On-line detection hybrid processing of soft magnetic ferrite material

Abstract

The application discloses an on-line detection and mixing processing technology of soft magnetic ferrite material, which comprises the following steps: initially dosing and mixing raw materials, and reserving compensation materials; obtaining detection material flow from multiple spatial positions of the mixed materials, determining overall formula deviation and spatial mixing deviation of target components; when an abnormality is detected, implementing diagnostic mixing disturbance without changing the overall composition of the materials, identifying spatial mixing abnormality or actual formula abnormality according to deviation changes before and after the disturbance; for the spatial mixing abnormality, adjusting material migration mode according to spatial deviation decay state; for the actual formula abnormality, implementing compensation in batches after the spatial deviation reaches the allowable range, and determining subsequent compensation amount according to actual detection responses before and after the first compensation; and determining a mixing end point through overall formula deviation, spatial mixing deviation and continuous detection stable state. The application can reduce false compensation caused by spatial uneven distribution, and improve consistency of the soft magnetic ferrite material mixing formula and spatial distribution.

Description

Technical Field

[0001] This invention relates to the field of magnetic materials, specifically to an online detection and mixing process for soft magnetic ferrite materials. Background Technology

[0002] Soft magnetic ferrite materials are typically made by mixing various raw materials containing iron, manganese, zinc, nickel, and / or copper according to a target formula. The mixing state of the raw materials affects subsequent pre-calcination, grinding, granulation, molding, and sintering processes. In existing production processes, raw materials are usually added according to a preset feeding ratio, and then mixed at a fixed speed and time. Sampling and testing are then used to determine whether the material composition meets the requirements. Due to differences in particle size, density, flowability, and surface condition among different raw materials, local enrichment, weak exchange regions, or uneven spatial distribution can easily occur during the mixing process. Therefore, when a component deviation is observed at a certain detection location, the deviation may originate from the actual formula deviation of the entire batch of materials, or it may be caused only by uneven distribution of materials in a localized area. Existing methods are unable to accurately distinguish between the two sources of anomaly.

[0003] When deviations occur in the test results, existing methods typically address them by extending the mixing time, changing the mixing state, or directly adding the corresponding raw materials. On the one hand, adding materials directly without identifying the source of the anomaly may misidentify the detection deviation caused by local enrichment as an overall formulation deviation, leading to overcompensation. On the other hand, simply extending the mixing time cannot determine whether the current material migration mode still has effective homogenization capabilities. After the material forms a stable circulation area or an area with insufficient exchange, continuing to use the original mixing method may not be able to further improve spatial uniformity. In addition, the theoretical compensation amount and the actual component changes may also be affected by powder adhesion to the wall, conveying stagnation, dispersion and propagation, and differences in the state of different batches of materials. Adding materials all at once according to a fixed compensation relationship is prone to undercompensation or overcompensation. Therefore, it is necessary to provide an online detection and mixing process for soft magnetic ferrite materials that can identify the source of the anomaly, adjust the material migration mode according to the actual mixing state, and iteratively correct based on the actual compensation response of the current batch. Summary of the Invention

[0004] The purpose of this invention is to provide an online detection and mixing process for soft magnetic ferrite materials. This invention can reduce false compensation caused by uneven spatial distribution and improve the consistency of the mixing formula and spatial distribution of soft magnetic ferrite materials.

[0005] To achieve the above objectives, the present invention proposes the following technical solution: an online detection and mixing process for soft magnetic ferrite materials, comprising the following steps: S1. Prepare the raw materials according to the target formula of the soft magnetic ferrite material to be processed. Add the raw materials to the mixing equipment for initial mixing and reserve the compensation material for subsequent component correction. S2. During the mixing process, the test flow is obtained from multiple different spatial locations of the mixed materials, and the target components in each test flow are detected online. Based on the detection results of multiple spatial locations, the overall formulation deviation and spatial mixing deviation of each target component are determined. S3. When the overall formula deviation or spatial mixing deviation exceeds the corresponding allowable range, the mixture is subjected to diagnostic mixing disturbance without the addition of compensating materials, and the detection results of multiple different spatial locations are obtained again. Based on the changes in the overall formula deviation and spatial mixing deviation before and after the diagnostic mixing disturbance, the current abnormality is identified as either a spatial mixing abnormality or an actual formula abnormality. S4. When the spatial mixing abnormality is identified, the mixture is homogenized and mixed. The current mixing method is judged to eliminate the spatial mixing deviation based on the attenuation state of the spatial mixing deviation during continuous detection. When the elimination ability decreases, the migration mode of the material is changed until the spatial mixing deviation reaches the allowable range. S5. When the spatial mixing deviation reaches the allowable range but the overall formula deviation still exceeds the allowable range, the target component with actual formula abnormality is compensated in stages. First, a first compensation less than the current theoretical compensation amount is performed. After the mixture after the first compensation reaches the allowable range of spatial mixing deviation again, the actual compensation response of the current batch of materials to the corresponding compensation material is determined according to the online detection results before and after the first compensation, and the subsequent compensation amount is determined according to the actual compensation response. S6. During the subsequent compensation and mixing process, continuous online detection at multiple locations is carried out. When the overall formulation deviation and spatial mixing deviation of each target component continuously meet the corresponding allowable range and the component changes in adjacent detection cycles reach the stable condition, the mixing process of the current batch of soft magnetic ferrite materials is terminated.

[0006] Furthermore, in this invention, in step S1, the raw materials corresponding to the target formula are divided into a main feeding part and a compensation feeding part. The main feeding part is used to form an initial mixture that is close to the target formula, and the compensation feeding part is retained in the initial mixing stage and not entirely added to the mixing equipment. For each target component, a component compensation material is prepared to increase the relative content of the corresponding target component, and a dilution correction material is prepared to decrease the relative content of the corresponding target component. In the dilution correction material, the content of the target component to be reduced is lower than its content in the target formulation. The remaining main components are prepared in proportions corresponding to the target formulation, so that the actual formulation anomaly can be corrected along the direction of increasing or decreasing component content.

[0007] Furthermore, in this invention, in S2, the multiple different spatial positions include at least positions located in different radial positions, different height positions, and / or different material circulation paths, so that each detection position corresponds to a different material space region; The target component content and moisture content of each test material stream are detected separately, and the target component detection results are uniformly converted into dry basis component content based on the moisture content at the corresponding detection location. The average component content of the target component is determined based on the dry basis component content at multiple detection locations. The overall formulation deviation is determined based on the difference between the average component content and the corresponding target component content in the target formulation. The spatial mixing deviation is determined based on the difference between the maximum and minimum dry basis component content of the same target component at different detection locations.

[0008] Furthermore, in this invention, the diagnostic mixing disturbance in S3 includes: keeping the material composition and total amount of the current batch of material unchanged, stopping the addition of component compensation material and dilution correction material, and changing the spatial migration state of the mixed material within a preset diagnostic cycle; Before and after diagnosing the mixing disturbance, the average component content and spatial mixing deviation of each target component are determined respectively. The decrease in spatial mixing deviation before and after diagnosing the mixing disturbance is used to characterize the response of spatial distribution to the diagnosing mixing disturbance. The change in average component content before and after diagnosing the mixing disturbance is used to characterize the stability of the overall composition of the mixture. Thus, the source of the anomaly can be identified by the difference between the change in spatial distribution and the change in overall composition.

[0009] Furthermore, in this invention, in step S3, when the spatial mixing deviation of the corresponding target component decreases and the average component content remains within a preset stable range after diagnosing the mixing disturbance, the corresponding anomaly is determined as a spatial mixing anomaly. When the spatial mixing deviation reaches the allowable range after the diagnosis of mixing disturbance, and the average component content of the corresponding target component continues to deviate from the corresponding target component content in the target formulation, the corresponding anomaly is identified as an actual formulation anomaly. When both spatial mixing deviation and overall formulation deviation exceed the corresponding allowable range, the current state is prioritized as the spatial interference state to be eliminated. Component compensation based directly on the current overall formulation deviation is prohibited. The overall formulation deviation is re-determined after the spatial mixing deviation reaches the allowable range.

[0010] Furthermore, in this invention, in step S4, the homogenization mixing is divided into multiple consecutive short mixing cycles, and after each short mixing cycle, multi-position online detection is performed again. The degree of spatial deviation attenuation is determined based on the proportional relationship between the decrease in spatial mixing deviation corresponding to adjacent short mixing cycles and the spatial mixing deviation of the previous short mixing cycle. When the degree of spatial deviation attenuation indicates that the spatial mixing deviation continues to decrease effectively, the current material migration mode is maintained; when the spatial mixing deviation still exceeds the allowable range and the degree of spatial deviation attenuation decreases to the preset attenuation condition for several consecutive short mixing cycles, it is determined that the current material migration mode has entered an inefficient homogenization state, and the material migration mode is changed.

[0011] Furthermore, in this invention, changing the material migration method includes changing the exchange path between different spatial areas of the mixture, so that material areas that did not exchange sufficiently under the previous material migration method can re-establish material exchange. The method of changing the material migration is achieved by at least one of the following: changing the mixing direction, changing the mixing speed, changing the material pick-up position of the circulating material flow, changing the return position of the circulating material flow, and changing the direction of the circulating material flow. After changing the material migration method, continue to perform short mixing cycles and multi-location online detection, and determine whether the changed material migration method has restored the ability to effectively eliminate spatial mixing deviation based on the re-obtained spatial mixing deviation.

[0012] Furthermore, in this invention, in step S5, the theoretical compensation amount of the corresponding target component is determined based on the current material quantity of the mixture, the target content of the target component, and the average component content obtained from online detection at multiple locations. A portion of the theoretical compensation amount is used as the first compensation amount to perform the first compensation. After the first compensation is completed, the compensation is stopped and the added compensation material is mixed and propagated. After the spatial mixing deviation reaches the allowable range again after the first compensation, the actual compensation response of the current batch of materials to the corresponding compensated material is determined according to the correspondence between the average component content change before and after the first compensation and the first compensation amount, so as to use the actual compensation response of the current batch of materials to correct the theoretical compensation relationship.

[0013] Furthermore, in this invention, the next compensation amount is determined based on the remaining overall formula deviation after the first compensation and the actual compensation response, and the next compensation amount retains a margin for subsequent corrections. After each compensation is completed, mixing propagation and multi-location online detection are performed first. After the spatial mixing deviation returns to the allowable range, the actual compensation response of the corresponding target component is updated based on the change in average component content before and after this compensation and the actual amount of compensation material added this time. The amount of compensation for the next time is determined based on the updated actual compensation response. When the content of the target component is lower than the target content, the corresponding component compensation material is called; when the content of the target component is higher than the target content, the corresponding dilution correction material is called, so as to form a two-way iterative correction process based on the actual compensation response of the current batch.

[0014] Furthermore, in this invention, in step S6, the overall formulation state, spatial mixing state, and time stability state of each target component are simultaneously determined for multiple consecutive detection cycles. When the overall formulation deviation of all target components is within the corresponding allowable range, the spatial mixing deviation of all target components is within the corresponding allowable range, and the average component content change of each target component between adjacent detection cycles is less than the preset stable change amount, the current batch is determined to have reached the mixing endpoint. When the overall formulation deviation reaches the allowable range while the spatial mixing deviation exceeds the allowable range, return to perform spatial homogenization mixing; when the spatial mixing deviation reaches the allowable range while the overall formulation deviation exceeds the allowable range, return to perform component compensation; when both the overall formulation deviation and the spatial mixing deviation exceed the corresponding allowable range, return to perform diagnostic mixing disturbance, so that the mixing process selects between the spatial homogenization path and the formulation compensation path according to the anomaly source identification result, until the mixing endpoint is reached.

[0015] Beneficial effects: The technical solution of this application has the following technical effects: This invention utilizes multi-location online detection of mixed materials to determine the overall formulation deviation and spatial mixing deviation of the target components. Upon detecting anomalies, a diagnostic mixing disturbance is first implemented without altering the overall composition of the materials. The source of the anomaly is identified based on the changes in spatial mixing deviation and overall formulation deviation before and after the disturbance. This allows for the differentiation between detection anomalies caused by local enrichment or uneven spatial distribution and deviations in the actual feed ratio. This avoids directly compensating for components based on local detection results before the materials are fully homogenized, reducing the possibility of erroneous feeding and further deviations from the formulation.

[0016] Simultaneously, this invention determines the homogenization capability of the current material migration method based on the attenuation state of spatial mixing deviation during continuous mixing cycles. When the original material migration method's ability to eliminate spatial deviation decreases, the material exchange path is changed, allowing insufficiently exchanged areas to re-participate in material migration. After the spatial mixing deviation meets the requirements, a limited initial compensation is used to obtain the actual compensation response of the current batch of materials, and the subsequent compensation amount is determined accordingly. This reduces the impact of powder adhesion to walls, conveying stagnation, propagation delay, and batch differences on compensation accuracy. Finally, the mixing endpoint is determined by jointly considering the overall formulation state, spatial mixing state, and continuous monitoring of the stable state, ensuring that the final mixing state simultaneously considers formulation accuracy and spatial uniformity, while reducing ineffective mixing and compensation overshoot.

[0017] It should be understood that all combinations of the foregoing concepts and the additional concepts described in more detail below can be considered part of the inventive subject matter of this disclosure, provided that such concepts do not contradict each other.

[0018] The foregoing and other aspects, embodiments, and features of the teachings of the present invention will be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the invention, such as features and / or beneficial effects of exemplary embodiments, will become apparent from the following description or may be learned through practice of specific embodiments according to the teachings of the present invention. Attached Figure Description

[0019] The accompanying drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component shown in the various figures may be denoted by the same reference numeral. For clarity, not every component is labeled in each figure. Embodiments of various aspects of the invention will now be described by way of example and with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the process flow of the present invention. Detailed Implementation

[0020] The technical solution of the present invention will be further described below with reference to specific embodiments. It should be noted that the following embodiments are only used to illustrate the technical solution of the present invention and are not intended to limit the scope of protection of the present invention. Those skilled in the art can make adaptive adjustments to the corresponding process parameters according to the specific grade of the soft magnetic ferrite material, the type of raw material, and the specifications of the mixing equipment without departing from the technical concept of the present invention.

[0021] This embodiment takes Mn-Zn based soft magnetic ferrite material as an example. The main raw materials include Fe2O3, Mn3O4, and ZnO, and the normalized mass ratio of the components on a dry basis is used as the evaluation basis for the mixed state and formulation state. In the target formulation, the target mass ratio of Fe2O3 is 70.00%, the target mass ratio of Mn3O4 is 23.30%, and the target mass ratio of ZnO is 6.70%. Depending on the actual material grade, corresponding trace additives can also be added. These trace additives can be those commonly used in soft magnetic ferrite materials of the corresponding grade in this field.

[0022] This embodiment employs a powder mixing device with a main mixing zone and a circulating material channel. The feed end and return end of the circulating material channel are connected to different positions in the main mixing zone, and the feeding position, return position, and circulation direction of the circulating material flow are changed by a reversing valve or multiple switchable feed and discharge branches, thereby changing the material exchange path between different spatial zones.

[0023] Three online detection positions, A, B, and C, are set up. Detection position A corresponds to the upper outer perimeter area of ​​the mixture, detection position B corresponds to the main mixing area, and detection position C corresponds to the lower circulation area. During online detection, a portion of the material flow is obtained from the corresponding position for detection, and the material after detection is returned to the mixing equipment.

[0024] Component detection employs an online detection unit capable of obtaining the content of Fe, Mn, and Zn elements and converting them to the corresponding oxide content. This embodiment uses online X-ray fluorescence detection. Moisture detection uses near-infrared moisture detection. Before use, the online detection equipment is calibrated using a standard sample with a composition similar to the powder to be tested, and the state of the detection layer, detection distance, and data acquisition method are kept consistent throughout different detection processes.

[0025] The Fe2O3, Mn3O4 and ZnO contents in the following tables are all mass percentages after moisture content correction and dry basis normalization.

[0026] Example 1

[0027] This embodiment provides an online detection and mixing process for soft magnetic ferrite materials, including the following steps.

[0028] S1, Initial ingredient preparation and compensation material reservation Fe2O3, Mn3O4, and ZnO are weighed separately according to the target formula. During the initial feeding, not all raw materials used to achieve the final target composition are added to the mixing equipment at once, but the raw materials are divided into a main feeding part and a compensation feeding part for subsequent adjustments.

[0029] In this embodiment, the main feed includes 69.45 kg of Fe2O3, 23.10 kg of Mn3O4 and 6.60 kg of ZnO, with a total mass of 99.15 kg.

[0030] Simultaneously, Fe2O3, Mn3O4, and ZnO compensators were set up separately. When the content of the target component was lower than the target value, the corresponding enrichment compensator was used for correction; when the content of the target component was higher than the target value, the corresponding dilution compensator was used for correction.

[0031] In the dilution correction material, the content of the target component to be reduced is lower than the content of the target component in the target formulation, and the other main components are configured according to the relative proportions in the target formulation. In this way, while reducing the relative content of the corresponding target component, the impact on the proportions of other target components is reduced.

[0032] After the main material is fed in, the mixing equipment is started for initial mixing. In this embodiment, the initial mixing time is 8 minutes. This stage allows the newly added powders to undergo preliminary spatial migration, thereby reducing large-scale stratification formed during the feeding process. However, the initial mixing time itself is not used as the end condition for the entire mixing process.

[0033] This step allows for a certain margin of error in formula adjustment, so that if subsequent online testing confirms a real formula deviation, the overall composition can be adjusted in both directions by adding compensating agents or diluting correction agents.

[0034] S2. Multi-location online detection and determination of overall formulation deviation and spatial mixing deviation. After initial mixing is completed, while the mixing equipment is running, the test streams are obtained from detection positions A, B and C respectively, and the content of the target component and the moisture content in each test stream are detected.

[0035] When online component detection results are expressed as wet basis mass fraction, they are converted to dry basis component content based on the moisture content at the corresponding location:

[0036] in, Indicates the first The first detection location The dry basis content of the target component; Indicates the first The first detection location directly detected at the first detection position The wet basis content of the target component; Indicates the first Each detection location corresponds to the moisture content of the material flow being detected; Indicates the spatial detection location; This indicates the target component being tested.

[0037] Further, the average component content at multiple locations for the same target component was determined based on the dry basis content at each detection location:

[0038] in, Indicates the first Multi-site average dry basis content of the target components; Indicates the first The first detection location The dry basis content of the target component; This indicates the number of spatial detection locations participating in this evaluation, which is 3 in this embodiment; Indicates the detection location sequence number; Indicates the target component.

[0039] The overall formulation deviation is determined based on the difference between the average content at multiple locations and the target formulation content.

[0040] in, Indicates the first Overall formulation deviation of the target component; Indicates the first Multi-site average dry basis content of the target components; Indicates the first in the target formulation The target content of the target component; when A positive value indicates that the corresponding component is generally high. A negative value indicates that the corresponding component is generally low.

[0041] Spatial mixing bias is determined based on the maximum and minimum dry basis content of the same target component at different detection locations:

[0042] in, Indicates the first Spatial mixing bias of the target components; Indicates the first of multiple detection locations Maximum dry basis content of the target component; Indicates the first of multiple detection locations Minimum dry basis content of the target component; This indicates the target content of the corresponding target component in the target formulation.

[0043] In this embodiment, the allowable range for overall formula deviation is set to an absolute value of no more than 0.20%, and the allowable range for spatial mixing deviation is set to no more than 0.60%. The corresponding allowable ranges can be adjusted according to the product grade, the repeatability of the testing equipment, and the degree to which subsequent sintering affects formula fluctuations.

[0044] The detection results after initial mixing are shown in Table 1.

[0045] Table 1 Initial multi-location detection results

[0046] As shown in Table 1, there are significant differences in component distribution among the three locations. The average ZnO content is lower than the target content, but there are also large differences in ZnO content across different spatial locations. Therefore, instead of directly feeding based on the average ZnO content, a diagnostic mixing stage is initiated.

[0047] S3. Identify the source of abnormality through non-feeding diagnostic mixing. When the overall formulation deviation or spatial mixing deviation exceeds the allowable range, close the addition channels of each compensating material and dilution correction material, and implement diagnostic mixing disturbance without changing the overall composition of the current batch.

[0048] In this embodiment, the diagnostic mixing time is 2 minutes. During the diagnostic mixing process, the material flow direction in the circulating material channel is changed by the reversing valve, so that the material flow that originally circulates from the lower region to the upper region is temporarily changed to circulate from the upper region to the lower region, thereby changing the spatial migration state of the material, but without adding new raw materials.

[0049] After the diagnostic mixture was completed, tests were performed again at positions A, B, and C. The test results are shown in Table 2.

[0050] Table 2. Diagnostic results from multiple locations after mixing

[0051] The degree of response of spatial deviation to diagnostic mixing is determined based on the spatial mixing deviation before and after diagnostic mixing:

[0052] in, Indicates the first The degree of reduction in spatial bias of the target components after diagnostic mixing; Indicates the first diagnosis before mixed diagnosis Spatial mixing bias of the target components; Indicates the diagnosis after mixing. Spatial mixing bias of the target components; superscript Indicates the state before the diagnosis of mixed symptoms; superscript This indicates the state after the diagnosis is mixed.

[0053] As shown in Tables 1 and 2, the compositional differences between different spatial locations decreased significantly after the diagnostic mixing, while the average composition at the three locations remained relatively stable. For ZnO, the spatial differences decreased significantly, but the average content remained at approximately 6.66%.

[0054] Since no materials that could alter the overall composition were added or removed during the diagnostic mixing process, the changes in spatial positions were mainly caused by powder redistribution, while the portion of the average composition that consistently deviated from the target value reflected the actual deviation of the overall composition of the current batch.

[0055] When both spatial mixing deviation and overall formulation deviation exceed the allowable range, this embodiment prioritizes handling spatial mixing deviation and does not perform precise formulation compensation until the spatial mixing deviation reaches the allowable range.

[0056] S4. Implement homogenization mixing based on the spatial deviation attenuation state. For materials identified as having spatial mixing anomalies by S3, the homogenization process is divided into multiple consecutive short mixing cycles. In this embodiment, each short mixing cycle is 2 minutes, and a multi-location online detection is performed after each short mixing cycle is completed.

[0057] The degree of spatial deviation attenuation is determined based on the maximum spatial mixing deviation between two adjacent detection cycles:

[0058] in, Indicates the first The degree of spatial deviation decay in a short mixing cycle; This indicates the maximum spatial mixing deviation in the previous detection cycle; This indicates the maximum spatial mixing deviation in the current detection cycle; Indicates the short mixing cycle number.

[0059] In this embodiment, the maximum spatial mixing deviation after diagnostic mixing is approximately 1.04%. After maintaining the original homogenized material migration method and continuing short-cycle mixing, the maximum spatial mixing deviation changes sequentially to approximately 0.91%, 0.84%, and 0.80%.

[0060] Correspondingly, the rate of decrease in spatial deviation gradually decreases. When the spatial deviation decay rate corresponding to two consecutive short mixing cycles is less than 10%, while the current spatial mixing deviation is still greater than 0.60%, it is determined that the current material migration mode has entered an inefficient homogenization state.

[0061] At this point, the material pick-up and return positions are switched, allowing the previously weaker material exchange area to re-establish material exchange with the main mixing area. After changing the material migration path, a short mixing cycle is performed, reducing the maximum spatial mixing deviation to approximately 0.45%.

[0062] The test results after completing the above homogenization process are shown in Table 3.

[0063] Table 3. Detection results after spatial homogenization.

[0064] At this point, the spatial mixing deviation of each target component is within the allowable range, but the average content of ZnO at multiple locations is still lower than the target content of 6.70%. Therefore, it is determined that there is an actual negative deviation in the ZnO formulation, and the formulation compensation stage is entered.

[0065] S5. Implement phased compensation based on the actual compensation response of the current batch. Once the spatial mixing deviation reaches the allowable range, the theoretical compensation amount is determined based on the current material quality, the average content of the target component, and the target content.

[0066] For positive compensation using compensating material rich in the corresponding target component, the theoretical compensation amount is determined according to the following formula:

[0067] in, Indicates the first The theoretical compensation mass of the compensation material corresponding to the target component; This indicates the total mass of material in the mixing equipment before compensation was performed; Indicates the first in the target formulation Target mass fraction of the target component; Indicates the first before compensation Multi-position average mass fraction of target components; Indicates the first in the compensation material The actual mass fraction of the target component; superscript This represents the theoretical value calculated based on the material mass balance relationship.

[0068] In this embodiment, ZnO compensation material with a ZnO content of not less than 99.5% is used. Based on the actual online detection results (unrounded) and the current total mass of the material, the theoretical ZnO compensation amount is approximately 46g.

[0069] In this embodiment, instead of adding the entire theoretical compensation amount at once, 20.0g of ZnO compensation material is added first as the initial compensation amount. Immediately after the first compensation is completed, the feeding is stopped, and a 2-minute propagation mixing process is initiated to allow the newly added ZnO to migrate to different spatial regions.

[0070] Once the spatial mixing deviation returns to the allowable range, the actual compensation response for the current batch is determined based on the change in average content at multiple locations before and after the first compensation.

[0071] in, Indicates the current batch for the first... The actual compensation response coefficient of the compensation material; This indicates the first compensation and remixing. The average content of the target components; Indicates the first compensation before the The average content of the target components; This indicates the mass of the first batch of compensating material actually added; superscript Indicates the state after compensation; superscript This indicates the state before compensation; superscript This indicates the first compensation.

[0072] The amount of compensation for the next step is determined based on the remaining formula deviation and the actual compensation response coefficient after the first compensation.

[0073] in, Indicates the first The quality of the compensation material required for this compensation; Indicates the compensation convergence coefficient; Indicates the first The target content of the target component; Indicates completion of the first The average component content after secondary compensation and re-reaching a spatially homogeneous state; This indicates the actual compensation response coefficient determined or updated based on the completed compensation process; This indicates the sequence number of the compensation cycle that has been completed.

[0074] In this embodiment, the compensation convergence coefficient is set to 0.70. After the first compensation and remixing, the average ZnO content at multiple sites increased from approximately 6.66% to approximately 6.68%. Based on the remaining deviation and the actual compensation response of the first compensation, the amount of the second compensation was calculated, and approximately 18.5g of ZnO was added for the second time.

[0075] After the second addition, propagation mixing is performed for another 2 minutes. Once the spatial mixing deviation returns to the allowable range, the actual compensation response is updated, and approximately 5.5g of ZnO is added for a third compensation.

[0076] The ZnO states during the three compensation cycles are shown in Table 4.

[0077] Table 4. ZnO compensation process in stages

[0078] As can be seen from Table 4, after each compensation is completed, the spatial mixing deviation is first reconfirmed through propagation mixing before the next compensation amount is calculated.

[0079] This allows the next compensation to be based on the detection status after the previous compensation has been fully reflected, reducing the possibility that continuous feeding due to newly added material not yet being fully propagated may cause the component to exceed the target value.

[0080] S6. Determine the mixing endpoint by considering the overall formulation, spatial distribution, and time stability. After compensation is completed, multi-location online detection continues, and the maximum overall formulation deviation among all target components in the current detection cycle is determined:

[0081] in, Indicates the first The maximum overall formulation deviation among all target components in a single testing cycle; Indicates the first In the first detection cycle Overall formulation deviation of the target component; This represents the absolute value of the overall formula deviation. Indicates different target components; This indicates the detection cycle number.

[0082] Further determine the maximum spatial mixing bias of the current detection cycle:

[0083] in, Indicates the first The maximum spatial mixing deviation of all target components in a detection cycle; Indicates the first In the first detection cycle Spatial mixing bias of the target components; Indicates different target components; This indicates the detection cycle number.

[0084] Simultaneously, the time-steady state is determined based on the change in the average content of the target component corresponding to adjacent detection cycles:

[0085] in, Indicates the first Between the first and the previous testing cycle The average change in the content of the target components; Indicates the first In the first detection cycle The average content of the target component at multiple sites; Indicates the first detection cycle in the previous detection period The average content of the target components at multiple locations; Indicates the target component; This indicates the detection cycle number.

[0086] In this embodiment, the allowable value for the average component content change between adjacent detection cycles is set to 0.02 percentage points.

[0087] After the third compensation was completed, three consecutive testing cycles were conducted, and the test results are shown in Table 5.

[0088] Table 5 Final Continuous Detection Results

[0089] In the above three consecutive testing cycles, the overall formula deviation, spatial mixing deviation, and component changes in adjacent cycles all met the set conditions, therefore it was determined that the current batch had reached the mixing endpoint.

[0090] If the overall formulation deviation meets the requirements but the spatial mixing deviation exceeds the allowable range, return to S4 for spatial homogenization; if the spatial mixing deviation meets the requirements but the overall formulation deviation exceeds the allowable range, return to S5 for formulation compensation; if both exceed the allowable range, return to S3 to re-implement the no-feed diagnostic mixing.

[0091] This creates a closed-loop mixing process that selects between diagnostic, homogenization, and formulation compensation processes based on the actual material condition.

[0092] Example 2

[0093] This embodiment illustrates the processing method when the content of the target component is higher than the target content.

[0094] The same mixing equipment and multi-location online detection method as in Example 1 were used. After initial mixing, the average Mn3O4 content in the average detection results of the three detection locations was approximately 23.45%, which is higher than the target content of 23.30%. At the same time, there were certain spatial differences in the Mn3O4 distribution between different detection locations.

[0095] First, a diagnostic mixing without replenishment was performed according to S3 in Example 1. After diagnostic mixing, the difference in Mn3O4 content between different locations was significantly reduced, but the average content at multiple locations remained above 23.30%, thus confirming that there was a positive deviation in the actual Mn3O4 formulation of the current batch.

[0096] Then, spatial homogenization is continued according to S4 until the spatial mixing deviation of Mn3O4 and other target components reaches the allowable range.

[0097] To address the issue of excessive Mn3O4 content, a dilution correction material with a Mn3O4 content lower than the target ratio is used. In this embodiment, the dilution correction material does not contain Mn3O4; instead, Fe2O3 and ZnO are prepared according to the relative proportions of the two in the target formulation.

[0098] When the dilution correction material is in the first When the content of a target component is lower than the target value, its theoretical dilution correction amount can be determined according to the following formula:

[0099] in, Indicates that for the first The theoretical mass of dilution correction material required for a positive deviation of the target component; This indicates the total mass of the material before the addition of the diluent / correction agent; Indicates the first The current average content of the target component; Indicates the first The target content of the target component; Indicates the first in the diluted correction material The actual content of the target component; superscript This indicates a dilution correction status.

[0100] For approximately 100 kg of material with an average Mn3O4 content of approximately 23.45%, when using a dilution correction material that is essentially free of Mn3O4, the theoretical dilution correction amount is approximately 0.64 kg.

[0101] In practice, the addition is still done in stages. First, a portion of the dilution correction material is added. After the propagation and mixing are completed, the actual response of the current batch to the dilution correction material is determined based on the actual average content change of Mn3O4, and then the amount of subsequent addition is determined.

[0102] The variations in this embodiment are shown in Table 6.

[0103] Table 6. Correction Results for Positive Deviations in Mn3O4

[0104] This shows that when the target component is lower than the target content, a compensating material rich in the corresponding component can be used for correction, and when the target component is higher than the target content, a diluted correction material formulated for the target component can be used for correction.

[0105] Comparative Example 1 Comparative Example 1 used the same raw materials, main feed amount and mixing equipment as Example 1, and the initial mixing time was also 8 minutes.

[0106] The difference is that online component detection is performed only at detection location A, and the detection results at detection locations B and C are not obtained, nor is the spatial mixing bias calculated.

[0107] When the ZnO content at detection location A is lower than the target content, the ZnO compensation amount is determined directly based on the detection result at detection location A and the material is replenished.

[0108] Since the initial detection location A is in a relatively depleted ZnO region, the ZnO content detected at this location is lower than the actual average content at the three spatial locations. Therefore, the compensation requirement determined based on this is too high. After compensation, as ZnO gradually spreads to other spatial regions, the ZnO content in some regions exceeds the target state.

[0109] Comparative Example 2 Comparative Example 2 used the same three detection locations A, B, and C as Example 1, and determined the overall formulation deviation based on the average content at the three detection locations.

[0110] The difference is that when the average ZnO content is lower than the target content, no feed-free diagnostic mixing is performed, and it is not judged whether the spatial mixing deviation has entered the allowable range. Instead, ZnO compensation is performed directly based on the average test results.

[0111] Because there are still significant spatial distribution differences in the original batch when compensation occurs, the newly added ZnO will further form a temporary local concentration gradient as it spreads from the feed area to other areas, causing the detection results at different locations to fluctuate significantly after compensation.

[0112] Comparative Example 3 Comparative Example 3 uses the same multi-location detection and non-feeding diagnostic hybrid method as Example 1.

[0113] After determining that there is a spatial mixing anomaly, homogenization mixing continues, but the same material pick-up position, the same return position, and the same circulation direction are always maintained, and the material migration path is not changed according to the decay state of the spatial mixing deviation.

[0114] In the initial stage of mixing, spatial mixing deviation can continue to decrease; as mixing continues, the rate of decrease in spatial mixing deviation gradually decreases, and the mixing time needs to be extended to continue to improve the spatial distribution.

[0115] Comparative Example 4 Comparative Example 4 employed the same multi-location detection, non-feeding diagnostic mixing, and spatial homogenization process as Example 1.

[0116] Once the spatial mixing deviation reaches the allowable range, it is confirmed that there is an actual negative deviation in the ZnO formulation, and the theoretical ZnO compensation amount is determined based on the mass conservation relationship.

[0117] The difference is that Comparative Example 4 adds the theoretical ZnO compensation amount to the mixing equipment all at once, without implementing the initial limited compensation, and does not determine the actual compensation response of the current batch based on the actual component changes after the first compensation.

[0118] After one-time compensation is completed, mixing and online detection are performed. The final spatial uniformity can be maintained at a low level. However, due to the actual process differences in material conveying, equipment adhesion, compensation material propagation and online detection response, the final average formula still has a certain deviation.

[0119] Comparison of results between the examples and the comparative examples Example 1 and Comparative Examples 1 to 4 were evaluated using the same target formulation, similar bulk feed amounts, and mixing equipment with the same structure. The main difference lay in the anomaly detection and adjustment control methods. The comparison results are shown in Table 7.

[0120] Table 7 Results of Examples and Comparative Examples

[0121] As can be seen from Table 7, the processing time of Comparative Example 1 is relatively short. However, since it uses single-location detection for formula compensation, the local enrichment or depletion at the detection location will directly affect the judgment of the compensation amount. As a result, its overall formula deviation and spatial mixing deviation are relatively large.

[0122] After using the multi-location average value in Comparative Example 2, the influence of a single detection location was reduced compared to Comparative Example 1. However, since the spatial distribution anomaly was not eliminated before compensation, the propagation process of the newly added material will still be reflected in the online detection results along with the actual formula changes. Therefore, the final overall formula deviation and spatial mixing deviation are still higher than those in Example 1.

[0123] Comparative Example 3 was able to perform anomaly diagnosis before refueling, but it always used a fixed material migration method. As the material exchange efficiency under the original circulation path decreased, the improvement on spatial mixing deviation by continuing to extend the mixing time gradually weakened, so it took a long time to obtain a relatively stable spatial state.

[0124] Comparative Example 4 already had good spatial uniformity before feeding, so its final spatial mixing deviation was close to that of Example 1. However, it was fed in one go according to the theoretical compensation amount without further correction based on the actual compensation response of the current batch. Therefore, the final overall formula deviation was still higher than that of Example 1, and it may slightly exceed the target value.

[0125] Example 1 maintained low levels in both overall formulation deviation and spatial mixing deviation, without exhibiting significant compensation exceeding the target value. Although its processing time was not the shortest among all methods, it was able to achieve relatively stable overall formulation and spatial mixing states within a reasonable processing period.

[0126] To more clearly explain the technical effects and working mechanism analysis of the specific embodiments, the following analysis is made: The main feed and compensation materials in S1 are reserved to establish space for subsequent formula adjustments. Traditionally, when all materials are fed according to the theoretical formula in one go, if online detection finds that a target component is generally too high or too low, the subsequent adjustment space is limited. This embodiment separates the main feed and compensation materials, allowing the system to perform targeted compensation after detecting actual formula deviations; simultaneously, a dilution correction material is set up, ensuring that both high and low component values ​​have corresponding adjustment paths. Therefore, S1 not only performs the initial batching function but also provides the material basis for subsequent closed-loop component adjustments.

[0127] S2 establishes both the overall formulation state and the spatial mixing state simultaneously through detection results from multiple spatial locations. For powder mixtures, the component detection result at a single location is affected not only by the true overall composition of the entire batch but also by local enrichment, local depletion, and spatial migration of powder particles at that location. Therefore, relying solely on a single detection value cannot reliably distinguish between "the entire batch of materials is indeed mismixed" and "this location is temporarily not mixed evenly." The average value of multiple spatial locations is primarily used to characterize the overall composition, while the dispersion between different locations is used to characterize spatial uniformity, enabling subsequent control to handle the two different states separately.

[0128] S2 and S3 together transform static detection results into dynamic information that can be used to determine the source of anomalies. Unreplenished diagnostic mixing only alters the material distribution between different spatial regions without adding or subtracting any target component. Therefore, under ideal mass conservation conditions, diagnostic mixing can change local detection values ​​at various locations without substantially altering the overall average composition of the entire batch. When the spatial differences before and after diagnosis are significantly reduced while the average value remains essentially unchanged, it can be determined that the original detection anomaly contained significant spatial distribution factors; when the average value continues to deviate from the target value even after the spatial differences have decreased, the residual deviation can more reliably reflect the true overall formulation state.

[0129] S4 further addresses the question of whether spatial uniformity is still effectively improving while the equipment is still mixing. Powder does not always migrate completely randomly within the mixing equipment. After a period of mixing, some materials may repeatedly move along relatively stable circulation paths, while the effective mass exchange between different circulation zones gradually decreases. At this point, although the equipment continues to operate, the rate of decrease in spatial component differences has slowed. By utilizing the spatial deviation decay state obtained from consecutive short mixing cycles, it is possible to determine whether the current material migration pattern still possesses effective homogenization capabilities.

[0130] When the spatial deviation remains large and the descent rate continues to decrease, changing the material intake position, return position, or circulation direction of the circulating material flow can disrupt the previously established stable local circulation, allowing the previously under-exchanged material areas to re-exchange with the main mixing area. Therefore, this embodiment does not simply improve uniformity by increasing the mixing time, but rather changes the spatial exchange relationship after the original material migration path enters an inefficient state. Comparative Example 3 requires a longer time to reduce the spatial deviation, reflecting that changing the material migration path has a practical effect on shortening the ineffective mixing stage.

[0131] A clear sequential constraint is also established between S4 and S5. Precise formulation compensation is not performed if the spatial mixing deviation does not reach the allowable range. This is because if the newly added compensating material is still concentrated in a certain spatial area, the concentration change observed at a certain detection location does not represent a change in the overall composition of the entire batch to the same degree. Only by first reducing the spatial difference to the allowable range can the average detection results from multiple locations more stably characterize the overall composition, thereby allowing subsequent compensation calculations to be based on a relatively reliable material state.

[0132] S5 employs an initial limited compensation method instead of directly adding the entire theoretical compensation amount at once. The theoretical compensation amount is based on an ideal mass balance relationship, but in actual production, there are also factors such as short-term retention of the compensation material in the conveying channel, powder adhesion to the walls, spatial propagation after addition, and differences in online detection response. Therefore, the first small-dose compensation is equivalent to applying a known material input to the current batch. After remixing, the actual change in the average composition is used to obtain the actual response of the current batch to the compensation operation. Subsequent compensation amounts are adjusted accordingly, allowing the compensation process to adapt to the actual material state of the current batch.

[0133] Staged compensation can also reduce the phenomenon of compensation exceeding the target value caused by continuous feeding. The compensating material needs time to spread from its addition to the equipment to the entire batch. If feeding continues based on the original deviation before the previous compensation effect is fully reflected in the online detection results, the multiple compensation effects may overlap after subsequent full spread, causing the final content to exceed the target value. This embodiment adopts the sequence of "compensation - spread mixing - spatial state confirmation - re-detection - next compensation," ensuring that each new compensation is based on the previous compensation result having basically stabilized.

[0134] S6 simultaneously evaluates the overall formulation, spatial distribution, and temporal stability, avoiding premature termination of mixing based solely on average component content. When the target component is high in one region and low in another, the average value across different regions may be close to the target value, but the actual material still exhibits significant spatial inhomogeneity. Therefore, in addition to meeting the overall formulation deviation requirements, further requiring the spatial mixing deviation to meet the requirements can prevent situations where the average value is acceptable while local conditions are unacceptable. The continuous detection cycle stability assessment is used to exclude situations where the material accidentally enters the allowable range at a particular detection moment.

[0135] Throughout the processing, the two types of state parameters obtained in S2 provide the diagnostic basis for S3. After identifying the source of the anomaly, S3 decides whether to proceed to S4 or S5. After S4 completes spatial homogenization, it provides stable overall formula judgment conditions for S5. Each time S5 completes compensation, it undergoes spatial homogenization testing again. Finally, S6 jointly confirms the overall composition, spatial state, and temporal state. Therefore, the entire mixing process does not use a fixed mixing time or a single test value as the control basis, but rather selects the appropriate processing path step by step according to the actual state exhibited by the material at different stages.

[0136] Through the above process, the interference of local enrichment or depletion on the overall formula judgment can be reduced during the mixing of the target soft magnetic ferrite material, and the situation of incorrect material feeding when the spatial state is not yet stable can be reduced. At the same time, when the homogenization efficiency of the original material migration mode decreases, the spatial exchange path can be changed, and the component can be corrected in stages according to the actual compensation response of the current batch. This ensures that the overall formula state and spatial distribution state of the mixture are well consistent, providing a relatively stable soft magnetic ferrite mixed raw material for subsequent pre-calcination, grinding, granulation, molding and sintering processes.

[0137] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. An online detection and mixing process for soft magnetic ferrite materials, characterized in that, Includes the following steps: S1. Prepare the raw materials according to the target formula of the soft magnetic ferrite material to be processed. Add the raw materials to the mixing equipment for initial mixing and reserve the compensation material for subsequent component correction. S2. During the mixing process, the test flow is obtained from multiple different spatial locations of the mixed materials, and the target components in each test flow are detected online. Based on the detection results of multiple spatial locations, the overall formulation deviation and spatial mixing deviation of each target component are determined. S3. When the overall formula deviation or spatial mixing deviation exceeds the corresponding allowable range, the mixture is subjected to diagnostic mixing disturbance without the addition of compensating materials, and the detection results of multiple different spatial locations are obtained again. Based on the changes in the overall formula deviation and spatial mixing deviation before and after the diagnostic mixing disturbance, the current abnormality is identified as either a spatial mixing abnormality or an actual formula abnormality. S4. When the spatial mixing abnormality is identified, the mixture is homogenized and mixed. The current mixing method is judged to eliminate the spatial mixing deviation based on the attenuation state of the spatial mixing deviation during continuous detection. When the elimination ability decreases, the migration mode of the material is changed until the spatial mixing deviation reaches the allowable range. S5. When the spatial mixing deviation reaches the allowable range but the overall formula deviation still exceeds the allowable range, the target component with actual formula abnormality is compensated in stages. First, a first compensation less than the current theoretical compensation amount is performed. After the mixture after the first compensation reaches the allowable range of spatial mixing deviation again, the actual compensation response of the current batch of materials to the corresponding compensation material is determined according to the online detection results before and after the first compensation, and the subsequent compensation amount is determined according to the actual compensation response. S6. During the subsequent compensation and mixing process, continuous online detection at multiple locations is carried out. When the overall formulation deviation and spatial mixing deviation of each target component continuously meet the corresponding allowable range and the component changes in adjacent detection cycles reach the stable condition, the mixing process of the current batch of soft magnetic ferrite materials is terminated.

2. The online detection and mixing process for soft magnetic ferrite materials according to claim 1, characterized in that: In step S1, the raw materials corresponding to the target formula are divided into a main feeding part and a compensation feeding part. The main feeding part is used to form an initial mixture that is close to the target formula, and the compensation feeding part is retained in the initial mixing stage and not added to the mixing equipment. For each target component, a component compensation material is prepared to increase the relative content of the corresponding target component, and a dilution correction material is prepared to decrease the relative content of the corresponding target component. In the dilution correction material, the content of the target component to be reduced is lower than its content in the target formulation. The remaining main components are prepared in proportions corresponding to the target formulation, so that the actual formulation anomaly can be corrected along the direction of increasing or decreasing component content.

3. The online detection and mixing process for soft magnetic ferrite materials according to claim 2, characterized in that: In S2, the multiple different spatial positions include at least positions located in different radial positions, different height positions, and / or different material circulation paths, so that each detection position corresponds to a different material space region; The target component content and moisture content of each test material stream are detected separately, and the target component detection results are uniformly converted into dry basis component content based on the moisture content at the corresponding detection location. The average component content of the target component is determined based on the dry basis component content at multiple detection locations. The overall formulation deviation is determined based on the difference between the average component content and the corresponding target component content in the target formulation. The spatial mixing deviation is determined based on the difference between the maximum and minimum dry basis component content of the same target component at different detection locations.

4. The online detection and mixing process for soft magnetic ferrite materials according to claim 3, characterized in that: The diagnostic mixing disturbance in S3 includes: keeping the material composition and total amount of the current batch of material unchanged, stopping the addition of component compensation material and dilution correction material, and changing the spatial migration state of the mixed material within a preset diagnostic cycle; Before and after diagnosing the mixing disturbance, the average component content and spatial mixing deviation of each target component are determined respectively. The decrease in spatial mixing deviation before and after diagnosing the mixing disturbance is used to characterize the response of spatial distribution to the diagnosing mixing disturbance. The change in average component content before and after diagnosing the mixing disturbance is used to characterize the stability of the overall composition of the mixture. Thus, the source of the anomaly can be identified by the difference between the change in spatial distribution and the change in overall composition.

5. The online detection and mixing process for soft magnetic ferrite materials according to claim 4, characterized in that: In S3, when the spatial mixing deviation of the corresponding target component decreases and the average component content remains within a preset stable range after diagnosing the mixing disturbance, the corresponding anomaly is determined as a spatial mixing anomaly. When the spatial mixing deviation reaches the allowable range after the diagnosis of mixing disturbance, and the average component content of the corresponding target component continues to deviate from the corresponding target component content in the target formulation, the corresponding anomaly is identified as an actual formulation anomaly. When both spatial mixing deviation and overall formulation deviation exceed the corresponding allowable range, the current state is prioritized as the spatial interference state to be eliminated. Component compensation based directly on the current overall formulation deviation is prohibited. The overall formulation deviation is re-determined after the spatial mixing deviation reaches the allowable range.

6. The online detection and mixing process for soft magnetic ferrite materials according to claim 5, characterized in that: In step S4, the homogenization mixing is divided into multiple consecutive short mixing cycles, and multi-position online detection is performed again after each short mixing cycle. The degree of spatial deviation attenuation is determined based on the proportional relationship between the decrease in spatial mixing deviation corresponding to adjacent short mixing cycles and the spatial mixing deviation of the previous short mixing cycle. When the degree of spatial deviation attenuation indicates that the spatial mixing deviation continues to decrease effectively, the current material migration mode is maintained. When the spatial mixing deviation still exceeds the allowable range and the spatial deviation decay rate of several consecutive short mixing cycles decreases to the preset decay condition, it is determined that the current material migration mode has entered an inefficient homogenization state, and the material migration mode is changed.

7. The online detection and mixing process for soft magnetic ferrite materials according to claim 6, characterized in that: The change in material migration method includes changing the exchange path of the mixture between different spatial areas, so that the material areas that were not sufficiently exchanged under the previous material migration method can re-establish material exchange. The method of changing the material migration is achieved by at least one of the following: changing the mixing direction, changing the mixing speed, changing the material pick-up position of the circulating material flow, changing the return position of the circulating material flow, and changing the direction of the circulating material flow. After changing the material migration method, continue to perform short mixing cycles and multi-location online detection, and determine whether the changed material migration method has restored the ability to effectively eliminate spatial mixing deviation based on the re-obtained spatial mixing deviation.

8. The online detection and mixing process for soft magnetic ferrite materials according to any one of claims 5 to 7, characterized in that: In step S5, the theoretical compensation amount of the corresponding target component is determined based on the current material quantity of the mixture, the target content of the target component, and the average component content obtained from online detection at multiple locations. A portion of the theoretical compensation amount is used as the first compensation amount to perform the first compensation. After the first compensation is completed, the compensation is stopped and the added compensation material is mixed and propagated. After the spatial mixing deviation reaches the allowable range again after the first compensation, the actual compensation response of the current batch of materials to the corresponding compensated material is determined according to the correspondence between the average component content change before and after the first compensation and the first compensation amount, so as to use the actual compensation response of the current batch of materials to correct the theoretical compensation relationship.

9. The online detection and mixing process for soft magnetic ferrite materials according to claim 8, characterized in that: The next compensation amount is determined based on the remaining overall formula deviation after the first compensation and the actual compensation response, and the next compensation amount retains a margin for subsequent corrections. After each compensation is completed, mixing propagation and multi-location online detection are performed first. After the spatial mixing deviation returns to the allowable range, the actual compensation response of the corresponding target component is updated based on the change in average component content before and after this compensation and the actual amount of compensation material added this time. The amount of compensation for the next time is determined based on the updated actual compensation response. When the content of the target component is lower than the target content, the corresponding component compensation material is called; when the content of the target component is higher than the target content, the corresponding dilution correction material is called, so as to form a two-way iterative correction process based on the actual compensation response of the current batch.

10. The online detection and mixing process for soft magnetic ferrite materials according to claim 9, characterized in that: In step S6, the overall formulation state, spatial mixing state, and time stability state of each target component are judged simultaneously for multiple consecutive detection cycles. When the overall formulation deviation of all target components is within the corresponding allowable range, the spatial mixing deviation of all target components is within the corresponding allowable range, and the average component content change of each target component between adjacent detection cycles is less than the preset stable change amount, the current batch is determined to have reached the mixing endpoint. When the overall formulation deviation reaches the allowable range while the spatial mixing deviation exceeds the allowable range, return to perform spatial homogenization mixing; When the spatial mixing deviation reaches the allowable range while the overall formulation deviation exceeds the allowable range, return to perform component compensation; when both the overall formulation deviation and the spatial mixing deviation exceed the corresponding allowable range, return to perform diagnostic mixing disturbance, so that the mixing process selects between the spatial homogenization path and the formulation compensation path according to the abnormality source identification result, until the mixing endpoint is reached.

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