A method and apparatus for sorting nickel powder for silver-nickel paste

Abstract

This invention discloses a method and apparatus for sorting nickel powder for silver-nickel paste, relating to the field of electronic material preparation technology. The invention involves pretreatment via atmosphere replacement, followed by deagglomeration under an alternating magnetic field, corona charging, grading and screening, and closed-loop gas circulation to complete the sorting process. Each stage is equipped with a precise detection module to collect data in real time, while the main control module dynamically adjusts parameters. During grading, a voltage of the same polarity is applied to form an electrostatic shielding layer, and the purified gas is recycled and reused. The apparatus includes a chamber, a Venturi device, an alternating magnetic field dispersion chamber, a grading chamber, a fan, and various detection modules, exhibiting an integrated structure and strong interconnectivity. This invention achieves precise control and integrated operation throughout the entire sorting process, effectively improving the uniformity and purity of nickel powder particle size, reducing energy consumption and material loss, avoiding nickel powder oxidation contamination, and meeting the stringent requirements of silver-nickel paste for raw materials. Its practicality and economic efficiency are significant.

Description

Technical Field

[0001] This invention relates to the field of electronic material preparation technology, specifically to a method and apparatus for sorting nickel powder for silver-nickel paste. Background Technology

[0002] Silver-nickel paste, as an important electronic functional material, is widely used in the electrical contact parts of electronic components such as circuit breakers, relays, and switches due to its excellent conductivity, wear resistance, and stability. Its performance directly determines the service life and operational reliability of the end product. Nickel powder, as one of the core raw materials of silver-nickel paste, has extremely high requirements for its particle size distribution, purity, and dispersibility. Uneven particle size, residual impurities, or excessive agglomerates will lead to uneven mixing of the silver-nickel paste, deterioration of conductivity and printability, and consequently affect the contact resistance and conduction stability of electronic components.

[0003] Currently, the sorting of nickel powder for silver-nickel paste mostly adopts a combination of traditional airflow classification and sieving. There is a major core technical bottleneck that needs to be addressed: the existing process lacks a precise detection and dynamic control mechanism that links all stages. The parameters of each stage of dispersion, charging, and classification are poorly matched. Traditional dispersion methods lack quantitative detection and dynamic adjustment capabilities. Charge detection is easily interfered with and cannot match the classification flow rate. The control of classification flow rate lacks reliable data support. Ultimately, this results in poor consistency of nickel powder particle size distribution and insufficient target particle size screening accuracy, making it difficult to meet the stringent requirements of silver-nickel paste for raw materials.

[0004] Therefore, we provide a method and apparatus for sorting nickel powder for silver-nickel paste to solve one or more of the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for sorting nickel powder for silver-nickel paste, so as to solve one or more problems mentioned in the background art.

[0006] This invention provides a method for sorting nickel powder for silver-nickel paste, comprising the following steps: Step 1: The data detection and extraction module collects real-time data of the crude nickel powder to be sorted in the chamber and feeds it back to the main control module. After receiving various types of data, the main control module analyzes and controls the airflow velocity and voltage of the alternating electromagnetic coil, the corona discharge module, and the classification chamber. High-purity nitrogen is introduced through the high-purity nitrogen inlet on the side wall of the chamber, while the exhaust port is opened to discharge the original gas in the chamber, thus completing the atmosphere replacement in the chamber. After the data collected by the data detection and extraction module meets the preset requirements, the crude nickel powder in the chamber is sent into the alternating magnetic field dispersion chamber through the Venturi device.

[0007] Step 2: The main control module generates the first acquisition trigger command to the alternating electromagnetic coil based on the real-time data of the coarse nickel powder to be sorted, starts the alternating magnetic field deagglomeration, and collects particle dispersion data through the deagglomeration effect detection module and feeds it back to the main control module. If the dispersion does not reach the preset threshold, the magnetic field parameters are adjusted until the standard is met. After the standard is met, the main control module sends a synchronous trigger signal to control the alternating electromagnetic coil to start the charging process. Step 3: The main control module generates a second acquisition trigger command based on the real-time data of the coarse nickel powder to be sorted and sends it to the corona discharge module. The deagglomerated particles are charged to obtain charged particles. The charge effect detection module collects the charge data of the particles and feeds it back to the main control module. If the charge does not reach the preset threshold, the charge parameters are adjusted until the standard is met. After the standard is met, the main control module sends a grading start signal and fine-tunes the airflow speed according to the charge data. The second fan is started to send the charged particles from the alternating magnetic field dispersion cavity into the grading chamber.

[0008] Step 4: After being charged, the particles are introduced into the classification chamber. The main control module dynamically adjusts the airflow speed based on the feedback signal of the large particle retention amount detected by the large particle retention amount detection module in the first classification chamber. At the same time, the main control module controls the high-voltage power supply module to apply a voltage with the same polarity as the charge carried by the charged particles to the inner walls and screen surface of the first and second classification chambers, forming an electrostatic repulsion shielding layer. Step 5: Large particles are intercepted by the coarse sieve in the first classification chamber, and particles of the target particle size are intercepted by the fine sieve in the second classification chamber. Small particles smaller than the sieve aperture are carried away by the airflow. Particles within the target particle size range are intercepted and sealed in packaging to obtain the target nickel powder. Step 6: After the inert gas drawn from the classification chamber is purified by the high-efficiency dust filter, it is returned to the inlet of the first fan to form a closed loop. The inert gas discharged from the first fan is selectively introduced into the chamber for atmosphere maintenance or into the Venturi device to assist in the transportation of coarse nickel powder through the three-way valve.

[0009] Preferably, in step 1, the data detection and extraction module includes a magnetization intensity detection module, an initial aggregation degree detection module, an oxygen content detection module, and a data extraction trigger unit; The magnetization intensity detection module is used to collect the magnetization intensity data of the coarse nickel powder to be sorted in the chamber; The initial agglomeration detection module is used to collect the initial agglomerate particle size distribution data of the coarse nickel powder to be sorted in the chamber; The oxygen content detection module is used to collect oxygen content data within the chamber.

[0010] Preferably, the data extraction triggering unit includes: The data extraction unit is used to read the generated magnetization intensity data, initial agglomerate particle size distribution data, and oxygen content data from the corresponding detection module; The signal processing unit is used to receive the first data stream composed of the generated magnetization intensity data, initial aggregate particle size distribution data, and oxygen content data, and to perform time synchronization calibration on the first data stream to form a summary data stream in a unified format. The signal transmission unit is used to send data transmission requests to the main control module and send the aggregated data stream to the main control module.

[0011] Preferably, the signal processing unit includes: The data parsing module is used to parse each branch data stream in the first data stream frame by frame and extract the collection timestamp information corresponding to each data point in each branch data stream; The data comparison module is used to compare the acquisition timestamp information of each branch data stream with the preset timing calibration reference clock signal and calculate the time deviation value of each branch data stream relative to the reference clock signal. The data calculation module performs timing compensation adjustment on the time misaligned data points in each branch data stream based on the calculated time deviation value, so that the time axes of the three branch data streams are kept synchronized and aligned. The data processing module is used to perform data integrity checks on the three branch data streams after timing adjustment. After confirming that there are no data missing, duplicate or misaligned issues, it calls the pre-stored unified data format template and fills the synchronized magnetization intensity data, initial agglomerate particle size distribution data and oxygen content data into the corresponding fields according to the field definitions of the unified data format template to generate integrated data. The data validation module is used to validate the format of the integrated data after the fields are filled. Once the data format is confirmed to meet the preset specifications, a unified format summary data stream is generated.

[0012] Preferred, In step 2, the deagglomeration effect detection module is used to respond to the first acquisition trigger command, perform real-time dispersion detection on the particles in the flow path, and generate corresponding particle dispersion data. The depolymerization effect detection module includes: a laser emission unit, a reference calibration unit, a signal receiving unit, a signal processing submodule, a feature extraction submodule, and a feature calculation submodule; The laser emitting unit is used to continuously emit laser light according to a set emission power to form a detection light field covering the particle flow path; The reference calibration unit is used to control the laser emitting unit to emit detection lasers to a preset standard monodisperse particle calibration sample, and to receive and record the reference value of the scattered light signal of the calibration sample. The signal receiving unit is used to convert the captured scattered light signal into an electrical signal and transmit it to the signal processing submodule through the signal transmission line; The signal processing submodule is used to filter the received electrical signal to remove ambient light interference and noise signals caused by circuit noise to form an effective electrical signal. The feature extraction submodule is used to extract amplitude, phase and frequency features from the filtered effective electrical signal to obtain scattering signal feature parameters related to the particle dispersion state. The feature calculation submodule is used to call the pre-stored correspondence model between scattering signal feature parameters and particle dispersion, input the extracted scattering signal feature parameters, and calculate the particle dispersion data.

[0013] Preferably, the charge effect detection module is used to respond to the second acquisition trigger command, perform real-time charge detection on the charged particles on the flow path, and generate corresponding particle charge data. The charge effect detection module includes: an electrostatic detection array unit, a charge reference calibration unit, a charge signal quantization unit, an interference suppression submodule, a charge feature extraction submodule, a charge calculation submodule, and a flow velocity adaptation calculation submodule. The electrostatic detection array unit is used to be deployed along the particle flow path at the outlet of the corona discharge module to form an enclosed charge detection area, and to capture the electrostatic induction signal generated by charged particles in real time through the array of electrodes. The charge reference calibration unit is used to call the pre-stored standard charged particle sample parameters, control the electrostatic detection array unit to perform induction detection on the standard sample with known charge, record the electrostatic induction signal reference value corresponding to the standard sample, and establish the calibration relationship between the detection signal and the charge. The charge signal quantization unit is used to convert the electrostatic induction signal captured by the electrostatic detection array unit into a continuously changing analog voltage signal, and then convert the analog voltage signal into a digital charge signal through a high-precision analog-to-digital converter chip. The interference suppression submodule is used to perform electromagnetic interference filtering and baseline drift correction on the digital charge signal, remove environmental electrostatic interference and inherent circuit noise, and obtain an effective charge signal that is directly related to the particle charge. The charge feature extraction submodule is used to extract features of effective charge signals, such as charge peak value, charge surface density, cumulative charge amount and signal duration, to obtain core feature parameters characterizing the charge state of particles. The charge calculation submodule is used to call the pre-stored mapping model between charge characteristic parameters and particle charge, substitute the extracted core characteristic parameters into the model for calculation, and obtain quantified particle charge data. The flow rate adaptation calculation submodule is used to pre-store the airflow velocity adjustment coefficient table corresponding to different charge ranges, receive the qualified charge data output by the charge calculation submodule, determine the range to which the charge belongs and match the corresponding flow rate adjustment coefficient, convert the flow rate adjustment coefficient into specific airflow velocity fine-tuning parameters, and feed them back to the main control module to achieve precise fine-tuning of the airflow velocity in the classifier.

[0014] Preferably, the large particle retention detection module includes a particle image acquisition unit, a retention weight sensing unit, a signal fusion processing unit, a retention amount calculation unit, and a feedback signal generation unit. The particle image acquisition unit is deployed at a preset observation position above the coarse screen in the first classification chamber. It uses a high-speed camera to acquire two-dimensional image data of large particles trapped on the surface of the coarse screen in real time and synchronously records the acquisition time information of each frame of the image. The interception weight sensing unit is integrated into the support structure of the coarse screen in the first grading chamber to sense the total weight change of the coarse screen and the large particles intercepted in real time and output a continuous weight sensing electrical signal. The signal fusion processing unit is used to receive the two-dimensional image data output by the particle image acquisition unit and retain the weight sensing electrical signal output by the weight sensing unit. It performs noise reduction and enhancement preprocessing on the image data, and filters and performs baseline calibration on the weight sensing electrical signal to obtain effective image data and effective weight signal. The interception amount calculation unit is used to call the pre-stored large particle image feature and single particle weight mapping relationship library, count particles and screen particle size on effective image data, and calculate the cumulative interception amount data of large particles on the coarse screen by combining the effective weight signal. The feedback signal generation unit is used to convert the cumulative interception data into a standardized large-particle interception feedback signal according to a preset signal encoding rule, establish a signal transmission link with the main control module, and send the feedback signal.

[0015] A sorting device for nickel powder used in silver-nickel paste is used to operate by a sorting method for nickel powder used in silver-nickel paste. The device includes a chamber, the bottom of which is connected to an alternating magnetic field dispersion chamber via a Venturi device. An alternating electromagnetic coil is installed in the alternating magnetic field dispersion chamber, and one side of the alternating electromagnetic coil is divided to form a corona discharge area. A corona discharge module is installed in the corona discharge area. The alternating magnetic field dispersion chamber is connected to the top of a classification chamber via a second fan. The bottom of the classification chamber is connected to a high-efficiency dust filter. The air inlet of the first fan is connected to the high-efficiency dust filter. The air outlet of the first fan is connected to the chamber and the Venturi device via a three-way valve.

[0016] Preferably, the top of the chamber is provided with a feeding port, the side wall of the chamber is provided with a high-purity nitrogen inlet and an exhaust port, and the data detection and extraction module is installed in the chamber.

[0017] Preferably, the grading chamber is divided into a first grading chamber and a second grading chamber arranged vertically by a screen. A high-voltage power supply module is installed on the outer wall of the grading chamber, and the high-voltage power supply module is electrically connected to the inner walls of the first grading chamber, the second grading chamber, and the screen.

[0018] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention achieves integrated, precise, and low-consumption operation of the entire nickel powder sorting process for silver-nickel paste through the synergistic adaptation of methods and devices. Utilizing multi-dimensional real-time detection and dynamic parameter control mechanisms, it effectively solves the problems of insufficient dispersion, uneven charging, and inadequate classification accuracy in traditional processes, significantly improving the particle size consistency and purity of the target nickel powder and reducing material adsorption losses. Through an inert gas closed-loop circulation design, it not only reduces resource and energy consumption but also maintains a stable and clean atmosphere throughout the process, preventing nickel powder oxidation or contamination. The overall process is seamlessly connected, with a reasonable device structure layout that balances sorting efficiency, operational stability, and ease of maintenance. It not only meets the stringent requirements of silver-nickel paste for raw materials but also significantly improves the practicality and economy of the process, providing a high-quality raw material guarantee for silver-nickel paste preparation. Attached Figure Description

[0019] Figure 1 This is a schematic diagram illustrating the sorting principle of the present invention.

[0020] In the diagram: 1. Chamber; 2. Alternating magnetic field dispersion chamber; 3. Alternating electromagnetic coil; 4. Corona discharge zone; 5. Classification chamber; 6. First classification chamber; 7. Second classification chamber; 8. Screen; 9. High-efficiency dust filter; 10. First fan; 11. Crude nickel powder to be sorted; 12. Feed port; 13. Second fan; 14. High-purity nitrogen inlet; 15. Venturi device; 16. Exhaust port. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," "outer," "front end," "rear end," "both ends," "one end," and "the other end," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0023] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installed," "equipped with," "connected," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0024] Example 1: This example provides a method for sorting nickel powder for silver-nickel paste, such as... Figure 1 As shown, it includes the following steps: Step 1: The data detection and extraction module collects real-time data of the crude nickel powder 11 to be sorted in chamber 1 and feeds it back to the main control module. After receiving various types of data, the main control module analyzes and controls the airflow velocity and voltage in the alternating electromagnetic coil 3, the corona discharge module, and the classification chamber 5. High-purity nitrogen is introduced through the high-purity nitrogen inlet 14 on the side wall of chamber 1, and the exhaust port 16 is opened to discharge the original gas in chamber 1, thus completing the atmosphere replacement in the chamber. After the data collected by the data detection and extraction module meets the preset requirements, the crude nickel powder in the chamber is sent into the alternating magnetic field dispersion chamber 2 through the Venturi device 15.

[0025] Step 2: The main control module generates the first acquisition trigger command to the alternating electromagnetic coil 3 based on the real-time data of the coarse nickel powder 11 to be sorted, and starts the alternating magnetic field deagglomeration. The particle dispersion data is collected by the deagglomeration effect detection module and fed back to the main control module. If the dispersion does not reach the preset threshold, the magnetic field parameters are adjusted until the standard is met. After the standard is met, the main control module sends a synchronous trigger signal to control the alternating electromagnetic coil 3 to start the charging process. Step 3: The main control module generates a second acquisition trigger command based on the real-time data of the coarse nickel powder 11 to be sorted and sends it to the corona discharge module to charge the deagglomerated particles to obtain charged particles. The charge effect detection module collects the particle charge data and feeds it back to the main control module. If the charge does not reach the preset threshold, the charge parameters are adjusted until the standard is met. After the standard is met, the main control module sends a grading start signal and fine-tunes the airflow speed according to the charge data, starts the second fan 13, and sends the charged particles from the alternating magnetic field dispersion cavity 2 into the grading chamber 5.

[0026] Step 4: After being charged, the particles are introduced into the classification chamber 5. The main control module dynamically adjusts the airflow speed according to the feedback signal of the large particle retention amount detected by the large particle retention amount detection module in the first classification chamber 6. At the same time, the main control module controls the high-voltage power supply module to apply a voltage with the same polarity as the charge carried by the charged particles to the inner wall of the first classification chamber 6 and the second classification chamber 7 and the surface of the screen 8, forming an electrostatic repulsion shielding layer. Step 5: Large particles are intercepted by the coarse sieve in the first classification chamber 6, and particles of the target particle size are intercepted by the fine sieve in the second classification chamber 7. Small particles smaller than the sieve aperture are carried away by the airflow. Particles within the target particle size range are intercepted and sealed in packaging to obtain the target nickel powder. Step 6: The inert gas drawn from the classification chamber 5 is purified by passing it through the high-efficiency dust filter 9 and then returned to the inlet of the first fan 10 to form a closed loop. The inert gas discharged from the first fan 10 is selectively passed into the chamber 1 through the three-way valve for atmosphere maintenance or into the venturi device 15 to assist in the conveying of coarse nickel powder.

[0027] In this embodiment, the coarse nickel powder 11 to be sorted refers to the raw nickel powder material that needs to be sorted and used to prepare silver-nickel paste.

[0028] In this embodiment, alternating magnetic field deagglomeration refers to the process of breaking the agglomeration of coarse nickel powder through alternating electromagnetic action, so that the agglomerated particles are dispersed into single particles or small agglomerates.

[0029] In this embodiment, charged particles refer to dispersed nickel powder particles that have undergone corona treatment and have a certain charge on their surface.

[0030] In this embodiment, the target particle size refers to nickel powder particles within a specific particle size range that meet the requirements for silver-nickel paste preparation and are retained through grading.

[0031] In this embodiment, the electrostatic repulsion shielding layer refers to an electrostatic protective layer formed by applying a voltage with the same polarity as the particle charge to the surface of the grading area, which prevents particles from adsorbing onto the wall surface and the screen surface.

[0032] In this embodiment, closed-loop circulation refers to a gas recycling method in which inert gas is purified and reused to maintain the atmosphere of the chamber or to transport materials.

[0033] In this embodiment, atmosphere replacement refers to the operation of introducing high-purity nitrogen to expel the original gas in the chamber, thereby creating a stable and clean gas environment inside the chamber.

[0034] The beneficial effects of the above technical solution are as follows: By pre-treating the environment in which the materials are located, a stable and clean operating atmosphere is established, and then continuous operation is achieved in the order of dispersion, charging, and grading. By real-time monitoring of the material status and dynamic adjustment of process parameters, coupled with electrostatic auxiliary protection and a closed-loop gas circulation design, material adsorption loss and environmental interference are effectively avoided, significantly improving the screening accuracy and recovery rate of the target materials. The overall process balances sorting efficiency and operational stability, reduces resource waste, lowers process energy consumption, and can precisely adapt to the stringent requirements of raw material particle size and purity in silver-nickel paste preparation, providing a reliable guarantee for the quality of subsequent silver-nickel paste preparation, thus combining practicality and economy.

[0035] Example 2: Based on Example 1, this example provides a method for sorting nickel powder for silver-nickel paste. The data detection and extraction module includes a magnetization intensity detection module, an initial agglomeration detection module, an oxygen content detection module, and a data extraction trigger unit. The magnetization intensity detection module is used to collect the magnetization intensity data of the coarse nickel powder 11 to be sorted in chamber 1; The initial agglomeration detection module is used to collect the initial agglomerate particle size distribution data of the coarse nickel powder 11 to be sorted in chamber 1; The oxygen content detection module is used to collect oxygen content data in chamber 1; In this embodiment, the magnetization intensity data refers to the quantitative data that reflects the magnetic characteristics of the coarse nickel powder to be sorted in chamber 1, and is used to characterize the magnetic properties of the coarse nickel powder.

[0036] In this embodiment, the initial agglomerate particle size distribution data refers to the detection data of the particle size and distribution range of the agglomerated particles of the crude nickel powder 11 to be sorted before it has undergone dispersion treatment.

[0037] In this embodiment, the oxygen content data refers to the detection data of the oxygen content in the air after the atmosphere in the chamber is replaced and during the operation, which is used to determine whether the environment of chamber 1 meets the material handling requirements.

[0038] In this embodiment, the data extraction triggering unit refers to the functional unit used to read the raw data generated by each detection module, process and integrate the data, and then feed it back to the main control module.

[0039] The beneficial effects of the above technical solution are as follows: This embodiment, by supplementing the multi-dimensional basic data collection process, comprehensively acquires key information on the material's own characteristics and its environment, providing reliable data support for the precise control of subsequent process parameters and effectively avoiding process adjustment deviations caused by incomplete data collection. By accurately capturing the initial state of the material and environmental indicators, the material's suitability for processing can be predicted in advance, providing targeted control basis for subsequent steps such as dispersion and charging, further improving the controllability and stability of the sorting process, ensuring the consistency of the target material screening quality, and strengthening the scientific rigor of the overall sorting scheme.

[0040] Example 3: Based on Example 2, this example provides a method for sorting nickel powder for silver-nickel paste. The data extraction triggering unit includes: The data extraction unit is used to read the generated magnetization intensity data, initial agglomerate particle size distribution data, and oxygen content data from the corresponding detection module; The signal processing unit is used to receive the first data stream composed of the generated magnetization intensity data, initial aggregate particle size distribution data, and oxygen content data, and to perform time synchronization calibration on the first data stream to form a summary data stream in a unified format. The signal transmission unit is used to send data transmission requests to the main control module and send the aggregated data stream to the main control module.

[0041] In this embodiment, the first data stream refers to the original data set composed of magnetization intensity data, initial aggregate particle size distribution data, and oxygen content data generated by the magnetization intensity detection module, the initial agglomeration detection module, and the oxygen content detection module, respectively.

[0042] In this embodiment, timing synchronization calibration refers to the process of comparing and compensating the acquisition timestamps of each branch of data in the first data stream to keep the timelines of data from different sources synchronized and to eliminate acquisition timing deviations.

[0043] In this embodiment, the unified format summary data stream refers to a comprehensive data set that is structurally standardized and can be directly recognized by the main control module after being integrated and verified according to a preset data format template after time synchronization calibration.

[0044] In this embodiment, the data transmission request refers to a signal sent to the main control module to request the establishment of a data transmission link and to inform the main control module that it is ready to receive the aggregated data stream.

[0045] The beneficial effects of the above technical solution are as follows: This embodiment refines the extraction, processing, and transmission process of multi-source detection data, achieving standardized integration and precise calibration of different types of raw data, effectively eliminating interference caused by data acquisition timing deviations and inconsistent formats. By first reading the raw data, then performing synchronous calibration and format unification, and finally transmitting it to the control core in a standardized manner, the integrity, consistency, and accuracy of the transmitted data are ensured. This allows the control core to quickly and accurately acquire effective data and make control decisions, further strengthening the data's support for subsequent processes, improving the automation level and control accuracy of the overall sorting process, and ensuring the smoothness and stability of the sorting process.

[0046] Example 4: Based on Example 3, this example provides a method for sorting nickel powder for silver-nickel paste, wherein the signal processing unit includes: The data parsing module is used to parse each branch data stream in the first data stream frame by frame and extract the collection timestamp information corresponding to each data point in each branch data stream; The data comparison module is used to compare the acquisition timestamp information of each branch data stream with the preset timing calibration reference clock signal and calculate the time deviation value of each branch data stream relative to the reference clock signal. The data calculation module performs timing compensation adjustment on the time misaligned data points in each branch data stream based on the calculated time deviation value, so that the time axes of the three branch data streams are kept synchronized and aligned. The data processing module is used to perform data integrity checks on the three branch data streams after timing adjustment. After confirming that there are no data missing, duplicate or misaligned issues, it calls the pre-stored unified data format template and fills the synchronized magnetization intensity data, initial agglomerate particle size distribution data and oxygen content data into the corresponding fields according to the field definitions of the unified data format template to generate integrated data. The data validation module is used to validate the format of the integrated data after the fields are filled. Once the data format is confirmed to meet the preset specifications, a unified format summary data stream is generated.

[0047] In this embodiment, the branch data stream refers to the single type of raw data stream in the first data stream, which comes from the magnetization intensity detection module, the initial aggregation degree detection module, and the oxygen content detection module respectively, with each path corresponding to a type of detection data.

[0048] In this embodiment, the timestamp information refers to the specific collection time information corresponding to each data point extracted when parsing the branch data stream, which is used to characterize the time node of data generation.

[0049] In this embodiment, the timing calibration reference clock signal refers to a preset unified time standard signal, which is used as a reference for comparing the acquisition timestamps of each branch data stream to eliminate time dimension deviation.

[0050] In this embodiment, the time deviation value refers to the time difference between each data stream and the reference time, calculated by comparing the acquisition timestamp of each branch data stream with the timing calibration reference clock signal.

[0051] In this embodiment, timing compensation adjustment refers to the process of correcting the time-misaligned data points in each branch data stream according to the calculated time deviation value, so as to keep the time axis of the three branch data streams synchronized.

[0052] In this embodiment, data integrity detection refers to the process of checking the three branch data streams after timing adjustment to confirm that there are no abnormalities such as missing, duplicate, or misaligned data.

[0053] In this embodiment, the unified data format template refers to a pre-stored fixed data structure template, which includes field definitions for corresponding magnetization intensity data, initial aggregate particle size distribution data, and oxygen content data, and is used to standardize the data integration format.

[0054] In this embodiment, integrated data refers to the structured data set formed by filling the three types of detection data after time synchronization into the corresponding positions according to the field definitions of a unified data format template.

[0055] In this embodiment, format compliance verification refers to the process of checking the completed integrated data to confirm that its structure, field content, etc., comply with preset specifications and ensure that it can be recognized by the main control module.

[0056] The beneficial effects of the above technical solution are as follows: This embodiment achieves refined processing of the entire data process by performing frame-by-frame analysis, time-series comparison, and precise compensation on multi-source detection data, followed by integrity detection and format compliance verification. This effectively eliminates problems such as time-series misalignment, missing data, and duplication of data from different sources, ensuring that the final generated summary data stream possesses time-series consistency, data integrity, and format standardization. This provides high-precision and high-reliability data support for the control core, facilitating more precise subsequent process parameter control and further guaranteeing the stability of the sorting process and the consistency of sorting quality.

[0057] Example 5: Based on Example 1, this example provides a sorting method for nickel powder for silver-nickel paste. The deagglomeration effect detection module (deagglomeration effect detection module is deployed at the outlet end of alternating magnetic field dispersion cavity 2) is used to respond to the first acquisition trigger command, perform real-time dispersion detection on particles in the flow path, and generate corresponding particle dispersion data. The depolymerization effect detection module includes: a laser emission unit, a reference calibration unit, a signal receiving unit, a signal processing submodule, a feature extraction submodule, and a feature calculation submodule; The laser emitting unit is used to continuously emit laser light according to a set emission power to form a detection light field covering the particle flow path; The reference calibration unit is used to control the laser emitting unit to emit detection lasers to a preset standard monodisperse particle calibration sample, and to receive and record the reference value of the scattered light signal of the calibration sample. The signal receiving unit is used to convert the captured scattered light signal into an electrical signal and transmit it to the signal processing submodule through the signal transmission line; The signal processing submodule is used to filter the received electrical signal to remove ambient light interference and noise signals caused by circuit noise to form an effective electrical signal. The feature extraction submodule is used to extract amplitude, phase and frequency features from the filtered effective electrical signal to obtain scattering signal feature parameters related to the particle dispersion state. The feature calculation submodule is used to call the pre-stored correspondence model between scattering signal feature parameters and particle dispersion, input the extracted scattering signal feature parameters, and calculate the particle dispersion data.

[0058] Among them, the extracted scattering signal feature parameters include the variance of the scattered light intensity distribution. Average scattering angle scattering signal pulse width The three parameters are the core input parameters for calculating particle dispersion; The model for the correspondence between pre-stored scattering signal characteristic parameters and particle dispersion adopts a linear weighted calculation model, and its formula is: ; in, For particle dispersity data, , , These are the preset weighting coefficients corresponding to the variance of the scattered light intensity distribution, the average scattering angle, and the pulse width of the scattered signal, respectively. This is the preset correction factor; The feature calculation submodule reads the pre-stored weight coefficients from the storage unit. , , and correction factor The coefficients are obtained by calibrating the scattering signals of multiple sets of standard dispersion samples, and the normalized variance of the scattered light intensity distribution is used. Average scattering angle scattering signal pulse width Substitute these values ​​sequentially into the linear weighted calculation model to obtain the particle dispersion data.

[0059] In this embodiment, particle dispersion data refers to quantitative data used to characterize the particle dispersion state, which is calculated by detecting the characteristic parameters of particle scattering signals and substituting them into a preset correspondence model.

[0060] In this embodiment, the detection light field refers to the detection area formed by continuous laser light covering the particle flow path, used to capture particle scattering signals.

[0061] In this embodiment, the standard monodisperse particle calibration sample refers to a preset standard sample with uniform particle dispersion, which is used to calibrate the detection system and obtain a reference value for the scattered light signal.

[0062] In this embodiment, the reference value of the scattered light signal refers to the reference value of the scattered light signal received and recorded by the detection system after the standard monodisperse particle calibration sample is irradiated by laser.

[0063] In this embodiment, the effective electrical signal refers to the electrical signal that is directly related to the particle scattering signal after the original electrical signal has been filtered to remove ambient light interference and circuit noise.

[0064] In this embodiment, the scattering signal characteristic parameters refer to the core parameters related to the particle dispersion state obtained after extracting the amplitude, phase and frequency features of the effective electrical signal.

[0065] In this embodiment, the correspondence model between the scattering signal characteristic parameters and the particle dispersion refers to a pre-stored computational model used to establish the mapping relationship between the scattering signal characteristic parameters and the particle dispersion values.

[0066] The beneficial effects of the above technical solution are as follows: This embodiment achieves real-time, high-precision detection of particle dispersion by establishing a standardized detection and calibration process, coupled with precise signal filtering, purification, and feature extraction methods. Compared with traditional detection methods, it effectively solves problems such as the lack of unified calibration standards, susceptibility to environmental interference, large deviations in detection data, and feedback lag. This method can quickly capture the core characteristics of particle dispersion, accurately determine whether the dispersion effect meets the standards, and provide reliable data support for timely and targeted adjustments to subsequent process parameters. It effectively avoids problems such as reduced efficiency and fluctuations in sorting quality in subsequent processes due to insufficient dispersion, further improving the dynamic controllability of the sorting process and the screening accuracy of target materials, ensuring the stability, consistency, and efficiency of the overall sorting process, and providing strong technical support for high-quality nickel powder sorting.

[0067] Example 6: Based on Example 1, this example provides a sorting method for nickel powder for silver-nickel paste. The charging effect detection module (deployed at the outlet end of the corona discharge module 4) is used to respond to the second acquisition trigger command to perform real-time charge detection on the charged particles in the flow path and generate corresponding particle charge data. The charge effect detection module includes: an electrostatic detection array unit, a charge reference calibration unit, a charge signal quantization unit, an interference suppression submodule, a charge feature extraction submodule, a charge calculation submodule, and a flow velocity adaptation calculation submodule. The electrostatic detection array unit is used to be deployed along the particle flow path at the outlet of the corona discharge module to form an enclosed charge detection area, and to capture the electrostatic induction signal generated by charged particles in real time through the array of electrodes. The charge reference calibration unit is used to call the pre-stored standard charged particle sample parameters, control the electrostatic detection array unit to perform induction detection on the standard sample with known charge, record the electrostatic induction signal reference value corresponding to the standard sample, and establish the calibration relationship between the detection signal and the charge. The charge signal quantization unit is used to convert the electrostatic induction signal captured by the electrostatic detection array unit into a continuously changing analog voltage signal, and then convert the analog voltage signal into a digital charge signal through a high-precision analog-to-digital converter chip. The interference suppression submodule is used to perform electromagnetic interference filtering and baseline drift correction on the digital charge signal, remove environmental electrostatic interference and inherent circuit noise, and obtain an effective charge signal that is directly related to the particle charge. The charge feature extraction submodule is used to extract features of effective charge signals, such as charge peak value, charge surface density, cumulative charge amount and signal duration, to obtain core feature parameters characterizing the charge state of particles. The charge calculation submodule is used to call the pre-stored mapping model between charge characteristic parameters and particle charge, substitute the extracted core characteristic parameters into the model for calculation, and obtain quantified particle charge data. Among them, the core feature parameters extracted by the charge calculation submodule include: peak charge. Surface charge density Accumulated charge Signal duration The four parameters are the core input parameters for quantifying particle charge. The mapping model formula between charge characteristic parameters and particle charge is as follows: ; in, This is the final output of quantized particle charge data; The normalized charge peak value is denoted as , and the core feature parameters are denoted as after parameter preprocessing. The numerical range matches the input requirements of the mapping model. , where is the normalized surface charge density, and is the core feature parameter after parameter preprocessing, with a numerical range matching the input requirements of the mapping model; The normalized cumulative charge is denoted as , and the core feature parameters are denoted as after parameter preprocessing. The numerical range matches the input requirements of the mapping model. The normalized signal duration is denoted as , and the core feature parameters are denoted as after parameter preprocessing. The numerical range matches the input requirements of the mapping model. , , , The preset weighting coefficients corresponding to the charge peak, charge surface density, cumulative charge, and signal duration are read from the storage unit and obtained through charge signal calibration of multiple sets of standard charge samples. The preset offset correction coefficient is the inherent structural parameter of the mapping model, which is read from the storage unit and used to compensate for the inherent bias of the detection system. The pre-stored model system error correction coefficients are read from the storage unit and used to compensate for errors in the original calculation results; This is a quantization function for pre-stored charge values, used to convert corrected intermediate values ​​into quantization results that meet preset accuracy requirements; The flow rate adaptation calculation submodule is used to pre-store the airflow flow rate adjustment coefficient table corresponding to different charge ranges, receive the qualified charge data output by the charge calculation submodule, determine the range to which the charge belongs and match the corresponding flow rate adjustment coefficient, convert the flow rate adjustment coefficient into specific airflow flow rate fine-tuning parameters, and feed them back to the main control module to achieve precise fine-tuning of the airflow flow rate in the staged chamber 5.

[0068] The velocity adaptation calculation submodule pre-stores a table of correspondences between multiple sets of experimentally calibrated charge ranges and airflow velocity adjustment coefficients. This table contains continuously divided charge ranges. , … and the unique flow velocity adjustment coefficient for each interval , , … Where n is a positive integer, and the adjustment coefficient f is preset to a range of 0.8-1.2; the flow velocity adaptation calculation submodule receives the compliant particle charge data output by the charge calculation submodule. Start the interval matching algorithm, and The boundary values ​​of each charge range in the corresponding relationship table are compared sequentially to determine the value. The target charge range (of which, 1) According to the target charge range Extract the target flow rate adjustment coefficient bound to this interval from the correspondence table. The flow rate adaptation calculation submodule reads the pre-stored reference airflow velocity of the graded system. The reference flow rate is the initial operating flow rate preset by the grading system; according to the preset calculation formula... Calculations are performed to obtain the target airflow velocity of the graded system. ; Invoke the pre-stored flow rate parameter conversion protocol to convert the target airflow velocity The airflow velocity is converted into a digital control signal that can be recognized by the graded system drive unit. This digital control signal is the specific airflow velocity fine-tuning parameter. The airflow velocity fine-tuning parameter is fed back to the main control module through the signal transmission channel, so that the main control module can send a velocity adjustment command to the airflow drive unit of the graded system to achieve precise fine-tuning of the airflow velocity of the graded system.

[0069] In this embodiment, the electrostatic induction signal refers to the induction signal generated by the charge carried by the particles, which is captured in real time by an array of electrodes when charged particles flow through the detection area.

[0070] In this embodiment, the enclosed charge detection area refers to the detection space formed by arranging electrodes along the particle flow path at the outlet end of the corona discharge module, which can capture the electrostatic induction signal of the particles from all directions.

[0071] In this embodiment, the standard charged particle sample refers to a standard particle sample with pre-stored parameters and known charge values, which is used to calibrate the correspondence between the detection signal and the charge.

[0072] In this embodiment, the reference value of the electrostatic induction signal refers to the reference signal value recorded by the detection system after sensing the standard charged particle sample, which serves as the calibration basis for calculating the charge.

[0073] In this embodiment, the analog voltage signal refers to the continuously changing voltage signal that characterizes the charge intensity obtained after converting the captured electrostatic induction signal.

[0074] In this embodiment, the digital charge signal refers to the digital signal that is converted from the analog voltage signal by a high-precision analog-to-digital converter chip, making it easier for subsequent processing.

[0075] In this embodiment, the effective charge signal refers to the signal that is directly related to the particle charge after filtering, baseline correction, and removing environmental interference and circuit noise from the digitized charge signal.

[0076] In this embodiment, the core feature parameters refer to the charge peak value, charge surface density, cumulative charge amount and signal duration extracted from the effective charge signal, which are used to characterize the charge state of the particles.

[0077] In this embodiment, the mapping model between charge characteristic parameters and particle charge refers to a pre-stored computational model that can be used to calculate quantified charge data from core characteristic parameters.

[0078] In this embodiment, the airflow velocity adjustment coefficient table refers to a pre-stored table of correspondences between different charge ranges and corresponding velocity adjustment coefficients, used to match velocity parameters.

[0079] In this embodiment, the airflow velocity fine-tuning parameter refers to the specific parameter that, after converting the velocity adjustment coefficient, can control the airflow velocity in the staged chamber 5 and can be recognized by the main control module.

[0080] The beneficial effects of the above technical solution are as follows: This embodiment achieves real-time high-precision detection of the charge of charged particles by constructing an encircling detection and standardized benchmark calibration system, coupled with precise signal quantization, interference suppression, and feature extraction technologies, effectively avoiding detection deviations caused by environmental static electricity and electromagnetic interference. Simultaneously, through a dynamic adaptation mechanism between charge and airflow velocity, the detection results are directly converted into targeted flow rate fine-tuning parameters, ensuring precise matching between the grading flow rate and the particle charge state, solving the problems of no precise basis for flow rate adjustment and easy fluctuations in grading effects in traditional processes. The overall process achieves closed-loop linkage between charge detection and grading control, improving charge consistency and grading accuracy, ensuring the screening quality of target materials, enhancing the automation and intelligence level of the sorting process, and adapting to the stringent processing requirements of silver-nickel paste raw materials.

[0081] Example 7: Based on Example 1, this example provides a method for sorting nickel powder for silver-nickel paste. The large particle retention detection module includes a particle image acquisition unit, a retention weight sensing unit, a signal fusion processing unit, a retention amount calculation unit, and a feedback signal generation unit. The particle image acquisition unit is deployed at a preset observation position above the coarse sieve in the first classification chamber 6. It acquires two-dimensional image data of large particles trapped on the surface of the coarse sieve in real time through a high-speed camera, and records the acquisition time information of each frame of the image simultaneously. The interception weight sensing unit is integrated into the support structure of the first grading chamber 6 coarse screen to sense the total weight change of the coarse screen and the large particles intercepted in real time and output a continuous weight sensing electrical signal. The signal fusion processing unit is used to receive the two-dimensional image data output by the particle image acquisition unit and retain the weight sensing electrical signal output by the weight sensing unit. It performs noise reduction and enhancement preprocessing on the image data, and filters and performs baseline calibration on the weight sensing electrical signal to obtain effective image data and effective weight signal. The interception amount calculation unit is used to call the pre-stored large particle image feature and single particle weight mapping relationship library, count particles and screen particle size on effective image data, and calculate the cumulative interception amount data of large particles on the coarse screen by combining the effective weight signal. The interception calculation unit locates and reads a pre-stored mapping database of large particle image features and single particle weights using a preset storage index address. This database contains calibration data for different particle size ranges, contour area ranges, and corresponding single particle weights. It then calls an image segmentation algorithm to perform pixel-level segmentation on each valid image frame in the valid image data, distinguishing between the coarse sieve background area and the large particle target area, and extracting the contour boundary information of each target area. Based on the extracted contour boundary information, it calculates the actual particle size value corresponding to each target area using an image size calibration coefficient. Simultaneously, it filters out target particles with a particle size greater than the coarse sieve aperture size, and removes impurity particles and background interference areas with a particle size less than or equal to the sieve aperture size. Finally, it counts the filtered target particles frame by frame, accumulating the total count of large particles corresponding to the valid image data. ; Calculate the average calculated weight of a single target particle. Combined with the total count of large particles The theoretical total weight of large particles was obtained. Read the real-time total weight value corresponding to the valid weight signal. Simultaneously, the pre-stored coarse sieve reference weight is invoked. The measured total weight of the retained particles was calculated. = - ; Invoke the preset weight calibration algorithm to adjust the theoretical total weight Compared with the measured total weight Perform a comparison and calculate the calibration coefficient S= (when When S=0, S=1); the theoretical total weight is corrected using a calibration coefficient to obtain the cumulative large particle retention data. ; The cumulative amount of data retained By associating and integrating the image acquisition timestamp information with the corresponding time period, a complete cumulative interception dataset containing both weight values ​​and time dimensions is formed.

[0082] The feedback signal generation unit is used to convert the cumulative interception data into a standardized large-particle interception feedback signal according to a preset signal encoding rule, establish a signal transmission link with the main control module, and send the feedback signal. The feedback signal generation unit receives a large-particle cumulative retention dataset output by the retention calculation unit. This dataset includes the cumulative retention weight value and the corresponding acquisition timestamp information. The feedback signal generation unit reads pre-stored signal encoding rules through a preset storage address. These rules include data quantization precision, byte arrangement format, timestamp embedding position, and signal frame structure definition. According to the preset quantization precision in the encoding rules, the cumulative retention weight value is converted into a fixed-bit digital value, and the acquisition timestamp information is converted into a time encoding field conforming to the encoding rules. Based on the signal frame structure defined by the encoding rules, the quantized weight digital value and time encoding field are filled into the corresponding data segments of the frame structure, and a frame header identifier, frame tail identifier, and data length field are added to form the original signal frame. A preset Cyclic Redundancy Check (CRC) algorithm is called to perform checksum calculations on the data segments in the original signal frame, generating a checksum field. The checksum field is embedded with a preset check bit in the original signal frame to form a complete standardized large-granularity cutoff feedback signal. The feedback signal generation unit initiates the link establishment procedure with the main control module and sends a link connection request signal to the main control module. After receiving the link response signal returned by the main control module and confirming that the signal transmission link has been successfully established, the unit configures the transmission baud rate, data bits, stop bits, and other link transmission parameters to ensure that the parameters are consistent with the receiving parameters of the main control module. The standardized large-granularity cutoff feedback signal is sent to the main control module in real time according to a preset transmission cycle through a dedicated signal transmission channel. The unit receives the signal reception confirmation signal returned by the main control module. If no confirmation signal is received within a preset timeout period, the feedback signal is retransmitted until a confirmation signal is received or the preset retransmission limit is reached. The feedback signal, transmission time, link status, and reception confirmation result of each transmission are recorded to form a signal transmission log, which is stored in the local cache unit.

[0083] In this embodiment, the two-dimensional image data refers to the image data collected by a high-speed camera above the coarse screen in the first grading chamber 6, which reflects the shape and distribution of large particles intercepted on the surface of the coarse screen, and the acquisition time of each frame of the image is recorded synchronously.

[0084] In this embodiment, the weight sensing electrical signal refers to the continuous electrical signal output by the sensing unit integrated in the coarse screen support structure of the first grading chamber 6 after capturing the change in the total weight of the coarse screen and the intercepted large particles in real time.

[0085] In this embodiment, effective image data refers to image data with clear outlines and identifiable particle features after noise reduction and enhancement preprocessing of the original two-dimensional image data.

[0086] In this embodiment, the effective weight signal refers to the signal that is directly related to the weight of the large particles after filtering, baseline calibration, and removing interference from the original weight-sensing electrical signal.

[0087] In this embodiment, the large particle image feature and single particle weight mapping relationship library refers to a pre-stored database containing large particles of different sizes and contour areas and corresponding single particle weight calibration data.

[0088] In this embodiment, the cumulative retention data refers to the total retained weight data of large particles on the coarse sieve of the first grading chamber 6, calculated by combining the particle count, particle size screening results and effective weight signal of the effective image data.

[0089] In this embodiment, the preset signal encoding rules refer to pre-stored rules that include data quantization precision, frame structure, verification method, etc., used to convert the accumulated intercepted data into a standardized signal.

[0090] In this embodiment, the standardized large particle rejection feedback signal refers to the rejection data signal that is structurally standardized and can be recognized by the main control module after being processed according to preset coding rules.

[0091] The beneficial effects of the above technical solution are as follows: This embodiment adopts a dual-dimensional detection fusion approach combining image acquisition and weight sensing, along with signal preprocessing and data calibration techniques, to achieve real-time and accurate calculation of the amount of large particles retained by the coarse sieve. This effectively compensates for the shortcomings of single detection methods, such as susceptibility to interference and large data deviations. Particle counting and particle size screening are achieved through image feature analysis, and weight signal calibration improves the reliability of the cumulative retention data. Standardized encoding then generates feedback signals to ensure efficient and accurate data transmission to the control core, providing timely basis for dynamic adjustment of airflow velocity. This avoids flow rate control deviations caused by misjudgment of retention volume, ensures stable operation of the grading process, improves the purity of the target material, enhances the overall process controllability and consistency, and adapts to the fine sorting requirements of silver-nickel paste raw materials.

[0092] Example 8: This example provides a sorting device for nickel powder used in silver-nickel paste, such as... Figure 1 As shown, the system includes a chamber 1. The bottom of the chamber 1 is connected to an alternating magnetic field dispersion chamber 2 via a Venturi device 15. An alternating electromagnetic coil 3 is installed inside the alternating magnetic field dispersion chamber 2, and one side of the alternating electromagnetic coil 3 is divided to form a corona discharge area 4. A corona discharge module is installed inside the corona discharge area 4. The alternating magnetic field dispersion chamber 2 is connected to the top of a classification chamber 5 via a second fan 13. The bottom of the classification chamber 5 is connected to a high-efficiency dust filter 9. The air inlet of the first fan 10 is connected to the high-efficiency dust filter 9. The air outlet of the first fan 10 is connected to the chamber 1 and the Venturi device 15 via a three-way valve.

[0093] Preferably, the top of the chamber 1 is provided with a feeding port 12, the side wall of the chamber 1 is provided with a high-purity nitrogen inlet 14 and an exhaust port 16, and the data detection and extraction module is installed in the chamber 1.

[0094] Preferably, the grading chamber 5 is divided into a first grading chamber 6 and a second grading chamber 7 arranged vertically by a screen 8. A high-voltage power supply module is installed on the outer wall of the grading chamber 5, and the high-voltage power supply module is electrically connected to the inner walls of the first grading chamber 6 and the second grading chamber 7 as well as the screen 8.

[0095] Preferably, the Venturi device 15 is a prior art.

[0096] The working principle and beneficial effects of the above scheme are as follows: The overall structure of the nickel powder sorting device for silver-nickel paste is compact and highly interconnected. During operation, the coarse nickel powder to be sorted is first fed into the chamber 1 through the feeding port 12 at the top of the chamber 1. High-purity nitrogen is introduced through the high-purity nitrogen inlet 14 on the side wall of the chamber 1 and the original gas is discharged through the exhaust port 16 to complete the atmosphere replacement. The data detection and extraction module in the chamber 1 simultaneously collects material and environmental data. Subsequently, the Venturi device 15 at the bottom of the chamber 1 sends the material into the alternating magnetic field dispersion chamber 2 connected to it. The alternating electromagnetic coil 3 in the alternating magnetic field dispersion chamber 2 generates an alternating magnetic field to deagglomerate the material. The deagglomerated particles enter the corona discharge zone 4 on one side of the alternating electromagnetic coil 3 and pass through the corona discharge zone. The discharge module completes the charging process; then the second fan 13 sends the charged particles into the classification chamber 5 connected to it. The classification chamber 5 is divided into a first classification chamber 6 and a second classification chamber 7 set up vertically by a screen 8. The high-voltage power supply module on the outer wall applies voltage to the inner walls of the first classification chamber 6 and the second classification chamber 7 and the screen 8 to form an electrostatic repulsion shielding layer, thereby realizing particle classification and screening. Large particles that exceed the target particle size are intercepted by the first classification chamber 6, and particles of the target particle size are retained in the second classification chamber 7. Small particles are carried by the airflow into the high-efficiency dust filter 9 connected to the bottom of the classification chamber 5 for purification. The purified gas is drawn by the first fan 10 and selectively sent back to the chamber 1 through a three-way valve to maintain the atmosphere or sent to the venturi device 15 to assist in material conveying, forming a closed loop. This device achieves integrated operation of the entire material sorting process through precise adaptation and linkage of its components. The Venturi device 15 ensures efficient material transport, while the integrated design of the alternating magnetic field dispersion chamber 2 and the corona discharge zone 4 shortens the material transport path. The dual-chamber structure of the classification chamber 5, combined with the electrostatic auxiliary function of the high-voltage power supply module, effectively reduces particle adsorption loss. The closed-loop circulation design consisting of the first fan 10 and the three-way valve not only reduces inert gas consumption and energy consumption but also maintains the stability of the atmosphere within the system. The entire device can precisely match the various process requirements of the corresponding sorting method, ensuring smooth connection of each link such as dispersion, charging, and classification, significantly improving sorting efficiency and the purity and recovery rate of the target nickel powder. At the same time, the reasonable structural layout facilitates installation, commissioning, and daily maintenance, combining practicality and economy, and can stably adapt to the stringent requirements of raw material sorting in silver-nickel paste preparation.

[0097] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for sorting nickel powder for silver-nickel paste, characterized in that, Includes the following steps: Step 1: The real-time data of the crude nickel powder (11) to be sorted in the chamber (1) is collected by the data detection and extraction module and fed back to the main control module. After receiving various data, the main control module analyzes and controls the airflow velocity and voltage in the alternating electromagnetic coil (3), corona discharge module and grading chamber (5). High-purity nitrogen is introduced through the high-purity nitrogen inlet (14) on the side wall of the chamber (1), and the exhaust port (16) is opened to discharge the original gas in the chamber (1) to complete the atmosphere replacement in the chamber. After the data collected by the data detection and extraction module meets the preset requirements, the crude nickel powder in the chamber is sent into the alternating magnetic field dispersion chamber (2) through the Venturi device (15). Step 2: The main control module generates the first acquisition trigger command to the alternating electromagnetic coil (3) based on the real-time data of the coarse nickel powder (11) to be sorted, and starts the alternating magnetic field deagglomeration. The particle dispersion data is collected by the deagglomeration effect detection module and fed back to the main control module. If the dispersion does not reach the preset threshold, the magnetic field parameters are adjusted until the standard is met. After the standard is met, the main control module sends a synchronous trigger signal to control the alternating electromagnetic coil (3) to start the charging process. Step 3: The main control module generates a second acquisition trigger command based on the real-time data of the coarse nickel powder (11) to be sorted and sends it to the corona discharge module. The deagglomerated particles are charged to obtain charged particles. The charge data of the particles is collected by the charge effect detection module and fed back to the main control module. If the charge does not reach the preset threshold, the charge parameters are adjusted until the standard is met. After the standard is met, the main control module sends a grading start signal and fine-tunes the airflow speed according to the charge data. The second fan (13) is started to send the charged particles from the alternating magnetic field dispersion cavity (2) into the grading chamber (5). Step 4: After being charged, the particles are introduced into the grading chamber (5). The main control module dynamically adjusts the airflow speed according to the feedback signal of the large particle retention amount detected by the large particle retention amount detection module in the first grading chamber (6). At the same time, the main control module controls the high-voltage power supply module to apply a voltage with the same polarity as the charge carried by the charged particles to the inner wall of the first grading chamber (6) and the second grading chamber (7) and the surface of the screen (8), forming an electrostatic repulsion shielding layer. Step 5: Large particles are intercepted by the coarse sieve in the first classification chamber (6), and particles of the target particle size are intercepted by the fine sieve in the second classification chamber (7). Small particles smaller than the sieve aperture are carried away by the airflow. Particles within the target particle size range are intercepted and sealed in packaging to obtain the target nickel powder. Step 6: After the inert gas drawn from the classification chamber (5) is purified by the high-efficiency dust filter (9), it is returned to the inlet of the first blower (10) to form a closed loop. The inert gas discharged from the first blower (10) is selectively introduced into the chamber (1) through the three-way valve for atmosphere maintenance or into the venturi device (15) to assist in the conveying of crude nickel powder.

2. The method for sorting nickel powder for silver-nickel paste according to claim 1, characterized in that: In step 1, the data detection and extraction module includes a magnetization intensity detection module, an initial aggregation degree detection module, an oxygen content detection module, and a data extraction trigger unit; The magnetization intensity detection module is used to collect the magnetization intensity data of the coarse nickel powder (11) to be sorted in the chamber (1); The initial agglomeration detection module is used to collect the initial agglomerate particle size distribution data of the crude nickel powder (11) to be sorted in the chamber (1); The oxygen content detection module is used to collect oxygen content data in chamber (1).

3. The method for sorting nickel powder for silver-nickel paste according to claim 2, characterized in that: The data extraction trigger unit includes: The data extraction unit is used to read the generated magnetization intensity data, initial agglomerate particle size distribution data, and oxygen content data from the corresponding detection module; The signal processing unit is used to receive the first data stream composed of the generated magnetization intensity data, initial aggregate particle size distribution data, and oxygen content data, and to perform time synchronization calibration on the first data stream to form a summary data stream in a unified format. The signal transmission unit is used to send data transmission requests to the main control module and send the aggregated data stream to the main control module.

4. The method for sorting nickel powder for silver-nickel paste according to claim 3, characterized in that: The signal processing unit includes: The data parsing module is used to parse each branch data stream in the first data stream frame by frame and extract the collection timestamp information corresponding to each data point in each branch data stream; The data comparison module is used to compare the acquisition timestamp information of each branch data stream with the preset timing calibration reference clock signal and calculate the time deviation value of each branch data stream relative to the reference clock signal. The data calculation module performs timing compensation adjustment on the time misaligned data points in each branch data stream based on the calculated time deviation value, so that the time axes of the three branch data streams are kept synchronized and aligned. The data processing module is used to perform data integrity checks on the three branch data streams after timing adjustment. After confirming that there are no data missing, duplicate or misaligned issues, it calls the pre-stored unified data format template and fills the synchronized magnetization intensity data, initial agglomerate particle size distribution data and oxygen content data into the corresponding fields according to the field definitions of the unified data format template to generate integrated data. The data validation module is used to validate the format of the integrated data after the fields are filled. Once the data format is confirmed to meet the preset specifications, a unified format summary data stream is generated.

5. The method for sorting nickel powder for silver-nickel paste according to claim 1, characterized in that: In step 2, the deagglomeration effect detection module is used to respond to the first acquisition trigger command, perform real-time dispersion detection on the particles in the flow path, and generate corresponding particle dispersion data. The depolymerization effect detection module includes: a laser emission unit, a reference calibration unit, a signal receiving unit, a signal processing submodule, a feature extraction submodule, and a feature calculation submodule; The laser emitting unit is used to continuously emit laser light according to a set emission power to form a detection light field covering the particle flow path; The reference calibration unit is used to control the laser emitting unit to emit detection lasers to a preset standard monodisperse particle calibration sample, and to receive and record the reference value of the scattered light signal of the calibration sample. The signal receiving unit is used to convert the captured scattered light signal into an electrical signal and transmit it to the signal processing submodule through the signal transmission line; The signal processing submodule is used to filter the received electrical signal to remove ambient light interference and noise signals caused by circuit noise to form an effective electrical signal. The feature extraction submodule is used to extract amplitude, phase and frequency features from the filtered effective electrical signal to obtain scattering signal feature parameters related to the particle dispersion state. The feature calculation submodule is used to call the pre-stored correspondence model between scattering signal feature parameters and particle dispersion, input the extracted scattering signal feature parameters, and calculate the particle dispersion data.

6. The method for sorting nickel powder for silver-nickel paste according to claim 1, characterized in that: The charge effect detection module is used to respond to the second acquisition trigger command, perform real-time charge detection on charged particles on the flow path, and generate corresponding particle charge data. The charge effect detection module includes: an electrostatic detection array unit, a charge reference calibration unit, a charge signal quantization unit, an interference suppression submodule, a charge feature extraction submodule, a charge calculation submodule, and a flow velocity adaptation calculation submodule. The electrostatic detection array unit is used to be deployed along the particle flow path at the outlet of the corona discharge module to form an enclosed charge detection area, and to capture the electrostatic induction signal generated by charged particles in real time through the array of electrodes. The charge reference calibration unit is used to call the pre-stored standard charged particle sample parameters, control the electrostatic detection array unit to perform induction detection on the standard sample with known charge, record the electrostatic induction signal reference value corresponding to the standard sample, and establish the calibration relationship between the detection signal and the charge. The charge signal quantization unit is used to convert the electrostatic induction signal captured by the electrostatic detection array unit into a continuously changing analog voltage signal, and then convert the analog voltage signal into a digital charge signal through a high-precision analog-to-digital converter chip. The interference suppression submodule is used to perform electromagnetic interference filtering and baseline drift correction on the digital charge signal, remove environmental electrostatic interference and inherent circuit noise, and obtain an effective charge signal that is directly related to the particle charge. The charge feature extraction submodule is used to extract features of effective charge signals, such as charge peak value, charge surface density, cumulative charge amount and signal duration, to obtain core feature parameters characterizing the charge state of particles. The charge calculation submodule is used to call the pre-stored mapping model between charge characteristic parameters and particle charge, substitute the extracted core characteristic parameters into the model for calculation, and obtain quantified particle charge data. The flow rate adaptation calculation submodule is used to pre-store the airflow flow rate adjustment coefficient table corresponding to different load ranges, receive the qualified load data output by the load calculation submodule, determine the range to which the load belongs and match the corresponding flow rate adjustment coefficient, convert the flow rate adjustment coefficient into specific airflow flow rate fine-tuning parameters, and feed them back to the main control module to realize the precise fine-tuning of the airflow flow rate in the graded chamber (5).

7. The method for sorting nickel powder for silver-nickel paste according to claim 1, characterized in that: The large particle retention detection module includes a particle image acquisition unit, a retention weight sensing unit, a signal fusion processing unit, a retention calculation unit, and a feedback signal generation unit. The particle image acquisition unit is used to be deployed at a preset observation position above the coarse screen in the first grading chamber (6). It acquires two-dimensional image data of large particles intercepted on the surface of the coarse screen in real time through a high-speed camera, and records the acquisition time information of each frame of the image simultaneously. The interception weight sensing unit is integrated into the support structure of the coarse screen in the first grading chamber (6) to sense the total weight change of the coarse screen and the intercepted large particles in real time and output a continuous weight sensing electrical signal. The signal fusion processing unit is used to receive the two-dimensional image data output by the particle image acquisition unit and retain the weight sensing electrical signal output by the weight sensing unit. It performs noise reduction and enhancement preprocessing on the image data, and filters and performs baseline calibration on the weight sensing electrical signal to obtain effective image data and effective weight signal. The interception amount calculation unit is used to call the pre-stored large particle image feature and single particle weight mapping relationship library, count particles and screen particle size on effective image data, and calculate the cumulative interception amount data of large particles on the coarse screen by combining the effective weight signal. The feedback signal generation unit is used to convert the cumulative interception data into a standardized large-particle interception feedback signal according to a preset signal encoding rule, establish a signal transmission link with the main control module, and send the feedback signal.

8. A sorting device for nickel powder used in silver-nickel paste, used for operation by a sorting method for nickel powder used in silver-nickel paste as described in claims 1-7, characterized in that, The chamber (1) is connected to the alternating magnetic field dispersion chamber (2) at the bottom via a venturi device (15). An alternating electromagnetic coil (3) is installed in the alternating magnetic field dispersion chamber (2), and a corona discharge area (4) is formed on one side of the alternating electromagnetic coil (3). A corona discharge module is installed in the corona discharge area (4). The alternating magnetic field dispersion chamber (2) is connected to the top of the classification chamber (5) via a second fan (13). The bottom of the classification chamber (5) is connected to a high-efficiency dust filter (9). The air inlet of the first fan (10) is connected to the high-efficiency dust filter (9). The air outlet of the first fan (10) is connected to the chamber (1) and the venturi device (15) via a three-way valve.

9. A sorting device for nickel powder in silver-nickel paste according to claim 8, characterized in that: The top of the chamber (1) is provided with a feeding port (12), and the side wall of the chamber (1) is provided with a high-purity nitrogen inlet (14) and an exhaust port (16). The data detection and extraction module is installed in the chamber (1).

10. A sorting device for nickel powder in silver-nickel paste according to claim 8, characterized in that: The grading chamber (5) is divided into a first grading chamber (6) and a second grading chamber (7) set up vertically by a screen (8). A high-voltage power supply module is installed on the outer wall of the grading chamber (5), and the high-voltage power supply module is electrically connected to the inner wall of the first grading chamber (6), the second grading chamber (7) and the screen (8).

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