Intelligent screening and debris recycling method and device for steel ball hard grinding machine

Abstract

The application discloses a steel ball hard mill intelligent screening and scrap recovery method and device, and relates to the technical field of industrial automation control and recovery monitoring.The steel ball hard mill intelligent screening and scrap recovery method and device comprises the following steps: S1, collecting scrap separation operation data in real time, and preprocessing the scrap separation operation data; S2, performing scrap separation cooperative evaluation on the scrap separation operation data; S3, performing wind regulation decision guidance on the scrap separation operation data entering the adjustment area; S4, storing and analyzing historical operation data and adjustment results; and S5, executing operation fluctuation early warning triggering in combination with the scrap separation operation data, the scrap separation cooperative evaluation results and the wind regulation decision guidance results. The problems of separation efficiency fluctuation and serious misclassification caused by unstable air pressure, material distribution change and other factors in the wind selection and magnetic attraction recovery process after scrap screening are solved.

Description

Technical Field

[0001] This invention relates to the field of industrial automation control and recycling monitoring technology, specifically to a method and apparatus for intelligent screening and debris recycling in a steel ball hard grinding mill. Background Technology

[0002] With the widespread use of steel ball grinding equipment in industries such as mining and metallurgy, its role in debris crushing and recycling has gradually increased. In recent years, air separation and magnetic adsorption structures have been introduced to improve separation efficiency, and the accompanying data acquisition and monitoring control systems have been gradually applied to the recording and display of operating parameters. Industrial monitoring software has played an auxiliary role in equipment status monitoring.

[0003] For example, invention patent CN101971115B discloses a condensate recovery system including multiple vent lines for releasing condensate from an associated steam unit. Each vent line includes a steam trap and flows into a common return line between the vent line and the condensate receiving tank. The system also includes an acoustic sensor arranged along the common return line, located upstream of the condensate receiving tank, for providing an acoustic output indicating the total steam loss passing through the multiple steam traps located upstream of the sensor.

[0004] For example, invention patent CN104102198B discloses a PX energy recovery device fault monitoring system and method. The system includes N PX energy recovery devices and a PX energy recovery device fault detection device. The PX energy recovery device fault detection device includes N sampling interfaces, N solenoid valves respectively connected to the N sampling interfaces, a controller, a flow sensor, and a conductivity meter. The PX energy recovery device fault detection device is used to sequentially detect the flow rate of N sample water outputs from the N PX energy recovery devices according to a set PX energy recovery device fault detection procedure, and to detect the conductivity of the Mth sample water with normal flow rate. Based on the obtained conductivity of the Mth sample water, combined with the pre-stored conductivity of the original seawater and the recovery rate of the membrane seawater desalination system, the operating status of the Mth PX energy recovery device outputting the Mth sample water is determined, and corresponding operations are performed based on the determined operating status of the Mth PX energy recovery device.

[0005] Existing debris screening and recycling methods mostly rely on fixed control strategies, lacking dynamic identification and response mechanisms for operational status. Current equipment has limited data acquisition and control functions, with sampling delays and adjustment lags being common, often leading to imbalances in wind-magnetic coordination and increased error rates. Stability and control capabilities remain insufficient under complex operating conditions.

[0006] To address the above issues, there is an urgent need for intelligent screening and debris recovery methods and devices for steel ball hard grinding mills. Summary of the Invention

[0007] Technical problems to be solved

[0008] To address the shortcomings of existing technologies, this invention provides an intelligent screening and debris recovery method and device for steel ball hard grinding mills, which solves the problems of fluctuating separation efficiency and serious mis-segmentation caused by unstable air pressure, changes in material distribution and other factors during the air separation and magnetic adsorption recovery process after debris screening.

[0009] Technical solution

[0010] To achieve the above objectives, the present invention provides the following technical solution: an intelligent screening and debris recovery method for a steel ball hard grinding mill, comprising the following steps: S1: Real-time acquisition of debris separation operation data and preprocessing of the debris separation operation data; S2: Collaborative evaluation of debris separation operation data, identifying the coordination state of air separation and magnetic attraction based on the collaborative evaluation results, and determining whether it is necessary to enter the adjustment zone; S3: Wind force adjustment decision guidance for debris separation operation data entering the adjustment zone, dynamically adjusting the wind speed output based on the wind force adjustment decision guidance results, recording the correspondence between adjustment behavior and separation effect, and optimizing the wind speed adjustment range and execution rhythm; S4: Storage and analysis of historical operation data and adjustment results, extraction of the correlation between parameters and efficiency, and adjustment of the basic setting range of wind speed and magnetic force; S5: Execution of operation fluctuation early warning triggering based on the comprehensive debris separation operation data, debris separation collaborative evaluation results, and wind force adjustment decision guidance results, determining whether to execute backflushing action, limit wind speed output, or issue an alarm signal based on the operation fluctuation early warning triggering results, and returning the trigger information and corresponding adjustment results for historical data updates and correlation analysis.

[0011] Further, the specific steps for real-time acquisition of debris separation operation data and preprocessing of the debris separation operation data are as follows: The debris separation operation data includes: the amount of debris recovered by air classification, the total input amount of debris, the wind speed in the air classification channel, the magnetic coil current, the amount of debris recovered by magnetic attraction, the current sampling time, the control cycle length, the current power of the fan, and the early warning trigger time. The amount of debris recovered by air classification is obtained synchronously through a weighing sensor installed at the air classification recovery port and an infrared particle counter. The total input amount of debris is obtained through a mass flow sensor deployed at the front end of the separation section. The wind speed in the air classification channel is obtained through a wind speed sensor installed in the middle of the air classification channel. The current of the magnetic coil is obtained through the current feedback interface integrated on the magnetic control power board. The magnetic attraction is obtained through an electronic weighing device installed at the end of the magnetic channel recovery bin. The system recovers debris; obtains the current sampling time via a built-in real-time clock; obtains the control cycle length via the operating parameter setting interface; obtains the current power of the wind turbine in real time via the power measurement interface on the turbine drive side; calculates and generates the early warning trigger time point using the algorithm in the parameter setting rules; records the calculated debris separation coordination value, wind power adjustment decision value, and operating fluctuation early warning value in real time; the preprocessing steps include: identifying and removing anomalies in the collected data, excluding abrupt changes and invalid data, and retaining anomaly records for subsequent analysis; standardizing the cleaned data according to a unified reference center and fluctuation range; performing normalization operations on key variables and compressing them to a fixed range; classifying and storing the processed data according to its purpose for use by various judgment and control logics; and recording the processing method and time information for each round.

[0012] Further, the specific steps for the collaborative evaluation of debris separation operation data are as follows: Obtain the amount of debris recovered by air classification, the total input amount of debris, the wind speed in the air classification channel, the current of the magnetic coil, the amount of debris recovered by magnetic attraction, and the mass of misclassified debris; obtain the mass of misclassified debris by comparing the differences between the debris component analysis at the recovery port and the classification measurement results; add one to the ratio of the amount of debris recovered by air classification to the total input amount of debris and take the natural logarithm to obtain the first part; then divide the square of the wind speed in the air classification channel by the value of the misclassified debris mass plus one, use this as the input of the hyperbolic tangent function, and multiply it with the logarithmic result of the first part to form a combination of the first two terms; next, divide the current of the magnetic coil by the value of the amount of debris recovered by magnetic attraction plus one, add one to the whole, and take the natural logarithm to obtain the third part; finally, add the product of the first two parts to the logarithmic result of the third part to obtain the collaborative value of debris separation.

[0013] Furthermore, the specific steps for identifying the coordination state of air separation and magnetic attraction based on the debris separation coordination evaluation results and determining whether it is necessary to enter the adjustment zone are as follows: The debris separation coordination value is compared with the set response thresholds θ1, θ2, and θ3. Based on the comparison results, different levels of control response priorities and operating status are triggered. When the debris separation coordination value is greater than or equal to θ1, it is rated as a stable coordination level; when the debris separation coordination value is greater than or equal to θ2 and less than θ1, it is rated as a weak coordination level; when the debris separation coordination value is greater than or equal to θ3 and less than θ2, it is rated as a degraded coordination level; when the debris separation coordination value is less than θ3, it is rated as a failed coordination level. When the device is in a stable cooperative state, it maintains the current fan frequency and magnetic current, enters a low-power monitoring mode, and maintains a sampling period of 30 seconds, recording only the separation efficiency trend for subsequent analysis. When the device is in a weak cooperative state, the sampling period is shortened to 15 seconds. If the air separation efficiency is judged to be low, the fan frequency is increased and the flow guiding structure is adjusted. If the magnetic attraction is judged to be weak, the magnetic current is increased and switched to continuous adsorption mode, while monitoring the error rate change to evaluate the adjustment effect. When the device is in a degraded cooperative state, the fan frequency is increased to near the rated upper limit, the magnetic module starts the high magnetic pulse adsorption function, and automatically activates adsorption enhancement every 15 seconds, while recording the adjustment log and evaluating the adjustment feedback. If there is no improvement for three consecutive cycles, the device is preset to enter the protection preparation process. When the device is in a failed cooperative state, the air duct backflushing operation and magnetic power-off reset are performed, triggering the alarm module and entering the protection standby state, which will be reactivated after manual confirmation.

[0014] Further, the specific steps for guiding wind power regulation decisions based on debris separation operation data entering the regulation zone are as follows: Obtain the current sampling time, current separation efficiency, amount of debris recovered by wind separation, total debris input, and control cycle length; obtain the target separation efficiency by extracting the optimal separation efficiency interval from historical operation data; calculate the current separation efficiency by comparing the total amount of debris recovered by the wind separation module and magnetic suction module within the current operation cycle with the total debris input entering the separation zone; and utilize the historical separation efficiency data cache built into the control logic. Extract the current separation efficiency from several consecutive operating cycles and calculate the historical average efficiency using an arithmetic mean. Subtract the current separation efficiency from the target separation efficiency to obtain the numerator. Use the exponential function with the natural logarithm base as the exponent, the negative of the sum of the current separation efficiency and the historical average efficiency, plus one as the denominator, and calculate the numerator divided by the denominator. Then, multiply pi by the current sampling time and divide by the control cycle length to obtain the input of the sine function, and add one to the result as the multiplication factor. Finally, multiply the fractional result from the previous part by the sine function factor to obtain the wind power regulation decision value.

[0015] Furthermore, the specific steps for dynamically adjusting the wind speed output based on the wind force adjustment decision guidance results, recording the correspondence between adjustment behavior and separation effect, and optimizing the wind speed adjustment amplitude and execution rhythm are as follows: The wind force adjustment decision value is used directly as a continuous variable to guide the dynamic adjustment of wind speed, and the response strategy is executed according to its positive or negative sign and amplitude; when the wind force adjustment decision value is positive, a gradual and enhanced wind speed increase is executed according to its amplitude, and the angle of the wind guide plate is adjusted in conjunction if necessary, and the adjustment effect is monitored in the target tracking state; when the wind force adjustment decision value is negative, the wind speed is reduced according to its absolute value, and the flow suppression adjustment state is entered when the interference intensifies, the flow guide structure adjustment is suspended, and the magnetic module is observed for protection; when the absolute value of the wind force adjustment decision value is close to zero, the holding state is entered to maintain the current wind speed output, and only the low-frequency monitoring mechanism is activated to determine whether the adjustment needs to be reactivated.

[0016] Furthermore, the specific steps for storing and analyzing historical operating data and adjustment results, extracting the correlation between parameters and efficiency, and adjusting the basic setting range of wind speed and magnetic force are as follows: record key operating parameters during debris separation and store them synchronously with corresponding adjustment commands; compare and analyze historical data over multiple operating cycles, extract the correlation between different parameter combinations and separation efficiency, and identify optimal operating conditions; actively correct the basic setting range of wind speed and magnetic force based on the analysis results to adapt to changes in debris particle size, content, and physical properties; when a significant deviation in the operating trend is detected, generate an adjustment tendency reference value to assist the wind speed adjustment unit in optimizing the control strategy.

[0017] Further, the specific steps for triggering the operational fluctuation early warning based on the integrated debris separation operation data, debris separation collaborative evaluation results, and wind power regulation decision guidance results are as follows: Obtain the current separation efficiency, current turbine power, early warning trigger time, and current sampling time; divide the difference in current separation efficiency between two consecutive sampling periods by the time interval to calculate the separation efficiency change rate; calculate the turbine power change rate by dividing the difference in current turbine power between two consecutive moments by the time interval; square the separation efficiency change rate to form the first term; multiply the turbine power change rate by the natural logarithm of the current turbine power plus one, and then square the product to form the second term; add the first term and the second term and take the square root to form the core fluctuation value; use the difference between the current sampling time and the early warning trigger time as input, substitute it into the Dirac function, and calculate the pulse offset value triggered at the critical moment; add the fluctuation intensity value to the pulse offset value to finally obtain the operational fluctuation early warning value.

[0018] Furthermore, the specific steps for determining whether to execute backflushing, limit wind speed output, and issue an alarm signal based on the operational fluctuation warning trigger result, and returning the trigger information and corresponding adjustment results for historical data updates and correlation analysis, are as follows: Real-time comparison of the operational fluctuation warning value with the set fluctuation threshold; when the operational fluctuation warning value is less than the fluctuation threshold, maintaining the current fan frequency and magnetic current, performing only periodic monitoring, and writing all sampled data into the historical record; when the operational fluctuation warning value is greater than or equal to the fluctuation threshold, immediately switching to high-frequency sampling mode, analyzing the dominant trend between the current separation efficiency change rate and the fan power change rate; if the power change rate continues to increase, performing duct backflushing operation; if the separation efficiency drops sharply, synchronously reducing the wind speed output and activating the alarm prompt, returning the trigger information and adjustment feedback together for historical data correlation analysis and trend correction.

[0019] The second aspect of this invention provides an intelligent screening and debris recovery device for a steel ball hard grinding mill, comprising: a data acquisition and preprocessing unit, a collaborative evaluation unit, a wind speed adjustment unit, a historical analysis unit, and a fluctuation response unit. The device is characterized in that: the data acquisition and preprocessing unit is used to acquire operational data during the debris separation process and perform anomaly removal, standardization, and normalization processing; the collaborative evaluation unit is used to calculate the debris separation collaboration value, identify the coordination state of air separation and magnetic attraction, and determine whether the device enters the adjustment zone; the wind speed adjustment unit is used to dynamically adjust the fan frequency according to the wind force adjustment decision value, record the correspondence between adjustment behavior and separation efficiency, and optimize the control strategy; the historical analysis unit is used to store and analyze historical operational data, extract the correlation between parameters and separation efficiency, and update the set ranges of wind speed and magnetic force; the fluctuation response unit is used to calculate the operational fluctuation warning value, determine whether backflushing, speed limiting, and alarm operations are triggered, and transmit the trigger information back.

[0020] Beneficial effects

[0021] The present invention has the following beneficial effects:

[0022] (1) This invention constructs a structured input dataset by real-time acquisition and preprocessing of wind speed, magnetic current, recovery quality and other data during the debris separation process. This solves the problems of mixed sensor data, failure to remove anomalies and low algorithm calling efficiency in existing methods, and provides an accurate data foundation for subsequent intelligent judgment.

[0023] (2) By constructing a debris separation coordination value and setting multi-layer response thresholds, the present invention realizes the automatic identification and classification of the wind separation and magnetic attraction coordination state, overcoming the shortcomings of the prior art that lacks a real-time evaluation mechanism for wind-magnetic coordination and makes it difficult to dynamically perceive the misclassification state.

[0024] (3) The present invention designs a wind speed regulation decision value calculation function and combines the mapping relationship between regulation behavior and separation results to dynamically optimize the wind speed control strategy, avoiding the problems of wind speed regulation relying on static rules, regulation lag and disturbance amplification in traditional methods.

[0025] (4) By introducing a method for calculating early warning values ​​of operational fluctuations and combining it with historical data feedback, this invention enables early identification and refined intervention of abnormal states, improves the stability and response sensitivity of the control device under high load, and makes up for the problems of delayed early warning judgment and single response measures in existing devices.

[0026] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0027] Figure 1 This is a flowchart of the intelligent screening and debris recycling method for a steel ball hard grinding mill according to the present invention;

[0028] Figure 2 This is a structural diagram of the intelligent screening and debris recovery device for a steel ball hard grinding mill according to the present invention;

[0029] Figure 3 This is a trend chart illustrating the operational fluctuations of the present invention.

[0030] Figure 4 This is a distribution diagram of separation efficiency corresponding to different levels of coordinated adjustment in this invention. Detailed Implementation

[0031] 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.

[0032] Please see Figures 1-4This invention provides a technical solution: an intelligent screening and debris recovery method for a steel ball hard grinding mill, comprising the following steps: S1: Real-time acquisition of debris separation operation data and preprocessing of the debris separation operation data; S2: Collaborative evaluation of debris separation operation data, identifying the coordination state of air separation and magnetic attraction based on the collaborative evaluation results, and determining whether it is necessary to enter the adjustment zone; S3: Wind force adjustment decision guidance for debris separation operation data entering the adjustment zone, dynamically adjusting the wind speed output based on the wind force adjustment decision guidance results, recording the correspondence between adjustment behavior and separation effect, and optimizing the wind speed adjustment range and execution rhythm; S4: Storage and analysis of historical operation data and adjustment results, extracting the correlation between parameters and efficiency, and adjusting the basic setting range of wind speed and magnetic force; S5: Execution of operation fluctuation early warning triggering based on the comprehensive debris separation operation data, debris separation collaborative evaluation results, and wind force adjustment decision guidance results, determining whether to execute backflushing action, limit wind speed output, or issue an alarm signal based on the operation fluctuation early warning triggering results, and returning the trigger information and corresponding adjustment results for historical data updates and correlation analysis.

[0033] Specifically, real-time data collection of debris separation operation is performed, and the debris separation operation data is preprocessed. The specific steps are as follows: The debris separation operation data includes multiple dimensions of parameters such as the amount of debris recovered by air separation, the total amount of debris input, the wind speed in the air separation channel, the current of the magnetic coil, the amount of debris recovered by magnetic attraction, the current sampling time, the control cycle length, the current power of the fan, and the early warning trigger time point, which constitute the basic dataset of the device's operating status. The amount of debris recovered by air separation is simultaneously acquired by a weighing sensor and an infrared particle counter installed at the recovery port, taking into account both weight and particle throughput. The total input amount of debris is acquired by a mass flow sensor deployed at the front end of the separation section to measure the overall material load. The wind speed in the air separation channel is acquired by a wind speed sensor installed in the middle of the channel to reflect the airflow status in real time. The magnetic coil current is acquired through the current feedback interface integrated into the magnetic control power board to reflect changes in magnetic field strength. The amount of debris recovered by magnetic attraction is acquired by an electronic weighing device in the recovery bin at the end of the magnetic attraction channel to evaluate the magnetic attraction effect. The current sampling time is obtained by a built-in real-time clock, the control cycle length is read through the parameter setting interface, the current power of the fan is acquired in real time by the drive-side power measurement interface, and the warning trigger time is calculated and generated by a set algorithm. Based on the real-time acquisition of the above data, the calculated debris separation coordination value, wind power adjustment decision value, and operational fluctuation warning value are also recorded to provide structured input for subsequent judgment. The preprocessing steps include: performing anomaly identification and removal operations on the collected data to exclude abrupt changes and invalid data, and retaining anomaly records for traceability; standardizing the cleaned data according to a unified reference center and fluctuation range to eliminate dimensional differences between different variables; further normalizing key variables to compress values ​​into fixed intervals, enhancing the convergence and stability of the discrimination and adjustment algorithms; and storing the data according to their functional uses after preprocessing, allowing collaborative assessment, wind speed adjustment, and early warning triggering logic to call them as needed, while recording the processing method and time information for each round to achieve process traceability and logical closed loop.

[0034] In this implementation plan, this step establishes a complete set of operating parameters covering multiple dimensions of variables, including wind-separated recovery volume, wind speed, magnetic current, and device power, through comprehensive collection and preprocessing of debris separation operation data. This ensures the stability, consistency, and discriminability of the data before it enters the control logic. Standardization and normalization processes eliminate scale differences between physical quantities, improving the algorithm's ability to identify abnormal operating conditions and its sensitivity to adjustment responses. Simultaneously, the classification storage and anomaly recording mechanism provides a reliable basis for subsequent status judgment, trend analysis, and risk warning, laying the foundation for building a data-driven intelligent control mechanism for the device.

[0035] Specifically, a collaborative evaluation of debris separation operation data is conducted, with the following steps: First, core variables are acquired, including the amount of debris recovered by air classification, total debris input, air velocity in the air classification channel, magnetic coil current, amount of debris recovered by magnetic attraction, and the quality of misclassified debris. This forms the basis for a set of key indicators reflecting the separation status. The quality of misclassified debris is obtained by comparing the differences between the debris component analysis at the recovery port and the classification measurement results, thus quantifying the degree of separation deviation. The ratio of the amount of debris recovered by air separation to the total input amount of debris is incremented by one and then the natural logarithm is taken as the first part, reflecting the basic level of air separation recovery efficiency. Next, the square of the air separation channel velocity is divided by the value of the misclassified debris mass plus one, and this value is used as the input of the hyperbolic tangent function. This is then multiplied with the result of the first part to form a composite expression of the first two terms, used to characterize the trend of recovery quality change under the action of airflow. Subsequently, the magnetic coil current is divided by the value of the magnetically recovered debris plus one, and the result is incremented by one and then the natural logarithm is taken to form the third part, used to reflect the energy efficiency matching degree of the magnetic attraction device. Finally, the product of the first two parts is added to the logarithmic result of the third part to obtain the debris separation coordination value, which serves as a quantitative indicator for evaluating the coordination state of air separation and magnetic attraction, and is used to support subsequent adjustment judgment and control triggering logic.

[0036] The specific calculation method for the debris separation synergy value is as follows:

[0037]

[0038] In the formula, Indicates the debris separation synergy value. This indicates the amount of debris recovered by air separation. This indicates the total amount of debris input. Indicates the mass of misclassified debris. Indicates the wind speed in the air separation channel. Indicates the current in the magnetic coil. This indicates the amount of debris that is magnetically collected.

[0039] In this implementation plan, this step, by constructing a debris separation coordination value, achieves a quantitative assessment of the coordination state between air separation and magnetic attraction, fusing multi-source operational data into a core indicator that can be used to determine the state of the regulation zone. The calculation process of the coordination value fully considers air separation efficiency, airflow disturbance intensity, magnetic attraction current and recovery matching degree, as well as misseparation, and can comprehensively reflect the coordination and stability of the current debris separation process. This indicator provides data basis for the triggering and graded response of the regulation strategy, helping to improve the judgment accuracy and timeliness of the regulation response of the device under complex operating conditions.

[0040] Specifically, based on the debris separation coordination evaluation results, the coordination status of air separation and magnetic attraction is identified to determine whether it is necessary to enter the adjustment zone. The specific steps are as follows: The debris separation coordination value is compared with the set response thresholds θ1, θ2, and θ3. Based on the comparison results, different levels of control response priorities and operating status judgments are triggered. When the debris separation coordination value is greater than or equal to θ1, it is rated as a coordinated stability level, indicating that the current air separation and magnetic attraction are well coordinated. The device maintains the fan frequency and magnetic attraction current unchanged, does not perform adjustment actions, and only enters a low-power monitoring state. The sampling period is maintained at 30 seconds, and the separation efficiency trend is recorded for subsequent analysis. When the debris separation coordination value is greater than or equal to θ2 and less than θ1, it is rated as a weak coordination level, indicating a slight imbalance in the wind-magnetic coordination. The device shortens the sampling period to 15 seconds and performs differentiated adjustments: if the wind separation efficiency is judged to be low, the fan frequency is increased by 5%–10%, and the angle of the guide structure is appropriately adjusted to guide the airflow deflection direction; if the magnetic attraction ability is judged to be weak, the magnetic attraction current is increased by 0.3–0.5A, and the device is switched to continuous adsorption mode, while monitoring the change in the error rate to dynamically judge the effectiveness of the adjustment. When the debris separation coordination value is greater than or equal to θ3 and less than θ2, it is rated as a coordination degradation level. The device enters an enhanced control state, the fan frequency is increased to more than 90% of the rated upper limit, the magnetic attraction module starts a high magnetic pulse mode, and automatically activates an adsorption enhancement operation every 15 seconds. This adsorption enhancement function uses short-duration, high-frequency, high-current excitation of the magnetic coil to release a stronger magnetic field instantaneously, enhancing the capture ability of low-magnetic and boundary debris, increasing the recovery coverage area, and reducing adsorption blind zones. It is particularly suitable for working conditions with uneven material particle size and unstable distribution. During adjustment, the device continuously records the adjustment log and monitors the adjustment feedback in real time. If there is no significant improvement within three consecutive cycles, it will enter the protection preparation process. When the debris separation coordination value is lower than θ3, it is rated as a coordination failure level, indicating that the air separation and magnetic attraction coordination mechanism is seriously out of sync, with the risk of misseparation and operational interference. The device immediately stops all adjustment logic, performs air duct backflushing and magnetic attraction power-off reset operations, and triggers the alarm device, entering a protection standby state. Operation can only be resumed after manual confirmation.

[0041] like Figure 4The figure shows the separation efficiency distribution corresponding to different coordination adjustment levels provided in this application embodiment. The separation state is divided into four categories: "coordinated stability," "weak coordination," "coordinated degradation," and "coordinated failure." It is evident that the separation efficiency distribution trend at different levels shows a progressively decreasing characteristic. The "coordinated stability" level has the highest overall separation efficiency, concentrated in the range of 0.89 to 0.92 with relatively small fluctuations. The "weak coordination" range is slightly wider, with efficiency decreasing to approximately 0.79 to 0.84. "Coordinated degradation" further declines, concentrated in the range of 0.72 to 0.77, showing a clear degradation trend. The "coordinated failure" state has the lowest efficiency level and a large fluctuation range, distributed between 0.60 and 0.67. This graph helps to intuitively identify the impact of different adjustment levels on separation performance, providing a distribution basis for the formulation of refined adjustment strategies.

[0042] In this implementation scheme, this step, by setting multi-layered response thresholds, classifies and judges the synergistic value of debris separation, achieving real-time identification and classification response to the coordination state of air separation and magnetic attraction. The device can dynamically adjust the sampling frequency, fan output, and magnetic attraction intensity according to different levels of coordination, selectively performing gradual adjustment, continuous adsorption, and high-magnetic-pulse operation to ensure that appropriate measures are taken in situations of slight imbalance, significant degradation, and severe failure during the separation process. The adsorption enhancement function can effectively expand the magnetic attraction coverage area, improve the ability to capture edge debris, and enhance recovery stability. Through this graded control mechanism, the device possesses strong state recognition capabilities and response adaptability, providing fundamental support for intelligent control of the debris separation process.

[0043] Specifically, the wind-driven adjustment decision is guided by the debris separation operation data entering the adjustment zone. The specific steps are as follows: Key variables such as the current sampling time, current separation efficiency, amount of debris recovered by wind separation, total debris input, and control cycle length are acquired as the basic input for adjustment judgment. The target separation efficiency is obtained by extracting the interval with the best separation efficiency performance from historical operation data, reflecting the optimal performance level of the device under similar operating conditions. The current separation efficiency is calculated as the ratio between the total amount of debris recovered by the wind separation module and the magnetic attraction module in the current operating cycle and the total debris input, used to measure the current separation performance. The historical average efficiency is calculated by extracting efficiency data from multiple consecutive cycles from the separation efficiency data buffer built into the control logic and calculating it using an arithmetic mean, used to determine the current deviation trend. In the calculation of the adjustment value, the target separation efficiency minus the current separation efficiency is first used as the numerator to reflect the degree of deviation between the target and reality. Then, the exponential function is used with the current separation efficiency minus the negative of the historical average efficiency as the exponent, plus one to form the denominator, which describes the relative difference between the separation state and the operating trend. Subsequently, pi multiplied by the current sampling time divided by the control cycle length is used as the input of the sine function, and the result is added to one as the multiplication factor to introduce the periodic fluctuation factor. Finally, the above fractional results are multiplied by the sine factor, and the static deviation and dynamic rhythm are combined to obtain the wind speed adjustment decision value, which provides a direct basis for the amplitude and direction of wind speed adjustment.

[0044] The specific calculation method for the wind force regulation decision value is as follows:

[0045]

[0046] In the formula, This represents the wind speed regulation decision value. Indicates the target separation efficiency. Indicates the current separation efficiency. Indicates historical average efficiency. Indicates the current sampling time. Indicates the length of the control cycle.

[0047] In this implementation plan, this step achieves dynamic guidance of wind speed adjustment needs by constructing a wind force adjustment decision value. This value comprehensively considers the deviation relationship between target efficiency, current efficiency, and historical operating trends, and incorporates periodic variation characteristics by combining sampling time series factors, enabling it to accurately characterize the adjustment direction and intensity of current separation performance. Compared with traditional adjustment methods based on fixed differences, this guidance mechanism is more responsive and trend-adaptive, providing a quantitative basis for subsequent wind speed output control and helping to improve the accuracy and energy efficiency in the debris separation process.

[0048] Specifically, the wind speed output is dynamically adjusted based on the wind force adjustment decision guidance results, and the correspondence between adjustment behavior and separation effect is recorded to optimize the wind speed adjustment amplitude and execution rhythm. The specific steps are as follows: The wind force adjustment decision value is used as a continuous variable to directly guide the dynamic adjustment of wind speed. The adjustment logic executes a graded response strategy based on its positive and negative signs and amplitude. When the value is positive, it indicates that the current separation efficiency is lower than the target level. The device will perform a gradual and enhanced wind speed increase according to its value. For slight deviations, the fan frequency is slowly increased. For larger deviations, the angle of the air guide plate is adjusted simultaneously to concentrate the airflow to the recovery area and enter the target tracking state to monitor the changes in separation effect after the wind speed increase in real time. When the adjustment value is negative, it indicates that the wind speed is too high, causing misseparation and magnetic attraction interference. The device will reduce the fan frequency according to its absolute value. When the deviation is significant, it enters the flow suppression adjustment state, suspends the flow guide structure operation to stabilize the airflow field, and initiates protective observation of the magnetic attraction module to avoid high-speed airflow interference and adsorption. When the absolute value of the adjustment is close to zero, it indicates that the current operation is basically consistent with the target state. The device enters the holding state, maintains the current wind speed, and only activates the low-frequency monitoring mechanism to check whether the operation stability is still within the allowable range at regular intervals, so as to ensure the continuity of the adjustment rhythm and the control accuracy.

[0049] In this implementation scheme, this step guides the dynamic adjustment of wind speed output through a wind force adjustment decision value, achieving precise response and rhythm control to separation efficiency deviations. Based on the sign and magnitude of this value, the device can flexibly execute various adjustment strategies, including gradual increase, enhanced intervention, disturbance suppression, and stable maintenance, and continuously optimize the correspondence between adjustment behavior and separation effect by combining real-time feedback. This mechanism effectively improves the responsiveness and operational stability of the wind separation process, avoids debris mis-separation and magnetic interference caused by unbalanced wind speed settings, and provides continuous adaptive wind force support for the entire separation process.

[0050] Specifically, the system stores and analyzes historical operating data and adjustment results, extracts the correlation between parameters and efficiency, and adjusts the basic setting range of wind speed and magnetic force. The specific steps are as follows: Key operating parameters during debris separation, such as wind speed, magnetic current, recovery efficiency, and error rate, are recorded and stored synchronously with each corresponding adjustment command, constructing a traceable operating database. Over multiple operating cycles, the device performs horizontal comparisons and vertical trend analysis on historical data, extracting the correlation between different parameter combinations and separation efficiency, and identifying the optimal operating conditions for specific material characteristics and operating conditions. Based on the analysis results, the device can proactively correct the basic setting range of wind speed and magnetic force, no longer relying on static parameter settings, but continuously adapting to changes in debris particle size, content, and physical properties, improving the targeting and adaptability of the adjustment basis. When a significant deviation in the operating trend is detected, such as increased efficiency fluctuations and response lag, an adjustment tendency reference value is automatically generated to assist the wind speed adjustment unit in optimizing the control strategy, achieving long-term stable evolution of separation behavior.

[0051] In this implementation plan, this step achieves dynamic optimization of the wind speed and magnetic field baseline setting range through continuous storage and analysis of historical operating data and adjustment results. By extracting the correlation between parameters and separation efficiency, the device can identify optimal combinations under different materials and operating conditions, and promptly adjust the setting range when the operating trend deviates, generating a reference value for adjustment tendency. This mechanism enhances the device's adaptability to changing operating conditions, avoids efficiency decline due to fixed parameters, and provides data support and evolutionary basis for long-term optimization of the adjustment strategy.

[0052] Specifically, the operational fluctuation early warning trigger is executed by integrating debris separation operation data, debris separation collaborative evaluation results, and wind power regulation decision guidance results. The specific steps are as follows: First, key inputs such as current separation efficiency, current turbine power, early warning trigger time, and current sampling time are obtained to construct the data foundation for fluctuation calculation. The difference in current separation efficiency between two consecutive sampling periods is divided by the corresponding time interval to calculate the separation efficiency change rate, reflecting the dynamic fluctuation degree of separation performance. Then, the turbine power change rate is calculated by the ratio of the difference in turbine power at adjacent times to the sampling interval, which is used to measure the variation of turbine operating load. The separation efficiency change rate is squared to form the first term, representing the intensity of efficiency fluctuation. The turbine power change rate is multiplied by the natural logarithm of the current turbine power plus one, and then squared to form the second term, introducing the nonlinear weight of power disturbance. The square root of the sum of the two terms forms the core fluctuation value that comprehensively reflects separation efficiency and energy consumption disturbance. Subsequently, the time difference between the current sampling time and the early warning trigger time is used as the input variable and substituted into the Dirac function to calculate the pulse offset at the key moment, emphasizing the response characteristics to special instants. Finally, the core fluctuation value and the pulse offset value are added together to obtain the operational fluctuation warning value, which provides a triggering basis for subsequent protection response and adjustment intervention.

[0053] The specific calculation method for the operational fluctuation warning value is as follows:

[0054]

[0055] In the formula, This indicates the operational fluctuation warning value. Indicates the current separation efficiency. Indicates the current power of the wind turbine. Indicates the time point when the warning is triggered. Indicates the current sampling time.

[0056] Table 1 shows the operational fluctuation warning value data table provided in this embodiment of the application. In this embodiment, the current separation efficiency of data 1 is set to 0.85, the current power of the wind turbine is set to 2.1, and the warning trigger time point is set to 1; the current separation efficiency of data 2 is set to 0.82, the current power of the wind turbine is set to 2.5, and the warning trigger time point is set to 1; the current separation efficiency of data 3 is set to 0.78, the current power of the wind turbine is set to 2.8, and the warning trigger time point is set to 1; the current separation efficiency of data 4 is set to 0.81, the current power of the wind turbine is set to 2.3, and the warning trigger time point is set to 1; the current separation efficiency of data 5 is set to 0.79, the current power of the wind turbine is set to 2.0, and the warning trigger time point is set to 1.

[0057] Table 1. Operational Fluctuation Early Warning Value Data Table

[0058]

[0059] like Figure 3 The figure shows a trend chart of operational fluctuation warning values ​​provided in this application embodiment. According to the data in the image and table, the set operational fluctuation threshold is 1.2. The operational fluctuation warning values ​​corresponding to the five sets of data fluctuate between 0.00 and 1.50, showing an overall trend of first rising and then falling. The operational fluctuation warning value of data 2 is 1.50, significantly exceeding the threshold, indicating significant fluctuations in current separation efficiency and fan power, indicating a high-fluctuation abnormal state. The operational fluctuation warning values ​​of data 3 and 4 are 0.40 and 0.60 respectively. Although they do not exceed the threshold, they show significant fluctuations, suggesting the need to pay attention to adjustment stability. The operational fluctuation warning values ​​of data 5 and 1 are 0.33 and 0.00 respectively, both below the threshold, indicating a relatively stable operating state. This figure can be used to intuitively determine whether there are abnormal fluctuations in operation, providing auxiliary judgment basis for subsequent triggering of backflushing, speed limiting, and alarm operations.

[0060] In this implementation plan, this step achieves dynamic identification and quantitative assessment of fluctuation risks in the debris separation process by constructing an operational fluctuation early warning value. This value comprehensively considers the rate of change in separation efficiency and the intensity of fan power disturbances, and incorporates a pulse response factor at critical moments, enabling it to accurately capture abnormal trends and sudden fluctuations in the operating state. The early warning value serves as the basis for triggering adjustment and protection logic, effectively improving the sensitivity and response accuracy of the device under complex operating conditions, and providing a real-time and reliable basis for subsequent execution of backflushing, speed limiting, and alarm measures.

[0061] Specifically, the system determines whether to execute backflushing, limit wind speed output, or issue an alarm signal based on the operational fluctuation warning trigger result. The trigger information and corresponding adjustment results are returned for historical data updates and correlation analysis. The specific steps are as follows: The operational fluctuation warning value is compared with the preset fluctuation threshold in real time as the basis for triggering protective actions. When the operational fluctuation warning value is less than the fluctuation threshold, it indicates that the current operating state is stable. The device maintains the original fan frequency and magnetic current settings, performs only low-frequency periodic monitoring, and writes all sampled data completely into the historical record area for subsequent trend analysis. When the operational fluctuation warning value is greater than or equal to the fluctuation threshold, the device immediately switches to high-frequency sampling mode, significantly improving the data refresh rate and quickly capturing device fluctuation details. Simultaneously, it analyzes the dominant relationship between the current separation efficiency change rate and the fan power change rate. If a continuous increase in the power change rate is detected, it indicates abnormal fan load. A backflushing operation is executed to clear channel blockages and turbulent debris. If the separation efficiency drops sharply, it is considered sorting instability. The device simultaneously reduces the wind speed output and activates an alarm signal to prompt maintenance intervention. All trigger information and corresponding adjustment feedback will be simultaneously written into the historical database, serving as an important basis for trend correction and parameter updates, and realizing the dynamic improvement of the data loop.

[0062] In this implementation plan, this step achieves real-time judgment and response control of abnormal fluctuations in the debris separation process by comparing the operational fluctuation warning value with the set threshold. Based on the warning value, the device can dynamically select to initiate high-frequency sampling, perform duct backflushing, reduce airflow speed, trigger alarms, and perform other operations. All response results and process parameters are synchronously written into the historical record for subsequent data analysis and adjustment strategy correction. This mechanism effectively improves the timeliness of anomaly identification and the targeted nature of intervention responses, enhancing the overall operational stability and safety.

[0063] like Figure 2 The diagram shown is a structural schematic of the intelligent screening and debris recovery device for a steel ball hard grinding mill provided in this embodiment of the application. The intelligent screening and debris recovery device for a steel ball hard grinding mill provided in this embodiment of the application applies an intelligent screening and debris recovery method for steel ball hard grinding mills, including: a data acquisition and preprocessing unit, a collaborative evaluation unit, a wind speed adjustment unit, a historical analysis unit, and a fluctuation response unit. The data acquisition and preprocessing unit is used to acquire key operating data during the debris separation process, including wind speed, magnetic current, recovery quality, and other parameters, and performs anomaly removal, standardization, and normalization processing on the data to improve the stability and accuracy of subsequent calculations. The collaborative evaluation unit is used to combine multiple separation-related variables to calculate the debris separation collaborative value and make real-time judgments. The system checks whether the wind separation and magnetic attraction work in coordination and identifies whether it needs to enter the adjustment zone. The wind speed adjustment unit dynamically adjusts the fan frequency based on wind force adjustment decision values, while simultaneously recording the response relationship between wind speed changes and separation efficiency, providing feedback for control strategy optimization. The historical analysis unit stores operating data and adjustment results long-term, extracts the correlation between parameters and separation effects through comparative analysis, and dynamically corrects the set ranges for wind speed and magnetic force. The fluctuation response unit integrates current efficiency fluctuations and power disturbances, calculates operating fluctuation warning values, and determines whether to trigger backflushing operations, limit wind speed, and issue alarm signals. It also sends the response information back to update historical data and adjustment logic.

[0064] In this implementation plan, this step achieves data-driven intelligent control of the entire debris separation process by constructing five functional units: data acquisition and preprocessing, collaborative evaluation, wind speed adjustment, historical analysis, and fluctuation response. These units form a closed-loop collaborative mechanism: from accurately acquiring and preprocessing raw data, to real-time evaluation of the separation status and making wind speed adjustment decisions, then optimizing parameters based on historical operating experience, and finally improving the timeliness and accuracy of anomaly intervention through a fluctuation response mechanism. This structure enables the entire device to possess dynamic sensing, real-time judgment, intelligent adjustment, and continuous evolution capabilities, effectively enhancing the stability, adaptability, and intelligence level of the separation process.

[0065] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0066] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for intelligent screening and debris recovery in a steel ball hard grinding mill, characterized in that, Includes the following steps: S1: Real-time acquisition of debris separation operation data and preprocessing of the debris separation operation data; The specific steps for real-time acquisition of debris separation operation data and preprocessing of the debris separation operation data are as follows: The debris separation operation data includes: the amount of debris recovered by air classifier, the total amount of debris input, the wind speed in the air classifier channel, the current of the magnetic coil, the amount of debris recovered by magnetic attraction, the current sampling time, the control cycle length, the current power of the fan, and the warning trigger time. The amount of debris recovered by air separation is obtained synchronously by a weighing sensor installed at the air separation recovery port and an infrared particle counter; the total input amount of debris is obtained by a mass flow sensor deployed at the front end of the separation section; the wind speed in the air separation channel is obtained by a wind speed sensor installed in the middle of the air separation channel; the current of the magnetic coil is obtained by the current feedback interface integrated into the magnetic control power board; the amount of debris recovered by magnetic attraction is obtained by an electronic weighing device installed in the recovery bin at the end of the magnetic attraction channel; the current sampling time is obtained by a built-in real-time clock; the control cycle length is obtained by the operating parameter setting interface; the current power of the fan is obtained in real time by the power measurement interface on the fan drive side; the early warning trigger time point is calculated and generated by the algorithm in the parameter setting rules; and the calculated debris separation coordination value, wind power adjustment decision value, and operating fluctuation early warning value are recorded in real time. The preprocessing steps include: identifying and removing anomalies in the collected data, excluding mutated values ​​and invalid data, and retaining anomaly records for subsequent analysis; standardizing the cleaned data according to a unified reference center and fluctuation range; performing normalization operations on key variables and compressing them to a fixed interval; classifying and storing the processed data according to their purpose for use by various judgment and control logics; and recording the processing method and time information for each round of processing. S2: Perform a collaborative evaluation of debris separation operation data, identify the coordination status of air separation and magnetic attraction based on the debris separation collaborative evaluation results, and determine whether it is necessary to enter the adjustment zone at present. The debris separation synergy value is obtained by performing a synergy evaluation on the debris separation operation data. The specific calculation method for the debris separation synergy value is as follows: In the formula, Indicates the debris separation synergy value. This indicates the amount of debris recovered by air separation. This indicates the total amount of debris input. Indicates the mass of misclassified debris. Indicates the wind speed in the air separation channel. Indicates the current in the magnetic coil. Indicates the amount of debris collected by magnetic attraction; S3: Conduct wind speed adjustment decision guidance on the debris separation operation data entering the adjustment zone, dynamically adjust the wind speed output based on the wind speed adjustment decision guidance results, record the correspondence between adjustment behavior and separation effect, and optimize the wind speed adjustment range and execution rhythm; The wind force regulation decision value is obtained by applying the debris separation operation data entering the regulation zone to the wind force regulation decision data. The specific calculation method of the wind force regulation decision value is as follows: In the formula, This represents the wind speed regulation decision value. Indicates the target separation efficiency. Indicates the current separation efficiency. Indicates historical average efficiency. Indicates the current sampling time. Indicates the length of the control cycle; S4: Store and analyze historical operating data and adjustment results, extract the correlation between parameters and efficiency, and adjust the basic setting range of wind speed and magnetic force; S5: Based on the integrated debris separation operation data, debris separation collaborative evaluation results and wind power regulation decision guidance results, the operation fluctuation early warning trigger is executed. The triggering results determine whether to execute backflushing action, limit wind speed output, or issue an alarm signal. The triggering information and corresponding regulation results are returned for historical data updates and correlation analysis. The operational fluctuation warning value is calculated by comprehensively considering the current separation efficiency, the current power of the wind turbine, the warning trigger time, and the current sampling time. The specific calculation method for the operational fluctuation warning value is as follows: In the formula, This indicates the operational fluctuation warning value. Indicates the current separation efficiency. Indicates the current power of the wind turbine. Indicates the time point when the warning is triggered. Indicates the current sampling time.

2. The intelligent screening and debris recovery method for a steel ball hard grinding mill according to claim 1, characterized in that: The specific steps for conducting a collaborative evaluation of debris separation operation data are as follows: The system acquires the amount of debris recovered by air separation, the total amount of debris input, the wind speed in the air separation channel, the current of the magnetic coil, the amount of debris recovered by magnetic attraction, and the mass of misseparated debris. The mass of misclassified debris is obtained by comparing the differences between the debris composition analysis and classification measurement results at the recovery port. The ratio of the amount of debris recovered by air separation to the total amount of debris input is increased by one and the natural logarithm is taken to obtain the first part. The square of the wind speed in the air separation channel is divided by the value of the misclassified debris mass plus one, which is used as the input of the hyperbolic tangent function and multiplied with the logarithmic result of the first part to form a combination of the first two terms. Next, the magnetic coil current is divided by the value of the magnetically recovered debris plus one, and the whole is increased by one and the natural logarithm is taken to obtain the third part. Finally, the product of the first two parts is added to the logarithmic result of the third part to obtain the debris separation synergy value.

3. The intelligent screening and debris recovery method for a steel ball hard grinding mill according to claim 1, characterized in that: The specific steps for identifying the coordination status of air separation and magnetic attraction based on the debris separation synergy evaluation results, and determining whether it is necessary to enter the adjustment zone, are as follows: The debris separation coordination value is compared with the set response thresholds θ1, θ2, and θ3, and different levels of control response priorities and operating status are triggered based on the comparison results. When the debris separation synergy value is greater than or equal to θ1, it is rated as a synergistic stability level; When the debris separation synergy value is greater than or equal to θ2 and less than θ1, it is rated as a weak synergy level. When the debris separation synergy value is greater than or equal to θ3 and less than θ2, it is rated as a synergy degradation level; When the debris separation synergy value is less than θ3, it is rated as a synergy failure level; When the device is in the cooperative stability level, it maintains the current fan frequency and magnetic current, enters the low power monitoring mode, maintains the sampling period at 30 seconds, and only records the separation efficiency trend for subsequent analysis. When the device is in a weak coordination level, the sampling period is shortened to 15 seconds. If the air separation efficiency is judged to be low, the fan frequency is increased and the flow guiding structure is adjusted. If the magnetic attraction ability is judged to be weak, the magnetic attraction current is increased and the device is switched to continuous adsorption mode. At the same time, the error rate is monitored to evaluate the adjustment effect. When the device is in the collaborative degradation level, the fan frequency increases to near the rated upper limit, the magnetic module starts the high magnetic pulse adsorption function, and automatically activates adsorption enhancement every 15 seconds. At the same time, it records the adjustment log and evaluates the adjustment feedback. If there is no improvement for three consecutive cycles, it will enter the protection preparation process. When the device is in a collaborative failure state, it performs a backflushing operation of the air duct and a magnetic power-off reset, triggering the alarm module and entering a protection standby state, which will be reactivated after manual confirmation.

4. The intelligent screening and debris recovery method for a steel ball hard grinding mill according to claim 1, characterized in that: The specific steps for guiding wind power regulation decisions based on debris separation operation data entering the regulation zone are as follows: Acquire the current sampling time, current separation efficiency, amount of debris recovered by air classification, total amount of debris input, and control cycle length; The target separation efficiency is obtained by extracting the interval with the best current separation efficiency performance from historical operating data; the current separation efficiency is obtained by calculating the ratio between the total amount of debris recovered by the air separation module and the magnetic attraction module in the current operating cycle and the total amount of debris entering the separation area. The current separation efficiency for several consecutive running cycles is extracted from the historical separation efficiency data cache built into the control logic, and the historical average efficiency is calculated by arithmetic averaging. Subtract the current separation efficiency from the target separation efficiency, and use the result as the molecule. The exponential function with the natural logarithm base is calculated by taking the negative of the total sum of the current separation efficiency minus the historical average efficiency as the exponent, adding one to it as the denominator, and then dividing the numerator by the denominator. Next, the input of the sine function is obtained by multiplying pi by the current sampling time and dividing by the control cycle length, adding one to the result as the multiplication factor. Finally, the fractional result of the first part is multiplied by the sine function factor to obtain the wind power regulation decision value.

5. The intelligent screening and debris recovery method for a steel ball hard grinding mill according to claim 1, characterized in that: The specific steps for dynamically adjusting wind speed output based on wind regulation decision guidance results, recording the correspondence between regulation behavior and separation effect, and optimizing wind speed adjustment range and execution rhythm are as follows: The wind speed adjustment decision value is used as a continuous variable to directly guide the dynamic adjustment of wind speed, and the response strategy is executed according to its positive or negative sign and magnitude. When the wind speed adjustment decision value is positive, the wind speed will be gradually increased and enhanced according to its magnitude. If necessary, the angle of the wind deflector will be adjusted in conjunction with the wind deflector, and the adjustment effect will be monitored in the target tracking state. When the wind speed adjustment decision value is negative, the wind speed is reduced based on its absolute value. When the interference intensifies, the system enters the flow suppression adjustment state, suspends the adjustment of the flow guide structure, and conducts protective observation of the magnetic module. When the absolute value of the wind speed regulation decision value is close to zero, it enters the hold state, maintains the current wind speed output, and only activates the low-frequency monitoring mechanism to determine whether the regulation needs to be reactivated.

6. The intelligent screening and debris recovery method for a steel ball hard grinding mill according to claim 1, characterized in that: The specific steps for storing and analyzing historical operating data and adjustment results, extracting the correlation between parameters and efficiency, and adjusting the basic setting range of wind speed and magnetic force are as follows: Record key operating parameters during debris separation and store them synchronously with corresponding adjustment commands; By comparing and analyzing historical data over multiple operating cycles, the correlation between different parameter combinations and separation efficiency is extracted, and optimal operating conditions are identified. Based on the analysis results, the basic setting range of wind speed and magnetic force is actively adjusted to adapt to changes in debris particle size, content and physical properties. When a significant deviation in the operating trend is detected, a reference value for adjustment tendency is generated to assist the wind speed regulation unit in optimizing the control strategy.

7. The intelligent screening and debris recovery method for a steel ball hard grinding mill according to claim 1, characterized in that: The specific steps for triggering the operational fluctuation early warning based on the integrated debris separation operation data, debris separation collaborative evaluation results, and wind power regulation decision guidance results are as follows: Obtain the current separation efficiency, current fan power, early warning trigger time, and current sampling time; The separation efficiency change rate is calculated by dividing the difference in current separation efficiency between two consecutive sampling periods by the time interval; the wind turbine power change rate is calculated by dividing the difference in current wind turbine power between two consecutive moments by the time interval; the separation efficiency change rate is squared to form the first term; the wind turbine power change rate is multiplied by the natural logarithm of the current wind turbine power plus one, and the product is squared to form the second term; the first and second terms are added together and the square root is taken to form the core fluctuation value; the difference between the current sampling time and the warning trigger time is used as input and substituted into the Dirac function to calculate the pulse offset value triggered at the critical moment; The fluctuation intensity value is added to the pulse offset value to obtain the operation fluctuation warning value.

8. The intelligent screening and debris recovery method for a steel ball hard grinding mill according to claim 1, characterized in that: The specific steps for determining whether to execute a backflushing action, limit wind speed output, and issue an alarm signal based on the operational fluctuation early warning trigger result, and returning the trigger information and corresponding adjustment results for historical data updates and correlation analysis, are as follows: Real-time comparison of operational fluctuation warning values ​​with set fluctuation thresholds; When the operating fluctuation warning value is less than the fluctuation threshold, the current wind turbine frequency and magnetic suction current are maintained, and only periodic monitoring is performed. All sampled data is written to the historical record. When the operation fluctuation warning value is greater than or equal to the fluctuation threshold, immediately switch to high-frequency sampling mode to analyze the dominant trend between the current separation efficiency change rate and the fan power change rate. If the power change rate continues to increase, execute the duct backflushing operation. If the separation efficiency drops sharply, the wind speed output will be reduced simultaneously and an alarm will be activated. The trigger information and adjustment feedback will be returned together for historical data correlation analysis and trend correction.

9. An intelligent screening and debris recovery device for a steel ball hard grinding mill, employing the intelligent screening and debris recovery method for a steel ball hard grinding mill as described in any one of claims 1-8, comprising: The data acquisition and preprocessing unit, collaborative evaluation unit, wind speed regulation unit, historical analysis unit, and fluctuation response unit are characterized by: The acquisition and preprocessing unit is used to acquire operational data during the debris separation process and to complete anomaly removal, standardization, and normalization. The collaborative evaluation unit is used to calculate the debris separation collaborative value, identify the coordination state of air separation and magnetic attraction, and determine whether to enter the adjustment zone. The wind speed regulation unit is used to dynamically adjust the fan frequency according to the wind force regulation decision value, record the correspondence between regulation behavior and separation efficiency, and optimize the control strategy. The historical analysis unit is used to store and analyze historical operating data, extract the correlation between parameters and separation efficiency, and update the set range of wind speed and magnetic force. The fluctuation response unit is used to calculate the operation fluctuation warning value, determine whether to trigger backflush, speed limit and alarm operations, and send back the trigger information.

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