A refining machine powder blockage monitoring system and a method for preventing and clearing blockage.

Abstract

This application discloses a refining machine clogging monitoring system and anti-clogging / unclogging method, relating to the field of metal refining technology. The system includes a main controller integrating an adaptive anti-clogging control algorithm, a pulse diagnostic analysis algorithm, and a linkage control algorithm; and a gas flow sensor communicatively connected to the main controller, used to detect the refining gas flow rate Q_actual in real time. This application, by analyzing the propagation characteristics of pressure pulses, can identify local clogging risks and their approximate locations in the early stages before a significant decrease in pipeline gas flow, overcoming the lag of traditional single flow threshold alarms and achieving proactive fault warning. By using the qualitative risk assessment results from pulse diagnosis as feedforward signals to dynamically adjust the sensitivity threshold and control parameters of the adaptive PID controller, the core control loop possesses risk self-awareness and strategy self-optimization capabilities.

Description

Technical Field

[0001] This application relates to the field of metal refining technology, and in particular to a refining machine powder blockage monitoring system and a method for preventing and clearing blockage. Background Technology

[0002] In the metallurgical refining process, desulfurizing agents, deoxidizing agents, and other refining powders need to be continuously and stably injected into the melt using carrier gas. The core of this process is to ensure the smooth and stable flow of powder in the pneumatic conveying pipeline. However, in actual production, due to reasons such as powder agglomeration due to moisture, fluctuations in conveying pressure, pipeline design defects, or poor matching of operating parameters, the powder conveying pipeline is prone to local blockage. Once the powder is blocked, it will directly lead to the interruption or fluctuation of powder delivery, which will seriously affect the refining reaction efficiency and melt purity. It may even cause safety hazards due to a surge in pressure, forcing production to be interrupted for manual unblocking, resulting in economic losses.

[0003] Existing methods for monitoring powder blockage mainly rely on single gas flow or pressure monitoring. When the flow rate is detected to be below a set threshold or the pressure exceeds the upper limit, the system issues an alarm or takes emergency measures such as stopping the pump or backflushing. These methods have obvious lag and passivity: by the time the alarm is triggered, the blockage has often developed to a relatively serious stage, and the handling process inevitably leads to production interruption. Moreover, they can only determine "whether there is powder blockage" and cannot identify and locate the early signs, risk level, and specific location of the blockage. This belongs to the "post-fault handling" mode. Some improvement solutions attempt to match the gas flow by adjusting the speed of the powder feeding motor to form a closed-loop control. However, its response is based on the flow deviation that has already occurred, which is essentially still an after-the-fact adjustment. It cannot prevent the occurrence of blockage and lacks the ability to directly perceive the internal state of the pipeline. The adjustment effect is limited when the powder characteristics change or there is slight wall adhesion. Summary of the Invention

[0004] To address the aforementioned problems, this application provides a refining mill powder blockage monitoring system and a method for preventing and clearing blockages.

[0005] This application provides a refining mill powder blockage monitoring system and a method for preventing and clearing blockage, which adopts the following technical solution:

[0006] A refining machine clogging monitoring system includes:

[0007] The main controller integrates an adaptive anti-blocking control algorithm, a pulse diagnosis and analysis algorithm, and a linkage control algorithm.

[0008] A gas flow sensor is communicatively connected to the main controller and is used to detect the refining gas flow value Q_actual in real time.

[0009] A powder dispensing mechanism, which includes a powder dispensing motor, is communicatively connected to the main controller;

[0010] Two pressure sensors are provided, which are communicatively connected to the main controller and are spaced apart along the powder feeding pipeline.

[0011] A pulse generator, which is communicatively connected to the main controller, is used to inject pressure pulses into the powder feeding pipeline;

[0012] The adaptive anti-clogging control algorithm is as follows: based on the deviation between the real-time gas flow rate value Q_actual and the target flow rate value Q_set, the speed setting value of the powder delivery motor is dynamically adjusted through PID calculation so that the powder delivery rate M_actual satisfies the relationship: M_actual=M_set+K*(Q_set-Q_actual), where M_set is the target powder delivery rate and K is a negative proportionality coefficient, and the refining time T_new=M_total / M_actual is recalculated based on the total powder delivery amount M_total;

[0013] The pulse diagnostic analysis algorithm is as follows: a pressure pulse is injected into the pipeline, and the response signals of at least two pressure sensors are collected. The propagation time difference Δt and amplitude attenuation rate ΔA between the signals are calculated and compared with a preset health baseline threshold to achieve a dust blockage risk assessment.

[0014] The linkage control algorithm is as follows: the output of the pulse diagnostic analysis algorithm is used as the feedforward input of the adaptive anti-blocking control algorithm, and its PID parameters or flow deviation threshold are adjusted.

[0015] As a preferred technical solution of this application, the PID operation in the adaptive anti-blocking control algorithm is specifically as follows: calculate the flow deviation e(t) = Q_set - Q_actual, and the adjustment amount u(t) of the powder discharge motor speed setting value is: u(t) = K_p*e(t) + K_i*∫e(t)dt + K_d*de(t) / dt, where K_p, K_i, and K_d are preset control parameters, and are tuned online through the linkage control algorithm.

[0016] As a preferred technical solution of this application, the main controller also integrates a purging sub-algorithm. The purging sub-algorithm is as follows: when it is detected that Q_actual has recovered to the normal range [Q_set-ΔQ, Q_set+ΔQ], the purging timer is triggered. During the purging time T_purge, the speed setting value u(t) of the powder discharge motor is locked to the current value. After T_purge ends, the lock is released and the normal PID operation is restored.

[0017] As a preferred technical solution of this application, the amplitude attenuation rate ΔA in the pulse diagnostic analysis algorithm is calculated as follows: ΔA=20*log10(A2 / A1), where A1 is the amplitude of the pulse signal received by the pressure sensor close to the pulse generator, and A2 is the amplitude of the pulse signal received by the pressure sensor far from the pulse generator.

[0018] The main controller also integrates a powder blockage location algorithm, which is as follows: calculate the actual pulse propagation speed according to the formula v_actual=L / Δt, where L is the distance between the two pressure sensors, compare v_actual with the reference speed v_base of the unobstructed pipeline, and use the pre-stored propagation speed-powder density relationship model to inversely calculate the approximate location of the powder blockage point.

[0019] As a preferred technical solution of this application, the linkage control algorithm specifically means that when the risk level output by the pulse diagnostic analysis algorithm exceeds the preset level, the flow deviation threshold that triggers intervention in the adaptive anti-blocking control algorithm is automatically reduced, that is, the ΔQ value is reduced, and the system sensitivity is improved.

[0020] As a preferred technical solution of this application, a method for preventing and clearing blockage in a refining machine includes the following steps:

[0021] S1, based on the deviation between the real-time detected refining gas flow rate value Q_actual and the target flow rate value Q_set, the speed of the powder delivery motor is dynamically adjusted through the control algorithm so that the actual powder delivery rate M_actual follows the change of the target powder delivery rate M_set.

[0022] S2, During the operation of the system, a pressure pulse is injected into the powder feeding pipeline, and the response signals of at least two pressure sensors arranged along the pipeline are collected. By analyzing the response signals, the propagation time difference Δt and amplitude attenuation characteristics of the pulse are calculated to assess the risk of pipeline blockage.

[0023] S3 takes the risk assessment results output from S2 as feedforward input and dynamically adjusts the control parameters or operating logic in S1.

[0024] As a preferred technical solution of this application, in S1, more specifically, the flow deviation e(t) = Q_set - Q_actual is calculated, and a PID controller is used to calculate the adjustment amount u(t) of the powder discharge motor speed based on the flow deviation e(t), where u(t) = K_p*e(t) + K_i*∫e(t)dt + K_d*de(t) / dt, K_p, K_i, and K_d are control parameters. The relationship between the actual powder delivery rate M_actual and the target powder delivery rate M_set satisfies: M_actual = M_set + K*(Q_set - Q_actual), and the refining time is recalculated based on the real-time powder delivery rate.

[0025] In summary, this application includes the following beneficial technical effects of a refining mill powder blockage monitoring system and anti-blockage and unblocking method:

[0026] This application, by analyzing the propagation characteristics of pressure pulses, can identify the risk and approximate location of local blockages in the early stages before the gas flow rate in the pipeline has significantly decreased. This overcomes the lag of traditional single flow threshold alarms and realizes proactive fault warning. By using the qualitative risk assessment results of pulse diagnosis as a feedforward signal to dynamically adjust the sensitivity threshold and control parameters of the adaptive PID controller, the core control loop has the ability to self-perceive risks and self-optimize strategies, enhancing the system's adaptability to complex operating conditions and the forward-looking nature of control. Through the deep integration of three-level mechanisms, the system can not only quickly suppress existing disturbances but also intervene in potential blockage trends in advance. Combined with automated purging and recovery procedures, it fundamentally reduces the frequency of unplanned shutdowns, ensures the continuity of refining operations and process stability, thereby improving overall production efficiency and equipment reliability. Attached Figure Description

[0027] Figure 1 This is the architecture diagram of the refining mill powder blockage monitoring system of this application;

[0028] Figure 2 This is a flowchart of the anti-clogging and unclogging method for the refining machine in this application. Detailed Implementation

[0029] The following is in conjunction with the appendix Figure 1-2 This application will be described in further detail.

[0030] See Figure 1-2 A refining machine clogging monitoring system, comprising:

[0031] The main controller integrates adaptive anti-blocking control algorithm, pulse diagnosis and analysis algorithm, and linkage control algorithm.

[0032] The gas flow sensor is connected to the main controller and is used to detect the refining gas flow rate value Q_actual in real time.

[0033] The powder dispensing mechanism includes a powder dispensing motor and is communicatively connected to the main controller.

[0034] Two pressure sensors are provided. The pressure sensors are connected to the main controller and are arranged at intervals along the powder feeding pipeline.

[0035] The pulse generator is connected to the main controller and is used to inject pressure pulses into the powder feeding pipeline.

[0036] The adaptive anti-blocking control algorithm is as follows: Based on the deviation between the real-time gas flow rate value Q_actual and the target flow rate value Q_set, the speed setpoint of the powder delivery motor is dynamically adjusted through PID calculation, so that the powder delivery rate M_actual satisfies the relationship: M_actual = M_set + K * (Q_set - Q_actual), where M_set is the target powder delivery rate and K is a negative proportional coefficient. The refining time T_new = M_total / M_actual is recalculated based on the total powder delivery amount M_total. The PID calculation in the adaptive anti-blocking control algorithm is as follows: The flow deviation e(t) = Q_set - Q_actual is calculated, and the adjustment amount u(t) of the speed setpoint of the powder delivery motor is: u(t) = K_p * e(t) + K_i * ∫e(t) dt + K_d * de(t) / dt, where K_p, K_i, and K_d are preset control parameters, and are tuned online through a linkage control algorithm. The main controller also integrates a purging sub-algorithm, which works as follows: when it is detected that Q_actual has recovered to the normal range [Q_set-ΔQ, Q_set+ΔQ], the purging timer is triggered. During the purging time T_purge, the set value of the powder discharge motor speed u(t) is locked to the current value. After T_purge ends, the lock is released and normal PID calculation is resumed.

[0037] The pulse diagnostic analysis algorithm is as follows: a pressure pulse is injected into the pipeline, and the response signals of at least two pressure sensors are collected. The propagation time difference Δt and amplitude attenuation rate ΔA between the signals are calculated and compared with a preset health baseline threshold to achieve a dust blockage risk assessment. The amplitude attenuation rate ΔA in the pulse diagnostic analysis algorithm is calculated as follows: ΔA = 20 * log10 (A2 / A1), where A1 is the amplitude of the pulse signal received by the pressure sensor closer to the pulse generator, and A2 is the amplitude of the pulse signal received by the pressure sensor farther from the pulse generator. The main controller also integrates a dust blockage location sub-algorithm, which calculates the actual propagation speed of the pulse according to the formula v_actual = L / Δt, where L is the distance between the two pressure sensors. By comparing v_actual with the baseline speed v_base of the unobstructed pipeline, the approximate location of the dust blockage point is calculated using a pre-stored propagation speed-powder density relationship model.

[0038] The linkage control algorithm is as follows: the output of the pulse diagnostic analysis algorithm is used as the feedforward input of the adaptive anti-blocking control algorithm to adjust its PID parameters or flow deviation threshold; the linkage control algorithm is specifically as follows: when the risk level output by the pulse diagnostic analysis algorithm exceeds the preset level, the flow deviation threshold that triggers intervention in the adaptive anti-blocking control algorithm is automatically reduced, that is, the ΔQ value is reduced to improve the system sensitivity.

[0039] The system collects the refining gas flow rate value Q_actual in real time through a gas flow sensor and compares it with the preset target flow rate value Q_set. It calculates the instantaneous flow deviation e(t) = Q_set - Q_actual. This deviation reflects the change in the powder conveying state in the pipeline: when Q_actual is lower than Q_set, it indicates that the gas flow rate is insufficient, which may be due to increased pipeline resistance caused by powder accumulation, and there is a risk of blockage. Conversely, if Q_actual is too high, it may mean that too little powder is conveyed and the gas has not been able to carry the powder sufficiently.

[0040] Based on this deviation, the algorithm dynamically adjusts the speed setpoint of the powder discharging motor through a PID controller. The control quantity u(t) consists of three terms: proportional, integral, and derivative: u(t) = K_p*e(t) + K_i*∫e(t)dt + K_d*de(t) / dt, where K_p, K_i, and K_d are preset control parameters that determine the system's response strength to the current deviation, the cumulative correction of historical deviations, and the pre-adjustment of the deviation change trend, respectively. The proportional term K_p*e(t) provides instant correction and rapid response to flow changes, the integral term K_i*∫e(t)dt eliminates steady-state error and ensures long-term accuracy, and the derivative term K_d*de(t) / dt suppresses overshoot and enhances system stability. Through this PID calculation, the system calculates the speed adjustment of the powder discharging motor in real time and sends it to the driver of the powder discharging mechanism for execution.

[0041] While adjusting the speed of the powder delivery motor, the algorithm also recalculates the refining time based on the real-time powder delivery rate M_actual. The relationship between M_actual and the target powder delivery rate M_set is: M_actual = M_set + K * (Q_set - Q_actual), where K is a negative proportionality coefficient to ensure that the powder delivery rate is appropriately reduced when the gas flow rate is low. The total powder delivery amount M_total is the preset process target. Therefore, the refining time is updated to T_new = M_total / M_actual. This dynamic time adjustment ensures that the total powder delivery task can still be accurately completed during the anti-blocking intervention process, avoiding insufficient powder delivery or process time loss due to speed adjustment.

[0042] In this application, at the start of the diagnosis, the main controller triggers the pulse generator to inject a short-duration, high-pressure pulse signal into the powder feeding pipeline. The pulse propagates along the pipeline and is collected by two pressure sensors arranged at intervals along the pipeline. The sensor closer to the pulse generator is denoted as Sensor1, and the received signal amplitude is A1. The sensor farther away from the pulse generator is denoted as Sensor2, and the received signal amplitude is A2. The system synchronously collects the response signals of the two sensors and performs filtering, amplification, and digital processing.

[0043] The core of signal processing is to calculate the pulse propagation time difference Δt and amplitude attenuation rate ΔA. The propagation time difference Δt is obtained through cross-correlation analysis or peak detection, that is, to calculate the time delay of the pulse propagating from Sensor1 to Sensor2. In a smooth pipeline, the pulse propagation speed is determined by the gas sound speed and powder concentration, and Δt is relatively stable. When the pipeline is partially blocked, the blockage point will change the pulse propagation path or the medium density, resulting in an increase in propagation time and a significant increase in Δt. The amplitude attenuation rate ΔA is calculated by the formula ΔA=20*log10(A2 / A1), which reflects the loss of pulse energy during propagation. In a healthy pipeline, attenuation is mainly caused by gas damping and powder scattering, and the attenuation rate is within a certain range. If there is a blockage in the pipeline, especially a dense accumulation, the pulse will encounter stronger reflection and absorption, resulting in an abnormal increase in ΔA.

[0044] Based on Δt and ΔA, the algorithm assesses the risk of toner congestion. By using preset health baseline thresholds, including Δt_max (maximum allowable time difference) and ΔA_max (maximum allowable decay rate), the measured Δt and ΔA are compared with the thresholds: if both are below the threshold, it is assessed as "low risk"; if either indicator exceeds the threshold, it is assessed as "medium risk"; if both significantly exceed the threshold, it is assessed as "high risk". The risk assessment results are output to the main controller in real time to trigger early warnings or linkage control.

[0045] During normal system operation, the adaptive anti-blocking control algorithm works independently based on gas flow deviation to maintain powder output rate regulation. The pulse diagnostic analysis algorithm performs an active diagnosis once according to a preset cycle or trigger condition and outputs the current powder blockage risk level of the pipeline, including three levels: "low risk", "medium risk" and "high risk". The linkage control algorithm receives the risk level in real time and adjusts the parameters of the adaptive anti-blocking control algorithm according to the predefined strategy.

[0046] When the pulse diagnostic analysis algorithm outputs "low risk," it indicates that the pipeline is unobstructed. The adaptive anti-blocking control algorithm maintains the original parameters and its trigger intervention flow deviation threshold is the default value ΔQ_normal. The system operates with standard sensitivity. When it outputs "medium risk," it indicates that there are early signs of powder aggregation in the pipeline. The linkage control algorithm automatically reduces the flow deviation threshold of the adaptive anti-blocking control algorithm, that is, reduces the ΔQ value, for example, from ΔQ_normal to 0.7*ΔQ_normal. The adaptive anti-blocking control algorithm becomes more sensitive to flow deviation. Even a small decrease in flow will trigger a stronger powder discharge speed regulation intervention, thereby more actively suppressing the blockage trend. The linkage algorithm can also fine-tune the PID parameters, such as appropriately increasing the proportional coefficient K_p, to make the speed regulation response faster.

[0047] When the output is "high risk", it indicates that there is a serious risk of blockage in the pipeline or that a partial blockage has occurred. The linkage control algorithm takes enhanced measures. On the one hand, it further reduces the flow deviation threshold to 0.5*ΔQ_normal, so that the system enters a high-sensitivity state. On the other hand, it adjusts the PID parameters, such as increasing the integral coefficient K_i to accelerate the elimination of steady-state deviation, and may introduce a feedforward compensation term to directly calculate an additional speed adjustment based on the risk level. In addition, the linkage algorithm can also trigger the preparatory command of the purging sub-algorithm. Once the flow recovery is detected, the extended purging time is immediately started to ensure that the blockage is completely removed.

[0048] The powder blockage location algorithm is used to estimate the location of the blockage point when an anomaly is detected. The actual pulse propagation speed is calculated according to the formula v_actual=L / Δt, where L is the distance between the two sensors. Then, v_actual is compared with the reference speed v_base of the unobstructed pipeline. The system has a pre-stored propagation speed-powder density relationship model, which was obtained through experimental calibration and describes the variation law of pulse propagation speed under different powder packing densities. Through inversion calculation, that is, using the deviation between v_actual and v_base, combined with the model, the approximate powder density increase area at the blockage point is inferred, and then the relative position of the blockage point between the two sensors is determined. For example, if v_actual is significantly lower than v_base, it indicates that there is high density packing in the middle section of the pipeline. The location algorithm can output the approximate distance of the blockage point from Sensor1. The pulse diagnosis and analysis algorithm realizes early diagnosis and accurate location of pipeline blockage through active pulse injection and signal analysis.

[0049] In addition, the algorithm integrates a purging sub-algorithm. When it is detected that Q_actual has recovered to the normal range [Q_set-ΔQ, Q_set+ΔQ], the purging timer is started. Within the preset purging time T_purge, the setpoint value u(t) of the powder discharge motor speed is locked at the current value. This locking mechanism prevents the system from oscillating due to frequent adjustments in PID calculations when it has just recovered, ensuring that the gas-solid two-phase flow in the pipeline reaches a stable state. After T_purge ends, the lock is released, and the system resumes normal PID calculations. The entire adaptive anti-clogging control algorithm forms a closed loop, and the prevention of pipeline blockage is achieved through real-time feedback adjustment, reducing the incidence of powder blockage.

[0050] A method for preventing and clearing blockages in a refining machine includes the following steps:

[0051] S1, based on the deviation between the real-time detected refining gas flow rate Q_actual and the target flow rate Q_set, the speed of the powder delivery motor is dynamically adjusted through a control algorithm so that the actual powder delivery rate M_actual follows the change of the target powder delivery rate M_set. More specifically in S1, the flow deviation e(t) = Q_set - Q_actual is calculated, and a PID controller is used to calculate the adjustment amount u(t) of the powder delivery motor speed based on the flow deviation e(t), where u(t) = K_p*e(t) + K_i*∫e(t)dt + K_d*de(t) / dt, K_p, K_i, and K_d are control parameters. The relationship between the actual powder delivery rate M_actual and the target powder delivery rate M_set satisfies: M_actual = M_set + K*(Q_set - Q_actual). Furthermore, the refining time is recalculated based on the real-time powder delivery rate.

[0052] S2, During system operation, a pressure pulse is injected into the powder feeding pipeline, and the response signals of at least two pressure sensors arranged along the pipeline are collected. By analyzing the response signals, the propagation time difference Δt and amplitude attenuation characteristics of the pulse are calculated to assess the risk of pipeline blockage.

[0053] S3 takes the risk assessment results output from S2 as feedforward input and dynamically adjusts the control parameters or operating logic in S1.

[0054] This method first uses real-time gas flow rate as feedback and dynamically adjusts the speed of the powder delivery motor through a PID algorithm to adaptively match the changes in gas flow rate, maintaining the stability of the gas-solid two-phase flow. Simultaneously, pressure pulses are periodically injected into the pipeline. By analyzing the time difference and amplitude attenuation characteristics of the pulse propagation, the risk of local blockage in the pipeline is identified and the blockage point is located in the early stage. Finally, the risk level diagnosed by the pulse is used as a feedforward signal to dynamically adjust the sensitivity threshold of the flow control and the PID parameters to achieve regulation. When the system detects the flow recovery, it automatically triggers the purging stabilization program. This method forms a synergistic mechanism of "real-time feedback to suppress disturbances, active diagnosis and early warning of risks, and feedforward linkage to optimize response", which improves the robustness and anti-blockage efficiency of the system.

[0055] This application, by analyzing the propagation characteristics of pressure pulses, can identify the risk and approximate location of local blockages in the early stages before the gas flow rate in the pipeline has significantly decreased. This overcomes the lag of traditional single flow threshold alarms and realizes proactive fault warning. By using the qualitative risk assessment results of pulse diagnosis as a feedforward signal to dynamically adjust the sensitivity threshold and control parameters of the adaptive PID controller, the core control loop has the ability to self-perceive risks and self-optimize strategies, enhancing the system's adaptability to complex operating conditions and the forward-looking nature of control. Through the deep integration of three-level mechanisms, the system can not only quickly suppress existing disturbances but also intervene in potential blockage trends in advance. Combined with automated purging and recovery procedures, it fundamentally reduces the frequency of unplanned shutdowns, ensures the continuity of refining operations and process stability, thereby improving overall production efficiency and equipment reliability.

[0056] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A refining machine powder blockage monitoring system, characterized in that, include: The main controller integrates an adaptive anti-blocking control algorithm, a pulse diagnosis and analysis algorithm, and a linkage control algorithm. A gas flow sensor is communicatively connected to the main controller and is used to detect the refining gas flow value Q_actual in real time. A powder dispensing mechanism, which includes a powder dispensing motor, is communicatively connected to the main controller; Two pressure sensors are provided, which are communicatively connected to the main controller and are spaced apart along the powder feeding pipeline. A pulse generator, which is communicatively connected to the main controller, is used to inject pressure pulses into the powder feeding pipeline; The adaptive anti-clogging control algorithm is as follows: based on the deviation between the real-time gas flow rate value Q_actual and the target flow rate value Q_set, the speed setting value of the powder delivery motor is dynamically adjusted through PID calculation so that the powder delivery rate M_actual satisfies the relationship: M_actual=M_set+K*(Q_set-Q_actual), where M_set is the target powder delivery rate and K is a negative proportionality coefficient, and the refining time T_new=M_total / M_actual is recalculated based on the total powder delivery amount M_total; The pulse diagnostic analysis algorithm is as follows: a pressure pulse is injected into the pipeline, and the response signals of at least two pressure sensors are collected. The propagation time difference Δt and amplitude attenuation rate ΔA between the signals are calculated and compared with a preset health baseline threshold to achieve a dust blockage risk assessment. The linkage control algorithm is as follows: the output of the pulse diagnostic analysis algorithm is used as the feedforward input of the adaptive anti-blocking control algorithm, and its PID parameters or flow deviation threshold are adjusted.

2. The refining machine powder blockage monitoring system according to claim 1, characterized in that, The PID operation in the adaptive anti-blocking control algorithm is as follows: calculate the flow deviation e(t) = Q_set - Q_actual, and the adjustment amount u(t) of the powder discharge motor speed setpoint is: u(t) = K_p*e(t) + K_i*∫e(t)dt + K_d*de(t) / dt, where K_p, K_i, and K_d are preset control parameters, and are tuned online through the linkage control algorithm.

3. The refining machine powder blockage monitoring system according to claim 1, characterized in that, The main controller also integrates a purging sub-algorithm, which is as follows: when it is detected that Q_actual has recovered to the normal range [Q_set-ΔQ, Q_set+ΔQ], the purging timer is triggered. During the purging time T_purge, the speed setting value u(t) of the powder discharge motor is locked to the current value. After T_purge ends, the lock is released and the normal PID operation is restored.

4. The refining machine powder blockage monitoring system according to claim 1, characterized in that, The amplitude attenuation rate ΔA in the pulse diagnostic analysis algorithm is calculated as follows: ΔA = 20 * log10 (A2 / A1), where A1 is the amplitude of the pulse signal received by the pressure sensor close to the pulse generator, and A2 is the amplitude of the pulse signal received by the pressure sensor far from the pulse generator. The main controller also integrates a powder blockage location algorithm, which is as follows: calculate the actual pulse propagation speed according to the formula v_actual=L / Δt, where L is the distance between the two pressure sensors, compare v_actual with the reference speed v_base of the unobstructed pipeline, and use the pre-stored propagation speed-powder density relationship model to inversely calculate the approximate location of the powder blockage point.

5. The refining machine powder blockage monitoring system according to claim 1, characterized in that, The linkage control algorithm specifically involves: when the risk level output by the pulse diagnostic analysis algorithm exceeds the preset level, automatically reducing the flow deviation threshold that triggers intervention in the adaptive anti-blocking control algorithm, i.e., reducing the ΔQ value and improving system sensitivity.

6. A method for preventing and clearing blockages in a refining machine, characterized in that, a refining machine powder blockage monitoring system according to any one of claims 1-5, is characterized in that, Includes the following steps: S1, based on the deviation between the real-time detected refining gas flow rate value Q_actual and the target flow rate value Q_set, the speed of the powder delivery motor is dynamically adjusted through the control algorithm so that the actual powder delivery rate M_actual follows the change of the target powder delivery rate M_set. S2, During the operation of the system, a pressure pulse is injected into the powder feeding pipeline, and the response signals of at least two pressure sensors arranged along the pipeline are collected. By analyzing the response signals, the propagation time difference Δt and amplitude attenuation characteristics of the pulse are calculated to assess the risk of pipeline blockage. S3 takes the risk assessment results output from S2 as feedforward input and dynamically adjusts the control parameters or operating logic in S1.

7. The method for preventing and clearing blockages in a refining machine according to claim 6, characterized in that, In S1, more specifically, the flow deviation e(t) = Q_set - Q_actual is calculated. A PID controller is used to calculate the adjustment amount u(t) of the powder discharge motor speed based on the flow deviation e(t), where u(t) = K_p*e(t) + K_i*∫e(t)dt + K_d*de(t) / dt, K_p, K_i, and K_d are control parameters. The relationship between the actual powder delivery rate M_actual and the target powder delivery rate M_set satisfies: M_actual = M_set + K*(Q_set - Q_actual). Furthermore, the refining time is recalculated based on the real-time powder delivery rate.

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