On-line monitoring system and method for gel solidification using multi-speckle diffuse wave spectroscopy

Abstract

This invention discloses an online monitoring system and method for speckle diffusion spectroscopy of gel curing. The system includes a laser source, a beam expander module, a beam adjustment module, a sample stage, a signal acquisition module, and a signal processing module. The laser source, beam expander module, and beam adjustment module are sequentially arranged on one side of the sample stage. The linearly polarized incident beam emitted by the laser source is expanded by the beam expander module, increasing the detection area of ​​the sample. The beam adjustment module adjusts the optical path of the incident beam to enter the sample at a small angle. The signal acquisition module is located directly above the sample stage to detect the backscattered light signal and acquire the speckle image formed by the interference of the backscattered light signal. The signal processing module receives and processes the speckle image and calculates the intensity correlation coefficient and intensity autocorrelation function of the speckle image. Based on the intensity autocorrelation function, relevant parameters can be obtained to acquire the curing information of the gel sample.

Description

Technical Field

[0001] This invention relates to the field of gel curing information measurement technology, and in particular to a diffusion wave spectroscopy measurement system and method for gel curing. Background Technology

[0002] Gels are polymer materials widely used in food, pharmaceuticals, electronic equipment, and construction engineering. During the curing process of gels, the cross-linking of polymer chains forms a three-dimensional network structure, giving them unique structure and properties. Among these, the gel's properties such as toughness, mechanical strength, and stability are directly related to the formation of the three-dimensional network structure.

[0003] However, the curing process of gels is complex due to material properties and the influence of external environmental factors such as temperature and humidity. In the development and research of gel products, rheology or differential scanning calorimetry are commonly used to study the curing process. However, these methods require complex experimental setups and demanding environmental conditions, hindering large-scale deployment and practical application. In practical applications, the curing process of gel products is often judged based on experience or tactile methods such as finger touch, which can easily lead to misjudgments of the curing stage and affect the post-curing properties. Summary of the Invention

[0004] The purpose of this invention is to provide an online monitoring system and method for multispot diffusion wave spectroscopy of gel curing. The system has a simple structure, high sensitivity and processing efficiency, and can realize real-time online monitoring of gel curing.

[0005] To achieve the objectives of this invention, an online monitoring system for speckle diffusion spectroscopy of gel-cured gel is provided, comprising a laser source, a beam expander module, a beam adjustment module, a sample stage, a signal acquisition module, and a signal processing module. The laser source, beam expander module, and beam adjustment module are sequentially disposed on one side of the sample stage. The linearly polarized incident beam emitted by the laser source is expanded by the beam expander module, increasing the detection area of ​​the sample. The beam adjustment module adjusts the optical path of the incident beam to enter the sample at a small angle, reducing the interference of specular reflection on the scattered light signal and improving the signal-to-noise ratio. The signal acquisition module is disposed directly above the sample stage and is used to detect the backscattered light signal and acquire the speckle image formed by the interference of the multiple scattered light signals. The signal processing module is connected to the signal acquisition module and is used to receive and process the speckle image, and calculate the intensity correlation coefficient and intensity autocorrelation function of the speckle image. Based on the intensity autocorrelation function, relevant parameters can be obtained to acquire the curing information of the gel sample.

[0006] Compared to existing technologies, this invention provides an online monitoring system for multi-spot diffusion wave spectroscopy of gel curing. This system utilizes the phenomenon of light scattering to obtain information on the motion of particles within the sample, reflecting the gel curing process and enabling non-contact measurement. Simultaneously, the system achieves small-angle incident light through a beam adjustment module, reducing interference from incoherent light such as specular reflections and improving the signal-to-noise ratio.

[0007] Furthermore, the center of the laser source and the center of the beam expander module are on the same axis.

[0008] Furthermore, the signal processing module receives and processes the speckle image. Through a baseline adaptive judgment scheme and a delay time adaptive adjustment scheme, it can realize the real-time processing and acquisition of the intensity autocorrelation function at different curing stages. The curing information can be obtained through the intensity autocorrelation function, thereby realizing online monitoring of the curing process.

[0009] Furthermore, the laser source includes a laser and a first polarizer, wherein the laser is used to emit an incident beam and the first polarizer is used to increase the polarization degree of the incident beam.

[0010] Furthermore, the signal acquisition module includes a second polarizer and an area array detector, with the second polarizer located above the sample stage and the area array detector located above the second polarizer.

[0011] Furthermore, the polarizer and the laser light source form a cross-polarization setting, which can reduce the intensity of specular reflected light and low-order scattered light from the sample surface, and can extract multiple scattered light signals from inside the sample, thereby reflecting the overall particle motion information of the sample.

[0012] Furthermore, the area array detector can simultaneously detect multiple scattered light signals from different regions within the sample, acquire speckle images formed by the interference of multiple scattered light, increase the detection area, and improve detection efficiency.

[0013] Area array detectors can increase the detection area, acquire multiple scattered light signals from moving particles at different spatial positions of the sample, and improve sensitivity, accuracy and processing efficiency.

[0014] This invention also provides an online monitoring method for speckle diffusion spectroscopy of gel-cured gels, employing the aforementioned monitoring system, and comprising the following steps:

[0015] S1: The linearly polarized incident beam emitted by the laser source is expanded by the beam expander module and then enters the sample at a small angle through the beam adjustment module.

[0016] S2: The signal acquisition module detects multiple scattered light signals from the sample in the back region and acquires speckle images formed by the interference of multiple scattered light.

[0017] S3: The signal processing module calculates the intensity correlation coefficient of the speckle image based on the speckle image, and obtains the intensity autocorrelation function of the speckle image sequence based on the intensity correlation coefficient; the intensity autocorrelation function can be used to obtain relevant parameters and reflect the curing information of the gel sample. The intensity autocorrelation function is processed and obtained in real time by judging the fluctuation intensity of the intensity autocorrelation function, and the delay time and characteristic time window for calculating the intensity autocorrelation function are adaptively adjusted according to the change of the dynamic intensity of the sample.

[0018] Furthermore, in step S3, a baseline adaptive judgment scheme is adopted to realize the real-time processing and acquisition of the intensity autocorrelation function by judging the intensity of the fluctuation of the intensity autocorrelation function, thereby achieving online monitoring; in step S3, a delay time adaptive adjustment scheme is adopted to adaptively adjust the delay time and characteristic time window for calculating the intensity autocorrelation function according to the change of the dynamic intensity of the sample, thereby improving statistical accuracy and reducing measurement error.

[0019] Compared with the prior art, the present invention can achieve at least the following beneficial effects:

[0020] (1) The present invention provides a simple, non-contact, highly sensitive real-time online monitoring system that can monitor the curing rate and degree of curing of gels, which helps to understand and control the curing process of gel products and guide and optimize the development and application of gel products.

[0021] (2) The present invention realizes the real-time processing and acquisition of the intensity autocorrelation function of different curing stages through the baseline adaptive judgment scheme and the delay time adaptive adjustment scheme. The curing information can be obtained through the intensity autocorrelation function, and the online monitoring of the curing process can be realized.

[0022] To better understand and implement this invention, the following detailed description is provided in conjunction with the accompanying drawings. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the structure of the gel-cured speckle diffusion wave spectroscopy online monitoring system of the present invention;

[0024] Figure 2 This is a schematic diagram of the signal acquisition module of the present invention.

[0025] Figure 3 The present invention provides an online monitoring method for multi-spot diffusion wave spectroscopy to monitor the intensity autocorrelation function curve of gel curing.

[0026] Figure 4 The graph shows the results of monitoring the attenuation rate of gel solidification using the multi-spot diffusion wave spectroscopy online monitoring method of the present invention.

[0027] Figure 5 The figure shows the results of monitoring the shape factor of gel curing using the multi-spot diffusion wave spectroscopy online monitoring method of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] In the description of this invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0030] The online monitoring system for multispot diffusion wave spectroscopy of the present invention is illustrated through the following embodiments.

[0031] Please see Figure 1 This is a schematic diagram of the structure of an online monitoring system for multispot diffusion wave spectroscopy of gel-cured gel. The system includes a laser source 1, a beam expander module 2, a beam adjuster module 3, a sample stage 4, a signal acquisition module 5, and a signal processing module 6.

[0032] The laser source 1, beam expander module 2, and beam adjustment module 3 are sequentially arranged on the same side of the sample stage 4. The center of the laser source 1 and the center of the beam expander module 2 are on the same axis. The linearly polarized incident beam emitted by the laser source 1 passes through the beam expander module 2 to expand the incident beam and increase the detection area of ​​the sample. The beam adjustment module 3 is located at the edge of the sample stage 4. The incident beam enters the beam adjustment module 3 through the center of the entrance port to adjust the incident light path. The incident light exits from the exit port of the beam adjustment module 3 at a small angle of 5 to 15 degrees. The incident light beam is directed towards the sample stage 4 to reduce the interference of specular reflection on the scattered light signal and improve the signal-to-noise ratio. Scattered light is generated by the interaction between moving particles in the sample and the incident light beam. The signal acquisition module 5 is located directly above the sample stage 4 to detect the backscattered light signal of the sample and acquire the speckle image formed by the interference of the multiple scattered light signals. The signal processing module 6 is connected to the signal acquisition module 5 to receive and process the speckle image and calculate the intensity correlation coefficient and intensity autocorrelation function of the speckle image. The relevant parameters can be obtained from the intensity autocorrelation function to acquire the curing information of the gel sample.

[0033] In some embodiments of the present invention, the laser source includes a laser and a first polarizer, the laser being used to emit an incident beam and the first polarizer being used to increase the polarization degree of the incident beam.

[0034] In some embodiments of the present invention, please refer to Figure 2 The signal acquisition module 5 includes a second polarizer 51 and an area array detector 52. The second polarizer 51 is located above the sample stage, and the area array detector is located above the second polarizer.

[0035] The second polarizer 51 is adjusted to a cross-polarization setting with the laser source 1, which can reduce the intensity of specular reflected light and low-order scattered light from the sample surface, detect multiple scattered light inside the sample after multiple scattering, extract the multiple scattered light from inside the sample, and improve the signal-to-noise ratio and accuracy of the measurement. The area array detector 52 is used to collect images of multiple speckle patterns formed by the interference of scattered light, containing information on the motion of particles inside the sample. Preferably, the second polarizer 51 is a polarizer with an extinction ratio of 500:1; the area array detector 52 is preferably a monochrome CCD camera, which realizes high sensitivity and high accuracy in acquiring speckle images, and reduces the load of subsequent speckle image processing and increases the processing speed.

[0036] In the signal processing module 6, the intensity correlation coefficient and intensity autocorrelation function of the speckle image are processed and obtained in real time. Then, the corresponding parameters are obtained by fitting the intensity autocorrelation function to reflect the curing process of the gel sample.

[0037] In some embodiments of the present invention, a method for online monitoring of speckle diffusion spectroscopy of gel-cured materials is provided, comprising the following steps:

[0038] S1: The linearly polarized incident beam emitted by the laser source 1 is expanded by the beam expander module 2 and then enters the sample at a small angle through the beam adjustment module 3.

[0039] S2: Signal acquisition module 5 detects multiple scattered light signals from the sample in the back region and acquires speckle images formed by the interference of multiple scattered light.

[0040] S3: Signal processing module 6 calculates the intensity correlation coefficient of the speckle image based on the speckle image, and obtains the intensity autocorrelation function of the speckle image sequence based on the intensity correlation coefficient; the correlation parameters can be obtained based on the intensity autocorrelation function, and can reflect the curing information of the gel sample.

[0041] The principle of the online monitoring method for speckle diffusion spectroscopy of gel-cured gel is as follows:

[0042] By acquiring and processing speckle images, computational efficiency can be improved, enabling online monitoring. Particle motion within a sample leads to variations in multiple scattered light signals, causing fluctuations in the intensity of the speckle patterns formed by their interference. The online monitoring method using multi-speckle diffuse wave spectroscopy can simultaneously obtain the intensity of multiple speckle signals by acquiring speckle images. Spatial statistical averaging can improve statistical accuracy, thereby increasing computational efficiency.

[0043] Online monitoring is achieved by acquiring intensity autocorrelation function (ICF) curves at different curing times in real time. The decay segment of the ICF curve reflects the dynamic information of the sample, thus the curing process can be reflected through the ICF. However, the system dynamics change during gel curing, and the time it takes for the ICF curve to decay to the baseline varies. Simultaneously, due to the weakening system dynamics, system noise such as detector dark current affects the calculation of the ICF, reducing the signal-to-noise ratio. Therefore, using fixed measurement and delay times when calculating the ICF curve for each stage cannot yield high-quality decay segments of the ICF curve. This invention employs a baseline adaptive judgment scheme and a delay time adaptive adjustment scheme, enabling real-time processing and acquisition of ICF curves at different curing stages, thus achieving online monitoring of the curing process.

[0044] Specifically, the intensity correlation coefficient g2(t, τ) of the speckle image is calculated based on the speckle image, and the expression for the intensity correlation coefficient is as follows:

[0045]

[0046] Where t is the acquisition time of the reference speckle image, and τ is the delay time; Ip (t), I p (t+τ) represent the intensity of the corresponding pixels in the speckle images acquired at times t and t+τ, respectively; <...>p is the ensemble average; the intensity autocorrelation function g2(τ) of the speckle image sequence can be obtained through the intensity correlation coefficient, and its expression is:

[0047] g2(τ)=<g2(t,τ)> δt

[0048] Here, δt is the characteristic time window. By statistically averaging the intensity correlation coefficient within a small time window smaller than the characteristic time scale, the error caused by statistical noise can be reduced, and an accurate intensity autocorrelation function can be obtained. The characteristic time window can be dynamically adjusted according to the dynamic changes of the system during the curing process.

[0049] The expression for obtaining gel sample curing information based on the intensity autocorrelation function is as follows:

[0050] g2(τ)=βexp[-2(Γt) γ ]+b

[0051] Where β is the coherence factor; τ is the delay time; b is the baseline; Γ is the decay rate; and γ is the shape factor. Γ, the decay rate, characterizes the rate of decay of the intensity autocorrelation function, reflects the motion information of particles within the sample, and can characterize the curing speed and curing process of the gel sample.

[0052] γ is a shape factor that describes the shape of the intensity autocorrelation function curve and characterizes the steepness of its decay. For stable Brownian suspensions, the decay of the intensity autocorrelation function follows a simple exponential behavior, i.e., γ = 1. However, for polymer samples such as gels, due to the restrictive effect of the three-dimensional cross-linked network on particle motion, the decay of the intensity autocorrelation function deviates from the simple exponential behavior (γ > 1). The change in γ reflects the formation process of the cross-linked network and characterizes the solidification state of the gel sample.

[0053] Real-time online monitoring is achieved through a baseline adaptive judgment scheme. When the intensity autocorrelation function reaches the baseline, it indicates that the speckle image and the reference speckle image are no longer correlated. The calculation of this intensity autocorrelation function curve can then be truncated, and the next stage of intensity autocorrelation function curve calculation can begin. The baseline adaptive judgment scheme method is as follows:

[0054]

[0055] Where X is the intensity autocorrelation function value, and n is the number of consecutive intensity autocorrelation function values. S is the mean of n consecutive intensity autocorrelation function values. 2This represents the fluctuation intensity of the intensity autocorrelation function. While calculating the intensity autocorrelation function, S is also calculated and determined. 2 The size of S. 2 Less than a preset value (in some embodiments of the present invention, the preset value is 10) -6 At this point, it is assumed that the intensity autocorrelation function curve has decayed to the baseline, and the speckle image is no longer correlated with the reference speckle image. Truncating the calculation of the intensity autocorrelation function at this stage yields the complete decay segment of the intensity autocorrelation function, allowing for the calculation of the intensity autocorrelation function in the next stage.

[0056] An adaptive delay time adjustment scheme reduces measurement errors and improves statistical accuracy. Before obtaining the intensity autocorrelation function for the next stage, the delay time τ and the characteristic time window δt are adjusted based on the relevant parameters obtained from fitting the intensity autocorrelation function of the previous stage. During online monitoring of the curing process, the system iterates continuously according to dynamic changes. When the system dynamics weaken, the delay time τ and the characteristic time window δt are increased to reduce errors caused by statistical noise and reduce computational load. Conversely, when the system dynamics suddenly accelerate, the delay time τ and the characteristic time window δt are decreased to obtain more data on the decay segment of the intensity autocorrelation function.

[0057] The following is an example of using the multi-spot diffusion wave spectroscopy online monitoring method of the present invention to monitor the curing process of epoxy resin gel samples.

[0058] In some embodiments of the present invention, such as Figure 3 , Figure 4 and Figure 5 As shown, the curing process of epoxy resin gel is monitored online using the multi-spot diffusion wave spectroscopy online monitoring method of the present invention.

[0059] Figure 3 The image shows the intensity autocorrelation function (IAF) curves and fitted curves obtained at different curing times during the gel sample curing process. It is evident that the online monitoring method of multi-spot diffusion wave spectroscopy of this invention can achieve real-time processing and acquisition of the IAF during the gel sample curing process. At different curing stages, the baseline adaptive judgment scheme can accurately determine the baseline of the IAF, obtaining the decay segment of the IAF curve; simultaneously, the delay time adaptive adjustment scheme adjusts the delay time and characteristic time window according to the dynamic changes of the sample, obtaining high-quality IAF curves; further fitting based on the decay segment of the IAF curve yields gel sample curing information.

[0060] Figure 4 and Figure 5The decay rate Γ and shape factor γ of the gel sample, obtained through the intensity autocorrelation function, are shown as solidification information during the gel solidification process. It is evident that the decay rate Γ and shape factor γ change accordingly as the cross-linked network of the gel sample forms. The solidification information of the gel is reflected through particle motion information. During the gel solidification process, the decay rate Γ decreases, and the shape factor γ > 1, indicating that the decay of the intensity autocorrelation function deviates from simple exponential behavior. This reflects that the formation of the three-dimensional cross-linked network during the gel solidification process restricts and hinders particle motion, leading to slower particle movement. Simultaneously, during the gel solidification process, the decreasing trend of the decay rate Γ and the shape factor γ also change accordingly at different stages of the three-dimensional network structure formation. This demonstrates that the present invention can achieve real-time online monitoring of gel solidification.

[0061] The embodiments described above are merely specific implementations of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and the present invention also intends to include these modifications and variations.

Claims

1. An online monitoring system for multi-spot diffusion wave spectroscopy of gel-cured materials, characterized in that, It includes a laser source, a beam expander module, a beam adjustment module, a sample stage, a signal acquisition module, and a signal processing module; The laser source, the beam expander, and the beam adjustment module are sequentially arranged on one side of the sample stage. The laser source is used to emit a linearly polarized incident beam, and the beam expander is used to expand the linearly polarized incident beam to increase the detection area of ​​the sample. The beam adjustment module is used to adjust the optical path of the incident beam so that it enters the sample at a small angle. The signal acquisition module is located directly above the sample stage and is used to detect backscattered light signals and acquire speckle images formed by interference of the backscattered light signals. The signal processing module is connected to the signal acquisition module and is used to receive and process the speckle image, calculate the intensity correlation coefficient and intensity autocorrelation function of the speckle image, obtain relevant parameters based on the intensity autocorrelation function, and acquire the curing information of the gel sample. The expression for the intensity correlation coefficient is: The intensity autocorrelation function of the speckle image sequence is obtained based on the intensity correlation coefficient. : The curing information of the gel sample is obtained based on the intensity autocorrelation function: In the formula, The intensity correlation coefficient of the speckle image. For reference, the acquisition time of the speckle image, For delay time; , They are and The intensity of the corresponding pixel in the speckle image acquired at any given time; It is the set average; is the intensity autocorrelation function of the speckle image sequence; For characteristic time windows; Coherence factor; For delay time; As the baseline; The decay rate is used to characterize the curing speed and curing process of gel samples. This is the shape factor.

2. The online monitoring system for multi-spot diffusion wave spectroscopy of gel-cured gel according to claim 1, characterized in that, The center of the laser source and the center of the beam expander module are on the same axis.

3. The online monitoring system for multi-spot diffusion wave spectroscopy of gel-cured gel according to claim 1, characterized in that, The laser source includes a laser and a first polarizer. The laser is used to emit an incident beam, and the first polarizer is used to increase the polarization degree of the incident beam.

4. The online monitoring system for multi-spot diffusion wave spectroscopy of gel-cured gel according to any one of claims 1-3, characterized in that, The signal acquisition module includes a second polarizer and an area array detector. The second polarizer is located above the sample stage, and the area array detector is located above the second polarizer.

5. The online monitoring system for multi-spot diffusion wave spectroscopy of gel-cured gel according to claim 4, characterized in that, The second polarizer forms a cross-polarization configuration with the laser source.

6. The online monitoring system for multi-spot diffusion wave spectroscopy of gel-cured gel according to claim 4, characterized in that, The array detector can simultaneously detect multiple scattered light signals from different regions within the sample to acquire speckle images formed by the interference of multiple scattered light signals.

7. A method for online monitoring of speckle diffusion spectroscopy in gel-cured gels, characterized in that, The online monitoring system according to any one of claims 1-6 includes the following steps: S1: The linearly polarized incident beam emitted by the laser source (1) is expanded by the beam expansion module (2) and then enters the sample at a small angle through the beam adjustment module (3); S2: The signal acquisition module (5) detects the multiple scattered light signals from the sample in the back region and acquires the speckle image formed by the interference of multiple scattered light. S3: The signal processing module (6) calculates the intensity correlation coefficient of the speckle image based on the speckle image, and obtains the intensity autocorrelation function of the speckle image sequence based on the intensity correlation coefficient; the relevant parameters can be obtained based on the intensity autocorrelation function, and the curing information of the gel sample can be reflected. In this case, the intensity autocorrelation function is processed and obtained in real time by judging the fluctuation intensity of the intensity autocorrelation function, and the delay time and characteristic time window for calculating the intensity autocorrelation function are adaptively adjusted according to the change of the dynamic intensity of the sample. The expression for the intensity correlation coefficient is as follows: The intensity autocorrelation function of the speckle image sequence is obtained based on the intensity correlation coefficient. : The curing information of the gel sample is obtained based on the intensity autocorrelation function: In the formula, The intensity correlation coefficient of the speckle image. For reference, the acquisition time of the speckle image, For delay time; , They are and The intensity of the corresponding pixel in the speckle image acquired at any given time; It is the set average; is the intensity autocorrelation function of the speckle image sequence; For characteristic time windows; Coherence factor; For delay time; As the baseline; The decay rate is used to characterize the curing speed and curing process of gel samples. This is the shape factor.

8. The method for online monitoring of speckle diffusion wave spectroscopy in gel-cured gels according to claim 7, characterized in that, The expression for the fluctuation intensity of the intensity autocorrelation function is as follows: In the formula, It is the value of the intensity autocorrelation function. It is the number of continuous intensity autocorrelation function values.

9. The method for online monitoring of speckle diffusion wave spectroscopy in gel-cured gels according to claim 8, characterized in that, The adaptive adjustment of the delay time and characteristic time window for calculating the intensity autocorrelation function includes: increasing the delay time when the system dynamically weakens. and characteristic time window When the system dynamics suddenly increase, reduce the delay time. and characteristic time window .

10. The method for online monitoring of speckle diffusion wave spectroscopy in gel-cured gels according to claim 7, characterized in that, The adaptive adjustment of the delay time and characteristic time window for calculating the intensity autocorrelation function includes: increasing the delay time when the system dynamically weakens. and characteristic time window When the system dynamics suddenly increase, reduce the delay time. and characteristic time window .

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