Low-temperature crystallization treatment system for precooling system of air separation device

Abstract

The invention discloses a low-temperature crystallization treatment system for a precooling system of an air separation device, and relates to the technical field of precooling systems of air separation devices, the system comprises a spectrum monitoring module, a microwave-assisted dissolution module, a treatment measure module, a control unit and an alarm module; according to the method, spectral characteristics of circulating water of a precooling system are monitored in real time by utilizing a spectral analysis technology, rapid and accurate judgment on crystallization conditions is realized, different salt crystals have unique absorption and reflection characteristics under spectrums with specific wavelengths, and the characteristic is fully utilized by the method, so that the method is suitable for large-scale popularization and application. By establishing a spectrum database containing standard spectrum data of a large number of different salt crystals under various conditions and combining a high-precision spectrum analysis model, the spectrum data can be collected and processed in real time, whether the crystals are formed or not and the specific types and concentrations of the crystals can be quickly identified, and the accuracy of the analysis is improved. The function not only improves the accuracy and efficiency of monitoring, but also provides a powerful basis for taking treatment measures in time.

Description

Technical Field

[0001] The invention relates to the technical field of air separation device precooling systems, in particular to a low-temperature crystallization processing system of an air separation device precooling system. Background Art

[0002] In the precooling system of the air separation unit, salt crystallization is prone to occur in the circulating water under low temperature conditions. These crystals will not only reduce the efficiency of the system, but may also cause damage to the equipment and potential safety hazards. Therefore, effective monitoring and treatment of crystallization in the circulating water of the precooling system is of great significance to ensure the normal operation of the air separation unit and extend the life of the equipment.

[0003] Traditional technology for monitoring and treating crystallization in circulating water of precooling system mainly relies on manual inspection and regular sampling analysis. This method is not only inefficient, but also difficult to detect crystallization problems in a timely and accurate manner. In addition, the judgment of the type and concentration of crystallization often relies on experience, which lacks scientificity and accuracy. Even if the crystallization problem is found, traditional technology can only take relatively extensive treatment measures, such as large-scale flushing or chemical cleaning, which not only wastes a lot of water resources and chemical reagents, but also pollutes the environment.

[0004] Therefore, a low-temperature crystallization treatment system for the precooling system of an air separation unit is developed. By utilizing advanced spectral analysis technology and microwave-assisted dissolution technology, efficient and accurate monitoring and treatment of crystallization in the circulating water of the precooling system can be achieved. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and provide a low-temperature crystallization treatment system for a precooling system of an air separation unit. The system integrates spectral monitoring, microwave-assisted dissolution, treatment measures, control and alarm modules. Through the spectral monitoring module, a high-precision spectral analysis model is used to monitor the formation and type concentration of salt crystals in circulating water in real time to achieve early warning. The microwave-assisted dissolution module uses microwave energy to effectively dissolve crystals and improve removal efficiency. The treatment measures module automatically takes treatment measures according to the crystallization situation to ensure stable operation of the system. The entire system coordinates the work of each module through a control unit and issues an alarm through the alarm module when necessary.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a low-temperature crystallization treatment system of a precooling system of an air separation device, the system comprising: a spectrum monitoring module, a microwave-assisted dissolution module, a treatment measure module, a control unit and an alarm module;

[0007] The spectrum monitoring module: selects a spectrum sensor with high sensitivity and wide wavelength range, installs it in the straight pipe section of the circulating water of the precooling system, and connects it to a high-speed data transmission interface, collects a large amount of standard spectrum data of different salt crystals under various conditions, and uses database management software to establish a spectrum database after sorting and classification and regularly updates it, builds a high-precision spectrum analysis model, trains and verifies it with a large amount of known spectrum data, and continuously optimizes the model. The spectrum sensor continuously collects data and transmits it to the analysis model for processing in real time. The analysis model quickly determines the crystallization situation. If crystals are formed, the system issues an alarm and sends the information to the control unit and the alarm module;

[0008] The spectrum database in the spectrum monitoring module is established by collecting spectrum data points (λ i ,I i ) to establish a spectral database, where λ i Indicates wavelength, I i Represents the corresponding spectral intensity. For each salt crystal, the function S j (λ) is used to represent its spectral characteristics, and the calculation formula is: Where j represents the type number of the salt, N j is the number of Gaussian components, A jk , μ jk and σ jk are the amplitude, mean, and standard deviation of the kth Gaussian component of the crystallization of the jth salt, respectively;

[0009] The analysis model in the spectrum monitoring module calculates the monitored spectrum I(λ) and the spectrum S of various salt crystals in the database. j (λ) to determine whether crystals are formed and the type and concentration of crystals. The similarity function D(I,S j ) is: When the similarity exceeds a certain threshold, it is determined that a corresponding type of crystal is formed, and the concentration of the crystal is estimated based on the similarity.

[0010] The microwave-assisted dissolution module: selects a microwave generator with adjustable power and frequency, installs the microwave generator at a location where crystallization is likely to occur, determines heating parameters according to the characteristics of the crystal and the dissolution requirements, monitors temperature changes in real time during the heating process, dynamically adjusts the microwave power through a microwave power adjustment factor based on the real-time monitored temperature data, clarifies the quantitative relationship between microwave parameters and the degree of destruction of the crystal lattice structure through a combination of experimental and theoretical analysis, and optimizes and adjusts the microwave parameters based on the relationship between the two;

[0011] The microwave-assisted dissolution module determines the heating parameters by the microwave crystallization processing formula. Assume that the mass of the crystal is M and the initial crystal concentration is C.0 , the target crystal concentration is C t , microwave power is P, heating time is t, microwave energy conversion efficiency is η, crystal heat loss coefficient is α, assuming that the dissolution rate is proportional to the nth power of the temperature, the relationship between the temperature change and the microwave power and heating time is ΔT = βPt. According to the law of energy conservation, part of the microwave input energy is used for heating and part is lost due to heat loss. The formula is: The relationship between dissolution rate and temperature is: Combining the above temperature change relationship, we can get: Among them, k 0 is the pre-factor, E a is the activation energy, R is the gas constant, k n is the proportionality coefficient;

[0012] The microwave-assisted dissolution module adjusts the microwave power by a microwave power adjustment factor F, and the calculation formula of the microwave power adjustment factor F is: F = e -α|ΔC|+β|ΔT|+γ|ΔS| , where ΔC is the difference between the current crystal concentration and the last crystal concentration, ΔT is the difference between the current temperature and the set temperature, ΔS is the difference between the current system stability index and the target stability index, α, β, γ are adjustment coefficients, and the new microwave power P new For: P new =P old F, where P old is the microwave power at the previous moment;

[0013] The microwave-assisted dissolution module uses a dissolution kinetic equation to describe the crystal dissolution rate, and the formula is: Where C is the concentration of crystals, k d (T) is the temperature-dependent dissolution rate constant, expressed using the Arrhenius equation: Among them, k 0 is the pre-factor, E a is the activation energy, R is the gas constant, T is the temperature, and f(C) is the concentration-dependent function, as shown in the formula: f(C) = -k 1 C, where k 1 is a proportionality constant, C represents the concentration of crystals;

[0014] The treatment measure module: when the spectrum monitoring module detects the formation of crystals, the system will automatically take corresponding treatment measures according to the type and concentration of the crystals. For mild crystals, the microwave-assisted dissolution module is activated to accelerate the dissolution of the crystals by microwaves. For severe crystals, a combination of chemical cleaning and microwave cleaning is used to remove the crystals.

[0015] The control unit coordinates the work of the spectrum monitoring module, the microwave-assisted dissolution module and the treatment measure module to ensure the stable operation of the entire system. The control unit automatically adjusts the monitoring frequency, microwave power and intensity of the treatment measure according to the actual situation.

[0016] The alarm module: When the concentration of crystals exceeds the set safety threshold, the alarm module will sound an alarm to remind the staff to take timely measures. The alarm method adopts a combination of sound and light alarm and SMS alarm.

[0017] Furthermore, the specific steps of establishing the spectrum database in the spectrum monitoring module are:

[0018] (1) Collect standard spectral data of different salt crystals under various conditions through laboratory experiments, simulation calculations and actual monitoring;

[0019] (2) Predict the spectral characteristics of salt crystallization under different conditions through algorithm formulas and verify them with experimental data, and install equipment to collect data during actual operation;

[0020] (3) Classifying the collected spectral data by salt type, and then subdividing them by crystal state, using a database to store and record condition information and spectral characteristics;

[0021] (4) Update the database regularly, add the spectral data of newly discovered salt crystals and update the existing data as the environment changes.

[0022] Furthermore, the spectral monitoring module predicts the spectral characteristics of salt crystallization under different conditions through an algorithm formula. Assuming that the spectral intensity of salt crystallization at a specific wavelength λ is I(λ), it is affected by the type S, concentration C, temperature T, and pressure P of the salt. The calculation formula of the spectral intensity is: I(λ)=f(S,C,T,P)=A(S)·g(C)·h(T)·k(P)+E, where A(S) represents the influence function of the salt type on the spectral intensity, and the calculation formula is: Among them, a i and b i With salt S i The correlation coefficient, g(C), represents the influence function of concentration on spectral intensity, and the calculation formula is: g(C) = e mC , where m is the concentration influence coefficient, h(T) represents the influence function of temperature on spectral intensity, and the calculation formula is: h(T)=nT+o, where n and o are temperature influence coefficients, k(P) represents the influence function of pressure on spectral intensity, and the calculation formula is: k(P)=pP+q, where p and q are pressure influence coefficients, and E is the error term.

[0023] Furthermore, the spectrum monitoring module can dynamically update the spectrum characteristics of salt crystals through an update function according to the spectrum data monitored in real time. Suppose the spectrum characteristic update function is: new (λ)=(1-∈)S old (λ)+∈I current (λ), where S old (λ) is the characteristic function of the salt crystal spectrum at the previous moment, I current (λ) is the currently monitored spectrum, and ∈ is the update coefficient.

[0024] Furthermore, the spectrum monitoring module has a remote monitoring function. Through a network connection, an operator can view the spectrum characteristics and crystallization judgment results of the circulating water in real time at a remote terminal.

[0025] Furthermore, the microwave-assisted dissolution module is provided with a safety protection device, which includes a power monitoring sensor and a temperature sensor. When the power monitoring sensor detects that the microwave power exceeds a normal range or the temperature sensor detects that the temperature of the crystallization is higher than a set safety threshold, the protection circuit is triggered to quickly cut off the power supply of the microwave generator.

[0026] Furthermore, the risk index is calculated by the crystallization risk assessment algorithm in the treatment measure module, and the crystallization risk index is defined as R, and the calculation formula is: R = w 1 C+w 2 T+w 3 Δλ+w 4 P microwave , where C is the current crystal concentration, T is the circulating water temperature, Δλ is the wavelength deviation between the currently monitored spectrum and the standard spectrum in the non-crystallized state, and P microwave is the microwave power, w 1 、w 2 、w 3 、w 4 is the weight coefficient.

[0027] Furthermore, the setting of the light crystal concentration threshold and the heavy crystal concentration threshold in the treatment measure module is as follows: the crystal concentration data is R i , calculate its mean and standard deviation, the mean calculation formula is: The formula for calculating standard deviation is: The concentration threshold for mild crystallization is: R th1 =μ+δ 1 σ, severe crystallization concentration threshold is: R th2 =μ+δ 2 σ, where δ 1 and δ 2 It is a coefficient determined according to actual needs.

[0028] Furthermore, the chemical cleaning in the treatment measure module, through the coordinated work with the spectral monitoring module, can accurately identify the specific types of crystals, use different chemical reagents for cleaning according to different types of crystals, and automatically and accurately control the amount of chemical reagents added according to the concentration of the crystals. When the crystal concentration is low, the amount of chemical reagents added will be reduced accordingly, and when the crystal concentration is high, the amount of chemical reagents added will be reasonably increased.

[0029] Compared with the prior art, the low-temperature crystallization treatment system of the air separation unit precooling system has the following beneficial effects:

[0030] 1. The present invention uses spectral analysis technology to monitor the spectral characteristics of the circulating water in the precooling system in real time, thereby realizing a rapid and accurate judgment of the crystallization situation. Different salt crystals will have unique absorption and reflection characteristics under a specific wavelength spectrum. This characteristic is fully utilized by the present invention. By establishing a spectral database containing a large number of standard spectral data of different salt crystals under various conditions, and combining it with a high-precision spectral analysis model, the spectral data can be collected and processed in real time, and whether crystals are formed, as well as the specific type and concentration of the crystals, can be quickly identified. This function not only improves the accuracy and efficiency of monitoring, but also provides a strong basis for taking timely treatment measures, effectively avoiding the influence of crystallization on the operation of the precooling system, and ensuring the stable operation of the system.

[0031] 2. The present invention provides an efficient and environmentally friendly solution for low-temperature crystallization treatment in a pre-cooling system by adopting microwave-assisted dissolution technology. Microwaves can quickly and evenly heat the crystals to increase their internal temperature, thereby significantly accelerating the dissolution rate of crystalline salts in water. This feature not only improves the dissolution efficiency but also reduces energy consumption. At the same time, microwaves can also destroy the lattice structure of the crystals during the heating process, making them easier to dissolve, further improving the efficiency of crystal removal. This technology is not only suitable for the treatment of mild crystallization, but can also be used in combination with other methods to achieve a more thorough removal effect for severe crystallization.

[0032] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 It is a flow chart of a low temperature crystallization treatment system of a precooling system of an air separation unit;

[0035] Figure 2 It is the flow chart of the spectrum monitoring module;

[0036] Figure 3 Flow chart of the microwave-assisted dissolution module. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Embodiment 1:

[0039] Application of low temperature crystallization treatment system in precooling system of air separation unit in chemical industry:

[0040] First, a spectral monitoring module is installed in the straight pipe section of the key position of the circulating water precooling system of the chemical industry air separation unit. The module establishes a spectral database by collecting standard spectral data of different salt crystals under various conditions. For possible calcium carbonate crystals, the spectral data points at specific wavelengths (λ i ,I i ), using the function S j (λ) is used to represent its spectral characteristics, where j represents the type number of the salt, and the calculation formula is: Where j represents the type number of the salt, N j is the number of Gaussian components, A jk , μ jk and σ jkare the amplitude, mean and standard deviation of the kth Gaussian component of the jth salt crystal, respectively. Standard spectral data of calcium carbonate crystallization under various conditions are collected through laboratory experiments, simulation calculations and actual monitoring. The spectral characteristics of calcium carbonate crystallization under different conditions are predicted by algorithm formulas and verified with experimental data. Equipment is installed to collect data during actual operation. The spectral intensity of salt crystallization at a specific wavelength λ is assumed to be I(λ), which is affected by the type S, concentration C, temperature T and pressure P of the salt. The calculation formula of the spectral intensity is: I(λ)=f(S,C,T,P)=A(S)·g(C)·h(T)·k(P)+E. The collected spectral data are classified one by one according to the type of salt, and then subdivided according to the crystallization state. The database is used to store and record the condition information and spectral characteristics. The database is updated regularly, and the newly discovered spectral data of calcium carbonate crystallization is added and the existing data is updated as the environment changes. The spectral monitoring module can also dynamically update the spectral characteristics of calcium carbonate crystallization according to the spectral data monitored in real time. The spectral characteristic update function is: S new (λ)=(1-∈)S old (λ)+∈I current (λ), where ∈ is the update coefficient and the module has a remote monitoring function. The operator can view the spectral characteristics and crystallization judgment results of the circulating water in real time at the remote terminal. The spectrum monitoring module calculates the monitored spectrum I(λ) and the spectrum S of calcium carbonate crystal in the database. j (λ) to determine whether crystals are formed and the concentration of crystals. The similarity function is defined as: When the similarity exceeds a certain threshold, it is determined that calcium carbonate crystals are formed, and the concentration of the crystals is estimated based on the similarity.

[0041] When the spectrum monitoring module detects that calcium carbonate crystals are formed and the concentration is low, which is a mild crystallization, the microwave-assisted dissolution module is started, and a microwave generator with adjustable power and frequency is selected and installed in a place where microwave energy can be effectively transmitted to the crystallization area. The heating parameters are determined according to the characteristics and dissolution requirements of calcium carbonate. The mass of the crystal is M and the initial crystal concentration is C. 0 , the target crystal concentration is C t , microwave power is P, heating time is t, microwave energy conversion efficiency is η, crystal heat loss coefficient is α, assuming that the dissolution rate is proportional to the nth power of the temperature, the relationship between the temperature change and the microwave power and heating time is ΔT = βPt. According to the law of energy conservation, part of the microwave input energy is used for heating and part is lost due to heat loss. The formula is: The relationship between dissolution rate and temperature is: Combining the above temperature change relationship, we can get: Among them, k 0 is the pre-factor, Ea is the activation energy, R is the gas constant, k n It is the proportionality coefficient. The microwave power is adjusted by the microwave power adjustment factor F. The calculation formula of the microwave power adjustment factor F is F = e -α|ΔC|+β|ΔT|+γ|ΔS| , where ΔC is the difference between the current crystal concentration and the last crystal concentration, ΔT is the difference between the current temperature and the set temperature, ΔS is the difference between the current system stability index and the target stability index, α, β, γ are adjustment coefficients, and the new microwave power P new =P old F, where P old is the microwave power at the previous moment. In the microwave-assisted dissolution process, the dissolution kinetic equation is used to describe the crystal dissolution rate. The formula is: Where C is the concentration of crystals, k d (T) is the temperature-dependent dissolution rate constant, expressed using the Arrhenius equation: Among them, k 0 is the pre-factor, E a is the activation energy, R is the gas constant, where k 1 is a proportional constant, C represents the concentration of crystals, and by adjusting these parameters and calculating the equation, microwaves are used to accelerate the dissolution of calcium carbonate crystals.

[0042] When the spectral monitoring module detects the formation of calcium carbonate crystals and the concentration is high and belongs to severe crystallization, a combination of chemical cleaning and microwave cleaning is used to remove the crystals. By working in coordination with the spectral monitoring module, the specific type of crystals can be accurately identified as calcium carbonate. The amount of chemical reagent added can be automatically and accurately controlled according to the concentration of calcium carbonate crystals. When the crystal concentration is high, the amount of chemical reagent added will be reasonably increased, and combined with microwave cleaning, the calcium carbonate crystals can be further removed to ensure the normal operation of the precooling system.

[0043] Embodiment 2:

[0044] Application of low temperature crystallization treatment system in precooling system of air separation unit in steel industry:

[0045] In the precooling system of the air separation unit in the steel industry, the spectral monitoring module is also installed in the straight pipe section at the key position of the circulating water. When monitoring calcium sulfate crystallization, the spectral database establishment process is similar to that of calcium carbonate crystallization in the chemical industry. The spectral data points of calcium sulfate crystallization at a specific wavelength (λ i ,I i ), establish a spectral database and predict its spectral characteristics through algorithm formula, classify and store it and update it regularly, and calculate the monitored spectrum I(λ) and the spectrum S of calcium sulfate crystal in the database. j The similarity of (λ) is used to determine whether crystals are formed and the concentration of crystals.

[0046] For mild calcium sulfate crystallization, the microwave-assisted dissolution module is started, a suitable microwave generator is selected and installed in an effective position, and the heating parameters are determined according to the characteristics and dissolution requirements of calcium sulfate. The mass of the crystallized material is M and the initial crystal concentration is C. 0 , the target crystal concentration is C t , microwave power is P, heating time is t, microwave energy conversion efficiency is η, crystal heat loss coefficient is α, assuming that the dissolution rate is proportional to the nth power of the temperature, the relationship between the temperature change and the microwave power and heating time is ΔT = βPt. According to the law of energy conservation, part of the microwave input energy is used for heating and part is lost due to heat loss. The formula is: The relationship between dissolution rate and temperature is: Combining the above temperature change relationship, we can get Among them, k 0 is the pre-factor, E a is the activation energy, R is the gas constant, k n The microwave power adjustment factor F is used to adjust the power. The microwave energy is used to destroy the lattice structure of calcium sulfate and accelerate its dissolution. The microwave power adjustment factor F is calculated based on the ΔC, ΔT and ΔS parameters. The new microwave power P new =P old F, at the same time, using the dissolution kinetics equation To describe the dissolution rate of calcium sulfate crystals, k d (T) is the temperature-dependent dissolution rate constant, expressed using the Arrhenius equation Among them, k 0 is the pre-factor, E a is the activation energy, R is the gas constant, T is the temperature, and f(C) is the concentration-dependent function, as shown in the formula: f(C) = -k 1 C, where k 1 is a proportionality constant and C represents the concentration of crystals.

[0047] For severe calcium sulfate crystallization, a combination of chemical cleaning and microwave cleaning is adopted. First, the type of calcium sulfate crystals is accurately identified, and then the amount of chemical reagents added is reasonably controlled according to the crystal concentration. At the same time, combined with microwave cleaning, the microwave cleaning parameters are adjusted to ensure the stable operation of the pre-cooling system and avoid affecting the performance of the air separation unit due to crystallization problems.

[0048] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A low temperature crystallization treatment system for a precooling system of an air separation unit, characterized in that: The system includes: a spectrum monitoring module, a microwave-assisted dissolution module, a treatment measure module, a control unit and an alarm module; The spectrum monitoring module: selects a spectrum sensor with high sensitivity and wide wavelength range, installs it in the straight pipe section of the circulating water of the precooling system, and connects it to a high-speed data transmission interface, collects a large amount of standard spectrum data of different salt crystals under various conditions, and uses database management software to establish a spectrum database after sorting and classification and regularly updates it, builds a high-precision spectrum analysis model, trains and verifies it with a large amount of known spectrum data, and continuously optimizes the model. The spectrum sensor continuously collects data and transmits it to the analysis model for processing in real time. The analysis model quickly determines the crystallization situation. If crystals are formed, the system issues an alarm and sends the information to the control unit and the alarm module; The spectrum database in the spectrum monitoring module is established by collecting spectrum data points 9λ of different salt crystals at specific wavelengths. i ,I i ) to establish a spectral database, where λ i Indicates wavelength, I i Represents the corresponding spectral intensity. For each salt crystal, the function S j 9λ) to represent its spectral characteristics, and the calculation formula is: Where j represents the type number of the salt, N j is the number of Gaussian components, A jk , μ jk and σ jk are the amplitude, mean, and standard deviation of the kth Gaussian component of the crystallization of the jth salt, respectively; The analysis model in the spectrum monitoring module calculates the monitored spectrum I9λ) and the spectrum S of various salt crystals in the database. j (λ) to determine whether crystals are formed and the type and concentration of crystals. The similarity function D(I,S j ) is: When the similarity exceeds a certain threshold, it is determined that a corresponding type of crystal is formed, and the concentration of the crystal is estimated based on the similarity. The microwave-assisted dissolution module: selects a microwave generator with adjustable power and frequency, installs the microwave generator at a location where crystallization is likely to occur, determines heating parameters according to the characteristics of the crystal and the dissolution requirements, monitors temperature changes in real time during the heating process, dynamically adjusts the microwave power through a microwave power adjustment factor based on the real-time monitored temperature data, clarifies the quantitative relationship between microwave parameters and the degree of destruction of the crystal lattice structure through a combination of experimental and theoretical analysis, and optimizes and adjusts the microwave parameters based on the relationship between the two; The microwave-assisted dissolution module determines the heating parameters by using the microwave crystallization processing formula. Assume that the mass of the crystallized material is M, the initial crystal concentration is C0, and the target crystal concentration is C. t , microwave power is P, heating time is t, microwave energy conversion efficiency is η, crystal heat loss coefficient is α, assuming that the dissolution rate is proportional to the nth power of the temperature, the relationship between the temperature change and the microwave power and heating time is ΔT = βPt. According to the law of energy conservation, part of the microwave input energy is used for heating and part is lost due to heat loss. The formula is: The relationship between dissolution rate and temperature is: Combining the above temperature change relationship, we can get: Among them, k0 is the pre-factor, E a is the activation energy, R is the gas constant, k n is the proportionality coefficient; The microwave-assisted dissolution module adjusts the microwave power by a microwave power adjustment factor F, and the calculation formula of the microwave power adjustment factor F is: F = e -α |ΔC|+β|ΔT|+γ|ΔS|, where ΔC is the difference between the current crystal concentration and the crystal concentration at the previous moment, ΔT is the difference between the current temperature and the set temperature, ΔS is the difference between the current system stability index and the target stability index, α, β, γ are adjustment coefficients, and the new microwave power P new For: P new =P old F, where P old is the microwave power at the previous moment; The microwave-assisted dissolution module uses a dissolution kinetic equation to describe the crystal dissolution rate, and the formula is: Where C is the concentration of crystals, k d (T) is the temperature-dependent dissolution rate constant, expressed using the Arrhenius equation: Among them, k0 is the pre-factor, E a is the activation energy, R is the gas constant, T is the temperature, and f(C) is the concentration-dependent function, as given by: f(C) = -k1C, where k1 is a proportionality constant and C represents the concentration of the crystal; The treatment measure module: when the spectrum monitoring module detects the formation of crystals, the system will automatically take corresponding treatment measures according to the type and concentration of the crystals. For mild crystals, the microwave-assisted dissolution module is activated to accelerate the dissolution of the crystals by microwaves. For severe crystals, a combination of chemical cleaning and microwave cleaning is used to remove the crystals. The control unit coordinates the work of the spectrum monitoring module, the microwave-assisted dissolution module and the treatment measure module to ensure the stable operation of the entire system. The control unit automatically adjusts the monitoring frequency, microwave power and intensity of the treatment measure according to the actual situation. The alarm module: When the concentration of crystals exceeds the set safety threshold, the alarm module will sound an alarm to remind the staff to take timely measures. The alarm method adopts a combination of sound and light alarm and SMS alarm.

2. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 1 is characterized in that: The specific steps of establishing the spectrum database in the spectrum monitoring module are: (1) Collect standard spectral data of different salt crystals under various conditions through laboratory experiments, simulation calculations and actual monitoring; (2) Predict the spectral characteristics of salt crystallization under different conditions through algorithm formulas and verify them with experimental data, and install equipment to collect data during actual operation; (3) Classifying the collected spectral data by salt type, and then subdividing them by crystal state, using a database to store and record condition information and spectral characteristics; (4) Update the database regularly, add the spectral data of newly discovered salt crystals and update the existing data as the environment changes.

3. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 2 is characterized in that: The spectral monitoring model predicts the spectral characteristics of salt crystallization under different conditions through an algorithm formula. Assuming that the spectral intensity of salt crystallization at a specific wavelength λ is I(λ), it is affected by the type S, concentration C, temperature T, and pressure P of the salt. The calculation formula of the spectral intensity is: I(λ)=f(S,C,T,P)=A(S)·g(C)·h(T)·k(P)+E, where A(S) represents the influence function of the salt type on the spectral intensity, and the calculation formula is: Among them, a i and b i With salt S i The correlation coefficient, g(C), represents the influence function of concentration on spectral intensity, and the calculation formula is: g(C) = e mC , where m is the concentration influence coefficient, h(T) represents the influence function of temperature on spectral intensity, and the calculation formula is: h(T)=nT+o, where n and o are temperature influence coefficients, k(P) represents the influence function of pressure on spectral intensity, and the calculation formula is: k(P)=pP+q, where p and q are pressure influence coefficients, and E is the error term.

4. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 2 is characterized in that: The spectrum monitoring module can dynamically update the spectrum characteristics of salt crystals through an update function according to the spectrum data monitored in real time. The spectrum characteristic update function is: new (λ)=(1-∈)S old (λ)+∈I current (λ), where S old (λ) is the characteristic function of the salt crystal spectrum at the previous moment, I current (λ) is the currently monitored spectrum, and ∈ is the update coefficient.

5. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 1 is characterized in that: The spectrum monitoring module has a remote monitoring function. Through a network connection, an operator can view the spectrum characteristics and crystallization judgment results of circulating water in real time at a remote terminal.

6. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 1, characterized in that: The microwave-assisted dissolution module is provided with a safety protection device, which includes a power monitoring sensor and a temperature sensor. When the power monitoring sensor detects that the microwave power exceeds the normal range or the temperature sensor detects that the temperature of the crystallized material is higher than the set safety threshold, the protection circuit is triggered to quickly cut off the power supply of the microwave generator.

7. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 1, characterized in that: The risk index is calculated by the crystallization risk assessment algorithm in the treatment measure module, and the crystallization risk index is defined as R, and the calculation formula is: R = w1C + w2T + w3Δλ + w4P microwave , where C is the current crystal concentration, T is the circulating water temperature, Δλ is the wavelength deviation between the currently monitored spectrum and the standard spectrum in the absence of crystallization, and P microwave is the microwave power, w1, w2, w3, w4 are weight coefficients.

8. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 1, characterized in that: The setting of the light crystal concentration threshold and the heavy crystal concentration threshold in the treatment measure module is as follows: i , calculate its mean and standard deviation, the mean calculation formula is: The formula for calculating standard deviation is: The concentration threshold for mild crystallization is: R th1 =μ+δ1σ, the severe crystallization concentration threshold is: R th2 =μ+δ2σ, where δ1 and δ2 are coefficients determined according to actual needs.

9. The low temperature crystallization treatment system of the precooling system of the air separation unit according to claim 1, characterized in that: The chemical cleaning in the treatment measure module works in conjunction with the spectral monitoring module to accurately identify the specific type of crystals, use different chemical reagents for cleaning according to different types of crystals, and automatically and accurately control the amount of chemical reagents added according to the concentration of the crystals. When the crystal concentration is low, the amount of chemical reagents added will be reduced accordingly, and when the crystal concentration is high, the amount of chemical reagents added will be reasonably increased.

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