adjacent position combinations to clarify the temperature gradient situation for each adjacent position combination. Finally, considering the spatial distribution of all locations within the sintering furnace, the temperature gradient states of all adjacent locations are integrated to form comprehensive information reflecting the steepness of temperature changes in various regions within the sintering furnace—this information is the real-time temperature gradient.

[0091] The preset gradient threshold is determined through extensive sintering experiments and data accumulation, based on the material characteristics of rare earth magnets, target magnetic performance indicators, and quality control requirements for industrial-scale sintering production. This threshold represents the temperature difference corresponding to the maximum allowable temperature gradient during sintering. Temperature gradients exceeding this threshold will lead to uneven temperature distribution within the rare earth magnet, thus affecting the magnet's sintering density and magnetic performance consistency. The temperature difference corresponding to each adjacent position combination is extracted from the real-time temperature gradient. This temperature difference is compared one by one with the preset gradient threshold. If the temperature difference corresponding to a certain adjacent position combination is greater than the preset gradient threshold, the area where that adjacent position combination is located is determined to be a temperature gradient anomaly region. All adjacent position combinations exceeding the preset gradient threshold after comparison are collected. Based on the coordinate information of these adjacent position combinations, their continuous spatial range within the sintering furnace is determined. These continuous spatial ranges are integrated to clarify the boundary coordinates and coverage area of ​​each anomaly range, forming information that can accurately identify specific areas within the sintering furnace where the temperature gradient exceeds the allowable range. This information is the temperature anomaly region.

[0092] All temperature difference values ​​are extracted from the temperature difference value set. Simultaneously, the location coordinates and identifiers of the two adjacent locations corresponding to each temperature difference value are retrieved from the location temperature association dataset. The retrieval process uses the association markers retained during the calculation phase to perform precise matching, ensuring that each temperature difference value corresponds to a unique set of adjacent locations. Each temperature difference value is then bound one-to-one with the location identifier and coordinates of its corresponding adjacent location. The binding includes the identifier and coordinates of the first location, the identifier and coordinates of the second location, and the corresponding temperature difference value. All bound information is arranged sequentially according to the spatial distribution order of adjacent location pairs within the sintering furnace, forming a structured tabular data record. This table, known as the temperature difference location correspondence table, fully preserves the correspondence between temperature difference values ​​and adjacent location pairs, providing clear data support for subsequent spatial spacing calculations.

[0093] The internal spatial layout parameters of the sintering furnace are collected. These parameters include the actual physical length, width, and height of the furnace chamber, as well as the calibration reference information for the position coordinates, i.e., the actual physical distance corresponding to each numerical unit in the position coordinates, ensuring that the coordinate data can be accurately converted into physical spatial distance. For each pair of adjacent positions in the difference position correspondence table, the coordinate information of each position is extracted. Based on the internal spatial layout parameters, the actual physical position corresponding to each coordinate value is determined. The actual distance between the first and second positions in the length, width, and height directions of the furnace chamber is calculated. That is, by combining the difference in coordinate values ​​of the two positions in the same direction with the actual physical distance corresponding to the coordinate unit, the actual spacing in that direction is obtained. Then, the straight-line distance between the two positions is calculated through geometric relationships. The calculation process involves constructing a virtual cuboid with the actual spacing in the three directions as its sides. The length of the body diagonal of this cuboid is the spatial straight-line distance between the two positions, which is the spatial spacing attribute of the adjacent position pair. The spatial spacing attribute is added to the records of adjacent position pairs and temperature differences in the difference position correspondence table. All the completed records are summarized to form the spacing difference association data, which includes four core contents: the identifier of the adjacent position pair, coordinates, temperature difference, and spatial spacing attribute.

[0094] The preset gradient state classification standard is formulated based on the temperature gradient requirements of rare earth magnet sintering processes and combined with a large amount of sintering test data. This standard uses the temperature change per unit distance as the core classification criterion, clearly dividing the gradient state into three intervals: gentle temperature gradient, moderate temperature gradient, and steep temperature gradient. Specifically, the interval with the smallest temperature change per unit distance corresponds to the gentle temperature gradient state, where the temperature change is uniform and will not affect the magnet sintering quality; the intermediate interval corresponds to the moderate temperature gradient state, where the temperature change is within an acceptable range and requires continuous monitoring; the interval with the largest temperature change per unit distance corresponds to the steep temperature gradient state, where the temperature change is drastic and may lead to uneven magnet performance. For each record in the spacing difference correlation data, the temperature difference value and spatial spacing attribute are extracted. The temperature difference value is used as the dividend, and the spatial spacing attribute value is used as the divisor, and a division operation is performed. The result is the temperature change per unit distance. The calculated temperature change per unit distance is compared one by one with the three intervals in the preset gradient state division standard to determine the interval to which the change belongs, and then corresponds to a unique temperature gradient state. Each interval difference correlation data is used to obtain the corresponding temperature gradient state, and finally the temperature gradient state corresponding to different positions in the sintering furnace is determined.

[0095] Temperature gradient attributes are a specific representation of the temperature gradient state, including the range of temperature change per unit distance, temperature change characteristics, and the degree of influence on rare earth magnet sintering for each gradient state. The temperature gradient state corresponding to each pair of adjacent locations is deeply correlated with the spatial coordinate information of that pair, clarifying the distribution of temperature gradient states around each spatial location. Following the three-dimensional spatial layout within the sintering furnace, the temperature gradient states of all adjacent locations are systematically connected and integrated, progressively sorting out the temperature gradient state of each region from one end of the furnace to the other, from the bottom to the top, and from one side to the other, ensuring that every spatial location within the sintering furnace corresponds to a clear temperature gradient attribute. Through this comprehensive integration, a holistic information system is formed that fully reflects the temperature change per unit distance and spatial distribution characteristics of each region within the sintering furnace. This information constitutes the real-time temperature gradient within the sintering furnace, clearly presenting the spatial differences in the temperature gradient within the furnace, providing detailed data support for precise adjustments to the subsequent sintering process.

[0096] The beneficial effects are as follows: by integrating temperature values ​​and location coordinates from temperature distribution information, a location-temperature association dataset is established, achieving precise binding between temperature and location, providing a reliable data foundation for subsequent temperature difference calculation; by clarifying the criteria for determining adjacent locations and calculating temperature differences, the resulting set of temperature difference values ​​comprehensively reflects the temperature differences between adjacent locations within the furnace; based on the set of temperature difference values, the temperature gradient state is defined, and the generated real-time temperature gradient clearly shows the steepness distribution of temperature changes within the furnace; by comparing with preset gradient thresholds to mark abnormal temperature areas, areas where the temperature gradient exceeds the standard within the furnace can be quickly and accurately located, providing a clear basis for timely adjustment of sintering process parameters and optimization of the temperature field distribution within the furnace, effectively improving the temperature control accuracy of the rare earth magnet sintering process, ensuring the consistency and stability of magnet sintering quality, and meeting the actual application needs of industrial production.

[0097] The temperature change rate fitting module 103 is used to fit the temperature change rate of the temperature anomaly region based on the continuous temperature data sequence of the temperature anomaly region.

[0098] In this embodiment of the invention, when the temperature change rate fitting module performs the task of fitting the temperature change rate of the temperature anomaly region based on the continuous temperature data sequence of the temperature anomaly region, it is specifically used for:

[0099] By associating the temperature anomaly area with the temperature sensor inside the sintering furnace, the temperature sensor corresponding to the temperature anomaly area is determined.

[0100] Using a fixed sliding window, the temperature sensor collects temperature data of the temperature anomaly area at different time points to form the original temperature data sequence of the temperature anomaly area.

[0101] After removing the pulse interference data from the original temperature data sequence, a stable temperature data sequence for the temperature anomaly region is obtained.

[0102] Add corresponding timestamps to the temperature data in the stable temperature data sequence to obtain a continuous temperature data sequence of the temperature anomaly region.

[0103] Observe the continuous temperature data sequence and record the correspondence between temperature changes at adjacent time points and time intervals;

[0104] Based on the aforementioned correspondence, the rate of temperature change in the temperature anomaly region is fitted.

[0105] The formula for calculating the rate of temperature change is as follows:

[0106] ;

[0107] In the formula, This indicates the rate of temperature change. This indicates the number of data points in the continuous temperature data sequence within a fixed sliding window. This indicates the first continuous temperature data sequence. The timestamp of each data point This indicates the first continuous temperature data sequence. Temperature values ​​for each data point.

[0108] The boundary coordinates and coverage information of the temperature anomaly area are extracted. This information clarifies the three-dimensional spatial boundary and specific distribution area of ​​the anomaly area within the sintering furnace. Simultaneously, the deployment coordinates and unique identifiers of all temperature sensors within the sintering furnace are retrieved to ensure complete and accurate sensor location information. Through spatial location comparison, the boundary coordinates of the temperature anomaly area are matched one-to-one with the deployment coordinates of each temperature sensor to determine whether the sensor's deployment location is within the coverage area of ​​the temperature anomaly area or on its boundary line. Sensors within this range or on the boundary line are the temperature sensors corresponding to the temperature anomaly area. All successfully matched sensors are identified and summarized, clearly defining all sensors corresponding to each temperature anomaly area to ensure accurate coverage of the anomaly area in subsequent temperature data acquisition.

[0109] A fixed sliding window refers to a continuous acquisition period with a fixed time span. This time span is determined based on the response speed of temperature changes and the requirements for anomaly monitoring during the sintering process of rare-earth magnets, ensuring that the dynamic temperature change characteristics of the anomaly area can be captured. The sliding window advances continuously without overlap; that is, the next window starts immediately as the previous one ends. Temperature sensors corresponding to the identified temperature anomaly areas are associated with this sliding window. The sensors automatically acquire temperature values ​​for the anomaly area at each time point corresponding to the time span set by the sliding window. During the acquisition process, the sensors maintain a stable operating state, ensuring the consistency and reliability of the temperature data acquired each time. As the sliding window advances continuously, the sensors continuously acquire temperature values ​​at different time points. These temperature values ​​are arranged sequentially according to the acquisition time, forming an ordered temperature data set, which is the original temperature data sequence of the temperature anomaly area.

[0110] Impulse interference data refers to transient, anomalous data that suddenly appears in the original temperature data sequence, differs greatly from adjacent temperature values, and has no physical cause to support its existence. Its characteristics include a single occurrence, extremely short duration, and rapid recovery to the normal fluctuation range. For each temperature data point in the original temperature data sequence, multiple consecutive temperature data points adjacent to it are extracted. These adjacent data points are used as reference benchmarks, and the average temperature of these reference benchmark data points is calculated by summing the values ​​of all reference benchmark data points and then dividing the sum by the number of reference benchmark data points. The current temperature data to be judged is compared with the calculated average temperature. If the difference between the current temperature data and the average temperature far exceeds the maximum range of normal temperature fluctuations during sintering, and this difference has no reasonable cause to support it at the sintering process or equipment operation level, then the temperature data is determined to be impulse interference data. All data points determined to be impulse interference are removed one by one from the original temperature data sequence. The remaining temperature data are arranged in their original time order to form a stable temperature data sequence for the temperature anomaly region. This sequence eliminates transient interference and can reflect the true temperature change trend of the anomaly region.

[0111] The timestamp provides the specific time information at the moment the temperature data was collected, including complete time dimensions such as year, month, day, hour, minute, and second, ensuring that each temperature data point corresponds to a unique collection moment. During the generation of the stable temperature data sequence, the temperature sensor simultaneously records the complete time information at the moment of collection for each temperature data point. This time information is accurately acquired through the sensor's built-in timing module, ensuring the accuracy of the time recording. Each temperature data point is bound to its corresponding complete time information, with precise matching based on the collection order during the binding process to avoid mismatches between temperature data and timestamps. All time-stamped temperature data are then rearranged and arranged according to the chronological order of collection time, forming an ordered data set containing temperature values ​​and corresponding collection times. This set constitutes the continuous temperature data sequence for the temperature anomaly region, fully presenting the continuous process of temperature change over time in the anomaly region.

[0112] The continuous temperature data sequence is analyzed chronologically based on the acquisition time. Starting from the first data point, the temperature data corresponding to adjacent time points are examined sequentially. The difference between the temperature value of the later time point and the temperature value of the earlier time point is recorded, including three possibilities: temperature increase, temperature decrease, or no change. The specific magnitude of the difference is also determined to comprehensively characterize the temperature changes between adjacent time points. Next, the timestamp information corresponding to these two adjacent time points is extracted, and the time length between the later and earlier timestamps is calculated. This time length is the time interval between adjacent time points, calculated using seconds as the smallest unit in the timestamp to ensure the accuracy of the interval recording. The temperature changes at each adjacent time point are mapped one-to-one with the corresponding time interval, forming a correlation record table containing both the changes and the time intervals, completely preserving the correspondence between the two.

[0113] The rate of temperature change refers to the amount of temperature change in an anomaly region per unit time. Its fitting process is based on the correspondence between recorded temperature changes at adjacent time points and time intervals. For each set of correspondences in the associated record table, the temperature change values ​​at adjacent time points are taken as the total change, and the corresponding time interval is taken as the change time. Dividing the total temperature change by the change time yields the temperature change per unit time for that set of correspondences. All calculated temperature changes per unit time are arranged in chronological order, and the overall distribution trend is observed. Individual extreme changes caused by random factors are removed. Based on the remaining temperature changes per unit time, the overall average level is taken to form a virtual curve that smoothly reflects the temperature change trend. The temperature change per unit time corresponding to this curve is the fitted rate of temperature change for the anomaly region, which objectively reflects the average speed of temperature change over time in the anomaly region, providing data support for subsequent anomaly processing.

[0114] The number of data points is derived from the number of data points in the continuous temperature data sequence within a fixed sliding window. The continuous temperature data sequence is obtained by adding corresponding timestamps to the stationary temperature data sequence. The fixed sliding window is a continuous acquisition period with a fixed time span. This number is calculated by counting all data points in the continuous temperature data sequence that fall within the fixed sliding window. The timestamp information is derived from the time information corresponding to each data point in the continuous temperature data sequence. This time information is recorded synchronously when adding timestamps to the stationary temperature data sequence. The stationary temperature data sequence is obtained after removing impulse interference data from the original temperature data sequence. The original temperature data sequence is acquired by temperature sensors corresponding to temperature anomaly areas within the fixed sliding window. The temperature value information is derived from the temperature value corresponding to each data point in the continuous temperature data sequence. This value comes from the stationary temperature data sequence, which is obtained by removing impulse interference data from the original temperature data sequence. The original temperature data sequence consists of temperature data from temperature anomaly areas acquired by temperature sensors.

[0115] This formula is used to calculate the rate of temperature change in an abnormal temperature region. This rate is the amount of temperature change in the abnormal temperature region per unit time. The calculation process combines the time information and the corresponding temperature values ​​in a continuous temperature data sequence. By integrating this information, a result that reflects the average speed of temperature change in the abnormal temperature region over time is obtained. This result is the rate of temperature change in the abnormal temperature region, which is used to clarify the specific situation of temperature change in the abnormal region over time.

[0116] When the temperature values ​​in a continuous temperature data series increase with time, the result obtained by this formula will show an upward trend, indicating that the temperature in the temperature anomaly area is gradually increasing over time. When the temperature values ​​in a continuous temperature data series decrease with time, the result obtained by this formula will show a downward trend, indicating that the temperature in the temperature anomaly area is gradually decreasing over time. When the temperature values ​​in a continuous temperature data series remain stable over time, the result obtained by this formula will be relatively stable, indicating that the temperature change in the temperature anomaly area is relatively gradual.

[0117] The beneficial effects are as follows: by associating abnormal temperature regions with corresponding temperature sensors, precise and targeted acquisition of temperature data in abnormal regions is achieved, ensuring the relevance and effectiveness of data acquisition; the use of a fixed sliding window to acquire raw temperature data sequences can comprehensively capture the dynamic change characteristics of abnormal temperature regions, providing a complete data foundation for subsequent analysis; the stable temperature data sequence obtained after removing pulse interference data eliminates the influence of instantaneous interference on the temperature change trend, ensuring the authenticity of the data; the continuous temperature data sequence after adding timestamps establishes a precise correlation between temperature and time, providing the necessary conditions for calculating the rate of change; recording the correspondence between temperature changes and time intervals at adjacent time nodes provides a direct basis for fitting the rate of temperature change; the temperature change rate obtained through fitting can objectively reflect the speed of temperature change in abnormal regions, providing precise data support for the formulation of sintering furnace temperature control strategies, and effectively improving the efficiency of abnormal handling and quality control level in the rare earth magnet sintering process.

[0118] The heating power adjustment module 104 is used to adjust the heating power of the temperature abnormal region according to the temperature change rate and the material phase transformation critical parameters of the rare earth magnet in the current sintering stage.

[0119] In this embodiment of the invention, when the heating power adjustment module adjusts the heating power in the temperature anomaly region based on the temperature change rate and the material phase transformation critical parameters of the rare earth magnet in the current sintering stage, it is specifically used for:

[0120] Based on the critical value of thermal stress of the rare earth magnet, the critical parameters of material phase transformation of the rare earth magnet in the current sintering stage are determined.

[0121] The difference between the temperature change rate and the critical phase transformation parameter of the material is compared to obtain the comparison result between the temperature change rate and the critical phase transformation parameter of the material;

[0122] Based on the comparison results, the heating power adjustment amount for the temperature anomaly area is determined;

[0123] Adjust the heating power of the temperature abnormal area according to the heating power adjustment amount.

[0124] The critical thermal stress value of rare earth magnets is the maximum thermal stress that such magnets can withstand during sintering. This value is determined through numerous materials mechanics experiments. During the experiments, gradually increasing thermal stress is applied to the rare earth magnet samples until microcracks or plastic deformation appear. The corresponding thermal stress value at this point is the critical thermal stress value. This value is an inherent characteristic parameter of the rare earth magnet material itself and is closely related to the magnet's composition and microstructure. The current sintering stage refers to the specific process stage of the rare earth magnet in the sintering furnace. The phase transformation characteristics of the magnet differ at different sintering stages. The critical phase transformation parameter of the material is the parameter that ensures that the magnet does not exceed the critical thermal stress value during the phase transformation process. It is mainly manifested as the maximum allowable temperature change rate during the phase transformation process. By consulting material property manuals and phase transformation law data for rare earth magnets, and combining them with the process requirements of the current sintering stage, a correspondence between the critical value of thermal stress and the critical parameter of material phase transformation was established. This correspondence was established by recording the temperature change rate of the magnet during phase transformation at different critical values ​​of thermal stress through multiple experiments under the same sintering stage. The maximum temperature change rate that the magnet phase transformation can withstand when the thermal stress is at the critical value was determined. This rate is the critical parameter of material phase transformation at the current sintering stage. This ensures that the parameter can accurately match the critical value of thermal stress of rare earth magnets and avoid excessive thermal stress caused by excessively rapid temperature changes during the phase transformation process.

[0125] The rate of temperature change is obtained by fitting a continuous temperature data sequence of a temperature anomaly region, reflecting the speed of temperature change per unit time in that region. The critical phase transformation parameter of the material is the maximum allowable rate of temperature change during the phase transformation of the magnet in the current sintering stage. Both belong to the same physical quantity category and have a basis for direct comparison. During the comparison process, the specific numerical characteristics of the rate of temperature change and the numerical characteristics of the critical phase transformation parameter of the material are first clarified. The two are then directly compared to determine whether the rate of temperature change exceeds the critical phase transformation parameter. If the temperature change rate is less than or equal to the critical parameter for material phase transformation, it indicates that the temperature change rate in the current abnormal temperature region is within the tolerable range of the magnet's phase transformation and will not cause damage to the magnet due to thermal stress exceeding the critical value. In this case, the comparison result is compliant. If the temperature change rate is greater than the critical parameter for material phase transformation, it indicates that the current temperature change rate is too fast, which may cause the thermal stress generated during the magnet's phase transformation to exceed the critical value, thereby causing problems such as magnet cracking and deformation. In this case, the comparison result is non-compliant. At the same time, the specific magnitude by which the temperature change rate exceeds the critical parameter for material phase transformation is specified. This magnitude is a description of the degree corresponding to the difference between the two values, and finally, a complete comparison result including whether it meets the requirements and the magnitude of the exceedance is formed.

[0126] A database of correspondences between comparison results and heating power adjustments was pre-established through extensive sintering experiments. This database was constructed based on experimental data from the same type of rare-earth magnets and the same sintering stage. During the experiments, different temperature change rates were artificially set to exceed the material's critical phase transformation parameters. The heating power adjustment required to bring the temperature change rate back to within the critical parameter range for each exceedance was recorded. The exceedance range and its corresponding heating power adjustment were then linked one-to-one, forming a standardized correspondence. Upon obtaining the comparison results, if the results meet the requirements, no adjustment of the current heating power is needed, and the corresponding adjustment amount is zero. If the results do not meet the requirements, a precise search is performed in the pre-established database based on the exceedance range specified in the comparison results to find the unique heating power adjustment amount corresponding to that exceedance range. The magnitude of this adjustment amount is positively correlated with the exceedance range; that is, the larger the exceedance range, the larger the corresponding heating power adjustment amount, ensuring that the adjusted heating power can quickly control the temperature change rate within the material's critical phase transformation parameter range.

[0127] The sintering furnace heating system comprises multiple independent heating modules, each corresponding to a specific spatial region within the furnace chamber. The location information of the temperature anomaly area has been determined through previous steps. Based on this location information, the corresponding heating module is selected to ensure that the adjustment operation is precisely applied to the temperature anomaly area. The determined heating power adjustment amount is transmitted to the control unit of the heating module. After receiving the signal, the control unit monitors the current output power of the heating module in real time to obtain the current actual heating power value. If the heating power adjustment amount is zero, the control unit maintains the current heating power unchanged and continues the original heating state. If the heating power adjustment amount is a power reduction value, the control unit reduces the supply current to the heating elements in the heating module, thereby reducing the heat generation of the heating elements and thus reducing the output power of the heating module. The reduction in supply current matches the heating power adjustment amount, ensuring that the output power is reduced to the target value. If the heating power adjustment amount is a power increase value, the control unit increases the supply current to the heating elements, thereby increasing the heat generation of the heating elements and increasing the output power of the heating module to the target value. During the adjustment process, the control unit monitors the output power of the heating module in real time to ensure that it accurately reaches the target value corresponding to the heating power adjustment amount, thereby achieving precise adjustment of the heating power in the abnormal temperature area and controlling the temperature change rate in that area to meet the requirements of the material phase transformation critical parameters.

[0128] The beneficial effects are as follows: Firstly, the critical parameters for material phase transformation are determined based on the critical value of thermal stress in rare earth magnets, ensuring precise matching between parameter settings and magnet material characteristics, thus preventing excessive thermal stress during phase transformation. Secondly, direct comparison between the temperature change rate and the critical parameters for material phase transformation allows for rapid identification of whether the current temperature change meets process requirements, with intuitive and reliable comparison results. Thirdly, the adjustment amount of heating power is determined based on a pre-set correspondence library, ensuring the scientific validity and accuracy of the adjustment and avoiding blind adjustments. Fourthly, heating power adjustment is achieved by precisely controlling the power supply current of the corresponding heating module, with direct and repeatable operation. This allows for rapid adjustment of the temperature change rate in abnormal temperature areas to a reasonable range, effectively reducing the risk of cracking and deformation of rare earth magnets due to excessive thermal stress, ensuring the stability of magnet sintering quality. Finally, the entire process aligns with actual industrial production and is highly operable.

[0129] The directional thermal energy compensation module 105 is used to perform directional thermal energy compensation on the temperature abnormal area based on the heating power, so as to obtain the power compensation amount of the sintering furnace.

[0130] In this embodiment of the invention, when the directional thermal energy compensation module performs directional thermal energy compensation on the temperature anomaly region based on the heating power to obtain the power compensation amount of the sintering furnace, it is specifically used for:

[0131] The three-dimensional coordinates and volume of the temperature anomaly region within the sintering furnace were determined.

[0132] Based on the three-dimensional coordinates, determine the heating equipment inside the sintering furnace corresponding to the temperature anomaly region;

[0133] The adjusted heating power and the thermal radiation efficiency of the heating equipment are weighted and fused to obtain the initial compensation power of the sintering furnace;

[0134] Based on the historical temperature data of the sintering furnace, the temperature equalization standard of the sintering furnace is determined, and the current temperature of the sintering furnace is compared with the temperature equalization standard to obtain the temperature deviation result of the sintering furnace.

[0135] Based on the temperature deviation, the initial compensation power is adjusted to obtain the power compensation amount of the sintering furnace.

[0136] Extract the boundary temperature data collected by all temperature sensors corresponding to the temperature anomaly region. Combine this with the existing three-dimensional position coordinates of these sensors to determine the boundary limits of the temperature anomaly region in the three dimensions of length, width, and height of the sintering furnace. In the length direction, identify the coordinates of the foremost and rearmost sensors among all sensors located at the boundary of the anomaly region; the range between these two coordinates represents the coverage area of ​​the anomaly region in the length direction. Similarly, in the width direction, determine the leftmost and rightmost boundary coordinates to define the width coverage area. In the height direction, determine the bottommost and topmost boundary coordinates to define the height coverage area. Combine the boundary coordinates of the three dimensions to form a three-dimensional coordinate range that completely encompasses the temperature anomaly region; this range is the three-dimensional coordinate of the temperature anomaly region. Based on the actual physical space corresponding to the three-dimensional coordinates, the actual distance of the boundary coordinates in the length direction is the region length, the actual distance of the boundary coordinates in the width direction is the region width, and the actual distance of the boundary coordinates in the height direction is the region height. By multiplying the actual physical dimensions corresponding to length, width, and height, the resulting spatial volume is the size of the temperature anomaly region. During the calculation, the accuracy of the size conversion is ensured based on the internal spatial layout parameters of the sintering furnace.

[0137] The layout, installation angle, and coverage area of ​​all heating equipment within the sintering furnace are pre-defined. Each heating device has a clearly defined three-dimensional coverage coordinate range, determined by its installation location and effective thermal radiation radius, ensuring a one-to-one correspondence between the coverage area of ​​each heating device and the spatial coordinates within the sintering furnace. The three-dimensional coordinates of the temperature anomaly area are then compared one by one with the three-dimensional coverage coordinate range of each heating device to determine whether the anomaly area falls entirely within the coverage of a single heating device or overlaps with the coverage of multiple heating devices. If the anomaly area falls entirely within the coverage of a single heating device, that device is the corresponding heating device. If multiple heating devices overlap with the anomaly area, the heating device with the largest coverage area is designated as the primary corresponding heating device, and the remaining devices covering the overlapping areas are designated as auxiliary corresponding heating devices, forming a combined heating device configuration corresponding to the temperature anomaly area. This ensures that subsequent power adjustments are precisely applied to the anomaly area.

[0138] The adjusted heating power is the actual output power after implementing the previously determined adjustment amount for areas with abnormal temperatures. This power is acquired in real time through the control unit of the heating equipment to ensure data authenticity and timeliness. The thermal radiation efficiency of the heating equipment is the effective utilization ratio of radiated heat per unit time at its rated power. This value is measured using professional thermal performance testing equipment. During the test, the radiated heat from the heating equipment at different power levels and the actual heat absorbed by the heated object are recorded. The ratio of these two values ​​determines the thermal radiation efficiency, which is an inherent characteristic parameter of the heating equipment and stored in the equipment parameter database. During the weighted fusion process, fixed weights are assigned based on the degree of influence of both factors on the temperature compensation effect. The weight of the adjusted heating power is higher than that of the thermal radiation efficiency because heating power directly determines the total heat output, while thermal radiation efficiency affects the heat transfer effect. The specific integration method is as follows: multiply the value corresponding to the adjusted heating power by its set weight to obtain the power weighted value; multiply the value corresponding to the thermal radiation efficiency of the heating equipment by its set weight to obtain the efficiency weighted value; add the power weighted value and the efficiency weighted value together to obtain the initial compensation power of the sintering furnace, ensuring that the weighting process can comprehensively reflect the contribution of both to temperature compensation.

[0139] The historical temperature data of the sintering furnace is a dataset of all clean temperatures recorded throughout the sintering process of the same type of rare earth magnets under the same sintering process. This data comes from qualified sintering batches, ensuring its reference value. Temperature data for each location within the furnace at each time point corresponding to the sintering stage is extracted from the historical temperature data. The temperature data for all locations at the same time point are accumulated and then divided by the number of locations to obtain the average temperature for that time point. The average temperatures of all time points are summarized to form a historical average temperature sequence. Based on this sequence, a very small number of extreme fluctuations in the average temperature are removed, and the median level of the remaining average temperature values ​​is the temperature equilibrium standard of the sintering furnace. This standard reflects the ideal temperature distribution level within the furnace under normal sintering conditions. The current temperature refers to the temperature data for each location within the furnace at the time point corresponding to the current sintering stage, extracted from the real-time collected clean temperature dataset. The temperature value at each location in the current temperature is compared with the temperature equilibrium standard. If the current temperature value is higher than the temperature equilibrium standard, it is recorded as a positive deviation; if it is lower than the standard, it is recorded as a negative deviation; if it is equal to the standard, it is recorded as no deviation. The deviation direction and actual magnitude at all locations are statistically analyzed to generate a temperature deviation result that includes both the overall deviation trend and local deviation details.

[0140] A comprehensive analysis of the temperature deviation results is conducted to clarify the overall characteristics of the deviation: if the overall deviation is positive, it indicates that the current furnace temperature is generally higher than the temperature equilibrium standard, requiring a reduction in the initial compensation power; if the overall deviation is negative, it indicates that the current furnace temperature is generally lower than the standard, requiring an increase in the initial compensation power; if only local deviations exist, the initial compensation power is adjusted according to the magnitude of the local deviation. The adjustment magnitude is determined based on the size of the deviation; the larger the deviation, the larger the adjustment. The specific correspondence is determined based on historical adjustment data, i.e., referring to the effective adjustment amounts under the same deviation magnitude in the past, to ensure the rationality of the adjustment. For positive deviations, the initial compensation power is subtracted from the adjustment amount corresponding to the deviation magnitude; for negative deviations, the initial compensation power is added to the adjustment amount corresponding to the deviation magnitude; for local deviations, the initial compensation power is adjusted for the heating equipment corresponding to the deviation area, while the initial compensation power remains unchanged for non-deviation areas. Through this adjustment process, the final power value that allows the furnace temperature to return to the temperature equilibrium standard is obtained, and this value is the power compensation amount for the sintering furnace.

[0141] The beneficial effects include: providing precise spatial basis for matching heating equipment and adjusting power by accurately locating the three-dimensional coordinates and volume of the temperature anomaly area; determining the corresponding heating equipment based on the three-dimensional coordinates ensures that power adjustments can be targeted to the anomaly area, avoiding ineffective adjustments; weighted integration of the adjusted heating power and thermal radiation efficiency ensures that the initial compensation power takes into account both heat output and transfer efficiency, improving the effectiveness of compensation; determining the temperature equilibrium standard based on historical temperature data ensures the rationality and reference value of the standard, and clearly understanding the temperature deviation in the furnace by comparing the current temperature with the standard; adjusting the initial compensation power according to the deviation results in a power compensation amount that can accurately compensate for the temperature deviation, allowing the temperature in the sintering furnace to quickly return to an equilibrium state, effectively ensuring the temperature stability of the rare earth magnet sintering process, improving the consistency of magnet product quality, and the entire process is clear in operation and logically rigorous, meeting the actual application needs of industrial production.

[0142] The optimized heating command generation module 106 is used to superimpose the power compensation amount and the reference power of the sintering furnace to generate the optimized heating command of the sintering furnace.

[0143] In this embodiment of the invention, when the optimized heating command generation module performs the superposition of the power compensation amount and the reference power of the sintering furnace to generate the optimized heating command for the sintering furnace, it is specifically used for:

[0144] According to the sintering process specifications corresponding to the sintering furnace, the reference power of the sintering furnace during the sintering stage is obtained;

[0145] Based on the compensation direction of the power compensation amount, the reference power is adjusted by increasing or decreasing the compensation amount to obtain the target heating power of the sintering furnace;

[0146] The location information of the temperature anomaly area is retrieved, and the target heating power is bound to the location information to obtain the heating area corresponding to the target heating power;

[0147] According to a predetermined instruction protocol format, the target heating power and the corresponding location information are integrated into the optimized heating instruction for the sintering furnace.

[0148] The sintering process specification for the sintering furnace is a standardized technical document formulated for the type of rare earth magnet currently being sintered. This document is compiled based on the material properties of rare earth magnets, target sintering performance, and industrial production practice data. It clearly specifies the process parameter requirements for each stage of the sintering process, including the standard heating power for each sintering stage. By retrieving this sintering process specification and finding the heating power requirement that perfectly corresponds to the current sintering stage of the furnace, this specified heating power value is a standard power that has been verified multiple times to ensure the sintering quality of the magnets. Furthermore, this power value matches the temperature requirements, holding time, and other process parameters of the current sintering stage without conflict or contradiction. The heating power value extracted from the specification is the reference power for the sintering furnace during the sintering stage.

[0149] The direction of power compensation is determined based on the previous temperature deviation results, and is clearly divided into two cases: increasing power and decreasing power. When the temperature deviation result is negative (i.e., the current temperature is lower than the temperature equilibrium standard), the compensation direction is to increase power; when the temperature deviation result is positive (i.e., the current temperature is higher than the temperature equilibrium standard), the compensation direction is to decrease power. The specific numerical characteristics of the reference power and the power compensation amount are obtained, and corresponding adjustment operations are performed according to the compensation direction. If the compensation direction is to increase power, the value corresponding to the reference power and the value corresponding to the power compensation amount are added together; the result is the adjusted power value. If the compensation direction is to decrease power, the value corresponding to the reference power is subtracted from the value corresponding to the power compensation amount; the result of the subtraction is the adjusted power value. This adjusted power value can accurately compensate for the deviation between the current temperature and the temperature equilibrium standard, ensuring that the furnace temperature returns to the ideal state. This value is the target heating power of the sintering furnace.

[0150] The location information of the temperature anomaly area was previously obtained through three-dimensional coordinate positioning, including the area's three-dimensional coordinate range, boundary position, and covered spatial area. This information is complete and accurate, clearly identifying the specific spatial location within the sintering furnace where the heating power needs adjustment. The complete location information of the temperature anomaly area is retrieved from the data storage unit, including key information such as the boundary coordinates of the length, width, and height dimensions, and the area's volume. This retrieved location information is then bound one-to-one with the target heating power. During the binding process, precise matching is performed using location identifiers to ensure that the target heating power is only associated with the location information of this temperature anomaly area and does not become confused with the location information of other normal areas. The resulting association data clearly identifies which spatial area needs to be heated at which power. The spatial area corresponding to this association data is the heating area corresponding to the target heating power, ensuring complete consistency between the heating area and the temperature anomaly area.

[0151] The predetermined command protocol format is a standardized data format that the sintering furnace heating control system can recognize and execute. This format predefines the core fields required for the command, including command type, target heating power, heating area location information, command execution priority, execution start time, and other fixed content. The order and data representation of each field are clearly defined to ensure that the heating control system can quickly parse and execute the data after receiving it. The specific numerical characteristics of the target heating power are expressed according to the requirements of the "target heating power" field in the protocol format, ensuring that the expression conforms to the format specification. The location information of the heating area, including the three-dimensional coordinate range and boundary position, is presented in a structured manner according to the requirements of the "heating area location information" field, without omitting any key location data. The expressed target heating power and location information are sequentially filled into the corresponding fields of the predetermined command protocol format, while supplementing necessary fields such as command type "optimized heating", execution priority "highest", and execution start time "immediate", ensuring that all field information is complete, accurate, and conforms to the format requirements. The completed protocol format data is integrated into a complete command, which is the sintering furnace optimized heating command, which can be directly sent to the heating control system and accurately executed.

[0152] The beneficial effects are as follows: obtaining the reference power through the sintering process specification ensures that the initial setting of the heating power meets the standardized requirements of magnet sintering, providing a reliable basis for subsequent adjustments; the reference power is precisely increased or decreased based on the compensation direction of the power compensation amount, enabling the target heating power to specifically compensate for temperature deviations and quickly restore the temperature balance in the furnace; binding the target heating power with the location information of the temperature anomaly area clarifies the precise range of the heating area, avoids ineffective heating of normal areas, and improves power utilization efficiency; and the optimized heating commands are integrated according to the predetermined command protocol format, ensuring the standardization and compatibility of the commands, which can be directly recognized and executed by the heating control system, realizing the automated and precise adjustment of the heating power, effectively ensuring the temperature stability of the rare earth magnet sintering process, further improving the quality consistency and production efficiency of magnet products. The entire process conforms to the actual operation logic of industrial production, is highly repeatable, and is easy to promote and apply.

[0153] like Figure 2 As shown, this embodiment also provides a production line, which may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as a rare earth magnet intelligent sintering control system.

[0154] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the production line, connecting various components of the entire production line via various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., executing a rare-earth magnet intelligent sintering control system) and calls data stored in the memory 11 to perform various functions of the production line and process data.

[0155] The memory 11 includes at least one type of medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the production line, such as a portable hard drive on the production line. In other embodiments, the memory 11 can be an external storage device of the production line, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the production line. Furthermore, the memory 11 can include both internal storage units and external storage devices of the production line. The memory 11 can be used not only to store application software and various types of data installed on the production line, such as the code of a rare earth magnet intelligent sintering control system, but also to temporarily store data that has been output or will be output.

[0156] The communication bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0157] The communication interface 13 is used for communication between the aforementioned production line and other production lines, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, Bluetooth interface, etc.), typically used to establish communication connections between this production line and other production lines. The user interface may be a display, an input unit (such as a keyboard), or optionally, a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed on the production line and to display a visual user interface.

[0158] The figure only shows a production line with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the production line and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0159] For example, although not shown, the production line may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The production line may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0160] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0161] The rare-earth magnet intelligent sintering control system stored in the memory 11 of the production line is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0162] Real-time temperature data of rare earth magnets at different locations inside the sintering furnace are collected to generate temperature distribution information reflecting the heating environment of the rare earth magnets inside the sintering furnace.

[0163] Based on the temperature distribution information, the real-time temperature gradient at different locations within the sintering furnace is evaluated, and the real-time temperature gradient is compared with a preset gradient threshold to identify abnormal temperature regions within the sintering furnace that pose a risk of cracking.

[0164] Based on the continuous temperature data sequence of the temperature anomaly region, fit the temperature change rate of the temperature anomaly region;

[0165] Based on the temperature change rate and the critical parameters of material phase transformation of the rare earth magnet in the current sintering stage, the heating power in the temperature anomaly region is adjusted.

[0166] Based on the heating power, directional thermal energy compensation is performed on the abnormal temperature region to obtain the power compensation amount of the sintering furnace;

[0167] The power compensation amount is superimposed with the reference power of the sintering furnace to generate an optimized heating command for the sintering furnace.

[0168] Specifically, the specific implementation method of the processor 10 for the above instructions can be referred to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, and will not be repeated here.

[0169] Furthermore, if the integrated modules / units of the system are implemented as software functional units and sold or used as independent products, they can be stored in a medium. The medium can be volatile or non-volatile. For example, the medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM). It will be apparent to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the invention.

[0170] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A rare earth magnet intelligent sintering control system, characterized in that, The system includes a temperature data acquisition module, a temperature gradient evaluation module, a temperature change rate fitting module, a heating power adjustment module, a directional thermal energy compensation module, and an optimized heating command generation module, wherein: The temperature data acquisition module is used to collect real-time temperature data of rare earth magnets at different locations in the sintering furnace, so as to generate temperature distribution information reflecting the heating environment of rare earth magnets in the sintering furnace. The temperature gradient assessment module is used to assess the real-time temperature gradient at different locations within the sintering furnace based on the temperature distribution information, and compare the real-time temperature gradient with a preset gradient threshold to identify abnormal temperature regions within the sintering furnace that pose a risk of cracking. The temperature change rate fitting module is used to fit the temperature change rate of the temperature anomaly region based on the continuous temperature data sequence of the temperature anomaly region, wherein the calculation formula for the temperature change rate is as follows: ； In the formula, This indicates the rate of temperature change. This indicates the number of data points in the continuous temperature data sequence within a fixed sliding window. This indicates the first continuous temperature data sequence. The timestamp of each data point This indicates the first continuous temperature data sequence. Temperature values ​​of each data point; The heating power adjustment module is used to adjust the heating power in the temperature anomaly region based on the temperature change rate and the critical parameters of the material phase transformation of the rare earth magnet in the current sintering stage. Specifically, it is used for: Based on the critical value of thermal stress of the rare earth magnet, the critical parameters of material phase transformation of the rare earth magnet in the current sintering stage are determined. The difference between the temperature change rate and the critical phase transformation parameter of the material is compared to obtain the comparison result between the temperature change rate and the critical phase transformation parameter of the material; Based on the comparison results, the heating power adjustment amount for the temperature anomaly area is determined; Adjust the heating power of the temperature abnormal area according to the heating power adjustment amount; The directional thermal energy compensation module is used to perform directional thermal energy compensation on the temperature anomaly region based on the heating power, to obtain the power compensation amount of the sintering furnace, specifically for: The three-dimensional coordinates and volume of the temperature anomaly region within the sintering furnace were determined. Based on the three-dimensional coordinates, determine the heating equipment inside the sintering furnace corresponding to the temperature anomaly region; The adjusted heating power and the thermal radiation efficiency of the heating equipment are weighted and fused to obtain the initial compensation power of the sintering furnace; Based on the historical temperature data of the sintering furnace, the temperature equalization standard of the sintering furnace is determined, and the current temperature of the sintering furnace is compared with the temperature equalization standard to obtain the temperature deviation result of the sintering furnace. Based on the temperature deviation, the initial compensation power is adjusted to obtain the power compensation amount of the sintering furnace; The optimized heating command generation module is used to superimpose the power compensation amount and the reference power of the sintering furnace to generate the optimized heating command for the sintering furnace.

2. The intelligent sintering control system for rare earth magnets as described in claim 1, characterized in that, When the temperature data acquisition module collects real-time temperature data of rare earth magnets at different locations within the sintering furnace to generate temperature distribution information reflecting the heating environment of the rare earth magnets within the sintering furnace, it is specifically used for: The real-time temperature data of rare earth magnets at corresponding locations is collected by temperature sensors installed inside the sintering furnace. By removing outlier data from the real-time temperature dataset, a clean temperature dataset for the sintering furnace is obtained. Based on the location information in the clean temperature dataset, the clean temperature dataset is integrated to generate temperature distribution information reflecting the heating environment of the rare earth magnets inside the sintering furnace.

3. The intelligent sintering control system for rare earth magnets as described in claim 1, characterized in that, The temperature gradient assessment module, when performing the evaluation of real-time temperature gradients at different locations within the sintering furnace based on the temperature distribution information, and comparing these real-time temperature gradients with preset gradient thresholds to identify temperature anomaly regions within the sintering furnace that pose a risk of cracking, is specifically used for: Integrate the temperature values ​​and coordinates corresponding to different locations in the temperature distribution information to establish a location-temperature association dataset for the sintering furnace; Based on the location temperature association dataset, the temperature difference between adjacent locations in the sintering furnace is determined, and the temperature difference set of the sintering furnace is obtained. Based on the set of temperature differences, the temperature gradient state corresponding to different locations in the sintering furnace is defined, and the real-time temperature gradient in the sintering furnace is obtained. The real-time temperature gradient is compared with the preset gradient threshold one by one to mark the location range in the sintering furnace that exceeds the preset gradient threshold, thereby obtaining the temperature anomaly area in the sintering furnace.

4. The intelligent sintering control system for rare earth magnets as described in claim 3, characterized in that, When the temperature gradient assessment module performs the operation of defining the temperature gradient state corresponding to different locations within the sintering furnace based on the set of temperature differences, and obtaining the real-time temperature gradient within the sintering furnace, it is specifically used for: Based on the set of temperature differences and the location temperature association dataset, the adjacent position pairs corresponding to the temperature differences are determined to generate the difference position correspondence table in the sintering furnace; The internal spatial layout parameters of the sintering furnace are mapped to the difference position correspondence table to obtain the spatial spacing attribute of the adjacent position pairs, so as to generate the spacing difference association data in the sintering furnace. The spacing difference correlation data is matched with the preset gradient state division standard to obtain the temperature gradient state corresponding to different positions in the sintering furnace. Based on the temperature gradient state, the temperature gradient attributes corresponding to different locations within the sintering furnace are determined to obtain the real-time temperature gradient within the sintering furnace.

5. The intelligent sintering control system for rare earth magnets as described in claim 1, characterized in that, When the temperature change rate fitting module performs the task of fitting the temperature change rate of the temperature anomaly region based on the continuous temperature data sequence of the temperature anomaly region, it is specifically used for: By associating the temperature anomaly area with the temperature sensor inside the sintering furnace, the temperature sensor corresponding to the temperature anomaly area is determined. Using a fixed sliding window, the temperature sensor collects temperature data of the temperature anomaly area at different time points to form the original temperature data sequence of the temperature anomaly area. After removing the pulse interference data from the original temperature data sequence, a stable temperature data sequence for the temperature anomaly region is obtained. Add corresponding timestamps to the temperature data in the stable temperature data sequence to obtain a continuous temperature data sequence of the temperature anomaly region. Observe the continuous temperature data sequence and record the correspondence between temperature changes at adjacent time points and time intervals; Based on the aforementioned correspondence, the rate of temperature change in the temperature anomaly region is fitted.

6. The intelligent sintering control system for rare earth magnets as described in claim 1, characterized in that, When the optimized heating command generation module performs the superposition of the power compensation amount and the reference power of the sintering furnace to generate the optimized heating command for the sintering furnace, it is specifically used for: According to the sintering process specifications corresponding to the sintering furnace, the reference power of the sintering furnace during the sintering stage is obtained; Based on the compensation direction of the power compensation amount, the reference power is adjusted by increasing or decreasing the compensation amount to obtain the target heating power of the sintering furnace; The location information of the temperature anomaly area is retrieved, and the target heating power is bound to the location information to obtain the heating area corresponding to the target heating power; According to a predetermined instruction protocol format, the target heating power and the corresponding location information are integrated into the optimized heating instruction for the sintering furnace.

7. A production line comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement a rare earth magnet intelligent sintering control system according to any one of claims 1 to 6.

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