Method for detecting content of bound acrylonitrile in butyronitrile degassing mucilage

Abstract

The invention discloses a method for detecting the content of bound acrylonitrile in butyronitrile degassed mucilage. The method comprises the following steps: step 1, collecting a nuclear magnetic resonance spectrum of a sample; 2, measuring the content of bound acrylonitrile in the sample; step 3, preprocessing the acquired nuclear magnetic resonance spectrum; step 4, dividing the data obtained in the step 3 into a correction set and a verification set, and then performing regression modeling; 5, evaluating the model to obtain a nuclear magnetic prediction model; and step 6, collecting the nuclear magnetic resonance spectrum of the to-be-detected mucilage and substituting the nuclear magnetic resonance spectrum into the nuclear magnetic prediction model to obtain the bound acrylonitrile content of the to-be-detected mucilage. The method for detecting the content of the binding acrylonitrile in the butyronitrile degassing mucilage solves the problems that in the prior art, measurement time is long, operation is tedious, sample pretreatment or sample preparation is needed, and operators make contact with chemical reagents for a long time.

Description

Technical Field

[0001] The invention belongs to the technical field of rapid analysis of physicochemical properties in rubber and relates to a method for detecting the content of bound acrylonitrile in degassed butadiene-acrylonitrile mortar. Background Art

[0002] Acrylonitrile-butadiene rubber (NBR), abbreviated as NBR, is a synthetic rubber produced by the copolymerization of acrylonitrile and butadiene. Due to its -CN content, it possesses strong polarity and exhibits excellent oil, wear, heat, and barrier properties. The bound acrylonitrile content influences the ease of rotation within the rubber molecular chain and the intermolecular forces, thus affecting the chain's flexibility and the product's physical and mechanical properties, such as its glass transition temperature, solubility parameter, and oil, wear, and cold resistance. Therefore, accurate measurement of bound acrylonitrile content is crucial in the synthetic rubber industry.

[0003] Currently available methods for testing the bound acrylonitrile content in NBR mainly include combustion method, Kjeldahl method, infrared spectroscopy, thermogravimetric and differential thermogravimetric analysis, and pyrolysis chromatography.

[0004] Combustion method: After preparing the sample, extract it with anhydrous ethanol, dry it, and cool it. The nitrogen content is then measured using an elemental analyzer. The bound acrylonitrile content is calculated using the formula. Because this method measures the sum of all nitrogen-containing substances in the sample, the results are easily affected by free acrylonitrile.

[0005] Kjeldahl method: The sample is pretreated and then alkalinized, and the total nitrogen content is calculated. This method is a classic and widely used method, but the catalyst used is highly toxic, environmentally unfriendly, and the experimental process is time-consuming.

[0006] Infrared spectroscopy: The sample is processed into a sheet, then heated and dissolved. The filtrate is applied to a salt sheet and dried to form a film, and its infrared spectrum is measured. This method is fast and simple to operate; it can analyze the bound acrylonitrile content of raw NBR rubber, vulcanized rubber, and NBR blends with other polymers. The advent of attenuated total reflectance Fourier transform infrared (ATR-FTIR) technology allows direct testing of raw rubber without the need for sample pretreatment such as dissolution or high-temperature pyrolysis. However, infrared spectroscopy also has some drawbacks: large relative error in the test; and the need to establish a working curve, which is affected by factors such as instrument resolution and sample preparation. ATR can only be used directly to test raw rubber samples; for vulcanized rubber samples, high-temperature pyrolysis is required, resulting in test results affected by the pyrolysis temperature and time. In summary, infrared spectroscopy is generally used to test raw or vulcanized rubber samples and cannot be used to test in-process control material mortars.

[0007] Pyrolysis chromatography: This method relies on a good linear relationship between the relative yields of acrylonitrile and butadiene in the pyrolysis products and the ratio of the two monomers in the corresponding NBR. It offers advantages such as high sensitivity, rapid analysis, low sample volume, no pretreatment required, and low cost. However, it suffers from poor reproducibility and requires high control of the pyrolysis temperature, otherwise accuracy is compromised.

[0008] Thermogravimetric and differential thermogravimetric analysis methods: Thermogravimetric and differential thermogravimetric curves of NBR are tested under nitrogen and air conditions respectively, and the amount of its carbon residue is calculated from the obtained curves, thereby establishing a working curve of carbon residue and acrylonitrile content.

[0009] Existing methods for measuring acrylonitrile content generally require sample pretreatment or preparation, and most test solid adhesives, with few directly testing adhesive mortars. These methods also pose challenges such as time-consuming measurements, cumbersome procedures, the need for sample pretreatment or preparation, and prolonged operator exposure to chemical reagents. The advantages and disadvantages of various methods are summarized in Table 1.

[0010] Table 1 Summary of advantages and disadvantages of existing test methods

[0011]

[0012] Summary of the Invention

[0013] The purpose of the present invention is to provide a method for detecting the content of bound acrylonitrile in degassed butyronitrile mortar, which solves the problems of the prior art such as long measurement time, complicated operation, need for sample pretreatment or sample preparation, and long-term exposure of operators to chemical reagents.

[0014] The technical solution adopted by the present invention is a method for detecting the content of acrylonitrile in degassed butyronitrile mortar, and the specific steps are as follows:

[0015] Step 1, collecting a nuclear magnetic resonance spectrum of a degassed nitrile mortar sample to obtain sample spectrum information;

[0016] Step 2, measuring the bound acrylonitrile content in the degassed butyronitrile mortar sample;

[0017] Step 3: Preprocess the sample spectrum information to obtain denoised spectrum information that eliminates noise interference;

[0018] Step 4: Divide the denoised spectrum information from step 3 into a calibration set and a validation set using the KS classification method, and then perform regression modeling on the bound acrylonitrile content obtained in step 2 and the calibration set spectrum data to find a mathematical relationship between the bound acrylonitrile content and the calibration set spectrum, thereby obtaining a nuclear magnetic resonance analysis model for the bound acrylonitrile content;

[0019] Step 5: Use the validation set to evaluate the NMR analysis model and select the analysis model with the correlation coefficient closest to 1 as the NMR prediction model;

[0020] Step 6: Collect the nuclear magnetic resonance spectrum of the mortar to be tested to obtain the spectrum information to be tested, substitute the spectrum information to be tested into the nuclear magnetic resonance prediction model in step 5 to obtain the bound acrylonitrile content of the mortar to be tested.

[0021] The present invention is also characterized in that:

[0022] The specific method for collecting the nuclear magnetic resonance spectrum of the degassed nitrile slurry sample in step 1 is: collecting the degassed nitrile slurry sample, shaking the collected degassed nitrile slurry sample, putting it into a nuclear magnetic resonance tube, placing it into the injection port of the nuclear magnetic resonance analyzer, and scanning. The acquisition conditions are: observation nucleus: H1 nucleus, operating frequency 60±0.5MHz, average resolution 0.5%<75; 10%<12; 50%<4.

[0023] In step 2, the bound acrylonitrile content is measured using the Kjeldahl method, which adopts the national standard SH / T1157.2-2015, "Determination of bound acrylonitrile content in raw rubber acrylonitrile-butadiene rubber (NBR)".

[0024] In step 3, the spectrum preprocessing method for the nuclear magnetic resonance spectrum is any one of the first-order derivative method, the second-order derivative method, and the SG smoothing method, or a combination of two or more of the above.

[0025] In step 4, partial least squares method is used in modeling to select the optimal displacement range, and abnormal data are eliminated based on Mahalanobis distance, and the optimal number of principal factors is selected to establish an analytical model combining acrylonitrile content.

[0026] When evaluating the model in step 5, the calibration standard deviation, validation standard deviation, and correlation coefficient are used. Finally, the model with the correlation coefficient closest to 1 and the smallest cross-validation standard deviation is selected as the NMR prediction model.

[0027] The specific method for collecting the nuclear magnetic resonance spectrum of the degassed nitrile slurry to be tested in step 6 is: collecting the degassed nitrile slurry to be tested, shaking the collected degassed nitrile slurry to be tested, putting it into a nuclear magnetic resonance tube, placing it into the injection port of the nuclear magnetic resonance analyzer, and scanning. The acquisition conditions are: observation nucleus: H1 nucleus, operating frequency 60±0.5MHz, average resolution 0.5%<75; 10%<12; 50%<4.

[0028] The beneficial effects of the present invention are:

[0029] (1) Compared with the 11-hour experimental time of the traditional Kjeldahl method, the detection method of the present invention can obtain the bound acrylonitrile content data in 10 minutes, which is a fast measurement speed;

[0030] (2) The detection method of the present invention does not require sample pretreatment and realizes non-destructive measurement;

[0031] (3) The entire operation process of the detection method of the present invention does not require contact with any chemical reagents and there is no waste liquid pollution, which is an environmentally friendly rapid analysis method;

[0032] (4) The object of measurement of the detection method of the present invention is the intermediate control material in the rubber production process - the slurry. More than 90% of the slurry is water. The existing detection method requires the slurry to be cured and pressed or other pre-processed, which is time-consuming and may cause varying degrees of loss or contamination during the processing. The method of the present invention realizes direct detection, avoiding this problem.

[0033] (5) The detection method of the present invention is simple to operate. Place the mortar sample into the NMR tube, insert it into the corresponding position of the device, and click "Start" to complete the operation;

[0034] (6) No need to prepare a working curve: The present invention does not require the preparation or calibration of a working curve. The mathematical model established by the detection method of the present invention does not require calibration when the production formula remains unchanged. Moreover, the method of the present invention becomes more stable and accurate as the size of the database increases (i.e., the longer it is used).

[0035] (7) The analysis model involved in the detection method of the present invention can be used in an online real-time monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a nuclear magnetic resonance spectrum of the degassed butyronitrile mortar sample in Example 1 of the present invention;

[0037] Figure 2 is a correlation diagram of the measured value and the predicted value of the acrylonitrile bound to the mortar in Example 1 of the present invention;

[0038] Figure 3 is a nuclear magnetic resonance spectrum of the degassed butyronitrile mortar sample in Example 2 of the present invention;

[0039] Figure 4 2 is a correlation diagram of the measured value and the predicted value of the mortar combined with acrylonitrile in Example 2 of the present invention. DETAILED DESCRIPTION

[0040] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0041] The method for detecting the content of acrylonitrile in the degassed butyronitrile mortar of the present invention comprises the following specific steps:

[0042] Step 1. Collect the nuclear magnetic resonance spectrum of the degassed nitrile slurry sample to obtain the sample spectrum information. The specific method is: collect the degassed nitrile slurry sample, shake the collected degassed nitrile slurry sample, put it into a nuclear magnetic resonance tube, put it into the injection port of the nuclear magnetic resonance analyzer, and scan it. The acquisition conditions are: observation nucleus: H1 nucleus, operating frequency 60±0.5MHz, average resolution 0.5%<75; 10%<12; 50%<4.

[0043] Step 2: Measure the bound acrylonitrile content in the degassed nitrile mortar sample, specifically by using the Kjeldahl method to measure the bound acrylonitrile content. The Kjeldahl method adopts the national standard SH / T 1157.2-2015, "Determination of bound acrylonitrile content in raw rubber acrylonitrile-butadiene rubber (NBR)".

[0044] Step 3: Preprocess the sample spectrum information to obtain denoised spectrum information that eliminates noise interference. The spectrum preprocessing method for the nuclear magnetic resonance spectrum is any one of the first-order derivative method, the second-order derivative method, and the SG smoothing method, or a combination of two or more of the above.

[0045] Step 4: Divide the denoised spectrum information of step 3 into a calibration set and a validation set using the KS classification method, then perform regression modeling on the bound acrylonitrile content obtained in step 2 and the calibration set spectrum data, find the mathematical relationship between the bound acrylonitrile content and the calibration set spectrum, and obtain a nuclear magnetic resonance analysis model of the bound acrylonitrile content. When modeling, the partial least squares method is used to select the optimal displacement range, and abnormal data is eliminated according to the Mahalanobis distance, and the optimal number of principal factors is selected to establish an analysis model for the bound acrylonitrile content.

[0046] Step 5. Use the validation set to evaluate the NMR analysis model, and select the analysis model with the correlation coefficient closest to 1 as the NMR prediction model. When evaluating the model, perform the evaluation based on the calibration standard deviation, validation standard deviation, and correlation coefficient. Finally, select the model with the correlation coefficient closest to 1 and the smallest cross-validation standard deviation as the NMR prediction model.

[0047] Step 6, collect the nuclear magnetic resonance spectrum of the slurry to be tested to obtain the spectral information to be tested, substitute the spectral information to be tested into the nuclear magnetic prediction model in step 5 to obtain the bound acrylonitrile content of the slurry to be tested, and collect the nuclear magnetic resonance spectrum of the degassed nitrile slurry to be tested. The specific method is as follows: collect the degassed nitrile slurry to be tested, shake the collected degassed nitrile slurry to be tested, put it into a nuclear magnetic resonance tube, put it into the sampling port of the nuclear magnetic resonance analyzer, and scan it. The acquisition conditions are: observation nucleus: H1 nucleus, operating frequency 60±0.5MHz, average resolution 0.5%<75; 10%<12; 50%<4.

[0048] Example 1

[0049] The nuclear magnetic resonance analyzer used in this embodiment is an Israeli AI 60 model, the modeling software is Hontye Chemo, and the nitrile degassed slurry sample comes from the nitrile degassed slurry produced in real time by the nitrile rubber unit of Lanzhou Petrochemical Company.

[0050] Step 1: Collect 34 batches of degassed nitrile mortar samples, shake the collected degassed nitrile mortar samples, put them into a nuclear magnetic resonance tube, put them into the injection port of the nuclear magnetic resonance analyzer, scan them, and obtain the nuclear magnetic resonance spectrum. The scanning results are as follows: Figure 1 As shown;

[0051] Step 2: Determine the bound acrylonitrile content of the degassed butyronitrile mortar sample in step 1 by Kjeldahl nitrogen determination. The test results are shown in Table 2.

[0052] Table 2 Measured data of acrylonitrile content in combination with degassed nitrile mortar samples

[0053]

[0054]

[0055] Step 3: preprocess the NMR spectrum obtained in step 1. The preprocessing method used in this embodiment is first-order derivative to obtain denoised spectrum information;

[0056] Step 4: Enter the denoised spectral information and corresponding combined acrylonitrile content data of 34 batches of nitrile degassed mortar samples into the modeling software to start building the analysis model. The specific process is: (1) Use the KS method to divide the calibration set and the validation set; (2) Optimal displacement point: 500-600; (3) Eliminate abnormal data of chemical values ​​and spectral values ​​based on the Mahalanobis distance; (4) Use partial least squares method for regression modeling.

[0057] Step 5: The established analysis model is evaluated by the calibration set standard deviation sec, the validation set standard deviation sep, the correlation coefficient R, and the optimal number of principal factors P. In this embodiment, sec = 0.295, sep = 0.226, R = 0.92, P = 8, and the correlation is as follows: Figure 2 As shown, the NMR prediction model is obtained.

[0058] Step 6: Collect the nuclear magnetic resonance spectrum information of 15 batches of degassed nitrile slurries to be tested (samples other than the 34 batches in step 1), substitute them into the nuclear magnetic resonance prediction model obtained in step 5, and obtain the predicted values ​​of the bound acrylonitrile content of the 15 batches of degassed nitrile slurries to be tested; then use the Kjeldahl method to measure the bound acrylonitrile content of the 15 batches of degassed nitrile slurries to be tested to obtain the measured values ​​and examine the accuracy of the model. The results are shown in Table 3.

[0059] Table 3 Comparison of measured and predicted values ​​of acrylonitrile content in the degassed nitrile mortar to be tested

[0060] Serial number Predicted value / % Measured value / % Absolute deviation 1 33.77 33.287 -0.483 2 34.39 34.377 -0.013 3 34.42 34.225 -0.195 4 33.84 33.437 -0.403 5 33.15 33.574 0.424 6 33.57 33.643 0.073 7 32.79 32.604 -0.186 8 33.86 33.233 -0.627 9 34.24 34.244 0.004 10 33.81 33.975 0.165 11 34.45 34.296 -0.154 12 34.1 33.813 -0.287 13 33.48 33.286 -0.194 14 33.71 33.775 0.065 15 33.38 33.556 0.176

[0061] As can be seen from Table 3, the rapid detection method of the present invention has high accuracy, with the maximum absolute deviation being only 0.627 and the standard deviation SD being 0.28.

[0062] Example 2

[0063] The nuclear magnetic resonance analyzer used in this embodiment is AI 60, the modeling software is Hontye Chemo, and the nitrile degassed mortar sample comes from the No. 2 nitrile degassed mortar produced in real time by the nitrile rubber unit of Lanzhou Petrochemical Company.

[0064] Step 1: Collect 30 batches of degassed nitrile mortar samples, shake the collected degassed nitrile mortar samples, put them into a nuclear magnetic resonance tube, and scan them in a nuclear magnetic resonance analyzer to obtain a nuclear magnetic resonance spectrum. The scanning results are as follows: Figure 3 As shown;

[0065] Step 2: Determine the bound acrylonitrile content of the degassed butyronitrile mortar sample in step 1 by Kjeldahl method.

[0066] Step 3: preprocess the NMR spectrum obtained in step 1. The preprocessing method used in this embodiment is second-order derivative to obtain denoised spectrum information;

[0067] Step 4: Enter the nuclear magnetic resonance spectra and corresponding acrylonitrile content data of 30 batches of degassed nitrile mortar samples into the modeling software to start building the analysis model, specifically: (1) divide the calibration set spectral information data and the verification set spectral information data using the KS method; (2) full-segment modeling; (3) eliminate abnormal chemical value and spectral value data based on the Mahalanobis distance; (4) use the partial least squares method for regression modeling.

[0068] Step 5: The established analysis model is evaluated by the calibration set standard deviation sec, the validation set standard deviation sep, the correlation coefficient R, and the optimal number of principal factors P. In this embodiment, sec = 0.456, sep = 0.512, R = 0.83, P = 5, and the correlation is as follows: Figure 4 As shown, the NMR prediction model is obtained.

[0069] Step 6: Collect the nuclear magnetic resonance spectrum information of 10 batches of degassed nitrile slurry to be tested (samples other than the 30 batches in step 1), substitute them into the nuclear magnetic resonance prediction model obtained in step 5, and obtain the predicted value of the bound acrylonitrile content of the degassed nitrile slurry to be tested; then use the Kjeldahl method to measure the bound acrylonitrile content of the 10 batches of degassed nitrile slurry to be tested, obtain the measured value, and examine the accuracy of the model.

[0070] The rapid detection method of the present invention has high accuracy, with a maximum absolute deviation of 1.23 and a standard deviation SD of 0.88.

[0071] Example 3

[0072] The data and steps used in the modeling process of this embodiment are the same as those in Example 1, except that the preprocessing method used in step 3 is SG smoothing to obtain denoised spectrum information;

[0073] Using the detection method of the present invention, the nuclear magnetic resonance spectrum information of 15 batches of degassed nitrile slurries to be tested was substituted into the obtained nuclear magnetic resonance prediction model, and then the Kjeldahl method was used to measure the bound acrylonitrile content of the 15 batches of degassed nitrile slurries to be tested to obtain actual measured values ​​and examine the accuracy of the model.

[0074] The rapid detection method of the present invention has high accuracy, with a maximum absolute deviation of 0.65 and a standard deviation SD of 0.31.

[0075] Example 4

[0076] The data and steps used in the modeling process of this embodiment are the same as those in Example 2, except that the preprocessing method used in step 3 is second-order derivative + SG smoothing to obtain denoised spectrum information;

[0077] Using the detection method of the present invention, the nuclear magnetic resonance spectrum information of 10 batches of degassed nitrile slurries to be tested was substituted into the obtained nuclear magnetic prediction model, and then the Kjeldahl method was used to measure the bound acrylonitrile content of the 10 batches of degassed nitrile slurries to be tested to obtain actual measured values ​​and examine the accuracy of the model.

[0078] The rapid detection method of the present invention has high accuracy, with a maximum absolute deviation of 1.24 and a standard deviation SD of 0.87.

[0079] Comparative Example 1

[0080] The data used in the modeling process of Comparative Example 1 and steps 1 and 2 are the same as those in Example 2, except that in step 3, the NMR spectrum obtained in step 1 is not preprocessed and is directly modeled;

[0081] Step 4: Enter the nuclear magnetic resonance spectra and corresponding acrylonitrile content data of 30 batches of degassed nitrile mortar samples into the modeling software to start building the analysis model, specifically: (1) divide the calibration set spectral information data and the verification set spectral information data using the KS method; (2) full-segment modeling; (3) eliminate abnormal chemical value and spectral value data based on the Mahalanobis distance; (4) use the partial least squares method for regression modeling.

[0082] Step 5: The established analysis model is evaluated by the calibration set standard deviation sec, the validation set standard deviation sep, the correlation coefficient R, and the optimal number of principal factors P. In this embodiment, sec = 0.456, sep = 0.512, R = 0.83, P = 5, and the correlation is as follows: Figure 4 As shown, the NMR prediction model is obtained.

[0083] Step 6: Collect the nuclear magnetic resonance spectrum information of 10 batches of degassed nitrile slurry to be tested (samples other than the 30 batches in step 1), substitute them into the nuclear magnetic resonance prediction model obtained in step 5, and obtain the predicted value of the bound acrylonitrile content of the degassed nitrile slurry to be tested; then use the Kjeldahl method to measure the bound acrylonitrile content of the 10 batches of degassed nitrile slurry to be tested, obtain the measured value, and examine the accuracy of the model. The results are shown in Table 4.

[0084] Table 4 Comparison of the measured and predicted values ​​of the combined acrylonitrile content of the tested nitrile deaerated mortar

[0085] Serial number Predicted value / % Measured value / % Absolute deviation 1 34.34 33.7 0.64 2 32.64 33.4 -0.76 3 33.62 33.4 0.22 4 33.64 33.4 0.24 5 33.36 33.2 0.16 6 33.3 32.6 0.7 7 33.61 32.6 1.01 8 32.89 32.6 0.29 9 33.3 34.2 -0.9 10 32.7 34.2 -1.5

[0086] From the data in Table 4, it can be seen that the rapid detection method of the present invention has high accuracy, with a maximum absolute deviation of 0.78 and a standard deviation SD of 0.32.

[0087] From the results of Example 2 and Comparative Example 1, it can be seen that for this sample, the model is overfitted after the second-order derivative processing when the preprocessing is performed in Example 2.

[0088] It can be seen from the results of the embodiments and comparative examples that the spectral preprocessing method is the first-order derivative, KS classification correction set and verification set, spectral range 500-600, Mahalanobis distance method to eliminate abnormal data, the optimal number of principal factors is selected as 5, and the analytical model for the combined acrylonitrile content in the nitrile mortar established by partial least squares regression has the best prediction performance.

Claims

1. A method for detecting the content of acrylonitrile in degassed butyronitrile mortar, characterized in that: The specific steps are as follows: Step 1, collecting a nuclear magnetic resonance spectrum of a degassed nitrile mortar sample to obtain sample spectrum information; Step 2, measuring the bound acrylonitrile content in the degassed butyronitrile mortar sample; Step 3: preprocessing the sample spectrum information to obtain denoised spectrum information that eliminates noise interference; Step 4: Divide the denoised spectrum information from step 3 into a calibration set and a validation set using the KS classification method, and then perform regression modeling on the bound acrylonitrile content obtained in step 2 and the calibration set spectrum data to find a mathematical relationship between the bound acrylonitrile content and the calibration set spectrum, thereby obtaining a nuclear magnetic resonance analysis model for the bound acrylonitrile content; Step 5: Use the validation set to evaluate the NMR analysis model, and select the analysis model with the correlation coefficient closest to 1 as the NMR prediction model; Step 6: Collect the nuclear magnetic resonance spectrum of the mortar to be tested to obtain the spectrum information to be tested, substitute the spectrum information to be tested into the nuclear magnetic resonance prediction model in step 5 to obtain the bound acrylonitrile content of the mortar to be tested.

2. The method for detecting acrylonitrile content in degassed butyronitrile mortar according to claim 1, wherein: The specific method for collecting the nuclear magnetic resonance spectrum of the degassed nitrile slurry sample in step 1 is: collecting the degassed nitrile slurry sample, shaking the collected degassed nitrile slurry sample, putting it into a nuclear magnetic resonance tube, placing it into the injection port of the nuclear magnetic resonance analyzer, and scanning. The collection conditions are: observation nucleus: H1 nucleus, operating frequency 60±0.5MHz, average resolution 0.5%<75; 10%<12; 50%<4.

3. The method for detecting acrylonitrile content in degassed butyronitrile mortar according to claim 1, wherein: In step 2, the bound acrylonitrile content is measured by the Kjeldahl method, and the Kjeldahl method adopts the national standard SH / T1157.2-2015, "Determination of bound acrylonitrile content in raw rubber acrylonitrile-butadiene rubber (NBR)".

4. The method for detecting acrylonitrile content in degassed butyronitrile mortar according to claim 1, wherein: The spectrum preprocessing method for the nuclear magnetic resonance spectrum in step 3 is any one of the first-order derivative method, the second-order derivative method, and the SG smoothing method, or a combination of the two.

5. The method for detecting acrylonitrile content in degassed butyronitrile mortar according to claim 1, wherein: In step 4, the partial least squares method is used in the modeling to select the optimal displacement range, and abnormal data are eliminated according to the Mahalanobis distance, and the optimal number of principal factors is selected to establish an analytical model combined with acrylonitrile content.

6. The method for detecting acrylonitrile content in degassed butyronitrile mortar according to claim 1, characterized in that: When the model is evaluated in step 5, it is performed according to the calibration standard deviation, the validation standard deviation and the correlation coefficient, and finally the model with the correlation coefficient closest to 1 and the smallest cross-validation standard deviation is selected as the NMR prediction model.

7. The method for detecting acrylonitrile content in degassed butyronitrile mortar according to claim 1, characterized in that: The specific method for collecting the nuclear magnetic resonance spectrum of the degassed nitrile slurry to be tested in step 6 is: collecting the degassed nitrile slurry to be tested, shaking the collected degassed nitrile slurry to be tested, putting it into a nuclear magnetic resonance tube, placing it into the injection port of the nuclear magnetic resonance analyzer, and scanning. The collection conditions are: observation nucleus: H1 nucleus, operating frequency 60±0.5MHz, average resolution 0.5%<75; 10%<12; 50%<4.

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