Particle size control and resource optimization method of well water evaporated crystalline salt

Abstract

The application discloses a method for controlling particle size and optimizing resources of well water evaporated crystalline salt, relates to the technical field of resource optimization, and predicts the concentration change trend of sodium chloride in brine at a treatment end, judges whether the concentration of sodium chloride in the brine exceeds a supersaturation point in a short time, generates a warning signal and automatically detects whether a by-product salt is precipitated from a mother liquor if the concentration of sodium chloride in the brine exceeds the supersaturation point, analyzes the current change trend of the by-product salt concentration, combines the concentration change trend prediction result of the sodium chloride in the brine with an equipment operation state to simulate the change of the by-product salt concentration, and generates an optimization strategy for salt crystal growth based on the brine sodium chloride concentration change trend prediction and the by-product salt concentration change simulation. The optimization method closely couples the crystal growth optimization strategy with the sodium chloride concentration trend and the by-product salt behavior, so that parameters such as crystal nucleus density, growth rate and residence time can be adaptively adjusted according to the system state, and the uniformity of particle size distribution and the controllability of crystal morphology are both improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of resource optimization, in particular to a particle size control and resource optimization method of well water evaporation crystallized salt. BACKGROUND

[0002] In the development of salt lake resources, the traditional open-air salt drying mode faces many challenges, such as large land occupation, long production cycle, and easy influence by climate, etc. With the progress of technology, more and more salt lake enterprises use the way of extracting resources from underground brine (i.e. well water) for industrial production. Well water, due to its high salt concentration, stable composition and controllable extraction method, has become a high-quality resource.

[0003] The prior art has the following defects:

[0004] 1. There is generally a lack of modeling of the trend of mother liquor by-product salt behavior and multi-factor correlation simulation, resulting in delayed discharge decision, high resource loss rate, and difficulty in efficient recovery of by-product salt resources;

[0005] 2. The existing evaporation crystallization process generally relies on fixed parameter setting and manual experience judgment, lacks real-time perception and response mechanism for dynamic environmental factors and equipment state, and in the case of sudden change of evaporation rate, sodium chloride in brine is easily oversaturated in a short time, forming a large number of uncontrollable crystal nuclei, resulting in uneven crystal particle size, serious agglomeration and difficulty in classification;

[0006] 3. At the same time, the by-product salt (especially magnesium salt) lacks effective prediction and separation management mechanism in the concentration process of the mother liquor, which is easy to co-crystallize with the main salt, seriously affecting the purity of sodium chloride and reducing the added value of the product.

[0007] Therefore, the present application proposes a particle size control and resource optimization method of well water evaporation crystallized salt, which closely couples the crystal growth optimization strategy with the sodium chloride concentration trend and the behavior of by-product salt, so that the crystal nucleus density, growth rate and residence time, etc. Parameters can be self-adaptively adjusted according to the system state, realizing the double improvement of particle size distribution uniformity and controllability of crystal morphology. SUMMARY

[0008] The purpose of the present application is to provide a particle size control and resource optimization method of well water evaporation crystallized salt to solve the problems in the background art.

[0009] In order to achieve the above purpose, the present application provides the following technical scheme: a particle size control and resource optimization method of well water evaporation crystallized salt, the optimization method comprising the following steps:

[0010] The acquisition end collects current environmental data during the evaporation concentration stage of well water, and the processing end predicts the trend of change of sodium chloride concentration in brine and judges whether the sodium chloride concentration in brine exceeds the supersaturation point in a short time;

[0011] If the value exceeds, a warning signal is generated and the automatic detection of the mother liquor whether the secondary salt is precipitated;

[0012] If the secondary salt is precipitated, the current trend of the secondary salt concentration is analyzed, the prediction result of the brine sodium chloride concentration trend is combined with the equipment operation state to simulate the secondary salt concentration change, and the corresponding management strategy is generated according to the simulation result of the secondary salt concentration change;

[0013] Based on the brine sodium chloride concentration trend prediction and the secondary salt concentration change simulation, an optimization strategy for salt crystal growth is generated.

[0014] In a preferred embodiment, based on the brine sodium chloride concentration trend prediction and the secondary salt concentration change simulation, an optimization strategy for salt crystal growth is generated, including the following steps:

[0015] Based on the brine sodium chloride concentration trend prediction and the secondary salt concentration change simulation, the salt crystal growth process is optimized and controlled;

[0016] Combined with the prediction of the secondary salt concentration rising rate and the concentration driving coefficient κ, the growth strategy parameters are corrected, including the crystal nucleus density, the stirring frequency and the crystal residence time.

[0017] In a preferred embodiment, the correction parameters include the crystal nucleus density, the stirring frequency and the crystal residence time, and the correction algorithm is: Wherein, is the corrected crystal nucleus density, is the reference crystal nucleus density, is the influence factor function, is the corrected stirring frequency, is the reference stirring frequency, is the predicted secondary salt concentration rising rate, is the corrected crystal residence time, is the reference residence time;

[0018] The function expression of the influence factor function is:

[0019] Wherein, C NaCl (t+Δt) represents the predicted sodium chloride concentration at time t+Δt, represents the predicted secondary salt concentration at future time t+Δt, C sat (T w ) is the solubility limit value at the current temperature, is the secondary salt change warning threshold, α is the amplification coefficient of the primary salt concentration on the crystal nucleus density improvement, and β is the sensitive coefficient of the secondary salt concentration on the crystal nucleus density inhibition.

[0020] In a preferred embodiment, the automatic detection of the precipitation of the secondary salt in the mother liquor comprises the following steps:

[0021] When it is determined that the concentration of sodium chloride in the brine exceeds the supersaturation point during the detection period, the process is automatically switched to the secondary salt detection process in the mother liquor to detect whether the secondary salt that precipitates first has reached the solubility limit. The judgment logic is as follows: if The precipitation of the secondary salt in the mother liquor is detected, wherein C 副盐 (t) represents the current concentration of the secondary salt, represents the solubility limit value of the corresponding secondary salt under the current temperature T(t) and the current pH condition pH(t).

[0022] In a preferred embodiment, after analyzing the current trend of the secondary salt concentration, the secondary salt concentration change is simulated by combining the prediction result of the sodium chloride concentration trend in the brine and the equipment operating state, which comprises the following steps:

[0023] When the precipitation of the secondary salt in the mother liquor is detected, the online ion analyzer is used to obtain the concentration of the secondary salt at the current time t, and the change rate of the secondary salt concentration is calculated.

[0024] The concentration driving coefficient is calculated according to the predicted sodium chloride concentration at time t+Δt, and a dynamic simulation model of the future concentration of the secondary salt is established, and the model expression is as follows:

[0025] wherein, represents the predicted secondary salt concentration at future time t+Δt, η represents the concentration trend weight factor, BC Mg is the change rate of the secondary salt concentration, κ is the concentration driving coefficient, Δt is the time interval, γ(t) is the pool liquid replacement frequency at the current time, C Mg (t) is the secondary salt concentration at the current time t.

[0026] In a preferred embodiment, the change rate of the secondary salt concentration is calculated, and the expression is as follows:

[0027] wherein, BC Mg is the change rate of the secondary salt concentration, Δt is the time interval, C Mg (t) is the secondary salt concentration at the current time t, C Mg (t-Δt) is the secondary salt concentration at the previous time t-Δt.

[0028] The concentration driving coefficient is calculated according to the predicted sodium chloride concentration at time t+Δt, and the expression is as follows: wherein, κ is the concentration driving coefficient, C NaCl (t+Δt) is the predicted sodium chloride concentration at time t+Δt, C NaCl (t) is the current sodium chloride concentration at time t.

[0029] In a preferred embodiment, the corresponding management strategy is generated according to the simulation results of the change of the by-product salt concentration, and the management strategy comprises the following steps:

[0030] If , is the by-product salt change warning threshold, represents the predicted by-product salt concentration at a future time t+Δt, the sub-strategy of activating the flow is activated, and the self-adaptive correction of the drainage rate is carried out in combination with the predicted by-product salt concentration rising rate, and the expression is: wherein Q adj is the adjusted drainage rate, Q0 is the initial drainage rate, λ is the by-product salt concentration growth response coefficient, is the predicted by-product salt concentration rising rate, and C Mg (t) is the by-product salt concentration at the current time t, and Δt is the time interval.

[0031] In a preferred embodiment, the acquisition end collects the current environmental data in the well water evaporation and concentration stage, and the processing end predicts the change trend of the sodium chloride concentration of the brine, comprising the following steps:

[0032] During the evaporation and crystallization process of the well water, the acquisition end obtains the environmental parameters related to the evaporation rate in real time, and the environmental parameters include the external environmental temperature, the relative humidity, the wind speed, the light intensity, and the liquid level temperature, the brine volume, the current sodium chloride concentration, the pH value and the conductivity inside the evaporation pond;

[0033] The processing end calculates the current evaporation water amount E of the brine based on the environmental parameters and the liquid state information, estimates the water loss per unit time, combines the initial brine volume V b , and obtains the predicted sodium chloride concentration of the brine at time t+Δt, which is used to predict the change trend of the sodium chloride concentration of the brine.

[0034] In a preferred embodiment, whether the sodium chloride concentration of the brine exceeds the supersaturation point in the detection time period is judged, comprising the following steps:

[0035] The processing end obtains the predicted sodium chloride concentration of the brine at time t+Δt, and when the predicted sodium chloride concentration C NaCl (t+Δt) at time t+Δt is higher than the solubility limit value at the current temperature, it is judged that the sodium chloride concentration of the brine exceeds the supersaturation point in the detection time period t+Δt: C NaCl (t+Δt)>C sat (T w ) exceeds the supersaturation point, wherein C sat (T w ) is the solubility limit value at the current temperature.

[0036] In a preferred embodiment, the formula for calculating the current brine evaporation water amount E is:

[0037] E=k·(P s (T w )-P a (T a ,H))·A·f(v), wherein E represents the brine evaporation water amount per unit time, k represents the evaporation coefficient, P s (T w ) represents the saturated water vapor pressure at the liquid surface temperature, P a (T a ,H) represents the actual water vapor pressure in the air, and P a (T a ,H)=H·P s (T a ), H is the relative humidity, P s (T a ) represents the saturated water vapor pressure at the external environment temperature, A represents the evaporation surface area, and f(v) represents the wind speed influence factor.

[0038] The predicted sodium chloride concentration of the brine at time t+Δt is obtained, and the expression is:

[0039] wherein C NaCl (t+Δt) represents the predicted sodium chloride concentration at time t+Δt, V b is the initial brine volume, Δt is the time interval, and m NaCl is the total mass of sodium chloride in the brine.

[0040] In the above technical solution, the present application provides the following technical effects and advantages:

[0041] 1. The present application collects the current environmental data at the well water evaporation concentration stage by the collection end, predicts the sodium chloride concentration trend of the brine by the processing end, judges whether the sodium chloride concentration of the brine exceeds the supersaturation point in a short time, generates a warning signal and automatically detects whether the by-product salt is precipitated from the mother liquor if it exceeds, analyzes the current change trend of the by-product salt concentration, simulates the by-product salt concentration change in combination with the sodium chloride concentration trend prediction result and the equipment operation state, generates the corresponding management strategy according to the simulation result of the by-product salt concentration change, and generates the optimization strategy for the salt crystal growth based on the sodium chloride concentration trend prediction and the by-product salt concentration change simulation. The optimization method closely couples the crystal growth optimization strategy with the sodium chloride concentration trend and the by-product salt behavior, so that the crystal nucleus density, growth rate and residence time and other parameters can be adaptively adjusted according to the system state, and the uniformity of particle size distribution and the controllability of crystal morphology are improved.

[0042] 2、The application realizes a multi-source data driven dynamic prediction and control mechanism by introducing environmental data acquisition, salt concentration change trend prediction and by-product salt precipitation trend detection modules in the evaporation and concentration stage. By judging whether the sodium chloride is about to exceed the supersaturation point, the system can issue an early warning signal in advance, link the by-product salt precipitation detection process, identify the abnormality of the magnesium ion concentration in the mother liquor, and combine the equipment operation state to numerically simulate and trend deduce the by-product salt concentration change. This mechanism significantly enhances the feedforward control ability of the by-product salt precipitation behavior, and drives the dynamic management strategies including by-product salt precipitation threshold reduction, small flow drainage activation, mother liquor component rebalancing and the like with simulation results, effectively avoiding the risk of by-product salt pollution of the main crystal. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0044] Figure 1 The flowchart of the optimization method of the present application.

[0045] Figure 2 The timing diagram of the optimization method of the present application.

[0046] Figure 3 The mind map of the optimization method of the present application.

[0047] Figure 4 The system architecture diagram of the optimization system of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0049] Embodiment 1: Please refer to Figures 1-3 The well water evaporation crystallization salt particle size control and resource optimization method described in this embodiment, the optimization method comprises the following steps:

[0050] The collection end collects current environmental data in the well water evaporation concentration stage, the processing end predicts the change trend of the sodium chloride concentration of the brine, judges whether the sodium chloride concentration of the brine exceeds the supersaturation point in a short time, if it exceeds, generates a warning signal and automatically detects whether the by-product salt (such as magnesium sulfate) in the mother liquor is precipitated, if it is precipitated, analyzes the current change trend of the by-product salt concentration, combines the prediction result of the change trend of the sodium chloride concentration of the brine with the simulation of the by-product salt concentration change based on the equipment operation state, generates the corresponding management strategy according to the simulation result of the by-product salt concentration change, and the management strategy includes: if it is found that the magnesium ion concentration in the mother liquor abnormally rises and exceeds the normal crystallization range, a small flow of liquid is discharged to prevent the by-product salt from polluting the main crystal, and an optimization strategy for salt crystal growth is generated based on the prediction of the change trend of the sodium chloride concentration of the brine and the simulation of the by-product salt concentration change.

[0051] The collection end collects current environmental data in the well water evaporation concentration stage, the processing end predicts the change trend of the sodium chloride concentration of the brine, judges whether the sodium chloride concentration of the brine exceeds the supersaturation point in a short time, if it exceeds, generates a warning signal and automatically detects whether the by-product salt in the mother liquor is precipitated, if it is precipitated, analyzes the current change trend of the by-product salt concentration, combines the prediction result of the change trend of the sodium chloride concentration of the brine with the simulation of the by-product salt concentration change based on the equipment operation state, generates the corresponding management strategy according to the simulation result of the by-product salt concentration change, and the management strategy includes: if it is found that the magnesium ion concentration in the mother liquor abnormally rises and exceeds the normal crystallization range, a small flow of liquid is discharged to prevent the by-product salt from polluting the main crystal, and an optimization strategy for salt crystal growth is generated based on the prediction of the change trend of the sodium chloride concentration of the brine and the simulation of the by-product salt concentration change. The optimization method closely couples the crystal growth optimization strategy with the sodium chloride concentration trend and the by-product salt behavior, so that the parameters such as crystal nucleus density, growth rate and residence time can be adaptively adjusted according to the system state, and the uniformity of particle size distribution and the controllability of crystal morphology are realized.

[0052] The collection end collects current environmental data in the well water evaporation concentration stage, the processing end predicts the change trend of the sodium chloride concentration of the brine, judges whether the sodium chloride concentration of the brine exceeds the supersaturation point in a short time, if it exceeds, generates a warning signal and automatically detects whether the by-product salt in the mother liquor is precipitated, if it is precipitated, analyzes the current change trend of the by-product salt concentration, combines the prediction result of the change trend of the sodium chloride concentration of the brine with the simulation of the by-product salt concentration change based on the equipment operation state, generates the corresponding management strategy according to the simulation result of the by-product salt concentration change, and the management strategy includes: if it is found that the magnesium ion concentration in the mother liquor abnormally rises and exceeds the normal crystallization range, a small flow of liquid is discharged to prevent the by-product salt from polluting the main crystal, and an optimization strategy for salt crystal growth is generated based on the prediction of the change trend of the sodium chloride concentration of the brine and the simulation of the by-product salt concentration change. The optimization method closely couples the crystal growth optimization strategy with the sodium chloride concentration trend and the by-product salt behavior, so that the parameters such as crystal nucleus density, growth rate and residence time can be adaptively adjusted according to the system state, and the uniformity of particle size distribution and the controllability of crystal morphology are realized.

[0053] Referring to Figure 4 As shown, the optimization system includes a sodium chloride concentration prediction module, a secondary salt concentration simulation module, and a particle size control and optimization module:

[0054] The sodium chloride concentration prediction module: collect current environmental data during the well water evaporation and concentration stage, predict the change trend of the brine sodium chloride concentration, judge whether the brine sodium chloride concentration exceeds the supersaturation point in a short time, and send the judgment result to the secondary salt concentration simulation module. The brine sodium chloride concentration change trend prediction result is sent to the particle size control and optimization module.

[0055] The secondary salt concentration simulation module: if the brine sodium chloride concentration exceeds the supersaturation point in a short time, a warning signal is generated and the precipitation of secondary salt (such as magnesium sulfate) in the mother liquor is automatically detected. If precipitation occurs, the current change trend of the secondary salt concentration is analyzed, the brine sodium chloride concentration change trend prediction result is combined with the equipment operation state to simulate the secondary salt concentration change, and the corresponding management strategy is generated according to the secondary salt concentration change simulation result. The management strategy includes: if it is found that the magnesium ion concentration in the mother liquor abnormally increases and exceeds the normal crystallization range, start the small flow liquid discharge to prevent the secondary salt from polluting the main crystal. The simulation result is sent to the particle size control and optimization module.

[0056] The particle size control and optimization module: based on the brine sodium chloride concentration change trend prediction and the secondary salt concentration change simulation, an optimization strategy for salt crystal growth is generated.

[0057] Example 2: The collection end collects current environmental data during the well water evaporation and concentration stage, and the processing end predicts the change trend of the brine sodium chloride concentration, judges whether the brine sodium chloride concentration exceeds the supersaturation point in a short time, including the following steps:

[0058] During the well water evaporation and crystallization process, the collection end first acquires environmental parameters closely related to the evaporation rate in real time. These parameters include external environmental temperature T α , relative humidity H, wind speed v, and light intensity I, as well as internal liquid surface temperature T w of the evaporation pond, brine volume V b , current sodium chloride concentration C NaCl (t), pH value, and conductivity, etc. Among them, temperature and humidity jointly determine the water vapor pressure difference, and then affect the evaporation rate, while wind speed and light intensity affect the evaporation driving energy. After these parameters are collected, they are transmitted to the processing end to provide input basis for subsequent prediction and control. Based on the environmental parameters and liquid state information, the processing end estimates the current brine evaporation water amount E. The evaporation rate can be modeled by using the modified Darcy's law and empirical coefficient method, and its calculation formula is:

[0059] E = k · (P s (T w ) - P a (T a,H))·A·f(v), where E represents the amount of brine water evaporated per unit time (unit: kg / h or L / h), k represents the evaporation coefficient, which is related to liquid surface disturbance and system openness, P s (T w P represents the saturated water vapor pressure (Pa) at the liquid surface temperature. This can be found in vapor pressure curves. a (T a H) represents the actual water vapor pressure in the air, calculated as P a (T a H) = H·P s (T a H represents relative humidity, P represents relative humidity. s (T a ) represents the saturated water vapor pressure (Pa) at the external ambient temperature, A represents the evaporation surface area, and f(v) represents the wind speed influence factor, which is commonly f(v) = 1 + a·v, where a is the wind speed correction coefficient.

[0060] By estimating the water loss per unit time, combined with the initial brine volume V b The trend of brine concentration change can be obtained. According to the mass conservation model, the evolution of sodium chloride concentration in the brine can be expressed as:

[0061] Where: C NaCl (t+Δt) represents the predicted sodium chloride concentration at time t+Δt, V b Let E represent the initial brine volume, E represent the amount of water evaporated from the brine per unit time, and Δt represent the time interval (h), m. NaCl Let C be the total mass (kg) of sodium chloride in the brine. The processing unit uses this expression to dynamically predict the change trend of sodium chloride concentration at time t+Δt. When the predicted sodium chloride concentration C at time t+Δt... NaCl (t+Δt) is higher than the solubility limit (i.e., supersaturation point) at the current temperature. sat (T w When the concentration of sodium chloride in the brine exceeds the supersaturation point within a short time (t+Δt), the following criteria are used to determine the saturation point: Among them, C sat (T w ) is the solubility limit (i.e., supersaturation point) at the current temperature.

[0062] In this application, the evaporation coefficient k, the wind speed influence factor f(v), the wind speed correction factor a, and the solubility limit C of sodium chloride are used. sat (T w This is a core parameter in the well water evaporation and crystallization process. The following explains the logic behind its acquisition:

[0063] 1) The acquisition logic of the evaporation coefficient k: The evaporation coefficient k is a comprehensive empirical parameter that reflects the evaporation capacity under the conditions of specific evaporation pond geometry, liquid surface disturbance, air flow organization state, and pond material.

[0064] The experimental calibration method: There are several methods under different environments:

[0065] The experimental calibration method: Under the conditions of humidity and wind speed, static evaporation tests are conducted on closed or semi-closed evaporation ponds. The mass loss of water in a unit of time (i.e., the evaporation E exp ) and the difference between the water surface vapor pressure ΔP = P s (T w ) - P a ) are measured, and the ratio between them is derived to obtain After multiple tests, the average is taken, or a piecewise fitting model is established for use under different wind speeds.

[0066] The recommended value reference method: ASHRAE_Handbook or Industrial Evaporation Design Handbook provides recommended evaporation coefficient ranges for various structures and conditions, such as open ponds under weak disturbance k ≈ 0.0008-0.0015 kg / (m 2 \cdotph\cdotpPa).

[0067] Numerical simulation assisted calibration: Use CFD software (such as Fluent) to simulate the mass transfer under evaporation boundary layer conditions, compare the theoretical calculation with the measured results, and iteratively correct the k value to improve the model accuracy.

[0068] 2) The acquisition logic of the wind speed influence factor f(v) and the wind speed correction coefficient a: The wind speed influence factor f(v) is usually used to describe the enhancement effect of wind speed on the evaporation process under natural convection and forced convection conditions, and the acquisition method is as follows:

[0069] The basic model form: f(v) = 1 + a·v, where v is the ground wind speed (m / s), and a is the wind speed correction coefficient.

[0070] Empirical acquisition: Measure the evaporation rate E v under different wind speeds, compare the wind speed-evaporation rate , and fit the measured points into the function. Use the least squares method to solve a, and if the goodness of fit R 2 > 0.9, the fitting is considered successful. The actual results show that in open ponds, the value of a is usually in the range of 0.1-0.3 (s / m).

[0071] Typical value reference: In the Meteorological Water Exchange Evaporation Formula Compilation, the shallow pond evaporation empirical model gives f(v) = 1 + 0.16v as a common form, and in laboratory simulators, a = 0.15-0.25 is often taken as the wind speed sensitivity adjustment factor.

[0072] 3) Sodium chloride solubility limit C s at(T w ) acquisition logic:

[0073] The saturated solubility concentration of sodium chloride (i.e. the supersaturation point) varies significantly with temperature, the acquisition logic includes two parts of database query + experimental verification, the acquisition method is as follows:

[0074] Standard database consultation: the solubility curve of sodium chloride can be found in CRC Handbook of Chemistry and Physics, Wanfang Data or Salt Industry Engineering Manual, such as the saturated concentration at 25°C is about 357 g / L (solution), and at 40°C is about 384 g / L, which can be interpolated to estimate the saturation point at any temperature.

[0075] On-site comparison and verification: continuously stir the saturated brine at the set temperature, take samples to analyze the sodium ion concentration (atomic absorption method) and conductivity, and compare them with the database values to verify whether they are consistent. If the equipment characteristics or water source composition is special, a one-time correction can be made (such as reducing the crystallization ability when impurities are present, the dissolution limit needs to be manually corrected).

[0076] If exceeded, generate a warning signal and automatically detect whether the by-product salt (such as magnesium sulfate) in the mother liquor is precipitated, including the following steps:

[0077] When the predicted sodium chloride concentration C NaCl (t+Δt) at time t+Δt is higher than the solubility limit value (i.e. the supersaturation point) C sat (T w ) at the current temperature, it is determined that the brine sodium chloride concentration exceeds the supersaturation point in a short time (t+Δt): Where C sat (T w ) is the solubility limit value (i.e. the supersaturation point) at the current temperature.

[0078] When it is determined that the brine sodium chloride concentration exceeds the supersaturation point in a short time (t+Δt), automatically switch to the mother liquor by-product salt detection process to detect whether the by-product salt (such as magnesium sulfate) that is easy to precipitate first in the mother liquor has reached its solubility limit, the judgment logic is as follows:

[0079] If detects that the by-product salt (such as magnesium sulfate) in the mother liquor is precipitated, where C 副盐 (t) represents the current by-product salt concentration, represents the solubility limit value of the corresponding by-product salt at the current temperature T(t) and the current pH condition pH(t).

[0080] The conventional detection methods include: ion chromatography to determine the magnesium concentration, conductivity mutation method to preliminarily judge the abnormal concentration of the by-product salt, and turbidimetry to detect the increase of the solution turbidity indicating the precipitation trend.

[0081] If precipitation occurs, the current change trend of the by-product salt concentration is analyzed, the prediction result of the sodium chloride concentration change trend of the brine is combined, and the by-product salt concentration change is simulated according to the equipment operation state, including the following steps:

[0082] When it is detected that the by-product salt (such as magnesium sulfate) in the mother liquor has appeared precipitation phenomenon, in order to realize the dynamic regulation and control of the by-product salt concentration and the pollution risk control, it is necessary to combine the current by-product salt concentration change trend, the prediction trend of the sodium chloride concentration in the brine, and the equipment operation state, and jointly simulate the evolution process of the by-product salt concentration in the future time period, so as to provide support for the subsequent optimization strategy.

[0083] Firstly, the by-product salt (such as magnesium sulfate) concentration C Mg (t) at the current time t is obtained by using an online ion analyzer or periodic experimental data, and the change rate thereof is calculated in combination with the data C Mg (t-Δt) at the previous time: In the formula, BC Mg is the change rate of the by-product salt (such as magnesium sulfate) concentration, Δt is the time interval, C Mg (t) is the by-product salt concentration at the current time t, and C Mg (t-Δt) is the by-product salt concentration at the previous time t-Δt. The expression represents the concentration change rate of the by-product salt per unit time, which is used to judge whether there is a rapid rising trend. If the change rate of the by-product salt (such as magnesium sulfate) concentration exceeds the change threshold θ Mg , it is judged that the by-product salt is enriched and accelerated.

[0084] Since the change trend of the sodium chloride concentration in the brine will directly affect the concentration rate of the mother liquor, and then affect the relative concentration of the by-product salt, the concentration driving coefficient is calculated according to the predicted sodium chloride concentration at the time t+Δt: In the formula, κ is the concentration driving coefficient, C NaCl (t+Δt) is the predicted sodium chloride concentration at the time t+Δt, C NaCl (t) is the sodium chloride concentration at the current time t, and Δt is the time interval. The coefficient κ(t) reflects the main salt concentration rate. The larger the value is, the faster the brine evaporation is, and the more easily the by-product salt is enriched and exceeds the solubility limit in a short period.

[0085] The adjustment of the device pool body liquid replacement frequency operation parameter is considered to represent the promotion or inhibition effect of the current device working condition on the by-product salt enrichment, and a dynamic simulation model of the future by-product salt concentration is established, and the model expression is: In the formula, C represents the predicted future time t+Δt by-product salt concentration, η represents the concentration trend weight factor, used to adjust the degree of influence of main salt on by-product salt enrichment, BC Mg is the by-product salt (such as magnesium sulfate) concentration change rate, κ is the concentration driving coefficient, Δt is the time interval, γ(t) is the current time pool liquid change frequency, C Mg (t) is the current time t by-product salt concentration, the dynamic simulation model can dynamically simulate the future trend of by-product salt, the predicted future time t+Δt by-product salt concentration value is larger, indicating that the by-product salt concentration rising trend is larger at future time t+Δt.

[0086] According to the simulation results of by-product salt concentration change, the corresponding management strategy is generated, the management strategy includes: if it is found that the magnesium ion concentration in the mother liquor abnormally rises, exceeds the normal crystallization range, starts the small flow drainage, prevents the by-product salt from polluting the main crystal, including the following steps:

[0087] When the predicted future time t+Δt by-product salt concentration increases, that is, , is the by-product salt change warning threshold, immediately activate the small flow drainage sub-strategy, to reduce the by-product salt content in the mother liquor and restore the balance of the crystallization environment, the core control parameter of the drainage operation is the starting time t s , the initial drainage rate Q0, which can be combined with the predicted concentration increase rate to adaptively correct: Where Q adj is the adjusted drainage rate, λ is the by-product salt concentration growth response coefficient, λ is 0.5, is the predicted by-product salt concentration rising rate, and The formula makes the drainage rate proportional to the risk level, and improves the flexibility of the drainage response in high-risk scenarios.

[0088] Based on the prediction of the concentration change trend of sodium chloride in brine and the simulation of the concentration change of by-product salt, an optimization strategy for salt crystal growth is generated, including the following steps:

[0089] Based on the prediction of the concentration change trend of sodium chloride in brine and the simulation of the concentration change of by-product salt (such as magnesium sulfate), the salt crystal growth process is optimized and controlled, which is a key link to ensure the uniformity of crystal particle size, improve the quality of main salt, and avoid by-product salt pollution.

[0090] Get the predicted by-product salt concentration rising rate and the concentration driving coefficient κ, the larger the predicted by-product salt concentration rising rate, the faster the by-product salt concentration rises in the prediction period, and the larger the concentration driving coefficient, the faster the sodium chloride concentration rises in the prediction period.

[0091] Combined with the predicted by-product salt concentration rising rate and the concentration driving coefficient κ is used to modify the growth strategy parameters, including the crystal nucleus density, stirring frequency and crystal residence time, and the modification algorithm is as follows: wherein, is the modified crystal nucleus density, is the reference crystal nucleus density, which refers to the number of crystal nuclei that should be set under ideal non-interference conditions, is the influence factor function, is the modified stirring frequency, is the reference stirring frequency, which refers to the ideal stirring speed set in a stable environment, is the predicted secondary salt concentration rising rate, is the modified crystal residence time, is the reference residence time, which refers to the pre-set time for the particle to grow naturally in the device, Δt r is the adjustment time amount.

[0092] In the present application:

[0093] The function expression of the influence factor function is:

[0094] wherein, C NaCl (t+Δt) represents the predicted sodium chloride concentration at time t+Δt, represents the predicted secondary salt concentration at future time t+Δt, C sat (T w ) is the solubility limit value at the current temperature, is the secondary salt change warning threshold, α is the amplification coefficient of the primary salt concentration on the improvement of the crystal nucleus density, and is usually valued at 0.5-1, and β is the sensitivity coefficient of the secondary salt concentration on the inhibition of the crystal nucleus density, and is usually valued at 0.3-1.

[0095] Specifically, the adjustment time amount Δt r is related to the primary and secondary salt concentration change trend, and the primary / secondary salt concentration change trend and the adjustment time amount are shown in Table 1:

[0096] Table 1

[0097]

[0098] In the primary / secondary salt concentration change trend and the adjustment time amount table, the concentration change rate unit is unified as “grams per liter per hour”, which should be combined with real-time online monitoring data; the trend description considers the coupling relationship between the crystallization stability and the influence of the impurity salt in the actual production process.

[0099] In the description of the specification, reference to "one embodiment", "an example", "a specific example" or the like means that a particular feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. The appearances of the phrases "in one embodiment", "an example", "a specific example" or the like in various places in the specification are not necessarily referring to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0100] The preferred embodiments of the application disclosed above are only to help explain the application. The preferred embodiments do not describe all the details of the application and limit the application to the specific embodiments. Obviously, many modifications and variations can be made in light of the contents of the specification. The specification selects and specifically describes these embodiments in order to better explain the principles and practical application of the application, so that those skilled in the art can well understand and utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A method for particle size control and resource optimization of well water evaporation crystallization salt, characterized in that: The optimization method includes the following steps: The data acquisition end collects current environmental data during the well water evaporation and concentration stage, and the processing end predicts the trend of sodium chloride concentration change in brine and determines whether the sodium chloride concentration in brine exceeds the supersaturation point in a short period of time. If the limit is exceeded, an alarm signal will be generated and the system will automatically detect whether byproduct salts are precipitated in the mother liquor. If precipitation occurs, the current trend of byproduct salt concentration is analyzed, and the change in byproduct salt concentration is simulated by combining the predicted trend of sodium chloride concentration change in brine with the equipment operating status. Based on the simulation results of byproduct salt concentration change, a corresponding management strategy is generated. The management strategy includes the following steps: like hour, The threshold for warning of changes in secondary salt content. Indicates the predicted future moment The concentration of secondary salts is used to activate the flow-through drainage sub-strategy. The drainage rate is adaptively adjusted based on the predicted rate of increase of the secondary salt concentration. The expression is as follows: ,in, The adjusted drainage rate, The initial drainage rate, This represents the response coefficient to the increase in byproduct salt concentration. To predict the rate of increase in byproduct salt concentration, and , For the current moment The concentration of by-salt, For time intervals; The optimization strategy for salt crystal growth based on the prediction of sodium chloride concentration variation trend in brine and the simulation of by-product salt concentration variation includes the following steps: Based on the prediction of the trend of sodium chloride concentration change in brine and the simulation of the change of by-product salt concentration, the salt crystal growth process is optimized and controlled. Combined with the predicted rate of increase in byproduct salt concentration and concentration driving coefficient The growth strategy parameters were modified, including nucleus density, stirring frequency, and crystal residence time. The modification algorithm is as follows: ,in, This is the corrected nucleus density. As a reference crystal nucleus density, For the influence factor function, This is the corrected stirring frequency. As the reference stirring frequency, To predict the rate of increase in byproduct salt concentration, This is the corrected crystal dwell time. The baseline stay time; The function expression for the impact factor is: ,in, Indicates time Predicted sodium chloride concentration at all times Indicates the predicted future moment Concentration of secondary salts, This is the solubility limit at the current temperature. The threshold for warning of changes in secondary salt content. The amplification factor of the main salt concentration on the increase in crystal nucleus density. This is the sensitivity coefficient of the secondary salt concentration to the suppression of crystal nucleus density.

2. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 1, characterized in that: Automatic detection of whether byproduct salts precipitate in mother liquor includes the following steps: When the concentration of sodium chloride in the brine exceeds the supersaturation point during the detection period, the system automatically switches to the mother liquor byproduct salt detection process to check whether the byproduct salts that are prone to precipitate in the mother liquor have reached their solubility limit. The judgment logic is as follows: If... The detection of byproduct salt precipitation in the mother liquor, among which, This indicates the current concentration of byproduct salts. This indicates the corresponding secondary salt at the current temperature. and current pH conditions The solubility limit value below.

3. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 2, characterized in that: After analyzing the current trend of by-product salt concentration, the change of by-product salt concentration is simulated by combining the predicted trend of sodium chloride concentration in brine with the equipment operating status, including the following steps: When precipitation of byproducts is detected in the mother liquor, the current time is obtained using an online ion analyzer. Calculate the rate of change of the concentration of the byproduct salt; Based on time The concentration-driving coefficient is calculated based on the predicted sodium chloride concentration at each time step, and a dynamic simulation model for the future concentration of by-product salt is established. The model expression is as follows: ,in, Indicates the predicted future moment Concentration of secondary salts, This represents the concentrated trend weighting factor. The rate of change of the concentration of byproduct salt. For the concentration driving coefficient, For time intervals, This represents the current liquid exchange frequency in the pool. For the current moment The concentration of by-product salts.

4. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 3, characterized in that: The rate of change of byproduct salt concentration is calculated using the following expression: In the formula, The rate of change of the concentration of byproduct salt. For time intervals, For the current moment The concentration of by-salt, For the previous moment The concentration of by-salts; Based on time The concentration-driving coefficient is calculated based on the predicted sodium chloride concentration at a given time, and the expression is as follows: In the formula, For the concentration driving coefficient, For time Predicted sodium chloride concentration at all times For the current moment The concentration of sodium chloride.

5. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 1, characterized in that: The data acquisition unit collects current environmental data during the well water evaporation and concentration stage, and the processing unit predicts the trend of sodium chloride concentration change in the brine, including the following steps: During the evaporation and crystallization process of well water, the acquisition terminal obtains environmental parameters related to the evaporation rate in real time. These environmental parameters include external ambient temperature, relative humidity, wind speed, light intensity, as well as the liquid surface temperature, brine volume, current sodium chloride concentration, pH value, and conductivity inside the evaporation tank. The processing unit calculates the current brine evaporation rate based on environmental parameters and liquid state information. By estimating the water loss per unit time, combined with the initial brine volume Obtaining brine in time The predicted sodium chloride concentration at any given time is used to predict the trend of sodium chloride concentration changes in brine.

6. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 5, characterized in that: Determining whether the sodium chloride concentration in the brine exceeds the supersaturation point within the specified time period includes the following steps: The processing end obtains the brine in time The predicted sodium chloride concentration at time, when time Predicted sodium chloride concentration at any time When the concentration of sodium chloride in the brine exceeds the solubility limit at the current temperature, determine the detection time period. Exceeding the supersaturation point: ,in, It is the solubility limit at the current temperature.

7. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 6, characterized in that: The formula for calculating the current amount of water evaporated from the brine is: ,in, This indicates the amount of water evaporated from the brine per unit time. Indicates the evaporation coefficient. Represents the saturated water vapor pressure at the liquid surface temperature. This represents the actual water vapor pressure in the air, and , Relative humidity, It represents the saturated water vapor pressure at the external ambient temperature. Represents the evaporation surface area. Indicates the wind speed influencing factor; Obtaining brine in time The predicted sodium chloride concentration at any given time is expressed as: ,in: Indicates time Predicted sodium chloride concentration at all times This represents the initial brine volume. For time intervals, This represents the total mass of sodium chloride in the brine.

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