Establishment method of near infrared spectrum off-line analysis model and method for measuring content of tricyclopentadiene in polydicyclopentadiene synthesis process

Abstract

The invention provides a method for establishing a near infrared spectrum off-line analysis model and a method for measuring the content of tricyclopentadiene in a polydicyclopentadiene synthesis process, and belongs to the technical field of analysis and detection. The method comprises the following steps: collecting reaction liquid at a sampling point to obtain a sample; respectively carrying out gas chromatographic analysis and near-infrared detection on the samples to obtain a measured value of the content of tricyclopentadiene in each sample and a near-infrared spectrogram of each sample; carrying out association and model optimization on the measured values of the tricyclopentadiene content in part of the samples and the near infrared spectrograms of the corresponding samples to obtain a to-be-verified model; and verifying the to-be-verified model through the residual samples to finally obtain the near infrared spectrum off-line analysis model. The near infrared spectrum off-line analysis model is established by adopting the method disclosed by the invention, the rapid and accurate detection of the TCPD content can be realized, and the rapid quality screening requirement in the PDCPD production process is met.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of analytical detection technology, in particular to a method for establishing a near-infrared spectroscopy offline analysis model and a method for determining the content of tricyclopentadiene in a polydicyclopentadiene synthesis process. BACKGROUND

[0002] Polydicyclopentadiene (PDCPD) is a high molecular polymer polymerized by metal catalysis through olefin metathesis reaction of dicyclopentadiene (DCPD) purified from petrochemical by-products C5 fraction and C9 fraction, and is a new type of thermosetting resin. PDCPD has high bending modulus and high impact strength, belongs to ductile material mainly in elastic deformation, and also has excellent properties such as wear resistance, surface finishing, acid and alkali resistance, and water resistance, and is widely used in automobile parts, engineering machinery shells and other fields.

[0003] DCPD is solid at room temperature, and TCPD is generated in the process of preparing PDCPD from DCPD as raw material. TCPD has a similar structure to DCPD, and the presence of TCPD can keep the raw material system in a liquid state, greatly improving the processability of the raw material. And the molecular weight of TCPD is larger than that of DCPD, and the rigidity is stronger. Copolymerization of TCPD and DCPD can significantly improve the rigidity of the obtained copolymer, while retaining excellent properties such as acid and alkali resistance and fatigue resistance. However, in the actual production process of PDCPD, too low TCPD content will cause the freezing point of the raw material system to decrease, and too high TCPD content will affect the copolymerization effect, so it is particularly important to accurately and quickly determine the TCPD content in the PDCPD synthesis process.

[0004] The related TCPD content determination methods are mainly gas chromatography (GC) and high performance liquid chromatography (HPLC), which are accurate in quantification, but have obvious defects such as complicated sample pretreatment, long detection period (30-60 min / time), consumption of organic solvents and generation of waste liquid, and dependence on professional personnel, which is difficult to meet the demand of rapid quality screening in the PDCPD production process. SUMMARY

[0005] The purpose of the present application is to provide a method for establishing a near-infrared spectroscopy offline analysis model and a method for determining the content of tricyclopentadiene in a polydicyclopentadiene synthesis process. The method for establishing a near-infrared spectroscopy offline analysis model can realize rapid and accurate detection of TCPD content and meet the demand of rapid quality screening in the PDCPD production process.

[0006] In order to achieve the above-mentioned purpose of the application, the present application provides the following technical solutions: The present application provides a method for establishing a near-infrared spectroscopy offline analysis model, comprising the following steps: The reaction solution was collected at the sampling points to obtain the sample; the sampling points were different time points in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction; the reaction solution was the reaction solution in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction. The samples were subjected to gas chromatography and near-infrared spectroscopy to obtain the measured value of tricyclopentadiene content and the near-infrared spectrum of each sample. The measured values ​​of tricyclopentadiene content in some samples were correlated with the near-infrared spectra of the corresponding samples, and the model was optimized to obtain the model to be verified. The near-infrared spectra of the remaining samples are imported into the model to be validated to obtain the predicted value of tricyclopentadiene content. The predicted value of tricyclopentadiene content is compared with the measured value of tricyclopentadiene content in the corresponding samples. When the percentage of samples with an absolute value of the relative deviation between the predicted value and the measured value of <3% accounts for ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained. When the percentage of samples with a relative deviation between the predicted value and the measured value of ≥3% accounts for >10% of the remaining samples, the model optimization method is adjusted until the percentage of samples with an absolute value of the relative deviation between the predicted value and the measured value of <3% accounts for ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained.

[0007] Preferably, the number of batches for preparing the polydicyclopentadiene is 2 to 4; when preparing each batch of polydicyclopentadiene, the number of sampling points is 2 to 5, and the number of samples collected at each sampling point is 8 to 12.

[0008] Preferably, the first sampling point is 2.5 to 3.5 hours after the start of the polymerization reaction, the remaining sampling points are spaced 1.5 to 2.5 hours apart from the previous sampling point, and the last sampling point is spaced <1 hour apart from the end of the polymerization reaction.

[0009] Preferably, the number of the partial samples is 80-90% of the total number of samples.

[0010] Preferably, the method for establishing the model to be verified includes the following steps: The measured values ​​of tricyclopentadiene content in some samples and the corresponding near-infrared spectra of the samples are input into the software; each near-infrared spectrum input into the software is sequentially processed by derivatives and smoothed, and then the band interface is selected to obtain the processed near-infrared spectrum; the measured values ​​of tricyclopentadiene content input into the software are correlated with the processed near-infrared spectrum to obtain an initial model; the initial model is optimized to obtain the model to be verified.

[0011] Preferably, the software is TQ Analyst EZ Edition software; the derivative processing includes first-order derivative processing or second-order derivative processing; the smoothing processing is Norris smoothing processing; and the selection criterion for the band interface is absorbance ≤3.

[0012] Preferably, the correlation method is a partial least squares regression quantitative method; the optimization method includes one or more of the following methods: removing outlier data, cross-validation, and changing the derivative and band range.

[0013] Preferably, the gas chromatographic analysis conditions include: using a Shimadzu GC2010 Plus gas chromatograph; an injection port temperature of 250~300℃; using split injection with a split ratio of 20:1; a column model of HP-5ms with dimensions of 30m×0.25mm×0.25μm; a column temperature program of: initial column oven temperature of 50~100℃, holding for 2 min, increasing to 250~300℃ at a rate of 10℃ / min, holding for 10 min, and then increasing to 300~330℃ at a rate of 10℃ / min; an FID detector with a detector temperature of 330℃; and nitrogen as the carrier gas. The near-infrared detection conditions include: a cuvette with a measurement range of 1 mm; 32 scans; and a resolution of 8.0 cm for each scan. -1 The spectral frequency range for each scan is 4000~1000 cm⁻¹. -1 .

[0014] This invention provides the application of the near-infrared spectroscopy offline analysis model established by the above-described technical solution in the quality control of polydicyclopentadiene chemical production.

[0015] This invention provides a method for determining the tricyclopentadiene content in the synthesis process of polydicyclopentadiene, comprising the following steps: The reaction solution was subjected to near-infrared detection to obtain a near-infrared spectrum; the reaction solution was the reaction solution in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction. The near-infrared spectrum is substituted into the near-infrared spectroscopy offline analysis model to obtain the content of tricyclopentadiene in the reaction solution; the near-infrared spectroscopy offline analysis model is the near-infrared spectroscopy offline analysis model established by the method described in the above technical solution.

[0016] Beneficial Effects: Near-infrared spectroscopy offers advantages such as rapid detection, no sample pretreatment required, simple operation, and no reagent consumption. This invention, based on near-infrared spectroscopy, provides a simple and stable method for establishing an offline near-infrared spectral analysis model. Specifically, it acquires data by collecting near-infrared spectra of samples and establishes a correlation model between TCPD content and near-infrared spectra, thereby achieving rapid and accurate detection of TCPD content and meeting the needs of rapid quality screening in PDCPD production. Results show that the model established using this method has an RMSEC value of 0.266–0.275 and a Corr.Coeff value of 0.9988–0.9989. When this model is used to determine the TCPD content in the PDCPD synthesis process, the number of samples with an absolute value of the relative deviation between the predicted and measured values ​​<3% accounts for 100% of the remaining samples, demonstrating accurate determination of the TCPD content in the PDCPD synthesis process. Attached Figure Description

[0017] Figure 1 This is a gas chromatogram of one of the samples used to establish the model to be verified in Example 1; Figure 2 The near-infrared spectra of the 50 samples used to establish the model to be verified in Example 1; Figure 3 The near-infrared spectra of 50 samples after first-order derivative processing were performed during the establishment of the model to be verified in Example 1. Figure 4 The near-infrared spectra of 50 samples were processed sequentially with first-order derivatives and Norris smoothing during the establishment of the model to be verified in Example 1. Figure 5 This is a result diagram of the model to be verified in Example 1; Figure 6 The result diagram is shown for the model to be verified in Example 2. Detailed Implementation

[0018] This invention provides a method for establishing an offline near-infrared spectroscopy analysis model, comprising the following steps: The reaction solution was collected at the sampling points to obtain the sample; the sampling points were different time points in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction; the reaction solution was the reaction solution in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction. The samples were subjected to gas chromatography and near-infrared spectroscopy to obtain the measured value of tricyclopentadiene content and the near-infrared spectrum of each sample. The measured values ​​of tricyclopentadiene content in some samples were correlated with the near-infrared spectra of the corresponding samples, and the model was optimized to obtain the model to be verified. The near-infrared spectra of the remaining samples are imported into the model to be validated to obtain the predicted value of tricyclopentadiene content. The predicted value of tricyclopentadiene content is compared with the measured value of tricyclopentadiene content in the corresponding samples. When the percentage of samples with an absolute value of the relative deviation between the predicted value and the measured value of <3% accounts for ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained. When the percentage of samples with a relative deviation between the predicted value and the measured value of ≥3% accounts for >10% of the remaining samples, the model optimization method is adjusted until the percentage of samples with an absolute value of the relative deviation between the predicted value and the measured value of <3% accounts for ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained.

[0019] In this invention, unless otherwise specified, all raw materials used are commercially available products well known to those skilled in the art or prepared using methods well known to those skilled in the art.

[0020] This invention collects reaction liquid at sampling points to obtain samples. In this invention, the sampling points are different time points in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization, and the reaction liquid is the reaction liquid in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization. As one embodiment of this invention, dicyclopentadiene, a first tackifier, a second tackifier, and an antioxidant are mixed and polymerized in a protective atmosphere; the first tackifier can be a polyolefin elastomer (purchased from Mitsui Chemicals, product model DF740); the second tackifier can be a polyurethane elastomer (purchased from Sinochem Plastics, product model R3000); the antioxidant can be butylated hydroxytoluene (purchased from BASF, product model BHT264); the dicyclopentadiene, the first tackifier, the second tackifier, and... The mass ratio of antioxidants can be 780~850:20~30:6~10:2.5~3; the protective atmosphere can specifically be nitrogen; the polymerization reaction temperature can be 150~180℃, and the heating rate from room temperature (25℃) to the polymerization reaction temperature can be 2.0~3.0℃ / min, specifically 2.5℃ / min; the polymerization reaction time can be 6~8h, and the polymerization reaction time is calculated from the start of heating to the polymerization reaction temperature; the material obtained during the polymerization reaction is the reaction liquid.

[0021] Specifically, this invention involves sampling the reaction liquid during the polymerization process as samples. In one embodiment, the batches used to prepare the polydicyclopentadiene can be 2-4, specifically 2 batches in this example; the number of sampling points for each batch of polydicyclopentadiene can be 2-5, specifically 3 in this example; the number of samples collected at each sampling point can be 8-12, specifically 10 in this example; the total number of samples collected from all batches can be 50-70, specifically 60 in this example. This invention limits the number of samples at each sampling point and the total number of samples to the above range, which helps improve the accuracy of model establishment. In one embodiment, the first sampling point can be 2.5-3.5 hours after the start of the polymerization reaction, specifically 3 hours; the remaining sampling points are spaced 1.5-2.5 hours apart from the previous sampling point, specifically 2 hours; the interval between the last sampling point and the end of the polymerization reaction is <1 hour. By setting the sampling points in the manner described above, this invention enables more accurate analysis of the tricyclopentadiene content throughout the entire polydicyclopentadiene synthesis process.

[0022] After obtaining the samples, the present invention performs gas chromatography and near-infrared spectroscopy on the samples respectively to obtain the measured value of tricyclopentadiene content in each sample and the near-infrared spectrum of each sample. As one embodiment of the present invention, the gas chromatography analysis conditions include: using a Shimadzu GC2010 Plus gas chromatograph; injection port temperature of 250~300℃; split injection with a split ratio of 20:1; HP-5ms column with dimensions of 30m×0.25mm×0.25μm; column temperature program: initial column oven temperature of 50~100℃, held for 2 min, increased to 250~300℃ at a rate of 10℃ / min, held for 10 min, and then increased to 300~330℃ at a rate of 10℃ / min; FID detector with a detector temperature of 330℃; and nitrogen as the carrier gas. In one embodiment of the present invention, the near-infrared detection conditions include: a cuvette with a measurement range of 1 mm; 32 scans; and a resolution of 8.0 cm for each scan. -1 The spectral frequency range for each scan is 4000~1000 cm⁻¹. -1 In one embodiment of the present invention, the cuvette is preferably wiped clean with lens paper before use.

[0023] After obtaining the measured tricyclopentadiene content and near-infrared spectrum of each sample, this invention correlates the measured tricyclopentadiene content of a subset of samples with the corresponding near-infrared spectra and optimizes the model to obtain the model to be validated. In one embodiment of this invention, the number of the subset of samples can be 80-90% of the total number of samples, specifically 83%. This invention uses data from a subset of samples to establish the model to be validated, retaining the remaining sample data for validation of the model. In another embodiment of this invention, the sampling points of the subset of samples cover all sampling points. The number of samples selected at each sampling point in the subset of samples can be the same or different. In this invention, the sampling points of the subset of samples cover all sampling points, meaning that the samples used to establish the model to be validated take into account samples from each sampling point, which helps to make the established model more accurate.

[0024] As one embodiment of the present invention, the method for establishing the model to be verified includes the following steps: The measured values ​​of tricyclopentadiene content in some samples and the corresponding near-infrared spectra of the samples are input into the software; each near-infrared spectrum input into the software is sequentially processed by derivatives and smoothed, and then the band interface is selected to obtain the processed near-infrared spectrum; the measured values ​​of tricyclopentadiene content input into the software are correlated with the processed near-infrared spectrum to obtain an initial model; the initial model is optimized to obtain the model to be verified.

[0025] In one embodiment of the present invention, the software can be TQ Analyst EZ Edition software, specifically TQ Analyst EZ Edition software from Thermo Fisher Scientific Inc. In another embodiment, the derivative processing can include first-order derivative processing or second-order derivative processing, preferably first-order derivative processing; by performing first-order or second-order derivative processing on the near-infrared spectrum, the present invention can eliminate drift on the Y-axis and reduce systematic differences in the near-infrared spectrum. In another embodiment, the smoothing processing can be Norris smoothing; the use of Norris smoothing can eliminate noise in the near-infrared spectrum, improve the quality of the spectral signal, reduce the influence of noise, improve the signal-to-noise ratio, and improve the accuracy of model establishment. In another embodiment, the selection criterion for the band interface can be absorbance ≤3; by selecting a band interface with absorbance ≤3, the present invention can fully extract the effective information in the spectrum.

[0026] In one embodiment of the present invention, the correlation method can be a partial least squares regression quantitative method; the present invention uses a partial least squares regression quantitative method to establish a more accurate model. In another embodiment of the present invention, the optimization method includes one or more of the following methods: removing outlier data, cross-validation, and changing the derivative and band range; that is, after the initial model is established, if there is outlier data, the outlier data can be directly removed, or it can be removed through cross-validation, or it can be removed by changing the derivative and band range. In another embodiment of the present invention, changing the derivative and band range refers to changing the derivative processing method and changing the band range; specifically, changing the derivative processing method means selecting either the first derivative or the second derivative, and changing the band range means selecting the range with the highest correlation coefficient on the Y-axis of the near-infrared spectrum as the appropriate band range for detection (in the near-infrared spectrum, the Y-axis represents the correlation coefficient, and the X-axis represents the sensitivity wavenumber). In this embodiment of the invention, the optimization method may include: firstly, eliminating outlier data (i.e., eliminating points with large deviations) by changing the derivative and band range; and then eliminating outlier data (i.e., eliminating points with large deviations) through cross-validation. The optimization method described above can make the established model more accurate. Specifically, in one implementation of the invention, an absolute relative deviation of 1-3% is defined as outlier data.

[0027] In one embodiment of the present invention, the RMSEC value of the model to be verified can be 0.266~0.275, and the coefficient Corr.Coeff value can be 0.9988~0.9989. In the present invention, the smaller the RMSEC value of the model to be verified and the closer the coefficient Corr.Coeff value is to 1, the higher the prediction accuracy of the obtained model to be verified.

[0028] After obtaining the model to be validated, this invention imports the near-infrared spectra of the remaining samples into the model to obtain the predicted value of tricyclopentadiene content. The predicted value of tricyclopentadiene content is then compared with the measured value of tricyclopentadiene content in the corresponding samples. When the percentage of samples with an absolute relative deviation of <3% between the predicted and measured values ​​is ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained. When the percentage of samples with a relative deviation of ≥3% between the predicted and measured values ​​is >10% of the remaining samples, the model optimization method is adjusted until the percentage of samples with an absolute relative deviation of <3% between the predicted and measured values ​​is ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained. This invention constructs a near-infrared spectroscopy offline analysis model using the above method. This model can quickly detect the corresponding tricyclopentadiene content, providing rapid and timely analysis results, enabling real-time monitoring of tricyclopentadiene content using near-infrared spectroscopy.

[0029] This invention establishes an offline near-infrared spectroscopy analysis model, enabling rapid and accurate detection of TCPD content during PDCPD production.

[0030] This invention provides the application of the near-infrared spectroscopy offline analysis model established by the above-described technical solution in the quality control of polydicyclopentadiene chemical production.

[0031] This invention provides a method for determining the tricyclopentadiene content in the synthesis process of polydicyclopentadiene, comprising the following steps: The reaction solution was subjected to near-infrared detection to obtain a near-infrared spectrum; the reaction solution was the reaction solution in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction. The near-infrared spectrum is substituted into the near-infrared spectroscopy offline analysis model to obtain the content of tricyclopentadiene in the reaction solution; the near-infrared spectroscopy offline analysis model is the near-infrared spectroscopy offline analysis model established by the method described in the above technical solution.

[0032] The polymerization reaction conditions and near-infrared detection conditions described in this invention are preferably consistent with the above-mentioned technical solutions, and will not be repeated here.

[0033] The technical solutions of this invention will be clearly and completely described below with reference to the embodiments thereof. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0034] Preparation Example 1 The following experiments involve a method for preparing PDCPD from DCPD as the initial raw material via polymerization, which includes the following steps: 780g of raw material DCPD was added to a reaction flask, followed by the addition of 20g of the first tackifier (specifically, a polyolefin elastomer, purchased from Mitsui Chemicals, product model DF740), 6g of the second tackifier (specifically, a polyurethane elastomer, purchased from Sinochem Plastics, product model R3000), and 2.5g of antioxidant (specifically, butylated hydroxytoluene, purchased from BASF, product model BHT264). The mixture was purged with nitrogen three times, and the temperature was increased from room temperature to 180℃ at a rate of 2.5℃ / min and held at that temperature for polymerization. The reaction liquid during the polymerization process was a colorless, transparent liquid with a certain viscosity. During the polymerization process, samples were taken to detect the TCPD content. When the TCPD content reached 15~20wt%, the reaction was stopped by cooling.

[0035] Example 1 The method for establishing the near-infrared spectroscopy offline analysis model in this embodiment includes the following steps: (1) Sample collection: The reaction liquid is collected at the sampling point to obtain the sample; the sampling point is a different time point in the process of preparing PDCPD by polymerization reaction with DCPD as the initial raw material, and the reaction liquid is the reaction liquid in the process of preparing PDCPD by polymerization reaction with DCPD as the initial raw material; the number of sampling points is 6; starting from the temperature rise to 180℃, the first sampling point (i.e., the reaction liquid) is collected when the polymerization reaction is carried out for 3 hours. The remaining sampling points are separated from the previous sampling point by 2 hours. A total of 2 batches of products are produced, and there are 3 sampling points for each batch. 10 samples are collected from each sampling point, that is, a total of 60 samples are collected for 2 batches of products. (2) Sample analysis: The 60 samples from step (1) were subjected to gas chromatography and near-infrared spectroscopy to obtain the measured values ​​of TCPD content and near-infrared spectra of the 60 samples; the gas chromatography analysis was performed using a Shimadzu GC2010. The analysis was performed using a Plus gas chromatograph; the injection port temperature was 250℃; split injection was used with a split ratio of 20:1; the column model used was HP-5ms (30m×0.25mm×0.25μm); the column temperature program was as follows: initial column temperature 50℃, hold for 2 min, increase to 250℃ at a rate of 10℃ / min, hold for 10 min, and then increase to 300℃ at a rate of 10℃ / min; detector: FID, temperature 330℃; carrier gas was nitrogen; the cuvettes used for near-infrared scanning were 1mm measuring cuvettes; the cuvettes were cleaned with lens paper before use; the near-infrared detection conditions included: 32 scans (i.e., one near-infrared spectrum is output through 32 scans), and a resolution of 8.0cm for each scan.-1 The spectral frequency range for each scan is 4000~1000 cm⁻¹. -1 ; (3) Establishment of the model to be verified: The measured values ​​of TCPD content of the 50 samples in step (2) and the corresponding near-infrared spectra are correlated and the model is optimized to obtain the model to be verified; the 50 samples used to establish the model to be verified are: 8 samples are taken from each of the 5 sampling points, and 10 samples are taken from the last remaining sampling point, for a total of 50 samples; the specific method for establishing the model to be verified is as follows: (31) Input the measured values ​​of TCPD content and the corresponding near-infrared spectra of 50 samples into TQ analyst EZEdition software (Thermo Fisher Scientific Inc.). (32) Input each near-infrared spectrum of step (31) into the TQ analyst EZ Edition software and perform first derivative processing and Norris smoothing processing in sequence. Then select the band interface with absorbance ≤3 to obtain the processed near-infrared spectrum. (33) The measured value of TCPD content input into TQ analyst EZ Edition software in step (31) and the processed near-infrared spectrum obtained in step (32) are correlated using the partial least squares regression quantitative method to obtain the initial model; (34) Optimize the initial model obtained in step (33) to obtain the model to be verified; the optimization method is to first use the method of changing the derivative and the band range to remove abnormal data (i.e., remove points with large deviations, with the absolute value of the relative deviation in the range of 1~3%). The method of changing the derivative and the band range refers to changing the derivative processing method and changing the band range. The method of changing the derivative processing method specifically refers to selecting the first derivative or the second derivative. The method of changing the band range refers to selecting the range with the highest correlation coefficient on the Y-axis in the near-infrared spectrum as the appropriate band range for detection. Then, the abnormal data (i.e., remove points with large deviations, with the absolute value of the relative deviation in the range of 1~3%) is removed through cross-validation. (4) Model verification: The near-infrared spectra of the remaining 10 samples in step (2) are imported into the model to be verified obtained in step (3) to predict the TCPD content and obtain the predicted value; the predicted value is compared with the measured value of the TCPD content of the corresponding sample. The results show that the percentage of samples with an absolute value of the relative deviation between the predicted value and the measured value <3% accounts for ≥90% of the remaining sample quantity (i.e., the remaining sample quantity is 10). That is, the model to be verified is a near-infrared spectroscopy offline analysis model and the near-infrared spectroscopy offline analysis model is successfully constructed.

[0036] Figure 1 The gas chromatogram of one of the samples used to establish the model to be verified in Example 1 shows that the characteristic peaks of the analyte TCPD appeared at retention times of 16.6 min and 16.9 min.

[0037] Figure 2 The near-infrared spectra of the 50 samples used to establish the model to be verified in Example 1 are shown. The results show that the original near-infrared spectra will drift on the Y-axis due to external interference (instrument or physical factors).

[0038] Figure 3 The near-infrared spectra of 50 samples were processed by first derivative during the establishment of the model to be verified in Example 1. The results show that the first derivative processing can effectively reduce the systematic differences in the near-infrared spectra.

[0039] Figure 4 The near-infrared spectra of 50 samples were processed by first-order derivative processing and Norris smoothing in the process of establishing the model to be verified in Example 1. The results show that the noise in the near-infrared spectrum can be eliminated by Norris smoothing.

[0040] Figure 5 The figure shows the results of the model to be verified in Example 1. It can be seen that the RMSEC value of the model to be verified in Example 1 is 0.266 and the coefficient Corr.Coeff value is 0.9989, indicating that the prediction accuracy of the model to be verified is high.

[0041] The verification process and results of the model to be verified in step (4) of Example 1 are as follows: After establishing the model to be verified, the near-infrared spectra of the remaining 10 samples are input into the model to be verified obtained in step (3). The TCPD content of the near-infrared spectra of the 10 samples is predicted to obtain the predicted value of TCPD content in the reaction solution. The predicted value of TCPD content is compared with the measured value of TCPD content (TCPD content of the 10 samples obtained by gas chromatography analysis). The results are shown in Table 1.

[0042] As can be seen from Table 1, in Example 1, the number of samples with an absolute value of the relative deviation between the predicted and measured values ​​of TCPD content in the reaction solution by the model to be verified is less than 3%, accounting for 100% of the remaining 10 samples. This indicates that the model has high accuracy in prediction and can be used for the analysis of TCPD content in the PDCPD synthesis process by near-infrared spectroscopy.

[0043] Table 1 Comparison of predicted and measured values ​​of TCPD content in the reaction solution

[0044] Application Example 1 The method for determining the TCPD content in the PDCPD synthesis process based on the near-infrared spectroscopy offline analysis model in Example 1 includes the following steps: Near-infrared spectroscopy was performed on samples of the reaction solution in the PDCPD synthesis process to obtain near-infrared spectra. The near-infrared spectrum was substituted into the near-infrared spectroscopy offline analysis model of Example 1 to obtain the TCPD content.

[0045] Example 2 The process is basically the same as in Example 1, except that the first derivative processing in step (32) is replaced with second derivative processing. That is, each near-infrared spectrum input in step (31) is subjected to second derivative processing and Norris smoothing processing in sequence, and then the band interface with absorbance ≤3 is selected to obtain the processed near-infrared spectrum. The rest is the same as in Example 1.

[0046] Figure 6 The figure shows the results of the model to be verified in Example 2. It can be seen that the RMSEC value of the model to be verified in Example 2 is 0.275 and the coefficient Corr.Coeff value is 0.9988, indicating that the prediction accuracy of the model to be verified is high.

[0047] The verification process and results of the model to be verified in Example 2 are as follows: The near-infrared spectra of the remaining 10 samples after the model to be verified were input into the model to be verified in Example 2. The TCPD content of the 10 samples was predicted by the near-infrared spectra of the 10 samples. The predicted value of TCPD content in the reaction solution was obtained. The predicted value of TCPD content was compared with the measured value of TCPD content (TCPD content of 10 samples obtained by gas chromatography analysis). The results are shown in Table 2.

[0048] As can be seen from Table 2, the number of samples in Example 2 with an absolute value of less than 3% relative deviation between the predicted and measured values ​​of TCPD content in the reaction solution by the model to be verified accounted for 100% of the remaining 10 samples. This indicates that the model has high accuracy in prediction and can be used for the analysis of TCPD content in the PDCPD synthesis process by near-infrared spectroscopy.

[0049] Table 2 Comparison of predicted and measured values ​​of TCPD content in the reaction solution

[0050] Comparing the data in Tables 1 and 2, it can be seen that using the first derivative processing can reduce the overall relative deviation between the model's predicted and measured values ​​of TCPD content in the reaction solution. Therefore, the near-infrared spectroscopy offline analysis model established in Example 1 has higher prediction accuracy.

[0051] Application Example 2 The method for determining the TCPD content in the PDCPD synthesis process based on the near-infrared spectroscopy offline analysis model in Example 2 includes the following steps: Near-infrared spectroscopy was performed on the reaction solution in the PDCPD synthesis process to obtain the near-infrared spectrum. The near-infrared spectrum was substituted into the near-infrared spectroscopy offline analysis model of Example 2 to obtain the TCPD content.

[0052] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for establishing an offline near-infrared spectroscopy analysis model, comprising the following steps: The reaction solution was collected at the sampling points to obtain the sample; the sampling points were different time points in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction; the reaction solution was the reaction solution in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction. The samples were subjected to gas chromatography and near-infrared spectroscopy to obtain the measured value of tricyclopentadiene content and the near-infrared spectrum of each sample. The measured values ​​of tricyclopentadiene content in some samples were correlated with the near-infrared spectra of the corresponding samples, and the model was optimized to obtain the model to be verified. The near-infrared spectra of the remaining samples are imported into the model to be validated to obtain the predicted value of tricyclopentadiene content. The predicted value of tricyclopentadiene content is compared with the measured value of tricyclopentadiene content in the corresponding samples. When the percentage of samples with an absolute value of the relative deviation between the predicted value and the measured value of <3% accounts for ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained. When the percentage of samples with a relative deviation between the predicted value and the measured value of ≥3% accounts for >10% of the remaining samples, the model optimization method is adjusted until the percentage of samples with an absolute value of the relative deviation between the predicted value and the measured value of <3% accounts for ≥90% of the remaining samples, the near-infrared spectroscopy offline analysis model is obtained.

2. The method for establishing according to claim 1, characterized in that, The number of batches for preparing the polydicyclopentadiene is 2 to 4; when preparing each batch of polydicyclopentadiene, the number of sampling points is 2 to 5, and the number of samples collected at each sampling point is 8 to 12.

3. The method for establishing according to claim 2, characterized in that, The first sampling point is 2.5 to 3.5 hours after the start of the polymerization reaction. The remaining sampling points are spaced 1.5 to 2.5 hours apart from the previous sampling point. The last sampling point is spaced less than 1 hour apart from the end of the polymerization reaction.

4. The method for establishing according to claim 1, characterized in that, The number of the sampled portions is 80-90% of the total number of samples.

5. The method for establishing according to any one of claims 1 to 4, characterized in that, The method for establishing the model to be verified includes the following steps: The measured values ​​of tricyclopentadiene content in some samples and the corresponding near-infrared spectra of the samples are input into the software; each near-infrared spectrum input into the software is sequentially processed by derivatives and smoothed, and then the band interface is selected to obtain the processed near-infrared spectrum; the measured values ​​of tricyclopentadiene content input into the software are correlated with the processed near-infrared spectrum to obtain an initial model; the initial model is optimized to obtain the model to be verified.

6. The method for establishing according to claim 5, characterized in that, The software is TQ Analyst EZ Edition; the derivative processing includes first-order derivative processing or second-order derivative processing; the smoothing processing is Norris smoothing processing; the selection criterion for the band interface is absorbance ≤3.

7. The method for establishing according to claim 6, characterized in that, The correlation method is a partial least squares regression quantitative method; the optimization method includes one or more of the following methods: removing outlier data, cross-validation, changing the derivative and band range.

8. The method for establishing according to claim 1, characterized in that, The conditions for the gas chromatography analysis included: a Shimadzu GC2010 Plus gas chromatograph; an injection port temperature of 250–300°C; split injection with a split ratio of 20:1; an HP-5ms column with dimensions of 30m × 0.25mm × 0.25μm; a column temperature program of: initial oven temperature of 50–100°C, held for 2 min, increased to 250–300°C at a rate of 10°C / min, held for 10 min, and then increased to 300–330°C at a rate of 10°C / min; an FID detector with a detector temperature of 330°C; and nitrogen as the carrier gas. The near-infrared detection conditions include: a cuvette with a measurement range of 1 mm; 32 scans; and a resolution of 8.0 cm for each scan. -1 The spectral frequency range for each scan is 4000~1000 cm⁻¹. -1 .

9. The application of the near-infrared spectroscopy offline analysis model established by the method described in any one of claims 1 to 8 in the quality control of polydicyclopentadiene chemical production.

10. A method for determining the tricyclopentadiene content in a polydicyclopentadiene synthesis process, comprising the following steps: The reaction solution was subjected to near-infrared detection to obtain a near-infrared spectrum; the reaction solution was the reaction solution in the process of preparing polydicyclopentadiene from dicyclopentadiene as the initial raw material through polymerization reaction. The near-infrared spectrum is substituted into the near-infrared spectroscopy offline analysis model to obtain the content of tricyclopentadiene in the reaction solution; the near-infrared spectroscopy offline analysis model is the near-infrared spectroscopy offline analysis model established by the method described in any one of claims 1 to 8.

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