Intelligent acoustic soot blower control system based on DCS

Abstract

This invention provides an intelligent acoustic sootblower control system based on DCS, comprising: a sensor module for collecting equipment operating parameters; a field control station for preliminary processing and buffering of the equipment operating parameters collected by the sensors; a data acquisition module for integrating and formatting the data; a distributed control module for establishing an optimal sootblowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment operating parameters, for calculating ideal sootblowing information and dynamic adjustment results determined based on the ideal sootblowing information; controlling the sootblowing action of the acoustic sootblower according to the dynamic adjustment results; and a central monitoring station for providing feedback on the differences in effects before and after sootblowing, and optimizing the dynamic adjustment model based on the differences. This invention aims to solve the problems of decreased heat exchange efficiency and increased resistance caused by ash accumulation in low-temperature economizers, improve the overall operating performance and lifespan of low-temperature economizers, and achieve energy-saving and environmental protection goals.

Description

Technical Field

[0001] This invention relates to the field of thermal power generation technology, and in particular to an intelligent acoustic soot blower control system based on DCS. Background Technology

[0002] In thermal power generation and many industrial sectors, boilers are one of the key pieces of equipment. With the continuous improvement of energy efficiency requirements, low-temperature economizers are increasingly widely used in boiler systems. By recovering waste heat from boiler flue gas, low-temperature economizers can improve boiler thermal efficiency, reduce fuel consumption, and reduce pollutant emissions, which has significant energy-saving and environmental protection significance.

[0003] During the operation of low-temperature economizers, dust particles in the flue gas gradually deposit on the surface of heat exchange elements, forming ash accumulation. Ash accumulation has always been a significant factor affecting the performance of low-temperature economizers, and its development process is quite complex. As time goes on, the thickness of the ash layer increases, which first leads to a gradual decrease in the heat exchange efficiency of the economizer. This is because the thermal conductivity of the ash layer is much lower than that of the heat exchange element material itself, hindering heat transfer and affecting the effective transfer of heat from the flue gas to the working fluid (such as water), thus reducing the overall system's heat recovery efficiency. At the same time, ash accumulation also increases the flow resistance of the flue gas. When ash accumulates on the surface of the heat exchange elements, the flue gas channel narrows, and the frictional resistance of gas flow increases. This requires the fan to provide a higher head to maintain the flue gas flow, thereby increasing the fan's energy consumption. Moreover, severe ash accumulation may cause problems such as equipment corrosion and wear. Some components in the ash (such as acidic substances) may react chemically with the metal surface under certain conditions, leading to corrosion of the heat exchange elements. Furthermore, the high-speed scouring of the heat exchange element surface by ash particles carried by the flue gas also causes surface wear, shortening the equipment's service life.

[0004] Traditional soot blowing methods mainly include steam soot blowing and mechanical rapping soot blowing. Steam soot blowing uses the impact force of high-temperature and high-pressure steam to remove accumulated ash. This method can remove ash to a certain extent, but it has many drawbacks. On the one hand, steam soot blowing requires a large amount of high-quality steam, increasing the operating cost of the system. On the other hand, during the steam soot blowing process, the high-temperature steam may cause thermal shock to the heat exchange elements, leading to a decline in the performance of the heat exchange element materials. Long-term use will affect the reliability and service life of the equipment. Moreover, the soot blowing effect of steam soot blowing is not ideal. For some sticky ash or ash that has already hardened, steam soot blowing is difficult to completely remove. Mechanical rapping soot blowing uses mechanical devices to generate vibration to dislodge the ash. However, this method is prone to causing mechanical damage to the equipment, and the rapping force and frequency are difficult to control precisely, resulting in uneven soot blowing. Local ash accumulation problems may still exist, and it cannot effectively solve the impact of ash accumulation on heat exchange efficiency and resistance.

[0005] With the development of automation control technology and information technology, distributed control systems (DCS) have been widely used in industrial process control. DCS systems can realize centralized monitoring and decentralized control of complex industrial processes, and have advantages such as high reliability and strong flexibility. However, in the field of low-temperature economizer soot blowing control, the existing technology has not fully utilized the advantages of DCS systems, and there is a lack of a soot blowing system that can comprehensively and accurately carry out intelligent control based on the economizer operating status and ash accumulation.

[0006] Therefore, there is an urgent need in this field for an intelligent acoustic soot blower control system based on DCS to solve the above problems. Summary of the Invention

[0007] This invention provides an intelligent acoustic sootblower control system based on DCS, which aims to solve the problems of decreased heat exchange efficiency and increased resistance caused by ash accumulation in low-temperature economizers, as well as various problems existing in the current sootblowing method, thereby improving the overall operating performance and equipment life of the low-temperature economizer and achieving the goal of energy conservation and environmental protection.

[0008] This invention provides an intelligent acoustic sootblower control system based on DCS, comprising:

[0009] The sensor module, installed in key parts of the acoustic soot blower, is used to collect equipment operating parameters in real time; the equipment operating parameters include economizer structural information and internal fluid information.

[0010] The field control station is connected to the sensor module and is used to perform preliminary processing and caching of the equipment operating parameters collected by the sensors.

[0011] The data acquisition module, which is connected to the field control station, is used to integrate and format the data to ensure that the equipment operating parameters are in a uniform and accurate format.

[0012] A distributed control module, connected to the data acquisition module, establishes an optimal soot blowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment operating parameters. This model is used to calculate ideal soot blowing information and dynamic adjustment results determined based on the ideal soot blowing information. The soot blowing action of the acoustic soot blower is controlled according to the dynamic adjustment results.

[0013] The central monitoring station, which is connected to the distributed control module and the sensor module, is used to provide feedback on the differences in the effects before and after soot blowing, and to optimize and adjust the dynamic adjustment model based on the differences.

[0014] According to the present invention, an intelligent acoustic soot blower control system based on DCS is provided, wherein the economizer structural information includes inlet and outlet pressure difference ΔP, temperature difference ΔT, pipe length L, pipe radius r, economizer volume V, ambient humidity H, and economizer heat exchange efficiency η.

[0015] The internal fluid information includes fluid viscosity μ, fluid flow rate Q, fluid density ρ, and fluid temperature T.

[0016] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the field control station includes:

[0017] The data caching unit is used to temporarily store the data collected by the sensor module. Its caching capacity and storage speed meet the requirements of the system's real-time data processing and ensure that data is not lost.

[0018] The preliminary processing unit performs preliminary processing on the cached data, including filtering, amplification, and digitization, to ensure that the data meets the format requirements for subsequent transmission and processing, thereby improving data quality.

[0019] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the data acquisition module includes:

[0020] The data integration unit receives data from the field control station and integrates the operating parameters of each device according to predetermined rules to ensure the correlation and integrity of the data.

[0021] The format processing unit formats the integrated device operating parameters, converting the data into a format that the distributed control module can recognize and process.

[0022] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the distributed control module includes:

[0023] The ash accumulation thickness simulation unit, which is connected to the format processing unit, establishes an ash accumulation thickness calculation model based on the inlet and outlet pressure difference ΔP, pipe length L, pipe radius r, fluid viscosity μ, and fluid flow rate Q, and is used to calculate the simulated ash accumulation thickness value h.

[0024] The rate of change calculation unit, which is connected to the ash thickness simulation unit and the format processing unit, determines the current rate of change of ash thickness based on the simulated ash thickness value h. Determine the current rate of change of temperature difference based on the inlet and outlet temperature difference ΔT.

[0025] The acoustic velocity simulation unit, which is connected to the format processing unit, establishes an acoustic velocity calculation model based on the economizer volume V, fluid temperature T, and gas parameters determined through previous experiments, and is used to calculate the simulated value v of the acoustic propagation velocity.

[0026] The optimal parameter determination unit, which is connected to the ash thickness simulation unit and the sound wave velocity simulation unit, is used to fuse the ash thickness simulation value h and the sound wave propagation velocity simulation value v to establish the optimal soot blowing simulation model and calculate the ideal soot blowing information; the ideal soot blowing information includes the ideal soot blowing frequency f0 and the ideal soot blowing power P0.

[0027] The dynamic adjustment unit, connected to the optimal parameter determination unit and the rate of change calculation unit, adjusts the current ash thickness based on the rate of change. Rate of change of temperature difference A dynamic adjustment model is established based on ideal soot blowing information to calculate the current dynamic adjustment result; the dynamic adjustment result includes adjusting the soot blowing frequency f. new And adjust the soot blowing power P new .

[0028] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the ash accumulation thickness calculation model is as follows:

[0029]

[0030] Where h is the simulated value of ash accumulation thickness, ΔP is the pressure difference between inlet and outlet, L is the pipe length, r is the pipe radius, μ is the fluid viscosity, Q is the fluid flow rate, and k is the ash accumulation permeability. The ash accumulation permeability k is used to reflect the ease with which fluid can pass through the ash accumulation layer. Its value is determined by back-calculation experiments using a permeability meter in conjunction with the ash accumulation thickness calculation model.

[0031] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the acoustic velocity calculation model is as follows:

[0032]

[0033] Where v is the simulated speed of sound, γ is the adiabatic index, V is the economizer volume, T is the fluid temperature, R is the gas constant, and M... eq For equivalent molar mass, a eq and b eq It is the equivalent van der Waals constant;

[0034] The adiabatic index γ and the gas constant R are determined by looking up a table based on the type of gas in the economizer.

[0035] Equivalent molar mass M eq Through formula Determine, where i is the gas type in the economizer. M represents the volume fraction of the i-th type of gas. i To and Corresponding molar mass; volume fraction and molar mass Mi All values ​​are known values;

[0036] Equivalent van der Waals constant a eq and b eq Through formula and Determined; where a i Let b be the first van der Waals constant for the i-th type of gas. i Let a be the second van der Waals constant for the i-th type of gas, and let a be the first van der Waals constant. i Second van der Waals constant b i All values ​​are known values.

[0037] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the optimal sootblowing simulation model is:

[0038]

[0039] Where f0 is the ideal soot blowing frequency, P0 is the ideal soot blowing power; v is the simulated value of sound wave propagation speed, h is the simulated value of ash accumulation thickness, μ is the fluid viscosity, ρ is the fluid density, H is the ambient humidity, η is the economizer heat exchange efficiency; λ is the thermal conductivity of the economizer heat exchange element, E is the elastic modulus of the heat exchange element material, and the values ​​of λ and E are determined based on the specific material of the economizer heat exchange element.

[0040] α is the first angular parameter, representing the angular parameter related to the reflection and refraction of sound waves in the dust-accumulating medium; the calculation formula is:

[0041] Where z1 = ρ1*v1, z2 = ρ2*v2; z1 is the air impedance, which is determined based on the air density ρ1 and the speed of sound propagation in the air v1; z2 is the ash impedance, which is determined based on the ash density ρ2 and the speed of sound propagation in the ash v2.

[0042] β is the second angle parameter, representing an angle parameter related to the economizer structure and ash accumulation distribution; the calculation formula is...

[0043] Among them, C un The coefficient of non-uniformity of ash accumulation on the pipeline is obtained by statistically analyzing the ash accumulation thickness at different locations on the pipeline; m and n are based on the arrangement of the economizer, i.e., m rows and n columns.

[0044] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the dynamic adjustment model is as follows:

[0045]

[0046] Among them, f newTo adjust the soot blowing frequency, P new To adjust the soot blowing power, k1, k2, k3, k4, k5, and k6 are dynamic adjustment coefficients, which are determined experimentally based on the economizer's design parameters and material properties.

[0047] According to the present invention, an intelligent acoustic sootblower control system based on DCS is provided, wherein the central monitoring station includes:

[0048] The strategy optimization unit is used to judge the soot blowing effect based on the change value ΔΔP of the economizer inlet and outlet pressure difference before and after soot blowing. When ΔΔP is lower than the preset threshold, it is determined that the soot blowing effect is not obvious and a feedback signal is generated.

[0049] A coefficient feedback unit, connected to the strategy optimization unit and the dynamic adjustment unit, is used to adjust the dynamic adjustment coefficients k1, k2, k3, k4, k5, and k6 in the dynamic adjustment model upon receiving a feedback signal, so as to adjust the soot blowing frequency f. new And adjust the soot blowing power P new The air is gradually raised according to the preset rising amount to improve the soot blowing effect until the feedback signal disappears.

[0050] Compared with the prior art, the beneficial effects of this application are as follows:

[0051] This application collects a wealth of operating parameters through sensor modules, such as the pressure difference and temperature difference between the economizer inlet and outlet, pipe dimensions, fluid characteristics, and ambient humidity. Based on these physical characteristics, it establishes ash thickness calculation models, sound wave velocity calculation models, and optimal soot blowing simulation models. These models can accurately calculate ash thickness and sound wave propagation speed, thereby determining the ideal soot blowing frequency and power to achieve precise soot blowing. Compared with the blindness of traditional soot blowing methods, this approach can effectively avoid over-blowing or under-blowing, significantly improve the soot blowing effect, and make ash cleaning more thorough. This maintains the economizer's high heat exchange efficiency, ensures high efficiency in heat recovery, reduces flue gas temperature, and further improves the overall thermal efficiency of the boiler system.

[0052] This application utilizes a dynamic adjustment model to adjust the soot blowing frequency and power in real time based on the rate of change of ash thickness and the rate of change of temperature difference, so that the soot blowing process can adapt to changes in the economizer's operating status in a timely manner; when ash accumulation increases rapidly or heat exchange efficiency decreases significantly, the soot blowing intensity is rapidly increased; when the ash accumulation is stable or the heat exchange effect is good, the soot blowing frequency and power are appropriately reduced to avoid energy waste and achieve a balance between energy saving and efficient soot blowing.

[0053] The precise soot blowing control in this application can avoid thermal shock and mechanical damage to the economizer heat exchange elements caused by excessive soot blowing, as well as corrosion and wear problems caused by long-term accumulation of ash due to insufficient soot blowing; by reasonably controlling the soot blowing parameters, damage to the heat exchange elements is reduced, the service life of the heat exchange elements is extended, and the equipment maintenance and replacement costs are reduced.

[0054] This application utilizes a DCS architecture to achieve fully automated control of the soot blowing process. From data acquisition and processing to the formulation and execution of soot blowing decisions, the entire process requires minimal human intervention, reducing the risk of human error and improving the reliability and stability of the system. The central monitoring station can provide real-time feedback on the differences in effects before and after soot blowing, and automatically optimize and dynamically adjust the coefficients in the model based on the effect evaluation. This allows the system to continuously learn and adapt to the soot blowing requirements under different working conditions, achieving intelligent adaptive control. As the system's operating time increases, its control strategy becomes more aligned with actual operating conditions, further improving the soot blowing effect and the overall system performance.

[0055] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0056] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0057] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0058] Figure 1 This is a schematic diagram of an intelligent acoustic sootblower control system based on DCS provided in an embodiment of the present invention. Detailed Implementation

[0059] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0060] Example 1:

[0061] This invention provides an intelligent acoustic sootblower control system based on DCS. Please refer to [link / reference]. Figure 1 ,include:

[0062] The sensor module, installed in key parts of the acoustic soot blower, is used to collect equipment operating parameters in real time; the equipment operating parameters include economizer structural information and internal fluid information.

[0063] The field control station, connected to the sensor module, is used to perform preliminary processing and caching of the equipment operating parameters collected by the sensors;

[0064] The data acquisition module, which connects to the field control station, is used to integrate and format data to ensure that the equipment operating parameters are in a consistent and accurate format.

[0065] The distributed control module, connected to the data acquisition module, establishes an optimal soot blowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment's operating parameters. This model is used to calculate ideal soot blowing information and the dynamic adjustment results determined based on the ideal soot blowing information. The soot blowing action of the acoustic soot blower is controlled according to the dynamic adjustment results.

[0066] The central monitoring station, connected to the distributed control module and sensor module, is used to provide feedback on the differences in the effects before and after soot blowing, and to optimize and adjust the dynamic adjustment model based on these differences.

[0067] The principle and beneficial effects of this embodiment are as follows: by precisely controlling the operation of the sonic soot blower, unnecessary energy consumption is reduced and work efficiency is improved; the optimized soot blowing process reduces maintenance needs and fuel consumption, thereby reducing operating costs; the intelligent control system can promptly detect and respond to potential problems, avoid malfunctions, and ensure the stable operation of the system; it effectively removes accumulated ash, improves combustion efficiency, reduces pollutant emissions, and meets environmental protection requirements; centralized management and remote monitoring functions make system maintenance more convenient and reduce labor costs.

[0068] To further optimize the above embodiments, the economizer structural information includes inlet and outlet pressure difference ΔP, temperature difference ΔT, pipe length L, pipe radius r, economizer volume V, ambient humidity H, and economizer heat exchange efficiency η.

[0069] Internal fluid information includes fluid viscosity μ, fluid flow rate Q, fluid density ρ, and fluid temperature T.

[0070] It should be noted that the pressure sensor:

[0071] Selection: Use a high-precision, high-stability differential pressure sensor. The measurement range should be selected based on the possible pressure difference between the inlet and outlet of the economizer, and should generally cover the normal operating conditions as well as the range of possible abnormal pressure fluctuations. For example, for common low-temperature economizers in coal-fired boilers, the inlet and outlet pressure difference may be between 0-5 kPa, so a sensor with a measurement range of 0-10 kPa can be selected, and its accuracy should reach ±0.2%FS (full scale) or higher.

[0072] Installation: Install pressure sensors on the straight sections of the economizer inlet and outlet pipelines. The installation location should be as far away as possible from valves, elbows, tees, and other components that may affect the accuracy of pressure measurement to ensure that the measured value is a stable static pressure value. The pressure tap of the sensor should be perpendicular to the inner wall of the pipeline and at a 90° angle to the pipeline axis. The inner diameter of the pressure tap is generally 4-10mm to avoid interference from fluid flow on the measurement.

[0073] Temperature sensor:

[0074] Selection: Use thermocouple or resistance temperature detector (RTD) sensors, and choose the appropriate temperature sensing element based on the temperature range of the fluid inside the economizer. For medium- and low-temperature economizers, the fluid temperature is generally between 100-400℃, so K-type thermocouples (temperature range -200-1372℃) or Pt100 RTDs (temperature range -200-850℃) can be selected. The accuracy of the sensor should be within ±0.5℃, and the response time should be short to quickly and accurately reflect temperature changes.

[0075] Installation: Install the temperature sensor in the direction of fluid flow in the economizer pipe, with an insertion depth of 1 / 3 to 1 / 2 of the pipe's inner diameter to ensure that the average temperature of the fluid is measured. The protective sleeve of the sensor should be made of high-temperature and corrosion-resistant materials, such as stainless steel, to adapt to the harsh working environment inside the economizer. For multi-pass economizers, temperature sensors should be installed at the inlet and outlet of each pass to accurately measure the temperature difference.

[0076] Length and radius measurements:

[0077] For the measurement of pipe length and radius, accurate measurements should be taken during economizer installation or maintenance. Pipe length can be measured using a laser rangefinder or steel tape measure. Measurements should be taken along the pipe centerline to ensure the straightness of the measurement path, with an accuracy within ±1mm. Pipe radius can be calculated by measuring the pipe's outer diameter. The outer diameter can be measured using an outside micrometer. Multiple measurement points (e.g., 4-8) should be evenly selected on the pipe circumference, and the average value should be taken as the pipe's outer diameter. The calculated radius should have an accuracy within ±0.1mm.

[0078] Volume measurement (approximate calculation):

[0079] The volume of an economizer can be approximated by measuring its external dimensions. For common tubular economizers, they can be considered as a combination of multiple cylinders. First, measure the length, outer diameter, and wall thickness of each heat exchange tube to calculate the volume of each tube, then multiply by the number of tubes to obtain the total volume of the heat exchange tube section. Next, measure the length, width, and height of the economizer shell to calculate its volume, then subtract the volume of the heat exchange tube section to obtain the economizer's volume. During the measurement process, the accuracy of length and dimension measurements should be within ±1mm. For economizers with complex shapes, three-dimensional scanning technology can be used to obtain the external dimensions to improve the accuracy of volume calculation.

[0080] Ambient humidity sensor:

[0081] Selection: Select a capacitive or resistive humidity sensor. The measurement range should cover the humidity range that may occur in the environment where the economizer is located, generally 0-100%RH (relative humidity), with an accuracy within ±2%RH. The sensor should have good stability and anti-interference ability and be able to adapt to the electromagnetic environment of the industrial site.

[0082] Installation: Install the humidity sensor in the air near the economizer, avoiding direct exposure to water vapor spray or high-temperature airflow; the sensor can be installed in a well-ventilated protective box to ensure that it measures the true humidity of the ambient air; the sensor's signal transmission line should be shielded to reduce the impact of electromagnetic interference on the measurement signal.

[0083] Heat exchange efficiency measurement (indirect calculation):

[0084] The heat exchange efficiency of the economizer is indirectly calculated using data measured by temperature and flow sensors.

[0085] Fluid viscosity and density measurement (online monitoring or table lookup estimation):

[0086] For fluid viscosity and density, in some large industrial systems, online viscometers and densitometers can be used for real-time measurement. Online viscometers can be vibratory or rotary, with the appropriate measurement principle and range selected based on the fluid characteristics. Densitometers can be differential pressure or Coriolis mass flow meters (which can also measure mass flow). These instruments should be installed on the economizer inlet pipe to ensure that the measured fluid state is that before it enters the economizer. In some cases, if online measuring instruments cannot be installed, the fluid viscosity and density can be estimated by referring to tables or empirical formulas based on the fluid's composition, temperature, and pressure. For example, for water-steam mixtures, the corresponding density and viscosity values ​​can be obtained from water vapor property tables based on temperature and pressure.

[0087] To further optimize the above embodiments, the field control station includes:

[0088] The data caching unit is used to temporarily store the data collected by the sensor module. Its caching capacity and storage speed meet the requirements of the system's real-time data processing and ensure that data is not lost.

[0089] The preliminary processing unit performs preliminary processing on the cached data, including filtering, amplification, and digitization, to ensure that the data meets the format requirements for subsequent transmission and processing, thereby improving data quality.

[0090] It should be noted that the sensors and the field control station (FCS) communicate using a high-speed, reliable fieldbus, such as PROFIBUS-DP or Modbus-RTU. The fieldbus should have good anti-interference capabilities, and the communication rate should meet the system's real-time data transmission requirements, generally not less than 1 Mbps. During wiring, communication cables should be laid separately from power cables to avoid electromagnetic interference affecting the accuracy of data transmission.

[0091] The data buffer unit of the field control station (FCS) should have sufficient storage capacity to buffer the data acquired by the sensors. For example, for a system with 100 sensors, each acquiring 10 data points per second, and a buffering time of 10 minutes, the storage capacity of the data buffer unit should be no less than 6 * 10^6. 6 The initial processing unit can use digital filtering algorithms, such as moving average filtering and median filtering, to remove noise interference from the data when filtering the data. For amplification and digitization processing, appropriate amplifiers and analog-to-digital converters (ADCs) should be selected according to the characteristics of the sensor output signal to ensure accurate signal conversion. The ADC resolution should be no less than 12 bits to ensure data accuracy.

[0092] To further optimize the above embodiments, the data acquisition module includes:

[0093] The data integration unit receives data from the field control station and integrates the operating parameters of each device according to predetermined rules to ensure the correlation and integrity of the data.

[0094] The format processing unit formats the integrated device operating parameters, converting the data into a format that the distributed control module can recognize and process.

[0095] It should be noted that after receiving data from the field control station (FCS), the data acquisition module (DAM) transmits the data to the data processing unit (DPU) of the distributed control system (DCS) via high-speed Ethernet. The Ethernet transmission rate should reach 100Mbps or higher to ensure fast data transmission. During transmission, data verification and retransmission mechanisms should be employed to ensure data integrity and accuracy. For example, a cyclic redundancy check (CRC) algorithm can be used to verify the transmitted data, and when an error is detected, a retransmission is automatically requested.

[0096] To further optimize the above embodiments, the distributed control module includes:

[0097] The ash accumulation thickness simulation unit, which is connected to the format processing unit, establishes an ash accumulation thickness calculation model based on the inlet and outlet pressure difference ΔP, pipe length L, pipe radius r, fluid viscosity μ, and fluid flow rate Q, and is used to calculate the simulated ash accumulation thickness value h.

[0098] The rate of change calculation unit, which is connected to the ash thickness simulation unit and the format processing unit, determines the current ash thickness change rate based on the simulated ash thickness value h. Determine the current rate of change of temperature difference based on the inlet and outlet temperature difference ΔT.

[0099] The acoustic velocity simulation unit, connected to the format processing unit, establishes an acoustic velocity calculation model based on the economizer volume V, fluid temperature T, and gas parameters determined through previous experiments, and is used to calculate the simulated value of acoustic propagation velocity v.

[0100] The optimal parameter determination unit, which is connected to the ash thickness simulation unit and the sound wave velocity simulation unit, is used to fuse the simulated ash thickness h and the simulated sound wave propagation velocity v to establish the optimal soot blowing simulation model and calculate the ideal soot blowing information; the ideal soot blowing information includes the ideal soot blowing frequency f0 and the ideal soot blowing power P0.

[0101] The dynamic adjustment unit, connected to the optimal parameter determination unit and the rate of change calculation unit, is based on the current rate of change of ash accumulation thickness. Rate of change of temperature difference In addition, a dynamic adjustment model is established based on ideal soot blowing information to calculate the current dynamic adjustment result; the dynamic adjustment result includes the adjustment of the soot blowing frequency f. new And adjust the soot blowing power P new .

[0102] The calculation model for ash accumulation thickness is as follows:

[0103]

[0104] Where h is the simulated value of ash accumulation thickness, ΔP is the pressure difference between inlet and outlet, L is the pipe length, r is the pipe radius, μ is the fluid viscosity, Q is the fluid flow rate, and k is the ash accumulation permeability. The ash accumulation permeability k is used to reflect the ease with which fluid can pass through the ash accumulation layer. Its value is determined by back-calculation experiments using a permeability meter combined with the ash accumulation thickness calculation model.

[0105] It should be noted that the back-calculation process, which uses a permeability meter combined with a dust accumulation thickness calculation model, includes the following steps:

[0106] Ash samples were obtained from actual low-temperature economizers or simulated experimental environments to ensure that their characteristics were consistent with actual operation. After collection, the samples were mixed evenly to ensure representativeness.

[0107] Select a suitable and accurate permeameter, calibrate and adjust it before the experiment to ensure it is working properly;

[0108] The ash-collected sample is filled into the permeability meter test chamber, maintaining the ash-collected structure, and then sealed to prevent fluid leakage after filling.

[0109] Multiple fluid flow rates were set, and experimental fluids of known viscosity were injected into the ash samples. After stabilization, the pressure difference between the two ends of the ash samples was measured at each flow rate. The average value was taken after multiple measurements, and the ambient temperature and pressure were recorded simultaneously.

[0110] Substitute the measured data into the ash accumulation thickness calculation model, where the ash accumulation thickness is a known quantity.

[0111] To solve for k by deforming the model, substitute each set of data into the deformation formula to calculate the value of k, and then take the average value.

[0112] Calculate the error range of the k-value, compare the consistency of the k-value under different conditions to assess its reliability, repeat the experiment to verify it, use the k-value to calculate the actual ash accumulation thickness and compare it with the actual data. If the deviation is large, check and improve the experiment.

[0113] To further optimize the above embodiments, the sound wave velocity calculation model is as follows:

[0114]

[0115] Where v is the simulated speed of sound, γ is the adiabatic index, V is the economizer volume, T is the fluid temperature, R is the gas constant, and M... eq For equivalent molar mass, a eq and b eq It is the equivalent van der Waals constant;

[0116] The adiabatic index γ and the gas constant R are determined by looking up a table based on the type of gas in the economizer;

[0117] Equivalent molar mass M eq Through formula Determine, where i is the gas type in the economizer. M represents the volume fraction of the i-th type of gas. i To and Corresponding molar mass; volume fraction and molar mass M i All values ​​are known values;

[0118] Equivalent van der Waals constant a eq and b eq Through formula and Determined; where a i Let b be the first van der Waals constant for the i-th type of gas. i Let a be the second van der Waals constant for the i-th type of gas, and let a be the first van der Waals constant. i Second van der Waals constant b i All values ​​are known values.

[0119] It should be noted that this sound wave velocity calculation model is based on the ideal gas law and the formula for the propagation speed of sound waves in an ideal gas, and is obtained by correcting for deviations of the actual gas from the ideal gas by combining the van der Waals equation; its purpose is to accurately calculate the simulated value of the propagation speed of sound waves in the mixed gas (including air and combustion products, etc.) in the economizer.

[0120] The adiabatic index and gas constant are constants related to the properties of a gas, and their values ​​depend on the type of gas in the economizer. By consulting relevant physicochemical handbooks or gas property databases, the corresponding values ​​of the adiabatic index and gas constant can be found based on the actual types of gas present in the economizer. For example, for common air, there are definite values ​​for its adiabatic index and gas constant.

[0121] The gas inside the economizer is a mixture of multiple gases. The equivalent molar mass is used to comprehensively consider the overall properties of the gas mixture. The parameters used to calculate the equivalent molar mass can be obtained by analyzing and measuring the composition of the gas inside the economizer. The methods for analyzing and measuring the gas composition are existing technologies, so they will not be elaborated on further.

[0122] Van der Waals constants are used to correct for deviations between real and ideal gases. These constants are known physical parameters for different gas types and can be obtained from relevant physicochemical data. By calculating equivalent van der Waals constants, the influence of intermolecular interactions on the speed of sound wave propagation can be considered more accurately.

[0123] To further optimize the above embodiments, the optimal soot blowing simulation model is:

[0124]

[0125] Where f0 is the ideal soot blowing frequency, P0 is the ideal soot blowing power; v is the simulated value of sound wave propagation speed, h is the simulated value of ash accumulation thickness, μ is the fluid viscosity, ρ is the fluid density, H is the ambient humidity, η is the economizer heat exchange efficiency; λ is the thermal conductivity of the economizer heat exchange element, E is the elastic modulus of the heat exchange element material, and the values ​​of λ and E are determined based on the specific material of the economizer heat exchange element.

[0126] α is the first angular parameter, representing the angular parameter related to the reflection and refraction of sound waves in the dust-accumulating medium; the calculation formula is:

[0127] Where z1 = ρ1*v1, z2 = ρ2*v2; z1 is the air impedance, which is determined based on the air density ρ1 and the speed of sound propagation in the air v1; z2 is the ash impedance, which is determined based on the ash density ρ2 and the speed of sound propagation in the ash v2.

[0128] β is the second angle parameter, representing an angle parameter related to the economizer structure and ash accumulation distribution; the calculation formula is...

[0129] Among them, C un The coefficient of non-uniformity of ash accumulation on the pipeline is obtained by statistically analyzing the ash accumulation thickness at different locations on the pipeline; m and n are based on the arrangement of the economizer, i.e., m rows and n columns.

[0130] It should be noted that the method for obtaining the dust accumulation unevenness coefficient is as follows:

[0131] First, determine the structural characteristics of the economizer, including the pipe arrangement (m rows and n columns), pipe length, and pipe diameter. Based on this information, select representative sampling locations. For regularly arranged economizer pipes, an equal-interval sampling method can be used, such as selecting sampling points at specific intervals in each row and column. Generally, for larger economizers, a sampling point can be selected every 3-5 pipes in each row and column. For smaller economizers, the sampling density can be appropriately increased, with a sampling point selected every 1-2 pipes. Simultaneously, ensure that the sampling points cover different areas of the economizer, including the inlet, outlet, edges, and center, as the ash accumulation in these areas may differ.

[0132] At the selected sampling locations, use appropriate measuring tools to measure the thickness of the ash accumulation on the pipe surface. For thin ash layers (thickness less than 10 mm), a high-precision thickness gauge, such as an ultrasonic thickness gauge or a coating thickness gauge, can be used. Position the thickness gauge probe perpendicular to the pipe surface and take multiple measurements (at least 3 times) at each sampling point. Use the average value as the ash thickness measurement for that point to improve accuracy. For thicker ash layers (thickness greater than 10 mm), carefully remove a portion of the ash to bring its thickness within the thickness gauge's measurement range before measuring. Correct the measurement based on the removed ash thickness to obtain the actual ash thickness. During the measurement process, record the location information (row number, column number) and the corresponding ash thickness value for each sampling point.

[0133] After the measurement is completed, the dust accumulation thickness data of all sampling points are sorted out; the average dust accumulation thickness is calculated, and then the standard deviation of the dust accumulation thickness is calculated; the non-uniformity coefficient of dust accumulation on the pipeline is the quotient of the standard deviation and the average value.

[0134] The value of the non-uniformity coefficient reflects the degree of unevenness in the distribution of ash on the pipe. The larger the value, the more uneven the ash distribution; the smaller the value, the more uniform the ash distribution.

[0135] To ensure the accuracy of the non-uniformity coefficient, verification and correction can be performed. One method is to compare the non-uniformity coefficients calculated under different time periods or operating conditions. If large fluctuations in the coefficient are found without a reasonable explanation, it may be necessary to re-examine the measurement process or increase the number of sampling points. Additionally, if the ash accumulation in certain areas is found to be inconsistent with the calculated results during economizer overhaul or maintenance, the non-uniformity coefficient should also be corrected according to the actual situation. For example, if the ash thickness in a certain area is significantly higher than in other areas but this was not fully reflected during sampling, the number of sampling points in that area can be appropriately increased, and the non-uniformity coefficient recalculated to improve its representativeness of the actual ash distribution. Through such verification and correction, the non-uniformity coefficient can more accurately reflect the true distribution characteristics of ash accumulation on the economizer pipeline, thereby providing more reliable parameters for the optimal soot blowing simulation model, optimizing the soot blowing control strategy, and improving the soot blowing effect and the economizer's operating efficiency.

[0136] To further optimize the above embodiments, the model is dynamically adjusted as follows:

[0137]

[0138] Among them, f new To adjust the soot blowing frequency, P new To adjust the soot blowing power, k1, k2, k3, k4, k5, and k6 are dynamic adjustment coefficients, which are determined experimentally based on the economizer's design parameters and material properties.

[0139] It should be noted that the process of determining the economizer's design parameters and material properties through experiments involves:

[0140] Based on the economizer's design parameters (such as pipe size, heat exchange area, material type, and arrangement) and material properties (such as thermal conductivity, elastic modulus, and corrosion resistance), design a series of representative experimental conditions. These conditions should cover different degrees of ash accumulation, fluid temperature changes, and flow fluctuations that the economizer may encounter during actual operation. Prepare the necessary equipment and instruments, including simulation devices capable of precisely controlling ash accumulation thickness (such as adjustable dust spraying systems or detachable ash samples), temperature and pressure sensors, flow measurement instruments, power monitoring equipment, and sonic soot blowers with different power and frequency settings. At the same time, ensure the stability of the experimental environment and minimize the interference of external factors on the experimental results.

[0141] Under different experimental conditions, the ash accumulation state of the economizer was gradually changed. A simulation device was used to uniformly or according to a specific pattern deposit ash of different thicknesses on the economizer surface. Simultaneously, parameters such as fluid temperature and flow rate were adjusted to meet preset operating conditions. Under each condition, the sonic sootblower was activated with different initial sootblowing frequencies and power. During sootblowing, various performance indicators of the economizer, such as inlet and outlet pressure difference, temperature difference, and heat exchange efficiency, as well as the actual power consumption and frequency changes of the sootblower, were monitored in real time. The changes in these indicators before and after each sootblowing operation were recorded, and the ash shedding was observed, including the ease of shedding, the uniformity of shedding, and whether any residual ash remained.

[0142] For each experimental condition, the soot blowing effect is evaluated based on the changes in the economizer performance indicators before and after soot blowing; the dynamic adjustment coefficient under different conditions is solved by mathematical methods such as multiple regression analysis, so that the adjusted soot blowing frequency and power calculated by the model can correspond to the actual optimal soot blowing effect.

[0143] The calculated dynamic adjustment coefficients were verified using another set of independent experimental data. Under new experimental conditions, the determined coefficients were applied to adjust the soot blowing frequency and power, and soot blowing was performed. The actual soot blowing effect was observed to ensure it matched expectations. If a significant deviation was found between the calculated results and the actual situation, the cause could be limitations of the experimental data, unreasonable model assumptions, or inaccurate coefficient calculation methods. Based on the analysis results, the experimental design, data processing methods, or coefficient calculation models were optimized, and the experiments and calculations were repeated until a more accurate and reliable dynamic adjustment coefficient was obtained. Through continuous verification and optimization, the dynamic adjustment coefficients were ensured to accurately reflect the actual operating characteristics of the economizer, enabling the dynamic adjustment model to effectively adjust the soot blowing frequency and power according to different operating conditions in practical applications, achieving the best soot blowing effect and improving the economizer's operating efficiency and reliability.

[0144] To further optimize the above embodiments, the central monitoring station includes:

[0145] The strategy optimization unit is used to judge the soot blowing effect based on the change value ΔΔP of the economizer inlet and outlet pressure difference before and after soot blowing. When ΔΔP is lower than the preset threshold, it is determined that the soot blowing effect is not obvious and a feedback signal is generated.

[0146] The coefficient feedback unit, connected to the strategy optimization unit and the dynamic adjustment unit, is used to adjust the dynamic adjustment coefficients k1, k2, k3, k4, k5, and k6 in the dynamic adjustment model upon receiving a feedback signal, thereby adjusting the soot blowing frequency f. new And adjust the soot blowing power P new The air is gradually raised according to the preset rising amount to improve the soot blowing effect until the feedback signal disappears.

[0147] It should be noted that the process of setting the preset threshold is as follows:

[0148] Analyze the economizer's design specifications and performance curves to understand its tolerance range for pressure differential under different levels of ash accumulation. If the economizer's design allows for stable operation under certain ash accumulation conditions, the threshold can be appropriately relaxed; conversely, if ash accumulation significantly impacts equipment performance, the threshold should be set more strictly. For example, for economizers with extremely high heat exchange efficiency requirements and strong ash accumulation sensitivity, the threshold can be set close to the lower limit of the normal operating pressure differential to ensure timely detection of poor soot blowing performance. For equipment with a certain tolerance for ash accumulation, the threshold can be appropriately higher than the lower limit, while ensuring equipment safety and basic performance, to avoid overly frequent soot blowing adjustments.

[0149] Another approach involves communicating with on-site operators and maintenance personnel to understand the actual pressure difference changes after previous soot blowing operations, as well as the equipment maintenance cycle and requirements. If it is found that the equipment began to experience performance degradation or required more frequent maintenance within a certain pressure difference variation range, this range can be used as a reference for setting a threshold. For example, if experience shows that when the pressure difference variation is less than 5 kPa, the economizer's heat exchange efficiency will significantly decrease in the short term, and subsequent maintenance workload will increase, then the threshold can be set at around 5 kPa to allow for timely measures to improve soot blowing performance and reduce adverse effects on equipment operation.

[0150] The preset increase amount is implemented by:

[0151] Based on the economizer's design parameters, material properties, and the experimentally determined relationship between the dynamic adjustment coefficient and the soot blowing effect, a coefficient adjustment step size table is established. The table lists the initial adjustment step size for each dynamic adjustment coefficient under different conditions. For example, for k1, when the soot blowing effect is not significant and the pressure difference change is small, the initial step size can be set to 0.05; when the pressure difference change is large, the initial step size can be increased to 0.1. These step size settings should be based on experimental data and experience to ensure that the soot blowing effect is gradually improved when adjusting the coefficients, while avoiding excessive adjustment that could lead to system instability.

[0152] When the coefficient feedback unit receives the feedback signal generated by the strategy optimization unit, it first determines the degree to which the current soot blowing effect is insignificant, for example, by calculating the difference between the current pressure difference change and the threshold. Based on the difference, it selects the appropriate step size from the coefficient adjustment step size table, and then adjusts the dynamic adjustment coefficient as follows:

[0153] For adjusting the soot blowing frequency coefficients k1 and k3, if the current soot blowing frequency is low and needs to be increased, k1 is multiplied by the current corresponding step size, and k3 is divided by (1 + the current corresponding step size) to increase the soot blowing frequency according to the preset increase amount. This adjustment method is based on the characteristics of the frequency calculation formula in the dynamic adjustment model, achieving the frequency increase by changing the coefficients, while also considering the interrelationships between the coefficients.

[0154] For adjusting the soot blowing power coefficients k4 and k6, if the current soot blowing power is insufficient and needs to be increased, k4 is multiplied by the current corresponding step size and then divided by (1 + the current corresponding step size), so that the soot blowing power gradually increases according to the preset increase amount. Similarly, this adjustment is based on the relationship between the power calculation formula and the coefficients.

[0155] After each coefficient adjustment, start a new round of soot blowing and continue to monitor the soot blowing effect. If the soot blowing effect is still not obvious and the feedback signal persists, select an appropriate step size in the coefficient adjustment step size table again based on the new pressure difference change (the step size may need to be increased or decreased appropriately according to the actual effect), and repeat the above coefficient adjustment process until the feedback signal disappears, that is, the soot blowing effect reaches the expected level and the pressure difference change value exceeds the threshold.

[0156] To ensure system stability and rationality, the adjustment range of the dynamic adjustment coefficients is limited. Upper and lower limits are set for each coefficient, with these values ​​determined within a safe range based on the economizer's physical characteristics and experimental results. For example, the value range of k1 might be set to 0.1-2.0. When the coefficient adjustment reaches the upper or lower limit, it stops increasing or decreasing by the preset amount, instead remaining at the boundary value, and the soot blowing effect is observed to see if it can be improved through adjustments of other coefficients or subsequent operation. Simultaneously, during coefficient adjustment, care must be taken to avoid excessively large adjustments between adjacent adjustments, which could cause system fluctuations. An adjustment range limit can be set, such as the coefficient change between two adjacent adjustments not exceeding a certain percentage (e.g., 20%), to ensure stable operation of the system while gradually optimizing the soot blowing effect.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent acoustic soot blower control system based on DCS, characterized in that, include: The sensor module, installed in key parts of the acoustic soot blower, is used to collect equipment operating parameters in real time; the equipment operating parameters include economizer structural information and internal fluid information. The field control station is connected to the sensor module and is used to perform preliminary processing and caching of the equipment operating parameters collected by the sensors. The data acquisition module, which is connected to the field control station, is used to integrate and format the data to ensure that the equipment operating parameters are in a uniform and accurate format. A distributed control module, connected to the data acquisition module, establishes an optimal soot blowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment operating parameters. This model is used to calculate ideal soot blowing information and dynamic adjustment results determined based on the ideal soot blowing information. The soot blowing action of the acoustic soot blower is controlled according to the dynamic adjustment results. The central monitoring station, which is connected to the distributed control module and the sensor module, is used to provide feedback on the differences in the effects before and after soot blowing, and to optimize and adjust the dynamic adjustment model based on the differences. The economizer structural information includes inlet and outlet pressure difference ΔP, temperature difference ΔT, pipe length L, pipe radius r, economizer volume V, ambient humidity H, and economizer heat exchange efficiency η. The internal fluid information includes fluid viscosity μ, fluid flow rate Q, fluid density ρ, and fluid temperature T; The data acquisition module includes: The data integration unit receives data from the field control station and integrates the operating parameters of each device according to predetermined rules to ensure the correlation and integrity of the data. The format processing unit formats the integrated device operating parameters, converting the data into a format that the distributed control module can recognize and process. The distributed control module includes: The ash accumulation thickness simulation unit, which is connected to the format processing unit, establishes an ash accumulation thickness calculation model based on the inlet and outlet pressure difference ΔP, pipe length L, pipe radius r, fluid viscosity μ, and fluid flow rate Q, and is used to calculate the simulated ash accumulation thickness value h. The rate of change calculation unit, which is connected to the ash thickness simulation unit and the format processing unit, determines the current rate of change of ash thickness based on the simulated ash thickness value h. Determine the current rate of change of temperature difference based on the inlet and outlet temperature difference ΔT. The acoustic velocity simulation unit, which is connected to the format processing unit, establishes an acoustic velocity calculation model based on the economizer volume V, fluid temperature T, and gas parameters determined through previous experiments, and is used to calculate the simulated value v of the acoustic propagation velocity. The optimal parameter determination unit, which is connected to the ash thickness simulation unit and the sound wave velocity simulation unit, is used to fuse the ash thickness simulation value h and the sound wave propagation velocity simulation value v to establish the optimal soot blowing simulation model and calculate the ideal soot blowing information; the ideal soot blowing information includes the ideal soot blowing frequency f0 and the ideal soot blowing power P0. The dynamic adjustment unit, connected to the optimal parameter determination unit and the rate of change calculation unit, adjusts the current ash thickness based on the rate of change. Rate of change of temperature difference A dynamic adjustment model is established based on ideal soot blowing information to calculate the current dynamic adjustment result; the dynamic adjustment result includes adjusting the soot blowing frequency f. new And adjust the soot blowing power P new .

2. The intelligent acoustic soot blower control system based on DCS according to claim 1, characterized in that, The field control station includes: The data caching unit is used to temporarily store the data collected by the sensor module. Its caching capacity and storage speed meet the requirements of the system's real-time data processing and ensure that data is not lost. The preliminary processing unit performs preliminary processing on the cached data, including filtering, amplification, and digitization, to ensure that the data meets the format requirements for subsequent transmission and processing, thereby improving data quality.

3. The intelligent acoustic soot blower control system based on DCS according to claim 1, characterized in that, The calculation model for the ash accumulation thickness is as follows: Where h is the simulated value of ash accumulation thickness, ΔP is the pressure difference between inlet and outlet, L is the pipe length, r is the pipe radius, μ is the fluid viscosity, Q is the fluid flow rate, and k is the ash accumulation permeability. The ash accumulation permeability k is used to reflect the ease with which fluid can pass through the ash accumulation layer. Its value is determined by back-calculation experiments using a permeability meter in conjunction with the ash accumulation thickness calculation model.

4. The intelligent acoustic soot blower control system based on DCS according to claim 3, characterized in that, The sound wave velocity calculation model is as follows: Where v is the simulated speed of sound, γ is the adiabatic index, V is the economizer volume, T is the fluid temperature, R is the gas constant, and M... eq For equivalent molar mass, a eq and b eq It is the equivalent van der Waals constant; The adiabatic index γ and the gas constant R are determined by looking up a table based on the type of gas in the economizer. Equivalent molar mass M eq Through formula Determine, where i is the gas type in the economizer. M represents the volume fraction of the i-th type of gas. i To and Corresponding molar mass; volume fraction and molar mass M i All values ​​are known values; Equivalent van der Waals constant a eq and b eq Through formula and Determined; where a i Let b be the first van der Waals constant for the i-th type of gas. i Let a be the second van der Waals constant for the i-th type of gas, and let a be the first van der Waals constant. i Second van der Waals constant b i All values ​​are known values.

5. The intelligent acoustic soot blower control system based on DCS according to claim 4, characterized in that, The optimal soot blowing simulation model is: Where f0 is the ideal soot blowing frequency, P0 is the ideal soot blowing power; v is the simulated value of sound wave propagation speed, h is the simulated value of ash accumulation thickness, μ is the fluid viscosity, ρ is the fluid density, H is the ambient humidity, η is the economizer heat exchange efficiency; λ is the thermal conductivity of the economizer heat exchange element, E is the elastic modulus of the heat exchange element material, and the values ​​of λ and E are determined based on the specific material of the economizer heat exchange element. α is the first angular parameter, representing the angular parameter related to the reflection and refraction of sound waves in the dust-accumulating medium; the calculation formula is: Where z1 = ρ1*v1, z2 = ρ2*v2; z1 is the air impedance, which is determined based on the air density ρ1 and the speed of sound propagation in the air v1; z2 is the ash impedance, which is determined based on the ash density ρ2 and the speed of sound propagation in the ash v2. β is the second angle parameter, representing an angle parameter related to the economizer structure and ash accumulation distribution; the calculation formula is... Among them, C un The coefficient of non-uniformity of ash accumulation on the pipeline is obtained by statistically analyzing the ash accumulation thickness at different locations on the pipeline; m and n are based on the arrangement of the economizer, i.e., m rows and n columns.

6. The intelligent acoustic soot blower control system based on DCS according to claim 5, characterized in that, The dynamic adjustment model is as follows: Among them, f new To adjust the soot blowing frequency, P new To adjust the soot blowing power, k1, k2, k3, k4, k5, and k6 are dynamic adjustment coefficients, which are determined experimentally based on the economizer's design parameters and material properties.

7. The intelligent acoustic soot blower control system based on DCS according to claim 6, characterized in that, The central monitoring station includes: The strategy optimization unit is used to judge the soot blowing effect based on the change value ΔΔP of the economizer inlet and outlet pressure difference before and after soot blowing. When ΔΔP is lower than the preset threshold, it is determined that the soot blowing effect is not obvious and a feedback signal is generated. A coefficient feedback unit, connected to the strategy optimization unit and the dynamic adjustment unit, is used to adjust the dynamic adjustment coefficients k1, k2, k3, k4, k5, and k6 in the dynamic adjustment model upon receiving a feedback signal, so as to adjust the soot blowing frequency f. new And adjust the soot blowing power P new The air is gradually raised according to the preset rising amount to improve the soot blowing effect until the feedback signal disappears.

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