Early warning method and device of coal mill, storage medium and computer program product

Abstract

The invention discloses an early warning method and device of a coal mill, a storage medium and a computer program product, and relates to the field of electric power engineering.The early warning method of the coal mill comprises the steps that first parameters of N outlet pipelines of the coal mill in a first time period are obtained, the first parameters comprise first air powder concentration, first pulverized coal fineness, first primary air speed and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer; according to the first parameter, an abnormity early warning model is constructed, and the abnormity early warning model is used for determining whether the coal mill is abnormal or not; the operation state of the coal mill is determined through the abnormity early warning model, under the condition that the operation state is abnormal, the abnormal state of the coal mill is displayed through visual equipment, an early warning signal is sent to a target object, and the visual equipment is connected with the coal mill. By adopting the technical scheme, the problem of inaccurate judgment of the running state of the coal mill in related technologies is solved.

Description

Technical Field

[0001] This application relates to the field of power engineering, and more specifically, to a method and device for early warning of a coal mill, a storage medium, and a computer program product. Background Technology

[0002] In thermal power plants, coal mills, as key equipment in the pulverizing system, bear the important task of grinding raw coal into pulverized coal suitable for boiler combustion. The operating status of the coal mill directly affects the boiler's combustion efficiency, economy, and safety. However, traditional measurements of coal mill operating parameters, such as air velocity, air volume, pulverized coal concentration, and pulverized coal fineness, often rely on offline detection methods, such as manual sampling and testing, and cold-state dynamic field commissioning. These methods are not only time-consuming and labor-intensive, but also cannot reflect the coal mill's operating status in real time, resulting in a lag in operators' judgment of the coal mill's current operating condition and making timely adjustments difficult.

[0003] There is currently no effective solution to the problem of inaccurate judgment of the operating status of coal mills in related technologies.

[0004] Therefore, it is necessary to improve the relevant technology to overcome the aforementioned defects. Summary of the Invention

[0005] This application provides an early warning method and device for a coal mill, a storage medium, and a computer program product, to at least solve the problem of inaccurate judgment of the operating status of a coal mill in related technologies.

[0006] According to one aspect of the embodiments of this application, a method for early warning of a coal mill is provided, comprising: acquiring first parameters of N outlet pipes of the coal mill within a first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity, and first primary air volume, the first time period being a period of time prior to the current time, and N being a positive integer; constructing an abnormality early warning model based on the first parameters, wherein the abnormality early warning model is used to determine whether the coal mill has experienced an abnormality; determining the operating status of the coal mill through the abnormality early warning model, and, in the event of an abnormality in the operating status, displaying the abnormal status of the coal mill through a visualization device and issuing an early warning signal to a target object, wherein the visualization device is interconnected with the coal mill.

[0007] In an exemplary embodiment, determining the operating status of the coal mill through the anomaly early warning model includes: acquiring second parameters of the N outlet pipes in real time, wherein the second parameters have the same parameter type as the first parameters; and determining the operating status through the anomaly early warning model based on the second parameters and a first threshold corresponding to the second parameters.

[0008] In an exemplary embodiment, before issuing a warning signal to the target object, the method further includes: determining the warning signal as a yellow warning when the second primary wind speed of the i-th outlet pipe deviates from the first average value of the third primary wind speed of the N outlet pipes, and the first deviation is greater than or equal to a first preset value; or when the second primary air volume of the i-th outlet pipe deviates from the second average value of the third primary air volume of the N outlet pipes, and the second deviation is greater than or equal to the first preset value; wherein the first threshold includes the first average value and the second average value, and i is a positive integer; and determining the warning signal as a red warning when the second primary wind speed deviates from the first average value, and the first deviation is greater than or equal to a second preset value; or when the second primary air volume deviates from the second average value, and the second deviation is greater than or equal to a second preset value; wherein the second preset value is greater than the first preset value.

[0009] In an exemplary embodiment, after issuing a warning signal to the target object, the method further includes: if there is an abnormality in the second primary wind speed or the second primary air volume, and the warning signal is a yellow warning, remotely adjusting the adjustable orifice of the i-th outlet pipe; if there is an abnormality in the second primary wind speed or the second primary air volume, and the warning signal is a red warning, stopping the operation of the coal mill, and sending the first abnormal result of the second primary wind speed or the second primary air volume to the target object to instruct the target object to overhaul the coal mill.

[0010] In an exemplary embodiment, before issuing a warning signal to the target object, the method further includes: determining the warning signal as a yellow warning when there is a third deviation between the second coal powder fineness of the coal mill and a second threshold corresponding to the second coal powder fineness, and the third deviation is greater than or equal to a third preset value, wherein the first threshold includes the second threshold; and determining the warning signal as a red warning when there is the third deviation between the second coal powder fineness and the second threshold, and the third deviation is greater than or equal to a fourth preset value, wherein the fourth preset value is greater than the third preset value.

[0011] In an exemplary embodiment, after issuing a warning signal to the target object, the method further includes: remotely adjusting the dynamic separator of the coal mill when the second coal powder fineness is abnormal and the coal mill is given a yellow warning; and stopping the operation of the coal mill when the second coal powder fineness is abnormal and the coal mill is given a red warning, and sending the second abnormal result of the second coal powder fineness to the target object to instruct the target object to overhaul the coal mill.

[0012] According to another aspect of the embodiments of this application, an early warning device for a coal mill is also provided, comprising: an acquisition module, configured to acquire first parameters of N outlet pipes of the coal mill within a first time period, wherein the first parameters include: a first air-coal concentration, a first coal powder fineness, a first primary air velocity, and a first primary air volume, the first time period being a period of time prior to the current time, and N being a positive integer; a construction module, configured to construct an abnormality early warning model based on the first parameters, wherein the abnormality early warning model is used to determine whether the coal mill has experienced an abnormality; and a determination module, configured to determine the operating status of the coal mill through the abnormality early warning model, and, in the event of an abnormality in the operating status, display the abnormal status of the coal mill through a visualization device and issue an early warning signal to a target object, wherein the visualization device is interconnected with the coal mill.

[0013] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, and the computer program is configured to execute the above-described early warning method for the coal mill when it is run.

[0014] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the early warning method for the coal mill through the computer program.

[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the methods described in various embodiments of this application.

[0016] This application obtains the first parameters of N outlet pipes of a coal mill within a first time period. These first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity, and first primary air volume. The first time period is a period prior to the current time, and N is a positive integer. An anomaly warning model is constructed based on these first parameters to determine whether an anomaly has occurred in the coal mill. The anomaly warning model determines the operating status of the coal mill. In the event of an anomaly, the abnormal state of the coal mill is displayed through a visualization device, and a warning signal is sent to the target object. The visualization device is interconnected with the coal mill. This solves the problem of inaccurate judgment of the operating status of the coal mill in related technologies. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a hardware structure block diagram of a computer terminal for an early warning method for a coal mill according to an embodiment of this application;

[0020] Figure 2 This is a flowchart of an early warning method for a coal mill according to an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of an early warning method for a coal mill according to an embodiment of this application;

[0022] Figure 4 This is a structural block diagram of an early warning device for a coal mill according to an embodiment of this application. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] The methods and embodiments provided in this application can be executed on a computer terminal or similar computing device. Taking running on a computer terminal as an example, Figure 1 This is a hardware structure block diagram of a computer terminal for an early warning method for a coal mill, according to an embodiment of this application. Figure 1 As shown, a computer terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a central processing unit (CPU) or a field-programmable gate array (FPGA)) and a memory 104 for storing data are also shown. The computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0026] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the early warning method for a coal mill in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the aforementioned method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0027] The computer terminal uses a wireless network provided by a communications provider. In one example, transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0028] This embodiment provides an early warning method for a coal mill, which is applied to the aforementioned computer terminal. Figure 2 This is a flowchart of an early warning method for a coal mill according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps:

[0029] Step S202: Obtain the first parameters of the N outlet pipes of the coal mill within the first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer;

[0030] Step S204: Construct an anomaly warning model based on the first parameter, wherein the anomaly warning model is used to determine whether an anomaly has occurred in the coal mill;

[0031] Step S206: Determine the operating status of the coal mill through the abnormal early warning model. If the operating status is abnormal, display the abnormal status of the coal mill through a visualization device and send an early warning signal to the target object. The visualization device is connected to the coal mill.

[0032] Through the above steps, the first parameters of N outlet pipes of the coal mill within a first time period are obtained. These first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity, and first primary air volume. The first time period is a period prior to the current time, and N is a positive integer. An anomaly warning model is constructed based on these first parameters to determine whether an anomaly has occurred in the coal mill. The anomaly warning model determines the operating status of the coal mill. If an anomaly occurs, the abnormal status of the coal mill is displayed through a visualization device, and a warning signal is sent to the target object. The visualization device is interconnected with the coal mill. This solves the problem of inaccurate judgment of the operating status of the coal mill in related technologies.

[0033] In an exemplary embodiment, determining the operating status of the coal mill through the anomaly early warning model includes: acquiring second parameters of the N outlet pipes in real time, wherein the second parameters have the same parameter type as the first parameters; and determining the operating status through the anomaly early warning model based on the second parameters and a first threshold corresponding to the second parameters.

[0034] The coal mill utilizes a combined laser and electromagnetic technology detection device to monitor the coal powder concentration and fineness at N outlet pipes. Simultaneously, an online air velocity (air volume) detection device monitors the primary air velocity and primary air volume at the same N outlet pipes. An anomaly warning model automatically analyzes and determines whether the coal mill's operating status is normal based on real-time collected secondary parameters and a set first threshold (i.e., the upper and lower limits of the normal operating range of the secondary parameters).

[0035] In an exemplary embodiment, before issuing a warning signal to the target object, the method further includes: determining the warning signal as a yellow warning when the second primary wind speed of the i-th outlet pipe deviates from the first average value of the third primary wind speed of the N outlet pipes, and the first deviation is greater than or equal to a first preset value; or when the second primary air volume of the i-th outlet pipe deviates from the second average value of the third primary air volume of the N outlet pipes, and the second deviation is greater than or equal to the first preset value; wherein the first threshold includes the first average value and the second average value, and i is a positive integer; and determining the warning signal as a red warning when the second primary wind speed deviates from the first average value, and the first deviation is greater than or equal to a second preset value; or when the second primary air volume deviates from the second average value, and the second deviation is greater than or equal to a second preset value; wherein the second preset value is greater than the first preset value.

[0036] Optionally, assume the coal mill has four outlet pipes, each with its own primary velocity and primary air volume parameters. Calculate the average primary velocity and primary air volume for all pipes, i.e., the first average and the second average. A first threshold includes these two averages, used as a standard for comparison and judgment. Monitor the second primary velocity and primary air volume of the i-th outlet pipe in real time, comparing the second primary velocity with the first average to determine if there is a first deviation. If a first deviation exists and reaches or exceeds a pre-set first preset value (e.g., 10%), the difference is deemed sufficient to attract attention but has not yet reached a crisis level, thus triggering a yellow warning. Alternatively, determine if there is a second deviation between the second primary air volume and the second average. If a second deviation exists and reaches or exceeds a pre-set first preset value (e.g., 10%), a yellow warning is triggered. If the first or second deviation further increases, reaching or exceeding a higher second preset value (e.g., 20%), this indicates a more serious situation that may directly affect the operating efficiency and safety of the coal mill, at which point a red warning will be issued.

[0037] In an exemplary embodiment, after issuing a warning signal to the target object, the method further includes: if there is an abnormality in the second primary wind speed or the second primary air volume, and the warning signal is a yellow warning, remotely adjusting the adjustable orifice of the i-th outlet pipe; if there is an abnormality in the second primary wind speed or the second primary air volume, and the warning signal is a red warning, stopping the operation of the coal mill, and sending the first abnormal result of the second primary wind speed or the second primary air volume to the target object to instruct the target object to overhaul the coal mill.

[0038] When an anomaly is detected in the primary air velocity or volume of the coal mill outlet pipe, and the warning signal is determined to be at the yellow warning level based on a preset threshold, it means that the operation of a certain pipe has begun to deviate from the normal range, but has not yet reached a critical state. At this time, remote adjustment measures can be taken to precisely control and adjust the adjustable orifice on the i-th outlet pipe. If the anomaly in primary air velocity or volume continues to worsen, causing the deviation to exceed the more stringent red warning threshold, this indicates that the current operating state may pose a significant threat to equipment safety. In this case, more stringent countermeasures will be taken immediately, namely, stopping the operation of the coal mill to avoid potential equipment damage or other serious consequences. At the same time, the first anomaly result of the primary air velocity or volume is sent to the target entity, which is usually the personnel or department responsible for equipment maintenance and management. This information transmission is rapid and direct, clearly instructing the target entity to immediately inspect the coal mill, find and eliminate the cause of the abnormal air velocity or volume, thereby ensuring the long-term stability and safety of the equipment.

[0039] In an exemplary embodiment, before issuing a warning signal to the target object, the method further includes: determining the warning signal as a yellow warning when there is a third deviation between the second coal powder fineness of the coal mill and a second threshold corresponding to the second coal powder fineness, and the third deviation is greater than or equal to a third preset value, wherein the first threshold includes the second threshold; and determining the warning signal as a red warning when there is the third deviation between the second coal powder fineness and the second threshold, and the third deviation is greater than or equal to a fourth preset value, wherein the fourth preset value is greater than the third preset value.

[0040] During operation, the coal mill continuously monitors the fineness of the produced pulverized coal, known as the second pulverized coal fineness. To maintain the fineness within the ideal range, a second threshold is set, based on the standard for pulverized coal fineness under normal operating conditions. This second threshold serves as a benchmark for judging whether the pulverized coal fineness is normal and is part of the first threshold, ensuring that all key parameters are monitored within a unified and precise framework. The difference between the second pulverized coal fineness and the second threshold is continuously analyzed, known as the third deviation. If the third deviation exceeds a third preset value (e.g., 15%), it means that the second pulverized coal fineness has begun to deviate from the ideal range, but the degree of deviation is still within a controllable range; in this case, a yellow warning is triggered. If the third deviation further expands, reaching or exceeding a more stringent fourth preset value (e.g., 25%), it indicates that the abnormality in the second pulverized coal fineness is very serious and may directly affect combustion efficiency and equipment safety; in this case, a red warning will be triggered.

[0041] In an exemplary embodiment, after issuing a warning signal to the target object, the method further includes: remotely adjusting the dynamic separator of the coal mill when the second coal powder fineness is abnormal and the coal mill is given a yellow warning; and stopping the operation of the coal mill when the second coal powder fineness is abnormal and the coal mill is given a red warning, and sending the second abnormal result of the second coal powder fineness to the target object to instruct the target object to overhaul the coal mill.

[0042] When abnormal fluctuations in the fineness of the second pulverized coal produced by the coal mill are detected, and the warning signal is yellow, it indicates that the fineness of the pulverized coal has begun to deviate from the expected normal range, but the situation is still within a controllable range. At this time, the warning mechanism will not take drastic measures to stop the equipment operation, but will instead automatically adjust the dynamic separator equipped with the coal mill through remote control, or instruct the target to adjust the static separator of the coal mill on-site. The function of the dynamic separator is to control the fineness of the pulverized coal by changing the rotation speed or guide angle of its internal structure to meet combustion requirements. Therefore, in the yellow warning stage, automatic fine-tuning is performed to try to bring the fineness of the pulverized coal back to the ideal range, which can avoid a significant drop in production efficiency and ensure that combustion efficiency and environmental protection requirements are met. If the abnormality in the fineness of the second pulverized coal continues to worsen, and the warning signal is red, it indicates that the deviation in the fineness of the pulverized coal has exceeded the safety limit, which may have a serious impact on the combustion process, equipment health, and even the operation of the entire power plant. In this case, the warning mechanism will respond quickly and immediately stop the operation of the coal mill to prevent potential risks from turning into actual hazards. At the same time, the second abnormal result of coal powder fineness is communicated to the pre-designated target group, namely the personnel or department responsible for equipment maintenance and safety management, in the fastest way possible, so as to instruct the target group to immediately carry out a comprehensive inspection and necessary maintenance of the coal mill.

[0043] To better understand the process of the above-mentioned early warning method for coal mills, the early warning method for coal mills will be described below in conjunction with optional embodiments, but this is not intended to limit the technical solutions of the embodiments of this application.

[0044] Figure 3 This is a schematic diagram of an early warning method for a coal mill according to an embodiment of this application, as shown below. Figure 3 As shown, it specifically includes the following:

[0045] Key operating parameters of medium-speed coal mills in thermal power units, including air temperature, primary air velocity, air pressure, air volume, coal powder concentration, and coal powder fineness, are input into an algorithm model based on big data and artificial intelligence technologies. This algorithm model is called the coal mill pulverizing anomaly algorithm model (equivalent to an anomaly early warning model). Through deep analysis and intelligent learning, it can accurately identify abnormal changes in parameters in complex operating environments and assess the health status and operating efficiency of the coal mill.

[0046] Specifically, the system collects and processes data on the six parameters mentioned above in real time. This data not only provides a direct reflection of the current operating status of the coal mill but also contains a wealth of operational information. For example, fluctuations in air temperature may affect the dryness of pulverized coal; uneven distribution of primary air velocity and volume may lead to incomplete combustion of pulverized coal; and abnormalities in air-to-coal concentration and pulverized coal fineness directly affect combustion efficiency and environmental performance. All these real-time parameters are transmitted to the anomaly early warning model, serving as the basis for analysis and decision-making. Within the model, these parameters undergo multi-dimensional cross-analysis, including but not limited to correlation analysis between parameters, historical data comparison, and trend prediction. Based on the deviation of parameter values ​​from preset thresholds, combined with the equipment's operating history and current conditions, the model automatically assesses the operating status of the coal mill and determines whether potential anomalies exist. This process relies not only on numerical comparisons but also integrates the complex interactions between parameters, continuously optimizing the model's judgment accuracy through machine learning algorithms.

[0047] When the model determines that one or more parameters are abnormal and the degree of abnormality reaches the warning standard, it generates a warning signal through analysis, warning, visualization, control, and adjustment systems. Warning signals are divided into different levels, such as yellow and red warnings, corresponding to different degrees of severity of the abnormality. For example, a yellow warning may mean that some parameters are slightly deviating from the normal range, but there is still a chance to adjust them back to the safe range, while a red warning indicates a serious abnormality, requiring immediate action to avoid damage to the equipment. Warning signals are presented to operators through a visual interface that clearly displays the operating status of the coal mill, marking the real-time values ​​and deviations of the parameters, while providing the warning level and corresponding handling suggestions. For example, if there is a deviation in primary air volume and primary air velocity, and the warning signal is yellow, the adjustable orifice on a specific outlet pipe can be adjusted; if the coal powder fineness is abnormal, and the warning signal is red, it may be recommended to stop the coal mill and perform maintenance. In addition, the warning system also has an automatic adjustment function, capable of attempting remote adjustments to equipment parameters during the yellow warning stage, such as adjusting the coal powder fineness by changing the settings of the dynamic separator, or adjusting the adjustable orifice to correct deviations in air velocity and volume, to prevent the problem from escalating. This combination of automatic adjustment and early warning greatly improves the operator's response speed and processing efficiency, ensures that the equipment operates in the best condition, and reduces unnecessary downtime and production losses.

[0048] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0049] This embodiment also provides an early warning device for a coal mill, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0050] Figure 4 This is a structural block diagram of an early warning device for a coal mill according to an embodiment of this application. The device includes:

[0051] The acquisition module 42 is used to acquire the first parameters of N outlet pipes of the coal mill within a first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer;

[0052] The construction module 44 is used to construct an anomaly warning model based on the first parameter, wherein the anomaly warning model is used to determine whether an anomaly has occurred in the coal mill;

[0053] The determination module 46 is used to determine the operating status of the coal mill through the abnormal early warning model. In the event of an abnormal operating status, the abnormal status of the coal mill is displayed through a visualization device, and an early warning signal is sent to the target object. The visualization device is interconnected with the coal mill.

[0054] Using the aforementioned device, first parameters of N outlet pipes of the coal mill are acquired within a first time period. These first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity, and first primary air volume. The first time period is a period prior to the current time, and N is a positive integer. An anomaly warning model is constructed based on these first parameters to determine whether an anomaly has occurred in the coal mill. The anomaly warning model determines the operating status of the coal mill. If an anomaly occurs, the abnormal status of the coal mill is displayed through a visualization device, and a warning signal is sent to the target object. The visualization device is interconnected with the coal mill. This solves the problem of inaccurate judgment of the operating status of the coal mill in related technologies.

[0055] In an exemplary embodiment, the determining module 46 is further configured to acquire second parameters of the N outlet pipes in real time, wherein the second parameters are of the same parameter type as the first parameters; and determine the operating status based on the second parameters and the first threshold corresponding to the second parameters through the anomaly warning model.

[0056] In an exemplary embodiment, the determining module 46 is further configured to determine the warning signal as a yellow warning when the second primary wind speed of the i-th outlet pipe deviates from the first average value of the third primary wind speed of the N outlet pipes, and the first deviation is greater than or equal to a first preset value, or when the second primary air volume of the i-th outlet pipe deviates from the second average value of the third primary air volume of the N outlet pipes, and the second deviation is greater than or equal to the first preset value; wherein the first threshold includes the first average value and the second average value, and i is a positive integer; and to determine the warning signal as a red warning when the second primary wind speed deviates from the first average value, and the first deviation is greater than or equal to a second preset value, or when the second primary air volume deviates from the second average value, and the second deviation is greater than or equal to a second preset value, wherein the second preset value is greater than the first preset value.

[0057] In an exemplary embodiment, the determining module 46 is further configured to remotely adjust the adjustable orifice of the i-th outlet pipe when there is an abnormality in the second primary wind speed or the second primary air volume and the warning signal is the yellow warning; and to stop the operation of the coal mill when there is an abnormality in the second primary wind speed or the second primary air volume and the warning signal is the red warning, and to send the first abnormal result of the second primary wind speed or the second primary air volume to the target object to instruct the target object to perform maintenance on the coal mill.

[0058] In an exemplary embodiment, the determining module 46 is further configured to determine the warning signal as a yellow warning when there is a third deviation between the second coal powder fineness of the coal mill and the second threshold corresponding to the second coal powder fineness, and the third deviation is greater than or equal to a third preset value, wherein the first threshold includes the second threshold; and to determine the warning signal as a red warning when there is the third deviation between the second coal powder fineness and the second threshold, and the third deviation is greater than or equal to a fourth preset value, wherein the fourth preset value is greater than the third preset value.

[0059] In an exemplary embodiment, the determining module 46 is further configured to remotely adjust the dynamic separator of the coal mill when the second coal powder fineness is abnormal and the coal mill is given a yellow warning; and to stop the operation of the coal mill when the second coal powder fineness is abnormal and the coal mill is given a red warning, and to send the second abnormal result of the second coal powder fineness to the target object to instruct the target object to perform maintenance on the coal mill.

[0060] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when run.

[0061] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0062] S1, obtain the first parameters of N outlet pipes of the coal mill within the first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer;

[0063] S2, construct an anomaly warning model based on the first parameter, wherein the anomaly warning model is used to determine whether the coal mill has an anomaly;

[0064] S3, the operating status of the coal mill is determined by the abnormal early warning model. If the operating status is abnormal, the abnormal status of the coal mill is displayed by a visualization device and an early warning signal is sent to the target object. The visualization device is connected to the coal mill.

[0065] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0066] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0067] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0068] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0069] S1, obtain the first parameters of N outlet pipes of the coal mill within the first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer;

[0070] S2, construct an anomaly warning model based on the first parameter, wherein the anomaly warning model is used to determine whether the coal mill has an anomaly;

[0071] S3, the operating status of the coal mill is determined by the abnormal early warning model. If the operating status is abnormal, the abnormal status of the coal mill is displayed by a visualization device and an early warning signal is sent to the target object. The visualization device is connected to the coal mill.

[0072] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0073] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium storing the computer program product, wherein the computer program, when executed by a processor, implements the steps of the methods described in various embodiments of this application.

[0074] Optionally, in this embodiment, the computer program described above can be configured to perform the following steps when executed by the processor:

[0075] S1, obtain the first parameters of N outlet pipes of the coal mill within the first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer;

[0076] S2, construct an anomaly warning model based on the first parameter, wherein the anomaly warning model is used to determine whether the coal mill has an anomaly;

[0077] S3, the operating status of the coal mill is determined by the abnormal early warning model. If the operating status is abnormal, the abnormal status of the coal mill is displayed by a visualization device and an early warning signal is sent to the target object. The visualization device is connected to the coal mill.

[0078] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0079] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0080] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for early warning of a coal mill, characterized in that, include: Obtain the first parameters of N outlet pipes of the coal mill within the first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer; An anomaly warning model is constructed based on the first parameter, wherein the anomaly warning model is used to determine whether an anomaly has occurred in the coal mill; The abnormal early warning model determines the operating status of the coal mill. If an abnormality occurs in the operating status, the abnormal status of the coal mill is displayed through a visualization device, and an early warning signal is sent to the target object. The visualization device is connected to the coal mill.

2. The early warning method for a coal mill according to claim 1, characterized in that, The abnormal early warning model is used to determine the operating status of the coal mill, including: The second parameter of the N outlet pipes is acquired in real time, wherein the second parameter has the same parameter type as the first parameter; The abnormal early warning model determines the operating status based on the second parameter and the first threshold corresponding to the second parameter.

3. The early warning method for a coal mill according to claim 2, characterized in that, Before issuing a warning signal to the target object, the method further includes: If there is a first deviation between the second primary air velocity of the i-th outlet pipe and the first average value of the third primary air velocity of the N outlet pipes, and the first deviation is greater than or equal to a first preset value, or if there is a second deviation between the second primary air volume of the i-th outlet pipe and the second average value of the third primary air volume of the N outlet pipes, and the second deviation is greater than or equal to the first preset value, the warning signal is determined to be a yellow warning, wherein the first threshold includes the first average value and the second average value, and i is a positive integer; If the second primary wind speed deviates from the first average value and the first deviation is greater than or equal to the second preset value, or if the second primary air volume deviates from the second average value and the second deviation is greater than or equal to the second preset value, the warning signal is determined to be a red warning, wherein the second preset value is greater than the first preset value.

4. The early warning method for a coal mill according to claim 3, characterized in that, After issuing a warning signal to the target object, the method further includes: If there is an abnormality in the second primary wind speed or the second primary air volume, and the warning signal is the yellow warning, the adjustable orifice of the i-th outlet pipe is remotely adjusted. If there is an abnormality in the second primary wind speed or the second primary air volume, and the warning signal is a red warning, the coal mill shall be stopped, and the first abnormal result of the second primary wind speed or the second primary air volume shall be sent to the target object to instruct the target object to carry out maintenance on the coal mill.

5. The early warning method for a coal mill according to claim 2, characterized in that, Before issuing a warning signal to the target object, the method further includes: If there is a third deviation between the second coal powder fineness of the coal mill and the second threshold corresponding to the second coal powder fineness, and the third deviation is greater than or equal to a third preset value, the warning signal is determined to be a yellow warning, wherein the first threshold includes the second threshold; If there is a third deviation between the second coal powder fineness and the second threshold, and the third deviation is greater than or equal to a fourth preset value, the warning signal is determined to be a red warning, wherein the fourth preset value is greater than the third preset value.

6. The early warning method for a coal mill according to claim 5, characterized in that, After issuing a warning signal to the target object, the method further includes: If the fineness of the second coal powder is abnormal and the yellow warning is issued for the coal mill, the dynamic separator of the coal mill is remotely adjusted. If the second coal powder fineness is abnormal and the coal mill is given a red warning, the coal mill shall be stopped and the second abnormal result of the second coal powder fineness shall be sent to the target object to instruct the target object to carry out maintenance on the coal mill.

7. An early warning device for a coal mill, characterized in that, include: The acquisition module is used to acquire the first parameters of N outlet pipes of the coal mill within a first time period, wherein the first parameters include: first air-coal concentration, first coal powder fineness, first primary air velocity and first primary air volume, the first time period is a period of time before the current time, and N is a positive integer; A construction module is used to construct an anomaly warning model based on the first parameter, wherein the anomaly warning model is used to determine whether an anomaly has occurred in the coal mill; The determination module is used to determine the operating status of the coal mill through the abnormal early warning model. In the event of an abnormal operating status, the abnormal status of the coal mill is displayed through a visualization device, and an early warning signal is sent to the target object. The visualization device is interconnected with the coal mill.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 6.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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