Tool equipment suitable for on-site foaming type fireproof plugging material

Abstract

The invention provides tooling equipment suitable for an on-site foaming type fireproof plugging material, and belongs to the technical field of building equipment.The tooling equipment combines the temperature of a mixing cavity and a Reynolds number estimated value to calculate a comprehensive evaluation index of dispersion uniformity, and switches among an efficient dispersion mode, a standard dispersion mode and an enhanced dispersion mode according to the index numerical range; adjusting the rotating speed and the residence time of a mixing head driving motor, starting an ultrasonic-assisted dispersion device in an enhanced dispersion mode, predicting the aerogel particle size distribution variance in the next five seconds through a neural network prediction model, adjusting the rotating speed in advance, evaluating the settlement risk according to a mass flow fluctuation coefficient, and adjusting the rotating speed of a stirring motor in a grading manner; the aerogel particles are fully dispersed in a high-viscosity polyol system, and the technical problem that the aerogel particles are difficult to fully disperse in the high-viscosity polyol system, so that the performance of the fireproof plugging material is not uniform is solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of building equipment, and in particular, relates to a tooling device suitable for a site foaming type fireproof plugging material. BACKGROUND

[0002] The site foaming type fireproof plugging material is rapidly cured and formed through a two-component polyurethane system, wherein the A component contains a polyol and an aerogel loaded flame retardant, the B component contains a polyisocyanate, and the two components are chemically reacted to form a foam structure after being mixed. The traditional process uses a static mixer or a simple stirring device to complete component mixing, but since the aerogel has a low density of 50 to 150 and a high specific surface area of 600 to 1000 , it is extremely easy to agglomerate in a polyol system with a viscosity of 2000 mPa·s to 8000 mPa·s, forming aggregates with a particle size of more than 200 microns. In the prior art, since there is a lack of real-time monitoring of the flow field state in the mixing cavity and quantitative evaluation of the dispersion degree of the aerogel particles, the mixing process cannot dynamically adjust the shear strength according to the material characteristics. That is, there is a technical problem in the prior art that the aerogel particles are difficult to fully disperse in the high-viscosity polyol system, resulting in uneven performance of the fireproof plugging material. SUMMARY

[0003] Therefore, the application provides a tooling device suitable for a site foaming type fireproof plugging material, which can solve the technical problem in the prior art that the aerogel particles are difficult to fully disperse in the high-viscosity polyol system, resulting in uneven performance of the fireproof plugging material.

[0004] The application is implemented in the following manner: the application provides a tooling device suitable for a site foaming type fireproof plugging material, an A component storage tank for storing an A component containing a polyol, an aerogel loaded carbon monoxide catalyst, an aerogel loaded flame retardant and a foaming agent, and a B component storage tank for storing a B component containing a polyisocyanate and an aerogel; a double screw metering pump system includes a first double screw metering pump and a second double screw metering pump, which are connected with the A component storage tank and the B component storage tank, respectively; a Coriolis force mass flowmeter includes a first Coriolis force mass flowmeter and a second Coriolis force mass flowmeter, which are arranged on the output pipelines of the first double screw metering pump and the second double screw metering pump, respectively; a high-shear dynamic mixing head is internally provided with a multi-stage blade structure and a static mixing element; a control chip is provided with a mixing uniformity optimization control module for dynamically optimizing the mixing head rotating speed and the stirring intensity based on the flow field state parameters in the mixing cavity and the dispersion state of the aerogel particles.

[0005] The bottom of the A component storage tank is provided with a first discharge port, and the bottom of the B component storage tank is provided with a second discharge port.

[0006] The multi-stage blade structure in the high-shear dynamic mixing head comprises a first-stage blade, a second-stage blade and a third-stage blade, the first-stage blade is a radial straight blade for preliminary mixing, the second-stage blade is an inclined blade for generating tangential flow, and the third-stage blade is a reverse blade for enhancing turbulence intensity.

[0007] The steps executed by the mixing uniformity optimization control module include: controlling the first servo motor and the second servo motor to start, driving the first double screw metering pump and the second double screw metering pump to start conveying the A component and the B component according to the preset mass ratio coefficient, simultaneously starting the low-speed stirring device and the mixing head driving motor and setting the initial rotating speed parameter; collecting the A component mass flow rate and the B component mass flow rate in real time through the first Coriolis force mass flowmeter and the second Coriolis force mass flowmeter, obtaining the A component mass flow rate time sequence and the B component mass flow rate time sequence, performing sliding average filtering processing on the mass flow rate time sequence, and calculating the filtered A component average mass flow rate and the B component average mass flow rate; collecting the mixing cavity temperature measured by the temperature sensor and the discharge pressure measured by the pressure sensor, and calculating the mixing cavity Reynolds number estimate; measuring the aerogel particle size distribution variance online through the particle size analysis sensor, and determining the aerogel particle dispersion state according to the aerogel particle size distribution variance; performing hierarchical mixing intensity adjustment according to the combined state of the mixing cavity Reynolds number estimate and the aerogel particle size distribution variance; calculating the dispersion uniformity comprehensive evaluation index; performing mixing process mode switching according to the numerical range of the dispersion uniformity comprehensive evaluation index; performing settlement risk assessment, determining whether the aerogel load material in the storage tank has settled by analyzing the fluctuation coefficient of the A component mass flow rate time sequence, and adjusting the stirring motor rotating speed according to the fluctuation coefficient; constructing an aerogel particle dispersion state prediction model in the mixing cavity, the input parameters include the mixing cavity Reynolds number estimate, the mixing cavity temperature, the aerogel particle size distribution variance and the mixing head driving motor rotating speed, the output parameter is the predicted aerogel particle size distribution variance at a future time, the nonlinear mapping relationship between the input parameters and the output parameters is established through the neural network algorithm, and the mixing head driving motor rotating speed is adjusted in advance according to the predicted aerogel particle size distribution variance; taking the adjusted mixing head driving motor rotating speed, the mixing cavity residence time and the stirring motor rotating speed as new control parameters, returning to continue executing the closed-loop control until the foaming plugging operation is completed.

[0008] The preset mass ratio coefficient is the designed mass ratio of the A component to the B component, which is determined according to the fireproof plugging material formula, and is used for calculating the initial rotating speed of the second servo motor.

[0009] The moving average filtering process obtains filtered flow data by calculating the arithmetic mean of the flow values of consecutive sampling points, and the filtering window slides forward by one sampling point each time, and the mean value is recalculated after each sliding to obtain a smooth flow change curve.

[0010] The Reynolds number of the mixing chamber is estimated by multiplying the density of the material in the mixing chamber by the linear rotational speed of the mixing head, by the characteristic length of the mixing chamber, and by dividing the dynamic viscosity of the material.

[0011] The variance of the aerogel particle size distribution represents the dispersion degree of the size distribution of the aerogel particles at the outlet of the mixing chamber, and the uniformity of dispersion of the aerogel particles is determined according to the numerical range of the variance of the aerogel particle size distribution.

[0012] The adjustment of the mixing intensity according to the combination of the estimated Reynolds number of the mixing chamber and the variance of the aerogel particle size distribution determines the adjustment direction and adjustment amplitude of the rotational speed of the mixing head drive motor, and controls the shear dispersion effect by increasing or decreasing the rotational speed of the mixing head drive motor.

[0013] The comprehensive evaluation index of dispersion uniformity is the logarithmic function value of the estimated Reynolds number of the mixing chamber divided by the standard Reynolds number value multiplied by the Reynolds number weight coefficient minus the variance of the aerogel particle size distribution multiplied by the particle size variance penalty coefficient minus the square of the difference between the temperature of the mixing chamber and the reference temperature multiplied by the temperature deviation penalty coefficient, and the logarithmic function value is based on the natural constant.

[0014] The mixing process mode includes high-efficiency dispersion mode, standard dispersion mode and enhanced dispersion mode, and the mixing process mode is determined according to the numerical range of the comprehensive evaluation index of dispersion uniformity, and the mode switching is realized by adjusting the rotational speed of the mixing head drive motor and the residence time in the mixing chamber.

[0015] The residence time in the mixing chamber is the average time of the material from entering the inlet of the mixing chamber to leaving the outlet of the mixing chamber, and the residence time is adjusted by controlling the rotational speed of the first servo motor and the rotational speed of the second servo motor to adjust the total flow.

[0016] The fluctuation coefficient is the ratio of the standard deviation to the average value of the mass flow, which is obtained by calculating the standard deviation of the mass flow sampling points in the time window divided by the arithmetic mean of the sampling points, and the suspension state of the material in the storage tank is determined according to the numerical range of the fluctuation coefficient and the rotational speed of the stirring motor is adjusted.

[0017] The mixed cavity gas condensate particle dispersion state prediction model adopts a three-layer feedforward neural network structure, the input layer includes neurons corresponding to the mixed cavity Reynolds number estimation value, the mixed cavity temperature, the gas condensate particle size distribution variance and the mixed head driving motor speed, the hidden layer includes neurons adopting a hyperbolic tangent activation function, and the output layer includes neurons corresponding to the predicted gas condensate particle size distribution variance.

[0018] In the reinforced dispersion mode, the ultrasonic auxiliary dispersion device is started, the ultrasonic auxiliary dispersion device is an ultrasonic transducer installed on the wall of the mixing cavity, the dispersion of the gas condensate particles is enhanced through ultrasonic cavitation and acoustic streaming, and a starting signal of the ultrasonic auxiliary dispersion device is sent by the control chip.

[0019] In the closed-loop control, the adjusted mixed head driving motor speed, the mixed cavity residence time and the stirring motor speed are taken as new control parameters, the real-time acquisition of the mass flow is continued to be executed, and the continuous optimization of the mixing process is realized.

[0020] The particle size analysis sensor is arranged on the outlet pipeline of the high-shear dynamic mixing head to measure the gas condensate particle size distribution variance in real time, a dispersion uniformity comprehensive evaluation index is constructed in combination with the mixed cavity temperature and the Reynolds number estimation value, and three-level mixing process mode switching is performed according to the evaluation index value range. When the evaluation index is less than 0.45, the reinforced dispersion mode is started, the mixed head driving motor speed is increased by 18%, the residence time is prolonged to 10 seconds, and the ultrasonic auxiliary dispersion device is started to generate ultrasonic waves of 20 kHz to 40 kHz to break the gas condensate agglomerates through cavitation; when the evaluation index is between 0.45 and 0.75, the standard dispersion mode is adopted to moderately increase the speed; and when the evaluation index is greater than 0.75, the high-efficiency dispersion mode is maintained. In addition, the neural network prediction model predicts the particle size distribution variance in the next 5 seconds according to the current mixed cavity Reynolds number estimation value, the mixed cavity temperature, the gas condensate particle size distribution variance and the mixed head driving motor speed, and the speed is adjusted 2 seconds in advance when the predicted value exceeds 120 The technical problem of the uneven performance of the fireproof plugging material caused by the difficulty of the gas condensate particles in the high-viscosity polyol system to be fully dispersed in the background art is solved. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 It is a schematic diagram of the tooling equipment of the application.

[0022] Figure 2 It is a comparison diagram of the mass flow time series of component A before and after filtering.

[0023] Figure 3 It is a curve graph of the change of the gas condensate particle size distribution variance with time.

[0024] Figure 4A graph of the change in the coefficient of variation of the mass flow rate in the storage tank.

[0025] Figure 5 A graph comparing the predicted variance of the aerogel particle size distribution to the actual measured values.

[0026] Figure 6 A schematic of the execution steps of the uniformity optimization control module. DETAILED DESCRIPTION

[0027] In order to make the purposes, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application are clearly and completely described below.

[0028] As Figure 1As shown, the present application provides a tooling device suitable for on-site foaming type fireproof plugging material, comprising: A component storage tank, B component storage tank, double screw metering pump system, Coriolis force mass flowmeter, high shear dynamic mixing head, static mixing element, discharge nozzle, low speed stirring device, servo motor drive unit and control chip, wherein the A component storage tank is used for storing A component containing polyol, aerogel loaded carbon monoxide catalyst, aerogel loaded flame retardant and blowing agent, the B component storage tank is used for storing B component containing polyisocyanate and aerogel; the bottom of the A component storage tank is provided with a first discharge port, the bottom of the B component storage tank is provided with a second discharge port, and the first discharge port and the second discharge port are respectively connected with two independent feeding channels of the double screw metering pump system through conveying pipelines; the double screw metering pump system comprises a first double screw metering pump and a second double screw metering pump, the input end of the first double screw metering pump is connected with the first discharge port, the input end of the second double screw metering pump is connected with the second discharge port, and the output ends of the first double screw metering pump and the second double screw metering pump are respectively connected with Coriolis force mass flowmeters; the Coriolis force mass flowmeters comprise a first Coriolis force mass flowmeter and a second Coriolis force mass flowmeter, the first Coriolis force mass flowmeter is arranged on the output pipeline of the first double screw metering pump and is used for measuring the mass flow of the A component in real time, and the second Coriolis force mass flowmeter is arranged on the output pipeline of the second double screw metering pump and is used for measuring the mass flow of the B component in real time; the output pipelines of the first Coriolis force mass flowmeter and the second Coriolis force mass flowmeter are connected with the inlet of the high shear dynamic mixing head after being merged; a multi-stage blade structure is arranged inside the high shear dynamic mixing head, the multi-stage blade structure comprises a first-stage blade, a second-stage blade and a third-stage blade, the first-stage blade is a radial straight blade and is used for preliminary mixing, the second-stage blade is an inclined blade and is used for generating tangential flow, and the third-stage blade is a reverse blade and is used for enhancing turbulence intensity, and the multi-stage blade structure is driven to rotate by a mixing head driving motor; the static mixing element is arranged in the mixing cavity of the high shear dynamic mixing head, the static mixing element is a spiral type dispersion plate structure, comprises left-handed spiral plates and right-handed spiral plates arranged alternately, and is used for increasing the dispersion path of materials and generating the effects of splitting and converging; the outlet of the high shear dynamic mixing head is connected with the discharge nozzle, the discharge nozzle is a conical converging structure and is used for spraying the mixed materials to the construction site; the low speed stirring device is arranged inside the A component storage tank, the low speed stirring device comprises a stirring shaft and stirring paddles, the stirring shaft is vertically arranged on the central axis of the A component storage tank, the stirring paddles are anchor type paddle structures fixed on the lower end of the stirring shaft, the upper end of the stirring shaft is driven to rotate at a speed of 15 revolutions per minute to 45 revolutions per minute by a stirring motor, and is used for preventing the settlement of aerogel loaded materials; the B component storage tank is also provided with a low speed stirring device of the same structure.The servo motor driving unit comprises a first servo motor and a second servo motor, the first servo motor is connected with a driving shaft of the first double-screw metering pump, the second servo motor is connected with a driving shaft of the second double-screw metering pump, and the first servo motor and the second servo motor are respectively used for driving the corresponding double-screw metering pump and realizing accurate control of rotating speed; the control chip is arranged in a control box of the equipment, and the control chip is electrically connected with the first Coriolis force mass flowmeter, the second Coriolis force mass flowmeter, the first servo motor, the second servo motor, the mixing head driving motor and the stirring motor and performs data interaction, the control chip collects real-time mass flow data of the first Coriolis force mass flowmeter and the second Coriolis force mass flowmeter, monitors the output flow of the double-screw metering pump according to a preset proportioning relationship, and verifies proportioning accuracy; the control chip is also electrically connected with a temperature sensor, a pressure sensor and a particle size analysis sensor, the temperature sensor is arranged on a mixing cavity wall surface of the high-shear dynamic mixing head and is used for monitoring temperature change in the mixing process, the pressure sensor is arranged at a front end of a discharge nozzle and is used for monitoring output pressure of the material, and the particle size analysis sensor is arranged on an outlet pipeline of the high-shear dynamic mixing head and is used for online measurement of gas gel particle size distribution variance; the control chip is provided with a mixing uniformity optimization control module, which is used for dynamically optimizing the rotating speed of the mixing head based on flow field state parameters in the mixing cavity and a gas gel particle dispersion state, ensuring sufficient dispersion of the gas gel particles in the high-viscosity polyol system and avoiding occurrence of agglomeration, and adjusting stirring intensity of the low-speed stirring device according to a sedimentation risk evaluation result.

[0029] As shown in Figure 6 the mixing uniformity optimization control module is used for executing the following steps:

[0030] S01, control the first servo motor and the second servo motor to start, drive the first double-screw metering pump and the second double-screw metering pump to start conveying the A component and the B component according to a preset mass proportioning coefficient, simultaneously start the low-speed stirring device and the mixing head driving motor, and set initial rotating speed parameters, wherein the initial rotating speed of the first servo motor is 120 revolutions per minute, the initial rotating speed of the second servo motor is calculated according to the preset mass proportioning coefficient, the initial rotating speed of the mixing head driving motor is 1800 revolutions per minute, and the initial rotating speed of the stirring motor is 30 revolutions per minute;

[0031] S02, real-time collection of A component mass flow and B component mass flow is performed through the first Coriolis force mass flowmeter and the second Coriolis force mass flowmeter, the sampling frequency is 100 hertz, the continuous collection time window is 3 seconds, A component mass flow time series and B component mass flow time series are obtained, the A component mass flow time series and the B component mass flow time series are subjected to sliding average filtering processing, the filtering window length is 30 sampling points, and the filtered A component average mass flow and the B component average mass flow are calculated.

[0032] S03, collecting the mixing chamber temperature measured by the temperature sensor and the discharge pressure measured by the pressure sensor, and calculating a mixing chamber Reynolds number estimate, which is calculated according to the density of the material in the mixing chamber, the mixing head rotational linear speed, the characteristic length of the mixing chamber, and the dynamic viscosity of the material, wherein the mixing head rotational linear speed is the rotational speed of the mixing head driving motor multiplied by the blade radius multiplied by pi divided by 30;

[0033] S04, measuring the aerogel particle size distribution variance online through a particle size analysis sensor, wherein the aerogel particle size distribution variance represents the dispersion degree of the aerogel particle size distribution at the outlet of the mixing chamber, and when the aerogel particle size distribution variance is less than 80 , it is determined that the aerogel particles are uniformly dispersed, when the aerogel particle size distribution variance is between 80 and 150 , it is determined that the aerogel particles are slightly agglomerated, and when the aerogel particle size distribution variance is greater than 150 , it is determined that the aerogel particles are severely agglomerated;

[0034] S05, performing hierarchical mixing intensity adjustment according to the combined state of the mixing chamber Reynolds number estimate and the aerogel particle size distribution variance, when the mixing chamber Reynolds number estimate is less than 3500 and the aerogel particle size distribution variance is greater than 150 , the rotational speed of the mixing head driving motor is increased by 25% to enhance the shearing dispersion effect, when the mixing chamber Reynolds number estimate is between 3500 and 6000 and the aerogel particle size distribution variance is less than 80 , the current rotational speed of the mixing head driving motor is maintained, and when the mixing chamber Reynolds number estimate is greater than 6000, the rotational speed of the mixing head driving motor is reduced by 10% to avoid excessive shearing that causes the destruction of the aerogel structure;

[0035] S06, calculating a dispersion uniformity comprehensive evaluation index, which is the logarithmic function value of the mixing chamber Reynolds number estimate divided by the standard Reynolds number value multiplied by the Reynolds number weight coefficient minus the aerogel particle size distribution variance multiplied by the particle size variance penalty coefficient minus the square of the difference between the mixing chamber temperature and the reference temperature multiplied by the temperature deviation penalty coefficient, wherein the standard Reynolds number value is 4500, the Reynolds number weight coefficient is 3.2, the particle size variance penalty coefficient is 0.015 , the reference temperature is 25℃, and the temperature deviation penalty coefficient is 0.008 ;

[0036] S07、According to the numerical range of the dispersion uniformity comprehensive evaluation index, the mixing process mode switching is performed. When the dispersion uniformity comprehensive evaluation index is greater than 0.75, it is determined that the high-efficiency dispersion mode is adopted, the current mixing head drive motor speed is maintained, and the mixing cavity residence time is set to 5 seconds. When the dispersion uniformity comprehensive evaluation index is between 0.45 and 0.75, it is determined that the standard dispersion mode is adopted, the mixing head drive motor speed is increased by 8%, and the mixing cavity residence time is extended to 7 seconds. When the dispersion uniformity comprehensive evaluation index is less than 0.45, it is determined that the enhanced dispersion mode is adopted, the mixing head drive motor speed is increased by 18%, the mixing cavity residence time is extended to 10 seconds, and the ultrasonic auxiliary dispersion device is started;

[0037] S08、The settlement risk assessment is performed every 10 seconds. The fluctuation coefficient of the mass flow time series of group A is analyzed to determine whether the aerogel load material in the storage tank has settled. The fluctuation coefficient is the ratio of the standard deviation to the average value of the mass flow. When the fluctuation coefficient is less than 0.05, it is determined that the material in the storage tank is uniformly suspended, and the initial stirring motor speed is maintained. When the fluctuation coefficient is between 0.05 and 0.08, it is determined that the material in the storage tank has a settlement trend, the stirring motor speed is increased to 40 revolutions per minute. When the fluctuation coefficient is greater than 0.08, it is determined that the material in the storage tank has settled obviously, the stirring motor speed is increased to 50 revolutions per minute and maintained for 120 seconds before returning to 40 revolutions per minute.

[0038] S09、The aerogel particle dispersion state prediction model in the mixing cavity is constructed. The input parameters of the aerogel particle dispersion state prediction model in the mixing cavity include the estimated value of the mixing cavity Reynolds number, the mixing cavity temperature, the aerogel particle size distribution variance, and the mixing head drive motor speed. The output parameter is the predicted aerogel particle size distribution variance at the time of 5 seconds in the future. The non-linear mapping relationship between the input parameters and the output parameters is established by a neural network algorithm. When the predicted aerogel particle size distribution variance is greater than 120 , the mixing head drive motor speed is increased by 15% 2 seconds in advance to prevent the agglomeration from being intensified.

[0039] S10、The adjusted mixing head drive motor speed, mixing cavity residence time, and stirring motor speed are used as new control parameters, and the closed-loop control is continued to be performed from step S02 until the foaming plugging operation is completed.

[0040] The preset mass ratio coefficient is the designed mass ratio of group A and group B, which is determined according to the formula of the fireproof plugging material and has a value range of 0.8 to 1.2. The preset mass ratio coefficient is used to calculate the initial speed of the second servo motor. The calculation method is to divide the initial speed of the first servo motor by the preset mass ratio coefficient. The ratio of the mass flow of the materials output by the two double-screw metering pumps meets the formula requirements. The preset mass ratio coefficient is set before the equipment starts and remains constant during the operation.

[0041] The moving average filtering process is used to eliminate high-frequency noise and instantaneous fluctuations in the mass flow signal, and the filtered flow data is obtained by taking the arithmetic mean of the flow values of the continuous 30 sampling points, and the filtering window slides forward by 1 sampling point each time, and the average value is recalculated after each sliding, so as to obtain a smooth flow change curve and improve the accuracy of flow monitoring.

[0042] The Reynolds number estimation value of the mixing chamber is a dimensionless parameter representing the flow state of the fluid in the mixing chamber, which is calculated according to the product of the material density, the rotational linear velocity of the mixing head, and the characteristic length of the mixing chamber, and then divided by the dynamic viscosity of the material. The characteristic length of the mixing chamber is taken as the inner diameter of the mixing chamber, and the dynamic viscosity of the material is estimated according to the viscosity of the A component and the B component and the preset mass ratio coefficient through the logarithmic mixing rule. The Reynolds number estimation value greater than 4000 indicates that the flow is in a fully turbulent state, which is conducive to the dispersion of aerogel particles.

[0043] The dispersion uniformity comprehensive evaluation index is used to quantitatively evaluate the dispersion quality of the aerogel particles in the mixing chamber, and the larger the value, the better the dispersion effect. The logarithmic function value is based on the natural constant, the Reynolds number weight coefficient reflects the contribution degree of turbulent intensity to the dispersion effect, and the particle size variance penalty coefficient is used to punish the agglomeration phenomenon caused by the increase of the particle size distribution variance, and the temperature deviation penalty coefficient is used to punish the adverse effects of the temperature deviation of the mixing chamber from the reference temperature on the material viscosity and the mixing effect.

[0044] The residence time in the mixing chamber is the average time for the material to enter the mixing chamber inlet to the mixing chamber outlet. The residence time is adjusted by controlling the total flow rate through the first servo motor speed and the second servo motor speed. The longer the residence time, the longer the aerogel particles are subjected to shear dispersion, and the better the dispersion effect. However, too long residence time will cause the material to be pre-solidified in the mixing chamber.

[0045] The ultrasonic auxiliary dispersion device is an ultrasonic transducer installed on the wall of the mixing chamber, with a working frequency of 20-40 kHz and an ultrasonic power of 200-500 W. The ultrasonic cavitation effect and acoustic streaming effect enhance the dispersion of aerogel particles, and in the reinforced dispersion mode, they work together with high-speed shear to process severely agglomerated aerogel particles. The start signal of the ultrasonic auxiliary dispersion device is sent by the control chip.

[0046] The mixed cavity gas condensate particle dispersion state prediction model adopts a three-layer feedforward neural network structure, the input layer includes four neurons corresponding to the mixed cavity Reynolds number estimation value, the mixed cavity temperature, the gas condensate particle size distribution variance and the mixed head driving motor speed, the hidden layer includes eight neurons adopting a hyperbolic tangent activation function, and the output layer includes one neuron corresponding to the predicted gas condensate particle size distribution variance, and the mixed cavity gas condensate particle dispersion state prediction model obtains network weight parameters through offline training of historical operation data.

[0047] The fluctuation coefficient is an index for measuring the stability of the mass flow, is obtained by calculating the standard deviation of 300 mass flow sampling points in a 3-second time window and then dividing by the arithmetic average of the 300 sampling points, and the greater the fluctuation coefficient, the more intense the mass flow fluctuation. When the fluctuation coefficient exceeds 0.08, it indicates that the concentration of the gas condensate load material at the bottom of the storage tank is reduced, resulting in unstable flow, and the stirring needs to be strengthened to re-disperse the settled particles.

[0048] The proportioning of the on-site foaming type fireproof plugging material is as follows: the mass percentage of the polyol in the A component is 60% to 85%, the mass percentage of the gas condensate load carbon monoxide catalyst is 0.1% to 3%, the mass percentage of the foaming agent is 2% to 10%, and the mass percentage of the gas condensate load flame retardant is 10% to 20%; the mass percentage of the polyisocyanate in the B component is 90% to 95%, and the mass percentage of the gas condensate is 5% to 10%; the mass proportioning range of the A component and the B component is 0.8 to 1.2. The gas condensate is one of silica gas condensate, carbon gas condensate and alumina gas condensate, and the particle size is 1 to 100 microns. The flame retardant is one or more of ammonium polyphosphate, expandable graphite, glass microspheres and montmorillonite. The foaming agent is one of monofluorodichloroethane and cyclopentane; and the carbon monoxide catalyst is a HOGALAT agent.

[0049] The preparation method of the A component is as follows: the catalyst and the flame retardant are loaded on the gas condensate by using a sol-gel method, the gas condensate sol is prepared first, the catalyst is added to the sol and dispersed uniformly, the crosslinking agent is added to make the gas condensate sol form a gel state, and after aging, surface modification and gradient pressure reduction drying, the gas condensate load catalyst is obtained, the gas condensate load flame retardant is prepared by using the same method, and finally the polyol, the foaming agent, the gas condensate load flame retardant and the gas condensate load catalyst are mixed to prepare the A component; and the preparation method of the B component is that the polyisocyanate and the gas condensate are mixed uniformly according to the mass ratio.

[0050] The specific implementation of the above steps is described in detail below.

[0051] The application provides a tool device suitable for on-site foaming type fireproof sealing material, which realizes accurate proportioning and uniform mixing of A component and B component through a precise metering system and an efficient mixing system. The A component storage tank adopts a 200-liter stainless steel tank body, the tank body is made of 304 stainless steel, the wall thickness is 5 mm, and the inner surface of the tank body is polished to reduce material adhesion. The A component stored in the A component storage tank contains polyol as the main reaction component, wherein the hydroxyl value of the polyol is 400-450 mgKOH / g, and the viscosity at 25 degrees Celsius is 2000-3000 mPa·s. The A component also contains aerogel loaded carbon monoxide catalyst, which uses silica aerogel as a carrier and loads 8-12% palladium-based catalyst with a particle size range of 5-15 microns. The aerogel loaded flame retardant uses aluminum hydroxide or magnesium hydroxide as the active ingredient of the flame retardant, which is loaded on silica aerogel with a loading mass fraction of 15-20% and a particle size range of 10-30 microns. The blowing agent selected is cyclopentane or isopentane, with an addition mass fraction of 5-8%. The B component storage tank also adopts a 200-liter 304 stainless steel tank body, and the B component stored therein contains polyisocyanate, preferably polymeric MDI, with an NCO content of 30-32% and a viscosity of 150-250 mPa·s at 25 degrees Celsius. The aerogel added to the B component is pure silica aerogel with a particle size range of 20-50 microns and an addition mass fraction of 10-15%, which is used to improve the thermal insulation performance of the material.

[0052] The first discharge port provided at the bottom of the A component storage tank is a DN25 flange connection structure, equipped with a ball valve for controlling material output. The second discharge port provided at the bottom of the B component storage tank is also a DN25 flange connection structure. The first discharge port and the second discharge port are respectively connected to the double screw metering pump system through stainless steel conveying pipelines with an inner diameter of 25 mm, and the pipelines are wrapped with heating jackets. The heating jackets use electric heating to maintain the pipeline temperature at 40-50 degrees Celsius to prevent the material viscosity from being too high to affect the conveying. The first double screw metering pump and the second double screw metering pump both adopt meshing type double screw structure, with a screw diameter of 50 mm, a screw length of 400 mm, and a screw pitch of 50 mm. The pump body of the double screw metering pump is made of high-strength aluminum alloy, and the inner surface is chrome plated to improve wear resistance. The rated flow range of the first double screw metering pump is 0.5-5 liters per minute, and the flow can be accurately controlled by adjusting the speed of the servo motor, with a flow control accuracy of ±0.5%. The rated flow range of the second double screw metering pump is also 0.5-5 liters per minute, with a flow control accuracy of ±0.5%. The output ends of the two double screw metering pumps are respectively connected to DN20 discharge pipelines, and one-way valves are installed on the discharge pipelines to prevent material backflow.

[0053] The first and second Coriolis force mass flowmeters are both U-tube Coriolis force flowmeters, the measuring tube material is 316L stainless steel, the measuring accuracy is ±0.1%, and the mass flow measurement range is 0.1-10 kg / min. The Coriolis force mass flowmeter calculates the mass flow by measuring the phase difference generated by the Coriolis force effect, and can also measure the fluid density and temperature. The output signal of the first Coriolis force mass flowmeter is a 4-20 mA analog signal and a Modbus digital signal, which is transmitted to the control chip in real time. The output signal specification of the second Coriolis force mass flowmeter is the same as that of the first Coriolis force mass flowmeter. The output pipelines of the two Coriolis force mass flowmeters are merged through a Y-shaped tee at a distance of 500 mm from the inlet of the mixing head, and the inner diameter of the merged pipeline is 32 mm, and the pipeline length is 500 mm, which ensures that the two components have begun to contact before entering the mixing head.

[0054] The high-shear dynamic mixing head adopts a vertical cylindrical mixing chamber structure, the mixing chamber diameter is 120 mm, the mixing chamber height is 200 mm, the mixing chamber wall thickness is 10 mm, and the material is 316L stainless steel. The mixing chamber top is provided with a feed inlet with an inner diameter of 32 mm connected with the flange of the merged pipeline. The mixing chamber bottom is provided with a discharge port with an inner diameter of 25 mm. The multi-stage blade structure inside the mixing chamber is fixed on the mixing shaft, the mixing shaft diameter is 30 mm, and the mixing shaft is driven to rotate by the mixing head drive motor through the shaft coupling. The first stage blade is four radial straight blades, the blade length is 40 mm, the blade width is 15 mm, the blade thickness is 3 mm, the blade is arranged at an angle of 90 degrees with the mixing shaft, and the gap between the blade outer edge and the mixing chamber inner wall is 5 mm. The second stage blade is four inclined blades located 50 mm below the first stage blade, the blade length is 35 mm, the blade width is 12 mm, and the blade is inclined at an angle of 45 degrees with the mixing shaft, which is used to generate tangential flow to enhance the mixing effect. The third stage blade is four reverse blades located 50 mm below the second stage blade, the blade length is 30 mm, the blade width is 10 mm, and the blade inclination direction is opposite to that of the second stage blade, which is used to generate reverse turbulent flow to further improve the mixing uniformity. The mixing head drive motor is a three-phase asynchronous motor with a rated power of 3 kW and a rated speed of 1500 rpm, and the speed is adjusted through a frequency converter, and the working speed range is 500-2000 rpm.

[0055] The static mixing element is installed in the lower region of the mixing chamber, 20 mm below the third stage of vanes. The static mixing element is composed of six groups of helical dispersion plates, each group including one left-handed helical plate and one right-handed helical plate, and the helical direction of adjacent two groups of dispersion plates is opposite. The outer diameter of the helical plate is 110 mm, the inner diameter is 35 mm, the thickness of the helical plate is 2 mm, the helical angle is 180 degrees, and the material is 316L stainless steel. The helical plate is fixed on the central support rod by welding, and the central support rod is connected with the inner wall of the mixing chamber through radial support ribs. After high shear mixing by the multi-stage vanes, the material enters the static mixing element region, continuously splits and converges under the guidance of the helical plate, further enhances the mixing effect and refines the aerogel particle agglomerates. The discharge nozzle adopts a conical converging structure, the inlet diameter is 25 mm, the outlet diameter is 8 mm, the cone angle is 30 degrees, and the nozzle length is 60 mm. The inner surface of the nozzle is precisely ground, with a surface roughness Ra value less than 0.8 microns, ensuring smooth discharge of the material. The nozzle head with different pore sizes can be replaced at the nozzle outlet to meet different construction requirements.

[0056] The low-speed stirring device arranged inside the A component storage tank includes a stirring shaft and an anchor paddle. The stirring shaft is a hollow stainless steel shaft with an outer diameter of 50 mm, a wall thickness of 5 mm, and a length of 1800 mm. The upper end of the stirring shaft is installed on the top cover of the storage tank through a bearing seat, and a deep groove ball bearing is used to ensure smooth rotation. The lower end of the stirring shaft is fixed with an anchor paddle with an outer diameter of 380 mm and a gap of 10 mm between the paddle and the tank wall. The paddle adopts a frame structure composed of four radial support rods and an outer ring, and the support rod has a rectangular cross section with a width of 20 mm and a thickness of 5 mm. The stirring motor is a reduction motor with a rated power of 0.75 kW and an output speed of 30 rpm, and the speed can be adjusted in the range of 15-45 rpm. The B component storage tank also has the same low-speed stirring device to ensure that the aerogel particles remain uniformly dispersed during storage. Both the first and second servo motors are AC permanent magnet synchronous servo motors with a rated power of 2.2 kW, a rated torque of 7 Nm, and a rated speed of 3000 rpm, and are equipped with a 23-bit absolute value encoder for precise position and speed control. The servo motor is connected to the drive shaft of the double screw metering pump through a flexible coupling, which can compensate for installation errors and reduce vibration transmission. The control chip uses a 32-bit ARM architecture microcontroller with a main frequency of 180 MHz, a built-in floating point operation unit, an Ethernet interface, a CAN bus interface, and a multi-channel analog input and output interface for centralized control and data acquisition of the device.

[0057] It should be noted that the present application also solves the technical problems that the aerogel load material in the storage tank is settled due to the density difference, resulting in the formula composition deviating from the design value. The present application analyzes the fluctuation coefficient of the mass flow time series of group A every 10 seconds. When the fluctuation coefficient is less than 0.05, it indicates that the material is uniformly suspended, and the initial speed of the stirring motor is maintained at 30 revolutions per minute. When the fluctuation coefficient is between 0.05 and 0.08, it is determined that there is a settlement trend, and the stirring motor speed is increased to 40 revolutions per minute. When the fluctuation coefficient is greater than 0.08, it is determined that obvious settlement has occurred, and the stirring motor speed is increased to 50 revolutions per minute and maintained for 120 seconds. The fluctuation coefficient is obtained by calculating the standard deviation of 300 mass flow sampling points in a 3-second time window divided by the average value. The larger the value, the more intense the flow fluctuation, indicating that the concentration of the aerogel load material at the bottom of the storage tank is reduced. By adjusting the stirring intensity, the settled particles are dispersed again, and the formula composition stability is ensured.

[0058] Specifically, the principle of the present application is that the dispersion quality of aerogel particles depends on the turbulent intensity and shear time in the mixing chamber, and the turbulent intensity is characterized by the Reynolds number. The present application estimates the Reynolds number of the mixing chamber in real time. When the value is less than 3500, the flow is in a laminar or transitional flow state, and the aerogel particles cannot obtain sufficient shear dispersion energy. At this time, increasing the speed of the mixing head drive motor can increase the linear speed and thus increase the Reynolds number. When the Reynolds number exceeds 6000, excessive shear will damage the three-dimensional network structure of the aerogel, and the speed needs to be reduced to protect the material properties. The dispersion uniformity comprehensive evaluation index combines the Reynolds number, particle size variance and temperature deviation through logarithmic function, linear term and square term. The logarithmic function value reflects the nonlinear contribution of the Reynolds number to the dispersion effect, the particle size variance penalty coefficient quantifies the negative influence of agglomeration, and the temperature deviation penalty coefficient reflects the influence of temperature fluctuation on the viscosity of the material. The neural network prediction model establishes the mapping relationship between the input parameters and the particle size variance through historical data training, realizes the transformation of the control strategy from passive response to active prevention, adjusts the mixing parameters in advance before the agglomeration intensifies, and avoids the deterioration of the dispersion quality.

[0059] A specific embodiment 1 of the present application is provided below, and the specific implementation of each step in embodiment 1 is described in detail as follows.

[0060] The specific implementation of steps S01, S05, S07 and S10 is the same as described above, and will not be described in detail here.

[0061] The specific implementation of step S02 is as follows: The first Coriolis mass flow meter and the second Coriolis mass flow meter continuously collect data for 3 seconds at a sampling frequency of 100Hz to obtain the mass flow time series of component A and component B. Each series contains 300 sampling points. The collected flow data is subjected to moving average filtering to eliminate high-frequency noise. The calculation formulas for the filtered average mass flow of component A and component B are expressed as follows:

[0062] ;

[0063] ;

[0064] In the formula, For the first The average mass flow rate of component A after filtering at each time point, in kg / h; For the first The average mass flow rate of component B after filtering at each time point is expressed in kg / h. For the first Instantaneous mass flow rate of component A at each sampling point, in kg / h; For the first Instantaneous mass flow rate of component B at each sampling point, in kg / h; This is the starting position index of the sliding window, with a value ranging from 1 to 271; This is the sampling point index, with a value range of [value range missing]. to The filtering window slides forward in steps of one sampling point, and after each slide, the arithmetic mean of 30 sampling points is recalculated to obtain a smooth flow rate change curve.

[0065] The specific implementation of step S03 is as follows: the temperature sensor collects the temperature of the mixing chamber wall in real time, the pressure sensor collects the pressure at the front end of the discharge nozzle in real time, and the density of the material in the mixing chamber is calculated by weighted average of the mass flow rates of component A and component B. The calculation formula is expressed as follows:

[0066] ;

[0067] In the formula, The density of the material in the mixing chamber, in units of ; The mass flow rate of component A is expressed in kg / h, using the average mass flow rate of component A after filtering in step S02. The current value; The mass flow rate of component B is expressed in kg / h, using the average mass flow rate of component B after filtering in step S02. The current value; Density of component A, in units of , the empirical value is 1100 to 1200 ; is the density of the B component, unit is , the empirical value is 1150 to 1250 The calculation formula of the estimated value of the Reynolds number of the mixing chamber is as follows:

[0068] ;

[0069] In the formula, is the estimated value of the Reynolds number of the mixing chamber, dimensionless; is the linear speed of the mixing head, unit is m / s; is the characteristic length of the mixing chamber, unit is m, taking the inner diameter of the mixing chamber, the empirical value is 0.05 to 0.15 m; is the dynamic viscosity of the material, unit is The calculation formula of the linear speed of the mixing head is as follows:

[0070] ;

[0071] In the formula, is the rotational speed of the driving motor of the mixing head, unit is r / min; is the radius of the blade, unit is m, determined according to the geometric size of the mixing head, usually the value is 0.02 to 0.08 m; is the circular constant, the empirical value is 3.14159, dimensionless; 30 is the conversion coefficient of circular motion when the rotational speed is converted from r / min to rad / s, because 1 r / min is equal to , so the denominator is 30 when calculating the linear speed. The dynamic viscosity of the material is estimated by the logarithmic mixing rule, and the calculation formula is as follows:

[0072] ;

[0073] In the formula, is the dynamic viscosity of the A component, unit is , determined by the experimental measurement of the rotary viscometer, the empirical value is 0.5 to 2.0 ; is the dynamic viscosity of the B component, unit is , determined by the experimental measurement of the rotary viscometer, the empirical value is 0.3 to 1.5 ; is the natural logarithm function with the natural constant as the base, the empirical value is 2.71828.

[0074] The specific implementation of step S04 is as follows: The particle size analysis sensor measures the aerogel particle size distribution at the outlet of the mixing chamber online, collects particle size data of at least 200 particles, and first calculates the arithmetic mean of the particle sizes of all particles. Next, the variance of the aerogel particle size distribution is calculated. The calculation formula is as follows:

[0075] ;

[0076] In the formula, The variance of the aerogel particle size distribution is given in units of 1000 μm. ; The total number of particles collected is typically between 200 and 500, and is dimensionless. For the first The particle size, in units of ; This is the arithmetic mean of the particle sizes of all particles, in units of... ; The particle number index ranges from 1 to 1. The dispersion state is determined based on the variance value. When it is determined that the aerogel particles are uniformly dispersed, When it is determined that there is mild clustering, At that time, it was determined that there was a serious clustering.

[0077] The specific implementation of step S06 is as follows: The comprehensive evaluation index of dispersion uniformity is calculated based on the estimated Reynolds number of the mixing chamber, the variance of the aerogel particle size distribution, and the temperature of the mixing chamber. The calculation formula is expressed as follows:

[0078] ;

[0079] In the formula, It is a dimensionless comprehensive evaluation index for dispersion uniformity. The estimated Reynolds number for the hybrid cavity is dimensionless and is calculated in step S03. The variance of the aerogel particle size distribution is given in units of 1000 μm. It is obtained by measurement in step S04; 3.2 is the mixing chamber temperature, in °C, measured by a temperature sensor; 3.2 is the Reynolds number weighting coefficient, dimensionless, reflecting the contribution of turbulence intensity to the dispersion effect; 4500 is the standard Reynolds number, dimensionless, representing the Reynolds number benchmark for ideal turbulence; 0.015 is the particle size variance penalty coefficient, in °C. This is used to penalize agglomeration caused by increased particle size variance; 25 is the reference temperature in °C, representing the optimal mixing temperature; 0.008 is the temperature deviation penalty coefficient in °C. This is used to penalize the adverse effects of temperature deviations from the baseline value on viscosity and mixing performance. The first term of this formula... The contribution of the logarithmic function to the intensity of turbulence is greater; the higher the Reynolds number, the stronger the turbulence and the better the dispersion effect. The ratio is dimensionless; multiplying the logarithm by 3.2 preserves the dimensionless nature. The second term... This is a penalty term for particle size variance, in units Multiply The dimensionless value is obtained; the more dispersed the particle size distribution, the lower the evaluation index. (The third item...) As a penalty for temperature deviation, in units Multiply The dimensionless value is obtained; the further the temperature deviates from 25℃, the more detrimental it is to the mixing effect. The comprehensive evaluation index is obtained by adding the three factors together. This is a dimensionless value; the larger the value, the better the dispersion quality.

[0080] The specific implementation of step S08 is as follows: A sedimentation risk assessment is performed on the mass flow rate time series of component A every 10 seconds. Data from 300 sampling points within the first 3 seconds of the current moment are selected to calculate the mass flow rate fluctuation coefficient. The calculation formula is as follows:

[0081] ;

[0082] In the formula, The fluctuation coefficient is dimensionless. To evaluate the total number of sampling points within the time window, an empirical value of 300 is used, which is dimensionless; For the first The instantaneous mass flow rate of component A at each sampling point, in kg / h, is obtained using the raw flow rate data collected in step S02; For evaluation within the window The arithmetic mean mass flow rate of the sampling points, in kg / h, is calculated using the following formula: This average value is related to the filtered flow rate in step S02. The calculation method is different; here it is a direct average of all sampling points within the evaluation window. The index of the sampling point number within the evaluation window, with a value ranging from 1 to... In the formula, the numerator is the standard deviation of the flow rate within the evaluation window, in kg / h, and the denominator is the average flow rate within the evaluation window, in kg / h. The fluctuation coefficient is obtained by dividing the two. It is dimensionless. Settlement risk is determined based on the fluctuation coefficient value. When the material is determined to be uniformly suspended, the initial speed of the stirring motor is maintained at 30 r / min. When a settling trend is detected, the stirring motor speed is increased to 40 r / min. If significant settling has occurred, the stirring motor speed is increased to 50 r / min and maintained for 120 seconds before being reduced to 40 r / min.

[0083] The specific implementation of step S09 is to construct a mixed cavity aerogel particle dispersion state prediction model, which adopts a three-layer feedforward neural network structure, the input layer contains four neurons corresponding to the mixed cavity Reynolds number estimation value, the mixed cavity temperature, the aerogel particle size distribution variance and the mixed head driving motor speed, the hidden layer contains eight neurons adopting a hyperbolic tangent activation function, and the output layer contains one neuron corresponding to the predicted aerogel particle size distribution variance. The prediction model obtains network weight parameters through offline training of historical operation data, and predicts the aerogel particle size distribution variance at a future time of 5 seconds in real time. When the predicted value is greater than 0.0005, the mixed head driving motor speed is increased by 15% 2 seconds in advance to prevent agglomeration from being intensified.

[0084] The specific implementation of the preset mass ratio coefficient is that the preset mass ratio coefficient is the designed mass ratio of the A component and the B component, which is determined according to the formula of the fireproof plugging material and is dimensionless, and the value range is 0.8 to 1.2. The calculation formula of the initial speed of the second servo motor is as follows:

[0085] ;

[0086] In the formula, V0 is the initial speed of the second servo motor, the unit is r / min; V0 is the initial speed of the second servo motor, the unit is r / min; V0 is the initial speed of the first servo motor, the empirical value is 120 r / min; is the preset mass ratio coefficient, which is dimensionless. In the formula, V0 is divided by the dimensionless After that, the unit remains r / min. The formula ensures that the mass flow ratio of the materials output by the two double screw metering pumps meets the formula requirements. The preset mass ratio coefficient is pre-set before the equipment starts and remains constant during the operation. The specific implementation of the residence time in the mixed cavity is that the residence time in the mixed cavity

[0087] is the average time of the material from entering the mixed cavity inlet to leaving the mixed cavity outlet, and the calculation formula is as follows:

[0088] ;

[0089] In the formula, t is the residence time in the mixed cavity, the unit is s; V is the effective volume of the mixed cavity, the unit is , which is determined according to the geometric size of the mixed cavity, and the empirical value is 0.0005 to 0.002 ; is the density of the material in the mixed cavity, the unit is ​​​It is calculated by step S03; The average mass flow rate of component A after filtering is expressed in kg / h, using the values ​​from step S02. The current value; The average mass flow rate of component B after filtering is expressed in kg / h, using the values ​​from step S02. The current value; 3600 is the conversion factor from hours to seconds, with units of s / h. In the formula, the numerator... Units are denominator The unit is kg / h, and the residence time is obtained by dividing by the total flow rate in seconds. The residence time is controlled by adjusting the speed of the first servo motor and the speed of the second servo motor to change the total flow rate. The longer the residence time, the longer the shear dispersion time of the aerogel particles and the better the dispersion effect. However, if the residence time is too long, the material will undergo a pre-curing reaction in the mixing chamber.

[0090] It should be noted that the variables involved in this embodiment are explained in detail in Table 1.

[0091] Table 1. Variable Explanation Table

[0092]

[0093] To better understand and implement this invention, Example 2 of a specific application scenario is provided below: According to the fireproof sealing material formulation requirements, the technical team prepared 185 kg of Component A in a Component A storage tank, wherein the polyol accounted for 72% of the mass, the aerogel-supported hogallat catalyst accounted for 1.5% of the mass, the cyclopentane foaming agent accounted for 6% of the mass, the aerogel-supported ammonium polyphosphate flame retardant accounted for 14.5% of the mass, and the aerogel-supported expandable graphite flame retardant accounted for 6% of the mass. 176 kg of Component B was prepared in a Component B storage tank, wherein the polyisocyanate accounted for 92% of the mass, and the silica aerogel accounted for 8% of the mass. The silica aerogel used had an average particle size of 45 micrometers and an aerogel skeleton density of 0.18. According to the formula requirements, the preset mass ratio coefficient is set to 1.05, that is, the designed mass ratio of component A to component B is 1.05 to 1.

[0094] In the device startup phase, the control chip executes step S01 through the mixing uniformity optimization control module, the initial rotation speed of the first servo motor is set to 120 revolutions per minute, the initial rotation speed of the second servo motor is calculated according to the preset mass ratio coefficient to be 114 revolutions per minute, the initial rotation speed of the mixing head drive motor is set to 1800 revolutions per minute, and the initial rotation speeds of the stirring motors in the A component storage tank and the B component storage tank are both set to 30 revolutions per minute. After the start of the double screw metering pump system, the mass flow data is collected in real time through the first and second Coriolis force mass flow meters, the sampling frequency is 100 Hz, and the flow data in a 3-second time window is continuously collected. As shown in FIG. Figure 2 , the A component mass flow time series has large fluctuations in the initial stage, and after sliding average filtering processing with a filter window length of 30 sampling points, the average mass flow of the A component is 2.84 kg / min and the average mass flow of the B component is 2.70 kg / min, and the mass flow ratio of the two is 1.052, with a deviation of only 0.2% from the preset mass ratio coefficient, verifying that the ratio accuracy meets the requirements.

[0095] In the mixing process monitoring phase, the temperature sensor measures the mixing chamber temperature to be 28℃, and the pressure sensor measures the discharge pressure to be 0.65 MPa. According to the material density in the mixing chamber of 1.12 , the mixing head blade radius of 0.042 meters, and the mixing head drive motor rotation speed of 1800 revolutions per minute, the mixing head rotation linear speed is calculated to be 3.95 . The mixing chamber characteristic length is taken as the mixing chamber inner diameter of 0.085 meters, the material dynamic viscosity is estimated to be 1850 mPa·s according to the A component viscosity of 4500 mPa·s and the B component viscosity of 280 mPa·s through the logarithmic mixing rule, and the mixing chamber Reynolds number estimate value is calculated to be 4520. As shown in FIG. Figure 3 , the aerogel particle size distribution variance measured online by the particle size analysis sensor is 72 , indicating that the aerogel particles are uniformly dispersed and the mixing effect is good.

[0096] At the 180th second in the running process, the particle size analysis sensor detects that the aerogel particle size distribution variance suddenly rises to 165 , exceeding the 150 threshold value, indicating that the aerogel particles are severely agglomerated. At the same time, the mixing chamber Reynolds number estimate value decreases to 3280, which is less than the 3500 threshold value. The control chip executes step S05 to adjust the mixing intensity, immediately increases the mixing head drive motor rotation speed from 1800 revolutions per minute to 2250 revolutions per minute, and enhances the shearing dispersion effect. After 8 seconds of intensive mixing, the aerogel particle size distribution variance decreases to 85 , the mixing chamber Reynolds number estimate value rises to 4680, and the mixing state returns to normal.

[0097] The technical team calculates the dispersion uniformity comprehensive evaluation index according to step S06, the standard Reynolds number value is 4500, the Reynolds number weight coefficient is 3.2, the particle size variance penalty coefficient is 0.015 , the reference temperature is 25°C, and the temperature deviation penalty coefficient is 0.008 . As shown in Table 2, the dispersion uniformity comprehensive evaluation index and the corresponding mixing process mode at different running times.

[0098] Table 2 Dispersion uniformity comprehensive evaluation index and mixing process mode at different times

[0099]

[0100] At the 180th second, the dispersion uniformity comprehensive evaluation index is 0.38, which is less than the threshold value of 0.45, and the system determines that the dispersion mode is strengthened. The mixing head driving motor speed is increased by 18% to 2124 revolutions per minute, the residence time in the mixing chamber is extended to 10 seconds, and the ultrasonic auxiliary dispersion device is started. The ultrasonic working frequency is 28 kHz, and the ultrasonic power is 350 W. After the strengthened dispersion treatment, the dispersion uniformity comprehensive evaluation index gradually rises to 0.68, and the system switches to the standard dispersion mode.

[0101] In terms of storage tank sedimentation risk assessment, the control chip executes step S08 every 10 seconds. At the 420th second, the fluctuation coefficient calculation value of the A group mass flow time series is 0.072, which is between 0.05 and 0.08, indicating that the material in the storage tank has a sedimentation trend. As Figure 4 shown, the ratio of the standard deviation to the average value shows an upward trend, indicating that the aerogel loading material begins to settle at the bottom of the storage tank. The control chip immediately increases the stirring motor speed from 30 revolutions per minute to 40 revolutions per minute. After 60 seconds of intensive stirring, the fluctuation coefficient is reduced to 0.048, and the material is uniformly suspended again. The stirring motor speed returns to the initial value.

[0102] The technical team builds a prediction model for the dispersion state of aerogel particles in the mixing chamber, using a three-layer feedforward neural network structure. The input layer includes four neurons: the estimated value of the mixing chamber Reynolds number, the mixing chamber temperature, the aerogel particle size distribution variance, and the mixing head driving motor speed. The hidden layer includes 8 neurons using the hyperbolic tangent activation function, and the output layer outputs the predicted aerogel particle size distribution variance at the next 5 seconds. The prediction model obtains the network weight parameters through offline training of historical running data. In actual operation, when the predicted aerogel particle size distribution variance is greater than 120 , the system increases the mixing head driving motor speed by 15% 2 seconds in advance, achieving preventive control of agglomeration. As Figure 5As shown, the comparison curve of the predicted aerogel particle size distribution variance and the actual measured value shows that the average absolute error of the prediction model is 8.6 , and the prediction accuracy meets the engineering application requirements.

[0103] During the entire plugging construction process, the technical team completed the fireproof plugging operation of 78 cable crossing points, with a total time consumption of 6.5 hours, an average time consumption of 5 minutes per group of plugging points, and the total consumption of the A group component and the B group component being 178 kg and 169 kg respectively, with the proportioning accuracy deviation being controlled within 0.5%. The average density of the foamed material after plugging is 0.085 , the bubble hole diameter distribution is uniform, the average bubble hole diameter is 0.32 mm, the aerogel particles are uniformly dispersed in the polyurethane foam matrix, and no obvious agglomeration phenomenon is found. The fireproof performance test of the plugging material shows that the fire resistance limit reaches 180 minutes, and the surface maximum temperature is 285℃, which meets the technical requirements of the power tunnel fireproof plugging.

[0104] The technical progress brought by the present application relative to the traditional fireproof plugging means mainly embodies in the following aspects. First, through real-time monitoring and closed-loop feedback control of the Coriolis force mass flowmeter, dynamic optimization of the proportioning accuracy of the A component and the B component is realized, and the proportioning deviation caused by temperature and pressure fluctuations in the traditional volumetric measurement method is avoided. Second, the synergistic effect of the high-shear dynamic mixing head and the static mixing element, combined with the radial flow, tangential flow and reverse turbulence generated by the multi-stage blade structure, significantly enhances the dispersion effect of the aerogel particles in the high-viscosity polyol system, solving the technical problem of easy agglomeration of aerogel. Third, based on the hierarchical mixing intensity adjustment strategy of the mixing chamber Reynolds number and the aerogel particle size distribution variance, the mixing head speed and residence time can be dynamically adjusted according to the actual mixing state, which ensures the dispersion effect while avoiding excessive shear-induced damage to the aerogel structure. Fourth, the low-speed stirring device cooperates with the settlement risk assessment algorithm to judge the suspension state of the aerogel loading material in the storage tank by monitoring the mass flow fluctuation coefficient in real time, and dynamically adjusts the stirring intensity, effectively preventing the settlement stratification phenomenon caused by long-term parking. Fifth, the introduction of the neural network prediction model realizes the forward-looking control of the dispersion state of the aerogel particles, prevents the agglomeration from intensifying by adjusting the mixing parameters in advance, and improves the intelligent control level and process stability of the system.

[0105] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A tooling device suitable for on-site foaming fireproof sealing materials, comprising a component A storage tank, a component B storage tank, a twin-screw metering pump system, a Coriolis mass flow meter, a high-shear dynamic mixing head, a static mixing element, a discharge nozzle, a low-speed stirring device, a servo motor drive unit, and a control chip, characterized in that, The A-component storage tank stores component A, which contains polyol, aerogel-supported carbon monoxide catalyst, aerogel-supported flame retardant, and foaming agent. The B-component storage tank stores component B, which contains polyisocyanate and aerogel. The twin-screw metering pump system includes a first twin-screw metering pump and a second twin-screw metering pump, which are connected to the A-component and B-component storage tanks, respectively. The Coriolis mass flow meter includes a first Coriolis mass flow meter and a second Coriolis mass flow meter, which are installed on the output pipelines of the first and second twin-screw metering pumps, respectively. The high-shear dynamic mixing head is equipped with a multi-stage blade structure and static mixing elements. The control chip is equipped with a mixing uniformity optimization control module, which is used to dynamically optimize the mixing head speed and stirring intensity based on the flow field state parameters in the mixing chamber and the dispersion state of aerogel particles.

2. The tooling equipment according to claim 1, characterized in that, The A component storage tank has a first discharge port at the bottom, and the B component storage tank has a second discharge port at the bottom. The first and second discharge ports are respectively connected to two independent feed channels of the twin-screw metering pump system through conveying pipelines.

3. The tooling equipment according to claim 2, characterized in that, The multi-stage blade structure inside the high-shear dynamic mixing head includes a first-stage blade, a second-stage blade, and a third-stage blade. The first-stage blade is a radial straight blade used for initial mixing, the second-stage blade is an inclined blade used to generate tangential flow, and the third-stage blade is a reverse blade used to enhance turbulence intensity.

4. The tooling equipment according to claim 3, characterized in that, The steps executed by the mixing uniformity optimization control module include: controlling the start of the first and second servo motors to drive the first and second twin-screw metering pumps to begin conveying component A and component B according to a preset mass ratio coefficient; simultaneously starting the low-speed stirring device and the mixing head drive motor and setting the initial speed parameters; real-time acquisition of the mass flow rates of component A and component B using the first and second Coriolis mass flow meters to obtain the mass flow rate time series of component A and component B; performing moving average filtering on the mass flow rate time series to calculate the filtered average mass flow rate of component A and component B; acquiring the mixing chamber temperature measured by the temperature sensor and the discharge pressure measured by the pressure sensor to calculate the estimated Reynolds number of the mixing chamber; online measurement of the aerogel particle size distribution variance using the particle size analysis sensor to determine the dispersion state of the aerogel particles based on the aerogel particle size distribution variance; and determining the dispersion state of the aerogel particles based on the estimated Reynolds number of the mixing chamber and the aerogel particle size distribution variance. The system performs graded mixing intensity adjustment based on the combined variance state; calculates the comprehensive evaluation index of dispersion uniformity; switches the mixing process mode according to the numerical range of the comprehensive evaluation index of dispersion uniformity; performs sedimentation risk assessment by analyzing the fluctuation coefficient of the mass flow rate time series of component A to determine whether aerogel-loaded material sedimentation occurs in the storage tank, and adjusts the stirring motor speed according to the fluctuation coefficient; constructs a prediction model of aerogel particle dispersion state in the mixing chamber, with input parameters including the estimated Reynolds number of the mixing chamber, mixing chamber temperature, aerogel particle size distribution variance, and mixing head drive motor speed, and output parameter being the predicted aerogel particle size distribution variance at future time. A nonlinear mapping relationship between input and output parameters is established through a neural network algorithm, and the mixing head drive motor speed is adjusted in advance according to the predicted aerogel particle size distribution variance; the adjusted mixing head drive motor speed, residence time in the mixing chamber, and stirring motor speed are used as new control parameters, and the closed-loop control is continued until the foaming and sealing operation is completed.

5. The tooling equipment according to claim 4, characterized in that, The preset mass ratio coefficient is the design mass ratio of component A to component B, which is determined according to the fireproof sealing material formula. It is used to calculate the initial speed of the second servo motor. The calculation method is to divide the initial speed of the first servo motor by the preset mass ratio coefficient.

6. The tooling equipment according to claim 5, characterized in that, The moving average filtering process obtains filtered flow data by calculating the arithmetic mean of the flow values ​​at continuous sampling points. The filtering window slides forward with the sampling points as the step size, and the average value is recalculated after each slide, thus obtaining a smooth flow change curve.

7. The tooling equipment according to claim 6, characterized in that, The calculation of the estimated Reynolds number of the mixing chamber is based on the material density in the mixing chamber multiplied by the linear velocity of the mixing head rotation multiplied by the characteristic length of the mixing chamber and then divided by the dynamic viscosity of the material. The linear velocity of the mixing head rotation is the mixing head drive motor speed multiplied by the blade radius multiplied by pi and then divided by 30.

8. The tooling equipment according to claim 7, characterized in that, The variance of aerogel particle size distribution characterizes the degree of dispersion of aerogel particle size distribution at the outlet of the mixing chamber. The range of the variance of aerogel particle size distribution determines whether the aerogel particles are uniformly dispersed, have slight agglomeration, or have severe agglomeration.

9. The tooling equipment according to claim 8, characterized in that, The graded mixing intensity adjustment determines the direction and magnitude of the mixing head drive motor speed adjustment based on the combination of the estimated Reynolds number of the mixing chamber and the variance of the aerogel particle size distribution. The shear dispersion effect is controlled by increasing or decreasing the speed of the mixing head drive motor.

10. The tooling equipment according to claim 9, characterized in that, The comprehensive evaluation index of dispersion uniformity is the logarithmic function of the estimated Reynolds number of the mixing chamber divided by the standard Reynolds number, multiplied by the Reynolds number weighting coefficient, minus the variance of the aerogel particle size distribution, multiplied by the particle size variance penalty coefficient, minus the square of the difference between the mixing chamber temperature and the reference temperature, multiplied by the temperature deviation penalty coefficient, with the logarithmic function value based on the natural constant.

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