A big data-based fly ash high-temperature thermal energy storage data analysis system and method

Abstract

The application relates to the field of fly ash treatment, in particular to a fly ash high-temperature heat storage data analysis system and method based on big data, which comprises a sample processing module, an information modeling module, a melting combustion module, a time-sharing feeding module and a crystallization inspection module, the sample processing module is used for collecting and inspecting samples, the information modeling module is used for determining the relationship among the melting rate, the energy absorption amount and the temperature rising rate, the melting combustion module is used for calculating the fuel mixing ratio, the time-sharing feeding module is used for calculating the optimal temperature rising rate, and the crystallization inspection module is used for adding a solidifying agent and prolonging the holding time. The application can improve the energy utilization efficiency, reduce the cost of secondary fly ash treatment, reduce the incomplete combustion phenomenon, reduce the fly ash residue, reduce the difficulty and cost of fly ash treatment, improve the combustion efficiency of fuel, realize transparent management of the melting furnace data, and improve the resource utilization quality of the melted fly ash.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of fly ash treatment, in particular to a fly ash high-temperature heat energy storage data analysis system and method based on big data. BACKGROUND

[0002] Fly ash resource is a process of converting fly ash generated by coal-fired power plants, waste incineration plants and the like into a usable resource through technical means. Fly ash generated by burning solid waste usually contains harmful substances such as heavy metals and dioxins. Direct discharge or landfill will pollute the environment. Improving resource processing can convert fly ash into building materials, insulation materials, soil conditioners and the like, realizing the reuse of waste.

[0003] Currently, there are two categories of fly ash treatment methods: stabilization and solidification method and separation and extraction method. In the process of preparing insulation materials, the stabilization and solidification method has lower cost. Fly ash is treated by water washing and high-temperature melting to realize crystallization and solidification. The stabilization and solidification method has high requirements for temperature. However, the melting furnace is fully enclosed, and the melting state of fly ash cannot be known. Under complex components and temperature rising conditions, it is difficult to control the addition time of the solidification agent, resulting in poor crystallization efficiency.

[0004] In addition, fly ash needs to be mixed with fuel such as natural gas before entering the furnace to support the combustion heat of fly ash in the furnace. However, the control of fuel addition amount is a big difficulty in fly ash melting. Too much addition amount will increase the cost of fly ash treatment and cause waste of heat. Too low addition amount cannot completely remove harmful substances in fly ash, prolonging the fly ash treatment time. The temperature rising and heat absorption properties of fly ash also make the process of controlling heat more complex. SUMMARY

[0005] The purpose of the present application is to provide a fly ash high-temperature heat energy storage data analysis system and method based on big data to solve the problems raised in the background.

[0006] In order to solve the above technical problems, the present application provides the following technical scheme: a fly ash high-temperature heat energy storage data analysis system based on big data, comprising: a sample processing module, an information modeling module, a melting combustion module, a time-sharing feeding module and a crystallization inspection module;

[0007] The sample processing module collects fly ash samples from electrostatic precipitators or bag-type dust collectors of fly ash sources, grinds, dries and fully mixes the fly ash, and then groups the samples. Each group is set to have a different temperature rising rate. The samples are heated at the temperature rising rate in an inert atmosphere until the samples are in a molten state. A simultaneous thermal analyzer is used to observe the melting process, record the heating time, the melting start temperature and the melting end temperature of the samples, collect the gas in the heating process, and pass the gas into an absorption liquid to analyze the residual amount of harmful gas.

[0008] The information modeling module is configured to obtain a DSC curve from a synchronous thermal analyzer, integrate an endothermic peak area to obtain a melting enthalpy, determine energy absorption of the sample when reaching a melting state at different temperature rise rates, calculate kinetic parameters in a reaction process according to a melting start temperature and a melting end temperature, determine a first function of a melting rate and a temperature rise rate and a second function between the energy absorption and the temperature rise rate, limit a function domain according to an influence of the temperature rise rate on a harmful gas residue, and make the harmful gas residue lower than a threshold value;

[0009] The melting combustion module is configured to solve a minimum energy required for fly ash melting according to a ratio of the second function to the first function, calculate a mixing ratio of the fuel and the fly ash according to a calorific value of the selected fuel, calculate fuel demand according to a fly ash feeding amount, adjust a fuel injection rate through a PID controller, send the mixed fly ash and fuel into a melting furnace for combustion, and monitor a furnace temperature deviation in real time and feed back to a monitoring platform.

[0010] The time-sharing feeding module is configured to calculate a temperature rise rate when the ratio of the second function to the first function is minimum, as an optimal temperature rise rate, substitute the optimal temperature rise rate into the first function to obtain a theoretical melting rate, and adjust the theoretical melting rate according to the feedback of the furnace temperature deviation until complete melting.

[0011] The crystallization inspection module is configured to add a crystal nucleus solidification agent and a mineralization solidification agent into the furnace at the melting start temperature and the melting end temperature respectively, and evaluate a crystallization effect after discharging, and if the crystallinity is less than a threshold value, extend a holding time before discharging.

[0012] Further, the sample processing module comprises a pretreatment unit, a melting experiment unit and a gas analysis unit.

[0013] The pretreatment unit is configured to collect fly ash samples, grind the fly ash to a particle size less than 75 μm, and remove free water.

[0014] The melting experiment unit is configured to heat the sample at a set temperature rise rate until the sample is melted, and observe the melting process.

[0015] The gas analysis unit is configured to connect a NaOH solution-containing absorption bottle to a STA tail gas outlet, and analyze a harmful gas residue.

[0016] Further, the information modeling module comprises an energy absorption unit and a dynamic fitting unit.

[0017] The energy absorption unit is configured to establish a model of the energy absorption and the temperature rise rate, and calculate a function between the energy absorption and the temperature rise rate.

[0018] The dynamic fitting unit is configured to fit the melting dynamic parameters according to a peak temperature of a DSC melting temperature curve.

[0019] Further, the melting combustion module comprises: a feed nozzle unit, a melting furnace unit and a state feedback unit;

[0020] The feed nozzle unit is used to calculate the minimum energy required for melting, adjust the fuel mixing ratio, and the fuel includes: natural gas, coke and biofuel;

[0021] The melting furnace unit is used to provide a container for fly ash melting combustion and to control the in-furnace feed;

[0022] The state feedback unit is used to establish a fly ash melting management platform and feedback the real-time deviation of the furnace temperature.

[0023] Further, the time-sharing feeding module comprises: a constant temperature solidification unit and a sintering discharge unit;

[0024] The constant temperature solidification unit is used to calculate the optimal temperature rise rate and adjust the furnace temperature according to the optimal temperature rise rate;

[0025] The sintering discharge unit is used to ensure that the fly ash is completely melted at the outlet of the melting furnace by matching the furnace rotation speed or the conveying belt speed.

[0026] Further, the crystallization inspection module comprises: a solidification test unit and a storage cooling unit;

[0027] The solidification test unit is used to establish a temperature field finite element model based on the in-furnace multi-point thermocouple data and determine the feeding temperature;

[0028] The storage cooling unit is used to detect the precipitated crystal phase and prolong the holding time before discharge when the crystallinity is insufficient.

[0029] A fly ash high-temperature thermal energy storage data analysis method based on big data, comprising the following steps:

[0030] Step S1. Collect fly ash samples from the dust collector, group the samples after pretreatment, set different temperature rise rates for each group, heat the samples at the set temperature rise rate in an inert atmosphere until the samples are in a molten state, observe the melting process using a simultaneous thermal analyzer, and generate a DSC melting temperature curve;

[0031] Step S2. Integrate the endothermic peak area of the DSC melting temperature curve to obtain the melting enthalpy, fit the energy absorption amount of the sample when reaching the molten state under different temperature rise rates to obtain the second function between the energy absorption amount and the temperature rise rate, calculate the apparent activation energy and the pre-exponential factor from the peak temperature of the endothermic peak, and determine the first function of the melting rate and the temperature rise rate;

[0032] Step S3. The gas during the heating of the sample is introduced into the absorption liquid, the residual amount of harmful gas is monitored, the range of the temperature rising rate is limited according to the influence of the residual amount of harmful gas on the temperature rising rate, and the residual amount of harmful gas is lower than the threshold value;

[0033] Step S4. The temperature rising rate when the ratio of the second function to the first function takes the minimum value is solved, the second function is substituted to obtain the minimum energy required for fly ash melting, the mixing ratio is calculated according to the heat value of the fuel, the fuel demand is obtained by multiplying the mixing ratio and the fly ash feed amount, and the fuel injection rate is adjusted through the PID controller, and the mixed fly ash and fuel are sent into the melting furnace;

[0034] Step S5. The temperature rising rate when the ratio of the second function to the first function takes the minimum value is taken as the optimal temperature rising rate to adjust the furnace temperature, the melting start temperature and the melting end temperature are determined according to the actual melting rate, and the nucleation solidification agent and the mineralization solidification agent are added into the furnace at the melting start temperature and the melting end temperature respectively.

[0035] Further, step S1 comprises:

[0036] Step S11. Collecting fly ash samples from electrostatic precipitators or bag filters of fly ash sources, grinding the fly ash to a particle size of less than 75 μm, mixing uniformly, drying at 105±5℃ for 24 hours to remove free water, and storing in a desiccator.

[0037] Step S12. The fly ash sample is divided into n groups, and a temperature rising rate is set for each group, so that the temperature rising rates have the same interval, and the temperature rising rate satisfies V=V0+i·Ve, wherein V is the temperature rising rate, V0 is the basic temperature rising rate, i is the group, and i∈{1,2,…,n}, and Ve is the interval of the temperature rising rate;

[0038] Step S13. Heating the sample in an inert atmosphere until the sample is in a molten state, observing the melting process by using a STA synchronous thermal analyzer combined with a HTM high temperature microscope, generating a DSC melting temperature curve, the starting point of the endothermic peak of the DSC curve is the melting start temperature, and the end point is the melting end temperature, and the inert atmosphere includes a nitrogen atmosphere and a rare gas atmosphere.

[0039] Further, step S2 comprises:

[0040] Step S21. Integrating the area of the endothermic peak of the DSC melting temperature curve to obtain the melting enthalpy, generating a function h(V) between the melting enthalpy and the temperature rising rate, using a function fitting tool to continuously fit h(V) to obtain a fitting function H(V), and establishing a relationship model between the energy absorption and the temperature rising rate:

[0041]

[0042] wherein Q(V) is a second function between energy absorption and temperature rising rate, T on and T end respectively represent the melting start temperature and the melting end temperature, C(T) is a specific heat capacity function of fly ash, which is obtained by sample test;

[0043] Step S22. Calculate the apparent activation energy and the pre-exponential factor from the peak temperature of the endothermic peak:

[0044]

[0045] wherein T p is the peak temperature of the endothermic peak at the temperature rising rate V, E is the apparent activation energy, R is the gas constant, and A is the pre-exponential factor;

[0046] Calculate the melting rate using the apparent activation energy and the pre-exponential factor, and output the first function P(V) of the melting rate and the temperature rising rate.

[0047] Further, step S3 comprises:

[0048] Step S31. Connect an absorption bottle to the STA tail gas outlet, the absorption bottle is filled with NaOH solution, after the melting is completed, analyze the residual amount of harmful gas in the absorption liquid using an ion chromatograph, the harmful gas is dioxin;

[0049] Step S32. Fit the function Y(V) between the residual amount of harmful gas and the temperature rising rate, let Y(V)≤Y0, solve the range of the independent variable V, as the definition domain of the first function and the second function, wherein Y0 is the threshold value of the residual amount of harmful gas.

[0050] Further, step S4 comprises:

[0051] Step S41. Solve the temperature rising rate V min when the ratio of the second function to the first function takes the minimum value, take Q(V min as the minimum energy required for melting, calculate the mixing ratio of fuel and fly ash, which satisfies K=Q(V min ) / u·μ, wherein K is the mixing ratio, u is the calorific value of the fuel, μ is the thermal efficiency of the furnace body, μ takes 0.7-0.8, the fuel includes: natural gas, coke and biofuel;

[0052] Step S42. Real-time obtain the fly ash feeding amount of the melting furnace feeding port, multiply the mixing ratio with the fly ash feeding amount to obtain the fuel demand amount, adjust the fuel injection rate through the PID controller, so that the fuel injection rate per unit time is equal to the fuel demand amount, and send the mixed fly ash and fuel into the melting furnace for combustion.

[0053] Further, step S5 comprises:

[0054] Step S51. Take the temperature rise rate at the minimum value of the ratio of the second function to the first function as the optimal temperature rise rate, adjust the furnace temperature according to the optimal temperature rise rate, and monitor the furnace temperature deviation in real time, and through the matching of the furnace speed or the conveying belt speed, ensure that the fly ash is completely melted at the outlet of the melting furnace;

[0055] Step S52. Substitute the optimal temperature rise rate into the first function to obtain the theoretical melting rate, adjust the theoretical melting rate according to the furnace temperature deviation, and obtain the melting start temperature and the melting end temperature according to the melting temperature curve corresponding to the melting rate;

[0056] At the melting start temperature and the melting end temperature respectively, add a crystal nucleus solidification agent and a mineralization solidification agent to the furnace, the crystal nucleus solidification agent is a silicon dioxide or aluminum oxide powder, and the mineralization solidification agent is a calcium fluoride or sodium carbonate crystal;

[0057] Step S53. Before the melted fly ash is discharged from the furnace, a sample is extracted from the furnace, the sample is detected for crystalline phase precipitation, and when the crystallinity is insufficient, the holding time before discharge is extended until the crystallinity meets the threshold value of the resource utilization of the melted fly ash.

[0058] Compared with the prior art, the beneficial effects achieved by the present application are:

[0059] The present application heats the fly ash sample at different temperature rise rates, establishes a melting energy absorption model, determines the energy absorption amount when the sample is melted at different temperatures, and calculates the kinetic parameters in the reaction process, which helps to understand the physical and chemical properties of the fly ash, optimize the resource utilization process, improve the energy utilization efficiency, and reduce the cost of secondary fly ash treatment.

[0060] The present application can determine the lower limit of fuel energy and the fuel mixing rate according to the functional relationship between energy absorption and temperature rise rate, mix the fly ash with fuel, send it into the melting furnace, calculate the melting rate according to the temperature rise rate when the energy absorption is lowest, determine the combustion time of the fly ash, realize the automatic adjustment of energy and the transparent management of melting furnace data, reduce the incomplete combustion phenomenon, reduce the fly ash residue, improve the combustion efficiency of fuel, and reduce the difficulty and cost of fly ash treatment.

[0061] The present application can predict the melting state of the fly ash in the melting furnace through the current temperature rise rate, add solidification agents to the melted fly ash taken out at different time points until the melted fly ash produced by the furnace is crystallized and solidified, evaluate the crystallization effect, adjust the length of time for the fly ash to be discharged, and make the melted fly ash meet the standard of building materials and cotton after cooling, so as to provide data support for resource utilization and improve the resource utilization quality of the melted fly ash. BRIEF DESCRIPTION OF DRAWINGS

[0062] The accompanying drawings are included to provide a further understanding of the application, and are incorporated in and constitute a part of the specification, illustrate embodiments of the application, and are used to explain the present application, but are not intended to limit the present application. In the drawings:

[0063] Figure 1 is a structural schematic diagram of a fly ash high-temperature heat energy storage data analysis system based on big data of the present application;

[0064] Figure 2 is a step schematic diagram of a fly ash high-temperature heat energy storage data analysis method based on big data of the present application. DETAILED DESCRIPTION

[0065] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0066] Please refer to Figure 1 The present application provides a technical solution: a fly ash high-temperature heat energy storage data analysis system based on big data, comprising: a sample processing module, an information modeling module, a melting combustion module, a time-sharing feeding module and a crystallization inspection module.

[0067] The sample processing module collects fly ash samples from electrostatic precipitators or bag-type dust collectors of fly ash sources, grinds, dries and fully mixes the fly ash, and then divides the samples into groups, each group being set with a different heating rate. The samples are heated in an inert atmosphere according to the heating rate until the samples are in a molten state. A simultaneous thermal analyzer is used to observe the melting process, and the sample heating time, the melting start temperature and the melting end temperature are recorded. Gases in the heating process are collected and introduced into an absorption liquid to analyze the residual amount of harmful gases.

[0068] The sample processing module comprises a pretreatment unit, a melting experiment unit and a gas analysis unit.

[0069] The pretreatment unit is used to collect fly ash samples, grind the fly ash to a particle size of less than 75 μm, and remove free water.

[0070] The melting experiment unit is used to heat the samples according to the set heating rate until the samples are molten, and the melting process is observed.

[0071] The gas analysis unit is used to connect a STA tail gas outlet with an absorption bottle containing NaOH solution to analyze the residual amount of harmful gases.

[0072] The information modeling module is used to obtain a DSC curve from a synchronous thermal analyzer, integrate an endothermic peak area to obtain a melting enthalpy, determine energy absorption of a sample when reaching a melting state under different temperature rise rates, calculate kinetic parameters in a reaction process according to a melting start temperature and a melting end temperature, determine a first function of a melting rate and a temperature rise rate and a second function between the energy absorption and the temperature rise rate, limit a function domain according to an influence of the temperature rise rate on a harmful gas residual amount, and make the harmful gas residual amount lower than a threshold value;

[0073] The information modeling module comprises an energy absorption unit and a dynamic fitting unit.

[0074] The energy absorption unit is used to establish a model of the energy absorption and the temperature rise rate, and calculate a function between the energy absorption and the temperature rise rate.

[0075] The dynamic fitting unit is used to fit the melting dynamic parameters according to a peak temperature of the DSC melting temperature curve.

[0076] The melting combustion module is used to solve the minimum energy required for fly ash melting according to a ratio of the second function to the first function, calculate a mixing ratio of fuel and fly ash according to a calorific value of the selected fuel, calculate fuel demand according to a fly ash feeding amount, adjust a fuel injection rate through a PID controller, send the mixed fly ash and fuel into a melting furnace for combustion, and monitor a furnace temperature deviation in real time and feed back to a monitoring platform.

[0077] The melting combustion module comprises a feeding nozzle unit, a melting furnace unit and a state feedback unit.

[0078] The feeding nozzle unit is used to calculate the minimum energy required for melting, and adjust a fuel mixing ratio, wherein the fuel comprises natural gas, coke and biofuel.

[0079] The melting furnace unit is used to provide a container for fly ash melting combustion, and perform in-furnace feeding control.

[0080] The state feedback unit is used to establish a fly ash melting management platform, and feed back a real-time deviation of a furnace temperature.

[0081] The time-sharing feeding module is used to calculate a temperature rise rate when a ratio of the second function to the first function takes a minimum value as an optimal temperature rise rate, substitute the optimal temperature rise rate into the first function to obtain a theoretical melting rate, adjust the theoretical melting rate according to a feedback furnace temperature deviation until complete melting.

[0082] The time-sharing feeding module comprises a constant-temperature solidification unit and a sintering discharging unit.

[0083] The constant-temperature solidification unit is used to calculate the optimal temperature rise rate, and adjust a furnace temperature according to the optimal temperature rise rate.

[0084] The sintering furnace outlet unit is used to ensure that the fly ash is completely melted at the outlet of the melting furnace by matching the furnace rotation speed or the conveying belt speed.

[0085] The crystallization test module is used to add nucleation solidification agents and mineralization solidification agents into the furnace at the melting start temperature and the melting end temperature respectively, and to evaluate the crystallization effect after the furnace is discharged. If the crystallinity is less than a threshold value, the holding time before the furnace is discharged is extended.

[0086] The crystallization test module includes a solidification test unit and a furnace storage cooling unit.

[0087] The solidification test unit is used to establish a temperature field finite element model based on multi-point thermocouple data in the furnace to determine the feeding temperature.

[0088] The furnace storage cooling unit is used to detect precipitated crystal phases and extend the holding time before the furnace is discharged when the crystallinity is insufficient.

[0089] As shown in Figure 2 A fly ash high-temperature thermal energy storage data analysis method based on big data includes the following steps:

[0090] Step S1. Collect fly ash samples from the dust collector, group the samples after pretreatment, set different heating rates for each group, heat the samples at the set heating rate in an inert atmosphere until the samples are in a molten state, observe the melting process using a simultaneous thermal analyzer, and generate a DSC melting temperature curve.

[0091] Step S1 includes:

[0092] Step S11. Collect fly ash samples from electrostatic precipitators or bag filters at the fly ash source, grind the fly ash to a particle size of less than 75 μm, mix uniformly, dry at 105±5℃ for 24 hours to remove free water, and store in a desiccator.

[0093] Step S12. Divide the fly ash samples into n groups, set a heating rate for each group, and make the heating rate intervals the same, so that the heating rate satisfies V=V0+i·Ve, where V is the heating rate, V0 is the basic heating rate, i is the group, and i∈{1,2,…,n}, Ve is the interval of the heating rate.

[0094] Step S13. Heat the samples in an inert atmosphere until the samples are in a molten state, observe the melting process using an STA simultaneous thermal analyzer combined with an HTM high-temperature microscope, generate a DSC melting temperature curve, the starting point of the DSC curve endothermic peak is the melting start temperature, and the end point is the melting end temperature, and the inert atmosphere includes a nitrogen atmosphere and a noble gas atmosphere.

[0095] Step S2. Integrate the endothermic peak area of the DSC melting temperature curve to obtain the melting enthalpy, fit the energy absorption amount of the sample when reaching the melting state at different temperature rise rates to obtain the second function between the energy absorption amount and the temperature rise rate, calculate the apparent activation energy and the pre-exponential factor from the peak temperature of the endothermic peak, and determine the first function of the melting rate and the temperature rise rate;

[0096] Step S2 includes:

[0097] Step S21. Integrate the endothermic peak area of the DSC melting temperature curve to obtain the melting enthalpy, generate the function h(V) between the melting enthalpy and the temperature rise rate, and use the function fitting tool to continuously fit h(V) to obtain the fitting function H(V), and establish the relationship model of the energy absorption amount and the temperature rise rate:

[0098]

[0099] Wherein, Q(V) is the second function between the energy absorption amount and the temperature rise rate, T on and T end respectively represent the melting start temperature and the melting end temperature, and C(T) is the specific heat capacity function of the fly ash, which is obtained by sample testing;

[0100] Step S22. Calculate the apparent activation energy and the pre-exponential factor from the peak temperature of the endothermic peak:

[0101]

[0102] Wherein, T p is the peak temperature of the endothermic peak at the temperature rise rate V, E is the apparent activation energy, R is the gas constant, and A is the pre-exponential factor;

[0103] Calculate the melting rate using the apparent activation energy and the pre-exponential factor, and output the first function P(V) of the melting rate and the temperature rise rate.

[0104] Step S3. During the heating process of the sample, the gas is introduced into the absorption liquid, and the residual amount of harmful gas is monitored, according to the influence of the temperature rise rate on the residual amount of harmful gas, the range of the temperature rise rate is limited, so that the residual amount of harmful gas is lower than the threshold value;

[0105] Step S3 includes:

[0106] Step S31. Connect the absorption bottle to the STA tail gas outlet, the absorption bottle is filled with NaOH solution, after the melting is completed, the residual amount of harmful gas in the absorption liquid is analyzed by ion chromatograph, and the harmful gas is dioxin;

[0107] Step S32. Fit the function Y(V) between the residual amount of harmful gas and the rate of temperature rise, let Y(V)≤Y0, solve for the range of the independent variable V, and use it as the domain of the first function and the second function, where Y0 is the threshold of the residual amount of harmful gas.

[0108] Step S4. Solve for the temperature rise rate when the ratio of the second function to the first function is minimized. Substitute the result into the second function to obtain the minimum energy required for fly ash melting. Calculate the mixing ratio based on the calorific value of the fuel. Multiply the mixing ratio by the fly ash feed rate to obtain the fuel requirement. Adjust the fuel injection rate using a PID controller to mix the fly ash and fuel before feeding them into the melting furnace.

[0109] Step S4 includes:

[0110] Step S41. Solve for the temperature rise rate V that is minimized when the ratio of the second function to the first function is minimized. min , Q(V) min As the minimum energy required for melting, calculate the mixing ratio of fuel and fly ash, satisfying K=Q(V min K / u·μ, where K is the mixing ratio, u is the calorific value of the fuel, and μ is the furnace thermal efficiency, μ is 0.7-0.8, and the fuel includes: natural gas, coke and biofuel;

[0111] Step S42. Obtain the fly ash feed rate at the inlet of the melting furnace in real time, multiply the mixing ratio by the fly ash feed rate to obtain the fuel demand, adjust the fuel injection rate through the PID controller to make the fuel injection rate per unit time equal to the fuel demand, and then feed the fly ash and fuel mixture into the melting furnace for combustion.

[0112] Step S5. The temperature rise rate at which the ratio of the second function to the first function is minimized is used as the optimal temperature rise rate to adjust the furnace temperature. The melting start temperature and melting end temperature are determined according to the actual melting rate. At the melting start temperature and melting end temperature, crystal nucleation solidifier and mineralization solidifier are added to the furnace respectively.

[0113] Step S5 includes:

[0114] Step S51. Take the temperature rise rate at which the ratio of the second function to the first function is at its minimum as the optimal temperature rise rate, adjust the furnace temperature according to the optimal temperature rise rate, and monitor the furnace temperature deviation in real time. Match the furnace rotation speed or conveyor belt speed to ensure that the fly ash is completely melted at the outlet of the melting furnace.

[0115] Step S52. Substitute the optimal temperature rise rate into the first function to obtain the theoretical melting rate. Adjust the theoretical melting rate according to the furnace temperature deviation. Obtain the melting start temperature and melting end temperature according to the melting temperature curve corresponding to the melting rate.

[0116] A nucleation solidification agent, which is a powder of silica or alumina, and a mineralization solidification agent, which is a crystal of calcium fluoride or sodium carbonate, are added into the furnace at the melting start temperature and the melting end temperature, respectively;

[0117] Step S53. A sample is extracted from the furnace before the molten fly ash is discharged, and the sample is detected for precipitated crystal phase. When the crystallinity is insufficient, the holding time before discharge is extended until the crystallinity meets the threshold value for the resource utilization of the molten fly ash.

[0118] Embodiment: After the fly ash is sampled, five groups of different temperature rise rates of 5℃ / min, 10℃ / min, 15℃ / min, 20℃ / min and 25℃ / min are set, and a test is performed at a base temperature of 1000℃. The energy absorption of the fly ash is 2000KJ, 2200KJ, 2400KJ, 2600KJ and 2800KJ, respectively, and the melting time is 1000min, 400min, 180min, 70min and 30min, respectively. It is calculated that the optimal temperature rise rate is 20℃ / min, and the furnace temperature is adjusted according to the optimal temperature rise rate.

[0119] It should be noted that the relational terms herein such as first and second and the like are used only to differentiate one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between or among the entities or operations. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0120] Finally, it should be noted that the above-described embodiments are merely exemplary of the application and should not be used to limit the present application and that, for persons having ordinary skill in the art, modifications can be made to the technical solutions recorded in the foregoing embodiments, or equivalent replacements can be made to some of the technical features. Any modifications, equivalent replacements, improvements, and the like made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A data analysis method for high-temperature thermal energy storage of fly ash based on big data, characterized in that, The method includes the following steps: Step S1. Collect fly ash samples from the dust collector, pre-treat the samples and group them, set different heating rates for each group, heat the samples in an inert atmosphere according to the set heating rates until the samples are in a molten state, observe the melting process using a synchronous thermal analyzer and generate DSC melting temperature curves. Step S2. Integrate the endothermic peak area of ​​the DSC melting temperature curve to obtain the melting enthalpy, fit the energy absorption when the sample reaches the melting state at different temperature rise rates, obtain the second function between energy absorption and temperature rise rate, calculate the apparent activation energy and pre-exponential factor from the peak temperature of the endothermic peak, and determine the first function between melting rate and temperature rise rate. Step S3. Pass the gas generated during the sample heating process into the absorption liquid, monitor the residual amount of harmful gas, and limit the range of the temperature rise rate based on the effect of the temperature rise rate on the residual amount of harmful gas so that the residual amount of harmful gas is below the threshold. Step S4. Solve for the temperature rise rate when the ratio of the second function to the first function is minimized. Substitute the result into the second function to obtain the minimum energy required for fly ash melting. Calculate the mixing ratio based on the calorific value of the fuel. Multiply the mixing ratio by the fly ash feed rate to obtain the fuel requirement. Adjust the fuel injection rate using a PID controller to mix the fly ash and fuel before feeding them into the melting furnace. Step S5. The temperature rise rate at which the ratio of the second function to the first function is minimized is used as the optimal temperature rise rate to adjust the furnace temperature. The melting start temperature and melting end temperature are determined according to the actual melting rate. At the melting start temperature and melting end temperature, crystal nucleation solidifier and mineralization solidifier are added to the furnace respectively.

2. The method for analyzing fly ash high-temperature thermal energy storage data based on big data according to claim 1, characterized in that: Step S1 includes: Step S11. Collect fly ash samples from the electrostatic precipitator or bag filter from which the fly ash originates, grind the fly ash to a particle size of less than 75 μm, mix evenly, dry at 105±5℃ for 24 hours to remove free moisture, and store in a desiccator. Step S12. Divide the fly ash samples into n groups, and set a heating rate for each group so that the intervals of the heating rates are the same, and the heating rates satisfy: V=V0+i·Ve, where V is the heating rate, V0 is the base heating rate, i is the group and i∈{1,2,…,n}, and Ve is the interval of the heating rates. Step S13. Heat the sample under an inert atmosphere until the sample is in a molten state. Use a STA simultaneous thermal analyzer and an HTM high-temperature microscope to observe the melting process and generate a DSC melting temperature curve. The starting point of the endothermic peak of the DSC curve is the melting start temperature, and the ending point is the melting termination temperature. The inert atmosphere includes a nitrogen atmosphere and a rare gas atmosphere.

3. The method for analyzing fly ash high-temperature thermal energy storage data based on big data according to claim 2, characterized in that: Step S2 includes: Step S21. Integrate the endothermic peak area of ​​the DSC melting temperature curve to obtain the enthalpy of fusion, generate the function h(V) between the enthalpy of fusion and the temperature rise rate, and use a function fitting tool to continuously fit h(V) to obtain the fitting function H(V), thus establishing a model of the relationship between energy absorption and temperature rise rate: Where Q(V) is the second function relating energy absorption and the rate of temperature rise, T on and T end These represent the melting start temperature and melting end temperature, respectively. C(T) is the specific heat capacity function of fly ash, obtained from sample testing. Step S22. Calculate the apparent activation energy and pre-exponential factor from the peak temperature of the endothermic peak: Among them, T p Let V be the peak temperature of the endothermic peak at the rate of temperature rise V, E be the apparent activation energy, R be the gas constant, and A be the pre-exponential factor. The melting rate is calculated using the apparent activation energy and the pre-exponential factor, and the first function P(V) of the melting rate versus the temperature rise rate is output.

4. The data analysis method for high-temperature thermal energy storage of fly ash based on big data according to claim 3, characterized in that: Step S3 includes: Step S31. Connect an absorption bottle to the STA tail gas outlet. The absorption bottle contains NaOH solution. After melting, use an ion chromatograph to analyze the residual amount of harmful gas in the absorption liquid. The harmful gas is dioxin. Step S32. Fit the function Y(V) between the residual amount of harmful gas and the rate of temperature rise, let Y(V)≤Y0, solve for the range of the independent variable V, and use it as the domain of the first function and the second function, where Y0 is the threshold of the residual amount of harmful gas; Step S4 includes: Step S41. Solve for the temperature rise rate V that is minimized when the ratio of the second function to the first function is minimized. min Q(V) min As the minimum energy required for melting, calculate the mixing ratio of fuel and fly ash, satisfying K=Q(V min K / u·μ, where K is the mixing ratio, u is the calorific value of the fuel, and μ is the furnace thermal efficiency, μ is 0.7-0.8, and the fuel includes: natural gas, coke and biofuel; Step S42. Obtain the fly ash feed rate at the inlet of the melting furnace in real time, multiply the mixing ratio by the fly ash feed rate to obtain the fuel demand, adjust the fuel injection rate through the PID controller to make the fuel injection rate per unit time equal to the fuel demand, and then feed the fly ash and fuel mixture into the melting furnace for combustion.

5. The data analysis method for high-temperature thermal energy storage of fly ash based on big data according to claim 4, characterized in that: Step S5 includes: Step S51. Take the temperature rise rate at which the ratio of the second function to the first function is at its minimum as the optimal temperature rise rate, adjust the furnace temperature according to the optimal temperature rise rate, and monitor the furnace temperature deviation in real time. Match the furnace rotation speed or conveyor belt speed to ensure that the fly ash is completely melted at the outlet of the melting furnace. Step S52. Substitute the optimal temperature rise rate into the first function to obtain the theoretical melting rate. Adjust the theoretical melting rate according to the furnace temperature deviation. Obtain the melting start temperature and melting end temperature according to the melting temperature curve corresponding to the melting rate. At the melting start temperature and melting end temperature, a nucleation solidifying agent and a mineralization solidifying agent are added to the furnace, respectively. The nucleation solidifying agent is silicon dioxide or alumina powder, and the mineralization solidifying agent is calcium fluoride or sodium carbonate crystals. Step S53. Before the molten fly ash is discharged from the furnace, a sample is extracted from the furnace and the crystalline phase precipitated in the sample is detected. If the crystallinity is insufficient, the holding time before discharge is extended until the crystallinity meets the threshold for the molten fly ash to be utilized as a resource.

6. A data analysis system for high-temperature thermal energy storage of fly ash based on big data, characterized in that, The system includes the following modules: sample processing module, information modeling module, melting and combustion module, time-sharing feeding module, and crystallization testing module; The sample processing module collects fly ash samples from the electrostatic precipitator or bag filter from which the fly ash originates. After grinding, drying, and thoroughly mixing the fly ash, the samples are grouped, with each group set with a different heating rate. The samples are heated at the heating rate under an inert atmosphere until they are in a molten state. The melting process is observed using a synchronous thermal analyzer, and the sample heating time, melting start temperature, and melting end temperature are recorded. At the same time, the gas collected during the heating process is passed into the absorption liquid to analyze the residual amount of harmful gases. The information modeling module is used to acquire DSC curves from the synchronous thermal analyzer, integrate the endothermic peak area to obtain the melting enthalpy, determine the energy absorption when the sample reaches the melting state at different temperature rise rates, and calculate the kinetic parameters of the reaction process based on the melting start temperature and melting end temperature. It determines the first function between melting rate and temperature rise rate, the second function between energy absorption and temperature rise rate, and restricts the domain of the function based on the influence of temperature rise rate on the residual amount of harmful gases, so that the residual amount of harmful gases is lower than the threshold. The melting and combustion module is used to solve the minimum energy required to melt fly ash based on the ratio of the second function to the first function, calculate the mixing ratio of fuel and fly ash based on the calorific value of the selected fuel, calculate the fuel demand according to the fly ash feed rate, adjust the fuel injection rate through the PID controller, mix fly ash and fuel and send them into the melting furnace for combustion, and monitor the furnace temperature deviation in real time and feed it back to the monitoring platform. The time-sharing feeding module is used to calculate the temperature rise rate when the ratio of the second function to the first function is minimized, which is taken as the optimal temperature rise rate. The optimal temperature rise rate is substituted into the first function to obtain the theoretical melting rate. The theoretical melting rate is adjusted according to the feedback furnace temperature deviation until complete melting. The crystallization inspection module is used to add nucleation solidifier and mineralization solidifier into the furnace at the melting start temperature and melting end temperature, respectively, and evaluate the crystallization effect after exiting the furnace. If the crystallinity is less than the threshold, the holding time before exiting the furnace is extended.

7. The fly ash high-temperature thermal energy storage data analysis system based on big data according to claim 6, characterized in that: The sample processing module includes: a pretreatment unit, a melting experiment unit, and a gas desorption unit; The pretreatment unit is used to collect fly ash samples, grind the fly ash to a particle size of less than 75 μm, and remove free moisture; The melting experiment unit is used to heat the sample at a set heating rate until the sample melts, and to observe the melting process. The gas analysis unit is used to connect an absorption bottle containing NaOH solution to the STA tail gas outlet to analyze the residual amount of harmful gases.

8. The fly ash high-temperature thermal energy storage data analysis system based on big data according to claim 7, characterized in that: The information modeling module includes: an energy absorption unit and a dynamic fitting unit; The energy absorption unit is used to establish a model of the relationship between energy absorption and temperature rise rate, and to calculate the function between energy absorption and temperature rise rate. The dynamic fitting unit is used to fit the melting kinetic parameters according to the peak temperature of the DSC melting temperature curve.

9. A data analysis system for high-temperature thermal energy storage of fly ash based on big data as described in claim 8, characterized in that: The melting and combustion module includes: a feed nozzle unit, a melting furnace unit, and a status feedback unit; The feed nozzle unit is used to calculate the minimum energy required for melting and adjust the fuel mixing ratio, including natural gas, coke and biofuel; The melting furnace unit is used to provide a container for the melting and combustion of fly ash and to control the in-furnace feeding. The status feedback unit is used to establish a fly ash melting management platform and provide feedback on the real-time deviation of the furnace temperature.

10. A data analysis system for high-temperature thermal energy storage of fly ash based on big data as described in claim 9, characterized in that: The time-sharing feeding module includes: a constant-temperature curing unit and a sintering and unloading unit; The constant-temperature curing unit is used to calculate the optimal temperature rise rate and adjust the furnace temperature according to the optimal temperature rise rate. The sintering furnace exit unit is used to ensure that fly ash is completely melted at the outlet of the melting furnace by matching the furnace rotation speed or the conveyor belt speed. The crystallization testing module includes: a solidification testing unit and a furnace cooling unit; The solidification test unit is used to establish a finite element model of the temperature field based on multi-point thermocouple data in the furnace, and to determine the feeding temperature. The furnace cooling unit is used to detect the precipitated crystalline phase, and if the crystallinity is insufficient, the holding time before unloading from the furnace is extended.

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