Method and system for producing powder fertilizer

Abstract

The invention discloses a powder fertilizer production method and system, and relates to the technical field of powder fertilizer.The method comprises the following steps that a powder fertilizer production formula of the current batch is obtained, and raw materials are automatically fed according to the powder fertilizer production formula; high-strength homogeneous mixing is conducted on the raw materials after automatic feeding, a physical field is applied in the high-strength homogeneous mixing process, and the physical field is used for conducting micro-crystallization treatment on the mixed raw materials to obtain micro-crystallized powder; carrying out constant-temperature forming on the micro-crystallized powder to obtain formed particles; cooling and curing the formed particles to obtain finished product particles; and the finished product particles are conveyed to automatic packaging equipment, and the automatic packaging equipment packages and seals the finished product particles according to preset packaging parameters. A distributed control system is adopted for fine control, and full-automatic and intelligent operation from raw material feeding, high-strength homogeneous mixing, micro-crystallization treatment, constant-temperature forming, cooling and curing to automatic packaging is achieved.

Description

Technical Field

[0001] This application relates to the field of powder fertilizer production technology, and more specifically, to a method and system for producing powder fertilizer. Background Technology

[0002] Modern agriculture has an ever-increasing demand for powder fertilizers due to their high content of active ingredients, good water solubility, and easy absorption by crops. However, traditional powder fertilizer production methods are often limited to simple crushing and mixing, making it difficult to meet the higher market demands for product quality consistency, nutrient uniformity, physical stability (such as anti-caking properties), and flexible production line customization capabilities in the context of precision agriculture and intelligent fertilization technologies. This gap highlights the urgent need to develop new production technologies that integrate fine processing and intelligent control.

[0003] Specifically, existing powder fertilizer production methods generally suffer from several technical bottlenecks. First, traditional processes often rely on extensive mixing, making it difficult to achieve precise nutrient homogenization. Furthermore, the resulting products tend to have large particle sizes or uneven distribution, easily leading to clumping and uneven fertilizer release. Second, the automation and intelligence levels of the production process are low, heavily reliant on manual experience for proportioning and control. This not only results in low efficiency but also makes it difficult to guarantee the stability and reproducibility between different batches. Third, existing production lines lack flexibility, making it difficult to quickly and economically respond to the needs of small-batch, multi-formulation customized production. These problems hinder the development and application of high-quality, functional powder fertilizers.

[0004] Therefore, in the production of powder fertilizers, facing the market's increasingly high demands for product quality consistency, nutrient uniformity, physical stability (such as anti-caking properties), and flexible customization capabilities of production lines, how to overcome the limitations of traditional processes in terms of extensive material mixing, low levels of automation and intelligence, poor batch stability, and difficulty in quickly responding to small-batch, multi-formulation customization needs, and thus achieve an efficient and flexible production method that integrates precise formulation, deep homogenization, microcrystalline modification, and intelligent control, is a technical problem that the industry urgently needs to solve. Summary of the Invention

[0005] This application discloses a method and system for producing powder fertilizer, which aims to address the shortcomings of traditional powder fertilizer production methods in terms of product quality consistency, nutrient uniformity, physical stability, and the ability to customize production lines.

[0006] The technical solution of this application is as follows: In a first aspect, this application discloses a method for producing powder fertilizer, which employs a distributed control system, including: Obtain the production formula for the current batch of powder fertilizer and automatically feed the raw materials according to the production formula; The raw materials after automatic feeding are subjected to high-intensity homogenization and mixing, and a physical field is applied during the high-intensity homogenization process. This physical field is used to microcrystallize the mixed raw materials to obtain microcrystallized powder. Microcrystalline powder is subjected to constant-temperature molding to obtain molded particles; The molded particles are cooled and solidified to obtain the finished particles; The finished pellets are conveyed to an automatic packaging device, which packages and seals the finished pellets according to preset packaging parameters.

[0007] Furthermore, the raw materials after automatic feeding are subjected to high-intensity homogenization mixing, and a physical field is applied during the high-intensity homogenization mixing process, including: The raw material sample is extracted by a cyclone separator and transported to the test chamber. The raw material sample is the pre-set mass of raw material that is automatically fed from the main mixing chamber inlet by the cyclone separator. The operating parameters in the test chamber are controlled to conduct microcrystallization treatment tests on raw material samples. The operating parameters include: uniform stirring operating parameters and microcrystallization treatment parameters, which are ultrasonic operating parameters or microwave operating parameters. To obtain the microstructure and surface properties of raw material samples under microcrystallization treatment experiments; The combination of physical field parameters of the raw material is determined based on the microstructure and surface properties of the raw material sample. The main physical field parameters under the main mixing chamber are adjusted based on the combination of physical field parameters, and the raw materials after automatic feeding are microcrystallized based on the main physical field parameters; the main physical field parameters are low-frequency sound waves generated by ultrasonic vibrators or non-thermal microwaves generated by microwave generators.

[0008] More specifically, obtaining the microstructure and surface properties of the raw material samples under microcrystallization treatment experiments includes: The dielectric spectrum data of the raw material sample under the microcrystallization treatment test is obtained by applying an AC electric field of scanning frequency to the raw material sample under the microcrystallization treatment test using an impedance analyzer controlled by a distributed control system. Acoustic emission data of raw material samples under microcrystallization treatment were obtained by a piezoelectric acoustic emission sensor controlled by a distributed control system. By fusing and analyzing dielectric spectroscopy data and acoustic emission data, scores were obtained for the microcrystalline layer density, uniformity, and bonding strength of the raw material samples under microcrystallization treatment.

[0009] Based on this, the main physical field parameters under the main mixing cavity are adjusted according to the combination of physical field parameters, including: Accelerated aging tests were conducted on the raw material samples after microcrystallization treatment, and the trend of surface property changes of the raw material samples during the accelerated aging tests was monitored. Obtain the actual long-term performance test results of the finished product granules; Compare the trend of surface properties with the actual long-term performance test results; The preset long-term performance correlation factor is dynamically calibrated based on the comparison results; The master physics parameters are adjusted based on the microcrystalline layer density, uniformity, and bonding strength scores, combined with the calibrated long-term performance correlation factor.

[0010] Preferably, the accelerated aging test is performed on the raw material sample after the microcrystallization treatment test, and the trend of surface property changes of the raw material sample during the accelerated aging test includes: The raw material samples after microcrystallization treatment in the test chamber are extracted using a distributed control system and then placed in a multi-functional aging test chamber. Monitor the changes in internal crystal structure, nutrient slow release rate, and medium crush resistance of raw material samples after microcrystallization treatment during accelerated aging; Based on changes in internal crystal structure, nutrient slow-release rate, and crush resistance, a trend map of changes in the internal structure and key functional properties of raw material samples after microcrystallization treatment was established.

[0011] Based on the above, the comparison between the surface performance change trend and the actual long-term performance test results includes: Based on the raw material characteristics and product formula of the current production batch, the corresponding dynamic long-term performance targets are matched and loaded from the preset long-term performance target library. Compare the trend graph with the dynamic long-term performance target; When a deviation is detected between the actual performance in the trend graph and the dynamic long-term performance target, the weight of the dynamic long-term performance target is adjusted.

[0012] As a technological improvement, monitoring changes in the internal crystal structure of raw material samples after microcrystallization treatment during accelerated aging includes: Layered scanning was performed on the raw material samples after the microcrystallization treatment experiment to obtain Raman spectral data of the surface layer and core region of the raw material samples after the microcrystallization treatment experiment; Raman spectral data of the surface layer and core region were used for crystal phase identification and quantitative analysis to obtain the content and crystallinity of each crystal phase. Compare the changes in the content and crystallinity of each crystalline phase before and after the microcrystallization treatment experiment; The comparison results distinguish between the degree of crystal phase optimization caused by the microcrystallization treatment experiment and the degree of crystal phase degradation caused by accelerated aging. Based on the degree of crystal phase optimization and the degree of crystal phase degradation, the contribution of the microcrystallization treatment experiment to the stability of the crystal structure in the surface layer and core region was calculated.

[0013] In one embodiment, the process of isothermal molding of microcrystalline powder to obtain molded particles includes: The absorption spectrum and phase spectrum of the microcrystalline powder were obtained using a terahertz spectrometer at the inlet of the molding equipment. Microrheological data of microcrystalline powder are measured using an optical microrheological sensor array at the inlet of the molding equipment. The particle binding potential index was calculated based on absorption and phase spectra, as well as microrheological data. Based on the particle bonding potential index and the preset potential index target range, the molding temperature and pressure required when the next segment of microcrystalline powder enters the main molding zone are dynamically predicted. The molding temperature control heating module operates, controlling the extrusion pressure of the rolling press based on the pressure value.

[0014] As a further improvement, the absorption spectrum and phase spectrum of the microcrystalline powder are obtained using a terahertz spectrometer at the inlet of the molding equipment, including: Fourier transform and baseline correction were performed on the raw terahertz spectral data; Extracting the absorption peak intensity and broadening at terahertz frequencies; The absorption spectrum and phase spectrum of the microcrystalline powder were determined based on the absorption peak intensity and broadening.

[0015] Secondly, this application also discloses a system for producing powder fertilizer, which employs a distributed control system, including: The automatic feeding module is used to obtain the production formula of the current batch of powder fertilizer and automatically feed the raw materials according to the production formula of powder fertilizer. The crystallization module is used to perform high-intensity homogenization mixing on the raw materials after automatic feeding, and to apply a physical field during the high-intensity homogenization mixing process. This physical field is used to perform microcrystallization treatment on the mixed raw materials to obtain microcrystallized powder. The constant-temperature molding module is used to mold microcrystalline powder into shaped particles at a constant temperature. The cooling and molding module is used to cool and solidify the molded particles to obtain finished particles; An automatic packaging module is used to transport finished product granules to an automatic packaging device, which packages and seals the finished product granules according to preset packaging parameters.

[0016] The powder fertilizer production method disclosed in this application employs a distributed control system for refined control of the entire production process, achieving fully automated and intelligent operation from raw material feeding, high-intensity homogenization mixing, microcrystallization treatment, constant-temperature molding, cooling and solidification to automatic packaging. Specifically, this method effectively solves problems such as coarse material handling, low nutrient homogenization, uneven product particle size, and easy agglomeration in traditional processes by applying a physical field to microcrystallize the raw materials during homogenization mixing. Microcrystallization treatment significantly improves the microstructure and surface properties of the powder fertilizer, thereby enhancing nutrient uniformity, physical stability, and slow-release performance. Furthermore, the application of the distributed control system allows for more precise and real-time parameter control of the production process, overcoming the drawbacks of traditional production's heavy reliance on manual experience and significantly improving production efficiency and batch-to-batch consistency and reproducibility. Through this novel production technology integrating refined processing and intelligent control, this application can meet the urgent needs of modern agriculture for high-quality, functional powder fertilizers and provides a flexible solution for customized production of small batches and multiple formulations, thus overcoming many technical bottlenecks in existing technologies. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the process for producing powder fertilizer according to an embodiment of the present invention; Figure 2 This is a flowchart of a method for high-intensity homogenization mixing of raw materials after automatic feeding, and applying a physical field during the high-intensity homogenization mixing process, according to an embodiment of the present invention. Figure 3 This is a flowchart of a method for obtaining shaped particles by constant-temperature molding of microcrystalline powder in an embodiment of the present invention. Figure 4 This is a schematic diagram of the system structure for producing powder fertilizer in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0020] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] Specifically, Figure 1 A schematic flowchart of a method for producing powder fertilizer according to an embodiment of the present invention is shown. The method is controlled by a distributed control system and includes: S101. Obtain the production formula of the current batch of powder fertilizer and automatically feed the raw materials according to the production formula of powder fertilizer. In the specific implementation process, it is necessary to obtain the production formula of the current batch of powder fertilizer and automatically feed the raw materials according to the formula. For example, the operator can input or select a preset production formula from the database through the human-machine interface of the distributed control system. This formula includes the types of various raw materials and the precise feeding ratios. The automatic feeding system can be implemented in various ways. For example, different types of raw materials can be accurately transported from their respective storage bins to the mixing equipment through gravity feeding, screw conveying, or pneumatic conveying. As a preferred embodiment, a hopper equipped with a weighing sensor can be used, which automatically stops feeding when the preset weight is reached. In another implementation, a volumetric metering pump can be used, and the feeding amount of liquid or semi-liquid raw materials can be controlled by precisely controlling the pump speed and working time.

[0022] S102. The raw materials after automatic feeding are subjected to high-intensity homogenization and mixing, and a physical field is applied during the high-intensity homogenization process. The physical field is used to microcrystallize the mixed raw materials to obtain microcrystallized powder. High-intensity homogeneous mixing can be achieved through various mixing equipment, such as high-speed mixers, plow mixers, or double-helix conical mixers. These devices ensure a highly uniform mixture of different raw materials at both the macroscopic and microscopic levels. Applying a physical field during mixing can be done using an ultrasonic generator, which converts electrical energy into mechanical vibration energy via a transducer, generating high-frequency sound waves. These sound waves propagate through the mixture, creating a cavitation effect that promotes the microcrystallization of the raw materials. Alternatively, a microwave generator can be used to apply a physical field during mixing. By generating microwaves of specific frequencies, the raw material molecules vibrate and rub against each other at the microscopic level, thus achieving microcrystallization. The physical field can be applied by directly integrating an ultrasonic probe or microwave transmitter into the mixing chamber of the mixing equipment.

[0023] S103. The microcrystalline powder is molded at a constant temperature to obtain molded particles; Isothermal forming is a crucial step in ensuring stable particle structure and properties. For example, it can be achieved using equipment such as extrusion granulators, disc granulators, or roller granulators. In extrusion granulation, microcrystalline powder is extruded into strips through a die plate at a specific temperature, and then cut into granules. Isothermal forming can be achieved by controlling the heating module of the forming equipment; for example, by using electric heating rods or steam heating jackets to heat the die or forming cavity, maintaining it at a preset constant temperature.

[0024] S104. Cool and solidify the molded particles to obtain finished particles; Cooling and solidification is a crucial step in stabilizing the structure and increasing the strength of the molded particles. For example, fluidized bed coolers, counter-current coolers, or vibratory coolers can be used. In a fluidized bed cooler, cold air is blown in from the bottom, suspending the particles and allowing them to fully contact the air, thus rapidly removing heat and solidifying the particles. The cooling and solidification process can be achieved by controlling the temperature and flow rate of the cooling medium (such as cold air or cold water).

[0025] S105. The finished product granules are conveyed to the automatic packaging equipment, which packages and seals the finished product granules according to the preset packaging parameters.

[0026] Finished pellets can be conveyed using belt conveyors, bucket elevators, or pneumatic conveying systems. Automated packaging equipment can precisely measure, fill, and seal the finished pellets according to preset packaging parameters, such as weight per bag, bag type, and sealing method. For example, vertical filling and sealing machines or pre-filled bag packaging machines can be used, enabling high-speed, high-precision automated packaging.

[0027] The powder fertilizer production method proposed in this application integrates all aspects of powder fertilizer production—from intelligent formula management and automatic feeding of raw materials to high-intensity homogenization mixing and simultaneous microcrystallization treatment, and finally to isothermal molding, cooling and solidification, and automatic packaging—through a distributed control system (DCS). By introducing physical field-assisted microstructure control methods and a full-process automated monitoring and adaptive adjustment mechanism, the method achieves high consistency in product quality at both the macro and micro levels, nutrient uniformity, and physical stability. It also endows the production line with the ability to quickly respond to multi-formulation and small-batch customization needs. The distributed control system consists of multiple independent controllers interconnected via a network, jointly monitoring and regulating the entire production process. This system enables real-time acquisition, processing, and feedback of production data, thereby improving the automation, intelligence, and flexible customization capabilities of production. The physical field refers to the energy field applied during the mixing process, such as an ultrasonic field or microwave field, which acts to microcrystallize the mixed raw materials, optimizing the microstructure and properties of the powder. Microcrystallization is a process that uses a physical field to make the crystal structure in raw materials smaller, more uniform, and denser, thereby improving the nutrient release efficiency, anti-caking properties, and physical stability of powder fertilizers.

[0028] The powder fertilizer production method of this application achieves fully automated and intelligent management of the entire production process through a distributed control system, from raw material feeding to finished product packaging. By obtaining the powder fertilizer production formula for the current batch and automatically feeding the raw materials, the accuracy and consistency of the raw material ratio are ensured. During high-intensity homogenization mixing, a physical field is applied for microcrystallization treatment, significantly improving the microstructure and performance of the powder fertilizer and solving the problems of insufficient nutrient homogenization and uneven particle size in traditional processes. The microcrystallized powder undergoes constant-temperature molding and cooling solidification to form structurally stable and physically superior shaped granules and finished granules, effectively improving the product's anti-caking properties and physical stability. Finally, automatic packaging equipment is used for sealing, improving production efficiency and product packaging quality. The entire method, through close coordination of each stage, forms a highly efficient, intelligent, and flexible production system, effectively solving problems such as low production efficiency, unstable product quality, and difficulty in meeting customized needs in existing technologies, thereby producing high-quality, functional powder fertilizers.

[0029] Specifically, Figure 2 This invention illustrates a method for high-intensity homogenization mixing of automatically fed raw materials, and the application of a physical field during the high-intensity homogenization mixing process, as shown in the following flowchart, which specifically includes: S201. Extract raw material samples using a cyclone separator and transport the raw material samples to the test chamber; It should be noted that the raw material sample is a preset mass of the automatically fed raw material non-invasively extracted from the inlet of the main mixing chamber by the cyclone separator. The cyclone separator is used to non-invasively extract a preset mass of the automatically fed raw material sample from the inlet of the main mixing chamber. This non-invasive extraction method avoids interference with the main production process and ensures production continuity. The extracted raw material sample is transported to the test chamber, which is an independent, controllable microprocessing environment used to simulate the microcrystallization process in the main mixing chamber.

[0030] S202. Control the operating parameters in the test chamber to conduct a microcrystallization treatment test on the raw material sample; It should be noted that the operating parameters include: uniform stirring parameters and microcrystallization treatment parameters, wherein the microcrystallization treatment parameters are ultrasonic or microwave operating parameters. The uniform stirring parameters aim to ensure that the raw material sample is fully mixed within the test chamber, simulating the homogeneous mixing state in the main mixing cavity. The microcrystallization treatment parameters can be ultrasonic or microwave operating parameters, used to apply a physical field to the raw material sample within the test chamber to induce microcrystallization. Ultrasonic operating parameters may include frequency, power, and duration, while microwave operating parameters may include frequency, power, and pulse mode.

[0031] S203. Obtain the microstructure and surface properties of the raw material samples under the microcrystallization treatment test; After the microcrystallization treatment experiment is completed, it is necessary to obtain the microstructure and surface properties of the raw material sample. The microstructure can include crystal size, crystal phase composition, lattice defects, etc., while the surface properties can include surface roughness, porosity, surface energy, etc. These properties are key indicators for evaluating the effectiveness of the microcrystallization treatment.

[0032] S204. Determine the combination of physical field parameters of the current raw material based on the microstructure and surface characteristics of the raw material sample. Based on the microstructure and surface properties of the obtained raw material sample, the optimal combination of physical field parameters can be determined. For example, if the microstructure shows that the crystal size is too large or the crystallinity is insufficient, it may be necessary to adjust the physical field parameters to enhance the microcrystallization effect; if the surface properties are not ideal, it may be necessary to adjust the parameters to optimize the surface morphology.

[0033] S205. Adjust the main physical field parameters under the main mixing chamber based on the combination of physical field parameters, and perform microcrystallization treatment on the raw materials after automatic feeding based on the main physical field parameters.

[0034] It should be noted that the main physical field parameter is the low-frequency sound wave generated by the ultrasonic vibrator or the non-thermal microwave generated by the microwave generator. The main physical field parameter is the physical field parameter applied during the microcrystallization treatment of raw materials after automatic feeding in actual production. Specifically, the main physical field parameter can be the low-frequency sound wave generated by the ultrasonic vibrator or the non-thermal microwave generated by the microwave generator. Low-frequency sound waves can promote crystal growth and rearrangement through cavitation effects and mechanical vibration, while non-thermal microwaves can affect the crystal structure through molecular polarization and dipole moment effects; both can effectively achieve the microcrystallization treatment of raw materials.

[0035] Here, a cyclone separator is used to non-invasively extract raw material samples, ensuring real-time performance and representativeness. In the test chamber, controlled microcrystallization experiments are conducted on the raw material samples, and their microstructure and surface properties are obtained. This provides a precise understanding of the microcrystallization potential of the current batch of raw materials and its response to the physical field. Based on this real-time data, the system can dynamically determine the most suitable combination of physical field parameters for the current raw material and apply it to the main mixing chamber, ensuring that each batch of raw materials undergoes microcrystallization under optimized physical field conditions. This closed-loop control principle allows the microcrystallization process to adaptively adjust to accommodate differences between batches of raw materials. This method can dynamically adjust physical field parameters according to the actual characteristics of different batches of raw materials, thereby ensuring that the microcrystallized powder has a superior and more stable microstructure and surface properties. This not only helps improve the quality and performance of the finished particles, such as increasing nutrient release efficiency and crush resistance, but also effectively reduces production losses caused by insufficient or excessive microcrystallization, thereby improving overall production efficiency and product qualification rate.

[0036] In some preferred embodiments, suppose a powder fertilizer production line receives two batches of raw materials. The first batch has a larger average particle size and slightly higher moisture content, while the second batch has a smaller average particle size and lower moisture content. If a fixed ultrasonic physical field parameter is used for microcrystallization treatment, the microcrystallization effect of the first batch of raw materials may be poor, resulting in larger crystal sizes, while the second batch of raw materials may undergo over-microcrystallization, leading to damage to the surface structure. Using the solution of this application, firstly, a cyclone separator extracts samples of both batches of raw materials from the inlet of the main mixing chamber and transports them to the test chamber. In the test chamber, a microcrystallization treatment test is conducted on the first batch of raw material samples. By obtaining its microstructure and surface characteristics, the system may identify that higher ultrasonic power and a longer treatment time are required to achieve the ideal microcrystallization effect. Subsequently, the system adjusts the ultrasonic vibrator parameters in the main mixing chamber according to this analysis result to adapt to the characteristics of the first batch of raw materials. When the second batch of raw materials enters the production line, samples are also extracted for testing. At this point, the system may determine that lower ultrasonic power and shorter duration are sufficient for optimal microcrystallization, and may even suggest switching to a microwave physical field to achieve better non-thermal effects. The system will then dynamically adjust the physical field parameters in the main mixing chamber again to precisely match the requirements of the second batch of raw materials. In this way, regardless of changes in raw material properties, the solution proposed in this application ensures that each batch of microcrystallized powder meets the expected quality standards.

[0037] Specifically, the acquisition of the microstructure and surface properties of the raw material samples under the microcrystallization treatment test includes: applying an alternating electric field of scanning frequency to the raw material samples under the microcrystallization treatment test using an impedance analyzer controlled by a distributed control system to obtain the dielectric spectrum data of the raw material samples under the microcrystallization treatment test; obtaining the acoustic emission data of the raw material samples under the microcrystallization treatment test using a piezoelectric acoustic emission sensor controlled by a distributed control system; and performing fusion analysis on the dielectric spectrum data and acoustic emission data to obtain the microcrystalline layer compactness, uniformity, and bonding strength scores of the raw material samples under the microcrystallization treatment test.

[0038] Impedance analyzers obtain dielectric spectrum data by applying an alternating electric field of a scanning frequency to a raw material sample and measuring the sample's response to that field. Dielectric spectrum data reflects the influence of the material's internal polarization behavior, charge transport, and microstructure (such as grain boundaries, defects, and crystal arrangement) on the electric field response. Specifically, the real and imaginary parts of the dielectric spectrum reveal the material's dielectric constant and dielectric loss, parameters closely related to the density, uniformity, and internal defects of the microcrystalline layers. For example, changes in the dielectric constant can indicate the distribution and polarization of the material's internal components, while dielectric loss may be related to energy dissipation and defect density within the material.

[0039] Furthermore, piezoelectric acoustic emission sensors are used to monitor acoustic emission signals generated in real time during the microcrystallization process of raw material samples. Acoustic emission refers to transient elastic waves generated when a material's internal structure changes, stress release, or microcrack propagation occurs. These waves are converted into analyzable electrical signals by the piezoelectric sensor. This acoustic emission data can provide dynamic information about the microcrystalline layer formation process, such as crystal growth, phase transitions, internal stress distribution, and bonding strength. For example, during microcrystallization or rearrangement, minute structural adjustments may occur within the material. These adjustments generate acoustic emission events that can be captured by the sensor, and their frequency, amplitude, and event rate can reflect the formation quality and stability of the microcrystalline layer.

[0040] Therefore, by fusing and analyzing the obtained dielectric spectroscopy data and acoustic emission data, a multi-dimensional and comprehensive evaluation of the microstructure and surface properties of raw material samples can be achieved. The fusing analysis aims to combine the advantages of both types of data; for example, dielectric spectroscopy data provides the correlation between macroscopic electrical properties and microstructure, while acoustic emission data provides information on dynamic structural changes. Through advanced data processing algorithms, such as pattern recognition and machine learning, key features can be extracted from the fused data, and scores for microcrystalline layer compactness, uniformity, and bonding strength can be calculated accordingly.

[0041] This application overcomes the limitations of traditional methods in evaluating the effects of microcrystallization treatment by fusing and analyzing acquired dielectric spectroscopy and acoustic emission data. Traditional methods may rely on a single characterization technique, making it difficult to comprehensively and accurately reflect the compactness, uniformity, and bonding strength of microcrystalline layers. Specifically, dielectric spectroscopy data can reveal the structural integrity, defect density, and uniformity of component distribution within microcrystalline layers from an electrical perspective. For example, highly compact and uniform microcrystalline layers typically exhibit specific dielectric response characteristics. Acoustic emission data, on the other hand, can reflect the physical changes during the formation of microcrystalline layers from a mechanical and dynamic perspective. For instance, during microcrystal growth or bonding, minute stress releases or structural rearrangements may occur within the material, generating acoustic emission signals that can be captured by sensors. By analyzing the frequency, amplitude, and event rate of the acoustic emission signals, the bonding strength and stability within the microcrystalline layer can be assessed. Therefore, fusing and analyzing dielectric spectroscopy and acoustic emission data enables a comprehensive and highly accurate evaluation of the compactness, uniformity, and bonding strength of microcrystalline layers. This multimodal data fusion method can more comprehensively capture the impact of microcrystallization on the microstructure and surface properties of raw material samples, thus providing a more reliable basis for subsequent physical field parameter adjustments.

[0042] In some embodiments described above, the adjustment of the principal physical field parameters is primarily based on the microcrystalline layer density, uniformity, and bonding strength scores of the raw material samples after microcrystallization treatment. However, relying solely on these immediate microstructure and surface characteristic scores may not adequately predict or guarantee the long-term performance and stability of the final product particles. This invention introduces accelerated aging tests and actual long-term performance data to dynamically calibrate the long-term performance correlation factor, thereby achieving precise adjustment of the principal physical field parameters to ensure the long-term performance of the finished particles.

[0043] The adjustment of the main physical field parameters under the main mixing chamber based on the combination of physical field parameters includes: conducting accelerated aging tests on the raw material samples after microcrystallization treatment and monitoring the surface performance change trend of the raw material samples during the accelerated aging test; obtaining the actual long-term performance test results of the finished particles; comparing the surface performance change trend with the actual long-term performance test results; dynamically calibrating the preset long-term performance correlation factor according to the comparison results; and adjusting the main physical field parameters according to the microcrystalline layer density, uniformity, and bonding strength scores, combined with the calibrated long-term performance correlation factor.

[0044] Specifically, accelerated aging tests on raw material samples after microcrystallization treatment involve placing the microcrystallized samples under simulated harsh environments (such as high temperature, high humidity, light exposure, and cyclic freeze-thaw cycles) to simulate their long-term performance changes under normal storage and use conditions within a short period. During this process, it is necessary to continuously monitor the surface properties of the raw material samples, such as their anti-caking properties, hygroscopicity, surface hardness, or nutrient release characteristics, to assess their stability under accelerated aging conditions.

[0045] The actual long-term performance test results of the finished product granules are obtained through long-term tracking tests on the packaged finished granules during actual production. For example, key performance indicators such as nutrient slow-release curves, crushing strength, and anti-caking rate are periodically tested under different storage conditions to obtain true and reliable long-term performance data. These data reflect the product's performance in practical applications.

[0046] In practical applications, comparing the surface performance change trend with the actual long-term performance test results means comparing and analyzing the surface performance change trend of the raw material sample observed in the accelerated aging test with the actual long-term performance test results of the finished particles.

[0047] Furthermore, based on the comparison results, the preset long-term performance correlation factors are dynamically calibrated. Through the above comparative analysis, the pre-set factors used to correlate the microcrystalline layer characteristics with long-term performance are adjusted in real time or periodically. These correlation factors can be weighting coefficients or transformation parameters in the mathematical model, and their dynamic calibration ensures that the model can more accurately reflect the actual long-term performance under the current production batch's raw material and process conditions.

[0048] Therefore, adjusting the master physical field parameters based on the microcrystalline layer's density, uniformity, and bonding strength scores, combined with calibrated long-term performance correlation factors, means that during microcrystallization treatment in the main mixing chamber, not only are the immediate microcrystalline layer scores obtained from the test chamber considered, but more importantly, these scores are combined with dynamically calibrated long-term performance correlation factors. This combination allows the adjustment of master physical field parameters (e.g., the frequency and power of low-frequency sound waves generated by an ultrasonic vibrator, or the intensity and duration of non-thermal microwaves generated by a microwave generator) to simultaneously optimize the immediate structural characteristics of the microcrystalline layer and the long-term functional performance of the final product, thereby achieving more comprehensive and intelligent process control.

[0049] The accelerated aging test of this application can simulate the performance degradation process of raw material samples under long-term storage and use conditions in a short time, thereby quickly obtaining the trend of surface performance changes. Simultaneously, by obtaining the actual long-term performance test results of the finished particles, it provides benchmark data for product performance in the real world. Comparing these two types of data allows the establishment of a mapping relationship between short-term accelerated aging performance and long-term actual performance. Based on this mapping relationship, preset long-term performance correlation factors are dynamically calibrated, enabling these factors to more accurately reflect the long-term performance patterns under the current production batch's raw material characteristics and process conditions. Finally, when adjusting the master physical field parameters, not only are immediate indicators such as microcrystalline layer density, uniformity, and bonding strength considered, but more importantly, these indicators are combined with the calibrated long-term performance correlation factors. This comprehensive consideration ensures that the adjustment of the master physical field parameters takes into account both the immediate formation quality of the microcrystalline layer and the long-term performance of the finished particles, thereby ensuring that the microcrystallization process can produce powder fertilizer products with excellent long-term stability and functionality.

[0050] In some preferred embodiments, it is assumed that in the production of a certain batch of powder fertilizer, the microcrystalline layer density, uniformity, and bonding strength scores of the raw material sample were obtained through a microcrystallization treatment test in a test chamber. To ensure the long-term sustained-release performance of the final product granules, the microcrystallized raw material sample was placed in a multi-functional aging test chamber for accelerated aging tests, for example, at 60°C and 80% relative humidity for 7 consecutive days, and the trend of its nutrient sustained-release rate was monitored. Simultaneously, the nutrient sustained-release performance test results of similar formulation finished granules after 12 months of actual storage were obtained from historical production data. By comparing the trend of nutrient sustained-release rate changes in the accelerated aging test with the actual long-term performance test results, it was found that the currently preset long-term performance correlation factor underestimated the impact of high temperature and high humidity on sustained-release performance. Based on this comparison result, the distributed control system dynamically calibrated the long-term performance correlation factor, increasing its weight under high temperature and high humidity conditions. Finally, when adjusting the master physical field parameters under the main mixing chamber, the system comprehensively considered the microcrystalline layer score obtained in real time and the calibrated long-term performance correlation factor. For example, if the calibrated factor indicates a need for stronger microcrystalline layer stability to resist humid and hot environments, the system may fine-tune the frequency or power of the ultrasonic vibrator to further optimize the crystal structure while ensuring the compactness of the microcrystalline layer, thereby improving the long-term stability of nutrient encapsulation and ensuring that the finished particles can achieve the expected long-term sustained-release effect in practical applications.

[0051] To address this, the accelerated aging test of the raw material sample after microcrystallization treatment in this application, and the monitoring of the surface property change trend of the raw material sample during the accelerated aging test, includes: extracting the raw material sample after microcrystallization treatment from the test chamber through a distributed control system, and placing the raw material sample after microcrystallization treatment in a multifunctional aging test chamber; monitoring the changes in the internal crystal structure, nutrient release rate, and crush resistance of the raw material sample after microcrystallization treatment during the accelerated aging process; and establishing a trend map of the changes in the internal structure and key functional characteristics of the raw material sample after microcrystallization treatment based on the changes in the internal crystal structure, the nutrient release rate, and the crush resistance.

[0052] Specifically, a distributed control system extracts the raw material samples after the microcrystallization treatment test from the test chamber. Representative raw material samples are accurately obtained from the test chamber according to a preset mass or volume, after the microcrystallization treatment test has been completed. Subsequently, the raw material samples after the microcrystallization treatment test are placed in a multifunctional aging test chamber. This multifunctional aging test chamber is a specialized device capable of simulating various harsh environmental conditions (such as high temperature, high humidity, ultraviolet radiation, and oxidizing atmospheres). Its purpose is to accelerate the aging process of the raw material samples, thereby allowing for the observation of potential performance changes under long-term storage or use conditions within a relatively short period.

[0053] Furthermore, the changes in internal crystal structure, nutrient slow-release rate, and crush resistance of the raw material samples after the microcrystallization treatment were monitored during accelerated aging. Internal crystal structure changes refer to the analysis of changes in microstructural parameters such as crystal phase composition, crystallinity, and grain size during the aging process using techniques such as X-ray diffraction (XRD), Raman spectroscopy, or Fourier transform infrared spectroscopy (FTIR). The purpose is to reveal the stability of the microcrystallization treatment effect and potential crystal degradation or reconstruction phenomena. Nutrient slow-release rate refers to the periodic detection of the release rate of nutrients (such as nitrogen, phosphorus, and potassium) in the raw material samples through simulated soil environments or specific solvent immersion tests. The purpose is to evaluate the functional stability of the microcrystallized powder as a slow-release fertilizer. Crushing resistance refers to the ability of the raw material samples to resist external force breakage during aging using methods such as particle strength testing or microindentation testing. The purpose is to reflect the mechanical strength and structural integrity of the particles.

[0054] Therefore, based on the changes in the internal crystal structure, the nutrient slow-release rate, and the crush resistance, a trend map of the changes in the internal structure and key functional properties of the raw material sample after the microcrystallization treatment experiment is established. This map integrates and visualizes the aforementioned multi-dimensional monitoring data, forming a curve or three-dimensional graph showing the changes over aging time. Its purpose is to intuitively and comprehensively demonstrate the dynamic evolution of the internal structure and key functional properties of the raw material sample during accelerated aging, providing comprehensive data support for subsequent performance evaluation and parameter calibration.

[0055] This application's method utilizes a distributed control system to precisely extract raw material samples after microcrystallization treatment and places them in a controllable multifunctional aging test chamber for accelerated aging, ensuring the accuracy and repeatability of the test. By comprehensively monitoring three key parameters—internal crystal structure changes, nutrient slow-release rate, and crush resistance—this method can comprehensively evaluate the long-term stability of microcrystallized powders from multiple dimensions, including microstructure, functional characteristics, and mechanical properties. This multi-dimensional data is integrated and used to establish trend maps, providing a deeper and more comprehensive understanding of the performance evolution of raw material samples during accelerated aging. This overcomes the limitations that may arise from focusing solely on surface properties and provides a more solid and reliable data foundation for subsequent calibration of long-term performance correlation factors.

[0056] In some preferred embodiments, the specific implementation is as follows: First, a robotic arm is precisely controlled by a distributed control system to extract 50 grams of the microcrystallized raw material sample from the test chamber. Then, the sample is evenly spread in the sample tray of a multi-functional aging test chamber. The test chamber is set to simulate a high-temperature and high-humidity environment, such as a temperature of 60°C and a relative humidity of 90%, supplemented by ultraviolet irradiation, for a continuous period of 7 days. During the aging process, the sample is monitored daily as follows: Changes in internal crystal structure: The sample was scanned using an X-ray diffractometer to obtain diffraction patterns. By analyzing the position, intensity, and full width at half maximum (FWHM) of the diffraction peaks, the changes in crystal phase composition and crystallinity were quantitatively analyzed.

[0057] Nutrient slow release rate: Some aged samples were soaked in simulated soil solution, and the concentration of key nutrient elements in the solution was periodically detected by inductively coupled plasma optical emission spectrometry (ICP-OES) to calculate their release rate.

[0058] Crushing resistance: Individual particles were crushed using a microindentation tester, and the crushing force was recorded to assess the change in the particle's mechanical strength.

[0059] Finally, these multi-dimensional data are input into the data processing module to generate internal crystal structure change curves, nutrient slow release rate curves, and crushability change curves. These curves are then integrated into a comprehensive trend graph to intuitively show the performance evolution of the raw material sample during accelerated aging.

[0060] The comparison of the surface performance change trend with the actual long-term performance test results in this application includes: matching and loading the corresponding dynamic long-term performance target from the preset long-term performance target library according to the raw material characteristics and product formula of the current production batch; comparing the change trend spectrum with the dynamic long-term performance target; and adjusting the weight of the dynamic long-term performance target when a deviation is detected between the actual performance in the change trend spectrum and the dynamic long-term performance target.

[0061] Specifically, before comparison, it is necessary to match and load corresponding dynamic long-term performance targets from a pre-set long-term performance target library based on the raw material characteristics and product formulation of the current production batch. This long-term performance target library can be understood as storing a set of long-term performance indicators for different raw material types, product formulations, and application scenarios, such as different nutrient release curves, crushing strength thresholds, and crystal structure stability requirements. The dynamic long-term performance targets refer to the performance expectations intelligently selected or generated from the target library based on the specific conditions of current production, which best match the characteristics of the current batch of products. The purpose is to ensure that subsequent comparison and calibration processes can specifically reflect the actual needs of the current product, avoiding deviations caused by using general targets.

[0062] Furthermore, comparing the trend chart with the dynamic long-term performance target refers to comparing the trend chart of changes in the internal structure and key functional characteristics of the raw material sample established based on accelerated aging tests with the applied dynamic long-term performance target. This comparison can be performed using various data analysis and pattern recognition techniques, such as calculating the similarity, difference, or deviation between the two. Its purpose is to quantify the gap between the performance of the raw material sample after microcrystallization treatment during accelerated aging and the expected target.

[0063] Furthermore, when a deviation is detected between the actual performance in the trend graph and the dynamic long-term performance target, the weight of the dynamic long-term performance target needs to be adjusted. This deviation can be understood as a quantitative difference between the actual performance and the dynamic target, such as exceeding a preset tolerance range. Adjusting the weight of the dynamic long-term performance target means correcting the influence of the dynamic target in subsequent calibration processes based on the magnitude and direction of the deviation. For example, if the deviation of a certain performance indicator is large, its weight can be appropriately increased to give it higher priority when calibrating the long-term performance correlation factor, thereby guiding the adjustment direction of the main physics parameters to more effectively compensate for the deficiency in that performance.

[0064] This application effectively addresses the lack of adaptability of traditional comparison methods in the face of diverse production scenarios by introducing dynamic long-term performance targets and their weight adjustment mechanisms. Specifically, by matching and loading dynamic long-term performance targets based on the characteristics of raw materials and product formulations of the current batch, the accuracy and relevance of the comparison benchmark are ensured, making the assessment of the surface performance change trend of raw material samples in accelerated aging tests more closely aligned with actual production needs. It is precisely this dynamic adaptability that allows subsequent comparison results to more accurately reflect the true performance gap of the current product. Furthermore, when a deviation between actual performance and the dynamic target is detected, adjusting the weight of the dynamic long-term performance target can specifically strengthen or weaken the influence of specific performance indicators in the calibration process of long-term performance correlation factors, thereby guiding the adjustment direction of the main physical field parameters. This allows for more precise optimization of the microcrystallization treatment effect to compensate for specific performance deficiencies. This adaptive feedback mechanism enables the entire production process to be intelligently optimized based on real-time data, significantly improving the accuracy and effectiveness of physical field parameter adjustments.

[0065] In some preferred embodiments, a specific example is given below. Suppose a powder fertilizer manufacturer needs to produce two slow-release fertilizer products with different formulations: one is a fast-acting slow-release fertilizer for rice, and the other is a long-term slow-release fertilizer for corn. These two products have drastically different requirements for nutrient release rate and crystal structure stability.

[0066] When producing fast-acting slow-release fertilizer for rice, the distributed control system matches and loads dynamic long-term performance targets for the fertilizer from a pre-set long-term performance target library based on the characteristics of the raw materials in the current batch (e.g., nitrogen source type, particle size) and the product formulation. This target might be set to release 80% of the nutrients within a specific timeframe, with moderate requirements for crystal structure stability. In accelerated aging tests, if the nutrient release rate trend chart of the raw material sample shows a slow release rate that deviates significantly from the dynamic target, the system will correspondingly increase the weight of the "nutrient release rate" indicator in the dynamic long-term performance targets. Subsequently, when calibrating the long-term performance correlation factor, this high-weight indicator will guide the system to adjust the master physical field parameters, such as increasing the frequency of the ultrasonic vibrator or the power of the microwave generator, to promote faster nutrient release, thus making the microcrystalline powder fertilizer more suitable for fast-acting slow-release fertilizer.

[0067] Conversely, when producing long-release corn fertilizer, the system loads dynamic long-term performance targets specific to long-release fertilizers. These targets may require uniform nutrient release over a longer period and place higher demands on crystal structure stability. If accelerated aging tests reveal that the crystal structure stability trend of the raw material sample indicates insufficient stability and deviates from the dynamic targets, the system will increase the weight of the "crystal structure stability" indicator. This will prompt the system to adjust the master physical field parameters, such as optimizing the amplitude of the ultrasonic vibrator or the action time of the microwave generator, to form a denser and more stable microcrystalline layer, thereby ensuring that the finished granules meet the requirements for long-term slow release.

[0068] Through this dynamic matching and weight adjustment mechanism, the powder fertilizer production method of this application can flexibly adapt to the production needs of different products and raw materials, ensuring that the best-performing finished granules can be obtained in each production run.

[0069] To address this, the monitoring of internal crystal structure changes in raw material samples after the microcrystallization treatment test during accelerated aging in this application includes: performing layer-by-layer scanning on the raw material samples after the microcrystallization treatment test to obtain Raman spectral data of the surface layer and core region of the raw material samples after the microcrystallization treatment test; performing crystal phase identification and quantitative analysis on the Raman spectral data of the surface layer and core region to obtain the content and crystallinity of each crystal phase; comparing the changes in the content and crystallinity of each crystal phase before and after the microcrystallization treatment test; distinguishing the degree of crystal phase optimization caused by the microcrystallization treatment test from the degree of crystal phase degradation caused by the accelerated aging based on the comparison results; and calculating the contribution of the microcrystallization treatment test to the stability of the crystal structure of the surface layer and the core region based on the degree of crystal phase optimization and the degree of crystal phase degradation.

[0070] Specifically, equipment such as a confocal Raman spectrometer can be used to perform non-destructive analysis of different depths of the raw material sample by adjusting the depth of focus, thereby obtaining Raman spectral data of its surface layer and core region. Raman spectral data can reflect the molecular vibrational information of a substance, thus revealing its microscopic properties such as crystal structure, crystal phase composition, and crystallinity. The surface layer typically refers to the outermost few micrometers to tens of micrometers of the sample, while the core region refers to the deeper internal structure of the sample.

[0071] Furthermore, by analyzing the position, intensity, and shape of characteristic peaks in the Raman spectrum, various crystalline phases present in the sample (e.g., compounds of different crystal forms, hydrates, or anhydrous substances) are identified. Quantitative calculations are then performed based on the intensity or area of ​​the characteristic peaks for each crystalline phase, thereby obtaining the relative content and crystallinity of each phase. Crystallinity can be understood as the proportion of crystalline components in the sample and is an important indicator of the ordered structure of a material.

[0072] Based on this, the sample data after microcrystallization treatment and accelerated aging were compared with the sample data without microcrystallization treatment or accelerated aging treatment to quantify the specific changes in crystal phase composition and crystallinity.

[0073] Therefore, distinguishing between the degree of crystal phase optimization caused by the microcrystallization treatment and the degree of crystal phase degradation caused by accelerated aging, based on the comparison results, refers to determining which structural changes are desired by the microcrystallization treatment (e.g., forming a more stable crystal form, increasing crystallinity, reducing grain size) and which are adverse effects of accelerated aging (e.g., crystal structure destruction, amorphization, forming an unstable crystal form). The degree of crystal phase optimization quantifies the positive contribution of microcrystallization treatment to structural stability, while the degree of crystal phase degradation quantifies the negative impact of the aging process on structural stability.

[0074] Finally, based on the degree of crystal phase optimization and the degree of crystal phase degradation, the contribution of the microcrystallization treatment experiment to the stability of the crystal structure of the surface layer and the core region is calculated. This contribution value can be a comprehensive index used to evaluate the actual effect of microcrystallization treatment in resisting aging and maintaining crystal structure stability.

[0075] The proposed method involves performing layer-by-layer scanning on raw material samples after microcrystallization treatment to obtain Raman spectral data of the surface layer and core region, thereby acquiring detailed information about the internal crystal structure of the sample at different depths. By performing crystal phase identification and quantitative analysis on these Raman spectral data, the content and crystallinity of each crystal phase can be accurately determined. Furthermore, by comparing the changes in the content and crystallinity of each crystal phase before and after the microcrystallization treatment, and combining this with an understanding of the mechanisms of microcrystallization treatment and accelerated aging, the degree of crystal phase optimization caused by microcrystallization treatment and the degree of crystal phase degradation caused by accelerated aging can be effectively distinguished. It is precisely this refined distinction that allows for the accurate calculation of the contribution of the microcrystallization treatment to the stability of the crystal structure in the surface layer and core region, thus overcoming the limitation of traditional monitoring methods that cannot effectively distinguish between the two effects.

[0076] In some preferred embodiments, the specific implementation is as follows: First, the raw material sample after microcrystallization treatment is extracted from the test chamber and divided into two parts. One part serves as a control group, and is immediately subjected to layered Raman spectroscopy scanning to obtain initial Raman spectral data of its surface layer and core region. Crystal phase identification and quantitative analysis are then performed to obtain the initial content and crystallinity of each crystal phase. The other part of the sample is placed in a multifunctional aging test chamber for accelerated aging testing. At different time points during the accelerated aging test (e.g., 24 hours, 48 ​​hours, 72 hours), or after the accelerated aging test, the aged sample is again subjected to layered Raman spectroscopy scanning to obtain Raman spectral data of its surface layer and core region. Subsequently, crystal phase identification and quantitative analysis are performed on the Raman spectral data after aging. By comparing the data after aging with the initial data, specific changes in the content and crystallinity of each crystal phase can be observed. For example, if the microcrystallization treatment aims to increase the proportion of a certain stable crystal phase, and the content of this crystal phase remains stable or slightly increases during the aging process, it can be determined as crystal phase optimization; conversely, if amorphization or the formation of unstable crystal phases occurs, it is determined as crystal phase degradation. Based on this quantitative data, a model or scoring system can be established to calculate the specific contribution of microcrystallization treatment to the stability of the crystal structure. For example, by comparing the relative magnitudes of the degree of optimization and the degree of degradation, the net effect of microcrystallization treatment in resisting aging can be obtained.

[0077] In response, Figure 3 The flowchart illustrates a method for obtaining molded particles by isothermal molding of microcrystalline powder according to an embodiment of the present invention, specifically including: 301. The absorption spectrum and phase spectrum of the microcrystalline powder are obtained using a terahertz spectrometer at the inlet of the molding equipment; Specifically, the process of obtaining the absorption spectrum and phase spectrum of the microcrystalline powder using a terahertz spectrometer at the inlet of the molding equipment includes: performing Fourier transform and baseline correction on the original terahertz spectral data; extracting the absorption peak intensity and broadening at the terahertz frequency; and determining the absorption spectrum and phase spectrum of the microcrystalline powder based on the absorption peak intensity and broadening.

[0078] Specifically, raw terahertz spectral data refers to the unprocessed, raw signal data directly acquired by a terahertz spectrometer, typically existing as a time-domain waveform. This raw data contains the absorption and scattering information of the microcrystalline powder in the terahertz frequency band, but may also contain interference such as noise and baseline drift. Fourier transform is used to convert the raw terahertz spectral data from the time domain to the frequency domain, thereby revealing the intensity information of different frequency components. Baseline correction is used to eliminate baseline shifts in the spectral data caused by instrument drift, environmental interference, or sample background absorption, ensuring the accuracy of subsequent analyses.

[0079] In this process, absorption peaks at specific terahertz frequencies are identified and quantified in the frequency domain spectrum after Fourier transform and baseline correction. The intensity of the absorption peak reflects the absorption capacity of the microcrystalline powder for terahertz waves at that frequency, and is typically related to factors such as the material's composition, concentration, and crystal structure. Broadening describes the width of the absorption peak, providing information about the material's internal structural uniformity, intermolecular interactions, and crystal defects. In practical applications, various spectral analysis algorithms, such as Gaussian fitting, Lorentz fitting, or multi-peak fitting, can be used to accurately identify and quantify the intensity and broadening of these absorption peaks.

[0080] The proposed method transforms the original terahertz spectral data into a frequency domain signal through Fourier transform, thus clearly revealing the response characteristics of microcrystalline powder at different terahertz frequencies. Furthermore, baseline correction effectively eliminates background interference, resulting in purer spectral data and laying the foundation for subsequent accurate analysis. Therefore, by extracting the absorption peak intensity and broadening at the processed terahertz frequencies, the characteristic absorption information of microcrystalline powder in the terahertz band can be accurately captured. Finally, based on these precise absorption peak intensity and broadening data, the absorption spectrum and phase spectrum of the microcrystalline powder can be reliably determined, providing high-quality input data for subsequent particle binding potential index calculations.

[0081] S302. Measure the microrheological data of the microcrystalline powder based on an optical microrheological sensor array at the inlet of the molding equipment; Specifically, before the microcrystalline powder enters the molding equipment, a terahertz spectrometer located at the equipment inlet can non-contactly acquire its absorption and phase spectra. The terahertz spectrometer provides information on the powder material's lattice vibrations, intermolecular interactions, and moisture content—information crucial for evaluating the powder's microstructure and bonding properties. Simultaneously, an optical microrheological sensor array is used to measure the microrheological data of the microcrystalline powder. This array can monitor the powder's flowability, viscosity, and interparticle interactions in real time, reflecting the powder's deformation and bonding behavior during the molding process.

[0082] S303. Calculate the particle binding potential index based on the absorption spectrum, phase spectrum, and microrheological data; The acquired absorption spectrum, phase spectrum, and microrheological data are input into a distributed control system for fusion analysis to calculate the particle binding potential index. The particle binding potential index is a comprehensive indicator used to quantify the potential ability of current microcrystalline powders to form stable particles under specific molding conditions. The calculation of this index can be based on a pre-defined mathematical model or machine learning algorithm, extracting and weighting key features from the spectral and rheological data.

[0083] S304. Based on the particle bonding potential index and the preset potential index target range, dynamically predict the molding temperature and pressure required when the next segment of microcrystalline powder enters the main molding zone. S305, The molding temperature control heating module operates to control the extrusion pressure of the rolling press based on the pressure value.

[0084] In practical applications, the distributed control system dynamically predicts the optimal molding temperature and pressure values ​​required for the next stage of microcrystalline powder entering the main molding zone, based on the calculated particle bonding potential index and a preset target range for the potential index. For example, when the particle bonding potential index is low, it may be necessary to appropriately increase the molding temperature or pressure to promote particle bonding; conversely, when the potential index is high, the molding temperature or pressure can be appropriately reduced to save energy. The predicted molding temperature value is used to control the operation of the heating module to precisely regulate the temperature of the molding zone; while the predicted pressure value is used to control the extrusion pressure of the roller press to ensure that the powder is pressed and molded under optimal conditions.

[0085] This application's solution effectively addresses the challenges faced by traditional isothermal molding methods when processing microcrystalline powders with significant property fluctuations by introducing a real-time online monitoring and dynamic parameter adjustment mechanism. Specifically, the collaborative operation of a terahertz spectrometer and an optical microrheological sensor array enables comprehensive and real-time capture of the microstructure and macroscopic rheological properties of the microcrystalline powder. This data is used to accurately calculate the particle bonding potential index, which serves as a quantitative indicator of powder molding performance and provides a scientific basis for subsequent parameter adjustments. It is precisely because the molding temperature and pressure can be dynamically predicted and adjusted based on real-time data that the molding process can adaptively optimize according to the actual state of the powder, thereby overcoming the limitations of fixed-parameter molding.

[0086] In some preferred embodiments, assuming that before a batch of microcrystalline powder enters the molding equipment, the terahertz spectrometer detects a slight decrease in the intensity of the absorption peak, indicating that its crystallinity may be slightly insufficient; simultaneously, the viscosity value measured by the optical microrheological sensor array in the microrheological data is high, indicating poor powder flowability. Based on this real-time data, the particle bonding potential index calculated by the distributed control system is lower than the preset ideal range. At this time, the system will dynamically predict and instruct the heating module to appropriately increase the molding temperature by 5°C, and instruct the roller press to increase the extrusion pressure by 10%, to compensate for the problems of insufficient powder crystallinity and poor flowability, ensuring that the microcrystalline powder can obtain the best bonding conditions when entering the main molding zone, ultimately forming high-strength, highly uniform molded particles.

[0087] Specifically, Figure 4 A schematic diagram of a powder fertilizer production system according to an embodiment of the present invention is shown. The system is controlled by a distributed control system and includes: An automatic feeding module is used to obtain the production formula of the current batch of powder fertilizer and automatically feed the raw materials according to the production formula of the powder fertilizer. The crystallization module is used to perform high-intensity homogenization mixing on the raw materials after automatic feeding, and to apply a physical field during the high-intensity homogenization mixing process. The physical field is used to perform microcrystallization treatment on the mixed raw materials to obtain microcrystallized powder. A constant-temperature forming module is used to form the microcrystalline powder at a constant temperature to obtain shaped particles; A cooling and molding module is used to cool and solidify the molded particles to obtain finished particles; An automatic packaging module is used to convey the finished product granules to an automatic packaging device, which packages and seals the finished product granules according to preset packaging parameters.

[0088] This system aims to overcome many problems in traditional powder fertilizer production through integrated modular design and intelligent coordination of a distributed control system. Through close collaboration among its functional modules, it achieves intelligent control throughout the entire process, from precise raw material feeding, refined microcrystalline processing, constant-temperature molding, cooling and solidification to automated packaging. This effectively improves the consistency of powder fertilizer product quality, nutrient uniformity, physical stability, and the flexibility and customization capabilities of the production line.

[0089] The powder fertilizer production system proposed in this application applies a physical field to microcrystallize the powder fertilizer during high-intensity homogenization mixing, fundamentally optimizing its microstructure and significantly improving its nutrient slow-release performance, anti-caking properties, and physical stability. Furthermore, the application of a distributed control system enables real-time linkage and precise control of all stages of the production process, effectively solving the problems of insufficient flexibility and difficulty in quickly responding to small-batch, multi-formulation customized production needs of traditional production lines. Through this integrated system design, this application not only improves production efficiency and product quality but also provides solid technical support for the development and application of high-quality, functional powder fertilizers, demonstrating significant progress.

[0090] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for producing powder fertilizer, characterized in that, The method employs a distributed control system for control, including: Obtain the production formula for the current batch of powder fertilizer, and automatically feed the raw materials according to the powder fertilizer production formula; The raw materials after automatic feeding are subjected to high-intensity homogenization and mixing, and a physical field is applied during the high-intensity homogenization process. The physical field is used to microcrystallize the mixed raw materials to obtain microcrystallized powder. The microcrystalline powder is subjected to constant temperature molding to obtain molded particles; The molded particles are cooled and solidified to obtain finished particles; The finished product granules are conveyed to an automatic packaging device, which packages and seals the finished product granules according to preset packaging parameters.

2. The method for producing powder fertilizer according to claim 1, characterized in that, The process of performing high-intensity homogenization mixing on the automatically fed raw materials, and applying a physical field during the high-intensity homogenization mixing process, includes: The raw material sample is extracted by a cyclone separator and transported to the test chamber. The raw material sample is the preset mass of the automatically fed raw material extracted non-invasively from the inlet of the main mixing chamber by the cyclone separator. The raw material sample is subjected to microcrystallization treatment test by controlling the operating parameters in the test chamber. The operating parameters include: uniform stirring operating parameters and microcrystallization treatment parameters, wherein the microcrystallization treatment parameters are ultrasonic operating parameters or microwave operating parameters. To obtain the microstructure and surface properties of raw material samples under microcrystallization treatment experiments; The combination of physical field parameters for the current raw material is determined based on the microstructure and surface properties of the raw material sample. The main physical field parameters under the main mixing chamber are adjusted based on the combination of physical field parameters, and the raw materials after automatic feeding are microcrystallized based on the main physical field parameters; the main physical field parameters are low-frequency sound waves generated by an ultrasonic vibrator or non-thermal microwaves generated by a microwave generator.

3. The method for producing powder fertilizer according to claim 2, characterized in that, The microstructure and surface properties of the raw material samples obtained under the microcrystallization treatment test include: An impedance analyzer controlled by a distributed control system is used to apply an alternating electric field of scanning frequency to the raw material sample under the microcrystallization treatment test to obtain the dielectric spectrum data of the raw material sample under the microcrystallization treatment test. Acoustic emission data of the raw material sample under the microcrystallization treatment test were obtained by a piezoelectric acoustic emission sensor controlled by a distributed control system. The dielectric spectrum data and the acoustic emission data are fused and analyzed to obtain the microcrystalline layer compactness, uniformity and bonding strength scores of the raw material sample under the microcrystallization treatment test.

4. The method for producing powder fertilizer according to claim 3, characterized in that, The adjustment of the main physical field parameters under the main mixing cavity based on the combination of physical field parameters includes: Accelerated aging tests were conducted on the raw material samples after microcrystallization treatment, and the trend of surface property changes of the raw material samples during the accelerated aging tests was monitored. Obtain the actual long-term performance test results of the finished product particles; Compare the trend of surface properties with the actual long-term performance test results; The preset long-term performance correlation factor is dynamically calibrated based on the comparison results; The master physics parameters are adjusted based on the microcrystalline layer density, uniformity, and bonding strength scores, combined with a calibrated long-term performance correlation factor.

5. The method for producing powder fertilizer according to claim 4, characterized in that, The accelerated aging test on the raw material samples after the microcrystallization treatment, and the monitoring of the surface property change trend of the raw material samples during the accelerated aging test, includes: The raw material sample after microcrystallization treatment in the test chamber is extracted by a distributed control system and then placed in a multifunctional aging test chamber. Monitor the changes in internal crystal structure, nutrient slow release rate, and medium crush resistance of the raw material samples after the microcrystallization treatment test during accelerated aging. Based on the changes in the internal crystal structure, the nutrient slow-release rate, and the crush resistance, a trend map of the changes in the internal structure and key functional properties of the raw material sample after the microcrystallization treatment experiment was established.

6. The method for producing powder fertilizer according to claim 5, characterized in that, The comparison of the surface performance change trend with the actual long-term performance test results includes: Based on the raw material characteristics and product formula of the current production batch, the corresponding dynamic long-term performance targets are matched and loaded from the preset long-term performance target library. Compare the trend graph with the dynamic long-term performance target; When a deviation is detected between the actual performance in the trend graph and the dynamic long-term performance target, the weight of the dynamic long-term performance target is adjusted.

7. The method for producing powder fertilizer according to claim 5, characterized in that, The monitoring of changes in the internal crystal structure of the raw material sample after the microcrystallization treatment test during accelerated aging includes: The raw material sample after the microcrystallization treatment experiment was subjected to layer scanning to obtain Raman spectral data of the surface layer and core region of the raw material sample after the microcrystallization treatment experiment; The Raman spectral data of the surface layer and the core region were used for crystal phase identification and quantitative analysis to obtain the content and crystallinity of each crystal phase. Compare the changes in the content and crystallinity of each crystalline phase before and after the microcrystallization treatment experiment; The comparison results distinguish between the degree of crystal phase optimization caused by the microcrystallization treatment test and the degree of crystal phase degradation caused by the accelerated aging. The contribution of the microcrystallization treatment experiment to the stability of the crystal structure of the surface layer and the core region is calculated based on the degree of crystal phase optimization and the degree of crystal phase degradation.

8. The method for producing powder fertilizer according to claim 1, characterized in that, The process of obtaining molded particles by constant-temperature molding of the microcrystalline powder includes: The absorption spectrum and phase spectrum of the microcrystalline powder were obtained using a terahertz spectrometer at the inlet of the molding equipment. The microrheological data of the microcrystalline powder are measured using an optical microrheological sensor array at the inlet of the molding equipment. The particle binding potential index is calculated based on the absorption spectrum, phase spectrum, and microrheological data. Based on the particle bonding potential index and the preset potential index target range, the required molding temperature and pressure values ​​when the next segment of microcrystalline powder enters the main molding zone are dynamically predicted. The forming temperature control heating module operates to control the extrusion pressure of the rolling press based on the pressure value.

9. The method for producing powder fertilizer according to claim 8, characterized in that, The terahertz spectrometer at the inlet of the molding equipment is used to obtain the absorption spectrum and phase spectrum of the microcrystalline powder, including: Fourier transform and baseline correction were performed on the raw terahertz spectral data; Extracting the absorption peak intensity and broadening at terahertz frequencies; The absorption spectrum and phase spectrum of the microcrystalline powder are determined based on the absorption peak intensity and broadening.

10. A system for producing powder fertilizer, characterized in that, The system employs a distributed control system, including: An automatic feeding module is used to obtain the production formula of the current batch of powder fertilizer and automatically feed the raw materials according to the production formula of the powder fertilizer. The crystallization module is used to perform high-intensity homogenization mixing on the raw materials after automatic feeding, and to apply a physical field during the high-intensity homogenization mixing process. The physical field is used to perform microcrystallization treatment on the mixed raw materials to obtain microcrystallized powder. A constant-temperature forming module is used to form the microcrystalline powder at a constant temperature to obtain shaped particles; A cooling and molding module is used to cool and solidify the molded particles to obtain finished particles; An automatic packaging module is used to convey the finished product granules to an automatic packaging device, which packages and seals the finished product granules according to preset packaging parameters.

Images