Automatic control method and device for hydraulic loading force of coal mill

Abstract

The application discloses a kind of automatic control method and device of hydraulic loading force of coal mill, it is related to coal mill control technical field.The present application includes parameter detection, PLC control, hydraulic execution and self-learning storage module, can collect many dimensions parameters such as grindability coefficient, stone coal coal content.Control method first according to grindability coefficient of coal kind determines loading force reference value, then combines stone coal coal content correction coefficient and coal kind characteristic correction coefficient, dynamically calculates target loading force, realizes self-adapting adjustment by PID closed-loop control, simultaneously has fault emergency algorithm and self-learning update function.The present application breaks through the limitation of prior art, solves the problems such as coal kind adaptation lag, single parameter, fault response deficiency, and is fast in response, easy to operate, high in reliability, suitable for the efficient and stable operation of various coal mills.

Description

Technical Field

[0001] This invention relates to the field of coal mill control technology, and in particular to an automatic control method and device for hydraulic loading force of a coal mill. Background Technology

[0002] Coal mills, as crucial fuel preparation equipment in thermal power generation and coal chemical industries, are widely used in coal crushing and pulverization. In related technologies, a traditional hydraulic loading force control system is constructed through the coordinated operation of fixed loading force and coal grinding quantity feedback. Specifically, this system covers the entire process from coal type characteristic detection to loading force adjustment, including key aspects such as grindability coefficient detection, PID control algorithms, and hydraulic actuators. With the development of industrial intelligence, existing technologies are gradually introducing multi-parameter detection and closed-loop control, but a complete dynamic adaptation system for coal quality characteristics and loading force has not yet been formed, and technical bottlenecks such as simple control logic and lag in response still exist.

[0003] However, existing hydraulic loading force control methods for coal mills directly use a fixed loading force combined with grinding volume feedback adjustment, without taking the coal grindability coefficient as a core input parameter. This may lead to deviations in the loading force benchmark setting. Specifically, when the coal type changes from... Switching from soft coal to When grinding hard coal, a fixed loading force results in insufficient grinding, increasing the coal content of the coking coal by more than 30%. Meanwhile, the manual adjustment method, due to a lag time of 1-2 hours, leads to an 8%-12% increase in unit coal consumption. The detection system only focuses on the grinding rate or the fineness of the pulverized coal at the outlet, failing to incorporate parameters such as the coking coal content, coal moisture / ash content, etc., into the control logic. When the moisture content of the coal fluctuates... At times, the coal mill efficiency fluctuated by up to 28%. Among these issues, the lack of a fault redundancy mechanism was particularly prominent. When the detection unit failed, it directly switched to manual mode without any emergency replacement algorithm, which could easily lead to overload or insufficient output of the coal mill, affecting the stable operation of the unit. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] Therefore, the first objective of this invention is to provide an automatic control method for hydraulic loading force in a coal mill.

[0006] Another objective of this invention is to provide an automatic control device for hydraulic loading force of a coal mill.

[0007] The third objective of this invention is to provide a computer device.

[0008] A fourth objective of this invention is to provide a non-transitory computer-readable storage medium.

[0009] To achieve the above objectives, a first aspect of the present invention provides an automatic control method for hydraulic loading force of a coal mill, comprising: S1 collects parameters such as the grindability coefficient, coal content, moisture, ash content, and hardness of the coal type, and determines the validity of each parameter data; if any parameter is missing or abnormal, an emergency substitution algorithm is activated to generate a temporary substitution value based on historical data or the correlation between parameters. S2, based on the grindability coefficient of coal, query the preset coal type-loading force mapping table, and use the piecewise linear interpolation method to calculate the loading force benchmark value; S3, combining the coal content of the stone coal and the coal type characteristic parameters, the stone coal correction coefficient and the coal type characteristic correction coefficient are generated by the dynamic correction model respectively, and the target loading force is obtained by multiplying the correction coefficients with the loading force benchmark value; S4 adjusts the hydraulic actuator through a PID closed-loop control algorithm to keep the deviation between the actual loading force and the target loading force within a preset range, and continuously monitors the coal milling efficiency and the coal content of the stone coal during operation.

[0010] In one embodiment of the present invention, S1 includes: S11, When a malfunction is detected in the coal grindability coefficient (HGI) detector, the formula is used. Generate a temporary HGI value, where M is the moisture content of the coal and H is the hardness of the coal. S12, if the detection data deviation exceeds 10% or the missing time exceeds 5s, an audible and visual alarm signal is triggered. The alarm signal frequency is 1Hz and the duration is ≥30s.

[0011] In one embodiment of the present invention, S2 includes: S21, when HGI∈[20,40], use the formula Calculate the baseline value of the applied force; S22, when HGI∈[80,120], use the formula Calculate the baseline value of the applied force.

[0012] In one embodiment of the present invention, S3 includes: S31, the calculation of the correction factor K1 for gravel and coal uses a double threshold logic: when C>8%, When C < 3%, Where C0=8%, C1=3%, k1=0.5, k2=0.3; S32, the coal type characteristic correction coefficient K2 is calculated using the formula... Where M is moisture, A is ash, and H is hardness.

[0013] In one embodiment of the present invention, S4 includes: S41, the PID control parameters are set as follows: proportional coefficient Kp = 1.2-2.0, integral time Ti = 0.5-2.0s, derivative time Td = 0.1-0.5s; S42, the deviation between the actual loading force and the target loading force is controlled within... Within the MPa range, and with a steady-state error not exceeding 12%.

[0014] To achieve the above objectives, a second aspect of the present invention provides an automatic control device for hydraulic loading force of a coal mill, comprising: The parameter acquisition and validity judgment module is used to collect parameters such as the grindability coefficient of coal, coal content of stone coal, moisture, ash content and hardness, and to judge the validity of each parameter data. If any parameter is found to be missing or abnormal, the emergency substitution algorithm is activated to generate a temporary substitution value based on historical data or the correlation between parameters. The coal type-loading force mapping table query module is used to query the preset coal type-loading force mapping table based on the coal type grindability coefficient, and calculates the loading force benchmark value using a piecewise linear interpolation method; The dynamic correction coefficient generation module is used to combine the coal content of the stone coal and the coal type characteristic parameters, generate the stone coal correction coefficient and the coal type characteristic correction coefficient respectively through the dynamic correction model, and multiply the correction coefficient with the loading force benchmark value to obtain the target loading force; The PID parameter adjustment and deviation control module is used to adjust the hydraulic actuator through the PID closed-loop control algorithm, so that the deviation between the actual loading force and the target loading force is controlled within the preset range, and the grinding efficiency and coal content of the stone coal are continuously monitored during operation.

[0015] The present invention discloses an automatic control method and device for hydraulic loading force of a coal mill, which can realize multi-parameter dynamic adaptive control of hydraulic loading force of the coal mill, significantly improve coal grinding efficiency and reduce unit coal consumption, and at the same time have fault redundancy and self-learning optimization functions, thereby improving the stability and control accuracy of system operation.

[0016] To achieve the above objectives, a third aspect of this application provides a computer device comprising a processor and a memory; wherein the processor runs a program corresponding to the executable program code stored in the memory, for implementing an automatic control method for hydraulic loading force of a coal mill as described in the first aspect embodiment.

[0017] To achieve the above objectives, the fourth aspect of this application provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements an automatic control method for hydraulic loading force of a coal mill as described in the first aspect embodiment.

[0018] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] Figure 1 This is a flowchart of an automatic control method for hydraulic loading force of a coal mill according to an embodiment of the present invention; Figure 2 This is a structural diagram of an automatic control device for hydraulic loading force of a coal mill according to an embodiment of the present invention; Figure 3 It is a computer device according to an embodiment of the present invention. Detailed Implementation

[0020] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

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

[0022] The following description, with reference to the accompanying drawings, describes an automatic control method and apparatus for hydraulic loading force of a coal mill according to an embodiment of the present invention.

[0023] Example 1 Figure 1 This is a flowchart of an automatic control method for hydraulic loading force of a coal mill according to an embodiment of the present invention, such as... Figure 1 As shown, it includes: S1 collects parameters such as the grindability coefficient, coal content, moisture, ash content, and hardness of the coal type, and determines the validity of each parameter data.

[0024] Specifically, in the automatic control method for hydraulic loading force of the coal mill of the present invention, parameter acquisition and validity judgment are the fundamental links for realizing intelligent control. Its technical implementation involves the synchronous acquisition of multi-source heterogeneous data, data integrity verification, and anomaly handling mechanisms. This step uses a multi-parameter detection module deployed at the coal mill inlet or coal bunker outlet to acquire physical property parameters such as the grindability coefficient of the coal type, coal content (C), moisture (M), ash content (A), and hardness (H) in real time. Specifically, HGI is measured online using an HGI-800 detector with a detection range of 20-120 HGI, an accuracy of ±2 HGI, and a response time ≤3s. The coal content of the coal is detected by an automatic sampling device in conjunction with a laser particle size analyzer, with a sampling frequency of 5 minutes / time, a particle size resolution range of 0.1-10mm, a data transmission rate of 100Mbps, and a bit error rate ≤10%. -6 Moisture and ash content were measured using a near-infrared spectroscopy instrument with a detection range of 0-30% and 5-40% respectively, with an accuracy of ±0.5%; hardness was measured using an ultrasonic hardness tester with a range of 50-100 HRB and an accuracy of ±1 HRB.

[0025] Furthermore, the system monitors the data output by each sensor in real time through a signal detection circuit. If a parameter fails to update within 5 consecutive seconds or deviates from historical data by more than 10%, the data is deemed invalid, triggering an emergency replacement mechanism. For example, when the HGI detector malfunctions, the system uses a linear combination formula of ash content and hardness. Estimate temporary HGI values ​​to maintain the continuity of control logic. Simultaneously, the system uses audible and visual alarms (such as flashing red lights and a 1Hz buzzer) to alert operators for inspection and maintenance.

[0026] Furthermore, this step, through high-precision sensors and a rigorous data validity judgment mechanism, ensures the reliability and representativeness of the input data for subsequent calculations of the loading force benchmark value, generation of dynamic correction coefficients, and PID closed-loop control. This improves the operating efficiency of the coal mill, reduces energy consumption, and extends equipment life. In practical industrial scenarios, this step is applicable to systems requiring continuous and efficient coal grinding, such as thermal power generation and coal chemical industries. Especially when coal types are frequently switched or occasional equipment failures occur, it can effectively prevent the coal mill from experiencing operational instability or equipment damage due to control signal distortion.

[0027] Furthermore, S1 includes: S11, When a malfunction is detected in the coal grindability coefficient detector, the formula is used. Generate a temporary HGI value, where M is the moisture content of the coal and H is the hardness of the coal.

[0028] Specifically, in some implementations, when the coal grindability coefficient detector malfunctions, the present invention uses a formula... Temporary HGI values ​​are generated to ensure the continuous operation of the coal mill's hydraulic loading force control system. This step belongs to the emergency algorithm part of the fault diagnosis module, and its technical implementation is based on the moisture content of the coal. and hardness The real-time detection data of the two key parameters are used to estimate the HGI value through a linear combination, thereby avoiding control failure caused by HGI detection interruption.

[0029] Furthermore, HGI is a key indicator for measuring the grindability of coal; the higher the value, the easier the coal is to grind. In actual operation, HGI is correlated with the moisture content and hardness of coal. This invention uses historical data modeling to determine the linear influence weights of moisture and hardness on HGI, where the influence coefficient of moisture on HGI is 1.2, and the influence coefficient of hardness is 0.8. This formula is applicable to short-term alternative calculations when the HGI detector malfunctions, ensuring that the system can still adjust the loading force based on a reasonably estimated HGI value.

[0030] Furthermore, moisture The detection range is 0-30%, with an accuracy of ±0.5%, provided by a near-infrared detector; hardness The detection range is 50-100 HRB, with an accuracy of ±1 HRB, achieved using an ultrasonic hardness tester. The coefficients 1.2 and 0.8 in the formula are derived from regression analysis of a large number of coal samples, demonstrating strong engineering applicability. The value will serve as the baseline value for subsequent loading forces. The input participates in the dynamic correction coefficient. and The calculation.

[0031] Furthermore, this step primarily addresses the issue of missing HGI values ​​caused by sensor failure, signal interruption, or data anomalies in the HGI detector. When the detector malfunction lasts for more than 5 seconds or the data deviation exceeds 10%, the fault diagnosis module will automatically trigger this emergency algorithm to generate a temporary HGI value using the current coal type's moisture and hardness data, ensuring the continuity of the coal mill's hydraulic loading force control logic. This mechanism is particularly suitable for industrial scenarios such as thermal power plants and coal chemical plants, where high grinding efficiency and system stability are required.

[0032] Furthermore, this step can maintain the loading force control accuracy of the coal mill in the event of an HGI detection interruption, avoiding a decrease in grinding efficiency or equipment overload due to the loss of control signals. According to the test results of Example 3, this emergency algorithm maintained the grinding efficiency at over 98% of normal operating conditions and controlled the coal content of the coke to below 6.2% during a 30-minute fault period, significantly outperforming the performance of existing technologies where efficiency drops below 75% in manual mode. Therefore, this step not only improves the system's fault tolerance but also enhances the operational stability and economy of the coal mill under complex operating conditions.

[0033] S12, if the detection data deviation exceeds 10% or the missing time exceeds 5s, an audible and visual alarm signal is triggered. The alarm signal frequency is 1Hz and the duration is ≥30s.

[0034] Specifically, in the automatic control method for hydraulic loading force of the coal mill of the present invention, the step "if the detected data deviation exceeds 10% or the missing time exceeds 5s, trigger an audible and visual alarm signal, the alarm signal frequency is 1Hz and the duration is ≥30s" ensures that the control logic can maintain basic operating performance in the event of abnormal or missing data by monitoring the data quality of the parameter detection module in real time, and promptly issues an alarm to the operator to ensure system safety and operational stability.

[0035] Furthermore, this step relies on the signal detection circuit in the fault diagnosis module, which determines the validity of data through timestamp comparison and numerical fluctuation analysis. Specifically, the system sets the data update cycle to 3 seconds. If a parameter (such as HGI, C, M, A, H) does not receive valid data within 5 consecutive seconds, it is determined to be missing data; if the received data deviates from the previous valid value by more than 10%, it meets the requirement of... If the data is abnormal, the system will trigger an alarm mechanism and output an alarm signal through the audible and visual alarm unit.

[0036] Furthermore, the alarm signal frequency is set to 1Hz, i.e., one pulse signal per second, to ensure that operators can clearly perceive the alarm status. The alarm duration is set to ≥30 seconds to avoid false alarms caused by momentary interference, while ensuring sufficient time to attract attention. The alarm signal output methods may include flashing red LEDs, buzzer sounds, etc., which comply with the requirements of the IEC60204-1 standard for indicating abnormal equipment status in industrial control.

[0037] Furthermore, this step applies to situations such as coal type switching, detection equipment failure, or communication interruption in coal mills, ensuring that the system can maintain basic control logic even when data is abnormal. For example, when the HGI detector loses data due to dust blockage, the system will immediately trigger an audible and visual alarm and simultaneously activate an emergency alternative algorithm, such as using the average value of the previous 10 minutes or an estimation formula based on ash content and hardness. In order to maintain control accuracy.

[0038] Furthermore, by setting clear alarm thresholds and response mechanisms, this step enables the system to provide timely feedback when data anomalies occur, preventing control deviations caused by erroneous data. Simultaneously, the frequency and duration of alarm signals are designed to balance the perceptibility of human-machine interaction with the timeliness of system response, ensuring that operators can intervene in the shortest possible time. This avoids problems such as decreased coal grinding efficiency, equipment overload, or abnormal coal content in the coke, ensuring the stable operation of the coal mill under complex working conditions.

[0039] S2. Based on the grindability coefficient of the coal type, query the preset coal type-loading force mapping table, and calculate the loading force benchmark value using a piecewise linear interpolation method.

[0040] Specifically, in some implementations, a preset coal type-loading force mapping table is consulted based on the coal type's grindability coefficient, and a piecewise linear interpolation method is used to calculate the loading force reference value. The technology is based on the nonlinear relationship between the physical properties of coal and the hydraulic loading force during the operation of the coal mill. This step establishes a mapping model between coal grindability and loading force to achieve a dynamic benchmark setting for the hydraulic loading force of the coal mill, thereby providing a basic input for subsequent dynamic correction and PID closed-loop control.

[0041] Furthermore, the control unit first receives the HGI value from the parameter detection module. This value is acquired in real time by the HGI-800 online detector, with a detection range of 20-120 HGI, an accuracy of ±2 HGI, and a response time of ≤3 seconds. Based on the range of the HGI value, the control unit selects the corresponding linear interpolation formula from the pre-stored coal type-loading force mapping table. The mapping table contains the correspondence between HGI and optimal loading force for more than 100 coal types (such as bituminous coal, anthracite, and lignite), and is divided into three ranges according to the HGI value: [20,40] (hard coal), [40,80] (medium-hard coal), and [80,120] (soft coal).

[0042] Furthermore, the output of this step The load reference value is in MPa, and its calculation result must meet the physical limitations of the coal mill hydraulic system, i.e. Where 6MPa is the minimum loading force and 16MPa is the maximum loading force (calibrated according to the ZGM113G coal mill). If the calculated result exceeds this range, the control unit will automatically truncate to the boundary value to ensure the safe operation of the system.

[0043] Furthermore, this step is widely applicable to coal grinding systems in thermal power generation, coal chemical industry, and other fields. Especially under conditions of frequent coal type switching or significant coal quality fluctuations, it can quickly respond and provide a reasonable loading force benchmark, avoiding problems such as decreased grinding efficiency and increased energy consumption caused by fixed loading forces or manual adjustments. For example, under the conditions of bituminous coal (HGI=55) or lignite (HGI=90), this step can calculate benchmark loading forces of 18.25 MPa and 20.96 MPa respectively, providing a basis for subsequent adjustments.

[0044] Furthermore, this step significantly improves the accuracy and adaptability of the loading force benchmark value by introducing a piecewise linear interpolation method. Compared with existing fixed loading force control, the coal grinding efficiency is increased by 15.6%, and the unit coal consumption is reduced by 8.3%. Compared with manual adjustment, the response time is shortened from 1-2 hours to ≤5 seconds, and the system stability is significantly enhanced. In addition, this step provides the foundation for subsequent dynamic correction coefficient calculation and is a key link in realizing integrated control of "multi-parameter linkage - real-time feedback - fault redundancy".

[0045] Furthermore, S2 includes: S21, when HGI∈[20,40], use the formula Calculate the baseline value of the applied force.

[0046] Specifically, in some implementations, when the grindability coefficient of the coal is in the range [20, 40], it indicates that the coal is hard coal, which is difficult to grind and requires increasing the loading force to ensure sufficient grinding. In this case, the control unit uses the formula... To calculate the benchmark value of the loading force The unit is megapascals (MPa). This formula is based on modeling the mechanical response characteristics of the coal mill hydraulic system to hard coal, and reflects the quantitative relationship between HGI and the required loading force through a linear relationship.

[0047] Further, this step is executed by the PLC controller (model S7-1500, operation speed 0.1μs / instruction). It first obtains the HGI value of the current coal type from the parameter detection module, which uses an HGI-800 online detector with a detection range of 20-120 HGI, an accuracy of ±2 HGI, and a response time ≤3 seconds. When the detected HGI value falls within the [20,40] range, the controller calls the formula to calculate the baseline loading force. The coefficients 0.3 and the constant 6 in the formula are derived through fitting of a large amount of experimental data, aiming to ensure grinding efficiency while avoiding overload risks.

[0048] Furthermore, this formula is applicable to hard coal conditions with HGI values ​​between 20 and 40, and the calculation results are... Usually in Within the range. Due to the safety limits of the coal mill hydraulic system, the actual loading force... It will be further corrected by the coefficient. and Make dynamic adjustments and ultimately limit it to Within the range (based on the ZGM113G coal mill calibration).

[0049] Furthermore, this step responds quickly and adjusts the loading benchmark value when coal type changes or coal quality fluctuates. For example, in hard coal conditions such as lignite or anthracite, this formula can effectively improve grinding efficiency and reduce the content of coking coal, thereby reducing energy consumption and equipment wear.

[0050] Furthermore, this step achieves initial adaptation of the loading force through HGI-based linear mapping, providing a reliable base value for subsequent dynamic correction and PID closed-loop control. Compared to fixed loading force control, this method can improve grinding efficiency by 15.6%, reduce unit coal consumption by 8.3%, and significantly extend the life of grinding roller liners under hard coal conditions.

[0051] S22, when HGI∈[80,120], use the formula Calculate the baseline value of the applied force.

[0052] Specifically, in the control method of the present invention, when the grindability coefficient of the coal is in the range [80, 120], the formula is used. Calculate the reference value of the applied force This formula is based on the grindability characteristics of coal and uses a linear mapping relationship to convert the HGI value into an initial loading force reference value, thereby providing a basic input for subsequent dynamic correction and PID closed-loop control.

[0053] Further, this step is executed by the loading force mapping model in the PLC control unit. In practice, the parameter detection module collects the HGI value of the coal type in real time, and the control unit first determines whether this value falls within the [80, 120] interval. If the condition is met, the formula is called for calculation. The coefficients in the formula... and constant term It is derived through fitting of a large amount of experimental data, and is applicable to soft coal types, effectively reflecting the minimum loading force required during coal grinding. For example, when hour, This value serves as the benchmark for subsequent correction factor calculations.

[0054] Furthermore, the formula outputs The unit is megapascals (MPa), and the calculated results need to be compared with the upper and lower limits of the loading force set by the system. According to the calibration of the coal mill model ZGM113G, the forced limit range of the loading force is... If the calculated result exceeds this range, the boundary value is taken as a temporary benchmark. Furthermore, the HGI detection accuracy is ±2HGI, and the response time is ≤3 seconds, ensuring the real-time performance and accuracy of the benchmark value.

[0055] Furthermore, this step is widely applicable to coal grinding systems in industries such as thermal power generation and coal chemical engineering, especially under conditions of frequent coal type switching or large fluctuations in coal quality. Through this formula, the system can quickly respond to changes in coal type, avoiding a decrease in grinding efficiency or accelerated equipment wear caused by improper loading force settings.

[0056] Furthermore, this step provides a stable basis for the subsequent dynamic correction coefficients (K1, K2), thereby improving the adaptability of the coal mill under different coal types. For example, in Example 2, when the HGI is 92, the formula calculated... After incorporating the correction coefficient, the final loading force was controlled at 17.25 MPa, effectively reducing unit coal consumption and improving grinding efficiency. This step significantly enhanced the control accuracy and stability of the grinding system under complex operating conditions, demonstrating the core value of this invention in the integrated control scheme of "multi-parameter linkage - real-time feedback - fault redundancy".

[0057] S3. Combining the coal content and coal type characteristic parameters of the stone coal, the correction coefficient of the stone coal and the correction coefficient of the coal type characteristic are generated by the dynamic correction model, and the target loading force is obtained by multiplying the correction coefficients with the loading force benchmark value.

[0058] Specifically, in some implementations, the present invention generates correction coefficients for stone coal using a dynamic correction model. Coal type characteristic correction coefficient and compare it with the loading force benchmark value. Multiply to obtain the target loading force This step is based on modeling the nonlinear relationship between coal grindability, the content of gravelly coal, and coal quality parameters (such as moisture, ash, and hardness), thereby enabling precise adjustment of the loading force.

[0059] Furthermore, the correction coefficient for stone coal The calculation depends on the coal content of the stone coal. Comparison with preset thresholds C_0=8% and C_1=3%. When When the time is right, it indicates that the coal grinding is insufficient and the loading force needs to be increased. The correction factor is: ,in For gain coefficient; when When this occurs, it indicates that the coal is relatively soft and there is a risk of excessive compression; the correction factor is [value missing]. ,in The loss coefficient; when When, correction factor , indicating that no adjustment is needed.

[0060] Furthermore, the coal content of the stone coal The particle size is determined by a combination of an automatic sampling device and a laser particle size analyzer. Sampling occurs every 5 minutes, the particle size resolution range is 0.1-10 mm, the data transmission rate is 100 Mbps, and the bit error rate is ≤ . Coal moisture and ash Measured by a near-infrared spectrometer, with detection ranges of 0-30% and 5-40%, and an accuracy of ±0.5%. Hardness Measured by an ultrasonic hardness tester, range 50-100 HRB, accuracy ±1 HRB. Correction factor. and All calculations are performed in the PLC controller (model S7-1500, operation speed 0.1μs / instruction) to ensure real-time performance and calculation accuracy.

[0061] Furthermore, this step is applicable to coal grinding systems in thermal power generation, coal chemical industry, and other fields, especially under conditions of frequent coal type switching or large fluctuations in coal quality, which can significantly improve grinding efficiency and reduce energy consumption. For example, under bituminous coal conditions, when HGI is 55, C is 10%, M is 12%, A is 25%, and H is 65HRB, the correction factor is... , Target loading force Finally, the hydraulic system is controlled to adjust the loading force to 16MPa to ensure sufficient coal grinding and stable equipment operation.

[0062] Furthermore, this step effectively solves the problem of loading force mismatch caused by changes in coal type characteristics in traditional control methods by introducing a multi-parameter dynamic correction mechanism. Experimental data show that compared with fixed loading force control, the present invention has significant improvements in key indicators such as unit coal consumption, grinding efficiency, and coal content in stone coal, while also possessing good fault redundancy capability, ensuring that the system can maintain high operating efficiency even when the detection unit fails.

[0063] Furthermore, S3 includes: S31, the calculation of the correction factor K1 for gravel and coal uses a double threshold logic: when C>8%, When C < 3%, , where C0=8%, C1=3%, k1=0.5, k2=0.3.

[0064] Specifically, in the automatic control method for hydraulic loading force of coal mill of the present invention, the calculation of the stone coal correction coefficient K1 adopts dual threshold logic to adapt to the change of stone coal content C of different coal types during the coal grinding process, thereby optimizing coal grinding efficiency and reducing stone coal emissions.

[0065] Furthermore, when the coal content C of the stone coal is greater than the benchmark value C0 (set to 8%), it indicates that there are insufficiently ground coal particles in the coal grinding process, which may be due to the high hardness of the coal or insufficient current loading force.

[0066] Furthermore, this correction mechanism, based on real-time feedback of coal powder particle size and coal content data, combined with a laser particle size analyzer and an automatic sampling device, achieves high-precision detection every 5 minutes (particle size resolution 0.1-10mm, data transmission rate up to 100Mbps, bit error rate ≤10%). -6 In the PLC controller (model S7-1500, operation speed 0.1μs / instruction), the calculation result of K1 will work together with F0 and K2 to generate the final target loading force F, thereby ensuring that the coal mill can maintain the optimal operating state when switching between different coal types.

[0067] Furthermore, this step, through the introduction of parameterized design of C0 and k1, enables the system to adapt to changes in coal grindability, effectively reducing the coal content of gravelly coal, improving grinding efficiency, and reducing energy consumption. In practical applications, this correction logic is suitable for industrial scenarios such as thermal power generation and coal chemical industry, and can significantly improve system stability and economy, especially under conditions of frequent coal type switching or large fluctuations in coal quality.

[0068] S32, the coal type characteristic correction coefficient K2 is calculated using the formula... Where M is moisture, A is ash, and H is hardness.

[0069] Specifically, in some implementations, the coal type characteristic correction coefficient The calculation is used to finely adjust the hydraulic loading force of the coal mill to adapt to the dynamic changes in moisture (M), ash (A), and hardness (H) of the coal. This correction factor further improves the energy efficiency ratio and equipment operation stability of the coal milling process by quantifying the impact of the physicochemical properties of the coal on the grinding resistance and grinding efficiency.

[0070] Furthermore, this formula is calculated in real time based on multi-parameter detection results for different coal types. Here, M represents the moisture content of the coal (in %), A represents the ash content (in %), and H represents the hardness of the coal (in HRB, Rockwell hardness). The ratio of moisture to ash content... This reflects the caking properties and grinding difficulty of coal. Higher moisture content and lower ash content make coal more prone to caking, thus increasing grinding resistance; while hardness... This directly affects the grindability of coal; the higher the hardness, the greater the energy required for grinding. In the formula, Used to compensate for the effects of changes in the caking properties of coal. This is used to adjust for changes in loading force requirements caused by the coal hardness deviating from the benchmark value (50HRB).

[0071] Furthermore, this correction factor The value range is limited to [0.9, 1.3] to ensure that the loading force adjustment remains within a reasonable range even when the coal characteristics change significantly. For example, when the coal hardness is 65 HRB, moisture content is 12%, and ash content is 25%, This indicates that the characteristics of coal have little impact on the loading force, and the system can maintain a control strategy close to the benchmark value.

[0072] Furthermore, this correction factor is widely used in coal grinding systems in thermal power generation, coal chemical industry, and other fields. Especially under conditions of frequent coal type switching or large fluctuations in coal quality, it can significantly improve grinding efficiency and reduce stone coal emissions. For example, in lignite conditions, due to its high moisture and low ash content... The value is large, resulting in This increases the loading force to overcome the caking properties of coal and prevent incomplete grinding.

[0073] Furthermore, the introduction of this correction coefficient effectively compensates for the deficiency of traditional control methods in neglecting the multi-parameter linkage of coal types, and realizes dynamic optimization of loading force. By combining... and With two correction coefficients, the system can perform closed-loop feedback control on key variables in the coal grinding process, thereby maintaining high grinding efficiency and low unit energy consumption under different coal types. Furthermore, this method maintains control accuracy even when coal hardness varies significantly, avoiding equipment wear and energy waste caused by insufficient or overloaded loading, thus improving the intelligence level and operational reliability of the coal grinding system.

[0074] S4 adjusts the hydraulic actuator through a PID closed-loop control algorithm to keep the deviation between the actual loading force and the target loading force within a preset range, and continuously monitors the coal milling efficiency and the coal content of the stone coal during operation.

[0075] Specifically, in the control method of this invention, the hydraulic actuator is adjusted through a PID closed-loop control algorithm to achieve high-precision dynamic control of the loading force on the coal mill. This step is the core of the entire control system, and its technical implementation is based on classical PID control theory, combined with the dynamic response characteristics of the hydraulic system, to ensure the actual loading force. With target loading force The deviation is always controlled within the preset range, that is... This ensures the stability and energy efficiency of the coal grinding process.

[0076] Furthermore, the PID controller consists of three parts: proportional (P), integral (I), and derivative (D), and its control signal output is:

[0077] in, This is the error signal at the current moment. For proportional gain, The integral time constant is... The time constant is the differential. In this invention, the PID parameters are set as follows: , , The specific values ​​can be automatically adjusted online according to the coal mill model and coal type characteristics.

[0078] Furthermore, the hydraulic actuator consists of a proportional relief valve, a loading cylinder, and a pressure sensor. The control unit receives the target loading force. The control signal is calculated using the PID algorithm. The proportional relief valve is driven to regulate the oil pressure, causing the loading cylinder to output a corresponding loading force. The pressure sensor provides real-time feedback. This leads to the control unit, forming a closed-loop control system.

[0079] Furthermore, this step continuously monitors the coal milling efficiency (t / h) and the coal content of the rough coal (%), and optimizes the PID parameters using a self-learning module. For example, when switching coal types or experiencing sudden changes in operating conditions, the PID controller can respond quickly, restoring the coal mill from a suboptimal state to a stable operating range, with the response time shortened to [time missing]. It is significantly better than the 1-2 hour lag time that is manually adjusted.

[0080] Furthermore, this step, through high-precision closed-loop control, effectively suppresses the impact of loading force fluctuations on coal grinding efficiency and equipment lifespan. The steady-state error is controlled within... Under these conditions, coal grinding efficiency is increased by 15.6%, unit coal consumption is reduced by 8.3%, and the coal content of gravel coal is significantly reduced, improving coal utilization and extending the life of grinding roller liners. Furthermore, this PID control strategy, combined with emergency algorithms and self-learning mechanisms, enhances the system's robustness and adaptability under complex operating conditions and fault states, achieving the integrated control objective of "multi-parameter linkage - real-time feedback - fault redundancy".

[0081] Furthermore, S4 includes: S41, the PID control parameters are set as follows: proportional coefficient Kp = 1.2-2.0, integral time Ti = 0.5-2.0s, derivative time Td = 0.1-0.5s.

[0082] Specifically, in the control method of the present invention, the setting of PID control parameters is achieved by reasonably configuring the proportional coefficient. Integral Time Differential time This ensures that the system achieves a balance between dynamic response and steady-state accuracy, thereby improving the operating efficiency and stability of the coal mill.

[0083] Furthermore, the PID controller employs a standard continuous-time control algorithm, and its control output... It consists of three parts: proportion, integral, and differential, and its expression is:

[0084] in, For setting value With actual loading force deviation, that is Proportional term Used for rapid response deviation, integral term Used to eliminate steady-state error, differential term Used to suppress system overshoot and oscillation. In this invention, the proportional coefficient... Set as To ensure the system has high sensitivity to changes in coal type; integral time Set as To balance the adjustment speed with the risk of integral saturation; differential time Set as It is used to enhance the system's ability to suppress transient changes and prevent drastic adjustments in loading force caused by fluctuations in coal quality.

[0085] Furthermore, the proportionality coefficient The value range has been experimentally verified and is suitable for adjusting the loading force of different coal types. Integral time The settings take into account the hysteresis characteristics of the coal grinding process to avoid excessive integral action leading to system instability. Differential time The value is relatively small, mainly used to smooth the control signal and reduce system oscillations caused by sudden changes in coal quality. The control accuracy requirement is steady-state error. The corresponding error rate is no more than 12%, which meets the basic requirements for the accuracy of loading force in industrial control.

[0086] Furthermore, this PID control strategy is integrated into the PLC control unit, working in conjunction with hydraulic actuators (such as proportional relief valves and loading cylinders) to achieve real-time closed-loop regulation of the hydraulic loading force of the coal mill. It is suitable for typical equipment such as the ZGM113G medium-speed coal mill and the MQY3200×4500 ball mill, exhibiting excellent adaptability and stability, especially under conditions of frequent coal type switching and large fluctuations in coal quality parameters.

[0087] Furthermore, this step, through precise PID parameter configuration, enables the system to... The response adjustment of the applied force is completed internally, which is significantly better than traditional manual adjustment. Response time. Simultaneously, improved control precision helps reduce the coal content in coke, increases grinding efficiency, lowers unit coal consumption, and extends equipment life. Furthermore, this PID control module, in conjunction with a self-learning mechanism and fault emergency algorithm, forms a closed-loop linkage, enhancing the system's robustness and reliability under complex operating conditions. This is the core support for achieving integrated control of "multi-parameter linkage - real-time feedback - fault redundancy" in this invention.

[0088] S42, the deviation between the actual loading force and the target loading force is controlled within... Within the MPa range, and with a steady-state error not exceeding 12%.

[0089] Specifically, in the control method of this invention, "the deviation between the actual loading force and the target loading force is controlled within..." "Within the MPa range and with a steady-state error not exceeding 12%" is the core element for achieving high-precision closed-loop control of the hydraulic loading force in a coal mill. This step, based on a PID (proportional-integral-derivative) control algorithm and combined with the dynamic response characteristics of the hydraulic system, ensures that the loading force converges quickly and stably to the target value within the set range, thereby improving coal grinding efficiency and extending equipment life.

[0090] Furthermore, this step involves adjusting the oil pressure via a proportional relief valve in the hydraulic actuator, so that the force output by the loading cylinder gradually approaches the target loading force. The pressure sensor collects the actual applied force in real time. This data is then fed back to the PLC control unit (model S7-1500, processing speed 0.1μs / instruction). The control unit processes the data according to the preset PID parameters (proportional coefficient). Integral time s, differential time s) Calculate the control signal and drive the proportional relief valve to perform dynamic adjustment to achieve closed-loop control.

[0091] Furthermore, this step requires that the absolute deviation between the actual applied force and the target applied force does not exceed 0.5 MPa, i.e. The target load is 17.72 MPa, while the steady-state error does not exceed 12%. This indicator ensures that the system has sufficient accuracy and stability during dynamic adjustment, avoiding a decrease in coal grinding efficiency or increased equipment wear due to excessive fluctuations in loading force. For example, in Example 1, the target loading force is 17.72 MPa, which is eventually stabilized at 16 MPa through PID control, with a deviation of 1.72 MPa, which does not exceed the set threshold of 0.5 MPa, indicating that the system has good control accuracy.

[0092] Furthermore, this step is widely applicable to coal grinding systems in industries such as thermal power generation and coal chemical engineering, especially under conditions of frequent coal type switching and large fluctuations in coal quality parameters. Through real-time feedback and PID control, the system can respond to changes in coal type within 5 seconds and restore grinding efficiency to optimal levels within 5-10 minutes, significantly better than the 1-2 hour response time of traditional manual adjustment methods. In addition, this step works in conjunction with a fault diagnosis module; when the detection unit malfunctions, the system can still maintain control accuracy through emergency algorithms, ensuring the continuous and stable operation of the coal mill.

[0093] Furthermore, this step enables high-precision control of the hydraulic loading force, effectively reducing the coal content in the coking coal, improving grinding efficiency, and reducing unit coal consumption. In Example 1, the grinding efficiency increased from 45 t / h to 52 t / h, the unit coal consumption decreased from 18 kWh / t to 16.5 kWh / t, and the coking coal content decreased from 12% to 5.2%. These data fully demonstrate the significant value of this step in improving system performance, reducing energy consumption, and enhancing operational reliability.

[0094] The dynamic control method for hydraulic loading force of coal mill in this invention can dynamically adapt to changes in coal characteristics, achieve precise control of hydraulic loading force of coal mill, significantly reduce coal content and unit coal consumption in stone coal, and improve coal milling efficiency and equipment operation reliability.

[0095] Example 2 This invention discloses an automatic control device and method for hydraulic loading force of a coal mill, relating to the field of coal mill control technology. The device includes a parameter detection module (containing multi-parameter detection units for grindability coefficient, coal content in rough stone, and coal type), a PLC control unit, a hydraulic execution unit, and a self-learning storage module. The control method determines the loading force reference value by collecting the coal grindability coefficient (HGI), dynamically calculates the target loading force by combining the coal content correction coefficient and the coal type characteristic correction coefficient, and achieves adaptive adjustment of the loading force through PID closed-loop control. The connection relationship of each module is shown in Table 1. Table 1

[0096] Furthermore, parameter acquisition and validity judgment: The parameter detection module acquires HGI, C (coal content of gravel), M (moisture), A (ash content), and H (hardness), and the fault diagnosis module judges the validity of the data - if a single parameter is missing for more than 5 seconds, an emergency replacement is triggered (such as estimating a temporary HGI by "ash content × 1.2 + hardness × 0.8" when HGI is missing), and at the same time, an audible and visual alarm is triggered; Further, the load reference value F0 is calculated as follows: The control unit queries the mapping table of the storage module and calculates F0 using linear interpolation: When HGI∈[20,40] (hard coal): F0= 0.3×HGI + 6 (MPa); when HGI∈[40,80] (medium-hard coal): F0= 0.15×HGI + 10 (MPa); when HGI∈[80,120] (soft coal): F0= 0.08×HGI + 13.6 (MPa); Furthermore, the dynamic correction coefficient is calculated (supplementing the ash-moisture interaction term): Correction factor K1 for gravel and coal: K1 = 1 + (C - C0) / C0 × k1 (C > C0 = 8%, k1 = 0.5, to avoid insufficient grinding of hard coal). K1 = 1 - (C1 - C) / C1 × k2 (C < C1 = 3%, k2 = 0.3, to avoid excessive compression of soft coal). K1=1 (3%≤C≤8%) Coal type characteristic correction factor K2: K2 = 0.9 + 0.02×(M / A) + 0.005×(H-50) (M / A is the moisture-ash ratio, H is the hardness HRB), with a value range of 0.9-1.3; Furthermore, the calculation of the target loading force F and the safety limit are as follows: F = F0×K1×K2, and F is forcibly limited to [Fmin=6MPa, Fmax=16MPa] (calibrated according to the coal mill model ZGM113G). Furthermore, PID closed-loop control: After the actuator adjusts the oil pressure, the pressure sensor feeds back Factual, and the control unit adjusts it through the PID algorithm to make |Factual - F| ≤ 0.5MPa (steady-state error ≤ 2%). Furthermore, self-learning updates: every 100 hours of operation, the control unit compares the "actual coal grinding efficiency (kWh / t of electricity consumption per ton of coal) and coal content of gravel coal" with the theoretical values ​​in the mapping table. If the error is >5%, the coefficients in the F0 calculation formula are automatically corrected (e.g., the F0 coefficient in the hard coal range is adjusted from 0.3 to 0.32).

[0097] The embodiments of the present invention also have the following technical effects: A comparison with existing fixed loading force control is shown in Table 2: Table 2

[0098] Compared to manual adjustment: Response time: reduced from 1-2 hours to ≤5 seconds; mill stabilization time during coal type switching reduced from 30 minutes to 5 minutes; Operational intensity: no manual sampling, calculation, or adjustment required, reducing maintenance personnel's workload by 60%; Interference resistance: when coal moisture content fluctuates by ±5%, the milling efficiency fluctuation of this invention is ≤3%, while that of existing technologies is ≥8%. Fault redundancy advantage: when the grindability coefficient detector malfunctions, this invention maintains milling efficiency ≥90% through an emergency algorithm, while the efficiency of existing technologies drops below 75% after manual switching, avoiding unit load fluctuations >5%.

[0099] Example 3 To achieve the above embodiments, such as Figure 2 As shown, this embodiment also provides an automatic control device 10 for hydraulic loading force of a coal mill, comprising: The parameter acquisition and validity judgment module 100 is used to acquire parameters such as the grindability coefficient of coal, coal content of stone coal, moisture, ash content and hardness, and to judge the validity of each parameter data. If any parameter is detected to be missing or abnormal, the emergency substitution algorithm is activated to generate a temporary substitution value based on historical data or the correlation between parameters. The coal type-loading force mapping table query module 200 is used to query the preset coal type-loading force mapping table according to the coal type grindability coefficient, and calculate the loading force benchmark value using a piecewise linear interpolation method; The dynamic correction coefficient generation module 300 is used to combine the coal content of the stone coal and the coal type characteristic parameters, generate the stone coal correction coefficient and the coal type characteristic correction coefficient respectively through the dynamic correction model, and multiply the correction coefficient with the loading force reference value to obtain the target loading force; The PID parameter adjustment and deviation control module 400 is used to adjust the hydraulic actuator through the PID closed-loop control algorithm so that the deviation between the actual loading force and the target loading force is controlled within a preset range, and the grinding efficiency and coal content of the stone coal are continuously monitored during operation.

[0100] Furthermore, the parameter acquisition and validity judgment module 100 is also used for: When a malfunction is detected in the coal grindability coefficient detector, the formula is used. Generate a temporary HGI value, where M is the moisture content of the coal and H is the hardness of the coal. If the detection data deviation exceeds 10% or the missing time exceeds 5 seconds, an audible and visual alarm signal will be triggered. The alarm signal frequency is 1Hz and the duration is ≥30 seconds.

[0101] Furthermore, the coal type-loading force mapping table query module 200 is also used for: When HGI∈[20,40], the formula is used. Calculate the baseline value of the applied force; When HGI∈[80,120], the formula is used. Calculate the baseline value of the applied force.

[0102] An automatic control device for hydraulic loading force of a coal mill according to an embodiment of the present invention can realize multi-parameter dynamic adaptive control of hydraulic loading force of the coal mill, significantly improve coal grinding efficiency and reduce unit coal consumption, and at the same time have fault redundancy and self-learning optimization functions, improving the stability and control accuracy of system operation.

[0103] Example 4 To implement the methods of the above embodiments, the present invention also provides a computer device, such as... Figure 3 As shown, the computer device 600 includes a memory 601 and a processor 602; wherein, the processor 602 reads the executable program code stored in the memory 601 to run a program corresponding to the executable program code, so as to implement the various steps of the automatic control method for hydraulic loading force of a coal mill described above.

[0104] Example 5 To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements an automatic control method for hydraulic loading force of a coal mill as described in the foregoing embodiments.

[0105] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0106] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. An automatic control method for hydraulic loading force in a coal mill, characterized in that, include: S1 collects parameters such as the grindability coefficient, coal content, moisture, ash content, and hardness of the coal type, and determines the validity of each parameter data; if any parameter is missing or abnormal, an emergency substitution algorithm is activated to generate a temporary substitution value based on historical data or the correlation between parameters. S2, based on the grindability coefficient of coal, query the preset coal type-loading force mapping table, and use the piecewise linear interpolation method to calculate the loading force benchmark value; S3, combining the coal content of the stone coal and the coal type characteristic parameters, the stone coal correction coefficient and the coal type characteristic correction coefficient are generated by the dynamic correction model respectively, and the target loading force is obtained by multiplying the correction coefficients with the loading force benchmark value; S4 adjusts the hydraulic actuator through a PID closed-loop control algorithm to keep the deviation between the actual loading force and the target loading force within a preset range, and continuously monitors the coal milling efficiency and the coal content of the stone coal during operation.

2. The method as described in claim 1, characterized in that, S1 includes: S11, When a malfunction is detected in the coal grindability coefficient detector, the formula is used. Generate a temporary HGI value, where M is the moisture content of the coal and H is the hardness of the coal. S12, if the detection data deviation exceeds 10% or the missing time exceeds 5s, an audible and visual alarm signal is triggered. The alarm signal frequency is 1Hz and the duration is ≥30s.

3. The method as described in claim 1, characterized in that, S2 includes: S21, when HGI∈[20,40], use the formula Calculate the baseline value of the applied force; S22, when HGI∈[80,120], use the formula Calculate the baseline value of the applied force.

4. The method as described in claim 1, characterized in that, The S3 includes: S31, the calculation of the correction factor K1 for gravel and coal uses a double threshold logic: when C>8%, When C < 3%, Where C0=8%, C1=3%, k1=0.5, k2=0.3; S32, the calculation of the coal type characteristic correction coefficient K2 adopts the formula Where M is moisture, A is ash, and H is hardness.

5. The method as described in claim 1, characterized in that, The S4 includes: S41, the PID control parameters are set as follows: proportional coefficient Kp = 1.2-2.0, integral time Ti = 0.5-2.0s, derivative time Td = 0.1-0.5s; S42, the deviation between the actual loading force and the target loading force is controlled within... Within the MPa range, and with a steady-state error not exceeding 12%.

6. An automatic control device for hydraulic loading force of a coal mill, characterized in that, include: The parameter acquisition and validity judgment module is used to collect parameters such as the grindability coefficient of coal, coal content of stone coal, moisture, ash content and hardness, and to judge the validity of each parameter data. If any parameter is found to be missing or abnormal, the emergency substitution algorithm is activated to generate a temporary substitution value based on historical data or the correlation between parameters. The coal type-loading force mapping table query module is used to query the preset coal type-loading force mapping table based on the coal type grindability coefficient, and calculates the loading force benchmark value using a piecewise linear interpolation method; The dynamic correction coefficient generation module is used to combine the coal content of the stone coal and the coal type characteristic parameters, generate the stone coal correction coefficient and the coal type characteristic correction coefficient respectively through the dynamic correction model, and multiply the correction coefficient with the loading force benchmark value to obtain the target loading force; The PID parameter adjustment and deviation control module is used to adjust the hydraulic actuator through the PID closed-loop control algorithm, so that the deviation between the actual loading force and the target loading force is controlled within the preset range, and the grinding efficiency and coal content of the stone coal are continuously monitored during operation.

7. The apparatus as claimed in claim 6, characterized in that, The parameter acquisition and validity judgment module is also used for: When a malfunction is detected in the coal grindability coefficient detector, the formula is used. Generate a temporary HGI value, where M is the moisture content of the coal and H is the hardness of the coal. If the detection data deviation exceeds 10% or the missing time exceeds 5 seconds, an audible and visual alarm signal will be triggered. The alarm signal frequency is 1Hz and the duration is ≥30 seconds.

8. The apparatus as claimed in claim 6, characterized in that, The coal type-loading force mapping table query module is also used for: When HGI∈[20,40], the formula is used. Calculate the baseline value of the applied force; When HGI∈[80,120], the formula is used. Calculate the baseline value of the applied force.

9. A computer device, characterized in that, Including processor and memory; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the automatic control method for hydraulic loading force of a coal mill as described in any one of claims 1-5.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements an automatic control method for hydraulic loading force of a coal mill as described in any one of claims 1-5.

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