State early warning method, device and equipment based on fuel quantity of coal mill and medium

Abstract

The application discloses a coal mill fuel quantity-based state early warning method and device, equipment and medium, relates to the computer technical field, and includes: if the coal mill meets the normal operation scene, the coal mill load air door opening, the coal mill inlet mixed primary air pressure and the coal mill drive end material level are respectively converted, the coal mill primary air quantity is converted into the initial fuel quantity, and the target fuel quantity is determined in combination with the correction coefficient output by the target model; if the shutdown scene is met, the target fuel quantity is determined based on the first initial value of the attenuation coefficient of the shutdown stage and the shutdown cumulative time; if the start-up scene is met, the target fuel quantity is determined based on the second initial value of the rising coefficient of the start-up stage and the start-up cumulative time; the target deviation of the target fuel quantity and the reference fuel quantity is used to diagnose the state of the coal mill, and the state diagnosis result is used for phase early warning operation. The calculation accuracy of the coal mill fuel quantity is improved, and the abnormal state of the coal mill is early warned.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, device, equipment, and medium for early warning of the status of coal mill fuel quantity. Background Technology

[0002] AGC (Automatic Generation Control) is an intelligent energy management system for the power grid. The AGC activation rate is a crucial indicator for evaluating a large power generation company's grid control capabilities, impacting grid security and stability, and ultimately affecting the overall economic performance of the power generation company. When AGC is activated, the start-up and shutdown phases of dual-inlet, dual-outlet coal mills can experience significant disturbances in boiler fuel quantity due to false material levels, leading to substantial fluctuations in the unit's main steam pressure and temperature. This, in turn, affects unit load control, and in severe cases, forces operators to disconnect the coordinated control, discontinue AGC operation, and manually intervene in the operating conditions.

[0003] Current implementation solutions: In coal-fired power plant boiler pulverizing systems, precise control of the amount of fuel entering the boiler is crucial for ensuring stable combustion, improving efficiency, and reducing emissions. Currently, the common practice is to automate the fuel quantity control displayed on the pulverizing system screen and obtain the instantaneous fuel quantity of a single coal mill through indirect calculation. Taking the drive end as an example, a common calculation method is: Coal mill drive end fuel quantity = F (calculated value of primary air volume at the coal mill drive end); the calculated value of primary air volume is derived from multiple parameters such as the coal mill inlet mixing primary air pressure, drive end material level, and drive end load damper opening through the function F. Existing solutions employ multi-layered indirect calculations, relying on the theoretical or empirical relationship between primary air volume and fuel quantity, resulting in a long error chain and large cumulative errors, especially with significant decreases in accuracy due to changes in coal quality and equipment wear. Secondly, the control models are mostly static or simply modified, lacking self-learning and adaptive capabilities, and unable to adapt to complex real-time operating conditions. Finally, existing methods only serve instantaneous control, failing to fully utilize the rich information in the calculation process, and cannot effectively assess and warn of the coal mill's own operational health status, resulting in limited functionality.

[0004] As can be seen from the above, improving the accuracy of coal mill fuel quantity calculation and providing early warning of abnormal conditions of coal mills are urgent problems to be solved. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method, device, equipment, and medium for early warning of the status of coal mill fuel quantity, which can improve the accuracy of coal mill fuel quantity calculation and provide early warning of abnormal conditions of the coal mill. The specific solution is as follows: Firstly, this application provides a method for early warning of the status of coal mill fuel quantity, including: If the coal mill meets the preset normal operation scenario, then based on each preset reference table, the coal mill load damper opening, coal mill inlet mixing primary air pressure, and coal mill drive end material level are converted into the corresponding damper air volume, air pressure coefficient, and material level coefficient; the preset normal operation scenario is that the coal mill is running and any coal feeder is running. The primary air volume of the coal mill is determined using the damper air volume, the air pressure coefficient, and the material level coefficient. The primary air volume of the coal mill is converted into an initial fuel quantity. A target model is constructed based on the equipment state parameters and target auxiliary parameters of the coal mill and using a gradient boosting tree. The target fuel quantity is determined using the correction coefficients output by the target model and the initial fuel quantity. If the coal mill meets the preset shutdown scenario, then the first target curve of the attenuation coefficient is determined based on the first initial value of the attenuation coefficient corresponding to the coal mill in the shutdown stage, the first preset time constant and the cumulative shutdown time. The rate of change of the first target curve is limited to obtain the target attenuation coefficient. The target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient. If the coal mill meets the preset start-up scenario, then the second target curve of the rise coefficient is determined based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up stage, the second preset time constant, and the cumulative start-up time. The rate of change of the second target curve is limited to obtain the target rise coefficient. The target fuel quantity is determined using the initial fuel quantity and the target rise coefficient. The state of the coal mill is diagnosed based on the target deviation between the target fuel quantity and the reference fuel quantity to obtain the corresponding state diagnosis results, and the corresponding early warning operations are performed using the state diagnosis results.

[0006] Optionally, if the coal mill meets the preset normal operation scenario, then based on each preset reference table, the coal mill load damper opening, the coal mill inlet mixing primary air pressure, and the coal mill drive end material level are converted into corresponding damper air volume, air pressure coefficient, and material level coefficient, including: If the coal mill meets the preset normal operation scenario, the coal mill load damper opening is converted into damper converted air volume based on the first preset comparison table, the coal mill inlet mixing primary air pressure is converted into air pressure conversion coefficient using the second preset comparison table, and the coal mill drive end material level is converted into material level conversion coefficient based on the third preset comparison table.

[0007] Optionally, the step of determining the primary air volume of the coal mill using the damper air volume, the air pressure coefficient, and the material level coefficient, converting the primary air volume of the coal mill into an initial fuel quantity, constructing a target model based on the equipment state parameters and target auxiliary parameters of the coal mill using a gradient boosting tree, and determining the target fuel quantity using the correction coefficients output by the target model and the initial fuel quantity includes: The primary air volume of the coal mill is determined using the damper air volume, the air pressure coefficient, and the material level coefficient. The primary air volume of the coal mill is then converted into the initial fuel quantity using the fourth preset reference table. Based on the equipment status parameters and target auxiliary parameters of the coal mill, a target model is constructed using a gradient boosting tree. The equipment status parameters include the main motor current of the coal mill, the bearing temperature of the reducer, and the vibration of the coal mill body. The target auxiliary parameters include the feeder speed / command, coal quality test data, and coal powder concentration measurement values. The target model is used to determine the correction coefficients, and the target fuel quantity is determined based on the initial fuel quantity and the correction coefficients.

[0008] Optionally, if the coal mill meets a preset shutdown scenario, then based on the first initial value of the attenuation coefficient corresponding to the coal mill during the shutdown phase, the first preset time constant, and the cumulative shutdown time, a first target curve of the attenuation coefficient is determined; the rate of change of the first target curve is limited to obtain a target attenuation coefficient; and the target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient, including: If the coal mill meets the preset shutdown scenario, then the first initial value of the attenuation coefficient corresponding to the shutdown stage is determined based on the first material level measurement value of the coal mill at the shutdown trigger time and the preset piecewise linear function. A first target curve for the attenuation coefficient is generated based on the first initial value, the cumulative downtime, and the first preset time constant. The first target curve is subjected to a rate of change limit using the first target descent rate and the first target ascent rate to obtain a target attenuation coefficient, and the target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient.

[0009] Optionally, if the coal mill meets a preset start-up scenario, then based on the second initial value of the rise coefficient corresponding to the coal mill during the start-up phase, the second preset time constant, and the cumulative start-up time, a second target curve of the rise coefficient is determined; the rate of change of the second target curve is limited to obtain a target rise coefficient; and the target fuel quantity is determined using the initial fuel quantity and the target rise coefficient, including: If the coal mill meets the preset start-up scenario, a start-up enable signal is generated based on the second material level value of the coal mill at the start-up trigger time and the current operating state of the coal mill. Determine a second initial value for the rise coefficient of the coal mill during the startup phase, and determine a second target curve for the rise coefficient based on the second initial value, a second preset time constant, and the cumulative startup time. The rate of change of the second target curve is limited by the mill start-up enable signal, the second target descent rate, and the second target ascent rate to obtain the target ascent coefficient. The target fuel quantity is then determined using the initial fuel quantity and the target ascent coefficient.

[0010] Optionally, the step of diagnosing the state of the coal mill based on the target deviation between the target fuel quantity and the reference fuel quantity to obtain a corresponding state diagnosis result, and using the state diagnosis result to perform corresponding early warning operations, includes: The reference fuel quantity is determined based on the total boiler air volume, flue gas oxygen content, and exhaust gas temperature using the inverse balance method. The real-time deviation and moving average deviation between the target fuel quantity and the reference fuel quantity are also determined. The analysis is based on the real-time deviation, the moving average deviation, and the target state parameters of the coal mill to obtain the corresponding analysis results; the target state parameters include current parameters, outlet temperature, coal mill load damper opening, and coal mill primary air volume. Based on the analysis results, the condition diagnosis results of the coal mill are determined, and corresponding early warning operations are performed using the condition diagnosis results.

[0011] Optionally, determining the condition diagnosis result of the coal mill based on the analysis results includes: The analysis results are judged based on a preset rule base to obtain the corresponding judgment result; If the determination result is that the moving average deviation meets the preset slow monotonically increasing trend and the current parameter meets the preset upward trend, then the condition diagnosis result of the coal mill is that the grinding roller of the coal mill is worn. If the determination result is that the real-time deviation meets the preset step increase trend and the outlet temperature is not within the preset temperature range, then the state diagnosis result of the coal mill is characterized as coal shortage or abnormal coal feeding. If the determination result is that the real-time deviation meets the preset fluctuation trend, and the opening of the coal mill load damper and the primary air volume of the coal mill both meet the preset change conditions, then the state diagnosis result of the coal mill is characterized as abnormal damper characteristics and / or failure of the primary air volume measuring element.

[0012] Secondly, this application provides a status early warning device based on the fuel quantity of a coal mill, comprising: The material level conversion module is used to convert the coal mill load damper opening, coal mill inlet mixing primary air pressure, and coal mill drive end material level into corresponding damper air volume, air pressure coefficient, and material level coefficient based on each preset reference table if the coal mill meets the preset normal operation scenario; the preset normal operation scenario is that the coal mill is running and any coal feeder is running. The first fuel quantity determination module is used to determine the primary air volume of the coal mill using the damper air volume, the air pressure coefficient and the material level coefficient, convert the primary air volume of the coal mill into an initial fuel quantity, construct a target model based on the equipment status parameters and target auxiliary parameters of the coal mill and using a gradient boosting tree, and determine the target fuel quantity using the correction coefficient output by the target model and the initial fuel quantity. The second fuel quantity determination module is used to determine a first target curve of the attenuation coefficient based on the first initial value of the attenuation coefficient corresponding to the coal mill in the shutdown stage, the first preset time constant and the cumulative shutdown time if the coal mill meets the preset shutdown scenario, and to limit the rate of change of the first target curve to obtain the target attenuation coefficient, and to determine the target fuel quantity based on the initial fuel quantity and the target attenuation coefficient. The third fuel quantity determination module is used to determine the second target curve of the rise coefficient based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up phase, the second preset time constant and the start-up cumulative time if the coal mill meets the preset start-up scenario, and to limit the rate of change of the second target curve to obtain the target rise coefficient, and to determine the target fuel quantity using the initial fuel quantity and the target rise coefficient. The status diagnosis module is used to diagnose the status of the coal mill based on the target deviation between the target fuel quantity and the reference fuel quantity, so as to obtain the corresponding status diagnosis results and to perform corresponding early warning operations using the status diagnosis results.

[0013] Thirdly, this application provides an electronic device, comprising: Memory, used to store computer programs; A processor is used to execute the computer program to implement the aforementioned method for early warning of coal mill fuel quantity status.

[0014] Fourthly, this application provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned state warning method based on the amount of fuel in a coal mill.

[0015] If the coal mill meets a preset normal operation scenario, this application converts the coal mill load damper opening, coal mill inlet mixing primary air pressure, and coal mill drive end material level into corresponding damper air volume, air pressure coefficient, and material level coefficient based on each preset reference table; the preset normal operation scenario is that the coal mill is running and any coal feeder is running; the coal mill primary air volume is determined using the damper air volume, the air pressure coefficient, and the material level coefficient, and the coal mill primary air volume is converted into initial fuel quantity; based on the coal mill's equipment state parameters and target auxiliary parameters, a target model is constructed using a gradient boosting tree; the target fuel quantity is determined using the correction coefficient output by the target model and the initial fuel quantity; if the coal mill meets a preset shutdown scenario, the first initial value and first preset time value of the attenuation coefficient corresponding to the coal mill during the shutdown stage are used to determine the target fuel quantity. The first target curve of the attenuation coefficient is determined by the time constant and the cumulative downtime. The rate of change of the first target curve is limited to obtain the target attenuation coefficient. The target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient. If the coal mill meets the preset start-up scenario, the second target curve of the rise coefficient is determined based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up stage, the second preset time constant, and the cumulative start-up time. The rate of change of the second target curve is limited to obtain the target rise coefficient. The target fuel quantity is determined using the initial fuel quantity and the target rise coefficient. The state of the coal mill is diagnosed based on the target deviation between the target fuel quantity and the reference fuel quantity to obtain the corresponding state diagnosis result. The corresponding early warning operation is performed using the state diagnosis result.

[0016] As can be seen from the above, under normal operating conditions of the coal mill, this application uses a reference table to convert the coal mill load damper opening, the coal mill inlet mixing primary air pressure, and the coal mill drive end material level into corresponding damper air volume, air pressure coefficient, and material level coefficient, thereby determining the primary air volume. The primary air volume is then converted into an initial fuel quantity. A target model constructed using a gradient boosting tree is used to determine the correction coefficient, and the target fuel quantity is determined based on the correction coefficient and the initial fuel quantity. Separate attenuation / rise coefficient target curves are set for the coal mill shutdown and startup scenarios, replacing the traditional... The algorithm directly applies the normal operating condition approach. In shutdown scenarios, the initial value corresponding to the coal inventory is used as the starting point for decay, mirroring the physical process of residual coal powder being gradually emptied by primary airflow, avoiding a sudden drop in fuel quantity caused by a direct zeroing. In startup scenarios, a time ramp is generated starting from a fixed initial value to avoid interference from false material levels in the initial startup phase, eliminating calculation jumps caused by material level distortion at the source. A rate of change limit is applied to the target curve to ensure smooth coefficients throughout the process without abrupt changes, preventing sudden fuel quantity commands and avoiding impact on the boiler combustion system. In this way, the target fuel quantity deviation from the reference fuel quantity is used as the core diagnostic basis to determine the mill's status diagnosis results, enabling corresponding early warnings. Maintenance plans can be scheduled in advance, avoiding unplanned shutdowns due to sudden failures, reducing maintenance and troubleshooting time, and lowering maintenance costs. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0018] Figure 1 This application discloses a flowchart of a state early warning method based on coal mill fuel quantity; Figure 2 This application discloses a first presupposed comparative representation intention; Figure 3 This application discloses a second presupposed comparative representation intention; Figure 4 This application discloses a third presuppositional comparison intention; Figure 5 This application discloses a fourth presuppositional comparison representation intention; Figure 6 This is a schematic diagram of the structure of a state early warning device based on the fuel quantity of a coal mill disclosed in this application; Figure 7 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Currently, the common practice is to automatically control the fuel quantity in the pulverizing system and obtain the instantaneous fuel quantity of a single coal mill through indirect calculation. Existing solutions employ multi-layered indirect calculations, relying on the theoretical or empirical relationship between primary air volume and fuel quantity, resulting in long error chains and large cumulative errors, with accuracy significantly decreasing, especially when coal quality changes or equipment wear occurs. Secondly, the control models are mostly static or simply modified, lacking self-learning and adaptive capabilities, and unable to adapt to complex real-time operating conditions. Finally, existing methods only serve instantaneous control, failing to fully utilize the rich information in the calculation process, and cannot effectively assess and warn of the coal mill's own operational health status, resulting in limited functionality. Therefore, this application provides a state early warning method based on coal mill fuel quantity. It uses the target deviation between the obtained target fuel quantity and the reference fuel quantity as the core diagnostic basis to determine the coal mill's state diagnosis result for corresponding early warning. This allows for advance scheduling of maintenance plans, avoiding unplanned downtime due to sudden failures, reducing maintenance and troubleshooting time, and lowering maintenance costs.

[0021] See Figure 1 As shown, this embodiment of the invention discloses a state early warning method based on the fuel quantity of a coal mill, including: Step S11: If the coal mill meets the preset normal operation scenario, then based on each preset reference table, the coal mill load damper opening, coal mill inlet mixing primary air pressure and coal mill drive end material level are converted into the corresponding damper air volume, air pressure coefficient and material level coefficient; the preset normal operation scenario is that the coal mill is running and any coal feeder is running.

[0022] In this embodiment, if the coal mill meets the preset normal operation scenario, that is, the coal mill is in operation and at least one coal feeder is in operation; the calculation method of the non-drive end is symmetrical and consistent with that of the drive end. Figure 2 As a first-preset reference representation, the reference table is calculated using piecewise linear interpolation. When the actual damper opening is at... Figure 2 When there are two adjacent inflection points, the corresponding equivalent air volume is calculated using a linear interpolation method. Figure 3This is a second pre-defined reference table, used to establish a functional mapping relationship between the primary air pressure at the coal mill inlet and the air pressure conversion factor. This table also uses piecewise linear interpolation. With 9 kPa as the baseline operating point, the conversion factor is 1; when the air pressure is below 9 kPa, the conversion factor is less than 1, and when the air pressure is above 9 kPa, the conversion factor is greater than 1, reflecting the correction effect of air pressure changes on the actual primary air conveying capacity. Figure 4 This is a third preset reference table, used to establish a functional mapping relationship between the coal mill drive end material level and the material level conversion factor. It should be noted that within the normal operating range of the coal mill, the impact of coal mill material level changes on the calculated fuel quantity is relatively small. Using a material level of 550mm as the benchmark, the conversion factor is 1; when the material level is below 550mm, the conversion factor is less than 1, and when the material level is above 550mm, the conversion factor is slightly greater than 1.

[0023] Specifically, if the coal mill meets the preset normal operation scenario, then based on each preset reference table, the coal mill load damper opening, the coal mill inlet mixing primary air pressure, and the coal mill drive end material level are converted into the corresponding damper air volume, air pressure coefficient, and material level coefficient, respectively. This includes: if the coal mill meets the preset normal operation scenario, then based on the first preset reference table, the coal mill load damper opening is converted into damper converted air volume; using the second preset reference table, the coal mill inlet mixing primary air pressure is converted into air pressure conversion coefficient; and based on the third preset reference table, the coal mill drive end material level is converted into material level conversion coefficient.

[0024] Step S12: Determine the primary air volume of the coal mill using the damper air volume, the air pressure coefficient, and the material level coefficient; convert the primary air volume of the coal mill into an initial fuel quantity; construct a target model based on the equipment state parameters and target auxiliary parameters of the coal mill using a gradient boosting tree; and determine the target fuel quantity using the correction coefficients output by the target model and the initial fuel quantity.

[0025] In this embodiment, the primary air volume of the coal mill is obtained by multiplying the damper air volume, the air pressure coefficient, and the material level coefficient. Then, the primary air volume of the coal mill is converted into the initial fuel quantity using a fourth preset lookup table. Figure 5 This fourth preset reference table represents a schematic diagram. It establishes a functional mapping relationship between the calculated primary air volume at the pulverizer drive end and the calculated fuel quantity at the pulverizer drive end, reflecting the pulverizing output capacity of the pulverizer under a specific air volume. In one specific embodiment, if the pulverizer primary air volume is 20.57 t / h, it falls between two inflection points of 14.7 t / h and 32 t / h. Through linear interpolation, the corresponding initial fuel quantity is calculated to be approximately 22.36 t / h.

[0026] Understandably, input parameters are constructed based on the equipment state parameters and target auxiliary parameters of the coal mill, and an intelligent correction model is built using the Gradient Boosting Decision Tree (GBDT) algorithm. The model is continuously updated using an online learning mechanism. Continuous parameter updates are performed using target auxiliary parameters (such as the coal feed rate estimated from the coal feeder speed and the coal powder concentration meter reading), enabling the model to automatically adapt to slow time-varying factors such as coal quality changes and equipment wear. Online learning employs an incremental learning approach, making only small adjustments each time to ensure model stability and safety, avoiding drastic model jumps. The gradient boosting tree is trained based on the input parameters to obtain the target model. The correction coefficients output by the target model are multiplied by the initial fuel quantity to obtain the target fuel quantity. This effectively compensates for the influence of dynamic factors that cannot be covered by static lookup tables, improving the accuracy of fuel quantity calculation.

[0027] Specifically, the process of determining the primary air volume of the coal mill using the damper air volume, the air pressure coefficient, and the material level coefficient; converting the primary air volume of the coal mill into an initial fuel quantity; constructing a target model based on the equipment status parameters and target auxiliary parameters of the coal mill using a gradient boosting tree; and determining the target fuel quantity using the correction coefficients output by the target model and the initial fuel quantity includes: determining the primary air volume of the coal mill using the damper air volume, the air pressure coefficient, and the material level coefficient; converting the primary air volume of the coal mill into an initial fuel quantity using a fourth preset lookup table; constructing a target model based on the equipment status parameters and target auxiliary parameters of the coal mill using a gradient boosting tree; the equipment status parameters include the main motor current of the coal mill, the reducer bearing temperature, and the vibration of the coal mill body; the target auxiliary parameters include the feeder speed / command, coal quality test data, and coal powder concentration measurement values; determining the correction coefficients using the target model; and determining the target fuel quantity based on the initial fuel quantity and the correction coefficients.

[0028] Step S13: If the coal mill meets the preset shutdown scenario, then the first target curve of the attenuation coefficient is determined based on the first initial value of the attenuation coefficient corresponding to the coal mill in the shutdown stage, the first preset time constant and the cumulative shutdown time. The rate of change of the first target curve is limited to obtain the target attenuation coefficient. The target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient.

[0029] In this embodiment, if the coal mill meets the preset shutdown scenario, the coal feeder is in a stopped state. A dynamic compensation model for shutdown conditions is introduced for refined simulation of fuel quantity during the coal mill shutdown phase. The first initial value of the attenuation coefficient during the shutdown phase is determined by the first material level measurement value P at the shutdown trigger moment through a preset piecewise linear function f(P). The first target curve corresponding to the attenuation coefficient is generated according to the following piecewise function: ; ; ; in, This refers to the first target curve; Pre-defined piecewise linear functions (multi-point polyline functions) for multiple inflection points (Xi, Yi) pre-stored within the control system; , This is the first preset time constant. It should be noted that before the grinding stops... Within seconds, the attenuation coefficient remains unchanged from its initial value, simulating the initial stage of mill shutdown where a significant amount of coal still remains in the mill; to During the time period, the attenuation coefficient linearly decreases from the initial value f(P) to 0, simulating the process of coal being gradually purged and emptied from the coal mill; when the time exceeds After that, the attenuation coefficient drops to 0, indicating that the coal stored in the coal mill has been basically emptied and there is no more fuel output.

[0030] Understandably, in order to ensure the stability of control and avoid drastic changes in the attenuation coefficient, the rate of change of the first target curve is limited to obtain the target attenuation coefficient. The dynamic characteristics of the rate of change limitation satisfy the following formula: ; ; ; ; in, The instantaneous rate of change of the mill shutdown rate, i.e., the mill shutdown rate. The first derivative with respect to time t; This refers to the first target curve; The first target is the rate of descent; The first target is the rate of increase; It is a predefined piecewise linear function; This refers to the shutdown rate corresponding to the shutdown time t=0. The target attenuation coefficient is defined as follows. The target attenuation coefficient gradually decreases from its initial value towards 0. The target attenuation coefficient is multiplied by the initial fuel quantity to obtain the target fuel quantity.

[0031] Specifically, if the coal mill meets a preset shutdown scenario, then a first target curve of the attenuation coefficient is determined based on a first initial value of the attenuation coefficient corresponding to the coal mill during the shutdown phase, a first preset time constant, and the cumulative shutdown time. The rate of change of the first target curve is limited to obtain a target attenuation coefficient. The target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient. This includes: if the coal mill meets a preset shutdown scenario, then a first initial value of the attenuation coefficient corresponding to the shutdown phase is determined based on a first material level measurement value of the coal mill at the shutdown trigger time and a preset piecewise linear function; a first target curve of the attenuation coefficient is generated based on the first initial value, the cumulative shutdown time, and the first preset time constant; the rate of change of the first target curve is limited using a first target descent rate and a first target ascent rate to obtain the target attenuation coefficient; and the target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient.

[0032] Step S14: If the coal mill meets the preset start-up scenario, then based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up stage, the second preset time constant, and the cumulative start-up time, determine the second target curve of the rise coefficient, limit the rate of change of the second target curve to obtain the target rise coefficient, and use the initial fuel quantity and the target rise coefficient to determine the target fuel quantity.

[0033] In this embodiment, when the coal mill meets the preset startup scenario, a dynamic compensation model for startup conditions is introduced for refined simulation of fuel quantity during the startup phase. When the material level meets the preset startup conditions and the coal mill is operating normally, S(t) = 1, allowing the rise coefficient to begin climbing; when the material level does not meet the conditions or an abnormal state occurs, S(t) = 0, and the rise coefficient is suppressed or returns to zero. The second initial value of the rise coefficient during the startup phase is 0, meaning that the rise coefficient starts climbing from 0 at the start of mill startup. The second target curve of the rise coefficient is a pure time ramp function, independent of the material level, and is generated according to the following piecewise function: ; ; ; in, The second target curve for the increase coefficient; , This is the second preset time constant. It should be noted that before the start of grinding... Within seconds, the ascent coefficient remains at 0, simulating the initial stage of a coal mill startup where material levels are established but stable pulverizing capacity has not yet been achieved; to During the time period, the coefficient of increase linearly rises from 0 to 1, simulating the process of a coal mill gradually building up its pulverizing capacity; when the time exceeds... Afterwards, the coefficient of increase reaches 1, indicating that the coal mill has entered normal operating condition.

[0034] It is understandable that the rate of change of the second target curve is limited to obtain the target rise coefficient. The rate of change limit is controlled by the mill start-up enable signal S(t). When S(t)=1, the dynamic characteristics satisfy the following formula: ; ; ; ; in, The instantaneous rate of change of the mill start-up rate, i.e., the mill start-up rate. The first derivative with respect to time t; The second target is the rate of increase; The second target is the rate of descent; This is the second target curve; The target increase coefficient; Let S(t) be the starting rate corresponding to the starting time t=0. When S(t)=0, it satisfies... This means the target rise coefficient is suppressed or returns to zero. When the start-up enable signal is valid, the rise coefficient tracks the target ramp curve at a limited rate; when the enable signal fails, the rise coefficient returns to zero at a limited rate, ensuring the safety and controllability of the start-up process. The target rise coefficient is multiplied by the initial fuel quantity to obtain the target fuel quantity.

[0035] Specifically, if the coal mill meets the preset start-up scenario, then based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up phase, the second preset time constant, and the cumulative start-up time, a second target curve of the rise coefficient is determined; the rate of change of the second target curve is limited to obtain the target rise coefficient; and the target fuel quantity is determined using the initial fuel quantity and the target rise coefficient. This includes: if the coal mill meets the preset start-up scenario, generating a start-up enable signal based on the second material level value of the coal mill at the start-up trigger time and the current operating state of the coal mill; determining the second initial value of the rise coefficient corresponding to the coal mill in the start-up phase; determining the second target curve of the rise coefficient based on the second initial value, the second preset time constant, and the cumulative start-up time; limiting the rate of change of the second target curve using the start-up enable signal, the second target descent rate, and the second target rise rate to obtain the target rise coefficient; and determining the target fuel quantity using the initial fuel quantity and the target rise coefficient.

[0036] It should be noted that during the actual start-up of the coal mill, the following operations should be coordinated to ensure a smooth and safe start-up process: (1) During the start-up of the coal mill, the primary air pressure should be kept stable and the opening speed of the coal mill load damper should be controlled; (2) When ventilating before the start-up of the coal mill, the opening of the coal mill load damper should be controlled to be no more than 20% and the opening of the coal mill bypass air should be more than 40%. The coal mill ventilation volume should be established through the coal mill hot primary air damper; (3) During the start-up of the coal mill to establish the material level, the opening of the coal mill load damper should be controlled to be no more than 20%. After the coal mill material level is established normally, the opening of the coal mill load damper should be adjusted to more than 30% according to the fuel quantity, and then automatic operation can be put into operation; (4) During the start-up of the coal mill, attention should be paid to monitoring the deviation between the boiler main control command and the actual fuel quantity. At the same time, the coal-water ratio matching should be comprehensively judged in conjunction with the changes in steam temperature and steam pressure to avoid coal-water ratio imbalance.

[0037] Step S15: Diagnose the state of the coal mill based on the target deviation between the target fuel quantity and the reference fuel quantity to obtain the corresponding state diagnosis result, and use the state diagnosis result to perform the corresponding early warning operation.

[0038] In this embodiment, the reference fuel quantity is calculated using the inverse balance method in boiler thermal balance. The inverse balance method is based on macroscopic operating parameters on the boiler side and is unaffected by measurement errors on the coal mill side; therefore, it can serve as a benchmark for evaluating the accuracy of the coal mill fuel quantity calculation. The input parameters for the reference fuel quantity include the total boiler air volume, flue gas oxygen content, and exhaust gas temperature. Specifically, by measuring the flue gas composition and temperature at the boiler outlet and combining this with the amount of air entering the furnace, the heat released by fuel combustion is calculated, and then converted into the total amount of fuel entering the furnace based on the calorific value of the fuel. The total fuel quantity is then allocated according to the operating status of each coal mill to obtain the reference fuel quantity for a single coal mill.

[0039] Understandably, the real-time deviation and moving average deviation are determined based on the target fuel quantity and reference fuel quantity at the current moment. The real-time deviation reflects the instantaneous difference between the target fuel quantity and the reference fuel quantity at the current moment. The moving average deviation is calculated by averaging the real-time deviation over a sliding window, with a window length of 24 hours, which can be adjusted according to actual conditions. The moving average deviation can filter out short-term random fluctuations and highlight the long-term trend of the deviation. Then, based on the real-time deviation, moving average deviation, and the target state parameters of the coal mill, a multivariate joint analysis is performed, and the analysis results are judged based on a preset rule base to identify the following three typical abnormal states of the coal mill.

[0040] Specifically, the process of diagnosing the state of the coal mill based on the target deviation between the target fuel quantity and the reference fuel quantity to obtain a corresponding state diagnosis result, and then using the state diagnosis result to perform corresponding early warning operations, includes: determining the reference fuel quantity based on the total boiler air volume, flue gas oxygen content, and exhaust gas temperature using the inverse balance method, and determining the real-time deviation and moving average deviation between the target fuel quantity and the reference fuel quantity; analyzing the real-time deviation, the moving average deviation, and the target state parameters of the coal mill to obtain corresponding analysis results; the target state parameters include current parameters, outlet temperature, coal mill load damper opening, and coal mill primary air volume; determining the state diagnosis result of the coal mill based on the analysis result, and then using the state diagnosis result to perform corresponding early warning operations.

[0041] Furthermore, abnormal conditions of the coal mill include grinding roller wear, coal shortage or abnormal coal feeding, and abnormal damper characteristics or primary air volume measurement element failure. First, grinding roller wear is determined by the moving average deviation showing a slow, monotonically increasing trend, and the current parameter showing an upward trend. Second, coal shortage or abnormal coal feeding is determined by the real-time deviation showing a step-increasing trend, and the outlet temperature being outside the preset temperature range, i.e., an abnormal rise. Finally, abnormal damper characteristics or primary air volume measurement element failure is determined by the real-time deviation showing a fluctuating trend, and significant changes in the coal mill load damper opening and the coal mill primary air volume. Based on different state diagnostic results, corresponding early warning operations are executed, including but not limited to: displaying alarm prompts on the DCS screen, showing the fault type and severity level; storing diagnostic results and related data in a historical database to form an equipment health record; triggering different levels of audible and visual alarms according to the severity of the fault; and pushing early warning information to the work terminals of operating and maintenance personnel to guide preventative maintenance.

[0042] Specifically, determining the state diagnosis result of the coal mill based on the analysis results includes: judging the analysis results based on a preset rule base to obtain corresponding judgment results; if the judgment result is that the moving average deviation meets a preset slow monotonically increasing trend and the current parameter meets a preset upward trend, then the state diagnosis result of the coal mill indicates that the grinding rollers of the coal mill are worn; if the judgment result is that the real-time deviation meets a preset step increase trend and the outlet temperature is not within a preset temperature range, then the state diagnosis result of the coal mill indicates that the coal mill is experiencing coal shortage or abnormal coal feeding; if the judgment result is that the real-time deviation meets a preset fluctuation trend and the opening of the coal mill load damper and the primary air volume of the coal mill both meet preset change conditions, then the state diagnosis result of the coal mill indicates that the damper characteristics are abnormal and / or the primary air volume measuring element is faulty.

[0043] As can be seen from the above, under normal operating conditions of the coal mill, this application uses a reference table to convert the coal mill load damper opening, the coal mill inlet mixing primary air pressure, and the coal mill drive end material level into corresponding damper air volume, air pressure coefficient, and material level coefficient, thereby determining the primary air volume. The primary air volume is then converted into an initial fuel quantity. A target model constructed using a gradient boosting tree is used to determine the correction coefficient, and the target fuel quantity is determined based on the correction coefficient and the initial fuel quantity. Separate attenuation / rise coefficient target curves are set for the coal mill shutdown and startup scenarios, replacing the traditional... The algorithm directly applies the normal operating condition approach. In shutdown scenarios, the initial value corresponding to the coal inventory is used as the starting point for decay, mirroring the physical process of residual coal powder being gradually emptied by primary airflow, avoiding a sudden drop in fuel quantity caused by a direct zeroing. In startup scenarios, a time ramp is generated starting from a fixed initial value to avoid interference from false material levels in the initial startup phase, eliminating calculation jumps caused by material level distortion at the source. A rate of change limit is applied to the target curve to ensure smooth coefficients throughout the process without abrupt changes, preventing sudden fuel quantity commands and avoiding impact on the boiler combustion system. In this way, the target fuel quantity deviation from the reference fuel quantity is used as the core diagnostic basis to determine the mill's status diagnosis results, enabling corresponding early warnings. Maintenance plans can be scheduled in advance, avoiding unplanned shutdowns due to sudden failures, reducing maintenance and troubleshooting time, and lowering maintenance costs.

[0044] Accordingly, see Figure 6 As shown, this application also provides a status early warning device based on the fuel quantity of a coal mill, comprising: The material level conversion module 11 is used to convert the coal mill load damper opening, coal mill inlet mixing primary air pressure and coal mill drive end material level into corresponding damper air volume, air pressure coefficient and material level coefficient based on each preset reference table if the coal mill meets the preset normal operation scenario; the preset normal operation scenario is that the coal mill is running and any coal feeder is running. The first fuel quantity determination module 12 is used to determine the primary air volume of the coal mill using the damper air volume, the air pressure coefficient and the material level coefficient, convert the primary air volume of the coal mill into an initial fuel quantity, construct a target model based on the equipment status parameters and target auxiliary parameters of the coal mill and using a gradient boosting tree, and determine the target fuel quantity using the correction coefficient output by the target model and the initial fuel quantity. The second fuel quantity determination module 13 is used to determine a first target curve of the attenuation coefficient based on the first initial value of the attenuation coefficient corresponding to the coal mill in the shutdown stage, the first preset time constant and the cumulative shutdown time if the coal mill meets the preset shutdown scenario, to limit the rate of change of the first target curve to obtain the target attenuation coefficient, and to determine the target fuel quantity based on the initial fuel quantity and the target attenuation coefficient. The third fuel quantity determination module 14 is used to determine the second target curve of the rise coefficient based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up stage, the second preset time constant and the start-up cumulative time if the coal mill meets the preset start-up scenario, to limit the rate of change of the second target curve to obtain the target rise coefficient, and to determine the target fuel quantity using the initial fuel quantity and the target rise coefficient. The status diagnosis module 15 is used to diagnose the status of the coal mill based on the target deviation between the target fuel quantity and the reference fuel quantity, so as to obtain the corresponding status diagnosis results and to perform corresponding early warning operations using the status diagnosis results.

[0045] In some specific embodiments, the material level conversion module 11 may specifically include: The coefficient conversion unit is used to convert the coal mill load damper opening into damper-converted air volume based on the first preset reference table if the coal mill meets the preset normal operation scenario, convert the coal mill inlet mixing primary air pressure into air pressure conversion coefficient based on the second preset reference table, and convert the coal mill drive end material level into material level conversion coefficient based on the third preset reference table.

[0046] In some specific embodiments, the first fuel quantity determination module 12 may specifically include: The air volume conversion unit is used to determine the primary air volume of the coal mill using the air volume of the damper, the air pressure coefficient and the material level coefficient, and to convert the primary air volume of the coal mill into the initial fuel quantity using the fourth preset reference table; The model building unit is used to construct a target model based on the equipment state parameters and target auxiliary parameters of the coal mill using a gradient boosting tree. The equipment state parameters include the main motor current of the coal mill, the bearing temperature of the reducer, and the vibration of the coal mill body. The target auxiliary parameters include the feeder speed / command, coal quality test data, and coal powder concentration measurement values. The first fuel quantity determination unit is used to determine the correction coefficient using the target model, and to determine the target fuel quantity based on the initial fuel quantity and the correction coefficient.

[0047] In some specific embodiments, the second fuel quantity determination module 13 may specifically include: The first initial value determination unit is used to determine the first initial value of the attenuation coefficient corresponding to the shutdown stage based on the first material level measurement value of the coal mill at the shutdown trigger time and the preset piecewise linear function if the coal mill meets the preset shutdown scenario. The first curve determination unit is used to generate a first target curve of the attenuation coefficient based on the first initial value, the cumulative downtime, and the first preset time constant. The second fuel quantity determination unit is used to limit the rate of change of the first target curve using the first target descent rate and the first target ascent rate to obtain the target attenuation coefficient, and to determine the target fuel quantity based on the initial fuel quantity and the target attenuation coefficient.

[0048] In some specific embodiments, the third fuel quantity determination module 14 may specifically include: The signal generation unit is used to generate a start-up enable signal based on the second material level value of the coal mill at the start-up trigger time and the current operating state of the coal mill if the coal mill meets the preset start-up scenario. The second curve determination unit is used to determine the second initial value of the rise coefficient corresponding to the coal mill in the start-up phase, and to determine the second target curve of the rise coefficient based on the second initial value, the second preset time constant and the cumulative start-up time. The third fuel quantity determination unit is used to limit the rate of change of the second target curve by using the mill start-up enable signal, the second target descent rate and the second target ascent rate to obtain the target ascent coefficient, and to determine the target fuel quantity by using the initial fuel quantity and the target ascent coefficient.

[0049] In some specific embodiments, the status diagnosis module 15 may specifically include: The deviation determination unit is used to determine the reference fuel quantity based on the total boiler air volume, flue gas oxygen content and exhaust gas temperature and using the inverse balance method, and to determine the real-time deviation and moving average deviation between the target fuel quantity and the reference fuel quantity. The parameter analysis unit is used to analyze the real-time deviation, the moving average deviation, and the target state parameters of the coal mill to obtain the corresponding analysis results; the target state parameters include current parameters, outlet temperature, coal mill load damper opening, and coal mill primary air volume. The diagnostic result determination submodule is used to determine the status diagnostic result of the coal mill based on the analysis results, and to perform corresponding early warning operations using the status diagnostic result.

[0050] In some specific implementations, the diagnostic result determination submodule may specifically include: The analysis result determination unit is used to determine the analysis result based on a preset rule base to obtain the corresponding determination result; The first diagnostic result determination unit is used to characterize the state diagnostic result of the coal mill as wear of the grinding rollers of the coal mill if the determination result is that the moving average deviation meets the preset slow monotonically increasing trend and the current parameter meets the preset upward trend. The second diagnostic result determination unit is used to characterize the state diagnostic result of the coal mill as coal shortage or abnormal coal feeding if the determination result is that the real-time deviation meets the preset step increase trend and the outlet temperature is not within the preset temperature range. The third diagnostic result determination unit is used to characterize the state diagnostic result of the coal mill as abnormal damper characteristics and / or primary air volume measurement element failure if the determination result is that the real-time deviation meets the preset fluctuation trend, and the opening degree of the coal mill load damper and the primary air volume of the coal mill both meet the preset change conditions.

[0051] Furthermore, embodiments of this application also disclose an electronic device, Figure 7 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the state warning method based on coal mill fuel quantity disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0052] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0053] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0054] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the coal mill fuel quantity status early warning method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0055] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed method for early warning of the state based on the coal mill fuel quantity. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0056] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0057] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0058] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0059] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0060] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for early warning of coal mill fuel quantity status, characterized in that, include: If the coal mill meets the preset normal operation scenario, then based on each preset reference table, the coal mill load damper opening, coal mill inlet mixing primary air pressure, and coal mill drive end material level are converted into the corresponding damper air volume, air pressure coefficient, and material level coefficient; the preset normal operation scenario is that the coal mill is running and any coal feeder is running. The primary air volume of the coal mill is determined using the damper air volume, the air pressure coefficient, and the material level coefficient. The primary air volume of the coal mill is converted into an initial fuel quantity. A target model is constructed based on the equipment state parameters and target auxiliary parameters of the coal mill and using a gradient boosting tree. The target fuel quantity is determined using the correction coefficients output by the target model and the initial fuel quantity. If the coal mill meets the preset shutdown scenario, then the first target curve of the attenuation coefficient is determined based on the first initial value of the attenuation coefficient corresponding to the coal mill in the shutdown stage, the first preset time constant and the cumulative shutdown time. The rate of change of the first target curve is limited to obtain the target attenuation coefficient. The target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient. If the coal mill meets the preset start-up scenario, then the second target curve of the rise coefficient is determined based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up stage, the second preset time constant, and the cumulative start-up time. The rate of change of the second target curve is limited to obtain the target rise coefficient. The target fuel quantity is determined using the initial fuel quantity and the target rise coefficient. The state of the coal mill is diagnosed based on the target deviation between the target fuel quantity and the reference fuel quantity to obtain the corresponding state diagnosis results, and the corresponding early warning operations are performed using the state diagnosis results.

2. The method for early warning of coal mill fuel quantity according to claim 1, characterized in that, If the coal mill meets the preset normal operation scenario, then based on each preset reference table, the coal mill load damper opening, the coal mill inlet mixing primary air pressure, and the coal mill drive end material level are converted into the corresponding damper air volume, air pressure coefficient, and material level coefficient, including: If the coal mill meets the preset normal operation scenario, the coal mill load damper opening is converted into damper converted air volume based on the first preset comparison table, the coal mill inlet mixing primary air pressure is converted into air pressure conversion coefficient using the second preset comparison table, and the coal mill drive end material level is converted into material level conversion coefficient based on the third preset comparison table.

3. The method for early warning of coal mill fuel quantity according to claim 1, characterized in that, The process of determining the primary air volume of the coal mill using the damper air volume, the air pressure coefficient, and the material level coefficient; converting the primary air volume of the coal mill into an initial fuel quantity; constructing a target model based on the equipment state parameters and target auxiliary parameters of the coal mill using a gradient boosting tree; and determining the target fuel quantity using the correction coefficients output by the target model and the initial fuel quantity includes: The primary air volume of the coal mill is determined using the damper air volume, the air pressure coefficient, and the material level coefficient. The primary air volume of the coal mill is then converted into the initial fuel quantity using the fourth preset reference table. Based on the equipment status parameters and target auxiliary parameters of the coal mill, a target model is constructed using a gradient boosting tree. The equipment status parameters include the main motor current of the coal mill, the bearing temperature of the reducer, and the vibration of the coal mill body. The target auxiliary parameters include the feeder speed / command, coal quality test data, and coal powder concentration measurement values. The target model is used to determine the correction coefficients, and the target fuel quantity is determined based on the initial fuel quantity and the correction coefficients.

4. The method for early warning of coal mill fuel quantity according to claim 1, characterized in that, If the coal mill meets the preset shutdown scenario, then based on the first initial value of the attenuation coefficient corresponding to the coal mill during the shutdown phase, the first preset time constant, and the cumulative shutdown time, a first target curve of the attenuation coefficient is determined. The rate of change of the first target curve is limited to obtain the target attenuation coefficient. The target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient, including: If the coal mill meets the preset shutdown scenario, then the first initial value of the attenuation coefficient corresponding to the shutdown stage is determined based on the first material level measurement value of the coal mill at the shutdown trigger time and the preset piecewise linear function. A first target curve for the attenuation coefficient is generated based on the first initial value, the cumulative downtime, and the first preset time constant. The first target curve is subjected to a rate of change limit using the first target descent rate and the first target ascent rate to obtain a target attenuation coefficient, and the target fuel quantity is determined based on the initial fuel quantity and the target attenuation coefficient.

5. The method for early warning of coal mill fuel quantity according to claim 1, characterized in that, If the coal mill meets the preset start-up scenario, then based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up phase, the second preset time constant, and the cumulative start-up time, a second target curve of the rise coefficient is determined. The rate of change of the second target curve is limited to obtain the target rise coefficient. The target fuel quantity is determined using the initial fuel quantity and the target rise coefficient, including: If the coal mill meets the preset start-up scenario, a start-up enable signal is generated based on the second material level value of the coal mill at the start-up trigger time and the current operating state of the coal mill. Determine a second initial value for the rise coefficient of the coal mill during the startup phase, and determine a second target curve for the rise coefficient based on the second initial value, a second preset time constant, and the cumulative startup time. The rate of change of the second target curve is limited by the mill start-up enable signal, the second target descent rate, and the second target ascent rate to obtain the target ascent coefficient. The target fuel quantity is then determined using the initial fuel quantity and the target ascent coefficient.

6. The method for early warning of coal mill fuel quantity according to claim 1, characterized in that, The process of diagnosing the state of the coal mill based on the target deviation between the target fuel quantity and the reference fuel quantity to obtain corresponding state diagnosis results, and using the state diagnosis results to perform corresponding early warning operations, includes: The reference fuel quantity is determined based on the total boiler air volume, flue gas oxygen content, and exhaust gas temperature using the inverse balance method. The real-time deviation and moving average deviation between the target fuel quantity and the reference fuel quantity are also determined. The analysis is based on the real-time deviation, the moving average deviation, and the target state parameters of the coal mill to obtain the corresponding analysis results; the target state parameters include current parameters, outlet temperature, coal mill load damper opening, and coal mill primary air volume. Based on the analysis results, the condition diagnosis results of the coal mill are determined, and corresponding early warning operations are performed using the condition diagnosis results.

7. The method for early warning of coal mill fuel quantity according to claim 6, characterized in that, The determination of the condition diagnosis result of the coal mill based on the analysis results includes: The analysis results are judged based on a preset rule base to obtain the corresponding judgment result; If the determination result is that the moving average deviation meets the preset slow monotonically increasing trend and the current parameter meets the preset upward trend, then the condition diagnosis result of the coal mill is that the grinding roller of the coal mill is worn. If the determination result is that the real-time deviation meets the preset step increase trend and the outlet temperature is not within the preset temperature range, then the state diagnosis result of the coal mill is characterized as coal shortage or abnormal coal feeding. If the determination result is that the real-time deviation meets the preset fluctuation trend, and the opening of the coal mill load damper and the primary air volume of the coal mill both meet the preset change conditions, then the state diagnosis result of the coal mill is characterized as abnormal damper characteristics and / or failure of the primary air volume measuring element.

8. A status early warning device based on coal mill fuel quantity, characterized in that, include: The material level conversion module is used to convert the coal mill load damper opening, coal mill inlet mixing primary air pressure, and coal mill drive end material level into corresponding damper air volume, air pressure coefficient, and material level coefficient based on each preset reference table if the coal mill meets the preset normal operation scenario; the preset normal operation scenario is that the coal mill is running and any coal feeder is running. The first fuel quantity determination module is used to determine the primary air volume of the coal mill using the damper air volume, the air pressure coefficient and the material level coefficient, convert the primary air volume of the coal mill into an initial fuel quantity, construct a target model based on the equipment status parameters and target auxiliary parameters of the coal mill and using a gradient boosting tree, and determine the target fuel quantity using the correction coefficient output by the target model and the initial fuel quantity. The second fuel quantity determination module is used to determine a first target curve of the attenuation coefficient based on the first initial value of the attenuation coefficient corresponding to the coal mill in the shutdown stage, the first preset time constant and the cumulative shutdown time if the coal mill meets the preset shutdown scenario, and to limit the rate of change of the first target curve to obtain the target attenuation coefficient, and to determine the target fuel quantity based on the initial fuel quantity and the target attenuation coefficient. The third fuel quantity determination module is used to determine the second target curve of the rise coefficient based on the second initial value of the rise coefficient corresponding to the coal mill in the start-up phase, the second preset time constant and the start-up cumulative time if the coal mill meets the preset start-up scenario, and to limit the rate of change of the second target curve to obtain the target rise coefficient, and to determine the target fuel quantity using the initial fuel quantity and the target rise coefficient. The status diagnosis module is used to diagnose the status of the coal mill based on the target deviation between the target fuel quantity and the reference fuel quantity, so as to obtain the corresponding status diagnosis results and to perform corresponding early warning operations using the status diagnosis results.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor is configured to execute the computer program to implement the state warning method based on the coal mill fuel quantity as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, wherein the computer program, when executed by a processor, implements the state warning method based on the coal mill fuel quantity as described in any one of claims 1 to 7.

Images