Chemical oxygen demand detection system for intermediate synthesis

Abstract

The invention discloses a chemical oxygen demand detection system for intermediate synthesis, and relates to the technical field of wastewater treatment and detection. The system monitors nitro group oxidation efficiency through the oxidation evaluation module, establishes an electron transfer enhancement model based on a density functional theory and an electron transfer theory in combination with the masking analysis module, and evaluates a signal masking condition; a signal correction module is used for carrying out multi-region synchronous acquisition, and COD signal correction is realized through verification of spatial uniformity and dynamic consistency; extracting a leading edge propagation band and dividing an effect interval through a dissipation identification module, and formulating a zoning COD signal compensation strategy; an oxidation-spectrum collaborative model is constructed through a collaborative optimization module, and real-time COD value inversion and process parameter feedback control are achieved. The nitro group concentration monitoring precision can be improved, the dissipation effect is recognized, partition compensation is carried out, and the COD detection precision and the wastewater treatment efficiency are guaranteed by combining real-time feedback optimization process parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of wastewater treatment detection, and particularly to a chemical oxygen demand detection system for intermediate synthesis. Background Art

[0002] In the field of intermediate synthesis, compounds containing nitro groups such as nitrobenzene and nitrophenol are key intermediates. The production wastewater thereof has the characteristics of complex composition and high chemical oxygen demand (COD) value, posing special challenges to the COD detection in wastewater treatment. The existing detection technologies have the following technical bottlenecks when dealing with such wastewater: Intermediate products such as nitroso and azo generated by the oxidation of nitro groups have overlapping absorption with the COD characteristic signal in the 260 nm ultraviolet region. The traditional spectral detection does not combine the electronic structure parameters and does not quantify the absorbance interference intensity through the electron transfer theory, resulting in the COD detection error caused by signal masking.

[0003] The existing technology often contains suspended particles in the intermediate synthesis wastewater, which are likely to cause particulate deposition in the inlet area and fluid stagnation in the dead volume area in the microfluidic chip reaction channel, resulting in differences in signal masking values in different regions (such as the inlet area and the middle reaction area). The traditional system does not perform collaborative analysis on the signals in independent regions such as the eddy current area and the outlet area, and cannot locate local interference sources.

[0004] Therefore, the present invention provides a chemical oxygen demand detection system for intermediate synthesis. Summary of the Invention

[0005] The purpose of the present invention is to provide a chemical oxygen demand detection system for intermediate synthesis to solve at least one of the above-mentioned existing technical problems.

[0006] A chemical oxygen demand detection system for intermediate synthesis includes the following modules: Oxidation evaluation module: During the treatment process of intermediate synthesis wastewater, monitor the oxidation efficiency of the nitro group of the target substance in the oxidation reactor, and evaluate whether the oxidation efficiency meets the detection requirements of chemical oxygen demand; Masking analysis module: If not, based on the molecular structure and oxidation potential parameters of the nitro group, establish an electron transfer enhancement model to obtain the signal masking value in the spectral detection stage, and evaluate whether the absorbance of the nitro group masks the characteristic signal; Signal correction module: If the characteristic signal is masked, synchronously collect the spectral signals in multiple regions in the microfluidic chip, and diagnose whether the spectral signal distribution is uniform; if the spectral signal distribution is uniform, obtain the spectral compensation amount and complete the COD signal correction; if the spectral signal distribution is not uniform, generate regional detection signals; Dissipation identification module: Based on the regional detection signal, the spectral signal of all regions is tested for effects, the spatial propagation characteristics of the dissipation effect between regions are identified, and a partition compensation strategy is formulated based on the spatial propagation characteristics.

[0007] As a further technical solution of the present invention: the signal masking value in the spectrum detection stage is obtained by: Obtain the absorbance A of the nitro group at an ultraviolet wavelength of 260 nm 260 , the linear correlation calculation is performed on the absorbance of the nitro group at 260nm in the ultraviolet region and the characteristic wavelength; If a linear correlation is present, the interference intensity value can be obtained by numerical analysis based on the electron transfer rate output by the electron transfer enhancement model; The interference intensity value and absorbance are analyzed for net value and characteristic value respectively to obtain characteristic absorbance ratio and interference net value ratio; The signal masking value is obtained by multiplying the characteristic absorbance ratio and the net interference value ratio.

[0008] As a further technical solution of the present invention: the method of performing net value and characteristic analysis on the interference intensity value and absorbance is as follows: Calculate the difference between the net interference intensity value and the interference intensity value to obtain the net interference value ratio; The absorbance of the nitro group at an ultraviolet wavelength of 260 nm is A 260 The characteristic absorbance ratio is obtained by ratio processing with the absorbance at the characteristic wavelength.

[0009] As a further technical solution of the present invention: the electron transfer enhancement model is constructed as follows: Get the molecular structure parameters of the nitro group; Calculate oxidation potential based on molecular structure parameters; The electron transfer rate was modeled based on the oxidation potential to obtain an electron transfer enhancement model; The electron transfer enhancement model is verified to determine the confidence level of the electron transfer enhancement model.

[0010] As a further technical solution of the present invention: the method for diagnosing whether the spectral signal distribution is uniform is: If the characteristic signal is masked, the reaction channel of the microfluidic chip is obtained and the reaction channel is divided into multiple independent detection areas, and a transparent detection window is set in each area; Obtain the signal masking value and electron transfer rate in the corresponding transparent detection window in each independent detection area, and construct a regional parameter group including the signal masking value and the electron transfer rate; Verify the spatial uniformity and kinetic consistency of the regional parameter group. If all the detection pairs in the regional parameter group meet the spatial uniformity and kinetic consistency, it is diagnosed that the spectral signal distribution is uniform.

[0011] As a further technical solution of the present invention: The method for verifying the spatial uniformity and kinetic consistency of the regional parameter group is as follows: Construct a regional detection pair, obtain the spatial uniformity value of the regional detection pair, and determine the regional spatial distribution uniformity; Among them, the method for obtaining the spatial uniformity value is as follows: Obtain any two independent detection regions to form a regional detection pair; Obtain the signal masking values of the regional detection pair in multiple monitoring periods, calculate the Pearson correlation coefficient of the signal masking values in the regional detection pair, and obtain the spatial uniformity value; Perform kinetic consistency verification based on the electron transfer model.

[0012] As a further technical solution of the present invention: The method for performing kinetic consistency verification based on the electron transfer model is as follows: Obtain the electron transfer rates of two independent detection regions of the regional detection pair in multiple monitoring periods, and calculate the mean and standard deviation of the electron transfer rates of the independent detection regions in multiple monitoring periods; Perform ratio processing on the mean and standard deviation of the electron transfer rates of the independent detection regions in multiple monitoring periods to obtain the dynamic stability value; Calculate the ratio of the difference in the dynamic stability values of the two independent detection regions within the regional detection pair to obtain the stable difference ratio; Based on the stable difference ratio, perform kinetic consistency verification on the regional detection pair.

[0013] As a further technical solution of the present invention: The method for identifying the spatial propagation characteristics of the dissipation effect between the regions is as follows: Obtain the stable difference ratio and spatial uniformity value of the adjacent region monitoring pair, and calculate the attenuation gradient of the stable difference ratio and spatial uniformity value of the adjacent region monitoring pair; Based on the attenuation gradient of the stable difference ratio and spatial uniformity value, extract the front propagation band of the dissipation effect; Take the front propagation band as the spatial propagation characteristic; Obtain the spectral curve of the spectral signal, extract the peak position offset of the spectral curve, and perform offset test to determine whether it is a real dissipation effect; If there is a real dissipation effect, based on the attenuation gradient of the stable difference ratio and spatial uniformity value, identify the effect interval of the front propagation band; Formulate a partition COD signal compensation strategy based on the effect interval.

[0014] A chemical oxygen demand (COD) detection system for intermediate synthesis further includes: A collaborative optimization module: constructs an oxidation-spectroscopy collaborative optimization model to output real-time COD values and feeds them back to the synthesis process control system.

[0015] As a further technical solution of the present invention: the method for constructing the oxidation-spectroscopy collaborative optimization model is as follows: Data fusion and establishment of an oxidation-spectroscopy coupling model; Parameter adaptive update and COD inversion calculation; COD parameter feedback control.

[0016] Advantages of the present invention: 1. The high-performance liquid chromatography method is used to collect the concentration of nitro groups, which is beneficial to reducing matrix interference and further reducing the calculation deviation rate of oxidation efficiency; by dynamically comparing the concentration deviation of the reaction nitro groups, it is evaluated whether the oxidation efficiency meets the COD detection requirements. When the oxidation efficiency deviates from the preset range, the oxidation potential is calculated, and a quantitative model of the oxidation potential and the electron transfer rate is established to characterize the oxidation reaction kinetics; the signal masking value is calculated, which can quantify the interference intensity in the spectral detection stage and provide a theoretical basis for signal correction.

[0017] 2. The reaction channels of the microfluidic chip are divided into independent detection areas. Through the Pearson correlation coefficient of the signal masking value and the dynamic stability value of the electron transfer rate analysis, the uniformity diagnosis of the spectral signal distribution is realized. For the uniform area, the spectral compensation amount is calculated based on the spatial uniformity value and the average value of the signal masking value, which is beneficial to reducing the COD detection deviation caused by the difference in the distribution of interfering substances in different regions.

[0018] 3. Through the calculation of the stable difference ratio between adjacent regions and the attenuation gradient of the spatial uniformity value, combined with the confidence interval test of the spectral peak position shift, the front propagation band of the dissipation effect is located and the effect interval is divided. Based on the gradient characteristics, different differential compensation strategies are implemented for different intervals to ensure that the deviation between the compensated spectrum and the high-performance liquid chromatography data is within a controllable range. At the same time, multi-source data such as oxidation efficiency and compensated spectrum are fused to construct an oxidation-spectroscopy coupling model and the parameters are updated online using the recursive least squares method to realize real-time inversion of the COD value. Based on the deviation between the inversion result and the target value, the process parameters are adjusted to form a closed-loop system of detection-modeling-control, which is beneficial to ensuring the coordinated operation of COD detection and wastewater treatment processes. Description of the Drawings

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0020] Figure 1 It is a module diagram of a chemical oxygen demand detection system for intermediate synthesis provided by the present invention; Figure 2 It is a flow chart for diagnosing whether the diagnostic spectral signal distribution is uniform provided by the present invention; Figure 3 It is a flow chart of a chemical oxygen demand detection method for intermediate synthesis provided by the present invention. Detailed implementation manners

[0021] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Embodiment 1

[0023] As Figure 1 shown, a chemical oxygen demand detection system for intermediate synthesis includes the following modules: Oxidation evaluation module: During the treatment process of intermediate synthesis wastewater, monitor the oxidation efficiency of the nitro group of the target substance in the oxidation reactor, and evaluate whether the oxidation efficiency meets the detection requirements of chemical oxygen demand; Among them, the method for monitoring the oxidation efficiency of the nitro group of the target substance in the oxidation reactor is: Preferably, when using high performance liquid chromatography (HLPC) to obtain the nitro group concentration during the monitoring period, first collect the wastewater sample to be treated before the start of the wastewater oxidation reaction, filter it through a 0.22 μm filter membrane, separate it with a C18 reverse phase chromatographic column, use methanol - water (such as 60:40, volume ratio) as the mobile phase, with a flow rate of 1.0 mL / min, a column temperature of 30 °C, and at a UV wavelength of 270 nm, establish a linear standard curve with standard substances such as nitrobenzene (0.1 - 10 mg / L), and calculate the initial concentration of the nitro group according to the peak area of the nitro group in the sample; collect the reaction solution at fixed monitoring times (such as 30 min and 1 h of reaction), filter it in the same way and inject it into the HPLC, maintain the same chromatographic conditions, and substitute the real-time peak area into the standard curve to obtain the nitro group concentration at the current moment; High performance liquid chromatography can reduce interference by chromatographic separation, which is beneficial to improving the monitoring accuracy of the nitro group concentration; Obtain the initial concentration of the nitro group and the concentration of the nitro group at the fixed monitoring time, calculate the deviation ratio of the initial concentration of the nitro group and the concentration of the nitro group at the current moment, and obtain the oxidation efficiency of the nitro group; Compare the oxidation efficiency of the nitro group with a preset range value. If the oxidation efficiency of the nitro group is within the preset range value, continuously monitor the oxidation efficiency of the nitro group; If the oxidation efficiency of the nitro group is not within the preset range value, it is determined that the oxidation efficiency does not meet the detection requirements of chemical oxygen demand.

[0024] Masking analysis module: If not satisfied, based on the molecular structure and oxidation potential parameters of the nitro group, establish an electron transfer enhancement model to obtain the signal masking value in the spectral detection stage, and evaluate whether the absorbance of the nitro group masks the characteristic signal; Among them, the method of establishing an electron transfer enhancement model based on the molecular structure and oxidation potential parameters of the nitro group is as follows: S201. Obtain the molecular structure parameters of the nitro group through density functional theory; Preferably, perform geometric structure optimization and frequency analysis on the nitro group (such as nitrobenzene, nitrophenol); obtain the stable configuration by minimizing the energy, and obtain geometric parameters such as bond length, bond angle, and dihedral angle, as well as electronic structure parameters such as molecular orbital energy level, charge distribution, and dipole moment; The geometric parameters and electronic structure parameters are the basis for subsequent oxidation potential calculations, and directly reflect the electron delocalization ability and steric hindrance characteristics of the molecule; S202. Calculate the oxidation potential based on the molecular structure parameters; Preferably, based on the stable configuration obtained in S1, calculate the ionization energy (IE) within the monitoring period, and derive the oxidation potential in combination with the thermodynamic cycle method; Exemplarily, for the oxidation process , calculate the gas-phase ionization energy IE through density functional theory (DFT). The ionization energy refers to the energy required to absorb 1 electron in the gas phase to form an ion; Among them, M represents a neutral gaseous atom or molecule, which is the reactant in the ionization process; is the gaseous monovalent positive ion formed after M loses 1 electron, which is the product in the ionization process, and e - is an electron; Use the solvation model (such as PCM) to correct the solvent effect, and use the formula: to obtain the oxidation potential ; Among them, n is the number of electron transfers, F is the Faraday constant, is the standard hydrogen electrode reference potential; S203. Perform electron transfer rate modeling based on the oxidation potential to obtain an electron transfer enhancement model; Preferably, adopt Marcus electron transfer theory, and use the oxidation potential Associated with the electron transfer rate constant Associated; Exemplarily, through the Marcus equation: Obtain the electron transfer rate ke; Wherein, Is the redox potential difference between the reactant and the product, Is the reorganization energy, V is the electron coupling matrix element, Is the reduced Planck constant, Is the Boltzmann constant, T is the absolute temperature, π is the pi; Verify the electron transfer enhancement model S204 and judge the confidence level of the electron enhanced transfer model; Preferably, measure the oxidation potential of the nitro compound by cyclic voltammetry (CV), calculate the deviation rate between the measured oxidation potential of the nitro compound and the oxidation potential of S2. If the deviation rate ≤ 5%, it meets the requirements; Use ultraviolet-visible spectroscopy or an electrochemical workstation to monitor the current-time curve in the oxidation reaction, obtain the experimental electron transfer rate Kse, compare it with the predicted value of the S3 model, and calculate the determination coefficient while the determination coefficient > 0.9; Wherein, to predict the signal interference intensity in the spectral detection stage and evaluate whether the absorbance of the nitro group masks the characteristic signal, the method is: Through the formula: Obtain the absorbance A of the nitro group at the ultraviolet wavelength of 260 nm 260 ; Wherein, Is the optical path of the cuvette, Are the extinction coefficient at 260 nm and the residual concentration of the nitro group respectively; Perform a linear correlation calculation on the absorbance of the nitro group at 260 nm in the ultraviolet region and the characteristic wavelength of 600 nm. If a linear correlation relationship is presented, then obtain the interference intensity value ; Preferably, through the formula: Obtain the interference intensity value ; Wherein, Is the preset mapping coefficient, Is the optical path, Is the reaction time; Through the double-wavelength subtraction method, introduce the reference wavelength and calculate the net interference intensity value ; Preferably, the reference wavelength is 580 nm; Calculate the difference ratio of the net interference intensity value and the interference intensity value to obtain the net interference ratio; Obtain the absorbance at a characteristic wavelength of 600 nm and the absorbance A of the nitro group at an ultraviolet wavelength of 260 nm. 260 ; Take the ratio of the absorbance A of the nitro group at an ultraviolet wavelength of 260 nm 260 and the absorbance at a characteristic wavelength of 600 nm to obtain a characteristic absorbance ratio; Multiply the characteristic absorbance ratio by the interference net ratio to obtain a signal masking value; It can be understood that the signal masking value can quantify the interference intensity of the nitro group absorbance on the COD characteristic signal. The signal masking value is obtained through the ratio of the absorbance of the nitro group in the 260 nm ultraviolet region (A260) to the absorbance at the COD characteristic wavelength (600 nm), combined with the interference net ratio calculated by the dual-wavelength subtraction method, and quantitatively characterizes the overlapping absorption degree of the nitro group on the COD characteristic signal when it is not completely oxidized. The magnitude of the signal masking value directly reflects the masking degree of the nitro group absorbance on the 600 nm characteristic signal. For example, when the signal masking value > 1, it indicates that the characteristic signal is significantly masked by the 260 nm absorbance interference, and the COD detection value will deviate from the true value; The signal masking value can correlate the oxidation reaction process with the electron transfer efficiency. The calculation of the signal masking value is based on the electron transfer enhancement model, thereby revealing the essential reason why the oxidation efficiency does not meet the COD detection requirements; Based on the signal masking value, perform characteristic signal masking determination; Exemplarily, the method for performing characteristic signal masking determination is as follows: If the signal masking value > 1, determine that the characteristic signal is masked; If the signal masking value ≤ 1, further verify in combination with the linear correlation coefficient of the absorbances at 260 nm and 600 nm. If the correlation coefficient is higher than 0.7, continuously monitor the change of the signal masking value.

[0025] It can be understood that the role of judging whether the nitro group absorbance masks the characteristic signal is as follows: Role 1: By calculating the linear correlation and interference net ratio between the absorbance of the nitro group in the 260 nm ultraviolet region and the COD characteristic wavelength (600 nm), quantify the masking degree of the nitro group on the characteristic signal, reduce the distortion of the COD detection value caused by absorbance overlap, and enable the detection result to reflect the oxidation state of organic matter in the wastewater; Role 2: Based on the signal masking value, determine whether the characteristic signal is masked, providing a quantitative basis for subsequent spectral signal correction, enabling the COD signal compensation coefficient in each region of the microfluidic chip to be dynamically adjusted according to the masking degree, and improving the detection accuracy; Function 3: Combine with the electron transfer enhancement model (established based on the molecular structure and oxidation potential parameters of nitro groups), correlate the degree of absorbance masking with the oxidation reaction kinetics, and assist in judging whether the oxidation reaction process meets the detection requirements. If the masking value is abnormal, it can be fed back to the oxidation evaluation module to guide the adjustment of the oxidant dosage or reaction time.

[0026] Example 2

[0027] As Figure 1 shown, a chemical oxygen demand detection system for intermediate synthesis includes the following modules: Signal correction module: If the characteristic signal is masked, multi-region synchronous acquisition of the spectral signal in the microfluidic chip is performed to diagnose whether the spectral signal distribution is uniform; if the spectral signal distribution is uniform, the spectral compensation amount is obtained to complete the COD signal correction; if the spectral signal distribution is not uniform, a regional detection signal is generated. Among them, the diagnostic method for whether the spectral signal distribution is uniform is: If the characteristic signal is masked, the reaction channel of the microfluidic chip is obtained, and the reaction channel is divided into multiple independent detection regions, and transparent detection windows are set in each region. Exemplarily, the reaction channel is divided into an inlet region, a middle reaction region, an outlet region, a dead volume region, and an eddy current region. Obtain the signal masking value and electron transfer rate in the corresponding transparent detection window in each independent detection region, and construct a regional parameter group including the signal masking value and electron transfer rate. Verify the spatial uniformity and kinetic consistency of the regional parameter group to diagnose whether the spectral signal distribution is uniform. Among them, the method for verifying the spatial uniformity and kinetic consistency of the regional parameter group is: S301: Construct a regional detection pair, obtain the spatial uniformity value of the regional detection pair, and determine the regional spatial distribution uniformity. Obtain any two independent detection regions to form a regional detection pair. Obtain the signal masking values of the regional detection pair in multiple monitoring periods, calculate the Pearson correlation coefficient of the signal masking values in the regional detection pair, and obtain the spatial uniformity value. It should be explained that the spatial uniformity value is a quantitative index obtained by calculating the Pearson correlation coefficient of the signal masking values of any two independent detection regions in the reaction channel of the microfluidic chip. Its physical meaning is to characterize the spatial consistency of the spectral signal masking characteristics in different regions. The higher the correlation coefficient, the stronger the linear correlation of the signal masking values in each region, and the better the uniformity of the spatial distribution of interference factors such as the absorbance of nitro groups; on the contrary, it reflects significant differences in the interference distribution between regions (such as high local masking values caused by particulate deposition in the inlet region), providing a key basis for diagnosing non-uniform spectral signal distribution. Preferably, the multiple monitoring periods refer to the number of monitoring periods being greater than 5; Exemplarily, the method for determining the spatial distribution uniformity based on the spatial uniformity value is as follows: Calculate the signal masking value S of any two regions i and j i and the signal masking value S j Pearson correlation coefficient of : where i and j are the numbers of independent detection regions respectively, S is the signal masking value, and S i represents the signal masking value of the independent detection region with the number i; If , then the regional signal masking characteristics of the regional detection pair are independent and the distribution is non-uniform; If , then the signal characteristics of the regional detection pair are similar and the distribution tends to be uniform; S302. Perform kinetic consistency verification based on the electron transfer model; Obtain the electron transfer rates of two independent detection regions of the regional detection pair within multiple monitoring periods, and calculate the mean and standard deviation of the electron transfer rates of the independent detection regions in multiple monitoring periods; Perform ratio processing on the mean and standard deviation of the electron transfer rates of the independent detection regions in multiple monitoring periods to obtain the dynamic stability value; Calculate the ratio of the difference in the dynamic stability values of two independent detection regions within the regional detection pair to obtain the stable difference ratio; Preferably, the multiple monitoring periods refer to the number of monitoring periods being greater than 5; Based on the stable difference ratio, perform kinetic consistency verification on the regional detection pair; It can be understood that the stable difference ratio characterizes the degree of consistency of the kinetic characteristics of the oxidation reaction in different regions. The smaller the ratio, the smaller the stability difference in the electron transfer rate between regions, and the higher the mass transfer efficiency and the uniformity of the reaction environment; on the contrary, it reflects significant kinetic characteristic differences between regions (such as different fluctuation amplitudes of the electron transfer rate in the strong effect region and the weak effect region), providing a judgment basis at the kinetic level for identifying the spatial propagation characteristics of the dissipation effect (such as parameter mutations in the front propagation band); If the stable difference ratio of the regional detection pair meets the preset difference stability interval, it is considered that the regional detection pair meets the kinetic consistency, otherwise it does not; As Figure 2 shown, if all regional detection pairs in the regional parameter group meet the spatial uniformity and kinetic consistency, it is diagnosed that the spectral signal distribution is uniform; If there are all regional detection pairs in the regional parameter group and not all meet the spatial uniformity and kinetic consistency, it is diagnosed that the spectral signal distribution is non-uniform, there is a potential dissipation effect and a regional detection signal is generated; Among them, if the spectral signal is evenly distributed, the method for obtaining the spectral compensation amount and completing the COD signal correction is as follows: Through the equation: Obtain the spectral compensation coefficient K; Among them, , are the mean value of the spatial uniformity value and the mean value of the signal masking value for all area detections, respectively; Through the formula: Obtain the spectral compensation amount ; It should be explained that the measurement of chemical oxygen demand (COD) depends on the electron transfer rate of the redox reaction. The reaction environment in the area with uneven characteristic signals is different, resulting in a deviation in the electron transfer rate and causing an error in the chemical oxygen demand; When the spectral signal is uneven, the distribution of interfering substances (such as turbidity, chromaticity or non-specific light-absorbing substances) in different regions of the reaction channel is significantly different, resulting in local masking of the characteristic light-absorbing signal (such as the absorption of organic matter at a wavelength of 260 nm); for example, if there is particulate deposition in the inlet area, its signal masking value is higher than that in the middle reaction area, causing the overall COD signal to be overestimated or underestimated; It can be understood that the role of judging whether the spectral signal is evenly distributed is as follows: Role 1: Through the collaborative analysis of the signal masking value in multiple regions and the electron transfer rate, judge the spatial distribution consistency of the spectral signal in the reaction channel of the microfluidic chip, provide a decision basis for the spectral compensation strategy. If the signal is evenly distributed, a unified compensation amount can be calculated based on the mean value of the full-area parameters to avoid compensation deviation caused by regional differences; Role 2: When the spectral signal is unevenly distributed, generate detection signals containing the characteristics of each region, provide raw data support for the dissipation identification module, and extract the spatial propagation characteristics of the dissipation effect by locating the signal mutation region (such as the parameter difference between the inlet area and the eddy current area); Role 3: Combine the dual verification of spatial uniformity and kinetic consistency to quantify the influence degree of the distribution difference of interfering substances in the reaction channel on the COD signal, correct the systematic overestimation or underestimation of the detection value caused by local masking (such as abnormal absorbance caused by fluid stagnation in the dead volume area), and ensure the reliability of the COD detection result.

[0028] Dissipation identification module: Based on the regional detection signal, perform an effect test on the spectral signals of all regions, identify the spatial propagation characteristics of the dissipation effect between regions, and formulate a zoning compensation strategy based on the spatial propagation characteristics; Among them, the method for performing an effect test on the spectral signals of all regions and identifying the spatial propagation characteristics of the dissipation effect between regions is as follows: Obtain the stable difference ratio and spatial uniformity value of adjacent area monitoring pairs, and calculate the attenuation gradient of the stable difference ratio and spatial uniformity value of adjacent area monitoring pairs; It should be noted that the stable difference ratio gradient of adjacent areas is positive and increasing, indicating that the dissipation effect propagates from high-stability areas to low-stability areas; Based on the attenuation gradient of the stable difference ratio and spatial uniformity value, extract the front propagation band of the dissipation effect; Preferably, when the dissipation effect propagates, the stable difference ratio and spatial uniformity value in the front area will mutate. By setting the gradient threshold, locate the area where the parameter change is the most significant to obtain the front propagation band; Take the front propagation band as the spatial propagation feature; Obtain the spectral curve of the spectral signal, extract the peak position offset of the spectral curve, and conduct an offset test to determine whether it is a real dissipation effect; If there is a real dissipation effect, based on the attenuation gradient of the stable difference ratio and spatial uniformity value, identify the effect interval of the front propagation band; It can be understood that baseline correction and denoising preprocessing are performed on the spectral signal. The characteristic peak position is extracted by the second derivative method, and the peak position difference between the current spectrum and the reference spectrum is calculated). And based on historical data or blank samples, a confidence interval for peak position fluctuations is established (such as mean ± 3 times the standard deviation). If the offset exceeds this interval, it is determined as a real dissipation effect; Confirm the existence of a real effect, calculate the attenuation gradient of the stable difference ratio and spatial uniformity value of adjacent areas, divide the continuous area where the absolute value of the gradient exceeds the dynamic threshold into the front propagation band, and then according to the relationship between the gradient attenuation rate and the spatial position, divide the front band and its adjacent areas into a strong effect area and a weak effect area to complete the identification of the effect interval; Formulate a partitioned COD signal compensation strategy based on the effect interval; Preferably, first match the corresponding compensation model according to the gradient characteristics of the effect interval, adopt gradient inversion gain compensation for the strong effect area, calculate the signal attenuation ratio through the stable difference ratio, and correct the spectral compensation coefficient in combination with the spatial uniformity value; The weak effect area adopts linear interpolation smoothing compensation to generate a smoothing compensation curve based on the parameter gradient of adjacent areas; determine the spectral deformation mode through the peak position offset amount, and then apply differential compensation to each area within the front band according to the gradient direction (such as a compensation coefficient of 1.5 at the front center and 1.2 at the edge). Finally, verify through the deviation rate between the compensated spectrum and the high-performance liquid chromatography data (deviation ≤ 5%) to optimize the strategy.

[0029] Example III

[0030] Such as Figure 1 shown, a chemical oxygen demand detection system for intermediate synthesis includes the following modules: Synergistic optimization module: Construct an oxidation-spectroscopy synergistic optimization model to output the real-time COD value and feedback it to the synthesis process control system; Among them, the method for constructing the oxidation-spectroscopy synergistic optimization model is as follows: S501. Data fusion and establishment of oxidation-spectroscopy coupling model; Preferably, based on the oxidation efficiency of nitro groups, the corrected spectral signal, and the partition compensation parameter, eliminate the dimension difference through standardization processing, remove abnormal data, and establish a unified data matrix; Describe the oxidation rate of nitro groups through the Michaelis-Menten equation, and establish the mapping relationship between absorbance, signal masking value, and COD by combining partial least squares regression; S502. Parameter adaptive update and COD inversion calculation; Preferably, after each new nitro group concentration data is collected, adjust the weight of historical data through the forgetting factor, calculate the gain matrix, and iteratively optimize the model coefficients to adapt to the fluctuation of wastewater quality; Input the current spectral signal and oxidation efficiency data, calculate the real-time COD value through the oxidation-spectroscopy coupling model, compare with the off-line detection result of high performance liquid chromatography (HPLC), if the deviation > 5%, trigger the self-correction of the model; S503. COD parameter feedback control; It can be understood that based on the deviation between the real-time COD value and the target value, adjust the adjustment parameters such as the dosage of oxidant and reaction time, implement partition control for the strong and weak effect regions, and optimize the control parameters through genetic algorithm to balance the COD removal rate and energy consumption.

[0031] Example 4

[0032] Such as Figure 3 shown, a method for detecting chemical oxygen demand in the synthesis of intermediates includes the following steps: S1. During the treatment of intermediate synthesis wastewater, monitor the oxidation efficiency of the nitro groups of the target substances in the oxidation reactor, and evaluate whether the oxidation efficiency meets the detection requirements of chemical oxygen demand; S2. If not, based on the molecular structure and oxidation potential parameters of nitro groups, establish an electron transfer enhancement model to obtain the signal masking value in the spectral detection stage, and evaluate whether the absorbance of nitro groups masks the characteristic signal; S3. If the characteristic signal is masked, perform multi-region synchronous acquisition of the spectral signal in the microfluidic chip, and diagnose whether the spectral signal distribution is uniform; if the spectral signal distribution is uniform, obtain the spectral compensation amount and complete the COD signal correction; if the spectral signal distribution is not uniform, generate a regional detection signal; S4. Based on the regional detection signals, conduct effect tests on the spectral signals of all regions, identify the spatial propagation characteristics of the dissipation effect among regions, and formulate a zoning compensation strategy based on the spatial propagation characteristics; S5. Construct an oxidation-spectroscopy collaborative optimization model to output the real-time COD value and feedback it to the synthesis process control system.

[0033] The above has described in detail an embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.

Claims

1. A chemical oxygen demand detection system for intermediate synthesis, characterized in that, It includes the following modules: Oxidation evaluation module: During the treatment of intermediate synthesis wastewater, monitor the oxidation efficiency of the nitro group of the target substance in the oxidation reactor, and evaluate whether the oxidation efficiency meets the detection requirements of chemical oxygen demand; Masking analysis module: If not, based on the molecular structure and oxidation potential parameters of the nitro group, establish an electron transfer enhancement model to obtain the signal masking value in the spectral detection stage, and evaluate whether the absorbance of the nitro group masks the characteristic signal; Signal correction module: If the characteristic signal is masked, synchronously collect the spectral signals in multiple regions of the microfluidic chip to diagnose whether the spectral signal distribution is uniform; if the spectral signal distribution is uniform, obtain the spectral compensation amount to complete the COD signal correction; if the spectral signal distribution is not uniform, generate regional detection signals; Dissipation identification module: Based on the regional detection signals, conduct effect tests on the spectral signals in all regions to identify the spatial propagation characteristics of the dissipation effect between regions, and formulate a partition compensation strategy based on the spatial propagation characteristics.

2. The chemical oxygen demand detection system for intermediate synthesis according to claim 1, characterized in that, The method for obtaining the signal masking value in the spectral detection stage is as follows: Obtain the absorbance A of the nitro group at the ultraviolet wavelength of 260 nm 260 , perform a linear correlation calculation on the absorbance of the nitro group at 260 nm in the ultraviolet region and the characteristic wavelength; If a linear correlation exists, perform numerical analysis by combining the electron transfer rate output by the electron transfer enhancement model to obtain the interference intensity value; Perform net value and characteristic analysis on the interference intensity value and absorbance respectively to obtain the characteristic absorption ratio and interference net value ratio; Multiply the characteristic absorption ratio by the interference net value ratio to obtain the signal masking value.

3. The chemical oxygen demand detection system for intermediate synthesis according to claim 2, wherein The method for performing net value and characteristic analysis on the interference intensity value and absorbance respectively is as follows: Calculate the difference ratio of the net interference intensity value to the interference intensity value to obtain the interference net value ratio; The absorbance A of the nitro group at an ultraviolet wavelength of 260 nm 260 is ratio-processed with the absorbance at the characteristic wavelength to obtain a characteristic absorbance ratio.

4. The chemical oxygen demand detection system for intermediate synthesis according to claim 2, characterized in that, The construction method of the electron transfer enhancement model is as follows: Obtain the molecular structure parameters of the nitro group; Calculate the oxidation potential based on the molecular structure parameters; Build an electron transfer rate model based on the oxidation potential to obtain the electron transfer enhancement model; Verify the electron transfer enhancement model to judge the confidence level of the electron transfer enhancement model.

5. The chemical oxygen demand detection system for intermediate synthesis according to claim 1, characterized in that, The method for diagnosing whether the spectral signal distribution is uniform is as follows: If the characteristic signal is masked, obtain the reaction channel of the microfluidic chip, divide the reaction channel into multiple independent detection regions, and set transparent detection windows in each region; Obtain the signal masking value and electron transfer rate in the corresponding transparent detection window in each independent detection region, and construct a regional parameter group including the signal masking value and electron transfer rate; Verify the spatial uniformity and kinetic consistency of the regional parameter group. If all region detections in the regional parameter group meet the spatial uniformity and kinetic consistency, diagnose that the spectral signal distribution is uniform.

6. The chemical oxygen demand detection system for intermediate synthesis according to claim 5, characterized in that, The method for verifying the spatial uniformity and kinetic consistency of the regional parameter group is as follows: Construct regional detection pairs, obtain the spatial uniformity value of the regional detection pairs and judge the regional spatial distribution uniformity; Among them, the method for obtaining the spatial uniformity value is as follows: Obtain any two independent detection regions to form a regional detection pair; Obtain the signal masking values of the regional detection pairs in multiple monitoring periods, calculate the Pearson correlation coefficient of the signal masking values in the regional detection pairs to obtain the spatial uniformity value; Conduct kinetic consistency verification based on the electron transfer model.

7. The chemical oxygen demand detection system for intermediate synthesis according to claim 6, characterized in that, The method for conducting kinetic consistency verification based on the electron transfer model is as follows: Obtain the electron transfer rates of two independent detection regions of the regional detection pair within multiple monitoring cycles, and calculate the mean and standard deviation of the electron transfer rates of the independent detection regions in multiple monitoring cycles; Perform a ratio process on the mean and standard deviation of the electron transfer rates of the independent detection regions in multiple monitoring cycles to obtain the dynamic stability value; Calculate the proportion of the difference in the dynamic stability values of the two independent detection regions within the regional detection pair to obtain the stability difference ratio; Based on the stability difference ratio, perform kinetic consistency verification on the regional detection pair.

8. The chemical oxygen demand detection system for intermediate synthesis according to claim 1, characterized in that, The method for identifying the spatial propagation characteristics of the dissipation effect between the regions is: Obtain the stability difference ratio and spatial uniformity value of the adjacent region monitoring pair, and calculate the attenuation gradient of the stability difference ratio and spatial uniformity value of the adjacent region monitoring pair; Based on the attenuation gradient of the stability difference ratio and spatial uniformity value, extract the front propagation band of the dissipation effect; Take the front propagation band as the spatial propagation characteristic; Obtain the spectral curve of the spectral signal, extract the peak position shift of the spectral curve, and perform shift inspection to determine whether it is a true dissipation effect; If there is a true dissipation effect, based on the attenuation gradient of the stability difference ratio and spatial uniformity value, identify the effect interval of the front propagation band; Formulate a partitioned COD signal compensation strategy based on the effect interval.

9. The chemical oxygen demand detection system for intermediate synthesis according to claim 1, wherein It also includes: Cooperative optimization module: Construct an oxidation-spectroscopy cooperative optimization model to output the real-time COD value and feedback it to the synthesis process control system.

10. The chemical oxygen demand detection system for intermediate synthesis according to claim 9, characterized in that, The method for constructing the oxidation-spectroscopy cooperative optimization model is: Data fusion and establishment of an oxidation-spectroscopy coupling model; Parameter adaptive update and COD inversion calculation; COD parameter feedback control.

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