Method and system for detecting emulsifying property of low-foam surfactant

Abstract

The invention relates to the technical field of liquid analysis, and discloses a method and a system for detecting the emulsifying property of a low-foam surfactant, and the method comprises the following steps: preparing a plurality of low-foam surfactant solutions with different concentrations, respectively preparing emulsion samples, irradiating the surfaces of the emulsion samples with mid-infrared light with a specific wavelength emitted by a laser, and detecting the emulsifying property of the low-foam surfactant. Collecting optical signals reflected by the emulsion sample; collecting absorption spectrums of a plurality of reference emulsions with preset concentrations under a plurality of specific wavelengths, establishing a relation model between the absorption spectrums of the reference emulsions and the substrate signal and the noise signal, and predicting the absorption spectrum of the emulsion sample based on the relation model; calculating the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample, and evaluating the emulsifying property of the emulsion based on a pre-established relationship curve of absorbance and concentration. According to the method, the efficiency and the accuracy of detecting the emulsifying property of the low-foam surfactant can be improved.

Description

Technical Field

[0001] This application relates to the technical field of liquid analysis, and particularly to a method and system for detecting the emulsifying performance of low-foaming surfactants. Background Art

[0002] Traditional methods for detecting the emulsifying performance of low-foaming surfactants usually rely on visual observation or complex laboratory equipment, which have the disadvantages of cumbersome operation, long time consumption, and difficulty in achieving continuous monitoring. At the same time, traditional emulsifying performance detection methods often cannot provide detailed information on the microstructure of emulsions, affecting the accuracy and reliability of detection.

[0003] A similar prior art is the Chinese patent application with the publication number CN115096914A, which provides a liquid detection method, device, and liquid detection equipment, applicable to the field of data processing technology. The method includes: obtaining the original detection data detected by the liquid detection equipment for the liquid, and determining the first characteristic information corresponding to the original detection data; determining the size information of the container according to the size detection data detected by the size detection sensor for the container during the liquid detection process; using a pre-determined first correspondence relationship to determine the compensation information corresponding to the first characteristic information and the determined size information; compensating the original detection data with the determined compensation information to obtain the target detection data; determining the type of the liquid based on the target detection data or the second characteristic information of the target detection data. However, when detecting the emulsifying performance of two or more liquids, the accuracy of the detection results of this solution cannot be guaranteed.

[0004] Another similar prior art is the Chinese patent application with the publication number CN115343769A, which provides a liquid detection method, device, and liquid detection equipment, applicable to the field of security inspection technology. The method includes: determining the first characteristic information of the original detection data, where the original detection data is the detection data measured by the liquid detection equipment for the liquid to be detected; determining the compensation information belonging to the first characteristic information based on the correspondence relationship between the characteristic information of the liquid and the compensation information preset; where the compensation information corresponding to the characteristic information of each liquid is: the difference information between the detection data measured by the reference equipment and the liquid detection equipment for this liquid; compensating the original detection data with the determined compensation information to obtain the target detection data; classifying the target detection data or the second characteristic information of the target detection data based on the preset liquid type classification standard to obtain the type of the liquid to be detected. However, when detecting the emulsifying performance of two or more liquids, the accuracy of the detection results of this solution cannot be guaranteed either. Summary of the Invention

[0005] To solve the above technical problems, the present application provides a method and system for detecting the emulsifying performance of a low-foaming surfactant, which is used to improve the efficiency and accuracy of detecting the emulsifying performance of a low-foaming surfactant.

[0006] In a first aspect, the present application provides a method for detecting the emulsifying performance of a low-foaming surfactant, and the method includes:

[0007] Step S1: Prepare low-foaming surfactant solutions with multiple different concentrations and make them into emulsion samples respectively, wherein the configuration temperature, stirring time, stirring speed and volume of each concentration of the emulsion sample are the same;

[0008] Step S2: Irradiate the surface of the emulsion sample with mid-infrared light of a specific wavelength emitted by a laser, and collect the optical signal reflected by the emulsion sample;

[0009] Step S3: Collect the absorption spectra of reference emulsions with multiple preset concentrations at multiple specific wavelengths, establish a relationship model between the absorption spectra of the reference emulsions and the base signal and noise signal, and predict the absorption spectrum of the emulsion sample based on the relationship model;

[0010] Step S4: Calculate the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample, and evaluate the emulsifying performance of the emulsion based on the pre-established relationship curve between absorbance and concentration.

[0011] Combined with the first aspect, in the first implementation manner of the first aspect of the present application, in step S2, collecting the optical signal reflected by the emulsion sample includes:

[0012] After the mid-infrared light penetrates through the first zinc selenide window and irradiates the surface of the emulsion sample, the detection unit detects the reflected light on the surface of the emulsion sample. If the first reflected light on the surface of the emulsion sample is less than a preset threshold, the angle of the mid-infrared light irradiating the surface of the emulsion sample is adjusted;

[0013] After adjusting the angle multiple times, if the second reflected light on the surface of the emulsion sample is still less than the preset threshold, the scattered light signal from the bottom of the emulsion sample container is captured as the optical signal reflected by the emulsion sample.

[0014] Combined with the first aspect, in the second implementation manner of the first aspect of the present application, capturing the scattered light signal from the bottom of the emulsion sample container includes:

[0015] After reaching the bottom of the emulsion sample container, the mid-infrared light scatters in all directions to generate scattered light. The scattered light passes through the second zinc selenide window and is collected by the first parabolic optical mirror through the middle hole, and then further focused by the second parabolic optical mirror and reaches the detector.

[0016] Combined with the first aspect, in the third implementation manner of the first aspect of the present application, in step S3, establishing the relationship model between the absorption spectrum of the reference emulsion and the substrate signal and the noise signal includes:

[0017] Collect the absorption spectra of multiple reference emulsions with preset concentrations at multiple specific wavelengths, store them in the spectral database, establish the relationship model between the absorption spectrum of the reference emulsion and the substrate signal and the noise signal, and use formula 1: A = (J0 - J1) - c1B - c2N to represent, where J0 represents the incident light signal of the reference emulsion, J1 represents the reflected light signal of the reference emulsion, A represents the measured absorption spectrum of the reference emulsion, B represents the substrate signal, N represents the noise signal, c1 represents the coefficient of the substrate signal, and c2 represents the coefficient of the noise signal.

[0018] Combined with the first aspect, in the fourth implementation manner of the first aspect of the present application, in step S3, predicting the absorption spectrum of the emulsion sample based on the relationship model:

[0019] Based on the minimum sum of squared errors between the predicted absorption spectrum of the reference emulsion and the measured absorption spectrum of the reference emulsion in formula 1, calculate the coefficient c1 of the substrate signal and the coefficient c2 of the noise signal;

[0020] Substitute the coefficient c1 of the substrate signal and the coefficient c2 of the noise signal into formula 1 to predict the absorption spectrum of the emulsion sample.

[0021] Combined with the first aspect, in the fifth implementation manner of the first aspect of the present application, in step S4, calculating the absorbance of the emulsion sample:

[0022] Based on the predicted absorption spectrum of the emulsion sample, use formula 2: Calculate the absorbance of the emulsion sample, where P represents the absorbance of the emulsion sample, and A' represents the predicted absorption spectrum of the emulsion sample.

[0023] Combined with the first aspect, in the sixth implementation manner of the first aspect of the present application, step S4 further includes:

[0024] Establish a relationship curve between absorbance and concentration, substitute the absorbance of the predicted emulsion sample into the relationship curve, obtain the concentration value corresponding to the emulsion sample, and evaluate the emulsification performance of the emulsion based on this concentration value.

[0025] Combined with the first aspect, in the seventh implementation manner of the first aspect of this application, the substrate signal refers to:

[0026] Before detecting the emulsion, use the laser to emit mid-infrared light with a specific wavelength to irradiate the container to hold the emulsion, and collect the optical signal reflected by the container; repeat this step to obtain the optical signals reflected by the container at multiple different specific wavelengths, and establish a relationship list between the substrate signal and the specific wavelength.

[0027] Combined with the first aspect, in the eighth implementation manner of the first aspect of this application, the noise signal refers to:

[0028] Measure the emulsion with the same concentration k times at the same specific wavelength, obtain the digital signal of each measurement, calculate and calculate the average value of the digital signals of the k measurements, and also calculate the difference between the digital signal of each measurement and the average value. Take the average value of the differences as the noise signal, where k represents a positive integer greater than or equal to 10.

[0029] In the second aspect, this application provides a detection system for the emulsification performance of a low-foaming surfactant. The system includes:

[0030] A configuration unit for configuring low-foaming surfactant solutions with multiple different concentrations and separately making them into emulsion samples, where the configuration temperature, stirring time, stirring speed, and volume of each emulsion sample with a certain concentration are the same;

[0031] A collection unit for irradiating the surface of the emulsion sample with mid-infrared light with a specific wavelength emitted by a laser and collecting the optical signal reflected by the emulsion sample;

[0032] A prediction unit for collecting the absorption spectra of reference emulsions with multiple preset concentrations at multiple specific wavelengths, establishing a relationship model between the absorption spectra of the reference emulsions, the substrate signal, and the noise signal, and predicting the absorption spectrum of the emulsion sample based on the relationship model;

[0033] An evaluation unit for calculating the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample and evaluating the emulsification performance of the emulsion based on the pre-established relationship curve between absorbance and concentration.

[0034] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0035] In the technical solution provided by this application, by configuring low-foaming surfactant solutions with multiple different concentrations and separately making them into emulsion samples, it provides a basis for accurately evaluating the emulsifying performance of the low-foaming surfactant solutions. By irradiating the surface of the emulsion sample with mid-infrared light of a specific wavelength emitted by a laser and collecting the optical signal reflected by the emulsion sample, it can detect the emulsifying performance of the low-foaming surfactant in real time and accurately without damaging the emulsion sample.

[0036] By collecting the absorption spectra of multiple reference emulsions with preset concentrations at multiple specific wavelengths, establishing a relationship model between the absorption spectrum of the reference emulsion and the base signal and noise signal, and predicting the absorption spectrum of the emulsion sample based on the relationship model. By matching the actually measured spectrum of the emulsion sample with the relationship model, the concentration of the low-foaming surfactant in the emulsion sample can be estimated, thereby quickly and accurately evaluating its emulsifying performance. Calculating the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample, and evaluating the emulsifying performance of the emulsion based on the pre-established relationship curve between absorbance and concentration. Through the cooperation between the above steps, this application can improve the efficiency and accuracy of detecting the emulsifying performance of the low-foaming surfactant. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of 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 some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0038] Figure 1 It is a schematic diagram of a method for detecting the emulsifying performance of a low-foaming surfactant in Embodiment 1 of this application;

[0039] Figure 2 It is a schematic diagram of the mid-infrared light emitted by the laser irradiating the emulsion sample in Embodiment 1 of this application;

[0040] Figure 3 It is a schematic diagram of the relationship curve between the absorbance and concentration of the emulsion in Embodiment 1 of this application;

[0041] Figure 4 It is a schematic diagram of a system for detecting the emulsifying performance of a low-foaming surfactant in Embodiment 2 of this application;

[0042] Wherein, Figure 2 In the figure: 10. The first zinc selenide window; 11. The container; 12. The mid-infrared light; 13. The scattered light; 14. The guiding laser; 15. The reflected light; 16. The second zinc selenide window; 21. The first parabolic-shaped optical reflector; 22. The second parabolic-shaped optical reflector; 23. The detector. Specific Embodiment

[0043] The embodiment of the present application provides a method and system for detecting the emulsifying performance of a low-foaming surfactant. Terms such as "first", "second", "third", "fourth", etc. (if any) in the specification, claims and above-mentioned drawings of the present application are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order different from that illustrated or described herein. In addition, the terms "comprising" or "having" and any variation thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0044] Embodiment 1: For ease of understanding, the specific process of Embodiment 1 of the present application is described below. As Figure 1 shown, an embodiment of a method for detecting the emulsifying performance of a low-foaming surfactant in an embodiment of the present application includes:

[0045] Step S1: Prepare low-foaming surfactant solutions with multiple different concentrations and make them into emulsion samples respectively. Among them, the configuration temperature, stirring time, stirring speed and volume of each emulsion sample with a certain concentration are the same.

[0046] Specifically, when mixing two or more immiscible liquids together, the interfacial tension between the two immiscible liquids is reduced by adding a surfactant to form a stable emulsion. For example, when mixing water and oil together, a stable emulsion can be formed by adding a surfactant. When preparing low-foaming surfactant solutions with multiple different concentrations, key parameters such as the configuration temperature, stirring time, stirring speed and volume of each emulsion sample with a certain concentration are also controlled, so that the conditions in the emulsifying performance test are consistent, providing a basis for accurately evaluating the emulsifying performance of the low-foaming surfactant solution.

[0047] Step S2: Irradiate the surface of the emulsion sample with mid-infrared light of a specific wavelength emitted by a laser, and collect the optical signal reflected by the emulsion sample.

[0048] Specifically, a laser that can emit mid-infrared light of a specific wavelength is used to directly irradiate the surface of the low-foaming surfactant emulsion sample to be measured. The mid-infrared light of the specific wavelength can effectively interact with the chemical components in the target emulsion, such as surfactant molecules and the emulsion droplets formed by them. Subsequently, an optical detector is used to collect the optical signal reflected back by the emulsion sample. The reflected optical signal contains information about the structure of the emulsion, the droplet size distribution, and the arrangement state of surfactant molecules at the interface, etc. Among them, the mid-infrared light of the specific wavelength is the incident optical signal for the emulsion sample, and the optical signal reflected by the emulsion sample is the reflected optical signal, and both will be converted into digital signals for transmission and analysis. This method can detect the emulsification performance of low-foaming surfactants in real time and accurately without destroying the emulsion sample.

[0049] Step S3: Collect the absorption spectra of reference emulsions with multiple preset concentrations at multiple specific wavelengths respectively, establish a relationship model between the absorption spectrum of the reference emulsion and the base signal and the noise signal, and predict the absorption spectrum of the emulsion sample based on the relationship model.

[0050] Specifically, after obtaining the absorption spectrum of the emulsion, a relationship model between the absorption spectrum of the reference emulsion and the base signal and the noise signal is established. The base signal is the optical signal reflected back by the container before loading the emulsion. The relationship model describes the influence of low-foaming surfactants on the absorption spectrum of the emulsion at different concentrations, including changes in the spectral shape, shifts of characteristic peaks, and increases and decreases in absorption intensity, etc. At the same time, this relationship model can also distinguish the base signal and the noise signal to ensure the accuracy of the prediction results. Based on the relationship model, the absorption spectrum of the emulsion sample with an unknown concentration is predicted. By matching the actual measured spectrum of the emulsion sample with the relationship model, the concentration of low-foaming surfactants in the emulsion sample can be estimated, thereby evaluating its emulsification performance. This method is not only fast and accurate, but also can avoid the complex chemical analysis in traditional detection methods.

[0051] Step S4: Calculate the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample, and evaluate the emulsification performance of the emulsion based on the pre-established relationship curve between absorbance and concentration.

[0052] Specifically, after obtaining the absorption spectrum of the emulsion sample predicted in the above step S4, according to the Lambert-Beer law, the absorbance of the emulsion sample at a specific wavelength is calculated. Among them, absorbance is a measure of the degree of light absorption by a substance, and its magnitude is related to the concentration of the substance. By calculating the absorbance, the concentration and distribution state of surfactant molecules in the emulsion can be indirectly reflected. Then, the pre-established relationship curve between the absorbance and concentration of the emulsion is used, such as Figure 3As shown, to evaluate the emulsifying performance of low-foaming surfactants and achieve a rapid and accurate evaluation of the emulsifying performance of low-foaming surfactants, avoiding the cumbersome chemical analysis and waiting in traditional detection methods. The relationship curve represents the corresponding relationship between the absorbance of the emulsion and the concentration at different concentrations. This relationship curve usually appears as a straight line or a curve close to a straight line. The slope of the relationship curve reflects the light absorption efficiency of the emulsion, that is, the emulsifying effect of surfactant molecules. By comparing the absorbance of the emulsion sample with the corresponding value on the relationship curve, the concentration of the surfactant in the sample can be deduced, and then its emulsifying performance can be evaluated. Through the above method, it can be obtained that when the concentration of the surfactant is moderate, the absorbance of the emulsion is high, the surfactant molecules are closely arranged at the interface of the emulsion droplets, and the emulsifying effect is good; while when the concentration of the surfactant is too high or too low, the absorbance of the emulsion will decrease, and the emulsifying effect will be affected.

[0053] Through the cooperation between the above steps, this application can improve the efficiency and accuracy of detecting the emulsifying performance of low-foaming surfactants.

[0054] Further, in the above step S2, collecting the optical signal reflected by the emulsion sample includes: as Figure 2 shown, after the mid-infrared light penetrates the first zinc selenide window 10 and irradiates the surface of the emulsion sample, the detection unit detects the reflected light 13 on the surface of the emulsion sample. If the first reflected light on the surface of the emulsion sample is less than the preset threshold, the angle of the mid-infrared light irradiating the surface of the emulsion sample is adjusted; in addition, when irradiating the surface of the emulsion sample, a guiding laser 14 is also added to help the mid-infrared light locate and align with the surface of the emulsion sample because the mid-infrared light is invisible to the naked eye.

[0055] After adjusting the angle multiple times, if the second reflected light on the surface of the emulsion sample is still less than the preset threshold, the scattered light signal from the bottom of the emulsion sample container is captured as the optical signal reflected by the emulsion sample.

[0056] Specifically, the mid-infrared light is selected to penetrate the zinc selenide window because the zinc selenide window has good mid-infrared light transmittance, which can ensure that the optical signal is not lost during the penetration process. The preset threshold is relatively small, specifically set in the actual application scenario. When the intensity of the first reflected light detected by the detection unit is less than the preset threshold, it indicates that the current mid-infrared light irradiation angle is not good, resulting in a weak reflected light signal. To solve this problem, the angle of the incident light is adjusted to find the optimal reflected light intensity. In addition, during the irradiation process, the added guiding laser mainly functions to help the mid-infrared light locate and align with the surface of the emulsion sample, ensuring that the light can accurately irradiate the target area, thereby improving the detection accuracy. After adjusting the angle multiple times, if the intensity of the reflected light on the surface of the emulsion sample is still less than the preset threshold, it may be due to the properties of the emulsion sample or the container structure. To address this situation, another signal collection strategy is carried out, that is, capturing the scattered light signal from the bottom of the emulsion sample container. Although the scattered light signal is not as strong and direct as the direct reflected light, it still contains the absorption data of the emulsion sample to light and can still be used for the analysis and evaluation of the emulsifying performance of low-foaming surfactants.

[0057] Further, capturing the scattered light signal from the bottom of the emulsion sample container includes: as Figure 2 , after the mid-infrared light 12 reaches the bottom of the emulsion sample container, it scatters in all directions, generating scattered light 13. The scattered light 13 penetrates the second zinc selenide window 16 and is collected by the first parabolic-shaped optical mirror 21 through the middle hole, and then further focused by the second parabolic-shaped optical mirror 22 and reaches the detector 23. The purpose of the second parabolic-shaped optical mirror 22 is to guide the scattered light 13 to the detector 23.

[0058] Specifically, to effectively capture the scattered light signal, a collection system composed of a second zinc selenide window, two parabolic-shaped optical mirrors, and a detector is designed to improve the collection efficiency and accuracy of the scattered light signal. The scattered light first penetrates the second zinc selenide window 10 to ensure that the scattered light is not lost during the penetration process; then, the scattered light 13 is collected by the first parabolic-shaped optical mirror 21 through the hole in the middle. The design of the parabolic mirror is to direct the scattered light to the next component; then, the scattered light is further focused by the second parabolic-shaped optical mirror 22, enhancing its intensity and more concentratedly irradiating the detector 23. The detector 23 can accurately capture and convert these scattered light signals into current signals. Through the above method, even when the scattered light intensity is weak, it can be effectively captured and guided to the detector.

[0059] Furthermore, when necessary, an optoelectronic converter can be used to convert the optical signal reflected by the emulsion sample into an electrical current signal, and the obtained electrical current signal is amplified to increase the amplitude of the electrical current signal so that it can be clearly captured even when the signal is weak, improving the detection accuracy. After obtaining the amplified electrical current signal, an analog-to-digital converter is used to convert it into a digital signal because digital signals are easy to store and transmit and are convenient for analysis on a computer. When the optical signal is captured by the detector and converted into a weak electrical current signal, the electrical current signal is sent into a signal amplifier. The role of the amplifier is to greatly enhance this weak electrical current signal to a suitable level for subsequent electrical data analysis. At the same time as amplification, a noise removal mechanism is equipped because during the actual detection process, the electrical current signal is often interfered by various external factors, such as electromagnetic noise, circuit noise caused by environmental temperature changes, etc. Noise will seriously affect the accuracy of subsequent data processing. The electrical current signal after amplification and noise removal is converted into a digital signal for computer data processing and analysis.

[0060] Furthermore, in the above step S3, establishing the relationship model between the absorption spectrum of the reference emulsion, the substrate signal, and the noise signal includes:

[0061] Collect the absorption spectra of reference emulsions with multiple preset concentrations at multiple specific wavelengths, store them in the spectral database, establish the relationship model between the absorption spectrum of the reference emulsion, the substrate signal, and the noise signal, and represent it using Equation 1: A = (J0 - J1) - c1B - c2N, where J0 represents the incident optical signal of the reference emulsion, J1 represents the reflected optical signal of the reference emulsion, A represents the measured absorption spectrum of the reference emulsion, B represents the substrate signal, N represents the noise signal, c1 represents the coefficient of the substrate signal, and c2 represents the coefficient of the noise signal.

[0062] Specifically, in order to accurately evaluate the emulsifying performance of low-foaming surfactants, it is necessary to establish a relationship model between the absorption spectrum of the reference emulsion, the substrate signal, and the noise signal, and predict the absorption spectrum of the emulsion sample through the relationship model. First, collect the absorption spectrum data of a series of reference emulsions with preset concentrations at multiple specific wavelengths. To ensure the accuracy of the reference data, the data is obtained under strictly controlled conditions. When establishing the relationship model, the influence of the substrate signal and the noise signal on the measured absorption spectrum is also considered. The substrate signal mainly comes from the sample container, while the noise signal may come from various factors such as environmental interference and instrument error. To accurately describe the influence of the above factors on the measured absorption spectrum, formula 1 is introduced: A = (J0 - J1) - c1B - c2N. The difference between J0 and J1 reflects the light absorption of the emulsion. A represents the measured absorption spectrum of the reference emulsion, which is the target signal that we hope to obtain through the model. B represents the substrate signal, and N represents the noise signal. They are combined with the measured absorption spectrum A through coefficients c1 and c2 respectively, and together constitute the difference between the measured signal and the theoretical signal.

[0063] By fitting the parameter data, the values of coefficients c1 and c2 can be determined, thus establishing a relationship model between the absorption spectrum of the reference emulsion, the substrate signal, and the noise signal. This relationship model can accurately extract the absorption spectrum information from the measured signal, providing a basis for subsequent calculation of absorbance and evaluation of emulsifying performance.

[0064] Furthermore, in the above step S3, based on the relationship model, predict the absorption spectrum of the emulsion sample:

[0065] Based on the minimum sum of the squares of the errors between the predicted absorption spectrum of the reference emulsion in formula 1 and the measured absorption spectrum of the reference emulsion, calculate the coefficient c1 of the substrate signal and the coefficient c2 of the noise signal; substitute the coefficient c1 of the substrate signal and the coefficient c2 of the noise signal into formula 1 to predict the absorption spectrum of the emulsion sample.

[0066] Specifically, using the known reference emulsion data, by minimizing the sum of the squares of the errors between the predicted absorption spectrum of the reference emulsion and the measured absorption spectrum of the reference emulsion, determine the optimal values of coefficients c1 and c2. Specifically, it can be solved by various methods, such as the gradient descent method. J0 and J1 respectively represent the incident light signal and the reflected light signal of the emulsion sample or the reference emulsion, which are obtained during actual application. The incident light signal of the emulsion sample is the mid-infrared light of a specific wavelength emitted by the laser, and the reflected light signal of the emulsion sample is the light signal reflected by the emulsion sample converted into a digital signal. The substrate signal and the noise signal will be described below.

[0067] Furthermore, the above step S4 also includes: Based on the predicted absorption spectrum of the emulsion sample, use formula 2: Measure the absorbance of the emulsion sample, where P represents the absorbance of the emulsion sample, and A′ represents the predicted absorption spectrum of the emulsion sample; establish a relationship curve between absorbance and concentration. As Figure 3 shown, substitute the absorbance of the predicted emulsion sample into the relationship curve to obtain and evaluate the emulsification performance of the emulsion based on the concentration value corresponding to the emulsion sample.

[0068] Specifically, the emulsification performance is evaluated by calculating the absorbance of the emulsion sample and establishing a relationship curve between absorbance and concentration, and the emulsification performance of the emulsion is quantitatively evaluated, making the detection result more accurate.

[0069] Furthermore, the above-mentioned base signal refers to: before detecting the emulsion, use a laser to emit mid-infrared light with a specific wavelength to irradiate the container 11 for holding the emulsion, and collect the optical signal reflected back by the container 11; repeat this step to obtain the optical signals reflected back by the container 11 at multiple different specific wavelengths, and establish a relationship list between the base signal and the specific wavelength. When calculating the coefficient of the above-mentioned base signal, obtain the corresponding base signal from the relationship list between the base signal and the specific wavelength based on the specific wavelength. Among them, the base signal corresponding to each specific wavelength is different, which can be reflected by the relationship list between the base signal and the specific wavelength.

[0070] Specifically, the base signal refers to a signal list related to the wavelength established by collecting and analyzing the reflection signals of the container under mid-infrared light irradiation with different specific wavelengths when using mid-infrared spectroscopy to detect the emulsion, providing a basis for subsequent solution component analysis.

[0071] Furthermore, the above-mentioned noise signal refers to: measure the emulsion with the same concentration k times at the same specific wavelength, and obtain the digital signal of each measurement. Calculate and based on the average value of the digital signals of the k measurements, and also calculate the difference between the digital signal of each measurement and the average value. Take the average value of the differences as the noise signal, where k represents a positive integer greater than or equal to 10.

[0072] Specifically, a laser is used to perform k measurements on the emulsion sample at this specific wavelength, where k is a positive integer greater than or equal to 10. This number of repeated measurements is to ensure that we can obtain sufficient data points to accurately estimate the noise signal. After each measurement, the reflected optical signal is converted into a digital signal and recorded. The digital signals of the k measurements are averaged to obtain the average digital signal value of the emulsion sample at this specific wavelength, which represents the true response of the emulsion to the light of this wavelength without noise interference. For the digital signal of each measurement, the difference between it and the average value is calculated, which reflects the degree of deviation between this measurement and the average value. The absolute values of all differences are averaged to obtain the average value of the differences, that is, the noise signal, which represents the measurement fluctuations caused by various random factors, such as instrument noise, environmental interference, etc. at the same specific wavelength and concentration. The noise signal provides a method for quantifying measurement fluctuations and interferences in this application, which helps to more accurately analyze the spectral characteristics of the emulsion.

[0073] Example Two:

[0074] The method for detecting the emulsifying performance of a low-foaming surfactant in Example One of the present application was described above. Next, a system for detecting the emulsifying performance of a low-foaming surfactant in Example Two of the present application will be described. As Figure 4 shown, a system for detecting the emulsifying performance of a low-foaming surfactant in Example Two of the present application includes:

[0075] A configuration unit for configuring low-foaming surfactant solutions with various different concentrations and separately making them into emulsion samples. Among them, the configuration temperature, stirring time, stirring speed, and volume of each emulsion sample with a certain concentration are the same;

[0076] A collection unit for irradiating the surface of the emulsion sample with mid-infrared light of a specific wavelength emitted by a laser and collecting the optical signal reflected by the emulsion sample;

[0077] A prediction unit for collecting the absorption spectra of a variety of reference emulsions with preset concentrations at a variety of specific wavelengths, establishing a relationship model between the absorption spectrum of the reference emulsion and the base signal and the noise signal, and predicting the absorption spectrum of the emulsion sample based on the relationship model;

[0078] An evaluation unit for calculating the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample and evaluating the emulsifying performance of the emulsion based on the pre-established relationship curve between absorbance and concentration.

[0079] Through the collaborative cooperation of the above-mentioned various components, the present application can improve the efficiency and accuracy of detecting the emulsifying performance of low-foaming surfactants.

[0080] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, systems, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0081] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0082] As described above, the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A method for detecting the emulsifying performance of a low-foaming surfactant, characterized in that The method includes: Step S1: Configure low-foaming surfactant solutions with multiple different concentrations, and respectively make them into emulsion samples. Among them, the configuration temperature, stirring time, stirring speed, and volume of each emulsion sample with a certain concentration are the same; Step S2: Irradiate the surface of the emulsion sample with mid-infrared light of a specific wavelength emitted by a laser, and collect the optical signal reflected by the emulsion sample; Step S3: Collect the absorption spectra of multiple reference emulsions with preset concentrations at multiple specific wavelengths, establish a relationship model between the absorption spectra of the reference emulsions and the substrate signal and the noise signal, and predict the absorption spectrum of the emulsion sample based on the relationship model; Step S4: Calculate the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample, and evaluate the emulsifying performance of the emulsion based on the pre-established relationship curve between absorbance and concentration.

2. The method according to claim 1, wherein In step S2, collecting the optical signal reflected by the emulsion sample includes: After the mid-infrared light penetrates the first zinc selenide window and irradiates the surface of the emulsion sample, the detection unit detects the reflected light on the surface of the emulsion sample. If the first reflected light on the surface of the emulsion sample is less than a preset threshold, adjust the angle of the mid-infrared light irradiating the surface of the emulsion sample; After adjusting the angle multiple times, if the second reflected light on the surface of the emulsion sample is still less than the preset threshold, capture the scattered light signal from the bottom of the emulsion sample container as the optical signal reflected by the emulsion sample.

3. The method according to claim 2, wherein Capturing the scattered light signal from the bottom of the emulsion sample container includes: The mid-infrared light scatters around after reaching the bottom of the emulsion sample container, generating scattered light. The scattered light penetrates the second zinc selenide window and is collected by the first parabolic-shaped optical reflector through the middle hole, and then further focused by the second parabolic-shaped optical reflector and reaches the detector.

4. The method according to claim 1, wherein In step S3, establishing the relationship model between the absorption spectra of the reference emulsions and the substrate signal and the noise signal includes: Collect the absorption spectra of multiple reference emulsions with preset concentrations at multiple specific wavelengths, store them in the spectral database, establish the relationship model between the absorption spectra of the reference emulsions and the substrate signal and the noise signal, and use formula 1: A = (J0 - J1) - c1B - c2N to represent, where J0 represents the incident optical signal of the reference emulsion, J1 represents the reflected optical signal of the reference emulsion, A represents the measured absorption spectrum of the reference emulsion, B represents the substrate signal, N represents the noise signal, c1 represents the coefficient of the substrate signal, and c2 represents the coefficient of the noise signal.

5. The method according to claim 4, wherein In step S3, predicting the absorption spectrum of the emulsion sample based on the relationship model: Based on the minimum sum of the squares of the errors between the predicted absorption spectrum of the reference emulsion and the measured absorption spectrum of the reference emulsion in formula 1, calculate the coefficient c1 of the substrate signal and the coefficient c2 of the noise signal; Substitute the coefficient c1 of the base signal and the coefficient c2 of the noise signal into Formula 1 to predict the absorption spectrum of the emulsion sample.

6. The method according to claim 4, wherein In step S4, calculate the absorbance of the emulsion sample: Based on the predicted absorption spectrum of the emulsion sample, use Equation 2: Calculate the absorbance of the emulsion sample, where P represents the absorbance of the emulsion sample and A′ represents the predicted absorption spectrum of the emulsion sample.

7. The method according to claim 6, wherein Step S4 further includes: Establish a relationship curve between absorbance and concentration. Substitute the predicted absorbance of the emulsion sample into the relationship curve to obtain and evaluate the emulsification performance of the emulsion based on the concentration value corresponding to the emulsion sample.

8. The method according to claim 4, characterized in that, The base signal refers to: Before detecting the emulsion, use the laser to emit mid-infrared light with a specific wavelength to irradiate the container to hold the emulsion, and collect the optical signal reflected by the container; Repeat this step to obtain the optical signals reflected by the container at multiple different specific wavelengths, and establish a relationship list between the base signal and the specific wavelength.

9. The method according to claim 4, characterized in that, The noise signal refers to: Perform k measurements on the emulsion with the same concentration at the same specific wavelength, and obtain the digital signal of each measurement. Calculate and based on the average value of the digital signals of the k measurements, also calculate the difference between the digital signal of each measurement and the average value, and take the average value of the differences as the noise signal, where k represents a positive integer greater than or equal to 10.

10. A detection system for the emulsifying performance of a low-foam surfactant, which is used to implement a detection method for the emulsifying performance of a low-foam surfactant according to any one of claims 1-9, characterized in that, The system includes: A configuration unit for configuring low-foaming surfactant solutions with multiple different concentrations and separately making them into emulsion samples, where the configuration temperature, stirring time, stirring speed, and volume of each emulsion sample with a certain concentration are the same; A collection unit for irradiating the surface of the emulsion sample with mid-infrared light with a specific wavelength emitted by the laser and collecting the optical signal reflected by the emulsion sample; A prediction unit for collecting the absorption spectra of reference emulsions with multiple preset concentrations at multiple specific wavelengths, establishing a relationship model between the absorption spectra of the reference emulsions, the base signal, and the noise signal, and predicting the absorption spectrum of the emulsion sample based on the relationship model; An evaluation unit for calculating the absorbance of the emulsion sample based on the predicted absorption spectrum of the emulsion sample and evaluating the emulsification performance of the emulsion based on the pre-established relationship curve between absorbance and concentration.

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