Screening efficiency online monitoring method, device and system based on vibrating screen

Abstract

The invention discloses a screening efficiency online monitoring method, device and system based on a vibrating screen, and relates to the technical field of vibrating screen efficiency monitoring, and the screening efficiency online monitoring method comprises the following steps: collecting working parameter data of the vibrating screen in real time through a sensor arranged on the vibrating screen; the accuracy and stability of screening efficiency are improved by monitoring key parameters such as humidity, particle size distribution and vibration frequency in real time and combining a screening effect model and a dynamic correction algorithm. The system automatically adjusts equipment parameters, equipment overload or screen damage is avoided, the material passing rate is optimized, and production losses are reduced. Meanwhile, manual intervention is reduced through an automatic control mechanism, the automation level of a production line is improved, human errors are reduced, the equipment fault and shutdown time is shortened, the production efficiency is improved, and the service life of the equipment is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of vibrating screen efficiency monitoring, and in particular to a vibrating screen-based screening efficiency online monitoring method, device and system. Background Art

[0002] Online monitoring of screening efficiency based on vibrating screens refers to evaluating the screening efficiency of vibrating screens by real-time monitoring and analyzing parameters such as the working status, material flow, and particle size distribution of vibrating screens, and automatically obtaining the material passing rate, separation effect, and screening accuracy during the screening process through data acquisition systems, sensors, image recognition, or other intelligent technologies. This monitoring method can reflect the operating status of the screening equipment in real time during the production process, detect abnormalities or reduced efficiency in a timely manner, and then optimize operation and maintenance, ensure screening quality, and improve production efficiency. Online monitoring technology not only improves the automation level of the screening process, but also provides a basis for production decisions, reduces manual intervention, and improves work efficiency and resource utilization.

[0003] The prior art has the following deficiencies:

[0004] During the screening process of the vibrating screen, the particle size distribution and humidity changes of the material will directly affect the screening effect and pass rate, and the existing online monitoring systems usually rely on sensors or image recognition to analyze these parameters in real time. However, when dealing with materials with high moisture content or large differences in particle size, changes in humidity or particle size may cause serious deviations in sensor readings. For example, materials with too high humidity may not pass through the screen easily due to increased cohesiveness, causing the monitoring system to misjudge the screening efficiency and show a lower screening effect, which in turn prompts the operator to increase the screening intensity or change the screen setting, which may cause the equipment to be overloaded or the screen to be damaged. If this interference problem is not identified and handled in a timely manner, it may lead to reduced production efficiency, shortened equipment life, and even production accidents.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide a method, device and system for online monitoring of screening efficiency based on a vibrating screen, which improves the accuracy and stability of screening efficiency by real-time monitoring of key parameters such as humidity, particle size distribution, vibration frequency, etc., and combining screening effect models and dynamic correction algorithms. The system automatically adjusts equipment parameters to avoid equipment overload or screen damage, optimizes material pass rate, and reduces production losses. At the same time, the automated control mechanism reduces manual intervention, improves the automation level of the production line, reduces human errors, reduces equipment failures and downtime, and improves production efficiency and equipment life to solve the problems in the above-mentioned background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: an online monitoring method for screening efficiency based on a vibrating screen, comprising the following steps:

[0008] The working parameter data of the vibrating screen is collected in real time through the sensors installed on the vibrating screen;

[0009] According to the collected vibrating screen working parameters, the current screening efficiency is evaluated using the known screening effect model to obtain a preliminary value of the screening efficiency;

[0010] Monitor the humidity and particle size changes of materials in real time, use humidity sensors and particle size analyzers to identify changes in materials during screening due to excessive humidity and particle size differences, and make corrections to the screening efficiency assessment in a timely manner;

[0011] According to the data of humidity and particle size changes, the dynamic compensation algorithm is used to correct the screening efficiency evaluation results to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective;

[0012] Based on the corrected screening efficiency value, it is fed back to the control system of the vibrating screen to automatically adjust the screening parameters to optimize the screening effect and ensure production efficiency and stable operation of the equipment.

[0013] Preferably, the specific steps of collecting the working parameter data of the vibrating screen in real time by means of a sensor arranged on the vibrating screen are as follows:

[0014] First, select the sensor that meets the requirements according to the working environment and collection requirements of the vibrating screen;

[0015] After the sensor is installed, start the data acquisition system to collect various working parameter data in real time;

[0016] The raw data collected by the sensors needs to be processed and analyzed.

[0017] Preferably, according to the collected vibrating screen working parameters, the current screening efficiency is evaluated using a known screening effect model to obtain a preliminary value of the screening efficiency. The specific steps are as follows:

[0018] Integrate the raw data collected from various sensors;

[0019] According to historical experimental data, the corresponding screening effect model is used to evaluate the screening efficiency;

[0020] After the screening effect model is established, the collected real-time data is input into the model to conduct a preliminary evaluation of the screening efficiency;

[0021] Based on the preliminary evaluation of the screening efficiency values, further analysis and suggestions for optimizing the screening efficiency are proposed.

[0022] Preferably, the humidity and particle size changes of the material are monitored in real time, and the changes of the material caused by excessive humidity and particle size differences during the screening process are identified by using a humidity sensor and a particle size analyzer, so as to make corrections to the screening efficiency evaluation in a timely manner. The specific steps are as follows:

[0023] Collect material moisture and particle size data in real time through humidity sensors and particle size analyzers;

[0024] After data collection and preprocessing, moisture and particle size data are fed into the established sieving effectiveness model;

[0025] Based on the real-time monitored moisture and particle size data, the screening efficiency assessment will be dynamically revised;

[0026] The screening efficiency is corrected and updated, and the new evaluation results are fed back to the vibrating screen control system for real-time adjustments.

[0027] Preferably, according to the data of humidity and particle size changes, a dynamic compensation algorithm is used to correct the screening efficiency evaluation results to obtain an accurate screening efficiency value, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective. The specific steps are as follows:

[0028] Before starting dynamic compensation, the humidity and particle size data are preprocessed. First, real-time data is collected through humidity sensors and particle size analyzers. These data need to be standardized to eliminate data deviations and dimensional differences between different sensors. The goal of data preprocessing is to convert humidity and particle size data into a unified quantitative standard to provide consistent data input for the compensation algorithm. The calculation expression is as follows:

[0029]

[0030] , where H normis the standardized humidity value, H is the real-time humidity value, and H min and H max is the minimum and maximum value of humidity data, P norm is the standardized particle size distribution value, P is the real-time particle size distribution value, and P min and P max are the minimum and maximum values ​​of the granularity data;

[0031] Based on the existing screening effect model, the standardized humidity value H norm And the standardized particle size distribution value P norm The influence on screening efficiency is quantified and the calculation expression is as follows:

[0032]

[0033] , where E corr is the corrected screening efficiency, E base is the uncorrected screening efficiency, α is the moisture correction factor, β is the particle size correction factor, γ is the moisture square correction factor, and δ is the particle size square correction factor;

[0034] In the actual operation process, the humidity and particle size of the material will change, affecting the screening efficiency. Therefore, the core of the dynamic compensation algorithm is to calculate the correction effect of humidity and particle size changes on the screening efficiency in real time, and update the screening efficiency value in time. In order to achieve this goal, a dynamic compensation factor is introduced. This factor adjusts the initial screening efficiency according to the real-time humidity and particle size changes. The calculation expression is as follows:

[0035] ΔE corr (t) = E corr (t)-E base (t) = E base (t)·(α·ΔH(t)+β·ΔP(t))

[0036] , where ΔE corr (t) is the corrected screening efficiency E at time point t corr The change in (t) represents the difference between the corrected screening efficiency and the uncorrected screening efficiency E at time point t. base (t), ΔH(t) is the change in humidity from the reference value at time point t, and ΔP(t) is the change in particle size from the reference value at time point t;

[0037] The screening efficiency correction value obtained by the dynamic compensation algorithm finally outputs an accurate screening efficiency value, which reflects the actual efficiency of the current screening process under the influence of humidity and particle size changes. At the same time, the accurate screening efficiency value is fed back to the control system of the screening equipment to adjust the screening parameters to optimize the screening process. The feedback mechanism ensures that the screening strategy can be adjusted according to real-time data during equipment operation, thereby improving the overall screening effect and production efficiency. The calculation expression is as follows:

[0038]

[0039] , where E final It is the precise screening efficiency value, which has been corrected by dynamic compensation.

[0040] Preferably, by calculating the accurate screening efficiency value E final The deviation between the target screening efficiency and the screening efficiency can be used to judge the shortcomings of the current screening state. If the accurate screening efficiency value E final If the value is greater than the target screening efficiency, the adjustment mechanism will be activated to optimize the screening process. The calculation expression is as follows:

[0041] ΔE=E target -E final

[0042] , where ΔE is the screening efficiency deviation value, E final is the exact screening efficiency value, E final is the target screening efficiency;

[0043] According to the deviation value ΔE, the screening parameters are automatically adjusted, including the vibration frequency f vib , sieve aperture d screen and material feed rate Q in , the calculation expression is as follows:

[0044] f vib (t) = f vib,0 +k f ΔE,

[0046] d screen (t) = d screen,0 +k d ΔE,

[0048] Q in (t) = Q in,0 +κ Q ΔE

[0049] , where f vib (t) is the adjusted vibration frequency, f vib,0is the initial vibration frequency, which indicates the default operating frequency of the vibrating screen without adjustment, κ f is the adjustment coefficient of the vibration frequency, which indicates the sensitivity of the screening efficiency deviation value ΔE to the vibration frequency adjustment, d screen (t) is the adjusted sieve aperture, d screen,0 is the initial mesh aperture, which indicates the default mesh aperture of the vibrating screen without adjustment, κ d It is the adjustment coefficient of the screen aperture, which indicates the influence of the screening efficiency deviation value ΔE on the adjustment of the screen aperture. in (t) is the adjusted material feed rate, Q in,0 is the initial material feed rate, indicating the default feed rate during the screening process, κ Q It is the adjustment coefficient of material feed rate, which indicates the adjustment response degree of screening efficiency deviation value ΔE to material feed rate;

[0050] After adjusting the screening parameters, the precise screening efficiency value E is monitored in real time. final , and evaluate whether the screening effect reaches the expected goal. If the precise screening efficiency value E final If the value is still less than the target value, the screening parameters are adjusted according to the deviation to form a closed-loop control. By continuously optimizing the screening parameters, the screening process is always in the best state. The calculation expression is as follows:

[0051] In the formula, F final (t) is the final accurate screening efficiency value at time point t, E base (t) is the uncorrected screening efficiency E at time point t base (t), H norm (t) is the standardized humidity value at time point t, P norm (t) is the normalized particle size distribution value at time point t, α is the humidity correction factor, β is the particle size correction factor, γ is the humidity square correction factor, and δ is the particle size square correction factor;

[0052] Dynamically monitor the screening quality and the operating status of the equipment during the screening process to ensure that the equipment is operating in a stable state and the screening quality meets the standards while adjusting the screening parameters. Combined with the equipment's operating health status, the equipment's operating status is judged. If the equipment status is abnormal, the screening process is automatically suspended, self-repair is performed, an early warning is issued, and the adjustment strategy of the screening parameters is re-evaluated. The calculation expression is as follows:

[0053] S health (t) = f(T screen ,A vib ,I motor ,ΔE)

[0054] , where Shealth (t) is the equipment health index, which evaluates the operating status of the equipment. Tscreen is the screen temperature, which indicates the workload of the equipment. A vib is the vibration amplitude, indicating the vibration state of the screen, I motor is the motor current, which indicates the motor load.

[0055] An online monitoring system for screening efficiency based on a vibrating screen includes a data acquisition module, a screening efficiency evaluation module, a material change monitoring module, a dynamic compensation module and a control feedback module:

[0056] The data acquisition module collects the working parameter data of the vibrating screen in real time through sensors arranged on the vibrating screen;

[0057] The screening efficiency evaluation module evaluates the current screening efficiency based on the collected vibrating screen working parameters and uses the known screening effect model to obtain a preliminary value of the screening efficiency;

[0058] The material change monitoring module monitors the humidity and particle size changes of the material in real time. It uses humidity sensors and particle size analysis devices to identify changes in the material during the screening process due to excessive humidity and particle size differences, and makes timely corrections to the screening efficiency assessment.

[0059] The dynamic compensation module uses a dynamic compensation algorithm to correct the screening efficiency evaluation results based on the data of humidity and particle size changes to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective;

[0060] The control feedback module feeds back the corrected screening efficiency value to the control system of the vibrating screen and automatically adjusts the screening parameters to optimize the screening effect and ensure production efficiency and stable operation of the equipment.

[0061] A vibrating screen-based screening efficiency online monitoring device comprises a vibrating screen-based screening efficiency online monitoring system.

[0062] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0063] The present invention can significantly improve the accuracy and stability of screening efficiency by real-time monitoring of key parameters such as humidity, particle size distribution, and vibration frequency, and combining the screening effect model and dynamic correction algorithm. In traditional screening efficiency monitoring, changes in humidity and particle size often lead to monitoring deviations, which in turn affect the operating status of the equipment. By collecting data in real time, the system can accurately evaluate the screening efficiency, promptly identify influencing factors such as excessive humidity or uneven particle size, and automatically adjust equipment parameters based on these data, thereby avoiding production stagnation caused by equipment overload or screen damage. In this way, the system ensures efficient and stable screening effects, optimizes material pass rate, improves overall production efficiency, and reduces equipment failures and production losses caused by uneven screening.

[0064] The present invention reduces human intervention and improves the automation level of the production line through an automated control mechanism. In the traditional production process, operators rely on experience to judge changes in humidity and particle size and manually adjust equipment parameters, which is not only inefficient but also prone to errors. With the help of real-time data analysis and automatic correction, the system can automatically optimize the working state of the screening equipment based on the real-time collected data, such as adjusting the vibration frequency of the screen or the feed amount. The operator only needs to check the system suggestions, which reduces human intervention and improves operational accuracy and production efficiency. This automated improvement makes the production process more efficient and reliable, reduces human errors, equipment failures and downtime, thereby improving the efficiency of the overall production line and the service life of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0066] Figure 1 The present invention is a method flow chart of an online monitoring method of screening efficiency based on a vibrating screen.

[0067] Figure 2 The module schematic diagram of an online monitoring system for screening efficiency based on a vibrating screen of the present invention. DETAILED DESCRIPTION

[0068] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0069] The present invention provides Figure 1The online monitoring method of screening efficiency based on a vibrating screen shown in the figure comprises the following steps:

[0070] The working parameter data of the vibrating screen is collected in real time through the sensors installed on the vibrating screen;

[0071] The specific steps for collecting the working parameter data of the vibrating screen in real time through the sensors installed on the vibrating screen are as follows:

[0072] First, select the sensor that meets the requirements according to the working environment and collection requirements of the vibrating screen;

[0073] These devices usually include particle size analysis sensors, humidity sensors, vibration sensors and flow meters. Particle size analysis sensors are used to detect the size and distribution of material particles in real time, humidity sensors are used to monitor the humidity changes of materials, and vibration sensors are used to record the vibration frequency, amplitude and stability of the screen. By installing sensors at key locations of the vibrating screen (such as the screen surface and the feed end), it is possible to ensure that data of different parameters are collected comprehensively and accurately. The selection and installation location of each sensor should be optimized according to the material characteristics, screening tasks and equipment working environment to avoid interference and signal attenuation.

[0074] After the sensor is installed, start the data acquisition system to collect various working parameter data in real time;

[0075] The particle size sensor will frequently scan the material and output real-time particle size distribution data according to the size and shape of the material particles; the humidity sensor will detect the humidity change of the material and transmit the humidity value in real time in the form of a digital signal; the vibration sensor will record the operating frequency and amplitude of the vibrating screen and analyze the dynamic response of the screen. The flow meter can accurately obtain the amount and flow of materials passing through the screen. These signals are sent to the central data acquisition system through wireless transmission or wired network, and the system stores and processes the data according to the acquisition frequency (usually real-time or periodic). The key point in this process is to ensure that the signal transmission process is stable and reliable to avoid data loss or errors due to communication delays or signal interference.

[0076] The raw data collected by the sensors needs to be processed and analyzed;

[0077] In the data preprocessing stage, the collected signals are cleaned through denoising, filtering and other technologies to remove the influence of environmental noise, instrument errors, etc., to ensure the accuracy of the data. For example, the data of the humidity sensor may be affected by temperature fluctuations, the signal of the particle size sensor may be disturbed by the collision between particles, and the signal of the vibration sensor may generate noise due to the irregular vibration mode. The processed data will be preliminarily analyzed by the algorithm model to generate the particle size distribution curve, humidity change trend chart, vibration frequency curve, etc., to provide basic information and provide reference for the subsequent screening efficiency analysis and optimization control. This step is very critical because it determines the accuracy of the subsequent screening efficiency evaluation and equipment adjustment.

[0078] According to the collected vibrating screen working parameters, the current screening efficiency is evaluated using the known screening effect model to obtain a preliminary value of the screening efficiency;

[0079] According to the collected vibrating screen working parameters, the current screening efficiency is evaluated using the known screening effect model to obtain the preliminary value of the screening efficiency. The specific steps are as follows:

[0080] Integrate the raw data collected from each sensor (including material particle size distribution, humidity change, vibration frequency of the screen, and the passing rate of the material through the screen);

[0081] The data collected by each sensor may be different in format and time dimension, so it is necessary to synchronize and unify these data. For example, the particle size sensor will generate real-time data on particle size, the humidity sensor will give the humidity value of the material, and the vibration sensor will provide information on vibration frequency and amplitude. These data need to be aligned according to the acquisition timestamp to ensure that the screening parameters at the same time point can correspond. In addition, by smoothing the data, short-term noise and outliers are removed to ensure the accuracy of the data entering the next step.

[0082] According to historical experimental data, the corresponding screening effect model is used to evaluate the screening efficiency;

[0083] The screening effect model usually involves a mathematical description of screening theory (such as screen aperture, screen type, screening speed, material properties, etc.). Common models include Markov models, hierarchical models, or empirical formulas established through regression analysis. In this step, parameters such as particle size distribution, humidity change, and vibration frequency obtained from the sensor are used as inputs, combined with the design parameters and working conditions of the screen, to establish a mathematical expression for screening efficiency. Through this model, the screening efficiency under different working conditions can be predicted. For example, if the humidity of the material is high, the screening efficiency will usually decrease, and when the particle size distribution is large, the screening effect may also be affected. The accuracy and effectiveness of the model are crucial to the reliability of subsequent results, so the material characteristics and the working conditions of the screening equipment need to be fully considered when designing the screening effect model.

[0084] After the screening effect model is established, the collected real-time data is input into the model to conduct a preliminary evaluation of the screening efficiency;

[0085] Based on factors such as the particle size distribution, humidity changes, and vibration frequency of the material, the model will calculate a preliminary value of the screening efficiency in the current screening process. For example, when the vibration frequency is high, the material may pass through the screen more easily, but if the humidity is too high, it may cause the material to adhere to the screen, reducing the screening efficiency. Materials with larger particle sizes may also cause the screen to block, affecting the pass rate. Therefore, based on these input parameters, the model will output a preliminary value of the screening efficiency, which represents the overall effect of the current screening process. This preliminary evaluation value is a rough estimate of the screening efficiency and provides a basis for subsequent optimization and adjustment.

[0086] Based on the preliminary evaluation of the screening efficiency value, further analysis and suggestions for optimizing the screening efficiency are made;

[0087] Compare the preliminary evaluation value with the target screening efficiency to analyze whether the current screening process has achieved the expected results. If the evaluation value is low, it may be necessary to adjust the vibration frequency of the screen, increase or decrease the screen aperture, adjust the material input, or take other measures to optimize the screening effect. For example, if high humidity affects the screening efficiency, it may be recommended to adjust the vibration frequency or introduce dehumidification equipment; if the particle size distribution is uneven, it may be necessary to adjust the screen angle or use screens of different specifications. These optimization suggestions not only help operators understand the problems in the current screening process, but also provide specific adjustment directions to ensure that the screening efficiency is effectively improved.

[0088] Monitor the humidity and particle size changes of materials in real time, use humidity sensors and particle size analyzers to identify changes in materials during screening due to excessive humidity and particle size differences, and make corrections to the screening efficiency assessment in a timely manner;

[0089] Monitor the humidity and particle size changes of the material in real time. Use humidity sensors and particle size analyzers to identify changes in the material during the screening process due to excessive humidity and particle size differences, and make corrections to the screening efficiency assessment in a timely manner. The specific steps are as follows:

[0090] Collect material moisture and particle size data in real time through humidity sensors and particle size analyzers;

[0091] The humidity sensor measures the moisture content on the surface of the material, captures the humidity change trend, and transmits the data in real time; the particle size analyzer obtains the particle size distribution information of the material particles through technologies such as laser scattering, image recognition or resistance method. These data need to be preprocessed after collection, including removing abnormal data and noise interference to ensure the accuracy of the data. After data preprocessing, the humidity and particle size data will enter the data analysis link to ensure that the model calculation and screening efficiency evaluation are based on high-quality data. The key to this stage is to ensure that the collected data can accurately and timely reflect the actual situation of the material.

[0092] After data collection and preprocessing, moisture and particle size data are fed into the established sieving effectiveness model;

[0093] The screening effect model is usually calculated based on the particle size distribution of the material, humidity changes, and the working parameters of the screen (such as vibration frequency, screen aperture, etc.). The model estimates the efficiency of the current screening process based on different material characteristics and their impact on screening efficiency. For example, too high humidity may cause the material to stick to the screen, resulting in a decrease in the pass rate; while too large a difference in particle size may prevent small particles from passing through the screen effectively, while large particles may cause the screen to be blocked. By combining humidity and particle size information, the model will give a preliminary screening efficiency assessment value, reflecting the working status and material distribution of the current screening process.

[0094] Based on the real-time monitored moisture and particle size data, the screening efficiency assessment will be dynamically revised;

[0095] When there are large fluctuations in humidity or particle size, the system will automatically adjust the model's input parameters and correct the initial screening efficiency assessment value. For example, when the humidity sensor detects that the material humidity exceeds the set threshold, the system will correct the screening effect, assuming that the screening efficiency of wet materials is reduced, and then adjust the vibration frequency or screen vibration mode to reduce the negative impact of wet materials on the screening effect. Similarly, when there are large differences in particle size distribution, the system may adjust the screen aperture or feed rate to optimize the screening effect. This step ensures that the screening efficiency assessment always matches the actual working status by adjusting the model input in real time, avoiding errors caused by humidity or particle size fluctuations.

[0096] The screening efficiency is corrected and updated, and the new evaluation results are fed back to the vibrating screen control system for real-time adjustment;

[0097] In actual production, this feedback control can optimize the screening effect by automatically adjusting the parameters of the vibrating screen. For example, if the evaluation results show that the screening efficiency is low, the humidity is high or the particle size difference is large, the system may recommend reducing the vibration frequency or increasing the discharge angle of the screen, or adjusting the feed amount to avoid too much material clogging the screen. At the same time, these correction results will be fed back to the operator through the display interface to help them understand the screening status and perform manual or automatic intervention. This link not only helps to adjust the screening efficiency in time, but also effectively avoids overload or damage to the equipment due to improper operation, and improves production stability and equipment life.

[0098] According to the data of humidity and particle size changes, the dynamic compensation algorithm is used to correct the screening efficiency evaluation results to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective;

[0099] According to the data of humidity and particle size changes, the dynamic compensation algorithm is used to correct the screening efficiency evaluation results to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective. The specific steps are as follows:

[0100] Before starting dynamic compensation, the humidity and particle size data are preprocessed. First, real-time data is collected through humidity sensors and particle size analyzers. These data need to be standardized to eliminate data deviations and dimensional differences between different sensors. The goal of data preprocessing is to convert humidity and particle size data into a unified quantitative standard to provide consistent data input for the compensation algorithm. The calculation expression is as follows:

[0101]

[0102] , where H norm is the standardized humidity value, H is the real-time humidity value, and H min and H max is the minimum and maximum value of humidity data, P norm is the standardized particle size distribution value, P is the real-time particle size distribution value, and P min and P max are the minimum and maximum values ​​of the granularity data;

[0103] This standardization process ensures that data from different sources are processed at a unified scale, eliminating dimensionality effects and providing more accurate input for subsequent algorithms.

[0104] Based on the existing screening effect model, the standardized humidity value H norm And the standardized particle size distribution value P norm The influence on screening efficiency is quantified and the calculation expression is as follows:

[0105]

[0106] , where E corr is the corrected screening efficiency, E base is the uncorrected screening efficiency, α is the moisture correction factor, β is the particle size correction factor, γ is the moisture square correction factor, and δ is the particle size square correction factor;

[0107] The humidity correction coefficient α, particle size correction coefficient β, humidity square correction coefficient γ and particle size square correction coefficient δ play a role in adjusting and correcting the screening effect in the screening efficiency evaluation, ensuring that the model can accurately reflect the screening performance of materials under different humidity and particle size conditions. The humidity correction coefficient α is used to quantify the linear effect of humidity changes on screening efficiency. Increased humidity usually causes material adhesion, thereby reducing screening efficiency. α controls the direct effect of humidity on efficiency; the particle size correction coefficient β reflects the effect of changes in particle size distribution on screening efficiency. Too large or too small particles may cause the screen to be blocked or not fully screened. β adjusts the degree of influence of particle size on efficiency. The humidity square correction coefficient γ and the particle size square correction coefficient δ are used to capture the nonlinear effects of humidity and particle size on screening efficiency, especially when humidity or particle size changes extremely. These coefficients help the model more accurately reflect the extent of the decrease in screening efficiency when humidity increases or particle size differences increase.

[0108] A humidity and particle size influence model was established to provide a dynamic correction factor for screening efficiency evaluation and solve the impact of excessive humidity and uneven particle size on screening effect.

[0109] In the actual operation process, the humidity and particle size of the material will change, affecting the screening efficiency. Therefore, the core of the dynamic compensation algorithm is to calculate the correction effect of humidity and particle size changes on the screening efficiency in real time, and update the screening efficiency value in time. In order to achieve this goal, a dynamic compensation factor is introduced. This factor adjusts the initial screening efficiency according to the real-time humidity and particle size changes. The calculation expression is as follows:

[0110] ΔE corr (t) = E corr (t)-E base (t) = E base (t)·(α·ΔH(t)+β·ΔP(t))

[0111] , where ΔE corr (t) is the corrected screening efficiency E at time point t corrThe change in (t) represents the difference between the corrected screening efficiency and the uncorrected screening efficiency E at time point t. base The change in (t) reflects the deviation of the screening efficiency due to the change in humidity and particle size. ΔH(t) is the change in humidity from the reference value at time point t, and ΔP(t) is the change in particle size from the reference value at time point t.

[0112] The screening efficiency is dynamically compensated based on the real-time changes in humidity and particle size. Through continuous monitoring and calculation, the screening efficiency assessment is always accurate.

[0113] The screening efficiency correction value obtained by the dynamic compensation algorithm finally outputs an accurate screening efficiency value, which reflects the actual efficiency of the current screening process under the influence of humidity and particle size changes. At the same time, the accurate screening efficiency value is fed back to the control system of the screening equipment to adjust the screening parameters to optimize the screening process. The feedback mechanism ensures that the screening strategy can be adjusted according to real-time data during equipment operation, thereby improving the overall screening effect and production efficiency. The calculation expression is as follows:

[0114]

[0115] , where E final It is the precise screening efficiency value, which has been corrected by dynamic compensation;

[0116] Accurate screening efficiency values ​​are used to control and optimize the screening process in real time, ensuring that the system can maintain efficient and stable screening performance under complex material conditions.

[0117] Based on the corrected screening efficiency value, the system is fed back to the vibrating screen control system to automatically adjust the screening parameters to optimize the screening effect and ensure production efficiency and stable operation of the equipment.

[0118] Based on the corrected screening efficiency value, the control system of the vibrating screen is fed back to automatically adjust the screening parameters to optimize the screening effect. The specific steps are as follows:

[0119] By calculating the accurate screening efficiency value E final The deviation between the target screening efficiency and the screening efficiency can be used to judge the shortcomings of the current screening state. If the accurate screening efficiency value E final If the value is greater than the target screening efficiency, the adjustment mechanism will be activated to optimize the screening process. The calculation expression is as follows:

[0120] ΔE=E target -E final

[0121] , where ΔE is the screening efficiency deviation value, E final is the exact screening efficiency value, E final is the target screening efficiency;

[0122] According to the deviation value ΔE, the screening parameters are automatically adjusted, including the vibration frequency f vib , sieve aperture d screen and material feed rate Q in These adjustments help maximize screening efficiency and maintain the stability of equipment operation. The adjustment of parameters is positively correlated with the deviation value of screening efficiency. The system will dynamically optimize the screening process based on real-time data. The calculation expression is as follows:

[0123] f vib (t) = f vib,0 +k f ΔE,

[0125] d screen (t) = d screen,0 +k d ΔE,

[0127] Q in (t) = Q in,0 +κ Q ΔE

[0128] , where f vib (t) is the adjusted vibration frequency, f vib,0 is the initial vibration frequency, which indicates the default operating frequency of the vibrating screen without adjustment, κ f is the adjustment coefficient of the vibration frequency, which indicates the sensitivity of the screening efficiency deviation value ΔE to the vibration frequency adjustment, d screen (t) is the adjusted sieve aperture, d screen,0 is the initial mesh aperture, which indicates the default mesh aperture of the vibrating screen without adjustment, κ d It is the adjustment coefficient of the screen aperture, which indicates the influence of the screening efficiency deviation value ΔE on the adjustment of the screen aperture. in (t) is the adjusted material feed rate, Q in,0 is the initial material feed rate, indicating the default feed rate during the screening process, κ Q It is the adjustment coefficient of material feed rate, which indicates the adjustment response degree of screening efficiency deviation value ΔE to material feed rate;

[0129] After adjusting the screening parameters, the precise screening efficiency value E is monitored in real time. final , and evaluate whether the screening effect reaches the expected goal. If the precise screening efficiency value E final If the value is still less than the target value, the screening parameters are adjusted according to the deviation to form a closed-loop control. By continuously optimizing the screening parameters, the screening process is always in the best state. The calculation expression is as follows:

[0130] In the formula, F final (t) is the final accurate screening efficiency value at time point t, E base (t) is the uncorrected screening efficiency E at time point t base (t), H norm (t) is the standardized humidity value at time point t, P norm (t) is the normalized particle size distribution value at time point t, α is the humidity correction factor, β is the particle size correction factor, γ is the humidity square correction factor, and δ is the particle size square correction factor;

[0131] Dynamically monitor the screening quality and the operating status of the equipment during the screening process to ensure that the equipment is operating stably and the screening quality meets the standards while adjusting the screening parameters. Combine the equipment's operating health status, such as the temperature, vibration amplitude, and current load of the vibrating screen, to determine the equipment's operating status. If the equipment is abnormal, the screening process will be automatically suspended, self-repair will be performed, an early warning will be issued, and the adjustment strategy of the screening parameters will be re-evaluated. The calculation expression is as follows:

[0132] S health (t) = f(T screen ,A vib ,I motor ,ΔE)

[0133] , where S health (t) is the equipment health index, which evaluates the operating status of the equipment, T screen is the screen temperature, indicating the workload of the equipment, A vib is the vibration amplitude, indicating the vibration state of the screen, I motor is the motor current, indicating the motor load;

[0134] Equipment Health Index S health (t) Combined with the deviation of screening efficiency, if the equipment health index S health (t) If the value is lower than the set threshold, the system will trigger equipment maintenance or adjustment measures.

[0135] Implementation method 1: Sensor-based data collection and real-time monitoring system

[0136] In this implementation, we deploy a series of sensors at key locations of the vibrating screen to monitor and collect various working parameters of the material in real time. The main sensors include humidity sensors, particle size analyzers, vibration sensors, and pass rate sensors. Through these sensors, the operating status of the vibrating screen during the screening process can be fully and accurately reflected, and accurate data support can be provided for subsequent screening efficiency evaluation.

[0137] First, humidity sensors are installed at the feed end and screening area of ​​the vibrating screen to monitor the humidity changes of the material in real time. The humidity of the material directly affects its ability to pass through the screen. Too high humidity will cause the material to stick together and reduce the screening efficiency. Therefore, the data collected by the humidity sensor can help understand the humidity fluctuations of the material in real time and promptly identify the impact of humidity changes on the screening effect. The selection of humidity sensors needs to ensure its accuracy and response speed to ensure that accurate humidity data can be collected at the moment when the humidity of the material changes.

[0138] The deployment of particle size analyzers is mainly to obtain the particle size distribution data of materials. The difference in particle size of materials will have a significant impact on the screening effect. Materials with larger particles are difficult to pass through the screen, while materials with smaller particles are easy to pass through, resulting in uneven screening effect. Therefore, the particle size analyzer needs to monitor the particle size distribution of the material in real time, capture the trend of particle size changes, and transmit this data to the central control system. The particle size analyzer can perform real-time analysis through technologies such as laser scattering, image recognition or resistance method. Selecting the appropriate particle size analysis method can ensure the accuracy and real-time nature of the data.

[0139] Vibration sensors are used to monitor the vibration frequency and amplitude of the screen. The vibration frequency directly affects the efficiency and effect of screening. If the vibration frequency is too high, the material may pass through the screen too quickly and cannot be fully separated; if the vibration frequency is too low, the material may stay on the surface of the screen and cause blockage. Therefore, monitoring the vibration state of the screen through vibration sensors and adjusting the vibration parameters in time can avoid excessive or insufficient vibration frequency leading to low screening efficiency.

[0140] Finally, the pass rate sensor is used to monitor the actual proportion of materials passing through the screen. Through this sensor, the amount of material passing through the screen and the screening accuracy can be obtained in real time. These data are crucial for the evaluation of screening efficiency. The sensor transmits all real-time data to the central control unit, which will integrate and process these data, conduct a preliminary evaluation of screening efficiency, and provide a basis for subsequent corrections and optimizations.

[0141] In terms of system architecture and data communication, by adopting industrial-grade Internet of Things (IoT) communication technology, all sensor data will be transmitted to the central data processing platform in real time. These sensors can transmit data wirelessly (such as Wi-Fi, ZigBee or LoRa, etc.), or connect to the data acquisition module through wires, and realize data aggregation and real-time processing through PLC controllers or industrial computers. These data will enter the data analysis module, and through data modeling, analyze the comprehensive impact of factors such as humidity, particle size, vibration, etc. on screening efficiency.

[0142] Ultimately, the real-time monitoring system uses this data to provide operators with accurate material screening status to ensure that screening efficiency remains within the optimal range. The system also generates alarms or prompts to help operators adjust screening parameters or equipment settings in a timely manner to ensure that the production line operates efficiently and stably under different working conditions.

[0143] Implementation method 2: Screening effect model and real-time correction mechanism

[0144] The core of this implementation method is to use the established screening effect model and combine it with the real-time collected data to evaluate and correct the screening efficiency through a dynamic correction algorithm. The parameters such as humidity, particle size, vibration frequency, etc. collected by the sensor are input into the preset screening effect mathematical model for calculation, thereby obtaining a preliminary screening efficiency value.

[0145] The construction of the screening effect model is the key. The model needs to comprehensively consider the moisture content of the material, the particle size distribution, the working parameters of the screen (such as vibration frequency, screen aperture, screen material, etc.) and the performance of the equipment itself. Common screening effect models include models based on classification theory, regression analysis models or prediction models based on machine learning. These models usually need to be trained based on a large amount of experimental data to ensure that they can accurately reflect the screening effects under different materials and working conditions. Specifically, the screening effect model will combine the moisture content and particle size data of the material, consider the possible adhesion of wet materials, and the impact of particle size differences on the screening effect, so as to calculate the estimated value of the screening efficiency.

[0146] Once the preliminary screening efficiency value is obtained, the next step is to make real-time corrections through a dynamic correction algorithm. This process adjusts the parameters of the model based on changes in real-time data to reflect changes in the actual screening process. For example, when the humidity sensor detects that the material humidity is too high, the model will automatically increase the viscosity coefficient of the material and adjust the screening efficiency prediction value; when the particle size distribution fluctuates greatly, the model will correct the estimated values ​​of the pass rate and screening efficiency based on the difference in particle size distribution. These dynamic corrections will help the system identify problems in the screening process in a timely manner and provide correction suggestions to operators.

[0147] The advantage of the dynamic correction algorithm lies in its efficiency and flexibility. In this process, the model can not only adapt to the fluctuations of material moisture and particle size, but also combine the control parameters such as screen vibration frequency and screen aperture to achieve multi-factor linkage correction. Through this real-time correction mechanism, the evaluation of screening efficiency can more accurately reflect the actual production conditions and avoid distortion of screening effect caused by material changes.

[0148] Finally, the corrected screening efficiency value will be transmitted to the equipment control system, and the system will automatically adjust the working parameters of the screen based on this new evaluation value, such as vibration frequency, screen aperture or feed speed. This mechanism can effectively avoid fluctuations in screening effect caused by changes in humidity and particle size, and ensure that the vibrating screen maintains an efficient and stable working state under complex working conditions.

[0149] Implementation method 3: Feedback control and automatic optimization adjustment

[0150] The focus of this implementation is to automatically optimize the working parameters of the vibrating screen through real-time screening efficiency feedback control to ensure that the screening process is always kept in the best state. Through the data such as material moisture, particle size and screening efficiency collected by the sensor, the system can automatically adjust the parameters such as the vibration frequency, screen aperture and feed speed of the screen to optimize the screening effect in real time.

[0151] The feedback control mechanism is the core of this implementation. Under this mechanism, the real-time screening efficiency evaluation results will be transmitted to the control system through the data processing module. The control system will automatically adjust the working state of the screening machine according to the deviation between the current screening efficiency value and the target screening efficiency. Assuming that the system detects that the screening efficiency has dropped and the reason may be too high humidity or too large particle size difference, the control system will automatically adjust the vibration frequency or feed amount of the screen to reduce the risk of material blocking the screen, or adjust the angle of the screen to make it more suitable for the current material conditions.

[0152] When the humidity is high, the screening efficiency of wet materials usually decreases. At this time, the system will reduce the contact time between the material and the screen by adjusting the vibration frequency to reduce the adhesion of wet materials. If the particle size difference is large, the system may automatically adjust the screen aperture or change the material input speed to ensure a balanced screening effect. The implementation of automated control can adjust the screening parameters in time under real-time changing production conditions to avoid equipment overload due to improper operation.

[0153] Operator interaction and optimization suggestions are also an important part of this implementation. The operator can view the screening efficiency evaluation results and equipment status in real time through the interface, and the system will also provide optimization suggestions to help the operator decide whether manual intervention is needed. The system can reduce the need for manual intervention through adaptive algorithms, while ensuring that operators can understand the working status of the equipment in a timely manner and make necessary adjustments based on the information provided by the system.

[0154] Through this automatic optimization and adjustment mechanism, the production line can not only improve screening efficiency, but also effectively reduce equipment failure rate. Automated adjustment avoids human error intervention, allowing the production line to operate in an efficient and stable state, extending the service life of the equipment and improving overall production efficiency.

[0155] The present invention can significantly improve the accuracy and stability of screening efficiency by real-time monitoring of key parameters such as humidity, particle size distribution, and vibration frequency, and combining the screening effect model and dynamic correction algorithm. In traditional screening efficiency monitoring, changes in humidity and particle size often lead to monitoring deviations, which in turn affect the operating status of the equipment. By collecting data in real time, the system can accurately evaluate the screening efficiency, promptly identify influencing factors such as excessive humidity or uneven particle size, and automatically adjust equipment parameters based on these data, thereby avoiding production stagnation caused by equipment overload or screen damage. In this way, the system ensures efficient and stable screening effects, optimizes material pass rate, improves overall production efficiency, and reduces equipment failures and production losses caused by uneven screening.

[0156] The present invention reduces human intervention and improves the automation level of the production line through an automated control mechanism. In the traditional production process, operators rely on experience to judge changes in humidity and particle size and manually adjust equipment parameters, which is not only inefficient but also prone to errors. With the help of real-time data analysis and automatic correction, the system can automatically optimize the working state of the screening equipment based on the real-time collected data, such as adjusting the vibration frequency of the screen or the feed amount. The operator only needs to check the system suggestions, which reduces human intervention and improves operational accuracy and production efficiency. This automated improvement makes the production process more efficient and reliable, reduces human errors, equipment failures and downtime, thereby improving the efficiency of the overall production line and the service life of the equipment.

[0157] The present invention provides Figure 2 The online monitoring system for screening efficiency based on a vibrating screen shown in the figure includes a data acquisition module, a screening efficiency evaluation module, a material change monitoring module, a dynamic compensation module and a control feedback module:

[0158] The data acquisition module collects the working parameter data of the vibrating screen in real time through sensors arranged on the vibrating screen;

[0159] The screening efficiency evaluation module evaluates the current screening efficiency based on the collected vibrating screen working parameters and uses the known screening effect model to obtain a preliminary value of the screening efficiency;

[0160] The material change monitoring module monitors the humidity and particle size changes of the material in real time. It uses humidity sensors and particle size analysis devices to identify changes in the material during the screening process due to excessive humidity and particle size differences, and makes timely corrections to the screening efficiency assessment.

[0161] The dynamic compensation module uses a dynamic compensation algorithm to correct the screening efficiency evaluation results based on the data of humidity and particle size changes to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective;

[0162] The control feedback module feeds back the corrected screening efficiency value to the control system of the vibrating screen and automatically adjusts the screening parameters to optimize the screening effect and ensure production efficiency and stable operation of the equipment.

[0163] An online monitoring method for screening efficiency based on a vibrating screen provided in an embodiment of the present invention is realized by the above-mentioned online monitoring system for screening efficiency based on a vibrating screen. The specific method and process of an online monitoring system for screening efficiency based on a vibrating screen are detailed in the embodiment of the above-mentioned online monitoring method for screening efficiency based on a vibrating screen, which will not be repeated here.

[0164] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for online monitoring of screening efficiency based on a vibrating screen, characterized in that: The following steps are involved: The working parameter data of the vibrating screen is collected in real time through the sensors installed on the vibrating screen; According to the collected vibrating screen working parameters, the current screening efficiency is evaluated using the known screening effect model to obtain a preliminary value of the screening efficiency; Monitor the humidity and particle size changes of materials in real time, use humidity sensors and particle size analyzers to identify changes in materials during screening due to excessive humidity and particle size differences, and make corrections to the screening efficiency assessment in a timely manner; According to the data of humidity and particle size changes, the dynamic compensation algorithm is used to correct the screening efficiency evaluation results to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective; Based on the corrected screening efficiency value, it is fed back to the control system of the vibrating screen to automatically adjust the screening parameters to optimize the screening effect and ensure production efficiency and stable operation of the equipment.

2. The method for online monitoring of screening efficiency based on a vibrating screen according to claim 1, characterized in that: The specific steps for collecting the working parameter data of the vibrating screen in real time through the sensors installed on the vibrating screen are as follows: First, select the sensor that meets the requirements according to the working environment and collection requirements of the vibrating screen; After the sensor is installed, start the data acquisition system to collect various working parameter data in real time; The raw data collected by the sensors needs to be processed and analyzed.

3. The method for online monitoring of screening efficiency based on a vibrating screen according to claim 1, characterized in that: According to the collected vibrating screen working parameters, the current screening efficiency is evaluated using the known screening effect model to obtain the preliminary value of the screening efficiency. The specific steps are as follows: Integrate the raw data collected from various sensors; According to historical experimental data, the corresponding screening effect model is used to evaluate the screening efficiency; After the screening effect model is established, the collected real-time data is input into the model to conduct a preliminary evaluation of the screening efficiency; Based on the preliminary evaluation of the screening efficiency values, further analysis and suggestions for optimizing the screening efficiency are proposed.

4. The method for online monitoring of screening efficiency based on a vibrating screen according to claim 1, characterized in that: Monitor the humidity and particle size changes of the material in real time. Use humidity sensors and particle size analyzers to identify changes in the material during the screening process due to excessive humidity and particle size differences, and make corrections to the screening efficiency assessment in a timely manner. The specific steps are as follows: Collect material moisture and particle size data in real time through humidity sensors and particle size analyzers; After data collection and preprocessing, moisture and particle size data are fed into the established sieving effectiveness model; Based on the real-time monitored moisture and particle size data, the screening efficiency assessment will be dynamically revised; The screening efficiency is corrected and updated, and the new evaluation results are fed back to the vibrating screen control system for real-time adjustments.

5. The method for online monitoring of screening efficiency based on a vibrating screen according to claim 1, characterized in that: According to the data of humidity and particle size changes, the dynamic compensation algorithm is used to correct the screening efficiency evaluation results to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective. The specific steps are as follows: Before starting dynamic compensation, the humidity and particle size data are preprocessed. First, real-time data is collected through humidity sensors and particle size analyzers. These data need to be standardized to eliminate data deviations and dimensional differences between different sensors. The goal of data preprocessing is to convert humidity and particle size data into a unified quantitative standard to provide consistent data input for the compensation algorithm. The calculation expression is as follows: ， In the formula, H norm is the standardized humidity value, H is the real-time humidity value, and H min and H max is the minimum and maximum value of humidity data, P norm is the standardized particle size distribution value, P is the real-time particle size distribution value, and P min and P max are the minimum and maximum values ​​of the granularity data; Based on the existing screening effect model, the standardized humidity value H norm And the standardized particle size distribution value P norm The influence on screening efficiency is quantified and the calculation expression is as follows: ， In the formula, E corr is the corrected screening efficiency, E base is the uncorrected screening efficiency, α is the moisture correction factor, β is the particle size correction factor, γ is the moisture square correction factor, and δ is the particle size square correction factor; In the actual operation process, the humidity and particle size of the material will change, affecting the screening efficiency. Therefore, the core of the dynamic compensation algorithm is to calculate the correction effect of humidity and particle size changes on the screening efficiency in real time, and update the screening efficiency value in time. In order to achieve this goal, a dynamic compensation factor is introduced. This factor adjusts the initial screening efficiency according to the real-time humidity and particle size changes. The calculation expression is as follows: ΔE corr (t)=E corr (t)-E base (t)=E base (t)·(α·ΔH(t)+β·ΔP(t)), Where ΔE corr (t) is the corrected screening efficiency E at time point t corr The change in (t) represents the difference between the corrected screening efficiency and the uncorrected screening efficiency E at time point t. base (t), ΔH(t) is the change in humidity from the reference value at time point t, and ΔP(t) is the change in particle size from the reference value at time point t; The screening efficiency correction value obtained by the dynamic compensation algorithm finally outputs an accurate screening efficiency value, which reflects the actual efficiency of the current screening process under the influence of humidity and particle size changes. At the same time, the accurate screening efficiency value is fed back to the control system of the screening equipment to adjust the screening parameters to optimize the screening process. The feedback mechanism ensures that the screening strategy can be adjusted according to real-time data during equipment operation, thereby improving the overall screening effect and production efficiency. The calculation expression is as follows: ， In the formula, E final It is the precise screening efficiency value, which has been corrected by dynamic compensation.

6. The method for online monitoring of screening efficiency based on a vibrating screen according to claim 1, characterized in that: By calculating the accurate screening efficiency value E final The deviation between the target screening efficiency and the screening efficiency can be used to judge the shortcomings of the current screening state. If the accurate screening efficiency value E final If the value is greater than the target screening efficiency, the adjustment mechanism will be activated to optimize the screening process. The calculation expression is as follows: ΔE=E target -E final , Where ΔE is the screening efficiency deviation value, E final is the exact screening efficiency value, E final is the target screening efficiency; According to the deviation value ΔE, the screening parameters are automatically adjusted, including the vibration frequency f vib , sieve aperture d screen and material feed rate Q in , the calculation expression is as follows: f vib (t)=f vib,0 +κ f ·ΔE, d screen (t)=d screen,0 +k d ·D.E., Q in (t)=Q in,0 +κ Q ·ΔE, In the formula, f vib (t) is the adjusted vibration frequency, f vib,0 is the initial vibration frequency, which indicates the default operating frequency of the vibrating screen without adjustment, κ f is the adjustment coefficient of the vibration frequency, which indicates the sensitivity of the screening efficiency deviation value ΔE to the vibration frequency adjustment, d screen (t) is the adjusted sieve aperture, d screen,0 is the initial mesh size, which means the default mesh size of the vibrating screen without adjustment, k d It is the adjustment coefficient of the screen aperture, which indicates the influence of the screening efficiency deviation value ΔE on the adjustment of the screen aperture. in (t) is the adjusted material feed rate, Q in,0 is the initial material feed rate, indicating the default feed rate during the screening process, κ Q It is the adjustment coefficient of material feed rate, which indicates the adjustment response degree of screening efficiency deviation value ΔE to material feed rate; After adjusting the screening parameters, the precise screening efficiency value E is monitored in real time. final , and evaluate whether the screening effect reaches the expected goal. If the precise screening efficiency value E final If the value is still less than the target value, the screening parameters are adjusted according to the deviation to form a closed-loop control. By continuously optimizing the screening parameters, the screening process is always in the best state. The calculation expression is as follows: In the formula, F final (t) is the final accurate screening efficiency value at time point t, E base (t) is the uncorrected screening efficiency E at time point t base (t), H norm (t) is the standardized humidity value at time point t, P norm (t) is the normalized particle size distribution value at time point t, α is the humidity correction factor, β is the particle size correction factor, γ is the humidity square correction factor, and δ is the particle size square correction factor; Dynamically monitor the screening quality and the operating status of the equipment during the screening process to ensure that the equipment is operating in a stable state and the screening quality meets the standards while adjusting the screening parameters. Combined with the equipment's operating health status, the equipment's operating status is judged. If the equipment status is abnormal, the screening process is automatically suspended, self-repair is performed, an early warning is issued, and the adjustment strategy of the screening parameters is re-evaluated. The calculation expression is as follows: S health (t)=f(T screen ,A vib ,I motor ,ΔE), In the formula, S health (t) is the equipment health index, which evaluates the operating status of the equipment, T screen is the screen temperature, indicating the workload of the equipment, A vib is the vibration amplitude, indicating the vibration state of the screen, I motor is the motor current, which indicates the motor load.

7. An online monitoring system for screening efficiency based on a vibrating screen, used to implement an online monitoring method for screening efficiency based on a vibrating screen as described in any one of claims 1 to 6, characterized in that: Including data acquisition module, screening efficiency evaluation module, material change monitoring module, dynamic compensation module and control feedback module: The data acquisition module collects the working parameter data of the vibrating screen in real time through sensors arranged on the vibrating screen; The screening efficiency evaluation module evaluates the current screening efficiency based on the collected vibrating screen working parameters and uses the known screening effect model to obtain a preliminary value of the screening efficiency; The material change monitoring module monitors the humidity and particle size changes of the material in real time. It uses humidity sensors and particle size analysis devices to identify changes in the material during the screening process due to excessive humidity and particle size differences, and makes timely corrections to the screening efficiency assessment. The dynamic compensation module uses a dynamic compensation algorithm to correct the screening efficiency evaluation results based on the data of humidity and particle size changes to obtain accurate screening efficiency values, avoid interference caused by excessive material humidity and uneven particle size, and ensure that the screening efficiency data output by the system is accurate and effective; The control feedback module feeds back the corrected screening efficiency value to the control system of the vibrating screen and automatically adjusts the screening parameters to optimize the screening effect and ensure production efficiency and stable operation of the equipment.

8. An online monitoring device for screening efficiency based on a vibrating screen, comprising the online monitoring system for screening efficiency based on a vibrating screen as claimed in claim 7.

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