A method and system for acoustic generator soot blowing test

Abstract

The application provides a kind of acoustic wave generator soot blowing test method and system, comprising: build experimental platform simulating low low temperature economizer working environment and install test sample and sensing equipment;Set power output parameters, including fixed power level and pulse power modulation parameters, soot blowing frequency and phase control parameters, time period and adaptive adjustment parameters, acoustic wave frequency and airflow speed and vector control parameters;Carry out soot blowing operation and collect data through sensing equipment, including obtaining soot coverage and particle information through optical imaging sensor, obtaining pressure generated by acoustic wave at the position of soot particle through acoustic sensor array;Calculate cleaning efficiency, and adjust and iterative experiment according to cleaning efficiency and data feedback;The application realizes the overall optimization of acoustic wave generator soot blowing process, improves the soot blowing effect of low low temperature economizer, and further improves the overall operation efficiency of energy equipment, prolongs the service life of equipment, meets the requirements of environmental protection and energy saving.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of equipment maintenance, and in particular to a method and system for acoustic generator soot blowing test. BACKGROUND

[0002] In the field of energy equipment, low-temperature economizer is an important component, which mainly recovers the waste heat of flue gas and improves energy utilization efficiency. However, in the actual operation process, the heat exchange elements of low-temperature economizer are prone to soot deposition. With the increasingly stringent environmental protection requirements, higher requirements are put forward for the efficient operation of energy equipment. Soot deposition will increase the resistance of low-temperature economizer, making the flue gas flow not smooth and increasing the energy consumption of the fan. At the same time, soot deposition will form an insulating layer on the surface of the heat exchange element, which will seriously reduce the heat exchange efficiency and affect the energy recovery effect, thereby being contrary to the trend of environmental protection and energy saving.

[0003] In the early stage, manual soot removal is a common way, in which the staff manually removes the soot on the surface of the heat exchange element regularly. This way has high labor intensity and low efficiency, and it is easy to cause damage to the equipment during cleaning, and it cannot meet the needs of continuous operation of large-scale energy equipment. The emergence of acoustic soot blowing technology brings a new idea to solve the problem of soot deposition. Acoustic soot blowing uses high-intensity sound waves generated by a sound wave generator to make soot particles vibrate. When the vibration reaches a certain degree, the soot particles overcome the adhesion to the surface of the heat exchange element and separate. Acoustic soot blowing has the advantages of non-contact and no thermal stress, and will not cause physical damage to the heat exchange element, and the energy consumption is relatively low. However, the existing acoustic soot blowing technology also has many problems.

[0004] The power output and sound wave frequency of most existing sound wave generators are fixed or have limited adjustable range. In actual application, different types of soot (such as different particle sizes, compositions, and viscosities) and different heat exchange element structures and working conditions have different requirements for the power and frequency of sound waves. Single power and frequency setting cannot achieve the best soot blowing effect for various situations, resulting in incomplete soot removal in many cases.

[0005] Current acoustic soot blowing technology often only focuses on the parameters of sound waves, ignoring the synergistic effect with other factors. For example, airflow can assist in carrying away the blown soot during soot blowing to avoid secondary deposition, but the existing technology rarely optimizes the airflow speed, direction, and sound wave parameters jointly. At the same time, factors such as the time period, frequency of soot blowing, and phase control between multiple sound wave generators have not been fully considered, and the overall soot blowing effect cannot be maximized.

[0006] For the evaluation of the soot blowing effect, the existing technology mainly relies on simple observation or some rough indicators such as the approximate change of heat exchange efficiency; there is a lack of accurate and comprehensive data collection and analysis methods, and it is difficult to accurately judge the specific reasons for the poor soot blowing effect, so as to adjust the soot blowing parameters, which limits the further optimization of the soot blowing technology;

[0007] Therefore, there is an urgent need in the art for a sound wave generator soot blowing test method and system to solve the above problems. SUMMARY

[0008] The present application provides a sound wave generator soot blowing test method and system, which aims to solve the above-mentioned problems in the prior art, to realize the comprehensive optimization of the sound wave generator soot blowing process, to improve the soot blowing effect of the low-temperature economizer, and to improve the overall operation efficiency of the energy equipment, prolong the service life of the equipment, and meet the requirements of environmental protection and energy saving.

[0009] In one aspect, the present application provides a sound wave generator soot blowing test method, comprising:

[0010] Step one, build an experimental platform simulating the working environment of a low-temperature economizer and install test samples and sensing equipment;

[0011] Step two, set the power output parameters, including fixed power level and pulse power modulation parameters, soot blowing frequency and phase control parameters, time period and adaptive adjustment parameters, sound wave frequency, and air flow speed and vector control parameters;

[0012] Step three, perform soot blowing operation and collect data through sensing equipment, including obtaining soot coverage and particle information through optical imaging sensors, and obtaining the pressure generated by sound waves at the location of soot particles through acoustic sensor arrays;

[0013] Step four, calculate the cleaning efficiency based on the collected data, and adjust and iterate the experiment according to the cleaning efficiency and data feedback.

[0014] According to the sound wave generator soot blowing test method provided by the present application, in step one, the size of the experimental platform and the standard values of temperature, humidity and pressure are preset;

[0015] A flat plate test sample is carried in the experimental platform, which is made of the same metal material as the actual economizer;

[0016] Sensing equipment is carried in the experimental platform, including high-resolution optical imaging sensors and acoustic sensor arrays.

[0017] According to the acoustic wave generator soot blowing test method provided by the application, in step two, the fixed power level and pulse power modulation parameters include:

[0018] The fixed power level is preset; the pulse power modulation has a preset pulse width and pulse interval;

[0019] The acoustic wave frequency is preset, and the acoustic wave angular frequency ω is calculated;

[0020] The initial phase is preset

[0021] The acoustic wave generator generates a certain acoustic pressure amplitude at a certain distance from the sample, based on the relationship between the structure of the acoustic wave generator and the sample position, the coefficient A is determined by the finite element simulation method s , the coefficient A s is used to reflect the spatial characteristics and energy coupling relationship of acoustic wave propagation;

[0022] For the soot particles, which have specific physical properties such as size, shape and material density, based on the calculation of Mie acoustic theory and the combination of acoustic resonance related experiments, the coefficient k is determined by the method combining theory and experiment s,i , the coefficient k s,i is used to reflect the absorption and response characteristics of the soot particles under the action of the acoustic wave.

[0023] According to the acoustic wave generator soot blowing test method provided by the application, in step two, the soot blowing frequency and phase control parameters include:

[0024] The initial soot blowing frequency is preset, and for multiple simulated acoustic wave generators working at the same time, the initial number and phase difference are preset.

[0025] According to the acoustic wave generator soot blowing test method provided by the application, the time period and adaptive adjustment parameters include:

[0026] The initial soot blowing time period is preset, the soot thickness threshold is set to 0.1mm, and when the optical imaging sensor detects that the soot thickness exceeds the threshold, the next soot blowing time interval is shortened by a preset value.

[0027] According to the acoustic wave generator soot blowing test method provided by the application, the airflow velocity and vector control parameters include:

[0028] The airflow velocity v g (t) and the angle θ between the airflow direction and the surface of the test sample are preset;

[0029] Based on the structural characteristics of the airflow generator and the flow field inside the platform, the airflow density ρ g is calculated by fluid mechanics software;

[0030] projected area A of the soot particle in the direction of the airflow g,i = πr 2 cosθ; where r is the average radius of the soot particle, determined by the optical imaging sensor detection in step three;

[0031] unit vector of the direction of the airflow

[0032] particle shape and Reynolds number of the soot particle to calculate the drag coefficient C d .

[0033] According to the acoustic wave generator soot blowing test method provided by the application, in step three, the process of performing soot blowing operation and collecting data by the sensing device includes:

[0034] acquiring the surface soot image of the test sample by the optical imaging sensor before the soot blowing starts;

[0035] obtaining the initial soot coverage G, the average radius r of the soot particle and the soot density ρ by the image analysis algorithm h ;

[0036] calculating the total mass of the initial soot where x is the area of the flat test sample;

[0037] acquiring the pressure P(N) generated by the acoustic wave at each moment at the position of the soot particle by the acoustic sensor array.

[0038] According to the acoustic wave generator soot blowing test method provided by the application, in step four, the calculation process of calculating the cleaning efficiency based on the collected data includes:

[0039] S41, calculating the acoustic wave force F s,i(t) experienced by the i-th soot particle at t moment, the calculation formula is:

[0040]

[0041] where P(t) is the acoustic wave pressure at t moment, determined based on the detection result P(N) of the acoustic sensor array; the acoustic wave force F s,i(t) is used to reflect the force applied to the soot particle by the acoustic wave during propagation;

[0042] S42, calculating the airflow force F g,i(t) experienced by the i-th soot particle at t moment, the calculation formula is:

[0043]

[0044] the airflow force F g,i(t)For reflecting the force of airflow acting on the ash deposition particles in the soot-blowing process;

[0045] S43, calculating the adhesion force F of the i-th ash deposition particle at t moment a,i(t) , the calculation formula is:

[0046] F a,i(t) = F v,i + F e,i + F m,i

[0047] Wherein, F v,i is the van der Waals force calculated based on the Lifshitz-van der Waals theory, F e,i is the electrostatic force based on the charge distribution of the ash deposition particles and the surface of the heat exchange element, F m,i is the capillary force calculated by the liquid surface tension coefficient and the contact angle, which are determined based on experiments before or after soot-blowing; the adhesion force F a,i(t) For reflecting the force hindering the ash deposition particles from separating from the surface of the heat exchange element;

[0048] S43, calculating the inter-particle interaction force F of the i-th ash deposition particle at t moment i,i(t) , the calculation formula is:

[0049]

[0050] Wherein, n is the total number of ash deposition particles; the van der Waals force F v,ij , the electrostatic force F e,ij and the determination process of F v,i , F e,i are the same, and F c,ij is the collision force determined based on the Hertzian contact theory, which are determined based on experiments before or after soot-blowing; the inter-particle interaction force F i,i(t) For reflecting the interaction between the ash deposition particles;

[0051] S44, determining the cleaning efficiency E; the calculation formula is:

[0052]

[0053] Wherein, t1 and t2 are the start and stop times of soot-blowing, respectively, and v is the velocity of the i-th ash deposition particle at t moment, which is obtained by solving the motion equation of the ash deposition particle based on Newton's second law.

[0054] According to the soot-blowing test method of the acoustic wave generator provided by the application, the process of adjusting and iterating experiments on parameters according to the cleaning efficiency and data feedback comprises:

[0055] After the end of the soot blowing experiment, the data collected by the sensor and the cleaning efficiency result are analyzed; if the cleaning efficiency E does not reach the expected target, i.e., the expected target is that the cleaning efficiency E is greater than the preset threshold, the fixed power level and the pulse power modulation parameter, the soot blowing frequency and the phase control parameter, the time period and the self-adaptive adjustment parameter, and the airflow speed and the vector control parameter are adjusted according to the data feedback;

[0056] Steps 1 to 4 are repeated to perform the next round of experiment, and the parameters are continuously optimized to improve the cleaning efficiency.

[0057] In another aspect, the present application provides a soot blowing test system of an acoustic wave generator, comprising:

[0058] An experimental platform building module is configured to build a space simulating the working environment of a low-temperature economizer, to provide an installation basis for a test sample and a sensing device, and to control the temperature, humidity and pressure parameters of the experimental environment to meet the experimental requirements;

[0059] A parameter setting module is connected with the experimental platform building module and is configured to preset various initial key parameters in the soot blowing test, including the fixed power level and the pulse power modulation parameter, the soot blowing frequency and the phase control parameter, the time period and the self-adaptive adjustment parameter, the acoustic wave frequency, and the airflow speed and the vector control parameter;

[0060] A soot blowing execution module is connected with the experimental platform building module and the parameter setting module and is configured to perform the soot blowing operation according to the preset parameters, including the acoustic wave generator generating acoustic waves acting on the soot particles, and the airflow generator generating airflow with a specific speed and direction to assist in soot blowing and carrying away the soot;

[0061] A data collection module is connected with the experimental platform building module and is configured to obtain various types of information in the soot blowing process through the sensing device, including the soot coverage, particle information, and the pressure generated by the acoustic waves at the position of the soot particles;

[0062] A data analysis module is connected with the parameter setting module and the data collection module and is configured to calculate the acoustic wave force, airflow force, adhesion force and interaction force of the soot particles according to the preset parameters, and to calculate the cleaning efficiency in combination with the information obtained by the data collection module;

[0063] An experimental optimization module is connected with the data analysis module and the parameter setting module and is configured to determine whether the expected target is reached according to the obtained cleaning efficiency, and if not, to adjust the various preset parameters in the parameter setting module according to the data feedback, to determine the parameter settings of the next round of experiment, and to realize the iterative optimization of the experiment to improve the cleaning efficiency.

[0064] Compared with the prior art, the present application has the following advantages:

[0065] The present application comprehensively considers various soot-blowing parameters, such as fixed power level and pulse power modulation parameters, soot-blowing frequency and phase control parameters, time period and adaptive adjustment parameters, acoustic wave frequency, and airflow speed and vector control parameters. By accurately setting and adjusting these parameters, more accurate soot-blowing operations can be achieved for different types of soot (such as soot of different particle sizes, compositions, and viscosities) and different heat exchange element structures and working conditions.

[0066] The present application accurately calculates the cleaning efficiency by considering the microscopic processes of soot particles during soot-blowing, such as force and motion, enabling researchers to accurately evaluate the soot-blowing effect and identify the specific reasons for poor soot-blowing effect, such as whether the lack of acoustic wave force, inappropriate airflow speed, or inter-particle interaction force is the cause of incomplete soot removal in a certain area.

[0067] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by means of the instrumentalities particularly pointed out in the written description and claims hereof.

[0068] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0069] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation on the present application. In the drawings:

[0070] Figure 1 is a flowchart of a soot-blowing test method of a sound wave generator provided by an embodiment of the present application;

[0071] Figure 2 is a structural schematic diagram of a soot-blowing test system of a sound wave generator provided by an embodiment of the present application. DETAILED DESCRIPTION

[0072] The preferred embodiments of the present application will be described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and do not limit the present application.

[0073] Example 1:

[0074] An embodiment of the present application provides a soot-blowing test method of a sound wave generator, please refer to Figure 1 , which comprises:

[0075] Step one, build an experimental platform simulating the working environment of a low-temperature economizer and install test samples and sensing equipment;

[0076] Step two, set power output parameters, including fixed power level and pulse power modulation parameters, soot blowing frequency and phase control parameters, time period and adaptive adjustment parameters, sound wave frequency, and air flow speed and vector control parameters;

[0077] Step three, perform soot blowing operation and collect data through sensing devices, including obtaining soot coverage and particle information through optical imaging sensors, and obtaining sound wave pressure generated at the location of soot particles through acoustic sensor array;

[0078] Step four, calculate cleaning efficiency based on collected data, and adjust and iterate experiments according to cleaning efficiency and data feedback.

[0079] The principle and beneficial effects of the embodiment are that sound wave is a mechanical wave, which can produce vibration effect when acting on soot surface, weakening the adhesion between particles and between particles and substrate in soot layer, thereby helping to remove soot; by adjusting the parameters of sound wave power output, frequency, soot blowing frequency, phase control, etc., the most effective removal strategy can be adopted for different types of soot (such as loose type and cohesive type); optical imaging sensors and acoustic sensor array are used to monitor soot condition and removal effect in real time, and parameters are automatically adjusted according to actual cleaning efficiency, realizing efficient and accurate soot removal;

[0080] Compared with traditional manual or mechanical cleaning methods, sound wave technology can more thoroughly remove soot in hard-to-reach parts, reduce energy consumption, and improve equipment operation efficiency; this method is suitable for soot removal tasks in various industrial scenarios, and is easy to adjust parameter settings according to different application requirements, having good applicability and flexibility.

[0081] In order to further optimize the above embodiment, in step one, the size of the experimental platform and the standard values of temperature, humidity and pressure are pre-set;

[0082] A flat plate test sample is mounted in the experimental platform, which is made of the same metal material as the actual coal economizer;

[0083] Sensing devices are mounted in the experimental platform, including high-resolution optical imaging sensors and acoustic sensor arrays;

[0084] In step two, the fixed power level and pulse power modulation parameters include:

[0085] The fixed power level is pre-set; the pulse power modulation has pre-set pulse width and pulse interval;

[0086] The sound wave frequency is pre-set, and the sound wave angular frequency ω is calculated;

[0087] Pre-set initial phase

[0088] The acoustic wave generator generates a certain sound pressure amplitude at a specific distance from the sample. Based on the relationship between the structure of the acoustic wave generator and the sample position, the coefficient A is determined by the finite element simulation method s , the coefficient A s is used to reflect the spatial characteristics and energy coupling relationship of sound wave propagation;

[0089] For the dust particles, which have specific physical properties such as size, shape, and material density, the coefficient k is determined by combining theoretical calculations based on Mie acoustic theory and relevant acoustic resonance experiments s,i , the coefficient k s,i is used to reflect the absorption and response characteristics of the dust particles under the action of sound waves.

[0090] It should be noted that the coefficient A s mainly reflects the comprehensive influence of the structure of the acoustic wave generator and the sample position on the propagation of sound wave energy. It links the output of the acoustic wave generator (such as sound pressure amplitude) with the effective sound wave energy acting on the dust particles. In terms of physical nature, it considers factors such as attenuation, reflection, refraction, and other factors during the propagation of sound waves from the generator to the location of the dust particles. If the acoustic wave generator is a horn-shaped device, factors such as the size and shape of its opening, the distance and relative angle to the sample, and other factors will affect the energy intensity of the sound wave at the sample location. The larger the value of the coefficient A s , the stronger the effective sound wave energy reaching the dust particle location under the same output power of the acoustic wave generator, and the more effectively it can drive the dust particles to vibrate. The finite element software (such as ANSYS, COMSOL, etc.) can be used to model the space where the acoustic wave generator and the sample are located. The structural parameters of the acoustic wave generator (such as size, material, vibration mode, etc.) and the position information of the sample (distance, angle, etc.) are used as input conditions. By solving the propagation equation of sound waves in this space, the relationship between the sound pressure distribution at different locations and the parameters of the acoustic wave generator is obtained, thereby determining the coefficient A s ;

[0091] The coefficient k s,i is closely related to the physical properties of the dust particles, including particle size, shape, material density, and elastic modulus. It represents the coupling efficiency of the dust particles under the action of sound waves, i.e., the ability of the particles to absorb and respond to sound wave energy. For smaller dust particles, their mass is small and they are more easily driven to vibrate under the same sound wave, which may have a larger k s,i value; while larger particles have larger inertia and respond relatively weakly to sound waves, which may have a smaller k s,i value. In addition, the material properties of the particles also affect ks,i For example, particles made of material with better elasticity can better generate elastic deformation and absorb energy under the action of sound waves, and their k s,i values will be different from those of particles made of rigid material. In theory, for spherical soot particles, their scattering and absorption characteristics of sound waves can be calculated according to the Mie theory to obtain coefficients related to particle size, material density, sound wave frequency, etc. However, the actual soot particles have complex shapes, which need to be modified by experiments. For example, through acoustic resonance experiments, the soot particles are placed in a sound wave field with a known frequency and intensity, and the resonance frequency and response amplitude of the particles are measured, which are compared with the theoretical calculation results to modify the coefficients, thereby obtaining k s,i .

[0092] In an embodiment, in the step of setting the power output parameters, the fixed power output level is set to 50%, the pulse width is set to 20 ms, the pulse interval is set to 100 ms, the sound wave frequency is selected to be 500 Hz, and the sound wave angular frequency ω = 2π * 500 Hz; the initial phase

[0093] To further optimize the above embodiment, in step two, the soot blowing frequency and phase control parameters include:

[0094] The initial soot blowing frequency is set in advance. For multiple simulated sound wave generators working simultaneously, the initial number and phase difference are set in advance.

[0095] It should be noted that in an embodiment, in the step of setting the soot blowing frequency and phase control parameters, the soot blowing frequency is set to 3 times per minute, and for multiple simulated sound wave generators working simultaneously, the number is set to 3 and the phase difference is set to 30°.

[0096] To further optimize the above embodiment, the time period and adaptive adjustment parameters include:

[0097] The initial soot blowing time period is set in advance, and the soot thickness threshold is set to 0.1 mm. When the soot thickness detected by the optical imaging sensor exceeds this threshold, the next soot blowing time interval is shortened by a preset value.

[0098] It should be noted that in an embodiment, in the step of setting the time period and adaptive adjustment parameters, the initial soot blowing time period is set to 10 minutes, and the soot thickness threshold is set to 0.1 mm. When the soot thickness detected by the optical imaging sensor exceeds this threshold, the next soot blowing time interval is shortened to 5 minutes.

[0099] To further optimize the above embodiment, the airflow speed and vector control parameters include:

[0100] The airflow speed vg (t) and the angle θ between the airflow direction and the surface of the test sample;

[0101] Based on the structural characteristics of the airflow generator and the flow field inside the platform, the airflow density p is calculated by fluid mechanics software g ;

[0102] The projected area A of the soot particles in the direction of the airflow is calculated g,i = πr 2 cos θ; where r is the average radius of the soot particles, determined by the optical imaging sensor in step three;

[0103] The unit vector of the airflow direction is determined

[0104] The particle shape and Reynolds number of the soot particles are calculated to determine the drag coefficient C d .

[0105] It should be noted that the principle of the optical imaging sensor for obtaining the average radius of the soot particles and the calculation principle of the drag coefficient C d are both existing technical means, so they will not be described in detail.

[0106] To further optimize the above embodiment, in step three, the process of blowing ash and collecting data by the sensing device includes:

[0107] The soot image of the test sample surface is obtained by the optical imaging sensor before blowing ash starts;

[0108] The initial soot coverage G, the average radius r of the soot particles, and the soot density p h are obtained by image analysis algorithm;

[0109] The total mass of the initial soot is calculated where x is the area of the flat test sample;

[0110] The pressure P(N) generated by the sound wave at each time at the location of the soot particles is obtained by the acoustic sensor array.

[0111] It should be noted that the image analysis algorithm is an existing technical means and will not be described; the area of the flat test sample is pre-set in step one.

[0112] To further optimize the above embodiment, in step four, the calculation process of calculating the cleaning efficiency based on the collected data includes:

[0113] S41, the sound wave force F s,i(t) experienced by the i-th soot particle at time t is calculated, and the calculation formula is:

[0114]

[0115] where P(t) is the sound wave pressure at time t, determined based on the detection result P(N) of the acoustic sensor array; the sound wave force F s,i(t) for reflecting the force exerted by the sound wave on the ash particles during the propagation process;

[0116] S42, calculating the airflow force F g,i(t) experienced by the i-th ash particle at time t, the calculation formula is:

[0117]

[0118] the airflow force F g,i(t) for reflecting the force exerted by the airflow on the ash particles during the soot blowing process;

[0119] S43, calculating the adhesion force F a,i(t) experienced by the i-th ash particle at time t, the calculation formula is:

[0120] F a,i(t) = F v,i + F e,i + F m,i

[0121] where F v,i is the van der Waals force calculated based on the Lifshitz-van der Waals theory, F e,i is the electrostatic force based on the charge distribution of the ash particles and the surface of the heat exchange element, F m,i is the capillary force calculated based on the liquid surface tension coefficient and the contact angle, all of which are determined based on experiments before or after soot blowing; the adhesion force F a,i(t) for reflecting the force that hinders the ash particles from detaching from the surface of the heat exchange element;

[0122] S43, calculating the inter-particle interaction force F i,i(t) experienced by the i-th ash particle at time t, the calculation formula is:

[0123]

[0124] where n is the total number of ash particles; the van der Waals force F v,ij , the electrostatic force F e,ij , the collision force F v,i , and the capillary force F e,i are determined in the same way as F c,ij is the collision force determined based on the Hertzian contact theory, all of which are determined based on experiments before or after soot blowing; the inter-particle interaction force F i,i(t) for reflecting the interaction between the ash particles;

[0125] S44, determining the cleaning efficiency E; the calculation formula is:

[0126]

[0127] where t1, t2 are blowing start and stop times, respectively, and vi is the velocity of the i-th soot particle at time t, which is obtained by solving the motion equation of the soot particle based on Newton's second law.

[0128] It should be noted that, for the adhesion force F a,i(t) , the van der Waals force F v,i can be calculated by their material properties (such as dielectric constant, refractive index, etc.) and geometric shape. For the case of spherical soot particles and planar heat transfer element surface, the van der Waals force formula is where A is the Hamaker constant, which depends on the properties of the particle and surface material, and can be obtained by consulting relevant material manuals or experimental measurement; d is the distance between the particle and the surface, which can be approximated as the atomic spacing (about several angstroms) when in close contact; another method is to use atomic force microscopy (AFM) to directly measure the van der Waals force. The AFM probe simulates the soot particle, and by measuring the force-distance curve between the probe and the sample surface (simulating the heat transfer element surface), when the distance is small enough, the measured force is mainly the van der Waals force. By measuring samples of different particle sizes and materials multiple times, the relationship between the van der Waals force and the particle size parameters is fitted.

[0129] The calculation of electrostatic force F e,i is based on Coulomb's law. First, the charge distribution of the soot particle and the heat transfer element surface needs to be determined. If it is assumed that the particle and the surface are uniformly charged with Q1 and Q2 respectively, the electrostatic force formula is where k is the Coulomb constant, and r is the distance between the center of the particle and the center of the surface charge; however, in actual situations, the charge distribution is usually non-uniform, and a more accurate electrostatic force needs to be obtained by solving the Poisson equation of the electrostatic field. This involves analysis of the conductivity, dielectric constant and charge generation mechanism (such as tribocharging, electrostatic induction, etc.) of the particle and surface material. Another method is to use an electrometer to measure the potential difference between the soot particle and the heat transfer element surface. By changing the environmental conditions (such as humidity, friction, etc.) to observe the change of the potential difference, the generation and distribution of the charge are inferred, and then the electrostatic force is calculated according to the theoretical model and measured potential difference parameters. In addition, an electric field force microscope (EFM) can also be used to directly measure the electrostatic force distribution between the particle and the surface.

[0130] Capillary force F m,iThe calculation is based on the surface tension theory. When there is a trace of liquid film (such as moisture) between the soot particles and the surface of the heat exchange element, the capillary force can be calculated according to the Young-Laplace equation. For a cylindrical liquid meniscus, a common simplified model, the capillary force formula is F m,i = 2πrγcosδ, where γ is the surface tension coefficient of the liquid, which can be obtained by consulting the physical property table of the liquid; δ is the contact angle between the liquid and the particle or the surface, which is measured by a contact angle measuring instrument; r is the radius of the soot particle; another method is to measure the contact angle by observing the shape of the liquid between the particle and the surface. A small amount of liquid is dropped on the simulated system of the particle and the surface, and an optical microscope or a video contact angle measuring system is used to record the shape of the liquid, so as to determine the contact angle. Then the capillary force is calculated by combining the surface tension coefficient of the liquid and the particle radius.

[0131] For the parameters in the interaction force F i,i(t) , the principles of determining van der Waals force and electrostatic force are the same as those of adhesion force, so they will not be further elaborated; the collision force F c,ij According to the Hertzian contact theory, the collision force of two elastic spheres (soot particles) is where E * is the equivalent elastic modulus, which is related to the elastic modulus of the particle material and is obtained by material mechanics performance test; is the equivalent radius, for two particles with radii R1 and R2, δ is the contact deformation when the particles collide, which can be calculated by combining the kinematic equation with the parameters such as the velocity, mass and elastic recovery coefficient of the particles; another method is to record the collision process of the soot particles by a high-speed camera, and measure the velocity, position change and other information of the particles before and after the collision. According to the law of conservation of momentum and the law of conservation of energy, combined with the material properties and geometric dimensions of the particles, the collision force can be calculated. Micro force sensor can also be used to directly measure the force generated when the particles collide.

[0132] In order to further optimize the above embodiment, the process of adjusting and iterating the parameters according to the cleaning efficiency and data feedback includes:

[0133] After the completion of this soot blowing experiment, the data collected by the sensor is analyzed according to the cleaning efficiency result; if the cleaning efficiency E does not reach the expected target, i.e. the expected target is that the cleaning efficiency E is greater than the preset threshold, the fixed power level and pulse power modulation parameters, soot blowing frequency and phase control parameters, time period and self-adaptive adjustment parameters, airflow velocity and vector control parameters are adjusted according to the data feedback;

[0134] Repeat steps one to four to perform the next round of experiment, and continuously optimize the parameters to improve the cleaning efficiency.

[0135] It should be noted that after the end of the soot blowing experiment, the data collected by the sensor is analyzed according to the cleaning efficiency result. If the cleaning efficiency does not reach the expected target (assuming that the expected target is that the cleaning efficiency is greater than 80%), the parameters are adjusted according to the data feedback. For example, if it is found that the soot removal effect in a certain area is poor, it may be that the air flow vector in that area is unreasonable, and the air flow direction can be adjusted or the local air flow speed can be increased; or it is found that the sound waves of certain frequencies have no obvious effect on soot removal, and the sound wave frequency combination is adjusted. Then repeat the above steps for the next round of experiment, and continuously optimize the parameters to improve the cleaning efficiency.

[0136] Embodiment 2:

[0137] The embodiment of the present application provides a sound wave generator soot blowing test system, please refer to Figure 2 , comprising:

[0138] The experimental platform building module is used to build a space simulating the working environment of a low-temperature economizer, provides a mounting basis for the test sample and the sensing device, and controls the temperature, humidity and pressure parameters of the experimental environment to meet the experimental requirements;

[0139] The parameter setting module is connected with the experimental platform building module, and is used to pre-set various initial key parameters in the soot blowing test, including the fixed power level and the pulse power modulation parameter, the soot blowing frequency and the phase control parameter, the time period and the self-adaptive adjustment parameter, the sound wave frequency, and the air flow speed and vector control parameter;

[0140] The soot blowing execution module is connected with the experimental platform building module and the parameter setting module, and is used to execute the soot blowing operation according to the pre-set parameters, including that the sound wave generator generates sound waves acting on the soot particles, and the air flow generator generates air flow with a specific speed and direction to assist in soot blowing and carry away the soot;

[0141] The data collection module is connected with the experimental platform building module, and is used to obtain various types of information in the soot blowing process through the sensing device, including the soot coverage, the particle information, and the pressure generated by the sound waves at the position of the soot particles;

[0142] The data analysis module is connected with the parameter setting module and the data collection module, and is used to calculate the sound wave force, the air flow force, the adhesion force and the interaction force of the soot particles according to the pre-set parameters, and calculate the cleaning efficiency in combination with the information obtained by the data collection module;

[0143] The experimental optimization module is connected with the data analysis module and the parameter setting module, and is used to determine whether the expected target is reached according to the obtained cleaning efficiency, and if not, the various pre-set parameters in the parameter setting module are adjusted according to the data feedback, the parameter settings of the next round of experiment are determined, and the iterative optimization of the experiment is realized to improve the cleaning efficiency.

[0144] The workflow of the embodiment is as follows: after the experimental platform building module builds the experimental platform and sets the environmental parameters, the parameter setting module sets various soot blowing parameters according to the experimental requirements;

[0145] The soot blowing execution module performs soot blowing operation according to the set parameters, and the data collection module collects various data in the soot blowing process in real time;

[0146] The data collection module transmits the data to the data processing and analysis module, which calculates the cleaning efficiency and performs data analysis;

[0147] The experimental optimization module judges whether the parameters need to be optimized according to the result of the data processing and analysis module. If so, the parameters in the parameter setting module are adjusted, and then the soot blowing operation is performed again. This cycle is repeated to continuously optimize the soot blowing effect.

[0148] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of sonic generator soot blowing test, characterized by, The method comprises the following steps: Step 1: build an experimental platform simulating the working environment of a low-temperature economizer, and install test samples and sensing equipment; Step 2: set power output parameters, including fixed power level and pulse power modulation parameters, soot blowing frequency and phase control parameters, time period and adaptive adjustment parameters, sound wave frequency, and airflow speed and vector control parameters; Step 3: perform soot blowing operation and collect data through sensing equipment, including obtaining soot coverage and particle information through optical imaging sensors, and obtaining sound wave pressure generated at the position of soot particles through acoustic sensor arrays; Step 4: calculate cleaning efficiency based on collected data, and adjust and iterate experiments according to cleaning efficiency and data feedback.

2. The sonic generator soot blowing test method of claim 1, wherein, In step 1, the size of the experimental platform and the standard values of temperature, humidity and pressure are pre-set; A flat test sample is carried in the experimental platform, which is made of the same metal material as the actual economizer; Sensing equipment is carried in the experimental platform, including high-resolution optical imaging sensors and acoustic sensor arrays.

3. The sonic generator soot blowing test method of claim 2, wherein, In step 2, the fixed power level and pulse power modulation parameters include: The fixed power level is pre-set; the pulse power modulation has a pre-set pulse width and pulse interval; Pre-set the sound wave frequency, and calculate the sound wave angular frequency ; Pre-setting initial phase ; The sound wave generator generates a certain sound pressure amplitude at a specific distance from the sample, and a coefficient is determined by a finite element simulation method based on the structure of the sound wave generator and the position relationship of the sample , the coefficient is used to reflect the spatial characteristics and energy coupling relationship of sound wave propagation; For the dust particles, it has specific size, shape, material density physical properties, based on the calculation of Mie acoustic theory and combined with acoustic resonance related experiments, through the combination of theory and experiment method to determine the coefficient , coefficient Reflects the dust particles under the action of acoustic wave itself physical properties of acoustic wave energy absorption and response characteristics.

4. The sonic generator soot blowing test method of claim 1, wherein, In step 2, the soot blowing frequency and phase control parameters include: The pre-set initial soot blowing frequency, and the pre-set initial number and phase difference when multiple simulated sound wave generators work simultaneously.

5. The sonic generator soot blowing test method of claim 1, wherein, The time period and adaptive adjustment parameters include: The initial soot blowing time period is pre-set, and the soot thickness threshold is set to 0.1 mm; when the soot thickness detected by the optical imaging sensor exceeds this threshold, the next soot blowing time interval is shortened by a pre-set value.

6. The sonic generator soot blowing test method of claim 3, wherein, The airflow speed and vector control parameters include: Pre-set air flow speed and the angle between the air flow direction and the surface of the test sample ; Based on the structural characteristics of the air flow generator and the flow field inside the platform, the air flow density is calculated by fluid mechanics software ; projected area of the soot particle in the direction of the airflow ; wherein is the average radius of the soot particle, determined by the optical imaging sensor detection in step three; Unit vector determining airflow direction ; Particle shape and reynolds number calculation of dust particle resistance coefficient .

7. The sonic generator soot blowing test method of claim 6, wherein, In step 3, the process of performing soot blowing operation and collecting data through sensing equipment includes: Before soot blowing starts, obtain the soot image of the test sample surface through the optical imaging sensor; obtained by an image analysis algorithm , average radius of the soot particles , soot density ; calculating the initial total mass of soot accumulation wherein A is the area of the flat plate test sample; acquiring, by the acoustic sensor array, the pressure generated by the sound wave at each time at the location of the dust particles .

8. The sonic generator soot blowing test method of claim 7, wherein, In step 4, the calculation process of calculating cleaning efficiency based on collected data includes: S41, calculate the sound wave force received by the ith soot particle at t moment The calculation formula is: wherein, P(t) is the sound wave pressure at time t, based on the acoustic sensor array detection results determined; the sound wave force for reflecting the force exerted by the sound wave on the soot particles during propagation; S42, calculate the airflow force received by the ith soot particle at time t The calculation formula is: the airflow force for reflecting the force of the airflow on the soot particles during the sootblowing process; S43, calculate the adhesion force received by the ith soot particle at time t The calculation formula is: wherein, is the van der Waals force calculated based on the Lifshitz-van der Waals theory, is the electrostatic force based on the charge distribution of the soot particles and the surface of the heat transfer element, is the capillary force calculated based on the surface tension coefficient and the contact angle of the liquid, both of which are determined experimentally before or after soot blowing; the adhesion force is used to reflect the force that hinders the soot particles from detaching from the surface of the heat transfer element; S43, calculate the inter-particle interaction force received by the ith soot particle at time t The calculation formula is: wherein, Total number of fouling particles; Van der Waals force Electrostatic force and , The determination process is the same, Collision force determined based on Hertzian contact theory, both based on experiments before or after blowing; the inter-particle interaction force for reflecting the interaction between the fouling particles; S44, determine the cleaning efficiency The calculation formula is: wherein, , are the blowing start and stop times, respectively, and vi(t) is the velocity of the ith ash particle at time t, which is obtained by solving the equation of motion of the ash particle based on Newton's second law.

9. The sonic generator soot blowing test method of claim 8, wherein, The process of adjusting and iterating experiments according to cleaning efficiency and data feedback includes: After the end of the soot blowing experiment, the data collected by the sensors are analyzed according to the cleaning efficiency results; if the cleaning efficiency does not reach the expected target, i.e. the expected target is that the cleaning efficiency is greater than a preset threshold, then the fixed power level and pulse power modulation parameters, the soot blowing frequency and phase control parameters, the time period and adaptive adjustment parameters, and the airflow speed and vector control parameters are adjusted according to the data feedback. Repeat steps 1 to 4 to perform the next round of experiments, and continuously optimize parameters to improve cleaning efficiency.

10. A sonic generator soot blowing test system for use in a sonic generator soot blowing test method as claimed in any one of claims 1 to 9, characterized in that, The method comprises the following steps: An experimental platform building module is used to build a space simulating the working environment of a low-temperature economizer, provide a mounting basis for test samples and sensing equipment, and control the temperature, humidity and pressure parameters of the experimental environment to meet the experimental requirements; A parameter setting module is connected with the experimental platform building module, and is used to pre-set various initial key parameters in soot blowing experiments, including fixed power level and pulse power modulation parameters, soot blowing frequency and phase control parameters, time period and adaptive adjustment parameters, sound wave frequency, and airflow speed and vector control parameters; A soot blowing execution module is connected with the experimental platform building module and the parameter setting module, and is used to perform soot blowing operation according to pre-set parameters, including sound wave generators generating sound waves acting on soot particles, and airflow generators generating airflow with specific speed and direction to assist soot blowing and carry away soot. a data collection module connected with the experimental platform building module, configured to acquire various information in the soot-blowing process through a sensing device, including soot coverage, particle information, and pressure generated by the sound wave at the position of the soot particle; a data analysis module connected with the parameter setting module and the data collection module, configured to calculate the sound wave force, airflow force, adhesion force, and interaction force of the soot particle according to the preset parameters, and calculate the cleaning efficiency in combination with the information acquired by the data collection module; an experimental optimization module connected with the data analysis module and the parameter setting module, configured to determine whether the expected target is reached according to the obtained cleaning efficiency, and if not, adjust various preset parameters in the parameter setting module according to the data feedback, determine the parameter setting of the next round of experiment, and realize the iterative optimization of the experiment to improve the cleaning efficiency.

Images