Particle size regulation and control and resource optimization method of well water evaporative crystallization salt

Abstract

The invention discloses a particle size regulation and resource optimization method of well water evaporative crystallization salt, and relates to the technical field of resource optimization. A processing end predicts the change trend of brine sodium chloride concentration and judges whether the brine sodium chloride concentration exceeds a supersaturation point in a short time, if yes, a warning signal is generated, and whether secondary salt in mother liquor is separated out is automatically detected; if so, analyzing the current change trend of the secondary salt concentration, simulating the secondary salt concentration change by combining the brine sodium chloride concentration change trend prediction result and the equipment operation state, and generating an optimization strategy for salt crystal growth based on brine sodium chloride concentration change trend prediction and secondary salt concentration change simulation. According to the optimization method, a crystal growth optimization strategy is tightly coupled with a sodium chloride concentration trend and a secondary salt behavior, so that parameters such as crystal nucleus density, growth rate and retention time can be adaptively adjusted according to a system state, and dual improvement of particle size distribution uniformity and crystal morphology controllability is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of resource optimization, and in particular to a method for controlling the particle size of well water evaporated crystallized salt and optimizing the resource. Background Art

[0002] In the development of salt lake resources, the traditional open-air salt drying model faces many challenges, such as large land area, long production cycle, and susceptibility to climate impact. With technological advancement, more and more salt lake companies are adopting the method of extracting resources from underground brine (i.e. well water) for industrial production. Well water has become a high-quality resource due to its high salt concentration, stable composition, and controllable extraction method.

[0003] The existing technology has the following defects:

[0004] 1. There is a general lack of trend modeling and multi-factor correlation simulation of the behavior of mother liquor and secondary salts, resulting in delayed drainage decisions, high resource loss rates, and difficulty in efficiently recovering secondary salt resources;

[0005] 2. The existing evaporation crystallization process generally relies on fixed parameter settings and manual experience judgment, lacking a real-time perception and response mechanism for dynamic environmental factors and equipment status. As a result, when the evaporation rate changes suddenly, the brine sodium chloride is easily oversaturated in a short period of time, forming a large number of uncontrolled crystal nuclei, resulting in uneven crystal particle size, severe agglomeration, and difficulty in classification;

[0006] 3. At the same time, the concentration process of secondary salts (especially magnesium salts) in the mother liquor lacks an effective prediction and separation management mechanism, which makes them prone to co-crystallization with the main salt, seriously affecting the purity of sodium chloride and reducing the added value of the product.

[0007] Based on this, the present invention proposes a particle size control and resource optimization method for well water evaporation crystallization salt, which closely couples the crystal growth optimization strategy with the sodium chloride concentration trend and the behavior of the secondary salt, so that parameters such as the crystal nucleus density, growth rate and residence time can be adaptively adjusted according to the system state, achieving a dual improvement in the uniformity of particle size distribution and the controllability of crystal morphology. Summary of the Invention

[0008] The purpose of the present invention is to provide a method for particle size control and resource optimization of well water evaporation crystallized salt to address the shortcomings of the background technology.

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

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

[0011] If it exceeds the limit, a warning signal will be generated and the mother liquor will be automatically checked for precipitation of secondary salts;

[0012] If precipitation occurs, the current trend of the secondary salt concentration is analyzed, and the secondary salt concentration change is simulated based on the predicted results of the brine sodium chloride concentration change trend and the equipment operation status. The corresponding management strategy is generated based on the simulation results of the secondary salt concentration change;

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

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

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

[0016] Combined with the prediction of the rate of increase of secondary salt concentration The concentration driving coefficient κ is used to correct the growth strategy parameters, including the crystal nucleus density, stirring frequency and crystal residence time.

[0017] In a preferred embodiment, the correction parameters include crystal nucleus density, stirring frequency and crystal residence time, and the correction algorithm is: in, is the corrected nucleus density, is the base nucleus density, is the impact factor function, is the corrected stirring frequency, is the reference stirring frequency, To predict the rate of increase of secondary salt concentration, is the corrected crystal residence time, is the baseline residence time;

[0018] The functional expression of the impact factor function is:

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

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

[0021] When it is determined that the sodium chloride concentration of the brine exceeds the supersaturation point within the detection period, it will automatically switch to the mother liquor secondary salt detection process to detect whether the secondary salt that is easy to precipitate first in the mother liquor has reached the solubility limit. The judgment logic is: if Detect the precipitation of secondary salts in the mother liquor, among which C 副盐 (t) represents the current secondary salt concentration, It indicates the solubility limit of the corresponding secondary salt at the current temperature T(t) and the current pH conditions pH(t).

[0022] In a preferred embodiment, after analyzing the current change trend of the secondary salt concentration, combining the brine sodium chloride concentration change trend prediction result and the equipment operation status to simulate the secondary salt concentration change, the following steps are included:

[0023] When the precipitation of secondary salt in the mother liquor is detected, the secondary salt concentration at the current time t is obtained using an online ion analyzer, and the rate of change of the secondary salt concentration is calculated;

[0024] The concentration driving coefficient is calculated based on the predicted sodium chloride concentration at time t+Δt, and a dynamic simulation model for the future concentration of secondary salts is established. The model expression is:

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

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

[0027] Where BC Mg is the rate of change 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 moment t-Δt;

[0028] The concentration driving coefficient is calculated based on the predicted sodium chloride concentration at time t+Δt, and the expression is: Where 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 sodium chloride concentration at the current time t.

[0029] In a preferred embodiment, a corresponding management strategy is generated based on the simulation results of the secondary salt concentration change, and the management strategy includes the following steps:

[0030] like hour, is the secondary salt change warning threshold, It represents the predicted secondary salt concentration at the future time t+Δt, activates the flow drainage sub-strategy, and adaptively modifies the drainage rate based on the predicted secondary salt concentration rising rate. The expression is: Among them, Q adj is the adjusted drainage rate, Q0 is the initial drainage rate, λ is the response coefficient of the secondary salt concentration growth, To predict the rate of increase of secondary salt concentration, C Mg (t) is the secondary salt concentration at the current time t, and Δt is the time interval.

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

[0032] During the evaporation and crystallization process of well water, the data collection end 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 inside the evaporation pool, brine volume, current sodium chloride concentration, pH value, and conductivity.

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

[0034] In a preferred embodiment, determining whether the sodium chloride concentration of the brine exceeds the supersaturation point within the detection time period comprises the following steps:

[0035] The processing end obtains the predicted sodium chloride concentration of brine at time t+Δt. When the predicted sodium chloride concentration C NaCl When (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 within the detection time period t+Δt: C NaCl (t+Δt)>C sat (T w ) Beyond the supersaturation point, where C sat (T w ) is the solubility limit at the current temperature.

[0036] In a preferred embodiment, the calculation formula for the current brine evaporated water volume E is:

[0037] E=k·(P s (T w )-P a (T a ,H))·A·f(v), where E represents the amount of brine evaporated per unit time, k represents the evaporation coefficient, and 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 relative humidity, P s (T a ) represents the saturated water vapor pressure at the external ambient temperature, A represents the evaporation surface area, and f(v) represents the wind speed factor;

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

[0039] Where: 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, m NaCl is the total mass of sodium chloride in the brine.

[0040] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0041] 1. The present invention collects current environmental data during the evaporation and concentration stage of well water through the collection end, and predicts the trend of change of sodium chloride concentration in brine at the processing end, and determines whether the sodium chloride concentration of brine exceeds the supersaturation point in a short period of time. If it exceeds, a warning signal is generated and the secondary salt in the mother liquor is automatically detected to see whether it is precipitated. If it is precipitated, the current trend of the secondary salt concentration is analyzed, and the secondary salt concentration change is simulated based on the prediction result of the change trend of sodium chloride concentration in brine and the equipment operation status. According to the simulation result of the secondary salt concentration change, a corresponding management strategy is generated, and an optimization strategy for salt crystal growth is generated based on the prediction of the change trend of sodium chloride concentration in brine and the simulation of the change of secondary salt concentration. This optimization method tightly couples the crystal growth optimization strategy with the sodium chloride concentration trend and the behavior of secondary salts, so that parameters such as crystal nucleus density, growth rate and residence time can be adaptively adjusted according to the system state, achieving a dual improvement in particle size distribution uniformity and crystal morphology controllability.

[0042] 2. The present invention realizes a dynamic prediction and control mechanism driven by multi-source data by introducing modules such as environmental data collection, salt concentration change trend prediction, and secondary salt precipitation trend detection in the evaporation and concentration stage. By judging whether sodium chloride is about to exceed the supersaturation point, the system can issue an early warning signal, link the secondary salt precipitation detection process, identify abnormal magnesium ion concentration in the mother liquor, and perform numerical simulation and trend deduction on the secondary salt concentration change in combination with the equipment operation status. This mechanism significantly enhances the feedforward control capability of the miscellaneous salt precipitation behavior, and uses the simulation results to drive dynamic management strategies including lowering the secondary salt precipitation threshold, enabling low-flow drainage, and rebalancing the mother liquor composition, effectively avoiding the risk of secondary salt contamination of the main crystal. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0044] Figure 1 Flowchart of the optimization method of the present invention.

[0045] Figure 2 This is a timing diagram of the optimization method of the present invention.

[0046] Figure 3 This is a mind map of the optimization method of the present invention.

[0047] Figure 4 This is a system architecture diagram of the optimization system of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] Example 1: Please refer to Figure 1-Figure 3 As shown, the particle size control and resource optimization method of well water evaporation crystallization salt described in this embodiment includes the following steps:

[0050] The collection end collects current environmental data during the evaporation and concentration stage of well water, and the processing end predicts the trend of changes in the sodium chloride concentration of the brine, and determines whether the sodium chloride concentration of the brine exceeds the supersaturation point in a short period of time. If exceeded, a warning signal is generated and the mother liquor is automatically detected to see whether secondary salts (such as magnesium sulfate) are precipitated. If precipitated, the current trend of changes in the secondary salt concentration is analyzed, and the change in the secondary salt concentration is simulated based on the prediction results of the change trend of the sodium chloride concentration of the brine and the operating status of the equipment. The corresponding management strategy is generated based on the simulation results of the change in the secondary salt concentration. The management strategy includes: if the magnesium ion concentration in the mother liquor is found to be abnormally high and exceeds the normal crystallization range, a small flow rate drainage is started to prevent the secondary salt from contaminating the main crystal, and an optimization strategy is generated for the salt crystal growth based on the prediction of the change trend of the sodium chloride concentration of the brine and the simulation of the change in the secondary salt concentration.

[0051] This application collects current environmental data during the evaporation and concentration stage of well water through the collection end, and predicts the trend of changes in the sodium chloride concentration of the brine at the processing end, and determines whether the sodium chloride concentration of the brine exceeds the supersaturation point in a short period of time. If exceeded, a warning signal is generated and the secondary salt in the mother liquor is automatically detected to see whether it is precipitated. If precipitated, the current trend of the secondary salt concentration is analyzed, and the secondary salt concentration change is simulated based on the prediction results of the brine sodium chloride concentration change trend and the equipment operation status. The corresponding management strategy is generated based on the simulation results of the secondary salt concentration change, and an optimization strategy is generated for salt crystal growth based on the prediction of the brine sodium chloride concentration change trend and the simulation of the secondary salt concentration change. This optimization method tightly couples the crystal growth optimization strategy with the sodium chloride concentration trend and the secondary salt behavior, so that parameters such as the crystal nucleus density, growth rate and residence time can be adaptively adjusted according to the system state, achieving a dual improvement in the uniformity of the particle size distribution and the controllability of the crystal morphology.

[0052] This application collects current environmental data at the stage of well water evaporation and concentration through the acquisition end, predicts the trend of brine sodium chloride concentration change at the processing end, determines whether the brine sodium chloride concentration exceeds the supersaturation point in a short period of time, and if so, generates a warning signal and automatically detects whether secondary salts are precipitated in the mother liquor. If so, the current trend of secondary salt concentration change is analyzed, and the secondary salt concentration change is simulated based on the prediction result of brine sodium chloride concentration change trend and equipment operation status. The corresponding management strategy is generated according to the simulation result of secondary salt concentration change. By introducing environmental data acquisition, salt concentration change trend prediction and secondary salt precipitation in the evaporation and concentration stage, the application can effectively improve the management of the environment and the environment. Modules such as trend detection have realized a dynamic prediction and control mechanism driven by multi-source data. By judging whether sodium chloride is about to exceed the supersaturation point, the system can issue an early warning signal, link the secondary salt precipitation detection process, identify abnormal magnesium ion concentration in the mother liquor, and perform numerical simulation and trend deduction on the changes in secondary salt concentration in combination with the equipment operating status. This mechanism significantly enhances the feedforward control capability of the precipitation behavior of impurities, and uses the simulation results to drive dynamic management strategies including lowering the secondary salt precipitation threshold, enabling low-flow drainage, and rebalancing the mother liquor composition, effectively avoiding the risk of secondary salt contamination of the main crystal.

[0053] See also 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] Sodium chloride concentration prediction module: collects current environmental data during the well water evaporation and concentration stage, predicts the trend of brine sodium chloride concentration changes, determines whether the brine sodium chloride concentration exceeds the supersaturation point in a short period of time, and sends 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] Secondary salt concentration simulation module: If the sodium chloride concentration of the brine exceeds the supersaturation point in a short period of time, an alarm signal is generated and the secondary salt (such as magnesium sulfate) in the mother liquor is automatically detected to see if it is precipitated. If so, the current change trend of the secondary salt concentration is analyzed, and the change of the secondary salt concentration is simulated based on the prediction result of the change trend of the sodium chloride concentration of the brine and the equipment operation status. The corresponding management strategy is generated based on the simulation result of the secondary salt concentration change. The management strategy includes: if the magnesium ion concentration in the mother liquor is found to be abnormally high and exceeds the normal crystallization range, a small flow discharge is started to prevent the secondary salt from contaminating the main crystal. The simulation results are sent to the particle size control and optimization module;

[0056] Particle size control and optimization module: Generates optimization strategies for salt crystal growth based on the prediction of brine sodium chloride concentration change trend and simulation of secondary salt concentration change.

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

[0058] During the evaporation and crystallization process of well water, the acquisition end first obtains the environmental parameters closely related to the evaporation rate in real time. These parameters include the external ambient temperature T α , relative humidity H, wind speed v, light intensity I, and the liquid surface temperature T inside the evaporation pool w , 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, which in turn affects 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 an input basis for subsequent prediction and control. Based on environmental parameters and liquid state information, the processing end estimates the current brine evaporation water volume E. The evaporation rate can be modeled using the modified Darcy's law and the empirical coefficient method. The 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 evaporated per unit time (unit: kg / h or L / h), k represents the evaporation coefficient, which is related to the liquid level disturbance and system openness, and P s (T w ) represents the saturated water vapor pressure (Pa) at the liquid surface temperature. The vapor pressure curve can be checked. P a (T a ,H) represents the actual water vapor pressure in the air, which is calculated as P a (T a ,H)=H·P s (T a ), H is relative humidity, P 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 influencing factor. The commonly used formula is 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 process of sodium chloride concentration in brine can be expressed as:

[0061] Where: C NaCl (t+Δt) represents the predicted sodium chloride concentration at time t+Δt, V b is the initial brine volume, E represents the amount of brine evaporated per unit time, Δt is the time interval (h), m NaCl is the total mass of sodium chloride in the brine (kg). The processing end uses this expression to dynamically predict the trend of sodium amide concentration change at time t+Δt. When the predicted sodium chloride concentration C at time t+Δt is NaCl (t+Δt) is higher than the solubility limit (i.e. supersaturation point) at the current temperature C sat (T w ), it is judged that the sodium chloride concentration of the brine exceeds the supersaturation point within a short time (t+Δt): Among them, C sat (T w ) is the solubility limit value (i.e. supersaturation point) at the current temperature.

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

[0063] 1) Logic for obtaining the evaporation coefficient k: The evaporation coefficient k is a comprehensive empirical parameter that reflects the evaporation capacity under specific conditions such as the geometric structure of the evaporation pool, liquid surface disturbance, airflow organization state, and pool material.

[0064] Acquisition method experimental calibration method: There are several types in different environments:

[0065] Experimental calibration method: Under the conditions of humidity and wind speed, static evaporation test is carried out on closed or semi-closed evaporation ponds. The water mass loss per unit time (i.e. evaporation amount E exp ) and the water surface vapor pressure difference ΔP=P s (T w )-P a The ratio between Take the average after multiple tests, or establish a segmented fitting model for use under different wind speeds.

[0066] Recommended value reference method: For example, ASHRAE_Handbook or Industrial Evaporation Design Manual provide recommended evaporation coefficient ranges under various structures and conditions. For example, for an open pool under weak disturbance, k≈0.0008~0.0015kg / (m 2 \cdotph\cdotpPa)).

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

[0068] 2) Logic for obtaining 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. The method for obtaining it is as follows:

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

[0070] Experience Gained: Measuring Evaporation Rate E in No Wind and at Different Wind Speeds v , comparing wind speed-evaporation improvement rate Substitute the measured points into the function fitting, use the least squares method to inversely calculate a, and the goodness of fit R 2 The fitting is considered successful when the value is >0.9. Actual results show that in an open pool, the a value usually ranges from 0.1 to 0.3 (s / m).

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

[0072] 3) Solubility limit of sodium chloride C s at(T w )'s acquisition logic:

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

[0074] Standard database query: The solubility curve of sodium chloride can be found in the "CRC_Handbook_of_Ch emistry_and_Physics", Wanfang Data or the Salt Industry Engineering Handbook. For example, the saturation concentration at 25°C is about 357g / L (solution), and at 40°C it is about 384g / L. The saturation point at any temperature can be estimated by interpolation.

[0075] On-site comparison and verification: Continuously stir the saturated brine at the set temperature, take samples to analyze its sodium ion concentration (atomic absorption method) and compare it with the conductivity database value to verify whether it is consistent. If the equipment characteristics or water source composition are special, a one-time correction can be made (for example, when it contains impurities, the crystallization ability is reduced, and the solubility limit needs to be manually corrected).

[0076] If it exceeds, a warning signal is generated and the mother liquor is automatically checked for precipitation of secondary salts (such as magnesium sulfate), including the following steps:

[0077] 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 C sat (T w ), it is judged that the sodium chloride concentration of the brine exceeds the supersaturation point within a short time (t+Δt): Among them, C sat (T w ) is the solubility limit value (i.e. supersaturation point) at the current temperature.

[0078] When it is determined that the sodium chloride concentration of the brine exceeds the supersaturation point within a short period of time (t+Δt), the process automatically switches to the mother liquor secondary salt detection process to detect whether the secondary 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] like Detect the precipitation of secondary salts (such as magnesium sulfate) in the mother liquor, where C 副盐 (t) represents the current secondary salt concentration, It indicates the solubility limit of the corresponding secondary salt at the current temperature T(t) and the current pH conditions pH(t).

[0080] Conventional detection methods include: ion chromatography to determine magnesium concentration, conductivity mutation method to preliminarily determine abnormal concentration of secondary salts, and turbidimetry to detect solution turbidity increase indicating precipitation trend.

[0081] If precipitation occurs, the current trend of the secondary salt concentration is analyzed, and the secondary salt concentration change is simulated by combining the prediction results of the brine sodium chloride concentration change trend with the equipment operating status, including the following steps:

[0082] When precipitation of secondary salts (such as magnesium sulfate) is detected in the mother liquor, in order to achieve dynamic regulation of the secondary salt concentration and pollution risk control, it is necessary to combine the current trend of secondary salt concentration changes, the predicted trend of sodium chloride concentration in the brine, and the equipment operating status, and jointly simulate the evolution process of secondary salt concentration in the future time period to provide support for subsequent optimization strategies.

[0083] First, use an online ion analyzer or periodic experimental data to obtain the concentration C of the secondary salt (such as magnesium sulfate) at the current time t. Mg (t), and combined with the previous moment data C Mg (t-Δt) calculates its rate of change: Where BC Mg is the rate of change of the concentration of the secondary salt (such as magnesium sulfate), Δt is the time interval, C Mg (t) is the secondary salt concentration at the current time t, C Mg (t-Δt) is the concentration of the secondary salt at the previous moment t-Δt. This expression represents the concentration change rate of the secondary salt per unit time and is used to determine whether it has a rapid upward trend. If the concentration change rate of the secondary salt (such as magnesium sulfate) exceeds the change threshold θ Mg , it is judged that the enrichment of secondary salts is accelerated.

[0084] Since the trend of sodium chloride concentration in brine will directly affect the concentration rate of the mother liquor, and thus affect the relative concentration of the secondary salts, the concentration driving coefficient is calculated based on the predicted sodium chloride concentration at time t+Δt: Where 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 sodium chloride concentration at the current moment t, Δt is the time interval, and this coefficient κ(t) reflects the concentration rate of the main salt. The larger the value, the faster the brine evaporates and the easier it is for the secondary salt to be enriched in a short period of time and exceed its solubility limit.

[0085] Considering the adjustment of the equipment's pool fluid replacement frequency operating parameters, the current equipment operating conditions are expressed to promote or inhibit the accumulation of secondary salts. A dynamic simulation model of the future concentration of secondary salts is established. The model expression is: in, represents the predicted secondary salt concentration at the future time t+Δt, η represents the concentration trend weight factor, which is used to adjust the influence of the main salt on the secondary salt enrichment, BC Mg is the concentration change rate of the secondary salt (such as magnesium sulfate), κ is the concentration driving coefficient, Δt is the time interval, γ(t) is the frequency of the cell body liquid change at the current moment, C Mg (t) is the secondary salt concentration at the current time t. The dynamic simulation model can dynamically simulate the future trend of secondary salt. The larger the value of the predicted secondary salt concentration at the future time t+Δt, the greater the upward trend of the secondary salt concentration at the future time t+Δt.

[0086] Generate corresponding management strategies based on the simulation results of the secondary salt concentration change. The management strategies include: if the magnesium ion concentration in the mother liquor is found to be abnormally high and exceeds the normal crystallization range, start small flow drainage to prevent the secondary salt from contaminating the main crystal, including the following steps:

[0087] When the concentration of secondary salt increases at the predicted future time t+Δt, that is, hour, The secondary salt change warning threshold is set, and the small flow rate drainage strategy is immediately activated to reduce the secondary salt content in the mother liquor and restore the balance of the crystallization environment. The core control parameter of the drainage operation is the start time t s , the initial discharge rate Q0, its scheduling can be adaptively modified in combination with the predicted concentration growth rate: Among them, Q adj is the adjusted drainage rate, λ is the response coefficient of the secondary salt concentration increase, and λ is set to 0.5. To predict the rate of increase of secondary salt concentration, This formula makes the drainage rate proportional to the risk level, improving the flexibility of the drainage response in high-risk scenarios.

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

[0089] Optimizing and controlling the salt crystal growth process based on the prediction of sodium chloride concentration change trends in brine and the simulation of secondary salt (such as magnesium sulfate) concentration changes is a key link in ensuring the uniformity of crystal particle size, improving the quality of main salt, and avoiding secondary salt contamination.

[0090] Get the predicted rate of increase of secondary salt concentration As well as the concentration driving coefficient κ, the larger the value of the predicted secondary salt concentration rising rate, the faster the secondary salt concentration rises during the predicted time period, and the larger the concentration driving coefficient, the faster the sodium chloride concentration rises during the predicted time period.

[0091] Combined with the prediction of the rate of increase of secondary salt concentration The concentration driving coefficient κ is used to correct the growth strategy parameters. The correction parameters include the crystal nucleus density, stirring frequency and crystal residence time. The correction algorithm is as follows: in, is the corrected nucleus density, is the benchmark crystal nucleus density, which refers to the number of crystal nuclei that should be set under ideal non-interference conditions. is the impact factor function, is the corrected stirring frequency, The ideal stirring speed is set in a stable environment. To predict the rate of increase of secondary salt concentration, is the corrected crystal residence time, is the benchmark residence time, which refers to the preset time for the particles to grow naturally in the device, Δt r To adjust the amount of time.

[0092] In this application:

[0093] The functional expression of the impact factor function is:

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

[0095] Specifically, adjust the time amount Δt r Related to the concentration change trend of the main and auxiliary salts, the comparison table of the concentration change trend of the main and auxiliary salts and the adjustment time is shown in Table 1:

[0096] Table 1

[0097]

[0098] In the comparison table of main salt / secondary salt concentration change trend and adjustment time, the unit of concentration change rate is unified as "grams / liter increased per hour", which should be combined with real-time online monitoring data; the trend description takes into account the coupling relationship between crystallization stability and the influence of impurity salts in the actual production process.

[0099] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0100] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for controlling the particle size of well water evaporation crystallized salt and optimizing its resources, characterized by: The optimization method comprises the following steps: The collection end collects current environmental data during the evaporation and concentration stage of well water, and the processing end predicts the trend of changes in the sodium chloride concentration of the brine and determines whether the sodium chloride concentration of the brine exceeds the supersaturation point in a short period of time; If it exceeds the limit, a warning signal will be generated and the mother liquor will be automatically checked for precipitation of secondary salts; If precipitation occurs, the current trend of the secondary salt concentration is analyzed, and the secondary salt concentration change is simulated based on the predicted results of the brine sodium chloride concentration change trend and the equipment operation status. The corresponding management strategy is generated based on the simulation results of the secondary salt concentration change; An optimization strategy for salt crystal growth is generated based on the prediction of brine sodium chloride concentration change trend and simulation of secondary salt concentration change.

2. The particle size control and resource optimization method of well water evaporation crystallization salt according to claim 1, characterized in that: Based on the prediction of the change trend of sodium chloride concentration in brine and the simulation of the change of secondary salt concentration, an optimization strategy for salt crystal growth is generated, which includes the following steps: Based on the prediction of sodium chloride concentration change trend in brine and simulation of secondary salt concentration change, the salt crystal growth process is optimized and controlled; Combined with the prediction of the rate of increase of secondary salt concentration The concentration driving coefficient κ is used to correct the growth strategy parameters, including the crystal nucleus density, stirring frequency and crystal residence time.

3. The particle size control and resource optimization method of well water evaporation crystallization salt according to claim 2, characterized in that: Correction parameters include crystal nucleus density, stirring frequency and crystal residence time. The correction algorithm is: in, is the corrected nucleus density, is the base nucleus density, is the impact factor function, is the corrected stirring frequency, is the reference stirring frequency, To predict the rate of increase of secondary salt concentration, is the corrected crystal residence time, is the baseline residence time; The functional expression of the impact factor function is: Among them, C NaCl (t+Δt) represents the predicted sodium chloride concentration at time t+Δt, represents the predicted secondary salt concentration at the future time t+Δt, C sat (T w ) is the solubility limit at the current temperature, is the warning threshold of the secondary salt change, α is the amplification coefficient of the main salt concentration on the increase of the crystal nucleus density, and β is the sensitivity coefficient of the secondary salt concentration on the inhibition of the crystal nucleus density.

4. The particle size control and resource optimization method of well water evaporation crystallization salt according to claim 3, characterized in that: Automatically detect whether secondary salts are precipitated in the mother liquor, including the following steps: When it is determined that the sodium chloride concentration of the brine exceeds the supersaturation point within the detection period, it will automatically switch to the mother liquor secondary salt detection process to detect whether the secondary salt that is easy to precipitate first in the mother liquor has reached the solubility limit. The judgment logic is: if Detect the precipitation of secondary salts in the mother liquor, among which C 副盐 (t) represents the current secondary salt concentration, It indicates the solubility limit of the corresponding secondary salt at the current temperature T(t) and the current pH conditions pH(t).

5. The particle size control and resource optimization method of well water evaporation crystallization salt according to claim 4, characterized in that: After analyzing the current trend of the secondary salt concentration, the secondary salt concentration change is simulated by combining the prediction results of the brine sodium chloride concentration change trend with the equipment operating status, including the following steps: When the precipitation of secondary salt in the mother liquor is detected, the secondary salt concentration at the current time t is obtained using an online ion analyzer, and the rate of change of the secondary salt concentration is calculated; The concentration driving coefficient is calculated based on the predicted sodium chloride concentration at time t+Δt, and a dynamic simulation model for the future concentration of secondary salts is established. The model expression is: in, represents the predicted secondary salt concentration at the future time t+Δt, η represents the concentration trend weight factor, BC Mg is the rate of change of the secondary salt concentration, κ is the concentration driving coefficient, Δt is the time interval, γ(t) is the frequency of the cell body liquid replacement at the current moment, C Mg (t) is the secondary salt concentration at the current time t.

6. The particle size control and resource optimization method of well water evaporation crystallization salt according to claim 5, characterized in that: Calculate the rate of change of secondary salt concentration, the expression is: Where BC Mg is the rate of change 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 moment t-Δt; The concentration driving coefficient is calculated based on the predicted sodium chloride concentration at time t+Δt, and the expression is: Where 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 sodium chloride concentration at the current time t.

7. The particle size control and resource optimization method of well water evaporation crystallization salt according to claim 6, characterized in that: Generate corresponding management strategies based on the simulation results of secondary salt concentration changes. The management strategies include the following steps: like hour, is the secondary salt change warning threshold, It represents the predicted secondary salt concentration at the future time t+Δt, activates the flow drainage sub-strategy, and adaptively modifies the drainage rate based on the predicted secondary salt concentration rising rate. The expression is: Among them, Q adj is the adjusted drainage rate, Q0 is the initial drainage rate, λ is the response coefficient of the secondary salt concentration growth, To predict the rate of increase of secondary salt concentration, C Mg (t) is the secondary salt concentration at the current time t, and Δt is the time interval.

8. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 1, characterized in that: The collection end collects current environmental data during the well water evaporation and concentration stage, and the processing end predicts the trend of changes in brine sodium chloride concentration, including the following steps: During the evaporation and crystallization process of well water, the data collection end 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 inside the evaporation pool, brine volume, current sodium chloride concentration, pH value, and conductivity. The processing end calculates the current brine evaporation volume E based on environmental parameters and liquid state information, and estimates the water loss per unit time, combined with the initial brine volume V b , obtain the predicted sodium chloride concentration of brine at time t+Δt, which is used to predict the changing trend of sodium chloride concentration in brine.

9. The method for particle size control and resource optimization of well water evaporation crystallization salt according to claim 8, characterized in that: Determining whether the sodium chloride concentration of brine exceeds the supersaturation point within the detection period includes the following steps: The processing end obtains the predicted sodium chloride concentration of brine at time t+Δt. When the predicted sodium chloride concentration C NaCl When (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 within the detection time period t+Δt: Among them, C sat (T w ) is the solubility limit at the current temperature.

10. The method for particle size control and resource optimization of well water evaporation crystallized salt according to claim 9, characterized in that: The calculation formula for the current brine evaporation volume is: E=k·(P s (T w )-P a (T a ,H))·A·f(v), where E represents the amount of brine evaporated per unit time, k represents the evaporation coefficient, and 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 relative humidity, P s (T a ) represents the saturated water vapor pressure at the external ambient temperature, A represents the evaporation surface area, and f(v) represents the wind speed factor; Get the predicted sodium chloride concentration of brine at time t+Δt, the expression is: Where: 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, m NaCl is the total mass of sodium chloride in the brine.

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