Intelligent sound wave soot blower control system based on DCS

Abstract

The invention provides an intelligent sound wave soot blower control system based on a DCS, and the system comprises a sensor module which is used for collecting equipment operation parameters; the field control station is used for carrying out primary processing and caching on the equipment operation parameters acquired by the sensor; the data acquisition module is used for integrating and formatting the data; the distributed control module is used for establishing an optimal soot blowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment operation parameters, and is used for calculating ideal soot blowing information and a dynamic adjustment result determined based on the ideal soot blowing information; controlling the soot blowing action of the sound wave soot blower according to the dynamic adjustment result; the central monitoring station is used for feeding back the difference between the effects before and after soot blowing and optimizing and adjusting the dynamic adjustment model based on the difference; the invention aims at solving the problems of heat exchange efficiency reduction and resistance increase caused by ash deposition of the low-low-temperature economizer, improving the overall operation performance of the low-low-temperature economizer, prolonging the service life of equipment and achieving the purposes of energy conservation and environmental protection.

Description

Technical Field

[0001] The invention relates to the technical field of thermal power generation, and in particular to an intelligent sonic soot blower control system based on DCS. Background Art

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

[0003] During the operation of the low-temperature economizer, dust particles in the flue gas will gradually deposit on the surface of the heat exchange element to form ash accumulation; the ash accumulation problem has always been an important factor affecting the performance of the low-temperature economizer, and its development process is relatively complicated; as time goes by, the thickness of the ash layer continues to increase, which will first lead to a gradual decrease in the heat exchange efficiency of the economizer; because the thermal conductivity of the ash layer is much lower than that of the heat exchange element material itself, the heat transfer is hindered, affecting the effective transfer of heat from the flue gas to the working fluid (such as water), and reducing the heat recovery efficiency of the entire system; at the same time, ash accumulation will also increase the flow resistance of the flue gas; when the ash accumulates on the surface of the heat exchange element, the flue gas channel becomes narrower and the friction resistance of the gas flow increases, which requires the fan to provide a higher pressure head to maintain the flue gas flow, thereby increasing the energy consumption of the fan; 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, causing corrosion of the heat exchange element; and the ash particles carried by the flue gas scour the surface of the heat exchange element at high speed, which will also cause wear on the surface of the element and shorten the service life of the equipment;

[0004] Traditional soot blowing methods mainly include steam soot blowing and mechanical vibration soot blowing. Steam soot blowing uses the impact force of high-temperature and high-pressure steam to remove accumulated soot. This method can remove accumulated soot to a certain extent, but it has many disadvantages. On the one hand, steam soot blowing consumes a large amount of high-quality steam, which increases the operating cost of the system. On the other hand, during the steam soot blowing process, high-temperature steam may cause thermal shock to the heat exchange element, resulting in a decrease in the performance of the heat exchange element material, and 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 soot or hardened soot, steam soot blowing is difficult to completely remove. Mechanical vibration soot blowing uses a mechanical device to generate vibration to remove accumulated soot. However, this method is prone to mechanical damage to the equipment, and the vibration force and frequency are difficult to accurately control, resulting in uneven soot blowing. Local soot accumulation problems may still exist, and the impact of soot accumulation on heat exchange efficiency and resistance cannot be effectively solved.

[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 the advantages of 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 lacks a soot blowing system that can comprehensively and accurately perform intelligent control based on the operating status and soot accumulation of the economizer.

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

[0007] The present invention provides an intelligent sonic sootblower control system based on DCS, which aims to solve the problems of reduced heat exchange efficiency and increased resistance caused by soot accumulation in low-temperature economizers, as well as various problems existing in existing sootblowing methods, improve the overall operating performance and equipment life of low-temperature economizers, and achieve energy conservation and environmental protection goals.

[0008] The present invention provides an intelligent sonic soot blower control system based on DCS, comprising:

[0009] A sensor module is installed at a key position of the sonic soot blower and is used to collect equipment operating parameters in real time; the equipment operating parameters include economizer structure information and internal fluid information;

[0010] A field control station connected to the sensor module and used for preliminarily processing and caching the equipment operating parameters collected by the sensor;

[0011] A data acquisition module, which is connected to the field control station and is used to integrate and format the data to ensure that the format of the equipment operating parameters is unified and accurate;

[0012] A distributed control module connected to the data acquisition module, which establishes an optimal sootblowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment operation parameters, and is used to calculate the ideal sootblowing information and the dynamic adjustment result determined based on the ideal sootblowing information; and controls the sootblowing action of the sonic sootblower according to the dynamic adjustment result;

[0013] A central monitoring station is connected to the distributed control module and the sensor module, and is used to provide feedback on the difference in effect before and after sootblowing, and optimize and adjust the dynamic adjustment model based on the difference.

[0014] According to an intelligent sonic soot blower control system based on DCS provided by the present invention, the economizer structural information includes inlet and outlet pressure difference ΔP, temperature difference ΔT, pipeline length L, pipeline 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 Q, fluid density ρ, and fluid temperature T.

[0016] According to an intelligent sonic sootblower control system based on DCS provided by the present invention, the field control station comprises:

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

[0018] The preliminary processing unit performs preliminary processing on the cached data, including filtering, amplifying and digitizing the data, so that the data meets the format requirements of subsequent transmission and processing and improves the data quality.

[0019] According to an intelligent sonic sootblower control system based on DCS provided by the present invention, the data acquisition module comprises:

[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 relevance and integrity of the data;

[0021] The format processing unit formats the integrated equipment operating parameters and converts the data into a format that can be recognized and processed by the distributed control module.

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

[0023] A dust accumulation thickness simulation unit is connected to the format processing unit, and establishes a dust accumulation thickness calculation model based on the inlet and outlet pressure difference ΔP, the pipeline length L, the pipeline radius r, the fluid viscosity μ, and the fluid flow rate Q, so as to calculate the dust accumulation thickness simulation value h;

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

[0025] A sound wave velocity simulation unit, which is connected to the format processing unit, establishes a sound wave velocity calculation model based on the economizer volume V, the fluid temperature T and the gas parameters determined by the previous experiment, and is used to calculate the sound wave propagation velocity simulation value v;

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

[0027] The dynamic adjustment unit is connected to the optimal parameter determination unit and the change rate calculation unit, and is based on the current dust accumulation thickness change rate. Temperature change rate and ideal soot blowing information to establish a dynamic adjustment model and calculate the current dynamic adjustment result; the dynamic adjustment result includes adjusting the soot blowing frequency f new and adjust the sootblowing power P new .

[0028] According to an intelligent sonic soot blower control system based on DCS provided by the present invention, the dust accumulation thickness calculation model is:

[0029]

[0030] Wherein, h is the simulated value of dust thickness, ΔP is the inlet and outlet pressure difference, 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 dust permeability; the dust permeability k is used to reflect the difficulty of the dust layer allowing fluid to pass through, and its value is determined by back-calculation experiment through permeability meter combined with the dust thickness calculation model.

[0031] According to an intelligent sonic sootblower control system based on DCS provided by the present invention, the sonic velocity calculation model is:

[0032]

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

[0034] The adiabatic index γ and the gas constant R are determined by looking up a table according to the type of gas in the economizer;

[0035] Equivalent molar mass M eq By formula Determine, where i is the type of gas in the economizer, is the volume fraction of the i-th type of gas, M i For Corresponding molar mass; volume fraction and molar mass Mi The values ​​of are all known values;

[0036] Equivalent van der Waals constant a eq and b eq By formula and Determine; among them a i is the first van der Waals constant of the i-th type of gas, b i is the second van der Waals constant of the i-th type of gas, the first van der Waals constant a i and the second van der Waals constant b i The values ​​of are all known values.

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

[0038]

[0039] Among them, f0 is the ideal soot blowing frequency, P0 is the ideal soot blowing power; v is the simulated value of the sound wave propagation velocity, h is the simulated value of the ash 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 materials of the economizer heat exchange element;

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

[0041] Among them, z1=ρ1*v1, z2=ρ2*v2; z1 is the air impedance, which is determined based on the air density ρ1 and the propagation speed of sound waves in the air v1; z2 is the dust accumulation impedance, which is determined based on the dust accumulation density ρ2 and the propagation speed of sound waves in the dust accumulation v2;

[0042] β is the second angle parameter, which represents the angle parameter related to the economizer structure and ash distribution; the calculation formula is:

[0043] Among them, C un is the non-uniform coefficient of ash accumulation on the pipe, which is obtained by counting the ash accumulation thickness of pipes at different positions; m and n are based on the arrangement of economizers, that is, m rows and n columns.

[0044] According to an intelligent sonic sootblower control system based on DCS provided by the present invention, the dynamic adjustment model is:

[0045]

[0046] Among them, f newTo adjust the soot blowing frequency, P new to adjust the sootblowing power; k1, k2, k3, k4, k5, and k6 are dynamic adjustment coefficients, which are determined through experiments based on the design parameters and material properties of the economizer.

[0047] According to an intelligent sonic sootblower control system based on DCS provided by the present invention, the central monitoring station comprises:

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

[0049] A coefficient feedback unit is connected to the strategy optimization unit and the dynamic adjustment unit, and is used to adjust the dynamic adjustment coefficients k1, k2, k3, k4, k5, k6 in the dynamic adjustment model accordingly when receiving the feedback signal, so as to adjust the soot blowing frequency f new and adjust the sootblowing power P new Increase gradually according to the preset increase 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:

[0051] This application collects a wealth of operating parameters through the sensor module, such as the economizer inlet and outlet pressure difference, temperature difference, pipeline size, fluid characteristics and ambient humidity, etc. The ash thickness calculation model, sound wave velocity calculation model and optimal soot blowing simulation model established based on these physical characteristics can accurately calculate the ash thickness and sound wave propagation speed, and then determine the ideal soot blowing frequency and power to achieve precise soot blowing; compared with the blindness of traditional soot blowing methods, it can effectively avoid excessive soot blowing or insufficient soot blowing, significantly improve the soot blowing effect, and make the ash cleaning more thorough, thereby maintaining a high heat exchange efficiency of the economizer, ensuring the high efficiency of heat recovery, reducing the exhaust temperature, and further improving the overall thermal efficiency of the boiler system;

[0052] The present application uses a dynamic adjustment model to adjust the soot blowing frequency and power in real time according to the change rate of the ash accumulation thickness and the temperature difference, so that the soot blowing process can timely adapt to the changes in the economizer operating state; when the ash accumulation increases rapidly or the heat exchange efficiency decreases significantly, the soot blowing intensity is quickly increased; when the ash accumulation situation 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 of the present 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 soot due to insufficient soot blowing; by reasonably controlling the soot blowing parameters, the damage to the heat exchange elements is reduced, the service life of the heat exchange elements is extended, and the cost of equipment maintenance and replacement is reduced;

[0054] This application realizes comprehensive automated control of the sootblowing process based on the DCS architecture; from data collection and processing to the formulation and execution of sootblowing decisions, the entire process does not require excessive human intervention, reducing the risks caused by human operational errors and improving the reliability and stability of system operation; the central monitoring station can provide real-time feedback on the difference in effects before and after sootblowing, and automatically optimize and dynamically adjust the coefficients in the model based on the effect evaluation, so that the system can continuously learn and adapt to the sootblowing needs under different working conditions, and realize intelligent adaptive control; as the system operating time increases, its control strategy is more in line with the actual operating conditions, further improving the sootblowing effect and the overall performance of the system.

[0055] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0056] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0058] Figure 1 It is a structural schematic diagram of a DCS-based intelligent sonic sootblower control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0060] Embodiment 1:

[0061] The embodiment of the present invention provides an intelligent sonic sootblower control system based on DCS, please refer to Figure 1 ,include:

[0062] The sensor module is installed at the key position of the sonic soot blower to collect the equipment operating parameters in real time; the equipment operating parameters include economizer structure information and internal fluid information;

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

[0064] The data acquisition module is connected to the field control station to integrate and format the data to ensure that the format of the equipment operating parameters is unified and accurate;

[0065] A distributed control module is connected to the data acquisition module, and establishes an optimal sootblowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment operation parameters, and is used to calculate the ideal sootblowing information and the dynamic adjustment result determined based on the ideal sootblowing information; and controls the sootblowing action of the sonic sootblower according to the dynamic adjustment result;

[0066] The central monitoring station is connected to the distributed control module and the sensor module to provide feedback on the difference in effects before and after sootblowing, and to optimize the dynamic adjustment model based on the difference.

[0067] The principles 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 requirements and fuel consumption, thereby reducing operating costs; the intelligent control system can promptly detect and respond to potential problems, avoid failures, and ensure stable operation of the system; effectively remove ash accumulation, improve combustion efficiency, reduce pollutant emissions, and meet environmental protection requirements; centralized management and remote monitoring functions make system maintenance more convenient and reduce labor costs.

[0068] In order to further optimize the above embodiment, the economizer structural information includes the inlet and outlet pressure difference ΔP, the temperature difference ΔT, the pipeline length L, the pipeline radius r, the economizer volume V, the ambient humidity H, and the economizer heat exchange efficiency η;

[0069] Internal fluid information includes fluid viscosity μ, fluid flow 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 according to the possible pressure difference range at the inlet and outlet of the economizer. Generally, it should cover the normal operating conditions and the possible abnormal pressure fluctuation range. For example, for the common low-temperature economizer of a coal-fired boiler, the inlet and outlet pressure difference may be between 0-5kPa. A sensor with a measurement range of 0-10kPa can be selected, and its accuracy should be above ±0.2% FS (full scale);

[0072] Installation: Install pressure sensors on the straight pipe sections of the economizer inlet and outlet pipes. The installation position 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 static pressure value is stable; the pressure tapping port of the sensor should be perpendicular to the inner wall of the pipe and form an angle of 90° with the axis of the pipe. The inner diameter of the pressure tapping port is generally 4-10mm to avoid interference of fluid flow on the measurement;

[0073] Temperature Sensor:

[0074] Selection: Use thermocouple or thermal resistor temperature sensor, and select appropriate temperature measuring element according to the temperature range of the fluid in the economizer; for medium and low temperature economizers, the fluid temperature is generally between 100-400℃, and K-type thermocouple (temperature measurement range -200-1372℃) or Pt100 thermal resistor (temperature measurement 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 pipeline. The insertion depth should reach 1 / 3-1 / 2 of the inner diameter of the pipeline 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 in 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 pipeline length and radius, accurate measurement should be carried out during the installation or maintenance of economizer; the pipeline length can be measured using a laser rangefinder or a steel tape measure. The measurement should be carried out along the center line of the pipeline to ensure the linearity of the measurement path. The accuracy should be within ±1mm; the pipeline radius can be calculated by measuring the outer diameter of the pipeline. The outer diameter of the pipeline can be measured using an outside diameter micrometer. Multiple measurement points (such as 4-8) are evenly selected on the circumference of the pipeline, and the average value is taken as the outer diameter of the pipeline. The calculated radius accuracy should be within ±0.1mm;

[0078] Volume measurement (approximate calculation):

[0079] The volume of the economizer can be approximately calculated by measuring its external dimensions. For common tubular economizers, they can be regarded as a combination of multiple cylinders. First, measure the length, outer diameter and wall thickness of each heat exchange tube, calculate the volume of each heat exchange tube, and then multiply it by the number of heat exchange tubes to get the total volume of the heat exchange tube part. Then measure the length, width and height of the economizer shell, calculate the volume of the shell, and subtract the volume of the heat exchange tube part to get the volume of the economizer. During the measurement process, the measurement accuracy of length and size should be within ±1mm. For economizers with complex shapes, 3D scanning technology can be used to obtain the external dimensions to improve the accuracy of volume calculation.

[0080] Ambient humidity sensor:

[0081] Selection: Choose capacitive or resistive humidity sensors. The measurement range should cover the possible humidity range of the economizer environment, 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. The installation location should avoid being directly affected by water vapor spray or high-temperature airflow. The sensor can be installed in a well-ventilated protective box to ensure that the actual humidity of the ambient air is measured. The signal transmission line of the sensor should use a shielded line to reduce the impact of electromagnetic interference on the measurement signal.

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

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

[0085] Fluid viscosity and density measurement (online monitoring or table 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 use vibration or rotational viscometers, and select appropriate measurement principles and ranges according to the characteristics of the fluid; density meters can use differential pressure or Coriolis mass flow meters (which can also measure mass flow), etc.; these instruments should be installed on the economizer inlet pipeline to ensure that the state of the fluid before entering the economizer is measured; in some cases, if it is not possible to install online measuring instruments, the viscosity and density of the fluid can be estimated by looking up tables or empirical formulas based on the composition, temperature and pressure of the fluid; for example, for a water-steam mixed fluid, the corresponding density and viscosity values ​​can be found based on the water vapor property table and the temperature and pressure.

[0087] In order to further optimize the above embodiment, the field control station includes:

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

[0089] The preliminary processing unit performs preliminary processing on the cached data, including filtering, amplifying and digitizing the data, so that the data meets the format requirements of subsequent transmission and processing and improves the data quality.

[0090] It should be noted that the sensor and the field control station (FCS) use a high-speed and reliable field bus for communication, such as Profibus-DP, Modbus-RTU, etc. The field bus should have good anti-interference ability, and the communication rate should meet the requirements of real-time data transmission of the system, generally not less than 1Mbps. When wiring, the communication cable should be laid separately from the power cable to avoid electromagnetic interference affecting the accuracy of data transmission.

[0091] The data cache unit of the field control station (FCS) should have sufficient storage capacity to cache the data collected by the sensors. For example, for a system with 100 sensors, each collecting 10 data points per second, and a cache time of 10 minutes, the storage capacity of the data cache unit should be no less than 6*10 6 Bytes; when filtering the data, the preliminary processing unit can use digital filtering algorithms, such as sliding average filtering, median filtering, etc., to remove noise interference in the data. For amplification and digital 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 resolution of the ADC should not be less than 12 bits to ensure data accuracy.

[0092] In order to further optimize the above embodiment, 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 relevance and integrity of the data;

[0094] The format processing unit formats the integrated equipment operating parameters and converts the data into a format that can be recognized and processed by the distributed control module.

[0095] It should be noted that after receiving the 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) through high-speed Ethernet. The transmission rate of Ethernet should reach 100Mbps or higher to ensure the fast transmission of data. During the transmission process, a data check and retransmission mechanism should be adopted to ensure the integrity and accuracy of the data. For example, a cyclic redundancy check (CRC) algorithm can be used to check the transmitted data, and when a data error is found, a retransmission is automatically requested.

[0096] In order to further optimize the above embodiment, the distributed control module includes:

[0097] The dust accumulation thickness simulation unit is connected to the format processing unit, and establishes a dust accumulation thickness calculation model based on the inlet and outlet pressure difference ΔP, the pipeline length L, the pipeline radius r, the fluid viscosity μ, and the fluid flow rate Q, so as to calculate the dust accumulation thickness simulation value h;

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

[0099] The acoustic wave velocity simulation unit is connected to the format processing unit, and establishes an acoustic wave velocity calculation model based on the economizer volume V, the fluid temperature T and the gas parameters determined by the previous experiments, so as to calculate the acoustic wave propagation velocity simulation value v;

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

[0101] The dynamic adjustment unit is connected with the optimal parameter determination unit and the change rate calculation unit, and is based on the current dust accumulation thickness change rate. Temperature change rate The dynamic adjustment model is established based on the ideal soot blowing information to calculate the current dynamic adjustment results; the dynamic adjustment results include adjusting the soot blowing frequency f new and adjust the sootblowing power P new .

[0102] Among them, the calculation model of dust accumulation thickness is:

[0103]

[0104] Wherein, h is the simulated value of dust thickness, ΔP is the inlet and outlet pressure difference, 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 dust permeability. The dust permeability k is used to reflect the difficulty of the dust layer allowing fluid to pass through. Its value is determined by back-calculation experiment through permeability meter combined with dust thickness calculation model.

[0105] It should be noted that the back-calculation process determined by back-calculation experiment using permeability meter combined with dust accumulation thickness calculation model includes:

[0106] Obtain ash samples from low-temperature economizers in actual operation or in simulated experimental environments to ensure that their characteristics are consistent with actual operation, and mix them evenly after collection to ensure representativeness;

[0107] Select a suitable permeability meter that meets the accuracy standards, and calibrate and debug it before the experiment to ensure that it works properly;

[0108] Fill the dust accumulation sample into the permeability test chamber, maintain the dust accumulation structure, and seal it after filling to prevent fluid leakage;

[0109] Set multiple groups of different fluid flow values, inject experimental fluids with known viscosity into the dust sample, measure the pressure difference at both ends of the dust sample at each flow rate after stabilization, take the average value of multiple measurements, and record the experimental environment temperature and pressure at the same time

[0110] Substitute the measured data into the dust accumulation thickness calculation model, at this time the dust accumulation thickness is a known quantity;

[0111] Solve k for the model deformation, substitute each set of data into the deformation formula to calculate the k value, and then take the average value;

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

[0113] In order to further optimize the above embodiment, the acoustic wave velocity calculation model is:

[0114]

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

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

[0117] Equivalent molar mass M eq By formula Determine, where i is the type of gas in the economizer, is the volume fraction of the i-th type of gas, M i For Corresponding molar mass; volume fraction and molar mass M i The values ​​of are all known values;

[0118] Equivalent van der Waals constant a eq and b eq By formula and Determine; among them a i is the first van der Waals constant of the i-th type of gas, b i is the second van der Waals constant of the i-th type of gas, the first van der Waals constant a i and the second van der Waals constant b i The values ​​of are all known values.

[0119] It should be noted that the acoustic wave velocity calculation model is based on the ideal gas state equation and the formula for the propagation velocity of acoustic waves in ideal gas, and is obtained by correcting the deviation 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 velocity of acoustic 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 gas properties, and their values ​​depend on the type of gas in the economizer. By consulting relevant physical and chemical manuals or gas property databases, the corresponding values ​​of the adiabatic index and gas constant can be found according to the type of gas actually present in the economizer. For example, for common air, its adiabatic index and gas constant have definite values ​​that can be found.

[0121] The gas in the economizer is a mixture of multiple gases. The equivalent molar mass is used to comprehensively consider the overall properties of the mixed gas. The various parameters used to calculate the equivalent molar mass can be obtained by analyzing and measuring the gas composition in the economizer. The analytical measurement method of the gas composition is an existing technology, so it will not be elaborated in detail.

[0122] Van der Waals constants are used to correct the deviation between actual gases and ideal gases. These constants are known physical parameters for different gas types and can be obtained from relevant physical and chemical data. By calculating the equivalent van der Waals constants, the effect of the interaction between gas molecules on the propagation speed of sound waves can be more accurately considered.

[0123] In order to further optimize the above embodiment, the optimal soot blowing simulation model is:

[0124]

[0125] Among them, f0 is the ideal soot blowing frequency, P0 is the ideal soot blowing power; v is the simulated value of the sound wave propagation velocity, h is the simulated value of the ash 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 materials of the economizer heat exchange element;

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

[0127] Among them, z1=ρ1*v1, z2=ρ2*v2; z1 is the air impedance, which is determined based on the air density ρ1 and the propagation speed of sound waves in the air v1; z2 is the dust accumulation impedance, which is determined based on the dust accumulation density ρ2 and the propagation speed of sound waves in the dust accumulation v2;

[0128] β is the second angle parameter, which represents the angle parameter related to the economizer structure and ash distribution; the calculation formula is:

[0129] Among them, C un is the non-uniform coefficient of ash accumulation on the pipe, which is obtained by counting the ash accumulation thickness of pipes at different positions; m and n are based on the arrangement of economizers, that is, m rows and n columns.

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

[0131] First, determine the structural characteristics of the economizer, including the arrangement of pipes (m rows and n columns), pipe length, pipe diameter, etc.; based on this information, select representative sampling locations; for regularly arranged economizer pipes, an equidistant sampling method can be used, such as selecting sampling points at specific intervals in each row and column; generally speaking, for larger economizers, a sampling point can be selected every 3-5 pipes in each row and column; for small economizers, the sampling density can be appropriately increased, with a sampling point selected every 1-2 pipes; at the same time, ensure that the sampling points cover different areas of the economizer, including the inlet, outlet, edge and center positions, because the ash accumulation in these areas may be different;

[0132] At the selected sampling location, use a suitable measuring tool to measure the dust thickness on the pipeline surface; for thin dust layers (thickness less than 10mm), use a high-precision thickness gauge, such as an ultrasonic thickness gauge or a coating thickness gauge; place the probe of the thickness gauge perpendicular to the pipeline surface, measure multiple times (at least 3 times) at each sampling point, and take the average value as the dust thickness measurement value of the point to improve the accuracy of the measurement; for thicker dust layers (thickness greater than 10mm), carefully remove a part of the dust so that its thickness is within the measurement range of the thickness gauge, and then measure it, and make corrections based on the removed dust thickness to obtain the actual dust thickness; during the measurement process, record the location information (row number, column number) of each sampling point and the corresponding dust thickness value;

[0133] After the measurement is completed, the dust thickness data of all sampling points are sorted out; the average value of the dust thickness is calculated, and then the standard deviation of the dust thickness is calculated; the unevenness 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 non-uniform distribution of dust accumulation on the pipeline. The larger the value, the more non-uniform the dust accumulation distribution; the smaller the value, the more uniform the dust accumulation distribution.

[0135] In order to ensure the accuracy of the unevenness coefficient, verification and correction can be carried out; one method is to compare the unevenness coefficients calculated in different time periods or under different operating conditions. If it is found that the coefficient fluctuates greatly and there is no reasonable reason, it may be necessary to re-check the measurement process or increase the number of sampling points; in addition, if it is found that the ash accumulation in certain areas is inconsistent with the calculated results during the overhaul or maintenance of the economizer, the unevenness coefficient should also be corrected according to the actual situation; for example, if it is found that the ash accumulation thickness in a certain area is significantly higher than that in other areas, but it is not fully reflected during sampling, the number of sampling points in that area can be appropriately increased, and the unevenness coefficient can be recalculated to improve its representativeness of the actual ash accumulation distribution; through such a verification and correction process, the unevenness coefficient can more accurately reflect the actual 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 operating efficiency of the economizer.

[0136] In order to further optimize the above embodiment, the dynamic adjustment model is:

[0137]

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

[0139] It should be noted that the process of experimentally determining the design parameters and material properties of the economizer is:

[0140] Design a series of representative experimental conditions according to the design parameters of the economizer (such as pipe size, heat exchange area, material type, arrangement, etc.) and material properties (such as thermal conductivity, elastic modulus, corrosion resistance, etc.); these conditions should cover different ash accumulation levels, fluid temperature changes, flow fluctuations, etc. that the economizer may encounter in actual operation; prepare the equipment and instruments required for the experiment, including simulation devices that can accurately control the ash thickness (such as adjustable dust injection systems or detachable ash accumulation 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 is gradually changed. Through the simulation device, different thicknesses of ash are deposited on the surface of the economizer evenly or in a specific pattern. At the same time, the temperature, flow rate and other parameters of the fluid are adjusted to meet the preset working conditions. Under each working condition, the sonic soot blower is started and the soot blowing operation is performed with different initial soot blowing frequencies and powers. During the soot blowing process, various performance indicators of the economizer are monitored in real time, such as the inlet and outlet pressure difference, temperature difference, heat exchange efficiency, etc., as well as the actual power consumption and frequency changes of the soot blower. The change data of these indicators before and after each soot blowing operation are recorded, and attention is paid to the shedding of the ash, including the difficulty of shedding, the uniformity of shedding, and whether there is any residual ash.

[0142] For each experimental condition, the soot blowing effect is evaluated based on the changes in economizer performance indicators before and after soot blowing. The value of the dynamic adjustment coefficient under different conditions is solved through mathematical methods such as multivariate 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] Use another set of independent experimental data to verify the calculated dynamic adjustment coefficient; under the new experimental conditions, apply the determined coefficient calculation to adjust the soot blowing frequency and power, perform soot blowing operations, and observe whether the actual soot blowing effect is consistent with expectations; if it is found that there is a large deviation between the calculated results and the actual situation, the reasons may be the limitations of the experimental data, the irrationality of the model assumptions, or the inaccuracy of the coefficient calculation method; according to the analysis results, optimize the experimental design, data processing method or coefficient calculation model, and then re-experiment and calculate until a more accurate and reliable dynamic adjustment coefficient is obtained; through continuous verification and optimization process, ensure that the dynamic adjustment coefficient can accurately reflect the actual operating characteristics of the economizer, so that the dynamic adjustment model can effectively adjust the soot blowing frequency and power according to different operating conditions in actual applications, achieve the best soot blowing effect, and improve the operating efficiency and reliability of the economizer.

[0144] In order to further optimize the above embodiment, the central monitoring station includes:

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

[0146] The coefficient feedback unit is connected to the strategy optimization unit and the dynamic adjustment unit, and is used to adjust the dynamic adjustment coefficients k1, k2, k3, k4, k5, k6 in the dynamic adjustment model accordingly when receiving the feedback signal, so as to adjust the soot blowing frequency f new and adjust the sootblowing power P new Increase gradually according to the preset increase 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:

[0148] Analyze the design instructions and performance curves of the economizer to understand its tolerance range for pressure difference under different degrees of ash accumulation. If the design of the economizer allows stable operation under certain ash accumulation conditions, the threshold can be appropriately relaxed; conversely, if ash accumulation has a greater impact on equipment performance, the threshold should be set more strictly. For example, for economizers with extremely high requirements for heat exchange efficiency and high sensitivity to ash accumulation, the threshold can be set close to the lower limit of the normal operating pressure difference to ensure timely detection of poor soot blowing effects; and for some equipment that has a certain tolerance for ash accumulation, the threshold can be appropriately higher than the lower limit value on the premise of ensuring equipment safety and basic performance, to avoid too frequent soot blowing adjustments.

[0149] Another method is to communicate with on-site operators and maintenance personnel to understand the actual situation of pressure difference changes after soot blowing operations in the actual operation process, as well as the equipment maintenance cycle and requirements. If it is found that the equipment has begun to show performance degradation or requires more frequent maintenance within a certain pressure difference change range, then this range can be used as a reference for setting the threshold. For example, if experience shows that when the pressure difference change value is less than 5kPa, the heat exchange efficiency of the economizer will be significantly reduced in the short term, and the subsequent maintenance workload will increase, then the threshold can be set at around 5kPa, so that timely measures can be taken to improve the soot blowing effect and reduce the adverse effects on equipment operation.

[0150] The method for realizing the preset rise amount is:

[0151] According to the design parameters of the economizer, material properties, and the experimentally determined relationship between the dynamic adjustment coefficient and the soot blowing effect, a coefficient adjustment step table is formulated. The table lists the initial adjustment step of each dynamic adjustment coefficient under different conditions. For example, for k1, when the soot blowing effect is not obvious and the pressure difference changes slightly, the initial step can be set to 0.05; when the pressure difference changes greatly, the initial step can be increased to 0.1. The setting of these step sizes should be based on experimental data and experience to ensure that the soot blowing effect can be gradually improved when adjusting the coefficient, while avoiding excessive adjustments that may cause system instability.

[0152] When the coefficient feedback unit receives the feedback signal generated by the strategy optimization unit, it first determines the extent to which the current soot blowing effect is not obvious, for example, by calculating the difference between the current pressure difference change value and the threshold value. According to the difference, the corresponding step size is selected in the coefficient adjustment step size table, and then the dynamic adjustment coefficient is adjusted in the following manner:

[0153] For the coefficients k1 and k3 for adjusting the soot blowing frequency, 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, and the frequency increase is achieved by changing the coefficients, while taking into account the relationship between the coefficients.

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

[0155] After each adjustment of the coefficient, start a new round of soot blowing operation and continue to monitor the soot blowing effect. If the soot blowing effect is still not obvious and the feedback signal persists, select the appropriate step size in the coefficient adjustment step size table again according to the new pressure difference change (it may be necessary to increase or decrease the step size 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 value and the pressure difference change value exceeds the threshold.

[0156] In order to ensure the stability and rationality of the system, the adjustment range of the dynamic adjustment coefficient is limited. The upper and lower limits of each coefficient are set. These values ​​are the safety range determined according to the physical characteristics of the economizer and experiments. For example, the value range of k1 may be set to 0.1-2.0. When the upper or lower limit is reached during the coefficient adjustment process, it will no longer continue to increase or decrease according to the preset increase, but will remain at the boundary value, and observe whether the soot blowing effect can be improved by adjusting other coefficients or subsequent operation. At the same time, in the process of adjusting the coefficient, care should be taken to avoid excessive adjustments between two adjacent adjustments, which may cause system fluctuations. An adjustment range limit can be set. For example, the coefficient change between two adjacent adjustments shall not exceed a certain percentage (such as 20%) to ensure that the system maintains stable operation 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, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The intelligent sonic sootblower control system based on DCS is characterized by: include: A sensor module is installed at a key position of the sonic soot blower and is used to collect equipment operating parameters in real time; the equipment operating parameters include economizer structure information and internal fluid information; A field control station connected to the sensor module and used for preliminarily processing and caching the equipment operating parameters collected by the sensor; A data acquisition module, which is connected to the field control station and is used to integrate and format the data to ensure that the format of the equipment operating parameters is unified and accurate; A distributed control module connected to the data acquisition module, which establishes an optimal sootblowing simulation model and a dynamic adjustment model based on the physical characteristics of the equipment operation parameters, and is used to calculate the ideal sootblowing information and the dynamic adjustment result determined based on the ideal sootblowing information; and controls the sootblowing action of the sonic sootblower according to the dynamic adjustment result; A central monitoring station is connected to the distributed control module and the sensor module, and is used to provide feedback on the difference in effect before and after sootblowing, and optimize and adjust the dynamic adjustment model based on the difference.

2. The DCS-based intelligent sonic sootblower control system according to claim 1 is characterized in that: The economizer structural information includes the inlet and outlet pressure difference ΔP, the temperature difference ΔT, the pipeline length L, the pipeline radius r, the economizer volume V, the ambient humidity H, and the economizer heat exchange efficiency η; The internal fluid information includes fluid viscosity μ, fluid flow Q, fluid density ρ, and fluid temperature T.

3. The DCS-based intelligent sonic sootblower control system according to claim 2 is characterized in that: The field control station comprises: The data cache unit is used to temporarily store the data collected by the sensor module. Its cache capacity and storage speed meet the requirements of real-time data processing of the system to ensure that data is not lost; The preliminary processing unit performs preliminary processing on the cached data, including filtering, amplifying and digitizing the data, so that the data meets the format requirements of subsequent transmission and processing and improves the data quality.

4. The DCS-based intelligent sonic sootblower control system according to claim 3 is characterized in that: The data acquisition module comprises: 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 relevance and integrity of the data; The format processing unit formats the integrated equipment operating parameters and converts the data into a format that can be recognized and processed by the distributed control module.

5. The DCS-based intelligent sonic sootblower control system according to claim 4 is characterized in that: The distributed control module comprises: A dust accumulation thickness simulation unit is connected to the format processing unit, and establishes a dust accumulation thickness calculation model based on the inlet and outlet pressure difference ΔP, the pipeline length L, the pipeline radius r, the fluid viscosity μ, and the fluid flow rate Q, so as to calculate the dust accumulation thickness simulation value h; The change rate calculation unit is connected to the dust accumulation thickness simulation unit and the format processing unit, and determines the current dust accumulation thickness change rate based on the dust accumulation thickness simulation value h. Determine the current temperature difference change rate based on the inlet and outlet temperature difference ΔT A sound wave velocity simulation unit, which is connected to the format processing unit, establishes a sound wave velocity calculation model based on the economizer volume V, the fluid temperature T and the gas parameters determined by the previous experiment, and is used to calculate the sound wave propagation velocity simulation value v; an optimal parameter determination unit, which is connected to the dust accumulation thickness simulation unit and the sound wave velocity simulation unit, and is used to fuse the dust accumulation thickness simulation value h and the sound wave propagation velocity simulation value v, establish an optimal soot blowing simulation model, and calculate ideal soot blowing information; the ideal soot blowing information includes an ideal soot blowing frequency f0 and an ideal soot blowing power P0; The dynamic adjustment unit is connected to the optimal parameter determination unit and the change rate calculation unit, and is based on the current dust accumulation thickness change rate. Temperature change rate and ideal soot blowing information to establish a dynamic adjustment model and calculate the current dynamic adjustment result; the dynamic adjustment result includes adjusting the soot blowing frequency f new and adjust the sootblowing power P new .

6. The DCS-based intelligent sonic sootblower control system according to claim 5 is characterized in that: The calculation model of dust accumulation thickness is: Wherein, h is the simulated value of dust thickness, △P is the inlet and outlet pressure difference, L is the pipeline length, r is the pipeline radius, μ is the fluid viscosity, Q is the fluid flow rate, and k is the dust permeability; the dust permeability k is used to reflect the difficulty of the dust layer allowing fluid to pass through, and its value is determined by back-calculation experiment through permeability meter combined with the dust thickness calculation model.

7. The DCS-based intelligent sonic sootblower control system according to claim 6 is characterized in that: The acoustic wave velocity calculation model is: Where v is the simulated value of the sound wave propagation velocity, γ is the adiabatic index, V is the economizer volume, T is the fluid temperature, R is the gas constant, M eq is the equivalent molar mass, a eq and b eq is the equivalent van der Waals constant; The adiabatic index γ and the gas constant R are determined by looking up a table according to the type of gas in the economizer; Equivalent molar mass M eq By formula Determine, where i is the type of gas in the economizer, is the volume fraction of the i-th type of gas, M i For Corresponding molar mass; volume fraction and molar mass M i The values ​​of are all known values ​​of μ; Equivalent van der Waals constant a eq and b eq By formula and Determine; among them a i is the first van der Waals constant of the i-th type of gas, b i is the second van der Waals constant of the i-th type of gas, the first van der Waals constant a i and the second van der Waals constant b i The values ​​of are all known values.

8. The DCS-based intelligent sonic sootblower control system according to claim 7 is characterized in that: The optimal sootblowing simulation model is: Among them, f0 is the ideal soot blowing frequency, P0 is the ideal soot blowing power; v is the simulated value of the sound wave propagation velocity, h is the simulated value of the ash 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 materials of the economizer heat exchange element; α is the first angle parameter, representing the angle parameter related to the reflection and refraction of sound waves in the dust-accumulated medium; the calculation formula is: Among them, z1=ρ1*v1, z2=ρ2*v2; z1 is the air impedance, which is determined based on the air density ρ1 and the propagation speed of sound waves in the air v1; z2 is the dust accumulation impedance, which is determined based on the dust accumulation density ρ2 and the propagation speed of sound waves in the dust accumulation v2; β is the second angle parameter, which represents the angle parameter related to the economizer structure and ash distribution; the calculation formula is: Among them, C un is the non-uniform coefficient of ash accumulation on the pipe, which is obtained by counting the ash accumulation thickness of pipes at different positions; m and n are based on the arrangement of economizers, that is, m rows and n columns.

9. The DCS-based intelligent sonic sootblower control system according to claim 8, characterized in that: The dynamic adjustment model is: Among them, f new To adjust the soot blowing frequency, P new to adjust the sootblowing power; k1, k2, k3, k4, k5, and k6 are dynamic adjustment coefficients, which are determined through experiments based on the design parameters and material properties of the economizer.

10. The DCS-based intelligent sonic sootblower control system according to claim 9, characterized in that: The central monitoring station comprises: A strategy optimization unit, which is used to judge the soot blowing effect according to the change value ΔΔP of the economizer inlet and outlet pressure difference AP before and after soot blowing. When ΔΔP is lower than a preset threshold, it is determined that the soot blowing effect is not obvious, and a feedback signal is generated; A coefficient feedback unit is connected to the strategy optimization unit and the dynamic adjustment unit, and is used to adjust the dynamic adjustment coefficients k1, k2, k3, k4, k5, k6 in the dynamic adjustment model accordingly when receiving the feedback signal, so as to adjust the soot blowing frequency f new and adjust the sootblowing power P new Increase gradually according to the preset increase amount to improve the soot blowing effect until the feedback signal disappears.

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