Graded closed-loop dust removal linkage control method for discharging of ultrafine grinder

Abstract

The invention relates to the technical field of linkage control, and discloses a grading closed-loop dust removal linkage control method for discharging of an ultrafine grinder, which comprises the following steps: extracting a discharging state signal of the ultrafine grinder during discharging to obtain particle characteristic parameters of the ultrafine grinder; based on the particle characteristic parameters, performing particle size grading analysis on the material to obtain a grading result; adjusting operation parameters according to the particle concentration and particle size distribution of the materials in the grading result; based on the discharging state signal and the grading result, linkage control is conducted on a dust removal module; obtaining an effect feedback signal of the dust removal module and a discharge quality feedback signal of the adjusted ultrafine grinder, and performing data fusion on the effect feedback signal and the discharge quality feedback signal to obtain initial adjustment feedback data; according to the primary adjustment feedback data, re-optimizing the adjustment process of the ultrafine grinder in the step S4 to obtain a compliant material; according to the invention, the efficiency of hierarchical closed-loop dust removal linkage control can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of linkage control, and in particular to a grading closed-loop dust removal linkage control method for discharging of a super-micro pulverizer. BACKGROUND

[0002] The prior art has significant deficiencies in the basic data processing and grading analysis link of the discharging control of the super-micro pulverizer. After collecting the discharging state signal, noise removal processing is not performed, and the original data containing noise is directly used to extract the particle characteristic parameters, which leads to poor accuracy of the particle concentration and size distribution indicators, and cannot provide reliable data support for subsequent grading analysis. When grading particles, the grading index is not calculated by a standardization formula combined with the concentration and size evaluation results, but is determined by a single threshold value or subjective judgment, which makes it difficult to accurately reflect the actual particle characteristics of the material, and the pulverizer operating parameters adjusted based on the grading results do not match the material requirements, which easily leads to uneven particle size, yield fluctuations and other problems, and seriously affects the discharging quality.

[0003] The prior art has prominent defects in the dust removal linkage control and closed-loop optimization link. In linkage control, the particle concentration trend in the discharging state signal is not analyzed to evaluate the dynamic load, and the dust removal intensity level is not determined according to the grading results, but only the dust removal module is started and stopped or the power is adjusted according to a fixed mode, which leads to a mismatch between the dust removal intensity and the actual dust production of the material, resulting in incomplete dust removal and environmental pollution, or excessive dust removal and increased energy consumption. At the same time, there is a lack of systematic fusion processing of the feedback signals of the dust removal effect and the discharging quality, and the comprehensive feedback data is not generated by time alignment and weighted fusion, but only the equipment is adjusted according to a single feedback indicator, which cannot fully grasp the equipment operating state. Moreover, there is no re-optimization mechanism based on the feedback data, which cannot finely optimize the adjustment process of the pulverizer and the dust removal module, and cannot continuously produce compliant materials, resulting in low linkage control efficiency and stability. SUMMARY

[0004] The present application provides a grading closed-loop dust removal linkage control method for discharging of a super-micro pulverizer to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides a grading closed-loop dust removal linkage control method for discharging of a super-micro pulverizer, comprising: S1, extracting a discharging state signal of a super-micro pulverizer during discharging to obtain particle characteristic parameters of the super-micro pulverizer; S2, based on the particle characteristic parameters, performing particle size grading analysis on the material to obtain grading results of the material; S3, adjusting the operating parameters of the super-micro pulverizer according to the particle concentration and particle size distribution of the material in the grading results; S4, linkage control of the dust removal module based on the discharging state signal and the grading result; S5, obtaining the effect feedback signal of the dust removal module and the discharging quality feedback signal of the ultrafine grinder after adjustment, data fusion of the effect feedback signal and the discharging quality feedback signal to obtain the initial adjustment feedback data of the ultrafine grinder; S6, re-optimization of the adjustment process of the ultrafine grinder in S4 according to the initial adjustment feedback data to obtain the compliant material of the ultrafine grinder.

[0006] In a preferred embodiment, the discharging state signal of the extraction ultrafine grinder during discharging obtains the particle characteristic parameters of the ultrafine grinder, including: Real-time acquisition of the discharging state signal of the ultrafine grinder to obtain the original monitoring signal of the ultrafine grinder; Removing noise points in the original monitoring signal to obtain the purified discharging state signal of the ultrafine grinder; Extracting the particle concentration index and particle size distribution index related to the material in the purified discharging state signal to obtain the particle characteristic parameters of the ultrafine grinder.

[0007] In a preferred embodiment, the particle size grading analysis of the material based on the particle characteristic parameters to obtain the grading result of the material, including: Comparing the particle concentration index in the grading result with the preset concentration threshold to obtain the concentration evaluation result of the material; Comparing the preliminary grading judgment in the grading result with the preset size threshold to obtain the size evaluation result of the material; Based on the concentration evaluation result and the size evaluation result, the grading result of the material is determined.

[0008] In a preferred embodiment, the calculation formula of the grading result is as follows: ; In the formula, is the grading index corresponding to the grading result, is the preset concentration coefficient, is the quantized value of the concentration evaluation result, is the preset size coefficient, is the quantized value of the size evaluation result.

[0009] In a preferred embodiment, the adjustment of the operating parameters of the ultrafine grinder according to the particle concentration and particle size distribution of the material in the grading result, including: generate an adjustment instruction for the feeding rate of the ultrafine grinder based on the grade information of the particle concentration in the classification result; generate an adjustment instruction for the grinding rotation speed of the ultrafine grinder based on the uniformity information of the particle size distribution in the classification result; synchronously adjust the feeding rate and the grinding rotation speed according to the adjustment instruction to obtain adjusted operation parameters.

[0010] In a preferred embodiment, the linkage control of the dust removal module based on the discharge state signal and the classification result comprises: analyze the real-time particle concentration change trend in the discharge state signal to obtain a dynamic load evaluation of the material; determine the dust removal intensity level required by the material according to the particle distribution uniformity level in the classification result; match a target control mode from preset linkage control modes based on the dynamic load evaluation and the dust removal intensity level; generate start-stop instructions and power adjustment instructions for the dust removal module according to the target control mode, and simultaneously start the linkage control process of the dust removal module according to the start-stop instructions and the power adjustment instructions.

[0011] In a preferred embodiment, the obtaining of the effect feedback signal of the dust removal module and the discharge quality feedback signal of the ultrafine grinder after adjustment, and the data fusion of the effect feedback signal and the discharge quality feedback signal to obtain the initial adjustment feedback data of the ultrafine grinder, comprises: generate the effect feedback signal of the dust removal module according to the dust removal state data of the exhaust particle concentration and the airflow resistance of the dust removal module; generate the discharge quality feedback signal of the ultrafine grinder after adjustment according to the quality state data of the material's discharge particle uniformity and yield rate; perform time alignment processing on the dust removal state data and the quality state data to obtain a synchronous feedback data set of the ultrafine grinder; perform weighted fusion processing on the synchronous feedback data set to obtain the initial adjustment feedback data of the ultrafine grinder.

[0012] In a preferred embodiment, the weighted fusion processing on the synchronous feedback data set to obtain the initial adjustment feedback data of the ultrafine grinder comprises: extract the exhaust particle concentration index, the airflow resistance index, the material particle uniformity index, and the yield rate index from the synchronous feedback data set; The exhaust particle concentration index, the airflow resistance index, the material particle uniformity index and the yield rate index are weighted and fused to obtain a fusion index value of the ultrafine grinder, wherein a calculation formula of the fusion index value is as follows: ; In the formula, is the fusion index value, is a particle concentration coefficient calibrated based on historical data, is the exhaust particle concentration index, is an airflow resistance coefficient calibrated based on historical data, is the airflow resistance index, is a particle uniformity coefficient calibrated based on historical data, is the material particle uniformity index, is a yield rate coefficient calibrated based on historical data, is the yield rate index. The fusion index value is compared with a preset threshold to obtain a fusion evaluation result of the synchronous feedback data set, and initial adjustment feedback data of the ultrafine grinder is generated according to the fusion evaluation result.

[0013] In a preferred embodiment, the adjustment process of the ultrafine grinder in S4 is re-optimized according to the initial adjustment feedback data to obtain compliant material of the ultrafine grinder, comprising: Analyzing the initial adjustment feedback data to obtain a comprehensive performance evaluation level and a to-be-optimized parameter identifier; Based on the comprehensive performance evaluation level, a target optimization strategy is selected from a preset optimization strategy library; According to the to-be-optimized parameter identifier and the target optimization strategy, a fine adjustment instruction for the feeding rate and the crushing rotating speed of the ultrafine grinder is obtained; The fine adjustment instruction is executed, and the particle characteristics of the output material are monitored. When the particle characteristics continuously remain within a preset compliance range, it is determined that the ultrafine grinder obtains compliant material.

[0014] In a preferred embodiment, the fine adjustment instruction is executed, and the particle characteristics of the output material are monitored. When the particle characteristics continuously remain within a preset compliance range, it is determined that the ultrafine grinder obtains compliant material, comprising: According to the fine adjustment instruction, the operating state of the ultrafine grinder is adjusted; The particle characteristics of the material output by the ultrafine grinder after the operating state is adjusted are monitored in real time to obtain particle characteristic monitoring data of the ultrafine grinder; Compare the particle characteristic monitoring data with a preset compliance range to obtain a compliance judgment result of the material; When the compliance judgment result indicates that the particle characteristics are continuously within the preset compliance range, the material is determined as a compliant material.

[0015] Compared with the prior art, the present application has the following beneficial effects: 1. The present application improves the reliability and accuracy of basic data by precise signal processing and grading analysis. First, the discharge state signal of the ultrafine pulverizer is collected in real time and noise points are removed, and the particle concentration and size distribution indicators in the purified signal are extracted as particle characteristic parameters to ensure data quality. Then, the concentration and size evaluation results are substituted into the standardization formula to calculate the grading index, and the grading result is determined in combination with the double evaluation results, which can accurately reflect the particle characteristics of the material. Based on the grading result, the feeding rate and pulverizing speed adjustment instructions are generated synchronously to realize precise matching of the operating parameters and material requirements, effectively improving the uniformity of the discharged particles and the stability of the yield of the ultrafine pulverizer, and laying a high-quality data and parameter foundation for subsequent linkage control.

[0016] 2. The present application improves the overall control efficiency and material compliance by scientific linkage control and closed-loop optimization mechanism. Based on the particle concentration trend evaluation of the discharge state signal, the dynamic load is evaluated, the particle distribution uniformity grade is determined in combination with the grading result, the dust removal intensity grade is determined, the target control mode is matched to generate dust removal module start-stop and power adjustment instructions, and the precise linkage of the pulverizer and the dust removal module is realized to ensure the dust removal effect while avoiding energy waste. At the same time, the dust removal effect and discharge quality feedback signals are obtained, the initial adjustment feedback data is generated after time alignment and weighted fusion, the target strategy is selected from the optimization strategy library after analyzing the data, and the fine adjustment instructions of the feeding rate and the pulverizing speed are generated. Real-time monitoring of particle characteristics until it is continuously within the compliance range, realizing closed-loop control of grading, dust removal and optimization, greatly improving the compliance material output efficiency and linkage control stability. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 A flowchart of a grading closed-loop dust removal linkage control method for the discharge of an ultrafine pulverizer according to an embodiment of the present application is provided. The implementation of the present application, functional features and advantages will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0018] It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0019] The embodiment of the present application provides a kind of super-micro pulverizer discharging grading closed loop dust removal linkage control method.The execution subject of the kind of super-micro pulverizer discharging grading closed loop dust removal linkage control method includes but is not limited to server, terminal and at least one of the electronic equipment that can be configured to execute the method provided in the embodiment of the present application, etc.The kind of super-micro pulverizer discharging grading closed loop dust removal linkage control method can be executed by software or hardware installed in terminal equipment or server equipment.The server includes but is not limited to: single server, server cluster, cloud server or cloud server cluster, etc.The server can be independent server, can be cloud server that provides cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, content distribution network (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platform.

[0020] Referring to Figure 1 As shown in the figure, a kind of super-micro pulverizer discharging grading closed loop dust removal linkage control method provided by the embodiment of the present application is flow chart diagram.In the embodiment, the kind of super-micro pulverizer discharging grading closed loop dust removal linkage control method includes: S1, the discharge state signal of super-micro pulverizer when discharging is extracted, and the particle characteristic parameter of the super-micro pulverizer is obtained; In the embodiment of the present application, the discharge state signal of super-micro pulverizer when discharging is extracted, and the particle characteristic parameter of the super-micro pulverizer is obtained, including: Real-time acquisition of the discharge state signal of super-micro pulverizer, to obtain the original monitoring signal of the super-micro pulverizer; Remove the noise point in the original monitoring signal, to obtain the purified discharge state signal of the super-micro pulverizer; Extract the particle concentration index and particle size distribution index related to material in the purified discharge state signal, to obtain the particle characteristic parameter of the super-micro pulverizer.

[0021] Specifically, when real-time acquisition of the discharge state signal of super-micro pulverizer, signal acquisition device is installed at the discharge port of super-micro pulverizer, the device includes sensor for monitoring material flow and data recording equipment, sensor continuously captures vibration, optical reflection and other physical signals generated by material particles during discharging process, data recording equipment synchronously records these signals according to set time interval, records the signal in the form of original waveform and intensity value, forms the original monitoring signal of super-micro pulverizer, the signal contains all original physical information related to material during discharging process.

[0022] Further, when removing the noise points in the original monitoring signal, first determine the signal values in the original monitoring signal that obviously deviate from the normal range, which are usually generated by mechanical vibration, environmental light change and other interference factors when the equipment is running, identify these abnormal signals, and then use the replacement method for processing, replace the average value of adjacent normal signal values for the continuous noise points, and directly replace the previous normal signal value for the isolated noise points, so that the signal obtained after the processing can more truly reflect the material discharge state, i.e., the purified discharge state signal of the super-fine grinder.

[0023] Further, when extracting the particle concentration index and the particle size distribution index of the material in the purified discharge state signal, first analyze the waveform characteristics of the purified discharge state signal, calculate the average value of the signal intensity in a unit time according to the corresponding relationship between the signal intensity and the number of material particles, and the average value directly corresponds to the particle concentration index of the material, reflecting the number of material particles in a unit volume. Then, by analyzing the frequency distribution characteristics of the signal, different sizes of particles will generate signals of different frequencies, the signal is decomposed into multiple frequency segments, the number and intensity of signals in each frequency segment are counted, and the proportion of different size particles is determined according to the known corresponding relationship between the frequency and the particle size, so as to form the particle size distribution index. The two indexes jointly constitute the particle characteristic parameters of the super-fine grinder.

[0024] In summary, the original monitoring signal is obtained by real-time signal acquisition, the related original information of the discharge can be completely obtained, the problem of incomplete data basis is solved, and the basis for subsequent feature parameter extraction is provided.

[0025] In summary, the purified signal is obtained by noise removal, the interference can be eliminated, the signal can truly reflect the discharge state, and the problem of inaccurate parameters caused by noisy data is solved.

[0026] In summary, the particle characteristic parameters are obtained by extracting two indexes, the physical signal can be converted into quantitative indexes, the problem of difficult and effective extraction of key parameters is solved, and accurate data is provided for the classification analysis.

[0027] S2, based on the particle characteristic parameters, performing particle size classification analysis on the material to obtain a classification result of the material; In the embodiment of the present application, based on the particle characteristic parameters, the particle size classification analysis on the material is performed to obtain the classification result of the material, which includes: Comparing the particle concentration index in the classification result with a preset concentration threshold to obtain a concentration evaluation result of the material; Comparing the preliminary classification judgment in the classification result with a preset size threshold to obtain a size evaluation result of the material; Based on the concentration evaluation result and the size evaluation result, the classification result of the material is determined.

[0028] The formula for calculating the grading results is as follows: ; In the formula, The grading index corresponds to the grading result. The preset concentration coefficient, This is the quantified value of the concentration assessment result. The preset size coefficient, This is the quantified value of the size evaluation result.

[0029] Specifically, when comparing the particle concentration index in the grading results with the preset concentration threshold, the particle concentration index of the material is first extracted from the particle characteristic parameters. This index reflects the number of material particles per unit volume. At the same time, the preset concentration threshold is retrieved from the system parameter library. This threshold is a standard value pre-set based on the subsequent processing requirements of the material and the processing capacity of the equipment, and is used to distinguish whether the material concentration meets the grading requirements.

[0030] Furthermore, the extracted particle concentration index is directly compared with a preset concentration threshold. If the particle concentration index is higher than the preset concentration threshold, the material concentration is determined to be outside the standard range and recorded as an assessment conclusion of excessively high concentration. If the particle concentration index is lower than the preset concentration threshold, the material concentration is determined to be below the standard range and recorded as an assessment conclusion of excessively low concentration. If the particle concentration index is consistent with the preset concentration threshold, the material concentration is determined to be within the standard range and recorded as an assessment conclusion of qualified concentration. These assessment conclusions together constitute the material concentration assessment result.

[0031] Furthermore, when comparing the preliminary classification judgment in the classification results with the preset size threshold, a preliminary classification judgment of the material particle size is first made based on the particle size distribution index in the particle characteristic parameters. For example, the material is initially divided into categories such as large particles, medium particles, and small particles according to the particle size range. Then, the preset size threshold is retrieved from the system parameter library. This threshold is a classification standard set according to the particle size requirements of different application scenarios, which clarifies the size boundaries corresponding to each category of particles.

[0032] Furthermore, the size range of each category of particles in the preliminary classification judgment is compared with the preset size threshold one by one. If the size range of a certain category of particles is completely within the qualified range corresponding to the preset size threshold, then the size of that category of particles is determined to meet the requirements; if the size range of a certain category of particles exceeds the qualified range corresponding to the preset size threshold, then the size of that category of particles is determined to not meet the requirements. The size evaluation result of the material is formed based on the comparison results of all categories.

[0033] Further, when determining the grading result of the material based on the concentration evaluation result and the size evaluation result, the specific contents of the two evaluation results are first comprehensively analyzed. If the concentration evaluation result is concentration qualified, and the particle sizes of all categories in the size evaluation result meet the requirements, it is determined that the overall material meets the grading standard, and the material is divided into a qualified grade, which is recorded as a grading conclusion that can directly enter the subsequent processing link. If the concentration evaluation result is concentration too high or too low, or there is a category of particle size that does not meet the requirements in the size evaluation result, it is determined that the material does not meet the grading standard, and the specific reasons for the non-compliance are further analyzed, for example, whether it is a concentration problem or a particle size problem. According to the severity of the non-compliance, the material is divided into an adjustment required grade or an unqualified grade. The material in the adjustment required grade needs to be re-evaluated after concentration adjustment or secondary crushing treatment, and the material in the unqualified grade needs to be processed according to a specific process. Finally, these determination results, grade division and subsequent processing suggestions are integrated to form the grading result of the material.

[0034] Specifically, the source of the grading index corresponding to the grading result is the quantitative value of the concentration evaluation result and the quantitative value of the size evaluation result, combined with the preset concentration coefficient and size coefficient. The index is used to quantitatively represent the degree of the material grading result, and is the core index for judging whether the material meets the subsequent processing requirements.

[0035] Further, the source of the preset concentration coefficient is the weight value preset according to the importance of the concentration index in the material processing process. For example, in a processing scenario with high concentration requirements, a higher concentration coefficient is set, and if the concentration requirement is low, a lower coefficient is set. The coefficient is stored in the parameter configuration module of the system and is called when calculating the grading index.

[0036] Further, the quantitative value of the concentration evaluation result is obtained by converting the concentration evaluation result of the material into a numerical value. For example, the evaluation result of concentration qualified is converted into a fixed positive numerical value, and the evaluation result of concentration too high or too low is converted into different numerical values according to the degree of deviation from the standard. The conversion rule is based on the influence of concentration on the grading result and is pre-established to ensure that the quantitative value accurately reflects the concentration evaluation.

[0037] Further, the source of the preset size coefficient is the weight value preset according to the attention degree of the particle size index in the material processing standard. If the particle size has a greater impact on product quality during processing, a higher size coefficient is set, and vice versa. The coefficient is also stored in the system parameter configuration module and participates in the calculation of the grading index together with the concentration coefficient.

[0038] Further, the quantitative value of the size evaluation result is obtained by numerical conversion of the size evaluation result of the material, for example, converting all evaluation results of the particle size of the same category into a fixed positive numerical value, and converting the numerical value according to the number of categories that do not meet the requirements and the degree of deviation from the threshold value when there are categories that do not meet the requirements, and the conversion rule is determined according to the influence of the particle size on the classification result, so that the quantitative value can truly reflect the size evaluation result.

[0039] Further, the meaning of the calculation logic is to give different weights to the concentration evaluation result and the size evaluation result, and to comprehensively consider the influence of the two on the classification of the material, so as to obtain a classification index that can fully reflect the classification quality of the material, and to avoid the classification deviation caused by the single dependence on the concentration or size index.

[0040] Further, the preset concentration coefficient and size coefficient respectively reflect the importance of the concentration and size index in classification, the quantitative value of the concentration evaluation result and the quantitative value of the size evaluation result convert the qualitative evaluation conclusion into a calculable numerical value, and the weighted sum of the two changes the classification result from a qualitative description to a quantitative index, which is more convenient for comparing and analyzing the classification quality of different batches of materials, and provides clear data basis for whether the subsequent processing parameters need to be adjusted.

[0041] Further, the classification index corresponding to the classification result has a positive change relationship with the quantitative value of the concentration evaluation result, and in the case of a fixed preset concentration coefficient and quantitative value of the size evaluation result, the higher the quantitative value of the concentration evaluation result, the more the concentration of the material meets the requirements, and the classification index increases accordingly; the lower the quantitative value of the concentration evaluation result, the more serious the deviation of the concentration of the material from the standard, and the classification index decreases accordingly.

[0042] Further, the classification index corresponding to the classification result has a positive change relationship with the quantitative value of the size evaluation result, and in the case of a fixed preset size coefficient and quantitative value of the concentration evaluation result, the higher the quantitative value of the size evaluation result, the more the particle size of the material meets the standard, and the higher the classification index; the lower the quantitative value of the size evaluation result, the more serious the deviation of the particle size of the material from the standard, and the lower the classification index.

[0043] Further, when the preset concentration coefficient is greater than the preset size coefficient, the quantitative value of the concentration evaluation result has a greater influence on the classification index, and at this time, the change of the concentration index will cause more obvious fluctuations in the classification index; when the preset size coefficient is greater than the preset concentration coefficient, the quantitative value of the size evaluation result has a more prominent influence on the classification index, and the change of the particle size index will cause more significant changes in the classification index.

[0044] In summary, the concentration evaluation result obtained by comparing the particle concentration index with the preset threshold value can accurately judge whether the concentration meets the classification requirements and solve the problem of single subjective judgment of concentration deviation.

[0045] In summary, comparing the preliminary grading judgment with the preset size threshold to obtain the size assessment result can clarify whether the particle size meets the standard and solve the problem of inaccurate particle size judgment.

[0046] In summary, combining the results of the two assessments to determine the grading results can comprehensively consider both concentration and magnitude factors, solve the problem of one-sided grading in existing technologies, and provide a reliable basis for subsequent adjustments to the pulverizer parameters.

[0047] In summary, this formula calculates the grading index by weighting concentration coefficient and size coefficient, which can integrate the assessment results of concentration and size, avoid the bias of judgment by a single indicator, and solve the problem of inaccurate grading in existing technologies.

[0048] In summary, converting qualitative assessments into quantitative indices facilitates a direct comparison of material grading quality, provides a clear quantitative basis for subsequent adjustments to the operating parameters of the ultrafine pulverizer, and improves the accuracy of parameter adjustments.

[0049] S3. Adjust the operating parameters of the ultrafine pulverizer according to the particle concentration and particle size distribution of the material in the grading results; In this embodiment of the invention, adjusting the operating parameters of the ultrafine pulverizer based on the particle concentration and particle size distribution of the material in the grading results includes: Based on the particle concentration level information in the classification results, an adjustment command for the feed rate of the ultrafine pulverizer is generated. Based on the uniformity information of particle size distribution in the grading results, an adjustment command for the grinding speed of the ultrafine pulverizer is generated. According to the adjustment command, the feeding rate and the crushing speed are adjusted synchronously to obtain the adjusted operating parameters.

[0050] Specifically, based on the grade information of the particle concentration in the classification result, when generating the adjustment instruction for the feeding rate of the ultrafine pulverizer, first, the classification standard of the particle concentration in the classification result is determined, for example, divided into three levels of too high, qualified, and too low, and each level corresponds to the adjustment direction and amplitude of the feeding rate. If the classification result shows that the particle concentration is too high, it means that the current feeding rate is too fast, causing material accumulation and concentration exceeding the standard when discharging. At this time, the adjustment instruction of reducing the feeding rate is generated, and the specific adjustment amplitude is determined according to the degree of concentration exceeding the qualified range. The greater the concentration exceeds the qualified range, the greater the feeding rate is reduced. If the classification result shows that the particle concentration is too low, it means that the current feeding rate is too slow, and the material supply is insufficient. The adjustment instruction of increasing the feeding rate is generated, and the increasing amplitude is also determined according to the degree of concentration below the qualified range. If the classification result shows that the particle concentration is qualified, the adjustment instruction of keeping the current feeding rate is generated to ensure that the feeding rate matches the processing capacity of the equipment. The instruction contains the specific value of the adjusted feeding rate and the execution time, that is, the adjustment instruction of the feeding rate of the ultrafine pulverizer.

[0051] Further, based on the uniformity information of the particle size distribution in the classification result, when generating the adjustment instruction for the pulverizing speed of the ultrafine pulverizer, first, the uniformity description of the particle size distribution in the classification result is analyzed, for example, divided into three categories of extremely uneven, relatively uneven, and uniform, and each category corresponds to the adjustment rule of the pulverizing speed. If the classification result shows that the particle size distribution is extremely uneven, there are a large number of oversized or undersized particles, which means that the current pulverizing speed is not suitable for the material characteristics. When there are too many oversized particles, it means that the speed is too low and the pulverization is insufficient. The adjustment instruction of increasing the pulverizing speed is generated. When there are too many undersized particles, it means that the speed is too high and the pulverization is excessive. The adjustment instruction of reducing the pulverizing speed is generated. The adjustment amplitude is determined according to the degree of deviation of the particle size from the uniform distribution. The more serious the deviation, the greater the adjustment amplitude of the speed.

[0052] Further, if the classification result shows that the particle size distribution is relatively uneven, there are a small number of particles that do not meet the requirements, the instruction of slightly adjusting the pulverizing speed is generated to slightly increase or decrease the speed to optimize the particle distribution. If the classification result shows that the particle size distribution is uniform, the instruction of keeping the current pulverizing speed is generated, which clearly indicates the specific value of the adjusted pulverizing speed and the execution mode, that is, the adjustment instruction of the pulverizing speed of the ultrafine pulverizer.

[0053] Further, according to the adjustment instruction, the feeding rate and the crushing rotating speed are synchronously adjusted to obtain the adjusted operation parameters, the adjusted specific values, execution time and sequence requirements are extracted from the feeding rate adjustment instruction and the crushing rotating speed adjustment instruction, the two adjustment operations are ensured to be synchronously performed in time, and imbalance of material processing in a short time caused by adjusting a single parameter is avoided. The value in the feeding rate adjustment instruction is transmitted to the feeding control module of the ultrafine crusher, the control module drives the feeding device to change the material conveying speed, and meanwhile, the value in the crushing rotating speed adjustment instruction is transmitted to the crushing motor control module, the control module adjusts the motor output rotating speed, and the rotating speed of the crushing part is synchronously changed.

[0054] Further, in the adjustment process, the equipment operation state and the discharging condition are monitored in real time, it is confirmed that the feeding rate and the crushing rotating speed are stably adjusted to the adjusted values, and the equipment has no abnormal vibration, noise and other problems, after the two parameters are stably operated, the feeding rate and the crushing rotating speed values at this time are recorded, and the two values jointly constitute the adjusted operation parameters of the ultrafine crusher.

[0055] In general, the feeding rate adjustment instruction is generated according to the particle concentration level, the material load can be matched and optimized, and the concentration abnormality problem is solved.

[0056] In general, the crushing rotating speed adjustment instruction is generated according to the particle uniformity, the particle size distribution can be optimized, and the particle nonuniformity is avoided.

[0057] In general, the two parameters are synchronously adjusted to obtain the new operation parameters, the parameters are accurately matched with the material demand, and the discharging quality and the equipment efficiency are improved.

[0058] S4, based on the discharging state signal and the classification result, the dust removal module is controlled in linkage; In the embodiment of the application, the dust removal module is controlled in linkage based on the discharging state signal and the classification result, which comprises: The real-time particle concentration change trend in the discharging state signal is analyzed to obtain the dynamic load evaluation of the material; According to the particle distribution uniformity level in the classification result, the dust removal intensity level required by the material is determined; Based on the dynamic load evaluation and the dust removal intensity level, a target control mode is matched from the preset linkage control mode; The start-stop instruction and the power adjustment instruction of the dust removal module are generated according to the target control mode, and the linkage control process of the dust removal module is started according to the start-stop instruction and the power adjustment instruction.

[0059] Specifically, the real-time particle concentration trend in the discharge state signal is analyzed to obtain the dynamic load evaluation of the material. First, the particle concentration data in the discharge state signal within a continuous time period is extracted, and the concentration change sequence is formed in chronological order. By observing the change direction and amplitude of the sequence, if the concentration data continuously rises and the rising amplitude is large, it indicates that the material discharge volume is increasing and the material load handled by the equipment is increasing. If the concentration data continuously decreases and the decreasing amplitude is large, it indicates that the material discharge volume is decreasing and the material load handled by the equipment is decreasing. If the concentration data fluctuates within a small range without obvious upward or downward trend, it indicates that the material load is in a stable state. Based on these observations, combined with the rated load range of the equipment, the current material load change is qualitatively described, such as "rapid load increase", "slow load decrease", "load stable", etc. These descriptions together constitute the dynamic load evaluation of the material.

[0060] Further, according to the particle distribution uniformity level in the classification result, the dust removal intensity level required by the material is determined. First, the classification of particle distribution uniformity in the classification result is determined, such as "extremely uneven", "relatively uneven", and "uniform". Each level corresponds to different dust removal requirements.

[0061] Further, if the uniformity level is "extremely uneven", it indicates that there are a large number of fine particles in the material, which are easy to diffuse with air flow and require strong dust removal capacity to capture. Therefore, it is determined as a high dust removal intensity level. If the uniformity level is "relatively uneven", it indicates that the number of fine particles in the material is moderate, and medium-intensity dust removal can meet the requirements, so it is determined as a medium dust removal intensity level. If the uniformity level is "uniform", it means that the particle size of the material is relatively consistent, and there are few fine particles, so only basic dust removal intensity is needed to achieve the effect, and it is determined as a low dust removal intensity level. This level is the dust removal intensity level required by the material.

[0062] Further, based on the dynamic load evaluation and the dust removal intensity level, the target control mode is matched from the pre-set linkage control mode. First, the pre-set linkage control mode library is sorted, which contains control modes corresponding to different dynamic load and dust removal intensity combinations, such as "high load + high dust removal intensity" corresponding to mode one, "stable load + medium dust removal intensity" corresponding to mode two, "low load + low dust removal intensity" corresponding to mode three, etc. Each mode specifies the operating parameter logic of the dust removal module.

[0063] Further, the current obtained dynamic load assessment is combined with the dust removal intensity level, such as "rapid load rise + high dust removal intensity", a mode completely matching the combination is searched in the preset mode library, if a completely matching mode is found, the mode is directly determined as the target control mode; if no completely matching combination is found, a mode closest to the dynamic load assessment and the dust removal intensity level is selected as the target control mode, so as to ensure that the target control mode can adapt to the current material processing situation.

[0064] Further, the start-stop instruction and the power adjustment instruction of the dust removal module are generated according to the target control mode, and when the linkage control process of the dust removal module is started according to the start-stop instruction and the power adjustment instruction, the running requirements of the dust removal module in the target control mode are analyzed first, if the mode requires the dust removal module to start immediately and run at high power, the "start immediately" start-stop instruction and the "adjust to the highest power" power adjustment instruction are generated; if the mode requires the dust removal module to maintain running and the power to remain medium, the "keep running" start-stop instruction and the "maintain the current medium power" power adjustment instruction are generated; if the mode requires the dust removal module to run at low power, the "keep running" start-stop instruction and the "reduce to the specified power" power adjustment instruction are generated.

[0065] Further, the two generated instructions are transmitted to the control unit of the dust removal module, the control unit first confirms the running state of the dust removal module according to the start-stop instruction, and then adjusts the motor speed or fan air volume of the dust removal module according to the power adjustment instruction, so that the dust removal module runs according to the instruction requirements, and the instruction execution time and the adjusted parameters are recorded, marking that the linkage control process of the dust removal module is formally started.

[0066] In summary, the dynamic load assessment obtained by analyzing the real-time particle concentration change trend in the discharge state signal can accurately capture the material load fluctuation and avoid the disconnection between the dust removal module and the material processing rhythm, thereby providing a basis for dust removal control that fits the actual working condition.

[0067] In summary, the dust removal intensity level is determined according to the particle distribution uniformity level in the classification result, so that the dust removal capacity can be matched according to the material characteristics, and the incomplete dust removal or excessive energy consumption can be prevented.

[0068] In summary, the target control mode is matched by combining the two, the start-stop and power instructions are generated to start the linkage control, the ultrafine grinder and the dust removal module are cooperated to work, the linkage control accuracy and energy efficiency are improved, and the problem of poor flexibility of fixed mode control is solved.

[0069] S5, obtaining the effect feedback signal of the dust removal module and the discharge quality feedback signal of the ultrafine grinder after adjustment, data fusion is performed on the effect feedback signal and the discharge quality feedback signal to obtain the initial adjustment feedback data of the ultrafine grinder; In the embodiment of the present application, the effect feedback signal of the dust removal module and the discharge quality feedback signal of the ultrafine grinder after adjustment are obtained, data fusion is performed on the effect feedback signal and the discharge quality feedback signal to obtain the initial adjustment feedback data of the ultrafine grinder, comprising: generating the effect feedback signal of the dust removal module according to the dust removal state data of the exhaust particle concentration and the airflow resistance of the dust removal module; generating the discharge quality feedback signal of the ultrafine grinder after adjustment according to the quality state data of the discharge particle uniformity and the yield rate of the material; performing time alignment processing on the dust removal state data and the quality state data to obtain the synchronous feedback data set of the ultrafine grinder; performing weighted fusion processing on the synchronous feedback data set to obtain the initial adjustment feedback data of the ultrafine grinder.

[0070] The weighted fusion processing on the synchronous feedback data set to obtain the initial adjustment feedback data of the ultrafine grinder, comprising: extracting the exhaust particle concentration index, the airflow resistance index, the material particle uniformity index and the yield rate index from the synchronous feedback data set; performing weighted fusion on the exhaust particle concentration index, the airflow resistance index, the material particle uniformity index and the yield rate index to obtain the fusion index value of the ultrafine grinder, wherein the calculation formula of the fusion index value is as follows: In the formula, the fusion index value is the particle concentration coefficient calibrated based on historical data is the exhaust particle concentration index is the airflow resistance coefficient calibrated based on historical data is the airflow resistance index is the particle uniformity coefficient calibrated based on historical data is the material particle uniformity index is the yield rate coefficient calibrated based on historical data is the yield rate index is comparing the fusion index value with a preset threshold to obtain the fusion evaluation result of the synchronous feedback data set, and generating the initial adjustment feedback data of the ultrafine grinder according to the fusion evaluation result.

[0071] ​Specifically, when generating the effect feedback signal of the dust removal module according to the dust removal state data of the exhaust particle concentration and the airflow resistance of the dust removal module, the particle concentration sensor installed at the exhaust port of the dust removal module is used to collect the number of particles in the exhaust, so as to obtain the exhaust particle concentration data, which reflects the effect of the dust removal module on capturing fine particles; at the same time, the airflow pressure sensor is used to collect the airflow resistance data inside the dust removal module, and the airflow resistance that is too large or too small will affect the dust removal efficiency. The two data are arranged in sequence at a fixed time interval. For the exhaust particle concentration data, if the concentration is lower than the preset standard, it is marked as "excellent", if it meets the standard, it is marked as "good", and if it is higher than the standard, it is marked as "poor"; for the airflow resistance data, if it is in the preset reasonable interval, it is marked as "normal", and if it is out of the interval, it is marked as "abnormal". The marking results of the two data are combined to form a signal containing "dust removal effect level" and "running state" in the form of text and numerical combination, which is the effect feedback signal of the dust removal module.

[0072] Further, when generating the output quality feedback signal of the adjusted ultrafine grinder according to the quality state data of the output particle uniformity and the output rate of the material, the particle analyzer is used to detect the material at the output port of the ultrafine grinder, the proportion of particles of different sizes is counted, and the particle uniformity data is calculated. If the proportion of particles of different sizes meets the preset proportion, the uniformity is qualified, otherwise it is not qualified; at the same time, the weighing sensor and the timer are used to weigh the output material weight in a fixed time, calculate the output rate in unit time, and obtain the output rate data. If the output rate is within the preset qualified range, it is qualified, and if it is lower than the range, the output is insufficient. The particle uniformity data and the output rate data are converted into quantitative scores respectively. The uniformity is given a high score if it is qualified, and a deduction score if it is not qualified according to the deviation degree; the output rate is given a high score if it is qualified, and a deduction score if it is insufficient according to the difference proportion. The two scores and the corresponding "qualification status" are integrated to form a comprehensive signal containing "quality score" and "output state", which is the output quality feedback signal of the adjusted ultrafine grinder.

[0073] Further, when generating the output quality feedback signal of the adjusted ultrafine grinder according to the quality state data of the output particle uniformity and the output rate of the material, the particle analyzer is used to detect the material at the output port of the ultrafine grinder, the proportion of particles of different sizes is counted, and the particle uniformity data is calculated. If the proportion of particles of different sizes meets the preset proportion, the uniformity is qualified, otherwise it is not qualified; at the same time, the weighing sensor and the timer are used to weigh the output material weight in a fixed time, calculate the output rate in unit time, and obtain the output rate data. If the output rate is within the preset qualified range, it is qualified, and if it is lower than the range, the output is insufficient. The particle uniformity data and the output rate data are converted into quantitative scores respectively. The uniformity is given a high score if it is qualified, and a deduction score if it is not qualified according to the deviation degree; the output rate is given a high score if it is qualified, and a deduction score if it is insufficient according to the difference proportion. The two scores and the corresponding "qualification status" are integrated to form a comprehensive signal containing "quality score" and "output state", which is the output quality feedback signal of the adjusted ultrafine grinder. Further, when generating the output quality feedback signal of the adjusted ultrafine grinder according to the quality state data of the output particle uniformity and the output rate of the material, the particle analyzer is used to detect the material at the output port of the ultrafine grinder, the proportion of particles of different sizes is counted, and the particle uniformity data is calculated. If the proportion of particles of different sizes meets the preset proportion, the uniformity is qualified, otherwise it is not qualified; at the same time, the weighing sensor and the timer are used to weigh the output material weight in a fixed time, calculate the output rate in unit time, and obtain the output rate data. If the output rate is within the preset qualified range, it is qualified, and if it is lower than the range, the output is insufficient. The particle uniformity data and the output rate data are converted into quantitative scores respectively. The uniformity is given a high score if it is qualified, and a deduction score if it is not qualified according to the deviation degree; the output rate is given a high score if it is qualified, and a deduction score if it is insufficient according to the difference proportion. The two scores and the corresponding "qualification status" are integrated to form a comprehensive signal containing "quality score" and "output state", which is the output quality feedback signal of the adjusted ultrafine grinder.

[0074] Further, when the initial adjustment feedback data of the super fine grinder is obtained by weighted fusion processing of the synchronous feedback data set, the weights of the dust removal effect and the discharge quality are preset according to the importance of the two in the overall equipment operation, for example, if the dust removal effect has a greater impact on subsequent processing, the dust removal state data weight is higher, otherwise the quality state data weight is higher. The dust removal state data and quality state data of each record in the synchronous feedback data set are first quantitatively scored and multiplied by the corresponding weight to obtain two weighted scores; then the two weighted scores are added to obtain the comprehensive score of the record. The comprehensive scores of all records are arranged in chronological order, and the corresponding original dust removal state and quality state key information of each record is attached, forming a structured data set containing "time-comprehensive score-original key data", which is the initial adjustment feedback data of the super fine grinder.

[0075] Specifically, when the exhaust particle concentration index, airflow resistance index, material particle uniformity index and production rate index are extracted from the synchronous feedback data set, the storage file of the synchronous feedback data set is first opened, which records the dust removal state data and quality state data at different time points in chronological order. In the dust removal state data part, the specific value of the exhaust particle concentration corresponding to each time point is located and extracted as the exhaust particle concentration index; at the same time, the specific value of the airflow resistance at the same time point is extracted as the airflow resistance index. In the quality state data part, the material particle uniformity detection result at the corresponding time point is found and converted into a quantifiable index value as the material particle uniformity index; then the production rate calculation result at the same time point is extracted as the production rate index. The four extracted indexes are correspondingly arranged in chronological order to form a four-dimensional index list containing "time-exhaust particle concentration index-airflow resistance index-material particle uniformity index-production rate index", ensuring that the four indexes at each time point are complete without missing.

[0076] Further, when the exhaust particle concentration index, the airflow resistance index, the material particle uniformity index and the production rate index are weighted and fused to obtain the fusion index value of the ultrafine grinder, the weight values corresponding to the four indexes are first retrieved from the system preset parameter library. These weight values are preset according to the equipment operation requirements and the influence degree of each index on the overall effect, for example, the material particle uniformity index has a greater impact on product quality, so the weight value is relatively higher, and the exhaust particle concentration index is critical to environmental protection requirements, so a higher weight is also set. The exhaust particle concentration index value at each time point is multiplied by its corresponding weight to obtain the exhaust particle concentration weighted value; in the same way, the airflow resistance weighted value, the material particle uniformity weighted value and the production rate weighted value are calculated respectively. The four weighted values at the same time point are added to obtain the comprehensive value at that time point, which is the fusion index value of the ultrafine grinder at that time point. The fusion index values at all time points are arranged in chronological order to form a fusion index value sequence.

[0077] Further, based on the comparison between the fusion index value and the preset threshold, the fusion evaluation result of the synchronous feedback data set is obtained, and the initial adjustment feedback data of the ultrafine grinder is generated according to the fusion evaluation result. First, the preset threshold is retrieved from the system parameter library, which is set according to the fusion index value range when the equipment is running normally, and is divided into three levels: excellent threshold, qualified threshold and unqualified threshold. The fusion index value at each time point is compared with the preset threshold. If the fusion index value is higher than the excellent threshold, the evaluation result at that time point is marked as “excellent”; if the fusion index value is between the excellent threshold and the qualified threshold, it is marked as “qualified”; if the fusion index value is lower than the qualified threshold, it is marked as “unqualified”.

[0078] Further, the evaluation results at all time points are arranged in chronological order, and the fusion index value, the four original index values and the weight information corresponding to each time point are attached to form a structured evaluation document containing “time-fusion index value-evaluation level-original index data-weight”. This document is the initial adjustment feedback data of the ultrafine grinder.

[0079] Specifically, the fusion index value is calculated by multiplying the exhaust particle concentration index, the airflow resistance index, the material particle uniformity index and the production rate index by the corresponding coefficients and then summing them up. This value is used to comprehensively measure the overall effect of the ultrafine grinder and the dust removal module running in cooperation, and is the core quantitative basis for subsequent evaluation of whether the adjustment is effective.

[0080] Further, the source of the particle concentration coefficient calibrated based on historical data is to select a large amount of exhaust particle concentration data and actual dust removal effect data in the past operation of the equipment, analyze the correlation between the two, if the exhaust particle concentration has greater influence on the dust removal effect, then increase the coefficient through historical data calibration, otherwise decrease, ensure that the coefficient can accurately reflect the importance of the particle concentration index in the fusion calculation, and finally determine the coefficient stored in the system parameter library.

[0081] Further, the source of the exhaust particle concentration index is to collect the particle number in the exhaust through the particle concentration sensor at the exhaust port of the dust removal module, and convert the collected raw data into standardized index values according to the preset calculation method. The index directly reflects the effect of removing fine particles by the dust removal module.

[0082] Further, the source of the airflow resistance coefficient calibrated based on historical data is to collect airflow resistance data and dust removal module operation efficiency data in the historical operation of the equipment, analyze the influence of airflow resistance change on dust removal efficiency, if the airflow resistance anomaly has serious interference on the dust removal efficiency, then increase the coefficient through historical data calibration, if the influence is smaller, then decrease the coefficient, and finally determine the final coefficient after multiple verification and adjustment and store it.

[0083] Further, the source of the airflow resistance index is to collect the resistance data of the airflow through the pressure sensor inside the dust removal module, and convert the original pressure data into index values that meet the evaluation standard. The index reflects the smoothness of the airflow circulation inside the dust removal module.

[0084] Further, the source of the particle uniformity coefficient calibrated based on historical data is to extract particle uniformity data and product quality data in the past processing of the equipment, analyze the influence weight of uniformity on product quality, if the uniformity plays a decisive role in product quality, then increase the coefficient through historical data calibration, otherwise decrease, and ensure that the coefficient matches the actual importance of uniformity.

[0085] Further, the source of the material particle uniformity index is to detect the particle size distribution of the material at the discharge port of the ultrafine grinder through a particle analyzer, and calculate the standardized uniformity index value according to the distribution. The index reflects the consistency of the particle size of the material.

[0086] Further, the source of the yield rate coefficient calibrated based on historical data is to collect yield rate data and production efficiency data in the historical operation of the equipment, analyze the influence degree of yield rate on production efficiency, if the yield rate is a key influencing factor of production efficiency, then increase the coefficient through historical data calibration, if the influence is smaller, then decrease the coefficient, and finally determine the coefficient after repeated verification and store it.

[0087] Further, the source of the yield rate index is to weigh the output weight by the weighing sensor and the timer in a fixed time, calculate the yield per unit time, and then convert it into a standardized rate index value, which reflects the material processing efficiency of the ultrafine grinder.

[0088] Further, the meaning of the calculation logic is to comprehensively consider the dust removal effect and material processing quality and efficiency by assigning different calibration coefficients to the four indexes, integrate the dispersed single indexes into a fusion index value that can reflect the overall operation state of the equipment, and avoid the one-sidedness of evaluation caused by relying on only one index.

[0089] Further, the coefficients calibrated based on historical data ensure that the weights of each index meet the actual operation rules of the equipment, so that the fusion index value can truly reflect the influence of each factor on the overall effect. Through this calculation, multi-dimensional operation data can be converted into a single quantitative index, which facilitates quick judgment of the current collaborative operation level of the equipment and provides clear data support for subsequent adjustment of parameters.

[0090] Further, the fusion index value and the exhaust particle concentration index have an inverse relationship. Under the condition that other indexes and coefficients are fixed, if the exhaust particle concentration index increases, it means that the dust removal effect is getting worse, and the fusion index value will decrease accordingly. If the exhaust particle concentration index decreases, the dust removal effect improves, and the fusion index value increases accordingly. The greater the particle concentration coefficient, the more significant the influence of the change in the exhaust particle concentration index on the fusion index value.

[0091] Further, the fusion index value and the airflow resistance index have an inverse relationship. When other conditions remain unchanged, if the airflow resistance index increases, it means that the airflow circulation in the dust removal module is not smooth, the dust removal efficiency decreases, and the fusion index value decreases. If the airflow resistance index decreases, the airflow circulation is smooth, the dust removal efficiency improves, and the fusion index value increases. The greater the airflow resistance coefficient, the more obvious the change trend.

[0092] Further, the fusion index value and the material particle uniformity index have a positive relationship. When other factors are fixed, if the material particle uniformity index increases, the consistency of the material particles improves, the product quality improves, and the fusion index value increases. If the material particle uniformity index decreases, the consistency of the material particles deteriorates, and the fusion index value decreases. The greater the particle uniformity coefficient, the more prominent the influence of the uniformity index on the fusion index value.

[0093] Further, the fusion index value and the yield rate index have a positive relationship. When other conditions remain unchanged, if the yield rate index increases, the processing efficiency of the ultrafine grinder improves, and the fusion index value increases. If the yield rate index decreases, the processing efficiency decreases, and the fusion index value decreases. The greater the yield rate coefficient, the more dramatic the fluctuation of the fusion index value caused by the change in the yield rate index.

[0094] Further, when a certain coefficient is significantly larger than other coefficients, the corresponding index has a dominant influence on the fusion index value, and at this time, the change of the index will become the main driving factor of the change of the fusion index value.

[0095] In summary, the effect feedback signal is generated according to the exhaust particle concentration and airflow resistance of the dust removal module, which can accurately reflect the actual operation effect of the dust removal module, avoid the deviation caused by subjective judgment of the dust removal effect, and provide data support for subsequent evaluation of whether the dust removal module is suitable for the current working condition.

[0096] In summary, the discharge quality feedback signal is generated according to the discharge particle uniformity and yield rate of the material, which can intuitively grasp the discharge quality and efficiency of the ultrafine grinder after adjustment, and solve the problem of lack of system feedback of the discharge quality in the prior art.

[0097] In summary, the synchronous feedback data set is obtained by time alignment processing of the dust removal state data and the quality state data, which can eliminate the analysis error caused by the time difference of data collection, ensure the correlation of the two data in the same time dimension, and improve the data correlation and reliability.

[0098] In summary, the initial adjustment feedback data is obtained by weighted fusion processing of the synchronous feedback data set, which can comprehensively consider the information of the dust removal effect and the discharge quality in two dimensions, avoid the one-sidedness of evaluation caused by a single feedback index, provide comprehensive and accurate feedback basis for subsequent optimization of the ultrafine grinder adjustment process, solve the defect of adjusting the equipment only according to a single feedback in the prior art, and improve the closed-loop nature and precision of the overall control.

[0099] In summary, the four key indexes are extracted from the synchronous feedback data set, which can accurately select the core data of the dust removal effect and the discharge quality and efficiency, avoid irrelevant data interference, lay a precise data foundation for subsequent fusion calculation, and solve the problem of evaluation deviation caused by disordered data extraction in the prior art.

[0100] In summary, the fusion index value is obtained by weighted fusion of the four indexes through a formula with a historical calibration coefficient, the coefficient is calibrated based on historical data to ensure that the weight conforms to the actual operation rule of the equipment, the multi-dimensional scattered data can be converted into a single quantitative index, the one-sidedness of single index evaluation can be avoided, and the cooperative operation effect of dust removal and crushing can be accurately reflected.

[0101] In summary, the fusion evaluation result is obtained by comparing the fusion index value with the preset threshold value, and the initial adjustment feedback data is generated, which can intuitively judge the pros and cons of the current operation state of the equipment, provide comprehensive and quantitative feedback basis for subsequent optimization of the ultrafine grinder adjustment process, solve the problem of blind optimization caused by lack of system feedback data in the prior art, and improve the precision and reliability of closed-loop control.

[0102] S6. Based on the initial adjustment feedback data, further optimize the adjustment process of the ultrafine pulverizer in S4 to obtain compliant materials for the ultrafine pulverizer.

[0103] In this embodiment of the invention, the step of further optimizing the adjustment process of the ultrafine pulverizer in S4 based on the initial adjustment feedback data to obtain compliant materials for the ultrafine pulverizer includes: Analyze the initial adjustment feedback data to obtain the comprehensive performance evaluation level and the identifier of the parameters to be optimized; Based on the comprehensive performance evaluation level, a target optimization strategy is selected from a preset optimization strategy library; Based on the parameter identifier to be optimized and the target optimization strategy, a fine adjustment instruction for the feeding rate and pulverizing speed in the ultrafine pulverizer is obtained; The fine adjustment command is executed, and the particle characteristics of the produced material are monitored. When the particle characteristics are continuously within the preset compliance range, it is determined that the ultrafine pulverizer has obtained compliant material.

[0104] The process of executing the fine adjustment command and monitoring the particle characteristics of the produced material, and determining that the ultrafine pulverizer has obtained compliant material when the particle characteristics remain within a preset compliance range, includes: The operating status of the ultrafine pulverizer is adjusted according to the fine adjustment instructions. The particle characteristics of the material produced by the ultrafine pulverizer are monitored in real time after the operating status is adjusted, and the particle characteristic monitoring data of the ultrafine pulverizer is obtained. By comparing the particle characteristic monitoring data with the preset compliance range, the compliance judgment result of the material is obtained; When the compliance judgment result indicates that the particle characteristics are continuously within the preset compliance range, the material is confirmed to be a compliant material.

[0105] Specifically, when parsing the initial adjustment feedback data to obtain the comprehensive performance evaluation level and the to-be-optimized parameter identifier, first, open the structured document corresponding to the initial adjustment feedback data, which contains information such as time, fusion index value, evaluation level, original index data, and weight. Locate the "evaluation level" field in the document, extract the evaluation results corresponding to each time point, such as "excellent", "qualified", and "unqualified", and determine the overall comprehensive performance evaluation level by synthesizing the evaluation results of all time points. If most of the time points are "excellent", the overall level is "excellent", and if there are many "unqualified", the overall level is "unqualified". Then check the original index data part, compare the standard range of each index, find out the indexes that exceed or fail to meet the standard range, such as high exhaust particle concentration and low material particle uniformity, and mark these non-standard indexes as to-be-optimized parameters to form the to-be-optimized parameter identifier, which clearly indicates the specific parameter name that needs to be adjusted.

[0106] Further, based on the comprehensive performance evaluation level, select the target optimization strategy from the preset optimization strategy library. First, sort the preset optimization strategy library, which stores different optimization strategies according to the comprehensive performance evaluation level, for example, the "excellent" level corresponds to the "maintain current parameter fine-tuning optimization" strategy, which only adjusts the parameters slightly to maintain stability; the "qualified" level corresponds to the "targeted parameter optimization" strategy, which adjusts the to-be-optimized parameters moderately; and the "unqualified" level corresponds to the "overall parameter reset optimization" strategy, which adjusts the key parameters significantly. Match the obtained comprehensive performance evaluation level with the level classification in the strategy library. If the comprehensive performance evaluation level is "excellent", select the "maintain current parameter fine-tuning optimization" strategy as the target optimization strategy; if it is "qualified", select the "targeted parameter optimization" strategy; and if it is "unqualified", select the "overall parameter reset optimization" strategy, to ensure that the target optimization strategy adapts to the current device performance state.

[0107] Further, according to the to-be-optimized parameter identifier and the target optimization strategy, the fine adjustment instruction for the feeding rate and the crushing rotation speed in the ultrafine pulverizer is obtained, the correlation between the to-be-optimized parameter identifier and the feeding rate and the crushing rotation speed is analyzed first, for example, if the to-be-optimized parameter is that the exhaust particle concentration is too high, combined with the target optimization strategy, it is determined that the feeding rate needs to be reduced to reduce the material load, so as to reduce the exhaust particle concentration; if the to-be-optimized parameter is that the particle uniformity is too low, according to the target optimization strategy, it is determined that the crushing rotation speed needs to be adjusted to optimize the particle size distribution. Then, the adjustment range of the parameter is referred to the requirement in the target optimization strategy, the adjustment range is small under the "maintain current parameter fine-tuning optimization" strategy, the adjustment range is moderate under the "targeted parameter optimization" strategy, and the adjustment range is large under the "comprehensive parameter reset optimization" strategy. According to the correlation and the adjustment range requirement, the specific adjustment value of the feeding rate and the crushing rotation speed is determined, for example, the feeding rate is reduced by a certain range from the current value, and the crushing rotation speed is increased or decreased by a corresponding range, the adjustment value, the adjustment direction and the execution time are integrated to form the fine adjustment instruction for the feeding rate and the crushing rotation speed in the ultrafine pulverizer.

[0108] Further, the fine adjustment instruction is executed, and the particle characteristics of the output material are monitored, when the particle characteristics continuously remain in the preset compliance range, it is determined that the ultrafine pulverizer obtains the compliant material, the fine adjustment instruction is first transmitted to the control unit of the ultrafine pulverizer, the control unit drives the feeding device to adjust the feeding rate according to the instruction, and adjusts the crushing motor speed to match the adjusted crushing rotation speed, to ensure that the two parameters are executed according to the instruction. After the parameter adjustment, the particle characteristics of the material at the discharge port are monitored in real time by the particle analyzer, including the particle size distribution, the particle uniformity and other indexes, and the monitoring data is recorded at a fixed time interval. The particle characteristic data recorded each time is compared with the preset compliance range, if the data of one time is within the compliance range, the subsequent data is continuously monitored; if the particle characteristic data recorded for multiple times continuously are within the preset compliance range, and there is no fluctuation out of the range, it is indicated that the particle characteristics of the material have been stabilized and meet the requirements, so it is determined that the material currently produced by the ultrafine pulverizer is the compliant material; if the data still exceeds the compliance range during the monitoring process, the initial adjustment feedback data needs to be analyzed again, and the adjustment instruction is further optimized.

[0109] Specifically, according to the fine adjustment instruction, when adjusting the operating state of the ultrafine pulverizer, the specific adjustment values of the feeding rate and the pulverizing rotating speed and the execution time are extracted from the fine adjustment instruction, and the information is transmitted to the main control module of the ultrafine pulverizer. After receiving the instruction, the main control module sends an adjustment signal to the feeding driving device to control the motor speed of the feeding device, so that the material conveying speed reaches the required feeding rate of the instruction; at the same time, the main control module sends an adjustment signal to the pulverizing motor to change the output power of the motor, so that the rotating speed of the pulverizing component reaches the required pulverizing rotating speed of the instruction. During the adjustment process, the main control module collects the actual values of the feeding rate and the pulverizing rotating speed in real time, compares them with the required values of the instruction, and continuously sends a fine adjustment signal if there is a deviation, until the actual values and the required values of the instruction are consistent, to ensure that the operating state of the ultrafine pulverizer is accurately executed according to the fine adjustment instruction.

[0110] Further, when monitoring the particle characteristics of the material output by the ultrafine pulverizer after the adjustment of the operating state, and obtaining the particle characteristic monitoring data of the ultrafine pulverizer, a particle characteristic detection device is installed at the discharge port of the ultrafine pulverizer. The device includes an optical sensor and a data processing unit. The optical sensor emits light of a specific wavelength to irradiate the discharged material, and captures the size, shape and distribution of the material particles by receiving changes in reflected light and transmitted light; the data processing unit converts the optical signals collected by the sensor into identifiable particle characteristic parameters, including average particle size, particle size distribution range, particle uniformity, etc. The detection device continuously collects and processes data at a set time interval, generates a set of records containing various particle characteristic parameters every fixed time interval, and arranges all records in chronological order to form the particle characteristic monitoring data of the ultrafine pulverizer.

[0111] Further, when comparing the particle characteristic monitoring data with the preset compliance range to obtain the compliance judgment result of the material, the preset compliance range is first called from the system parameter library. The range is preset according to the application scene and quality standard of the material, and includes the qualified interval of the average particle size, the qualified interval of the particle size distribution range, the qualified interval of the particle uniformity, etc. Each parameter in the particle characteristic monitoring data is compared with the corresponding preset compliance range, and if a parameter is within the corresponding qualified interval, the parameter is marked as "compliant"; if a parameter exceeds the corresponding qualified interval, the parameter is marked as "non-compliant". For each set of monitoring data, the marking results of all parameters are summarized, and if all parameters are "compliant", the compliance judgment result corresponding to the set of data is "qualified"; if any parameter is "non-compliant", the compliance judgment result corresponding to the set of data is "unqualified". The judgment results of all groups are arranged in chronological order to form the compliance judgment result sequence of the material.

[0112] Further, when the compliance judgment result indicates that the particle characteristics continuously remain within the preset compliance range, and the material is confirmed to be a compliant material, the sequence of compliance judgment results is first checked, and the starting point of the continuous appearance of the "qualified" result is found from the sequence. The number of continuous appearance of the "qualified" result from the starting point is counted. If the number of continuous appearance of the "qualified" result reaches a preset judgment threshold, for example, the monitoring result is "qualified" for five times in a row, it indicates that the particle characteristics have been stably within the preset compliance range, and the material currently produced by the ultrafine grinder is determined to meet the quality requirements, and the material is confirmed to be a compliant material. After confirmation, the time of the first appearance of the continuous qualified result, the last monitoring particle characteristic data and the compliance judgment result are recorded as the proof of material qualification, and a signal is sent to the control module of the ultrafine grinder to maintain the current running state, so as to maintain the continuous production of compliant materials.

[0113] In summary, analyzing the initial adjustment feedback data to obtain the comprehensive performance evaluation level and the identification of the parameter to be optimized can accurately locate the overall state of the current operation of the equipment and the specific parameter that needs to be improved, avoid blind optimization, solve the problem of lack of clear optimization direction in the prior art, and provide a clear target for subsequent optimization.

[0114] In summary, selecting a target optimization strategy from a preset strategy library based on the comprehensive performance evaluation level can match the actual performance state of the equipment to select an adaptive optimization scheme, avoid the disconnection between the strategy and the working condition, improve the targeting of optimization, and solve the defect of insufficient flexibility of the fixed strategy.

[0115] In summary, generating fine adjustment instructions for the feed rate and the crushing rotational speed in combination with the identification of the parameter to be optimized and the target optimization strategy can achieve accurate regulation of key operating parameters, avoid over-regulation or under-regulation of parameters, and solve the problem of rough parameter adjustment in the prior art.

[0116] In summary, the compliant material is determined to be obtained only when the execution instructions are executed and the particle characteristics are continuously compliant, which can ensure that the quality of the produced material is stable and meets the standards, avoid misjudgment of temporary qualification, form a closed loop of optimization-monitoring-confirmation, improve the stability and reliability of the production of compliant materials, and solve the problem of difficult continuous production of compliant materials in the prior art.

[0117] In summary, adjusting the operating state of the ultrafine grinder according to the fine adjustment instructions can accurately respond to the optimization requirements, adjust the key parameters such as the feed rate and the crushing rotational speed to values suitable for the current working condition, avoid the disconnection between the parameters and the material processing requirements, solve the problem of rough parameter adjustment and mismatch with actual requirements in the prior art, and lay a parameter foundation for the production of compliant materials.

[0118] In summary, the particle characteristics of the adjusted material are monitored in real time, and monitoring data are obtained, so that the core quality indexes such as the particle size distribution and uniformity of the material can be dynamically mastered, and the problem of lag in material quality control in the prior art can be solved, and real-time data support for compliance judgment can be provided.

[0119] In summary, the particle characteristics monitoring data are compared with the preset compliance range to obtain a compliance judgment result, so that whether the material quality meets the standard can be objectively measured, the deviation caused by subjective judgment can be avoided, the problem of fuzzy quality judgment standard in the prior art can be solved, and the accuracy and consistency of the judgment result can be ensured.

[0120] In summary, the material is confirmed to be compliant only when the compliance judgment result indicates that the particle characteristics are continuously within the compliance range, so that the situation of temporarily meeting the standard and then deviating can be excluded, the stable and reliable quality of the output material can be ensured, the unstable 'qualified material' is avoided from being misjudged as compliant material, the problem that stable and qualified material is difficult to be continuously output in the prior art can be solved, and finally, the super-micro pulverizer can continuously output compliant material meeting the quality requirements.

[0121] In the several embodiments of the present application, it should be understood that the disclosed method and system can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. In actual implementation, other division manners can be adopted.

[0122] The modules described as separate components can or can not be physically separate, and the components displayed as modules can or can not be physical units, i.e., they can be located in one place, or distributed on multiple network units. According to actual needs, some or all of the modules can be selected to achieve the purpose of the embodiment.

[0123] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically independently, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of hardware plus software functional modules.

[0124] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0125] The embodiments of the present application can acquire and process related data based on artificial intelligence technology. The artificial intelligence is a theory, method, technology and application system for simulating, extending and expanding human intelligence by using a digital computer or a machine controlled by a digital computer, perceiving an environment, acquiring knowledge and using the knowledge to obtain optimal results.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A classification closed-loop dust removal linkage control method for an ultrafine pulverizer discharge, characterized by, The method comprises: S1, extracting the discharging state signal of the ultrafine pulverizer during discharging, to obtain the particle characteristic parameters of the ultrafine pulverizer; S2, based on the particle characteristic parameters, performing particle size classification analysis on the material to obtain the classification result of the material; S3, adjusting the operating parameters of the ultrafine pulverizer according to the particle concentration and particle size distribution of the material in the classification result; S4, based on the discharging state signal and the classification result, performing linkage control on the dust removal module; S5, obtaining the effect feedback signal of the dust removal module and the discharging quality feedback signal of the ultrafine pulverizer after adjustment, and performing data fusion on the effect feedback signal and the discharging quality feedback signal to obtain the initial adjustment feedback data of the ultrafine pulverizer; S6, according to the initial adjustment feedback data, re-optimizing the adjustment process of the ultrafine pulverizer in S4 to obtain the compliant material of the ultrafine pulverizer.

2. The classification closed loop dust removal linkage control method of the discharge of the supermicro pulverizer according to claim 1, characterized in that, The method comprises: Real-time acquisition of the discharging state signal of the ultrafine pulverizer to obtain the original monitoring signal of the ultrafine pulverizer; Removing the noise points in the original monitoring signal to obtain the purified discharging state signal of the ultrafine pulverizer; Extracting the particle concentration index and particle size distribution index of the material in the purified discharging state signal to obtain the particle characteristic parameters of the ultrafine pulverizer.

3. The classification closed loop dust removal linkage control method of the discharge of the supermicro pulverizer according to claim 1, characterized in that, The method comprises: Comparing the particle concentration index in the classification result with the preset concentration threshold to obtain the concentration evaluation result of the material; Comparing the preliminary classification judgment in the classification result with the preset size threshold to obtain the size evaluation result of the material; Based on the concentration evaluation result and the size evaluation result, determining the classification result of the material.

4. The classification closed loop dust removal linkage control method of an ultrafine pulverizer discharge according to claim 3, characterized in that, The calculation formula of the grading result is as follows: ; In the formula, is a grading index corresponding to the grading result, is a preset concentration coefficient, is a quantized value of the concentration evaluation result, is a preset size coefficient, is a quantized value of the size evaluation result.

5. The classification closed loop dust removal linkage control method of an ultrafine pulverizer discharge according to claim 1, characterized by, The method comprises: Based on the classification result, generating an adjustment instruction for the feeding rate of the ultrafine pulverizer; Based on the uniformity information of the particle size distribution in the classification result, generating an adjustment instruction for the pulverizing rotation speed of the ultrafine pulverizer; According to the adjustment instruction, synchronously adjusting the feeding rate and the pulverizing rotation speed to obtain the adjusted operating parameters.

6. The classification closed loop dust removal linkage control method of an ultrafine pulverizer discharge according to claim 1, characterized by, The method comprises: Analyzing the real-time particle concentration change trend in the discharging state signal to obtain the dynamic load evaluation of the material; According to the particle distribution uniformity level in the classification result, determining the dust removal intensity level required by the material; Based on the dynamic load evaluation and the dust removal intensity level, matching the target control mode from the preset linkage control mode; According to the target control mode, generating the start-stop instruction and power adjustment instruction of the dust removal module, and simultaneously starting the linkage control process of the dust removal module according to the start-stop instruction and power adjustment instruction.

7. The closed loop dust removal linkage control method of the discharge of the supermicro pulverizer according to claim 1, characterized in that, The effect feedback signal of the dust removal module and the discharge quality feedback signal of the ultrafine grinder after adjustment are acquired, data fusion is performed on the effect feedback signal and the discharge quality feedback signal to obtain initial adjustment feedback data of the ultrafine grinder, and the method comprises the following steps: According to the dust removal state data of the exhaust particle concentration and the airflow resistance of the dust removal module, the effect feedback signal of the dust removal module is generated; According to the quality state data of the discharge particle uniformity and the output rate of the material, the discharge quality feedback signal of the ultrafine grinder after adjustment is generated; The dust removal state data and the quality state data are subjected to time alignment processing to obtain a synchronous feedback data set of the ultrafine grinder; The synchronous feedback data set is subjected to weighted fusion processing to obtain the initial adjustment feedback data of the ultrafine grinder.

8. The classification closed loop dust removal linkage control method of an ultrafine pulverizer discharge according to claim 7, characterized in that, The synchronous feedback data set is subjected to weighted fusion processing to obtain the initial adjustment feedback data of the ultrafine grinder, which comprises the following steps: Exhaust particle concentration indicators, airflow resistance indicators, material particle uniformity indicators and output rate indicators are extracted from the synchronous feedback data set; The exhaust particle concentration index, the airflow resistance index, the material particle uniformity index and the production rate index are weighted and fused to obtain a fusion index value of the supermicro pulverizer, wherein a calculation formula of the fusion index value is as follows: ; In the formula, is the fusion index value, is a particle concentration coefficient calibrated based on historical data, is the exhaust particle concentration index, is an air flow resistance coefficient calibrated based on historical data, is the air flow resistance index, is a particle uniformity coefficient calibrated based on historical data, is the material particle uniformity index, is a production rate coefficient calibrated based on historical data, is the production rate index; Based on the comparison of the fusion index value and the preset threshold value, a fusion evaluation result of the synchronous feedback data set is obtained, and the initial adjustment feedback data of the ultrafine grinder is generated according to the fusion evaluation result.

9. The classification closed loop dust removal linkage control method of the discharge of the supermicro pulverizer according to claim 1, characterized in that, According to the initial adjustment feedback data, the adjustment process of the ultrafine grinder in S4 is re-optimized to obtain compliant material of the ultrafine grinder, which comprises the following steps: The initial adjustment feedback data is analyzed to obtain a comprehensive performance evaluation level and a to-be-optimized parameter identifier; Based on the comprehensive performance evaluation level, a target optimization strategy is selected from a preset optimization strategy library; According to the to-be-optimized parameter identifier and the target optimization strategy, a fine adjustment instruction for the feeding rate and the crushing rotational speed of the ultrafine grinder is obtained; The fine adjustment instruction is executed, and the particle characteristics of the output material are monitored. When the particle characteristics continuously remain within a preset compliance range, it is determined that the ultrafine grinder obtains compliant material.

10. The classification closed loop dust removal linkage control method of an ultrafine pulverizer discharge according to claim 9, characterized by, The fine adjustment instruction is executed, and the particle characteristics of the output material are monitored. When the particle characteristics continuously remain within a preset compliance range, it is determined that the ultrafine grinder obtains compliant material, which comprises the following steps: According to the fine adjustment instruction, the operating state of the ultrafine grinder is adjusted; The particle characteristics of the material output by the ultrafine grinder after the operating state is adjusted are monitored in real time to obtain particle characteristic monitoring data of the ultrafine grinder; The particle characteristic monitoring data is compared with a preset compliance range to obtain a compliance judgment result of the material; When the compliance judgment result indicates that the particle characteristics continuously remain within the preset compliance range, it is confirmed that the material is compliant material.

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