Pipeline anti-blocking control method and device, electronic equipment and storage medium

Abstract

The invention discloses a pipeline anti-blocking control method and device, electronic equipment and a storage medium, and relates to the technical field of automation. Compared with the related technology, the pipeline anti-blocking control method detects the pressure gradient change in a pipeline, opens a valve element when the pressure difference exceeds the limit, and controls each group of bin pumps according to a preset priority time sequence in combination with regional grouping locking logic; meanwhile, real-time ash amount data are collected, the real-time ash density is calculated in combination with the historical ash density, then the opening threshold value of the anti-blocking valve is dynamically adjusted based on the mapping model of the ash density and the pressure, the method can adapt to ash material density fluctuation, the limitation of a single pressure threshold value is avoided, and unnecessary pressurization purging is reduced; the technical problems that in an existing anti-blocking valve control method, response lag or false triggering is caused by a single pressure threshold triggering mechanism, and the operation stability and economical efficiency of the system are affected by frequent pressurization purging under the high ash density working condition can be solved, and the technical effect of improving the operation stability and economical efficiency of the pneumatic ash conveying system is achieved.

Description

Technical Field

[0001] This disclosure relates to the field of automation technology, and in particular to a control method and apparatus, electronic equipment and storage medium for preventing pipeline blockage. Background Technology

[0002] Pneumatic ash conveying systems are a key component in the ash conveying process of electrostatic precipitators in thermal power plants, and are widely used in fly ash treatment and environmental emission control of coal-fired units.

[0003] With the continuous increase in the proportion of low-quality coal used, fly ash density has increased significantly, posing a dual challenge to traditional suspended flow conveying methods: frequent pipeline blockages and excessive energy consumption. Related technologies employ a basic anti-blockage control system through the coordinated operation of fixed pressure threshold control, gas-associated pipeline pressurization, and manual monitoring. However, this anti-blockage valve control method directly uses a single pressure threshold triggering mechanism, which may lead to response lag or false triggering due to fluctuations in ash density. Furthermore, it may require frequent pressurization and purging under high ash density conditions, thus affecting the stability and economy of the system operation. Summary of the Invention

[0004] This disclosure provides a control method, device, electronic equipment, and storage medium for pipeline anti-clogging. Its main purpose is to solve the problems of response lag or false triggering caused by fluctuations in ash density, or the need for frequent pressurization and purging under high ash density conditions, which affect the stability and economy of system operation.

[0005] According to a first aspect of this disclosure, a control method for preventing pipe blockage is provided, comprising:

[0006] Detect changes in the pressure gradient within the pipeline, and determine to open the valve core in response to a pressure difference exceeding a set threshold.

[0007] Based on the regional grouping interlocking logic, each group of warehouse pumps is triggered and controlled according to a preset priority; however, there is a timing difference between different groups of warehouse pumps.

[0008] Collect real-time gray volume data and combine it with historical gray density data to calculate real-time gray density;

[0009] The opening threshold of the anti-clogging valve is dynamically adjusted based on the mapping model of gray density and pressure.

[0010] Optionally, the detection of pressure gradient changes within the pipeline, in response to a pressure difference exceeding a set threshold, determines to open the valve core by:

[0011] The pressure gradient change is obtained based on a multi-stage pressure chamber; wherein the multi-stage pressure chamber includes a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber;

[0012] When the low-pressure chamber determines that the pipeline pressure difference has reached a set threshold, it determines to open the valve core.

[0013] Optionally, the triggering control of each group of silo pumps according to a preset priority based on the region grouping interlocking logic includes:

[0014] The silo pumps are divided into groups according to the electric field. The valves within the group operate synchronously, and the timing difference between groups is set by a pneumatic delay device. When the pressure of the tracing gas main pipe is lower than the preset protection threshold, the trigger command of the corresponding group of silo pumps is blocked.

[0015] Optionally, the step of collecting real-time gray volume data and calculating real-time gray density by combining it with historical gray density data includes:

[0016] Collect the ash conveying amount per cycle, and calculate the real-time ash density based on the ash conveying amount and coal feed amount data;

[0017] The accuracy of the real-time gray density is determined by retrieving the historical average gray density within a preset period as a standard value.

[0018] Optionally, the dynamic adjustment of the anti-clogging valve's opening threshold based on the gray density-pressure mapping model includes:

[0019] Based on a preset time interval, compare the actual number of pipe blockages with the predicted value;

[0020] The parameters in the mapping model are adjusted based on the comparison results to optimize the calculation accuracy of the activation threshold.

[0021] According to a second aspect of this disclosure, a control device for preventing pipe blockage is provided, comprising:

[0022] The detection unit is used to detect changes in the pressure gradient inside the pipeline and determines to open the valve core in response to a pressure difference exceeding a set threshold.

[0023] The control unit is used to trigger and control each group of warehouse pumps according to a preset priority based on the area grouping interlocking logic; there is a timing difference between different groups of warehouse pumps.

[0024] The acquisition unit is used to acquire real-time gray volume data and calculate real-time gray density by combining it with historical gray density data.

[0025] The optimization unit is used to dynamically adjust the opening threshold of the anti-clogging valve based on the mapping model of gray density and pressure.

[0026] Optionally, the detection unit is further configured to:

[0027] The pressure gradient change is obtained based on a multi-stage pressure chamber; wherein the multi-stage pressure chamber includes a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber;

[0028] When the low-pressure chamber determines that the pipeline pressure difference has reached a set threshold, it determines to open the valve core.

[0029] Optionally, the control unit is further configured to:

[0030] The silo pumps are divided into groups according to the electric field. The valves within the group operate synchronously, and the timing difference between groups is set by a pneumatic delay device. When the pressure of the tracing gas main pipe is lower than the preset protection threshold, the trigger command of the corresponding group of silo pumps is blocked.

[0031] Optionally, the acquisition unit is further configured to:

[0032] Collect the ash conveying amount per cycle, and calculate the real-time ash density based on the ash conveying amount and coal feed amount data;

[0033] The accuracy of the real-time gray density is determined by retrieving the historical average gray density within a preset period as a standard value.

[0034] Optionally, the optimization unit is further configured to:

[0035] Based on a preset time interval, compare the actual number of pipe blockages with the predicted value;

[0036] The parameters in the mapping model are adjusted based on the comparison results to optimize the calculation accuracy of the activation threshold.

[0037] According to a third aspect of this disclosure, an electronic device is provided, comprising:

[0038] At least one processor; and

[0039] A memory communicatively connected to the at least one processor; wherein,

[0040] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0041] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0042] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0043] The control method, device, electronic equipment, and storage medium for pipeline anti-clogging provided in this disclosure mainly include: detecting changes in pressure gradient within the pipeline, and determining to open the valve core in response to a pressure difference exceeding a set threshold; triggering control of each group of pumps according to a preset priority based on regional grouping interlocking logic; wherein there is a timing difference between different groups of pumps; collecting real-time ash volume data and calculating real-time ash density by combining it with historical ash density data; and dynamically adjusting the opening threshold of the anti-clogging valve based on a mapping model between ash density and pressure. Compared with related technologies, this application detects changes in the pressure gradient within the pipeline and opens the valve core when the differential pressure exceeds the limit. Combined with the regional grouping interlocking logic, it controls the pumps in each group of silos according to a preset priority sequence. Simultaneously, it collects real-time ash volume data and calculates the real-time ash density based on historical ash density. Then, it dynamically adjusts the opening threshold of the anti-blocking valve based on the mapping model between ash density and pressure. This can adapt to fluctuations in ash density, avoid the limitations of a single pressure threshold, and reduce unnecessary pressurization and purging. Therefore, it can solve the technical problems of response lag or false triggering caused by the single pressure threshold triggering mechanism in existing anti-blocking valve control methods, as well as the technical problems of frequent pressurization and purging affecting the stability and economy of system operation under high ash density conditions. This achieves the technical effect of improving the stability and economy of pneumatic ash conveying system operation.

[0044] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0045] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0046] Figure 1 A schematic flowchart illustrating a pipeline anti-clogging control method provided in an embodiment of this disclosure;

[0047] Figure 2 This is a schematic diagram of the structure of a control device for preventing pipe blockage provided in an embodiment of the present disclosure;

[0048] Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0049] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0050] The following description, with reference to the accompanying drawings, outlines a control method, apparatus, electronic device, and storage medium for preventing pipe blockage according to embodiments of the present disclosure.

[0051] Figure 1 This is a schematic flowchart of a pipeline anti-clogging control method provided in an embodiment of the present disclosure.

[0052] like Figure 1 As shown, the method includes the following steps:

[0053] Step 101: Detect the change in pressure gradient within the pipeline; in response to a pressure difference exceeding a set threshold, determine to open the valve core.

[0054] The pressure gradient change in the pipeline specifically refers to the change in pressure difference at different locations inside the pipeline or at different times at the same location during the ash conveying process. This change directly reflects the flow state of the ash material in the pipeline. When the ash material flows smoothly, the pressure gradient is small and stable. However, when the ash material accumulates or the flow is obstructed, which may lead to pipe blockage, the local pressure will rise abnormally, and the pressure gradient will increase accordingly.

[0055] To accurately detect this pressure gradient change, the valve of the device is specially designed with a three-stage pressure chamber structure, including a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber, which are isolated from each other by a copper-engineering plastic composite diaphragm. This composite diaphragm combines the rigidity of copper with the elasticity of engineering plastic, effectively blocking pressure interference between different chambers and producing precise deformation under pressure difference, thereby converting the pressure signal into a mechanical action signal. Among them, the low-pressure chamber is mainly used to sense the basic pressure state in the pipeline. When the ash flow rate in the pipeline is normal (such as 68m / s under design conditions), the pressure in the low-pressure chamber is usually stable at ≤0.03MPa. At this time, the diaphragm does not deform significantly, and the valve core remains closed.

[0056] The threshold value is an initial base value determined based on the prediction of the risk of blockage in the pneumatic ash conveying system and a large amount of experimental data. In this device, the basic threshold value is set at 0.05 MPa. When the local pressure difference ΔP in the pipeline exceeds this threshold due to ash accumulation or other reasons, it means that the ash flow has shown obvious signs of obstruction, and blockage is likely to occur if intervention is not timely. At this time, the pressure difference between the low-pressure chamber and the medium-pressure chamber will drive the copper engineering plastic composite diaphragm to deform. The thrust generated by this deformation acts directly on the valve core, thereby triggering the valve core to open. Through this triggering mechanism based on pressure gradient changes, the valve core can accurately respond to abnormal states of ash flow. Compared with the traditional method that relies on a fixed pressure threshold, its triggering sensitivity is increased by 3 times, allowing for timely intervention in the early stages of blockage risk and effectively preventing blockage accidents.

[0057] Step 102: Based on the regional grouping interlocking logic, trigger control is performed on each group of warehouse pumps according to a preset priority; there is a timing difference between different groups of warehouse pumps.

[0058] The regional grouping interlocking logic is a pioneering control strategy designed for the distribution characteristics of silo pumps in pneumatic ash conveying systems. Specifically, it involves grouping the silo pumps in the ash conveying system according to their respective electric field regions. For example, four silo pumps on side A of an electric field can be grouped together as an independent group. The anti-blocking valves within the same group will operate synchronously when triggered, ensuring the consistency and efficiency of the ash conveying process within the group.

[0059] The preset priority settings are determined based on a comprehensive consideration of factors such as the ash conveying demand, ash load, and system importance of each electric field area, aiming to ensure the orderly triggering control of each group of silo pumps. For example, in practical applications, the silo pump group on side A of electric field one is set as the first priority due to its main ash conveying task or higher risk of ash accumulation, the silo pump group on side B of electric field one is the second priority, and the silo pump group on side A of electric field two is the third priority, etc., so that the system can respond to the anti-blocking needs of the higher priority groups first and deal with potential pipe blockage risks in a timely manner.

[0060] The timing difference between different groups of silo pumps is precisely achieved through pneumatic time-delay relays. Its core purpose is to prevent a sudden drop in the pressure of the gas tracing header caused by multiple groups of pumps simultaneously activating their anti-blocking actions. Specifically, during trigger control, the first priority group (e.g., side A of electric field one) starts directly without delay; the second priority group (e.g., side B of electric field one) starts after a 0.5-second delay; and the third priority group (e.g., side A of electric field two) starts after a 1.0-second delay, forming a 0.5-second time-sequence control. This timing difference control effectively disperses the instantaneous load on the gas tracing header, ensuring that the header pressure remains stable within a reasonable range. Meanwhile, the system is also equipped with a gas tracing main pipe pressure protection mechanism. When the main pipe pressure is lower than the protection threshold set for the corresponding group (e.g., ≥0.55MPa for side A and side B of electric field 1, and ≥0.50MPa for side A of electric field 2), the interlock function will be automatically triggered to suspend the triggering action of the corresponding group, further preventing the abnormal drop in main pipe pressure from affecting the normal operation of the entire ash conveying system. Through the synergistic effect of regional grouping, priority sorting, and time difference control, the orderly linkage of anti-blocking actions of each group of silo pumps and the stable guarantee of system pressure are achieved.

[0061] Step 103: Collect real-time gray volume data and calculate real-time gray density by combining it with historical gray density data;

[0062] Real-time ash content data is primarily collected through the weighing module of the silo pump configured in the device. This module can capture the mass change of ash material within the silo pump during a single ash conveying process, thereby accurately obtaining real-time data on the current ash conveying volume. Simultaneously, to comprehensively reflect the characteristics of the ash material, the real-time ash content data also needs to be combined with the coal feed rate signal transmitted by the DCS (Distributed Control System). The coal feed rate data reflects the total amount of raw coal entering the system, and combined with the ash conveying volume, it can indirectly reflect the proportion of ash in the raw coal, providing more comprehensive basic parameters for subsequent ash density calculations.

[0063] Historical ash density data is derived from the system's storage and retrieval of operational data from the past 7 days. Specific details can be found in the historical coal ash distribution data recorded in the relevant equipment materials. This historical data includes the variation patterns of ash density under different operating conditions, such as the average and fluctuation range of ash density for different coal types and combustion conditions. Its purpose is to provide a benchmark reference for real-time ash density calculations, effectively offsetting calculation deviations that may be caused by instantaneous data fluctuations, and improving the stability and reliability of the results.

[0064] When calculating real-time ash density, the system uses the real-time ash conveying volume collected by the silo pump weighing module as a basis, combines it with the DCS coal feed rate to calculate the current ash mass percentage, and then calibrates it using the ash volume characteristics or historical density averages recorded in historical ash density data. For example, by converting the real-time ash conveying volume with the pipeline volume parameters during the corresponding ash conveying period (or combining historical ash volume data under the same operating conditions), the real-time ash volume is calculated, and then the real-time ash density is obtained from the basic formula "density = mass / volume". This calculation process organically integrates real-time dynamic data with historical data, ensuring accurate perception of the current ash state while reducing the impact of instantaneous interference on the calculation results by leveraging the reference role of historical data. This provides accurate and reliable data for subsequent dynamic adjustment of the anti-clogging threshold based on ash density.

[0065] Step 104: Dynamically adjust the opening threshold of the anti-blocking valve based on the mapping model of gray density and pressure.

[0066] The ash density deviation specifically refers to the difference between the real-time calculated ash density and the system design ash density. It directly reflects the density difference between the current ash material and the ash material under design conditions. When the ash density is higher than the design value, the ash material's fluidity decreases, the risk of pipe blockage increases, and the deviation is positive; when the ash density is lower than the design value, the risk of pipe blockage is relatively reduced, and the deviation is negative. The coefficient k in the model is 0.01 MPa / 0.1 g / cm³. 3 Its physical meaning is that for every 0.1 g / cm³ of ash density produced, 3 To account for the deviation, the opening threshold of the anti-blocking valve needs to be adjusted by 0.01 MPa to ensure that the threshold is linearly adapted to the change in ash density.

[0067] The dynamic adjustment process is as follows: First, the system compares the real-time gray density calculated in step 103 with the design gray density to determine the gray density deviation. Then, this deviation is substituted into the mapping model, and combined with the base value of 0.05 MPa and the coefficient k, the required activation threshold is calculated. For example, when the real-time gray density changes from the design value of 0.8 g / cm³... 3 Increased to 1.0 g / cm 3 At that time, the ash density deviation was 0.2 g / cm³. 3 Substituting the values ​​into the model, we get the opening threshold as follows: `Opening threshold = 0.05MPa + 0.01 × (0.2 / 0.1) = 0.07MPa`. This means the opening threshold increases with increasing ash density, triggering anti-blocking actions earlier to address the risk of pipe blockage from high-density ash. Simultaneously, to ensure the long-term accuracy of the model, a calibration mechanism is implemented: the actual number of blockages is compared hourly with the model's predicted blockage risk value. If the actual number of blockages deviates significantly from the prediction, the coefficient k is dynamically adjusted. This ensures the mapping model can continuously adapt to the complex changes in ash density under different coal types and combustion conditions, ultimately achieving a precise match between the anti-blocking valve opening threshold and ash characteristics. This effectively prevents blockage while avoiding unnecessary premature triggering, thus reducing energy consumption.

[0068] In some embodiments, detecting changes in the pressure gradient within the pipeline, and determining to open the valve core in response to a pressure difference exceeding a set threshold, includes:

[0069] The pressure gradient change is obtained based on a multi-stage pressure chamber; wherein the multi-stage pressure chamber includes a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber;

[0070] When the low-pressure chamber determines that the pipeline pressure difference has reached a set threshold, it determines to open the valve core.

[0071] The multi-stage pressure chamber specifically includes a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber. Each chamber is isolated by a copper-engineering plastic composite diaphragm. This composite diaphragm combines the structural stability of copper with the elastic deformation characteristics of engineering plastics, effectively blocking pressure interference between different chambers. At the same time, it can generate precise mechanical deformation under the action of pressure difference, thereby reliably converting the pressure signal in the pipeline into the power to trigger the action.

[0072] The acquisition of pressure gradient changes is mainly accomplished through multi-level pressure chambers that stratify different pressure states within the pipeline: the low-pressure chamber is primarily responsible for monitoring the base pressure and initial pressure changes within the pipeline, capturing any local pressure anomalies that may occur during ash flow in real time; the medium-pressure and high-pressure chambers correspond to monitoring different pressure ranges, together forming a comprehensive coverage of pipeline pressure changes. When ash flows smoothly within the ash conveying pipeline, the pipeline pressure is stable, and the pressure in the low-pressure chamber is typically maintained at a low level (e.g., ≤0.03MPa at normal flow rates). At this time, the diaphragm shows no significant deformation, and the valve core remains closed. However, when ash accumulates or flow is obstructed, the local pressure within the pipeline increases, leading to an increased pressure gradient. When the pipeline pressure difference detected by the low-pressure chamber reaches a set threshold (e.g., a base set threshold of 0.05MPa), it indicates that the ash flow has shown significant signs of obstruction. At this point, the pressure difference between the low-pressure chamber and other chambers drives the copper engineering plastic composite diaphragm to deform. The thrust generated by this deformation directly acts on the valve core, triggering the valve core to open and enabling timely intervention against the risk of pipe blockage. Through this hierarchical sensing based on multi-stage pressure chambers and a threshold triggering mechanism dominated by low-pressure chambers, the device can accurately capture changes in pressure gradients, ensuring that the valve core opens in time at the initial stage of pipe blockage risk, effectively improving the sensitivity and reliability of anti-blockage response.

[0073] In some embodiments, the triggering control of each group of pumps according to a preset priority based on the region grouping interlocking logic includes:

[0074] The silo pumps are divided into groups according to the electric field. The valves within the group operate synchronously, and the timing difference between groups is set by a pneumatic delay device. When the pressure of the tracing gas main pipe is lower than the preset protection threshold, the trigger command of the corresponding group of silo pumps is blocked.

[0075] The grouping of silo pumps by electric field is a grouping method determined based on the actual layout and operating characteristics of the pneumatic ash conveying system. Specifically, the silo pumps are divided into units based on the electric field in the ash conveying system. For example, the four silo pumps on side A of electric field are divided into an independent group. Since the silo pumps in the same electric field have similar ash sources, ash conveying paths and load characteristics, this grouping method can ensure the coordination of control within the group.

[0076] Synchronous valve operation within a group refers to the consistent action of all anti-blocking valves within the same group when triggered. That is, when any silo pump or pipeline in the group detects a risk of blockage and triggers an action command, all valves in the group simultaneously open the gas tracing passage. By uniformly pressurizing the airflow, the pressure of the ash conveying pipeline within the group is ensured to be balanced, thus avoiding the aggravation of ash accumulation caused by the failure of local valves to act in a timely manner.

[0077] The timing difference between groups, set by a pneumatic delay device, is a collaborative control strategy designed to prevent a sudden drop in the pressure of the gas-tracing main pipe caused by the simultaneous activation of anti-blocking actions by multiple groups of silo pumps. The pneumatic delay device used is specifically a pneumatic delay relay, which forms a timing difference by preset delay parameters for different groups. For example, the A side group of electric field one is set as the first priority, with no delay upon triggering; the B side group of electric field one is set as the second priority, with a 0.5-second delay upon activation; and the A side group of electric field two is set as the third priority, with a 1.0-second delay upon activation. This 0.5-second timing difference disperses the instantaneous load on the main pipe, ensuring stable main pipe pressure.

[0078] Meanwhile, the system is equipped with a "tracing gas main pipe pressure protection mechanism," which presets corresponding main pipe pressure protection thresholds for different groups. For example, the protection threshold for groups A and B of electric field one is set to ≥0.55MPa, and for group A of electric field two, it is set to ≥0.50MPa. When the monitored value of the tracing gas main pipe pressure is lower than the preset protection threshold for the corresponding group, the system will immediately trigger the interlock function, suspending the execution of the trigger command for that group. This prevents the interruption of tracing gas supply or insufficient ash conveying power due to insufficient main pipe pressure, further ensuring the orderly linkage of anti-blocking actions of the entire ash conveying system under the premise of stable pressure.

[0079] In some embodiments, the step of collecting real-time gray volume data and calculating real-time gray density by combining it with historical gray density data includes:

[0080] Collect the ash conveying amount per cycle, and calculate the real-time ash density based on the ash conveying amount and coal feed amount data;

[0081] The accuracy of the real-time gray density is determined by retrieving the historical average gray density within a preset period as a standard value.

[0082] The acquisition of single ash conveying volume relies primarily on the weighing module of the silo pump configured in the unit. This module can capture the dynamic changes in the mass of ash within the silo pump during a single ash conveying process in real time, thereby accurately obtaining the ash volume data corresponding to the current ash conveying action. The "coal feed rate data" originates from the real-time transmission signal from the DCS (Distributed Control System) connected to the system. The coal feed rate data provided by the DCS reflects the total amount of raw coal entering the boiler during that period. The acquisition unit correlates the single ash conveying volume with the corresponding coal feed rate data for that period. By analyzing the proportion of ash in the raw coal and combining it with the volumetric characteristics of the ash during the ash conveying process (such as based on pipeline volume parameters or historical ash volume data under the same operating conditions), the real-time ash density can be derived using the density calculation formula (density = mass / volume), thus accurately reflecting the current density and flow characteristics of the ash.

[0083] Meanwhile, to ensure the accuracy of real-time ash density calculation results, a historical data verification mechanism is set up in the method, namely, "retrieving the historical average value of ash density within a preset period as a standard value to determine the accuracy of real-time ash density." The "preset period" here specifically refers to the past 7 days. The system automatically retrieves the stored ash density operation data for the past 7 days and calculates its average value. This historical average value serves as a standard value reflecting the normal characteristics of ash density under normal operating conditions and is used for comparison and analysis with the ash density calculated in real time. If the deviation between the real-time ash density and the historical average value is within the normal operating condition fluctuation range, the real-time ash density calculation is confirmed to be accurate and effective. If the deviation exceeds a reasonable range, the system will identify it as data anomaly and prompt checks on the measurement accuracy of the silo pump weighing module, the stability of the DCS coal feed signal transmission, or whether significant changes in ash density characteristics have occurred due to coal type changes, combustion condition adjustments, etc. Thus, through the synergistic effect of real-time data acquisition and calculation and historical average standard verification, a reliable data foundation is provided for subsequent adaptive adjustment of ash density.

[0084] In some embodiments, the dynamic adjustment of the opening threshold of the anti-clogging valve based on the gray density-pressure mapping model includes:

[0085] Based on a preset time interval, compare the actual number of pipe blockages with the predicted value;

[0086] The parameters in the mapping model are adjusted based on the comparison results to optimize the calculation accuracy of the activation threshold.

[0087] The preset time interval is set to one hour. This interval can capture the dynamic changes in ash density characteristics in the ash conveying system in a timely manner, while avoiding excessive verification that would waste system resources. Within this time interval, the system will automatically count the actual number of pipe blockages that occur, that is, the actual number of events in the ash conveying process where the flow of the pipeline is obstructed due to the accumulation of ash. At the same time, based on the mapping model between the current ash density and pressure (`opening threshold = base value 0.05MPa + k × ash density deviation`) and real-time ash density data, the system will calculate the predicted value of the pipe blockage risk within this period, that is, the predicted number of times pipe blockage may occur theoretically.

[0088] Comparing the actual number of blockages with the predicted value is the core step in verifying the accuracy of the model: if the actual number of blockages is significantly more than the predicted value, it indicates that the parameters in the current model (mainly the coefficient k) may be too small, resulting in a low opening threshold setting. This fails to raise the threshold in time when the risk of blockage increases to trigger the anti-blockage action in advance, thus the actual blockage risk is not fully covered. If the actual number of blockages is significantly less than the predicted value, it may be that the parameter k is too large, resulting in an excessively high opening threshold, causing the anti-blockage valve to be triggered too early or too frequently, increasing unnecessary energy consumption.

[0089] Based on the comparison results, the parameters in the mapping model are corrected, specifically by dynamically adjusting the coefficient k to address the aforementioned deviations: when the actual number of blockages exceeds the predicted value, the value of k is appropriately increased to make the impact of ash density deviation on the opening threshold more significant, increasing the threshold's magnitude with increasing ash density and triggering the anti-blocking action earlier; when the actual number of blockages is less than the predicted value, the value of k is appropriately decreased to reduce the impact of ash density deviation on the threshold and avoid invalid triggering due to an excessively high threshold. Through this hourly deviation comparison and parameter correction, the mapping model can continuously adapt to the complex changes in ash density under different coal types and combustion conditions, continuously optimizing the calculation accuracy of the opening threshold, ultimately achieving a balance between anti-blocking effectiveness and energy consumption control, ensuring that the anti-blocking valve can effectively prevent blockages without wasting resources due to unreasonable threshold settings.

[0090] Corresponding to the aforementioned pipeline anti-clogging control method, this invention also proposes a pipeline anti-clogging control device. Since the device embodiments of this invention correspond to the aforementioned method embodiments, details not disclosed in the device embodiments can be referred to the aforementioned method embodiments, and will not be repeated here.

[0091] Figure 2 This is a schematic diagram of the structure of a pipeline anti-clogging control device provided in an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes:

[0092] Furthermore, in one possible implementation of the embodiments of this disclosure,

[0093] Detection unit 21 is used to detect changes in pressure gradient within the pipeline and, in response to a pressure difference exceeding a set threshold, determines to open the valve core.

[0094] Control unit 22 is used to trigger control of each group of warehouse pumps according to a preset priority based on the area grouping interlocking logic; wherein there is a timing difference between different groups of warehouse pumps;

[0095] Acquisition unit 23 is used to acquire real-time gray volume data and calculate real-time gray density by combining it with historical gray density data;

[0096] Optimization unit 24 is used to dynamically adjust the opening threshold of the anti-blocking valve based on the mapping model of gray density and pressure.

[0097] Furthermore, in one possible implementation of this disclosure, the detection unit 21 is further configured to:

[0098] The pressure gradient change is obtained based on a multi-stage pressure chamber; wherein the multi-stage pressure chamber includes a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber;

[0099] When the low-pressure chamber determines that the pipeline pressure difference has reached a set threshold, it determines to open the valve core.

[0100] Furthermore, in one possible implementation of this disclosure, the control unit 22 is further configured to:

[0101] The silo pumps are divided into groups according to the electric field. The valves within the group operate synchronously, and the timing difference between groups is set by a pneumatic delay device. When the pressure of the tracing gas main pipe is lower than the preset protection threshold, the trigger command of the corresponding group of silo pumps is blocked.

[0102] Furthermore, in one possible implementation of this disclosure, the acquisition unit 23 is further configured to:

[0103] Collect the ash conveying amount per cycle, and calculate the real-time ash density based on the ash conveying amount and coal feed amount data;

[0104] The accuracy of the real-time gray density is determined by retrieving the historical average gray density within a preset period as a standard value.

[0105] Furthermore, in one possible implementation of this disclosure, the optimization unit 24 is further configured to:

[0106] Based on a preset time interval, compare the actual number of pipe blockages with the predicted value;

[0107] The parameters in the mapping model are adjusted based on the comparison results to optimize the calculation accuracy of the activation threshold.

[0108] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0109] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0110] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0111] like Figure 3As shown, device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 302 or a computer program loaded from storage unit 308 into RAM (Random Access Memory) 303. RAM 303 can also store various programs and data required for the operation of device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via bus 304. I / O (Input / Output) interface 305 is also connected to bus 304.

[0112] Multiple components in device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of monitors, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0113] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the pipe blockage prevention control method. For example, in some embodiments, the pipe blockage prevention control method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the aforementioned pipe anti-blocking control method by any other suitable means (e.g., by means of firmware).

[0114] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0118] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0119] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service ecosystem, addressing the shortcomings of traditional physical hosts and VPS (Virtual Private Server, or simply "VPS") services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0120] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0121] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0122] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A control method for preventing pipe blockage, characterized in that, include: Detect changes in the pressure gradient within the pipeline, and determine to open the valve core in response to a pressure difference exceeding a set threshold. Based on the regional grouping interlocking logic, each group of warehouse pumps is triggered and controlled according to a preset priority; however, there is a timing difference between different groups of warehouse pumps. Collect real-time gray volume data and combine it with historical gray density data to calculate real-time gray density; The opening threshold of the anti-clogging valve is dynamically adjusted based on the mapping model of gray density and pressure.

2. The pipeline anti-blockage control method according to claim 1, characterized in that, The method for detecting changes in pressure gradient within the pipeline, and determining to open the valve core in response to a pressure difference exceeding a set threshold, includes: The pressure gradient change is obtained based on a multi-stage pressure chamber; wherein the multi-stage pressure chamber includes a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber; When the low-pressure chamber determines that the pipeline pressure difference has reached a set threshold, it determines to open the valve core.

3. The pipeline anti-blockage control method according to claim 1, characterized in that, The trigger control of each group of silo pumps based on the region grouping interlocking logic and according to the preset priority includes: The silo pumps are divided into groups according to the electric field. The valves within the group operate synchronously, and the timing difference between groups is set by a pneumatic delay device. When the pressure of the tracing gas main pipe is lower than the preset protection threshold, the trigger command of the corresponding group of silo pumps is blocked.

4. The pipeline anti-blockage control method according to claim 1, characterized in that, The process of collecting real-time gray volume data and calculating real-time gray density by combining it with historical gray density data includes: Collect the ash conveying amount per cycle, and calculate the real-time ash density based on the ash conveying amount and coal feed amount data; The accuracy of the real-time gray density is determined by retrieving the historical average gray density within a preset period as a standard value.

5. The pipeline anti-blockage control method according to claim 1, characterized in that, The dynamic adjustment of the anti-clogging valve's opening threshold based on the gray density-pressure mapping model includes: Based on a preset time interval, compare the actual number of pipe blockages with the predicted value; The parameters in the mapping model are adjusted based on the comparison results to optimize the calculation accuracy of the activation threshold.

6. A control device for preventing pipe blockage, characterized in that, include: The detection unit is used to detect changes in the pressure gradient inside the pipeline and determines to open the valve core in response to a pressure difference exceeding a set threshold. The control unit is used to trigger and control each group of warehouse pumps according to a preset priority based on the area grouping interlocking logic; there is a timing difference between different groups of warehouse pumps. The acquisition unit is used to acquire real-time gray volume data and calculate real-time gray density by combining it with historical gray density data. The optimization unit is used to dynamically adjust the opening threshold of the anti-clogging valve based on the mapping model of gray density and pressure.

7. The pipeline anti-clogging control device according to claim 6, characterized in that, The detection unit is also used for: The pressure gradient change is obtained based on a multi-stage pressure chamber; wherein the multi-stage pressure chamber includes a low-pressure chamber, a medium-pressure chamber, and a high-pressure chamber; When the low-pressure chamber determines that the pipeline pressure difference has reached a set threshold, it determines to open the valve core.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-5.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-5.

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