Control method and device of deslagging system, storage medium and electronic equipment

Abstract

The invention discloses a control method and device of a deslagging system, a storage medium and electronic equipment. The dynamic delay time is determined based on the conveying distance of the first temperature measuring point and the second temperature measuring point, the steel belt operation parameters and the slag block heat conduction characteristic parameters, slag block conveying lag can be accurately quantified, the historical temperature sequence and the real-time temperature are strictly aligned in the time dimension, and data distortion caused by time reference mismatching is avoided. The historical temperature sequence obtained based on the dynamic delay time can ensure that the temperatures of the two measuring points form a real corresponding slag temperature conduction relation, a reliable data basis is provided for lagging correlation analysis, extraction of a slag temperature inertia change feature group is more close to the actual heat conduction process of slag block transmission, and dynamic changes such as the cooling effect and slag block characteristics are accurately reflected. The opening degree of the cooling air door is controlled by combining the slag temperature inertia change characteristic set and the load slag quantity matching rule, the cooling efficiency can be improved, energy consumption can be reduced, and efficient and reliable operation of the slag discharging process is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of slag discharge, and in particular to a control method and device of a slag discharge system, a storage medium and an electronic device. BACKGROUND

[0002] In the process of boiler combustion, coal, biomass and other fuels are burned at high temperature, producing molten ash. After cooling and solidification, the ash forms slag. Since the temperature of the slag is usually as high as 800-1200℃, if it is not discharged and cooled in time, it will affect the heat transfer efficiency of the boiler furnace and the safety of the equipment. Therefore, the slag needs to be dropped into the slag discharge system and transported to the slag bin through a 30-40m long conveying steel belt. At the same time, air introduced by the cooling air door is used to cool the slag, so that the temperature of the slag is reduced to a reasonable range (e.g. ≤150℃), to ensure the safe and stable operation of the boiler system.

[0003] When the slag moves slowly along the steel belt for a long distance, it takes 20-30 minutes from entering the slag discharge system to reaching the slag bin. The cooling process depends on the continuous heat exchange between the air and the slag in the transmission path. Since the slag moves slowly and the transmission distance is long, the heat needs to be gradually dissipated through the air introduced by the cooling air door during the operation of the steel belt, and the cooling effect needs to be gradually accumulated as the slag moves. Therefore, there is a significant time lag between the adjustment of the cooling air volume and the actual change of the slag temperature.

[0004] The prior art usually presets the opening range of the cooling air door according to the load of the boiler. However, this method uses fixed preset values, which only match the average slag drop amount under a certain load, and cannot track the instantaneous change of the slag drop amount when the load suddenly changes. When the slag drop amount suddenly increases or decreases, the thermal load of the slag has changed, but the preset opening adjustment needs to be manually intervened or switched according to fixed logic, which cannot immediately respond to the change. In addition, due to the inherent delay of the steel belt transportation, when the adjustment action acts on the slag, the thermal load state of the slag has deviated from the initial state at the time of adjustment. The superposition of this adjustment lag and transmission delay makes the cooling air volume always lag behind the current real thermal load demand. When the air volume is adjusted, the slag may have entered a new thermal load stage, resulting in a dynamic mismatch between the cooling air volume and the real-time thermal load, and finally it is difficult to control the slag temperature within the preset range. SUMMARY

[0005] In view of the above problems, the present application provides a control method and device of a slag discharge system, a storage medium and an electronic device.

[0006] To solve the above technical problems, the present application proposes the following solutions:

[0007] In a first aspect, the application provides a control method of a slag removal system, the method comprising: determining a dynamic delay time of a slag block based on a conveying distance of a first temperature measuring point to a second temperature measuring point along a conveying direction of a steel belt, a steel belt operation parameter, and a slag block heat conduction characteristic parameter, the dynamic delay time being used to indicate a difference between a time required for the slag block to reduce a temperature at the first temperature measuring point to a preset temperature range and a moving time of the slag block moving from the first temperature measuring point to the second temperature measuring point; determining a historical time window based on the dynamic delay time, and obtaining an original temperature sequence of the first temperature measuring point before a current time in the historical time window; performing lag correlation analysis on a measured temperature sequence in a preset time range of the second temperature measuring point and the original temperature sequence to obtain a slag temperature inertia change characteristic group; and controlling an opening degree of a cooling air door of the slag removal system according to the slag temperature inertia change characteristic group and a preset load and slag amount matching rule, so as to control a temperature of the slag block when reaching the second temperature measuring point to be within the preset temperature range.

[0008] In a second aspect, the application provides a control device of a slag removal system, the control device of the slag removal system comprising:

[0009] a determination module configured to determine a dynamic delay time of a slag block based on a conveying distance of a first temperature measuring point to a second temperature measuring point along a conveying direction of a steel belt, a steel belt operation parameter, and a slag block heat conduction characteristic parameter, the dynamic delay time being used to indicate a difference between a time required for the slag block to reduce a temperature at the first temperature measuring point to a preset temperature range and a moving time of the slag block moving from the first temperature measuring point to the second temperature measuring point;

[0010] a first feature module configured to determine a historical time window based on the dynamic delay time, and obtain an original temperature sequence of the first temperature measuring point before a current time in the historical time window;

[0011] a second feature module configured to perform lag correlation analysis on a measured temperature sequence in a preset time range of the second temperature measuring point and the original temperature sequence to obtain a slag temperature inertia change characteristic group;

[0012] a control module configured to control an opening degree of a cooling air door of the slag removal system according to the slag temperature inertia change characteristic group and a preset load and slag amount matching rule, so as to control a temperature of the slag block when reaching the second temperature measuring point to be within the preset temperature range.

[0013] In order to achieve the above-mentioned purpose, according to a third aspect of the application, a storage medium is provided, the storage medium comprising a stored program, wherein when the program runs, the device where the storage medium is located performs the control method of the slag removal system of the first aspect.

[0014] In order to achieve the above-mentioned purpose, according to the fourth aspect of the present application, an electronic device is provided, the device comprising at least one processor, and at least one memory connected with the processor, a bus; wherein the processor, the memory complete mutual communication through the bus; the processor is used to call the program instruction in the memory, in order to execute the control method of the slag removal system of the first aspect.

[0015] By the above technical solution, the technical solution provided by the present application has at least the following advantages:

[0016] The present application can determine the physical movement time of the slag block between two temperature measuring points based on the conveying distance and the steel belt running parameters, and can represent the temperature decay rate of the slag block in the transmission process based on the thermal conduction characteristic parameters. By the difference between the physical movement time and the temperature decay time determined based on the thermal conduction characteristic parameters, the quantitative correlation between the physical displacement process and the heat conduction process of the slag block can be realized, so as to accurately obtain the time difference of temperature change relative to physical movement. The historical time window is determined in this way, and the original temperature sequence is extracted, and the lag correlation analysis is performed on the measured temperature sequence of the second measuring point, so as to obtain the inertia change rule of the slag temperature in the transmission process. The inertia change rule is combined with the preset load slag amount matching rule to control the damper opening degree, and the dynamic delay time is converted into a quantifiable adjustment advance to realize control. That is, by predicting the temperature of the slag block when it reaches the second measuring point, the cooling air volume is adjusted in advance, so that the damper adjustment action and the heat load change of the slag block are accurately coupled in the time dimension, so as to offset the superimposed effects of the steel belt transportation delay and the heat conduction lag, realize the dynamic following of the cooling air volume to the real-time heat load, and finally ensure that the slag temperature is controlled in the preset range.

[0017] The above description is only a summary of the technical solutions of the present application. In order to enable the technical means of the present application to be more clearly understood, the present application can be implemented according to the content of the specification, and in order to enable the above and other purposes, characteristics and advantages of the present application to be more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0018] By reading the detailed description of the preferred embodiments below, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of illustrating the preferred embodiments and are not considered limiting the present application. Moreover, the same reference symbols are used throughout the drawings to represent the same parts. In the drawings:

[0019] Figure 1 A structural schematic diagram of a control system of a slag removal system provided by an embodiment of the present application is shown;

[0020] Figure 2 A structural schematic diagram of a slag removal system provided by an embodiment of the present application is shown;

[0021] Figure 3 This illustration shows a structural schematic diagram of an electronic device provided in an embodiment of this application;

[0022] Figure 4 A flowchart illustrating a control method for a slag discharge system provided in an embodiment of this application is shown.

[0023] Figure 5 A schematic diagram of the structure of a control device for a slag discharge system provided in an embodiment of this application is shown. Detailed Implementation

[0024] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0025] In the embodiments of this application, the terms "first," "second," etc., do not have a logical or temporal dependency, nor do they limit the quantity or execution order. It should also be understood that although the following description uses the terms "first," "second," etc., to describe various elements, these elements should not be limited by the terms. These terms are merely used to distinguish one element from another.

[0026] In this application, the term "at least one" means one or more, and the term "multiple" means two or more.

[0027] It should also be understood that the term “if” can be interpreted as “when” or “upon”, or “in response to determination” or “in response to detection”. Similarly, depending on the context, the phrase “if determination…” or “if detection [the stated condition or event]” can be interpreted as “when determination…” or “in response to determination…” or “when detection [the stated condition or event]” or “in response to detection [the stated condition or event]”.

[0028] During boiler combustion, fuels such as coal and biomass produce molten ash after high-temperature combustion, which solidifies into slag blocks upon cooling. Since the slag blocks reach temperatures as high as 800-1200℃, failure to handle them promptly can affect boiler heat transfer efficiency and equipment safety. Therefore, they must be transported to the slag bin via a 30-40m long steel conveyor belt, while simultaneously cooling air is introduced through cooling dampers to lower the temperature to ≤150℃, ensuring subsequent processing and system safety.

[0029] The slag blocks move slowly along the steel conveyor belt over a long distance (20-30 minutes in total), and their cooling depends on the continuous heat exchange between the air and the slag blocks in the transport path. Due to the slow speed and long distance, the heat needs to be gradually dissipated through the air introduced by the cooling dampers. The cooling effect accumulates during the transport process, resulting in a significant time lag between airflow adjustment and slag block temperature changes.

[0030] Existing technology pre-sets the opening of cooling dampers according to boiler load segments, but its fixed preset values ​​only match the average ash discharge amount and cannot track the instantaneous changes in ash discharge amount during load changes. When the increase or decrease in ash discharge amount causes changes in the ash block heat load, the preset opening adjustment cannot respond immediately because it requires manual intervention or fixed logic switching. In addition, due to the delay in steel belt transportation, the heat load of the ash block has already changed when the adjustment action is applied, ultimately resulting in a mismatch between the cooling air volume and the actual heat load, making it difficult to control the ash temperature within the preset range.

[0031] Based on this, this application provides a control system for a slag discharge system. The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0032] Figure 1 This application provides a schematic diagram of a control system for a slag discharge system. The control system 100 of the slag discharge system includes a control device 110 and a slag discharge system 120. The control device 110 and the slag discharge system 120 communicate with each other via a network. For example, they communicate via a network 130, which can be a wired connection such as a serial cable or a Universal Asynchronous Receiver / Transmitter (UART), or a wireless connection such as a wireless signal.

[0033] The control device 110 can be used to execute the control method of the slag discharge system. Optionally, the control device 110 may be an electronic device with data processing capabilities, or a functional module of such electronic device, and there is no limitation thereto.

[0034] For example, the electronic device can be a server, which can be a single server or a server cluster consisting of multiple servers. As another example, the electronic device can be a mobile phone, tablet computer, desktop computer, laptop computer, handheld computer, notebook computer, ultra-mobile personal computer (UMPC), netbook, as well as cellular phones, personal digital assistants (PDAs), augmented reality (AR) devices, virtual reality (VR) devices, and other terminal devices. As yet another example, the electronic device can also be a recording device, video surveillance equipment, etc. This application does not impose any special limitations on the specific form of the electronic device.

[0035] The following example uses electronic equipment as the control device in the control system of a slag discharge system. Figure 2 As shown, Figure 2 The hardware structure of an electronic device 200 provided in this application.

[0036] like Figure 2 As shown, the electronic device 200 includes a processor 210, a communication line 220, and a communication interface 230.

[0037] Optionally, the electronic device 200 may also include a memory 240. The processor 210, memory 240, and communication interface 230 can be connected via a communication line 220.

[0038] The processor 210 can be a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 210 can also be any other device with processing capabilities, such as a circuit, device, or software module, without limitation.

[0039] In one example, processor 210 may include one or more CPUs, for example Figure 2 CPU0 and CPU1 in the CPU.

[0040] As an optional implementation, electronic device 200 may include multiple processors, for example, in addition to processor 210, it may also include processor 270. Communication line 220 is used to transmit information between the components included in electronic device 200.

[0041] Communication interface 230 is used to communicate with other devices or other communication networks. These other communication networks can be Ethernet, Radio Access Network (RAN), Wireless Local Area Networks (WLAN), etc. Communication interface 230 can be a module, circuit, transceiver, or any device capable of enabling communication.

[0042] The memory 240 is used to store instructions. These instructions can be computer programs.

[0043] The memory 240 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and / or instructions; it may also be a random access memory (RAM) or other type of dynamic storage device capable of storing information and / or instructions; it may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, etc., without limitation.

[0044] It should be noted that the memory 240 can exist independently of the processor 210, or it can be integrated with the processor 210. The memory 240 can be used to store instructions, program code, or some data, etc. The memory 240 can be located inside or outside the electronic device 200, without restriction.

[0045] Processor 210 is configured to execute instructions stored in memory 240 to implement the communication method provided in the following embodiments of this application. For example, when electronic device 200 is a terminal or a chip in a terminal, processor 210 can execute instructions stored in memory 240 to implement the steps performed by the sending end in the following embodiments of this application.

[0046] As an optional implementation, the electronic device 200 also includes an output device 250 and an input device 260. The output device 250 can be a display screen, speaker, or other device capable of outputting data from the electronic device 200 to the user. The input device 260 can be a keyboard, mouse, microphone, joystick, or other device capable of inputting data into the electronic device 200.

[0047] It should be pointed out that, Figure 2 The structure shown does not constitute a limitation on the electronic device, except... Figure 2 In addition to the components shown, the electronic device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0048] like Figure 3 As shown, the slag removal system 120 includes a slag well, a slag removal machine (including a conveyor belt, the conveying path of which is shown in a simplified diagram), a cooling damper, and a temperature detection unit. The specific structure and connection relationships are as follows:

[0049] The slag well serves as a temporary storage and slag discharge structure for molten ash that has cooled and solidified after fuel combustion. It receives high-temperature slag blocks (typically 800-1200℃) generated by boiler combustion. A hydraulic shut-off gate is installed at the bottom to control the timing and flow rate of slag blocks falling into the slag discharge machine. The gate can be opened and closed according to slag discharge and equipment maintenance needs to prevent air leakage and abnormal slag block accumulation.

[0050] The slag discharger is equipped with a 30-40m long conveyor steel belt (its conveying path is shown in simplified lines in the diagram) to carry slag blocks and transport them from the slag well to the slag bin (the slag bin structure is not fully shown in the diagram; in actual applications, the end of the steel belt connects to the slag bin). The slag blocks move slowly along the steel belt over a long distance, with the entire transportation taking 20-30 minutes. During the movement, heat exchange with cooling air is achieved to achieve cooling.

[0051] The cooling damper is located on the side of the slag discharger (near the slag discharge end or strategically positioned along the conveying path) to introduce ambient air, which acts as a cooling medium to exchange heat with the high-temperature slag, carrying away heat to achieve cooling. Its opening is adjustable to control the cooling airflow and adapt to the slag cooling requirements under different heat loads.

[0052] The temperature detection unit includes a first temperature measuring point and a second temperature measuring point, which are used to monitor the temperature status of key locations in the system in real time.

[0053] The first temperature measuring point is located on the steel strip below the slag well outlet, focusing on the core area where the slag falls near the slag well (it can be attached to the surface of the steel strip or placed in the surrounding space). Through non-contact infrared temperature measurement technology, the initial temperature of the slag block (or the environment of the slag falling area) that has just fallen into the slag discharge machine is detected in real time, which directly reflects the heat load input status of the slag falling process and provides original data support for judging the amount of slag falling and temperature fluctuations in the boiler.

[0054] The second temperature measuring point is set on the steel belt in front of the cooling air damper inlet, and is reasonably arranged along the steel belt conveying path of the slag discharger (such as the middle conveying section before the cooling air action). It also relies on infrared temperature measurement technology to non-contactly monitor the intermediate temperature of the slag block before the cooling air intervention, accurately capture the temperature node before the cooling air action in the heat exchange process, and help quantify the residual heat state of the slag block before the cooling air damper is opened. Linked with the data of the first temperature measuring point, it can more clearly define the heat exchange efficiency and control space of the cooling process, and provide key basis for subsequent cooling air volume adaptability analysis.

[0055] The control system and application scenarios of the slag discharge system described in this application are for the purpose of more clearly illustrating the technical solutions of this application, and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of the control system of the slag discharge system and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0056] Next, the control method of the slag discharge system will be explained in detail with reference to the attached diagram. Figure 4 A flowchart illustrating a control method for a slag discharge system provided in this application. Specifically, it includes the following steps:

[0057] Step 410: Based on the conveying distance along the steel belt conveying direction from the first temperature measuring point to the second temperature measuring point, the steel belt operating parameters, and the thermal conductivity parameters of the slag block, determine the dynamic delay time of the slag block.

[0058] In the slag removal system, determining the dynamic delay time requires comprehensive consideration of the spatial location of the temperature measuring point, the operating state of the steel belt, and the thermal conductivity characteristics of the slag, in order to accurately capture the lag effect of slag temperature transmission. The specific implementation process is as follows:

[0059] First, the spatial layout parameters of the first and second temperature measuring points are obtained. The straight-line distance between the two measuring points along the steel belt conveying direction is measured using a laser rangefinder. For example, in the slag discharge system of a 300MW thermal power unit, the first temperature measuring point is located 0.5 meters behind the slag well outlet, and the second temperature measuring point is located 0.8 meters in front of the cooling damper. The measured straight-line distance L between the two along the steel belt conveying direction is 3 meters, with the measurement accuracy controlled within ±5 mm to ensure the accuracy of the spatial parameters. Simultaneously, the running speed and acceleration of the steel belt are read in real time from the Programmable Logic Controller (PLC) control system, with a sampling frequency of no less than 10Hz, to reflect the dynamic operating status of the steel belt. For example, under a certain operating condition, the initial running speed of the steel belt is 0.5 m / s, accelerating to 0.6 m / s during monitoring, corresponding to an acceleration of 0.02 m / s².

[0060] Secondly, the movement time of the slag block between the first and second temperature measuring points is determined based on the straight-line distance, running speed, and acceleration. When the steel belt acceleration is small (e.g., the absolute value of the steel belt acceleration ≤ 0.01 m / s²), the steel belt is considered to be moving at a constant speed, and the movement time of the slag block between the first and second temperature measuring points is the ratio of the straight-line distance to the running speed; if the steel belt is accelerating or decelerating, the formula for uniformly accelerated motion is used. Calculation. Taking the aforementioned working condition as an example, since the acceleration is 0.02 m / s², substituting into the formula... The calculated travel time is approximately 4.64 seconds. This step ensures that the calculated travel time matches the actual transmission process by distinguishing the movement state of the steel belt.

[0061] Furthermore, the thermal conductivity correction coefficient for the slag is determined based on its thermal conductivity, specific heat capacity, and density. The thermal conductivity, specific heat capacity, and density of the slag are obtained through laboratory analysis or online testing. For example, a certain slag has a thermal conductivity λ of 2.5 W / (m·Kelvin) and a specific heat capacity c... p The thermal diffusivity is 800 J / (kg·Kelvin) and the density ρ is 2800 kg / m³. First, calculate the thermal diffusivity. We obtained approximately 1.12 × 10⁻⁶. -6 square meters per second; then, based on thermal diffusivity, linear distance, and travel time, the thermal conduction correction coefficient is derived using the Fourier heat conduction equation. The calculated result is approximately 0.93, a coefficient used to compensate for the delayed effect of temperature conduction within the slag block.

[0062] Finally, the movement time and the heat conduction correction factor are multiplied to obtain the dynamic delay time for the slag block to move from the first temperature measuring point to the second temperature measuring point. Taking the aforementioned data as an example, the dynamic delay time τ = 4.64 × 0.93 ≈ 4.32 seconds.

[0063] In summary, the dynamic delay time is used to indicate the time lag effect of the temperature change of the slag block during its movement from the first temperature measuring point to the second temperature measuring point, caused by the combined effect of its own thermal conductivity characteristics (determined by thermal conductivity, specific heat capacity, and density) and the movement process (affected by the running speed and acceleration of the steel belt and the conveying distance between the two measuring points). This time is used to quantify the degree of delay in the transmission of the slag block temperature signal between the two measuring points under the influence of thermal conduction.

[0064] In another implementation, a measuring tape is used to measure the straight-line distance between two measuring points along the conveying direction of the steel belt. For example, in a small slag removal device, the first temperature measuring point is located at the beginning of the slag removal section, and the second temperature measuring point is set at a designated downstream position, and the straight-line distance L is measured. The average speed v of the steel belt during stable operation is read from the equipment drive system (if the steel belt runs smoothly, the acceleration can be regarded as zero). If the steel belt moves at a constant speed of 0.4 m / s in actual operation, then v = 0.4 m / s is taken. The thermal conductivity parameters of the slag block can be obtained from the general thermal property table of similar slag blocks, such as thermal conductivity λ and specific heat capacity cp. For example, the thermal conductivity of common slag is about 2.3 W / (m·Kelvin), and the specific heat capacity is about 750 J / (kg·Kelvin). Since the acceleration is approximately zero, the movement time is calculated according to the formula for uniform motion, i.e. If L = 2 meters, the movement time is 5 seconds. The heat conduction correction factor is an empirical value; based on statistical data from similar operating conditions, a correction factor of 0.9 is used when the movement time is 5 seconds and the straight-line distance is 2 meters. The final dynamic delay time is the product of the movement time and the correction factor, i.e., 5 × 0.9 = 4.5 seconds. This method simplifies the parameter measurement and calculation process, making it suitable for simple slag removal systems with low accuracy requirements, and can meet basic temperature transmission hysteresis analysis needs.

[0065] Step 420: Determine the historical time window based on the dynamic delay time, and obtain the original temperature sequence of the first temperature measuring point before the current time within the historical time window.

[0066] The transfer of slag from the first temperature measuring point to the second temperature measuring point involves a time delay due to physical movement and heat conduction. This dynamic delay time τ reflects the time taken for the same slag to transfer between the two measuring points, making the real-time temperature change at the second temperature measuring point essentially a delayed response to the temperature state at the first temperature measuring point before time τ. Therefore, determining the historical time window based on the dynamic delay time τ allows for the precise identification of historical temperature data that has a physical correspondence with the current real-time temperature.

[0067] In one implementation, a historical time window is constructed based on a determined dynamic delay time τ. Using the current time t as a baseline, the time interval [t-τ, t] is traced back by τ to form the historical time window. For example, if the dynamic delay time is calculated to be 4.5 seconds, the historical time window is the period within 4.5 seconds before the current time. The determination of this window needs to be combined with the actual operating conditions of the slag discharge system. For systems with slow temperature changes, the window range can be appropriately widened; for systems with rapid changes, the window accuracy needs to be strictly controlled. The original temperature sequence of the first temperature measuring point within this historical time window is extracted from the temperature monitoring database. Data extraction is achieved through SQL query statements. The extraction process must ensure data integrity; missing values ​​are filled using linear interpolation. If a temperature value is missing at a certain moment, the average of the two adjacent valid data points is used as the supplement. This historical data acquisition method based on delay time eliminates the time lag effect during slag block transportation, ensuring the consistency and physical correlation of temperature data from two measuring points in the time dimension.

[0068] Furthermore, the raw data typically contains multiple interfering factors superimposed on the actual temperature change trend. On the one hand, electromagnetic interference and sensor accuracy limitations in industrial settings introduce random noise, causing irregular fluctuations in temperature data, which can easily lead to misjudgments of the trend if used directly. On the other hand, physical factors such as heat conduction delays during slag transport and fluctuations in steel belt speed can imply dynamic changes in the temperature sequence, requiring filtering to remove noise and highlight the true trend. In addition, abnormal operating conditions of the slag discharge system (such as slag coking and abnormal cooling air) are often accompanied by sudden changes in temperature trends or abnormally large fluctuations, which are difficult to accurately identify using only the raw data. Therefore, this application performs trend filtering and fluctuation feature extraction on the extracted raw temperature sequence.

[0069] The following section explains the specific implementation methods for trend filtering and fluctuation feature extraction of the extracted original temperature sequence.

[0070] First, based on the temporal continuity and numerical correlation of adjacent data points in the original temperature sequence, a smoothed sequence reflecting the overall trend of temperature change is determined. The original sequence {T1, T2, ..., T...} is sampled at equal intervals. nTaking a sampling interval of 1 second as an example, a smooth curve is constructed using cubic spline interpolation. This method constructs a cubic polynomial between adjacent data points to ensure the continuity of the first and second derivatives of the curve at the nodes, thus preserving the overall trend of temperature change. For example, for temperature points (0s, 520℃), (1s, 522℃), and (2s, 518℃), spline interpolation will generate a curve that passes through these three points and transitions smoothly, eliminating local fluctuations caused by sensor noise. Regarding time continuity, if a small deviation in the sampling interval occurs (e.g., 1.2 seconds), the sequence is first calibrated to an equally spaced sequence using linear interpolation before smoothing.

[0071] Next, a residual sequence containing local fluctuation information is generated. The original temperature sequence is subtracted from the corresponding points of the smoothed sequence to obtain the residual. in The residual is a smoothed value. For example, if the original temperature at a point is 525℃ and the smoothed value is 523℃, then the residual is +2℃, reflecting the local deviation of the temperature at that moment relative to the overall trend. The residual sequence can highlight the smoothed fluctuation characteristics in the original data, such as random noise and short-term temperature abrupt changes, providing a basis for subsequent fluctuation analysis.

[0072] Next, determine the amplitude index reflecting the severity of temperature fluctuations. Calculate the standard deviation of the residual series. in The standard deviation is the mean of the residuals. It quantifies the dispersion of the residual data; a larger standard deviation indicates greater temperature fluctuation. For example, a residual sequence [-1, +2, -3, +1, 0] with a mean of -0.4 and a standard deviation of approximately 1.83 corresponds to an amplitude index of 1.83℃, indicating significant temperature fluctuations during that period. A threshold (e.g., 1.5℃) is set; when the standard deviation exceeds this threshold, it is considered an abnormal fluctuation.

[0073] Finally, the frequency index of temperature fluctuations is determined through frequency domain transformation. A Fast Fourier Transform (FFT) is performed on the residual sequence to convert the time-domain signal into a frequency-domain spectrum, identifying the peak frequency of the power spectral density. For example, performing an FFT on the residual sequence with 100 sampling points yields a significant peak at 0.2 Hz in the spectrum, indicating a periodicity of approximately 5 seconds in the temperature fluctuation (period = 1 / frequency). To improve frequency identification accuracy, a sliding window FFT (window size 50 points, 25 overlapping points) is used to track frequency changes in real time. The peak frequency is compared with a reference frequency under normal operating conditions (e.g., 0.1 Hz). If the deviation exceeds ±0.05 Hz, the fluctuation periodicity is deemed abnormal, suggesting potential problems such as slag transport speed fluctuations or cooling damper oscillations.

[0074] Step 430: Perform hysteresis correlation analysis on the measured temperature sequence within the preset time range of the second temperature measuring point and the original temperature sequence to obtain the characteristic group of slag temperature inertial change.

[0075] Because of the physical movement time and thermal conduction delay in the movement of the slag block from the first temperature measuring point to the second temperature measuring point, the temperature changes at the two measuring points are not synchronous, but rather occur with a time difference. The dynamic delay time is a quantitative representation of this actual time lag. Therefore, based on the dynamic delay time, the real-time temperature value of the second temperature measuring point is aligned with the corresponding historical temperature values ​​in the original temperature sequence. This eliminates the delay effect during slag block transportation, ensuring a physical correspondence between the two sets of temperature data in the time dimension. This accurately reflects the temperature change characteristics of the same slag block at different measuring points, providing a consistent data foundation for subsequent temperature difference analysis, fluctuation feature extraction, and system stability assessment.

[0076] Specifically, using the real-time temperature value T2(t) of the second temperature measuring point as a benchmark, the corresponding historical time t-τ of the first temperature measuring point is determined according to τ. The temperature value T1(t-τ) at that time is extracted from the original temperature sequence to form a time-aligned temperature pair (T1(t-τ), T2(t)). For example, if the dynamic delay time is calculated to be 4.32 seconds, then a correspondence is established between the current temperature value of the second temperature measuring point and the temperature value of the first temperature measuring point 4.32 seconds ago. For delays that are not integer seconds, a linear interpolation method is used to obtain the precise value from the original sequence. For example, when τ = 4.32 seconds, the temperature values ​​of t-4 seconds and t-5 seconds are extracted and interpolated with a weight of 0.32 to obtain T1(t-4.32 seconds).

[0077] Due to the influence of factors such as cooling effect and heat conduction characteristics during the transportation of slag blocks, the real-time temperature of the second temperature measuring point will differ from the historical temperature of the first temperature measuring point. The temperature difference sequence ΔT(t)=T2(t)-T1(t-τ) formed by calculating the difference between the two points can intuitively reflect the temperature change range at different times.

[0078] The direction and rate of change of the temperature difference sequence contain key information about the operating status of the cooling system. For example, a continuous increase in temperature difference may indicate a weakening of the cooling effect, while an excessively rapid rate of change may indicate an abnormal operating condition. Therefore, by determining the temperature difference trend index, the trend characteristics of temperature change can be quantitatively characterized, providing a basis for judging the stability of the cooling process of the slag discharge system and adjusting subsequent control strategies.

[0079] Specifically, a difference operation is performed on the temperature difference sequence to obtain the change in temperature between adjacent points, ΔΔT(t) = ΔT(t) - ΔT(t - Δt), where Δt is the sampling interval (e.g., 1 second). The sign and absolute value of the change are used to determine the temperature difference trend index. If ΔΔT(t) > 0 and the absolute value is ≥ 0.5℃ / second, it is determined to be an upward trend in temperature difference; if ΔΔT(t) < 0 and the absolute value is ≥ 0.5℃ / second, it is determined to be a downward trend in temperature difference; if the absolute value is < 0.5℃ / second, it is determined to be a stable trend. For example, if the temperature difference rises from 5℃ to 7℃ in a certain period (within a 2-second interval), the rate of change is 1℃ / second, which is determined to be a significant upward trend.

[0080] Temperature fluctuation amplitude reflects the stability and operating condition changes of the cooling process. Significant differences between real-time temperature fluctuation amplitude and the amplitude index under normal operating conditions often indicate abnormal system operation, such as cooling damper malfunction or sudden changes in slag particle size. By comparing the fluctuation amplitude of real-time temperature values ​​with the amplitude index, a fluctuation amplitude comparison index is generated. This allows for a quantitative comparison of real-time fluctuations with historical normal conditions, effectively identifying abnormal temperature fluctuations caused by equipment failure or changes in operating conditions. This provides an intuitive and quantitative basis for system fault early warning and operational status assessment.

[0081] Specifically, the standard deviation σ2 of the real-time temperature value T2(t) within a sliding window (e.g., 10 sampling points) is calculated as the real-time fluctuation amplitude; simultaneously, the baseline value σ0 of the amplitude index from the same historical period (e.g., the same operating conditions in the previous hour) is extracted (obtained through historical data statistics), and then calculated using the formula... Calculate the fluctuation amplitude comparison index. When K > 1.2, the fluctuation amplitude is considered abnormally large; when K < 0.8, the fluctuation amplitude is considered abnormally small; when K is between 0.8 and 1.2, it is within the normal range. For example, if the real-time standard deviation σ2 = 3.5℃ and the baseline value σ0 = 2.8℃, then K = 1.25, which is considered an abnormal fluctuation amplitude.

[0082] Ideally, the original temperature sequence at the first temperature measuring point and the real-time temperature value at the second temperature measuring point should exhibit a significant correlation during slag transport. This correlation reflects the stability and consistency of the temperature conduction process. Determining the correlation coefficient between the real-time temperature value and the original temperature sequence can quantify the degree of correlation between the two sets of data over time. A strong correlation usually indicates a stable slag transport path and a controllable heat conduction process, while a weakened correlation may suggest abnormalities such as changes in transport delay or fluctuations in cooling conditions. For example, the Pearson correlation coefficient algorithm can be used to perform correlation analysis on the two time-aligned sequences. The formula is: Where n is the window length (e.g., 20 sampling points), and The mean of the two sets of sequences is given. The correlation coefficient r ranges from -1 to 1, where r > 0.8 indicates a strong positive correlation, and r < 0.2 indicates a weak or no correlation. For example, an r = 0.92 for the two sets of sequences indicates high stability of the temperature conduction process.

[0083] Finally, based on the analysis results of the periodicity of temperature fluctuations using correlation coefficient, temperature difference trend index, fluctuation amplitude comparison index, and frequency index, a comprehensive index is generated to characterize the stability of the temperature conduction process. Specifically, the correlation coefficient r, temperature difference trend index S (+1 for an upward trend, -1 for a downward trend, and 0 for a stable state), fluctuation amplitude comparison index K, and frequency index f are weighted and summed using the following formula: Where w1 = 0.4, w2 = 0.2, w3 = 0.3, and w4 = 0.1 are weighting coefficients, and f0 is the reference frequency under normal operating conditions (e.g., 0.1 Hz). When I > 0.6, the temperature conduction process is considered stable; when I < 0.3, the process is considered unstable and requires adjustment.

[0084] In another implementation, when performing hysteresis correlation analysis on the real-time temperature of the second temperature measuring point and the original temperature sequence, a simplified sliding window cross-correlation method can be used to obtain the characteristic set of slag temperature inertial change. Specifically, a set of hysteresis time intervals (e.g., 0.5 seconds, 1 second, 1.5 seconds...5 seconds) is first set, and 10 equally spaced hysteresis values ​​are selected within a range of ±2 seconds, based on a 5-second dynamic delay time. For each hysteresis time τ, the cross-correlation coefficient between the real-time temperature sequence T2(t) and the original temperature sequence T1(t-τ) within the window of 10 consecutive sampling points is calculated. The hysteresis time corresponding to the peak value of the cross-correlation coefficient is recorded as the characteristic delay τ0, and the correlation coefficients of the three hysteresis points near the peak value constitute the inertial characteristic set. For example, if the peak value r = 0.85 appears at τ = 4.8 seconds, the correlation coefficients of 0.82, 0.85, and 0.81 corresponding to τ = 4.5 seconds, 4.8 seconds, and 5.1 seconds are taken as the characteristic set. This feature set can reflect the inertial delay range of slag temperature changes. If the peak position deviates from the reference delay time by more than 0.5 seconds or the peak coefficient is less than 0.7, the slag temperature inertial characteristics are determined to be abnormal, indicating that there may be sudden changes in slag block transport speed or changes in heat conduction conditions.

[0085] Step 440: Based on the slag temperature inertial change characteristic group and the preset load and slag quantity matching rules, control the opening of the cooling damper of the slag discharge system to control the temperature of the slag block when it reaches the second temperature measuring point within the preset temperature range.

[0086] There is an inherent correlation between boiler load and ash discharge volume. Essentially, changes in real-time boiler load parameters (such as main steam flow and pressure) directly represent increases or decreases in fuel combustion, which in turn determines the ash discharge volume. The preset load-ash discharge matching rule is a correspondence built based on historical operating data, summarizing the distribution patterns of ash discharge volume under different load conditions. Therefore, by determining the theoretical ash discharge volume for the current operating condition based on the boiler's real-time load parameters and this matching rule, the expected ash discharge volume for the current operating condition can be quickly and accurately obtained by leveraging the regular correlation between load and ash discharge volume. This provides fundamental data support for determining the subsequent cooling damper opening, ensuring that the cooling damper adjustment matches the actual ash discharge volume, thereby guaranteeing that the cooling effect of the ash discharge system meets the operating requirements.

[0087] Specifically, load parameters such as current main steam flow and pressure are read from the distributed control system. For example, if the real-time load of a 300MW unit is 280MW, the theoretical slag discharge rate is calculated as Q = 0.85 × load + 15 based on the load-slag matching rules established from historical operating data (e.g., slag discharge rate Q = 0.85 × load + 15 obtained through linear regression) = 0.85 × 280 + 15 = 253t / h.

[0088] Since temperature difference trend indicators can quantify the deviation of cooling effect from normal conditions, helping to determine the effectiveness of the cooling system; fluctuation amplitude comparison indicators can reveal the stability of slag characteristics (such as particle size and composition), and changes in slag characteristics directly affect the heat transfer process; comprehensive indicators assess the overall stability level of temperature transfer. Therefore, multi-dimensional analysis of the slag temperature inertia change characteristics group can comprehensively capture the operating characteristics of the slag discharge system from multiple levels such as cooling effect, slag characteristics, and system stability, transforming abstract slag temperature changes into specific quantitative indicators. This provides a comprehensive and in-depth basis for accurately judging the system operating status, identifying potential anomalies, and formulating reasonable cooling damper control strategies, ensuring that the analysis results are more reliable and instructive.

[0089] For example, based on the characteristic group (such as correlation coefficients of 0.82, 0.85, and 0.81 for lags of 4.5 seconds, 4.8 seconds, and 5.1 seconds, respectively), the cooling effect deviation rate is calculated according to the temperature difference trend index: if the temperature difference trend is an increase of 2℃ every 10 seconds, and the temperature difference should be stable at ±1℃ under normal operating conditions, then the deviation rate = (2-1) / 1 × 100% = 100%. Based on the fluctuation amplitude comparison index K = 1.25 (real-time fluctuation amplitude 3.5℃, baseline value 2.8℃), the stability of the slag characteristics is determined to be "abnormal fluctuation" (K > 1.2). Combined with the comprehensive index I = 0.495, and compared with the preset stability level matrix (such as I ≥ 0.6 for "stable", 0.3 ≤ I < 0.6 for "early warning", and I < 0.3 for "fault"), the operating status level of the slag discharge system is determined to be "early warning".

[0090] Finally, the opening degree of the cooling damper is determined based on the theoretical ash discharge volume, the analysis results of the characteristic group, and the control strategy table. Specifically, the real-time load parameters of the boiler are matched with the load range in the control strategy table to determine the load range to which the real-time load parameters belong; the corresponding ash temperature characteristic condition type is determined based on the cooling effect deviation rate, the judgment results of ash block characteristic stability, and the operating status level of the ash discharge system; and the opening degree of the cooling damper that matches the load range to which the real-time load parameters belong and the ash temperature characteristic condition type is found in the control strategy table.

[0091] For example, a 280MW load is matched with load ranges (e.g., 200-250MW, 250-300MW, 300-350MW) in the control strategy table, and assigned to the 250-300MW range. Based on a 100% cooling effect deviation rate, "abnormal fluctuation" in slag characteristic stability, and "warning" operating status level, the slag temperature characteristic condition type is determined to be "insufficient cooling - abnormal fluctuation - warning". The matching item for this load range and condition type is found in the control strategy table. For example, the strategy table specifies that for a 250-300MW load, the damper opening for the insufficient cooling - abnormal fluctuation - warning condition is 60%-70%, and the midpoint 65% is taken as the control command. This strategy table is established based on historical commissioning data. For example, under similar conditions with a 280MW load, a damper opening of 65% can stabilize the temperature difference at 1.5℃, with fluctuations controlled within 3.0℃, meeting system operating requirements.

[0092] In another implementation, a simplified threshold linkage control method is used to adjust the cooling damper opening based on the slag temperature inertial change characteristic group and the load-slag quantity matching rule. Specifically, the theoretical slag discharge volume is first calculated using the load-slag quantity matching rule (e.g., linear formula Q = 0.9 × load + 10). If the boiler load is 200MW under a certain operating condition, the theoretical slag quantity Q = 190t / h, and the corresponding basic damper opening is set to 50%. At the same time, the peak value of the cross-correlation coefficient in the slag temperature inertial change characteristic group is analyzed. If the peak value appears after a delay of 4 seconds and the coefficient is 0.75, the slag temperature conduction is judged to be normal. If the peak value shifts to 5 seconds and the coefficient is lower than 0.7, it indicates that the slag temperature conduction delay has increased, possibly due to an increase in slag quantity or insufficient cooling. In this case, the damper opening is increased by 10% of the theoretical slag quantity, that is, 19% for 190t / h, and the basic opening is adjusted from 50% to 69%. In addition, a threshold for the fluctuation amplitude comparison index K is set. When K>1.2, regardless of the load and slag volume, the opening is directly adjusted by 20 times the percentage of K exceeding the value (e.g., 2% when K=1.3). The above adjustment amounts are added together and rounded to obtain the final damper opening.

[0093] After completing the matching control of the cooling damper opening based on the load range and slag temperature characteristics, further design is needed for a dynamic adjustment mechanism under abnormal conditions. Specifically, if the temperature difference trend index continuously deviates from the benchmark value within the preset sampling period and the fluctuation amplitude comparison index exceeds the corresponding benchmark value, it indicates that there is a persistent anomaly in the cooling system; while when the comprehensive index is lower than the benchmark value by a certain proportion within the preset sampling period and the fluctuation amplitude comparison index is greater than the preset range, it reflects that the system stability has deviated from the normal threshold. At this time, the following strategy is needed to achieve adaptive adjustment of the damper opening:

[0094] If the temperature difference trend indicator continuously deviates from the benchmark value within the preset sampling period and the fluctuation amplitude exceeds the corresponding benchmark value, the deviation of the temperature difference trend indicator is calculated in real time using the preset sampling period (e.g., 30 seconds) as the time window. For example, if the benchmark value is set as a temperature difference change of ≤1℃ every 10 seconds, and the measured temperature difference continues to rise at a rate of 2℃ / 10 seconds within 30 seconds, the deviation is (2-1) / 1×100%=100%. Based on the linear relationship between the deviation and the damper opening adjustment (e.g., a 100% deviation corresponds to a 10% increase in damper opening), combined with the current damper opening (e.g., an initial opening of 60%), the adjusted opening is calculated to be 60%+10%=70%. During the adjustment process, a step-by-step adjustment principle should be followed, increasing the opening by 2% every 5 seconds to avoid excessive adjustment leading to overcooling. At the same time, the temperature difference should be monitored in real time. If the temperature difference trend index falls back to the reference value ±0.5℃ within 10 seconds after adjustment, the adjustment should be stopped. If there is no improvement, continue to increase the opening by the above proportion until the deviation is less than 50% or the damper opening reaches the upper limit of 80%.

[0095] If the comprehensive indicator is lower than the benchmark value by a certain percentage within the preset adoption period and the fluctuation amplitude comparison indicator is greater than the preset range, first determine the benchmark value (e.g., 0.6) and preset percentage (e.g., lower than the benchmark value by 20%, i.e., I < 0.48) of the comprehensive indicator, and at the same time determine whether the fluctuation amplitude comparison indicator exceeds the preset range (e.g., K > 1.3). For example, at a certain moment, the comprehensive indicator I = 0.45 (lower than the benchmark value by 25%) and the fluctuation amplitude comparison indicator K = 1.4 (exceeding the upper limit of the normal range by 0.2). Based on the degree of excess (0.2 / 0.1 = 2 times, assuming the upper limit of the normal range is 1.2), according to the preset nonlinear adjustment formula △α = 5% × (K - 1.2) × 2 (where △α is the opening adjustment amount), we calculate △α = 5% × 0.2 × 2 = 2%. If the current damper opening is 65%, adjust it to 65% + 2% = 67%, and simultaneously activate the fluctuation amplitude opening feedback mechanism, updating the K value every 10 seconds. If the K value falls below 1.2 and the comprehensive index rises above 0.5, stop adjusting; if the K value continues to rise, adjust it in a gradient of 3% for every 0.1 increase, until K ≤ 1.3 or the opening reaches the safe upper limit of 75%.

[0096] In summary, this application constructs a dynamic time delay calculation model based on spatial layout, steel strip parameters, and slag thermal characteristics by setting dual temperature measuring points below the slag well outlet and in front of the cooling damper inlet on the steel strip. This model can accurately quantify the time lag of slag movement and heat conduction. By extracting the original temperature sequence using historical time windows, smoothing and residual analysis are performed to decompose trend and fluctuation information. Then, combined with lag correlation analysis, a slag temperature inertial feature set covering temperature difference trends, fluctuation amplitudes, periodicity, and conduction stability is generated, which can deeply characterize the thermal evolution law of the slag cooling process. Using load-slag matching rules to associate boiler operating conditions with theoretical slag discharge, and after multi-dimensional analysis of the feature set, the opening of the cooling damper is dynamically adjusted through load range matching, operating condition type determination, and strategy table lookup. Furthermore, for scenarios where the opening deviation exceeds the limit, differential adjustments are made based on the abnormal characteristics of temperature difference trends, comprehensive indicators, and fluctuation amplitudes, achieving precise matching between cooling air volume and slag heat load. These features work synergistically to effectively overcome the cooling delay of long-distance, slow slag discharge and the lag of traditional preset control, improve the stability of cooling effect, and ensure the safe and efficient operation of the boiler system.

[0097] It is understood that, in order to achieve the functions in the above embodiments, the computer device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and method steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0098] Furthermore, as a response to the above Figure 4 The implementation of the method embodiment shown in this application provides a control device for a slag discharge system. The embodiment of this device corresponds to the foregoing method embodiment. For ease of reading, this embodiment will not repeat the details of the foregoing method embodiment, but it should be understood that the device in this embodiment can correspondingly implement all the contents of the foregoing method embodiment. Specifically, as shown... Figure 5 As shown, the control device 500 of the slag discharge system includes:

[0099] The determination module 510 is used to determine the dynamic delay time of the slag block based on the conveying distance along the steel belt conveying direction from the first temperature measuring point to the second temperature measuring point, the steel belt operating parameters, and the slag block thermal conductivity parameters. The dynamic delay time is used to indicate the difference between the time required for the slag block to drop from the temperature of the first temperature measuring point to a preset temperature range and the time required for the slag block to move from the first temperature measuring point to the second temperature measuring point.

[0100] The first feature module 520 is used to determine the historical time window based on the dynamic delay time and obtain the original temperature sequence of the first temperature measuring point before the current time within the historical time window.

[0101] The second feature module 530 is used to perform hysteresis correlation analysis between the measured temperature sequence within a preset time range of the second temperature measuring point and the original temperature sequence to obtain the slag temperature inertial change feature group.

[0102] The control module 540 is used to control the opening of the cooling damper of the slag discharge system according to the slag temperature inertial change characteristics group and the preset load and slag quantity matching rules, so as to control the temperature of the slag block when it reaches the second temperature measuring point within the preset temperature range.

[0103] Furthermore, such as Figure 5 As shown, module 510 is specifically used to acquire the running speed and acceleration of the steel belt; determine the movement time of the slag block between the first temperature measuring point and the second temperature measuring point based on the conveying distance, running speed and acceleration; determine the thermal conductivity correction coefficient of the slag block based on the thermal conductivity, specific heat capacity and density of the slag block; and determine the dynamic delay time of the slag block based on the movement time and the thermal conductivity correction coefficient.

[0104] Furthermore, such as Figure 5 As shown, the first feature module 520 is specifically used to determine a smooth sequence reflecting the overall trend of temperature change based on the temporal continuity and numerical correlation of adjacent data points in the original temperature sequence; generate a residual sequence containing local fluctuation information based on the smooth sequence and the original temperature sequence; determine an amplitude index that can reflect the intensity of temperature fluctuation based on the dispersion of data points in the residual sequence and the degree of deviation from the mean; and determine a frequency index that can characterize the periodic characteristics of temperature fluctuation by performing frequency domain transformation analysis on the residual sequence.

[0105] Furthermore, such as Figure 5 As shown, the second feature module 530 is specifically used to align the real-time temperature values ​​in the measured temperature sequence within a preset time range of the second temperature measuring point with the corresponding historical temperature values ​​in the original temperature sequence based on the dynamic delay time; calculate the point-by-point difference between the real-time temperature value and the original temperature sequence to form a temperature difference sequence, and determine the temperature difference trend index based on the direction and rate of change of the temperature difference sequence; generate a fluctuation amplitude comparison index by comparing the fluctuation amplitude of the real-time temperature value with the difference of the amplitude index; determine the correlation coefficient between the real-time temperature value and the original temperature sequence; and generate a comprehensive index to characterize the stability of the temperature conduction process based on the analysis results of the correlation coefficient, temperature difference trend index, fluctuation amplitude comparison index, and frequency index on the periodicity of temperature fluctuation.

[0106] Furthermore, such as Figure 5As shown, the control module 540 is specifically used to determine the theoretical ash discharge volume under the current operating conditions based on the boiler's real-time load parameters and the preset load and ash volume matching rules. The load and ash volume matching rules are based on the correspondence between load and ash discharge volume established based on historical operating data. It calculates the cooling effect deviation rate based on the temperature difference trend index, judges the stability of ash block characteristics based on the fluctuation amplitude comparison index, and determines the operating status level of the ash discharge system based on the comprehensive index and the preset stability level matrix. It also determines the opening degree of the cooling damper based on the theoretical ash discharge volume, the characteristic group analysis results, and the control strategy table.

[0107] Furthermore, such as Figure 5 As shown, the control module 540 is specifically used to match the real-time load parameters of the boiler with the load range in the control strategy table to determine the load range to which the real-time load parameters of the boiler belong; determine the corresponding slag temperature characteristic working condition type based on the judgment results of the cooling effect deviation rate, slag block characteristic stability and the operating status level of the slag discharge system; and search in the control strategy table for the opening degree of the cooling damper that matches the load range to which the real-time load parameters of the boiler belong and the slag temperature characteristic working condition type, so as to control the temperature of the slag block when it reaches the second temperature measuring point to be within the preset temperature range.

[0108] Furthermore, such as Figure 5 As shown, the control module 540 is also used to adjust the cooling damper opening according to the degree of deviation of the temperature difference trend index if the temperature difference trend index continues to deviate from the benchmark value within the preset adoption period and the fluctuation amplitude comparison index exceeds the corresponding benchmark value; and to adjust the cooling damper opening according to the degree of deviation of the fluctuation amplitude comparison index if the comprehensive index is lower than the benchmark value by a certain percentage within the preset adoption period and the fluctuation amplitude comparison index is greater than the preset range.

[0109] This application provides a storage medium storing a program that, when executed by a processor, implements the control method of the slag discharge system.

[0110] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program with the following method steps: Based on the conveying distance along the steel belt conveying direction from the first temperature measuring point to the second temperature measuring point, the steel belt operating parameters, and the thermal conductivity parameters of the slag block, determine the dynamic delay time of the slag block; the dynamic delay time is used to indicate the difference between the time required for the slag block to drop from the temperature of the first temperature measuring point to a preset temperature range and the time required for the slag block to move from the first temperature measuring point to the second temperature measuring point; determine a historical time window based on the dynamic delay time, and obtain the original temperature sequence of the first temperature measuring point before the current moment within the historical time window; perform a hysteresis correlation analysis on the measured temperature sequence within the preset time range of the second temperature measuring point and the original temperature sequence to obtain a slag temperature inertial change characteristic group; and control the opening of the cooling damper of the slag discharge system according to the slag temperature inertial change characteristic group and a preset load and slag quantity matching rule, so as to control the temperature of the slag block when it reaches the second temperature measuring point to be within the preset temperature range.

[0111] Furthermore, the running speed and acceleration of the steel belt are obtained; the movement time of the slag block between the first and second temperature measuring points is determined based on the conveying distance, running speed, and acceleration; the thermal conductivity correction coefficient of the slag block is determined based on the thermal conductivity, specific heat capacity, and density of the slag block; and the dynamic delay time of the slag block is determined based on the movement time and the thermal conductivity correction coefficient.

[0112] Furthermore, based on the temporal continuity and numerical correlation of adjacent data points in the original temperature sequence, a smoothed sequence reflecting the overall trend of temperature change is determined; a residual sequence containing local fluctuation information is generated based on the smoothed sequence and the original temperature sequence; based on the dispersion of data points in the residual sequence and the degree of deviation from the mean, an amplitude index reflecting the severity of temperature fluctuation is determined; and through frequency domain transformation analysis of the residual sequence, a frequency index characterizing the periodicity of temperature fluctuation is determined.

[0113] Furthermore, based on the dynamic delay time, the real-time temperature values ​​in the measured temperature sequence within the preset time range of the second temperature measuring point are aligned with the corresponding historical temperature values ​​in the original temperature sequence along the time axis; the point-by-point difference between the real-time temperature value and the original temperature sequence is calculated to form a temperature difference sequence, and the temperature difference trend index is determined based on the direction and rate of change of the temperature difference sequence; by comparing the fluctuation amplitude of the real-time temperature value with the degree of difference of the amplitude index, a fluctuation amplitude comparison index is generated; the correlation coefficient between the real-time temperature value and the original temperature sequence is determined; based on the analysis results of the temperature fluctuation periodicity using the correlation coefficient, temperature difference trend index, fluctuation amplitude comparison index, and frequency index, a comprehensive index for characterizing the stability of the temperature conduction process is generated.

[0114] Furthermore, the theoretical ash discharge volume under the current operating condition is determined based on the boiler's real-time load parameters and the preset load and ash volume matching rules. The load and ash volume matching rules are based on the correspondence between load and ash discharge volume established from historical operating data. The cooling effect deviation rate is calculated based on the temperature difference trend index, the stability of ash block characteristics is judged based on the fluctuation amplitude comparison index, and the operating status level of the ash discharge system is determined based on the comprehensive index and the preset stability level matrix. The opening degree of the cooling damper is determined based on the theoretical ash discharge volume, the characteristic group analysis results, and the control strategy table.

[0115] Furthermore, the real-time load parameters of the boiler are matched with the load range in the control strategy table to determine the load range to which the real-time load parameters of the boiler belong; the corresponding slag temperature characteristic condition type is determined based on the judgment results of the cooling effect deviation rate, slag block characteristic stability and the operating status level of the slag discharge system; the opening of the cooling damper that matches the load range to which the real-time load parameters of the boiler belong and the slag temperature characteristic condition type is found in the control strategy table, so as to control the temperature of the slag block when it reaches the second temperature measuring point within the preset temperature range.

[0116] Furthermore, if the temperature difference trend indicator continuously deviates from the benchmark value within the preset adoption period and the fluctuation amplitude comparison indicator exceeds the corresponding benchmark value, the cooling damper opening is adjusted according to the degree of deviation of the temperature difference trend indicator; if the comprehensive indicator is lower than the benchmark value by a certain percentage within the preset adoption period and the fluctuation amplitude comparison indicator is greater than the preset range, the cooling damper opening is adjusted according to the degree to which the fluctuation amplitude comparison indicator exceeds the normal range.

[0117] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0118] In a typical configuration, the device includes one or more processors (CPUs), memory, and a bus. The device may also include input / output interfaces, network interfaces, etc.

[0119] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM, and memory includes at least one memory chip. Memory is an example of computer-readable media.

[0120] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0121] It should also be noted that 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 process, method, article, or apparatus. Unless otherwise specified, 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 that element.

[0122] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0123] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A control method for a slag discharge system, characterized in that, A first temperature measuring point is set on the steel strip below the slag well outlet, and a second temperature measuring point is set on the steel strip in front of the cooling air damper inlet. The method includes: Based on the conveying distance along the steel belt conveying direction from the first temperature measuring point to the second temperature measuring point, the steel belt operating parameters, and the thermal conductivity parameters of the slag block, the dynamic delay time of the slag block is determined. The dynamic delay time is used to indicate the difference between the time required for the slag block to drop from the temperature of the first temperature measuring point to a preset temperature range and the time required for the slag block to move from the first temperature measuring point to the second temperature measuring point. Based on the dynamic delay time, a historical time window is determined, and the original temperature sequence of the first temperature measuring point before the current moment is obtained within the historical time window. By performing hysteresis correlation analysis on the measured temperature sequence within a preset time range of the second temperature measuring point and the original temperature sequence, a set of slag temperature inertial change characteristics is obtained. Based on the slag temperature inertial change characteristic group and the preset load and slag quantity matching rules, the opening of the cooling damper of the slag discharge system is controlled so as to control the temperature of the slag block when it reaches the second temperature measuring point within the preset temperature range.

2. The method according to claim 1, characterized in that, Based on the conveying distance along the steel belt conveying direction from the first temperature measuring point to the second temperature measuring point, the steel belt operating parameters, and the thermal conductivity parameters of the slag block, the dynamic delay time of the slag block is determined, including: Obtain the running speed and acceleration of the steel strip; The movement time of the slag block between the first temperature measuring point and the second temperature measuring point is determined based on the conveying distance, the operating speed, and the acceleration. The thermal conductivity correction coefficient of the slag block is determined based on its thermal conductivity, specific heat capacity, and density. The dynamic delay time of the slag block is determined based on the movement time and the thermal conductivity correction coefficient.

3. The method according to claim 2, characterized in that, After obtaining the original temperature sequence of the first temperature measuring point within the historical time window up to the current time, the method further includes: Based on the temporal continuity and numerical correlation of adjacent data points in the original temperature sequence, a smooth sequence reflecting the overall trend of temperature change is determined. A residual sequence containing local fluctuation information is generated based on the smoothed sequence and the original temperature sequence; Based on the dispersion of data points in the residual sequence and the degree of deviation from the mean, an amplitude index that can reflect the severity of temperature fluctuations is determined. By performing frequency domain transformation analysis on the residual sequence, a frequency index that can characterize the periodicity of temperature fluctuations is determined.

4. The method according to claim 3, characterized in that, By performing hysteresis correlation analysis on the measured temperature sequence within a preset time range at the second temperature measuring point and the original temperature sequence, a set of slag temperature inertial change characteristics is obtained, including: Based on the dynamic delay time, the real-time temperature value in the measured temperature sequence within the preset time range of the second temperature measuring point is aligned with the temperature value at the corresponding historical moment in the original temperature sequence on the time axis. Calculate the point-by-point difference between the real-time temperature value and the original temperature sequence to form a temperature difference sequence, and determine the temperature difference trend index based on the direction and rate of change of the temperature difference sequence; A fluctuation amplitude comparison index is generated by comparing the fluctuation amplitude of the real-time temperature value with the difference between the amplitude index. Determine the correlation coefficient between the real-time temperature value and the original temperature sequence; Based on the analysis results of the correlation coefficient, the temperature difference trend index, the fluctuation amplitude comparison index, and the frequency index on the periodicity of temperature fluctuations, a comprehensive index is generated to characterize the stability of the temperature conduction process.

5. The method according to claim 4, characterized in that, Based on the slag temperature inertial change characteristic group and the preset load and slag quantity matching rules, the opening of the cooling damper of the slag discharge system is controlled, including: The theoretical ash discharge volume under the current operating conditions is determined based on the real-time load parameters of the boiler and the preset load and ash quantity matching rules. The load and ash quantity matching rules are based on the correspondence between load and ash discharge volume established by historical operating data. The cooling effect deviation rate is calculated based on the temperature difference trend index, the stability of slag block characteristics is judged based on the fluctuation amplitude comparison index, and the operating status level of the slag discharge system is determined based on the comprehensive index and the preset stability level matrix. The opening degree of the cooling damper is determined based on the theoretical slag discharge volume, the characteristic group analysis results, and the control strategy table.

6. The method according to claim 5, characterized in that, The opening degree of the cooling damper is determined based on the theoretical slag discharge volume, the characteristic group analysis results, and the control strategy table, including: Match the real-time load parameters of the boiler with the load range in the control strategy table to determine the load range to which the real-time load parameters of the boiler belong. The corresponding slag temperature characteristic working condition type is determined based on the cooling effect deviation rate, the judgment result of the slag block characteristic stability, and the operating status level of the slag discharge system. The control strategy table is used to find the cooling damper opening that matches the load range to which the boiler real-time load parameters belong and the slag temperature characteristic operating condition type, so as to control the temperature of the slag block when it reaches the second temperature measuring point to be within the preset temperature range.

7. The method according to claim 6, characterized in that, When the deviation between the cooling damper opening and the historical opening under the same operating conditions exceeds a preset threshold, the method further includes: If the temperature difference trend index continues to deviate from the benchmark value within the preset adoption period and the fluctuation amplitude comparison index exceeds the corresponding benchmark value, the opening of the cooling damper is adjusted according to the degree of deviation of the temperature difference trend index. If the comprehensive index is lower than the benchmark value by a certain percentage within a preset period and the fluctuation amplitude comparison index is greater than the preset range, the opening of the cooling damper is adjusted according to the degree to which the fluctuation amplitude comparison index exceeds the normal range.

8. A control device for a slag discharge system, characterized in that, The device includes: The determination module is used to determine the dynamic delay time of the slag block based on the conveying distance along the steel belt conveying direction from the first temperature measuring point to the second temperature measuring point, the steel belt operating parameters, and the thermal conductivity parameters of the slag block. The dynamic delay time is used to indicate the difference between the time required for the slag block to drop from the temperature of the first temperature measuring point to a preset temperature range and the time required for the slag block to move from the first temperature measuring point to the second temperature measuring point. The first feature module is used to determine a historical time window based on the dynamic delay time and obtain the original temperature sequence of the first temperature measuring point before the current moment within the historical time window. The second feature module is used to perform hysteresis correlation analysis on the measured temperature sequence within a preset time range of the second temperature measuring point and the original temperature sequence to obtain the slag temperature inertial change feature group. The control module is used to control the opening of the cooling damper of the slag discharge system according to the slag temperature inertial change characteristic group and the preset load and slag quantity matching rules, so as to control the temperature of the slag block when it reaches the second temperature measuring point within the preset temperature range.

9. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the storage medium to perform the control method of the slag discharge system as described in any one of claims 1-7.

10. An electronic device, characterized in that, The device includes at least one processor, at least one memory connected to the processor, and a bus; wherein the processor and the memory communicate with each other through the bus; the processor is used to call program instructions in the memory to execute the control method of the slag discharge system as described in any one of claims 1-7.

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