A method, equipment, medium, and product for detecting the content of silicone rubber.

Abstract

This application discloses a method, equipment, medium, and product for detecting the content of silicone rubber, relating to the field of silicone rubber content detection. The method includes obtaining silicone rubber samples with different silicone rubber formulations; performing terahertz detection on the silicone rubber samples to obtain the corresponding terahertz signals; determining the corresponding absorbance based on the terahertz signals; performing molecular simulations on the main components of the silicone rubber samples to obtain the vibrational characteristic frequencies of the main components at different terahertz frequencies; determining a regression function for silicone rubber content based on the vibrational characteristic frequencies of the main components at different terahertz frequencies and the corresponding absorbances; obtaining the absorbance of the silicone rubber to be tested, and using the regression function to determine the silicone rubber content. This application can improve the accuracy and efficiency of silicone rubber content detection.

Description

Technical Field

[0001] This application relates to the field of rubber content detection, and in particular to a method, equipment, medium, and product for detecting the rubber content of silicone rubber. Background Technology

[0002] Silicone rubber is a widely used insulating material in power grid systems. Devices and products made from silicone rubber include, but are not limited to, composite insulators, anti-flashover coatings, and cable termination accessories. However, silicone rubber is an organic polymer material, which is susceptible to aging under the stress of external environments during long-term operation. High-temperature vulcanized silicone rubber is the most widely used insulating material in power systems. Some high-temperature vulcanized silicone rubber insulating materials have poor aging resistance due to the use of inferior raw materials or processing techniques. The main components of silicone rubber are polydimethylsiloxane, silica, and aluminum hydroxide fillers, and the filler ratio has a significant impact on the performance of silicone rubber. An excessively high filler ratio leads to poor hydrophobicity, poor hydrophobic migration, low mechanical strength, and poor aging resistance in silicone rubber materials.

[0003] Therefore, the determination of rubber content plays a very important role in judging the performance of silicone rubber materials, and how to determine the rubber content is an urgent problem to be solved. Summary of the Invention

[0004] The purpose of this application is to provide a method, equipment, medium, and product for detecting the content of silicone rubber, which can improve the accuracy and efficiency of silicone rubber content detection.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] In a first aspect, this application provides a method for detecting the content of silicone rubber, the method comprising:

[0007] Obtain silicone rubber samples with different silicone rubber formulations;

[0008] Terahertz detection was performed on the silicone rubber sample to obtain the corresponding terahertz signal of the silicone rubber sample;

[0009] The corresponding absorption rate is determined based on the terahertz signal corresponding to the silicone rubber sample.

[0010] Molecular simulations were performed on the main components of the silicone rubber sample to obtain the vibrational characteristic frequencies of the main components at different terahertz frequencies.

[0011] The regression function for silicone rubber content was determined based on the vibration characteristic frequencies of the main components in the silicone rubber sample at different terahertz frequencies and the corresponding absorption rates.

[0012] The absorbance of the silicone rubber to be tested was obtained, and the rubber content of the silicone rubber was determined by regression function.

[0013] Optionally, the silicone rubber sample is high-temperature vulcanized silicone rubber for composite insulators; the main components of the high-temperature vulcanized silicone rubber for composite insulators are polydimethylsiloxane, aluminum hydroxide and fumed silica.

[0014] Optionally, obtaining silicone rubber samples with different silicone rubber formulations specifically includes:

[0015] Obtain raw materials for different silicone rubber formulations; the raw materials are polydimethylsiloxane, aluminum hydroxide, and fumed silica.

[0016] Add a predetermined amount of hydroxyl silicone oil and iron oxide red to the raw materials;

[0017] The raw materials containing a set amount of hydroxyl silicone oil and iron oxide red were mixed using a rubber mixing machine;

[0018] After mixing evenly, the mixed raw materials are heat-treated at a set temperature for a set time.

[0019] After heat treatment, a vulcanizing agent is added, and the raw material with the added vulcanizing agent is vulcanized and molded using a flat vulcanizing machine to obtain a silicone rubber sample.

[0020] Optionally, the thickness of the silicone rubber sample is 2 mm.

[0021] Optionally, the method for performing molecular simulations on the main components of the silicone rubber sample is the B3LYP method in density functional theory.

[0022] Optionally, the step of performing molecular simulations on the main components of the silicone rubber sample to obtain the vibrational characteristic frequencies of the main components at different terahertz frequencies specifically includes:

[0023] The vibration characteristic frequency analysis within the optimized and defined range was performed using Gaussian09 software.

[0024] The M06-2X / 6-31+G(d,p) function with corrected mixing was used for optimization and dispersion analysis of vibration characteristic frequencies.

[0025] Secondly, this application provides a silicone rubber content detection device, the silicone rubber content detection device comprising:

[0026] The silicone rubber sample acquisition module is used to acquire silicone rubber samples with different silicone rubber formulations.

[0027] The terahertz signal determination module is used to perform terahertz detection on the silicone rubber sample and obtain the terahertz signal corresponding to the silicone rubber sample.

[0028] The absorption rate determination module is used to determine the corresponding absorption rate based on the terahertz signal corresponding to the silicone rubber sample.

[0029] The molecular simulation module is used to perform molecular simulations on the main components of the silicone rubber sample to obtain the vibrational characteristic frequencies of the main components of the silicone rubber sample at different terahertz frequencies.

[0030] The module for determining the rubber content regression function is used to determine the rubber content regression function based on the vibration characteristic frequencies of the main components in the silicone rubber sample at different terahertz frequencies and the corresponding absorption rates.

[0031] The rubber content determination module is used to obtain the absorption rate of the silicone rubber to be tested and to determine the rubber content of the silicone rubber using a regression function.

[0032] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned method for detecting the content of silicone rubber.

[0033] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method for detecting the content of silicone rubber.

[0034] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method for detecting the content of silicone rubber.

[0035] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0036] This application provides a method, equipment, medium, and product for detecting the content of silicone rubber. By performing terahertz detection on silicone rubber samples with different formulations, corresponding terahertz signals are obtained. Then, molecular simulations are performed on the main components of the silicone rubber samples to obtain the vibrational characteristic frequencies of the main components at different terahertz frequencies. The silicone rubber content of the sample is determined based on the vibrational characteristic frequencies of the main components at different terahertz frequencies. This application combines the results of molecular simulations of different components in silicone rubber for content detection, achieving greater accuracy while maintaining efficiency. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic flowchart of a method for detecting the content of silicone rubber in one embodiment of this application;

[0039] Figure 2 This is a schematic diagram showing the absorption rate of the silicone rubber sample.

[0040] Figure 3 A schematic diagram of the molecular model of the main components in the silicone rubber sample;

[0041] Figure 4 A schematic diagram of the absorption rate of the molecular model for each component;

[0042] Figure 5 This is a schematic diagram showing the absorption rate of the silicone rubber sample in the range of 2.1 Hz to 2.3 Hz.

[0043] Figure 6 This is a schematic diagram showing the relationship between adhesive content and absorption rate. Detailed Implementation

[0044] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0045] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0046] In one exemplary embodiment, such as Figure 1 As shown, a method for detecting the content of silicone rubber is provided, the method comprising the following steps S101 to S106. Wherein:

[0047] S101, Obtain silicone rubber samples with different silicone rubber formulations;

[0048] S101 specifically includes:

[0049] S11, Obtain raw materials for different silicone rubber formulations; the raw materials are polydimethylsiloxane, aluminum hydroxide and fumed silica;

[0050] Among them, polydimethylsiloxane (rubber content) is the basic formula for high-temperature vulcanized silicone rubber; aluminum hydroxide and fumed silica are used to ensure that the sample has good mechanical strength and flame retardancy.

[0051] S12, add a set amount of hydroxyl silicone oil and iron oxide red to the raw materials;

[0052] S13, using a rubber mixing mill to mix raw materials with a set amount of hydroxyl silicone oil and iron oxide red, so that the components are evenly distributed, thereby eliminating the agglomeration of fillers in rubber.

[0053] S14, After mixing evenly, heat-treat the evenly mixed raw materials at a set temperature for a set time; wherein, the set temperature is 150℃ and the set time is 2 hours.

[0054] S15, after heat treatment, a vulcanizing agent is added, and the raw material with added vulcanizing agent is vulcanized and molded using a flat vulcanizing machine to obtain a silicone rubber sample.

[0055] The thickness of the silicone rubber sample was 2 mm.

[0056] The specific raw materials for different silicone rubber formulations are shown in Table 1:

[0057] Table 1

[0058] NO. Glue content % Aluminum hydroxide content % % of silica content A1 43.48 41.3 15.22 A2 38.46 48.08 13.64 A3 34.48 53.45 12.07 A4 38.71 50 11.29 A5 42.42 46.97 10.61 A6 45.71 44.29 10 A7 48.65 41.89 9.46

[0059] S102, perform terahertz detection on the silicone rubber sample to obtain the corresponding terahertz signal of the silicone rubber sample;

[0060] The process of performing terahertz detection on silicone rubber samples is as follows:

[0061] A femtosecond laser generates a pulsed laser beam, which is split into a pump beam and a probe beam by a beam splitter. A terahertz wave emitting crystal radiates terahertz waves through a photoconductive antenna. The pump beam passes through a time-delay device and then through a silicone rubber sample, arriving at the terahertz detector along with the probe beam. Finally, the signal collected by the terahertz detector is transmitted back to a computer for data processing.

[0062] Terahertz waves, after irradiating a silicone rubber sample, carry information about the sample's absorption and scattering parameters. Equivalent time sampling is achieved using a time delay device. By adjusting the optical path difference between the terahertz pulse and the probe pulse, values ​​are taken at each cycle of the recurring multi-cycle terahertz pulse, ensuring that information from different times is sampled until an equivalent periodic signal appears in the terahertz time-domain waveform. The detected signal is transmitted to a computer and converted into a frequency-domain signal containing the phase and amplitude information of the terahertz wave from the silicone rubber sample using Fast Fourier Transform (FFT).

[0063] The terahertz time-domain electric field can be converted into an angular frequency domain form as follows:

[0064]

[0065] Where ω is the angular frequency, E(ω) is the terahertz frequency-domain electric field, E(t) is the terahertz time-domain electric field, A(ω) is the frequency-domain amplitude, and φ(ω) is the frequency-domain phase. Spectral information is obtained by comparing the signal from the silicone rubber sample with a reference spectrum.

[0066]

[0067] In the formula, n is the refractive index of the silicone rubber sample, κ is the extinction coefficient of the silicone rubber sample, d is the thickness of the silicone rubber sample, and c is the speed of light in a vacuum.

[0068] S103, the corresponding absorption rate is determined based on the terahertz signal corresponding to the silicone rubber sample, and as follows: Figure 2 As shown;

[0069] S103 specifically includes:

[0070] Using formula Determine the absorption rate α;

[0071] like Figure 2 As shown, the silicone rubber sample exhibits absorption characteristic peaks between 1.2 THz and 1.4 THz. However, the peak values ​​of these absorption peaks cannot determine the rubber content in the silicone rubber. Therefore, molecular simulations were performed on the main substances in the silicone rubber to study its absorption characteristics at terahertz frequencies.

[0072] S104, Molecular simulations were performed on the main components of the silicone rubber sample to obtain the vibrational characteristic frequencies of the main components of the silicone rubber sample at different terahertz frequencies.

[0073] In an exemplary embodiment, the method for performing molecular simulations on the main components of the silicone rubber sample is the B3LYP method in density functional theory.

[0074] Density functional theory includes HK's first theorem and HK's second theorem;

[0075] The first theorem of HK is shown in the following equation:

[0076] E v (ρ)=∫ρ(r)v(r)dr+F hk (ρ);

[0077] Where E v (ρ) is the electron energy, v(r) is the system potential energy, ρ(r) is the electron density, and F hk (ρ) represents the energy of the exchange mutual repulsion.

[0078] The second theorem of HK states that, given the electronic ground state energy, for an N-electron system:

[0079] ∫ρ(r)dr=N;

[0080] The functional of ρ(r) satisfies:

[0081] E v (ρ)≥E(ρ0)=E0;

[0082] The extension, which corrects for density changes away from the coordinates, is called the generalized gradient approximation, and its form is as follows:

[0083] E0(n)≈∫ρ(r);

[0084] The B3LYP method can accurately describe the true electron density of molecular cluster systems, and then calculate the vibrational modes of molecules at terahertz frequencies.

[0085] S104 specifically includes:

[0086] The vibration characteristic frequency analysis within the optimized and defined range was performed using Gaussian09 software.

[0087] The M06-2X / 6-31+G(d,p) function with corrected mixing was used for optimization and dispersion analysis of vibration characteristic frequencies.

[0088] Finally, Multiwfn was used to further simulate the absorption spectrum from 0.2 THz to 3.0 THz, with a frequency correction factor of 0.94 for M06-2X / 6-31+G(d,p); the specific molecular model is as follows. Figure 3 As shown, the corresponding absorption rates are as follows: Figure 4 As shown.

[0089] like Figure 4 As shown, the absorption rates of various components in silicone rubber, such as silica (SiO2) and aluminum hydroxide (ATH), are not significant at frequencies of 0-3 Hz, with no corresponding absorption peaks. However, polydimethylsiloxane (PDMS) exhibits absorption peaks at frequencies of 1.26 THz, 1.90 THz, and 2.25 THz. The rubber content in silicone rubber can be detected by observing these absorption peaks.

[0090] S105, the regression function of rubber content is determined based on the vibration characteristic frequencies of the main components in the silicone rubber sample at different terahertz frequencies and the corresponding absorption rates.

[0091] like Figure 5 and Figure 6As shown, the analog and measured signals of the PDMS are basically consistent. The difference is due to the fact that the terahertz experiment was conducted at 293 K, while the theoretical calculation was performed at 0 K. A reasonable consistency exists between the calculated and experimentally measured spectra, especially at frequencies below 2 terahertz. Frequency differences may be attributed to a range of factors, including temperature. Additionally, factors such as crystal quality, ambient humidity, and limitations of the experimental system can also contribute to frequency deviations.

[0092] At a frequency of 1.9 Hz, the silicone rubber content and absorption rate are inversely proportional; that is, the higher the silicone rubber content, the lower the absorption rate. Thus, a regression function for silicone rubber content can be derived.

[0093] S106. Obtain the absorption rate of the silicone rubber to be tested, and use a regression function to determine the rubber content of the silicone rubber.

[0094] Based on the same inventive concept, this application also provides a silicone rubber content detection device for implementing the aforementioned silicone rubber content detection method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more silicone rubber content detection device embodiments provided below can be found in the limitations of the silicone rubber content detection method described above, and will not be repeated here.

[0095] In one exemplary embodiment, a silicone rubber content detection device is provided, comprising:

[0096] The silicone rubber sample acquisition module is used to acquire silicone rubber samples with different silicone rubber formulations.

[0097] The terahertz signal determination module is used to perform terahertz detection on the silicone rubber sample and obtain the terahertz signal corresponding to the silicone rubber sample.

[0098] The absorption rate determination module is used to determine the corresponding absorption rate based on the terahertz signal corresponding to the silicone rubber sample.

[0099] The molecular simulation module is used to perform molecular simulations on the main components of the silicone rubber sample to obtain the vibrational characteristic frequencies of the main components of the silicone rubber sample at different terahertz frequencies.

[0100] The module for determining the rubber content regression function is used to determine the rubber content regression function based on the vibration characteristic frequencies of the main components in the silicone rubber sample at different terahertz frequencies and the corresponding absorption rates.

[0101] The rubber content determination module is used to obtain the absorption rate of the silicone rubber to be tested and to determine the rubber content of the silicone rubber using a regression function.

[0102] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for detecting the content of silicone rubber.

[0103] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0104] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0105] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0106] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM).

[0107] Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM)

[0108] RandomAccess Memory, DRAM), etc.

[0109] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchain. The processors involved in the embodiments provided in this application may be, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc.

[0110] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0111] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for detecting the content of silicone rubber, characterized in that, The method for detecting the silicone rubber content includes: Obtain silicone rubber samples with different silicone rubber formulations; Terahertz detection was performed on the silicone rubber sample to obtain the corresponding terahertz signal of the silicone rubber sample; The corresponding absorption rate is determined based on the terahertz signal corresponding to the silicone rubber sample. Molecular simulations were performed on the main components of the silicone rubber sample to obtain the vibrational characteristic frequency of polydimethylsiloxane in the silicone rubber sample at 1.9 terahertz. The regression function for rubber content was determined based on the vibrational characteristic frequency of polydimethylsiloxane in the silicone rubber sample at 1.9 terahertz and the corresponding absorption rate. The absorbance of the silicone rubber to be tested was obtained, and the rubber content of the silicone rubber was determined by regression function; The silicone rubber sample is a high-temperature vulcanized silicone rubber for composite insulators; the main components of the high-temperature vulcanized silicone rubber for composite insulators are polydimethylsiloxane, aluminum hydroxide and fumed silica.

2. The method for detecting the silicone rubber content according to claim 1, characterized in that, The process of obtaining silicone rubber samples with different silicone rubber formulations specifically includes: Obtain raw materials for different silicone rubber formulations; the raw materials are polydimethylsiloxane, aluminum hydroxide, and fumed silica. Add a predetermined amount of hydroxyl silicone oil and iron oxide red to the raw materials; The raw materials containing a set amount of hydroxyl silicone oil and iron oxide red were mixed using a rubber mixing machine; After mixing evenly, the mixed raw materials are heat-treated at a set temperature for a set time. After heat treatment, a vulcanizing agent is added, and the raw material with the added vulcanizing agent is vulcanized and molded using a flat vulcanizing machine to obtain a silicone rubber sample.

3. The method for detecting silicone rubber content according to claim 2, characterized in that, The thickness of the silicone rubber sample is 2 mm.

4. The method for detecting silicone rubber content according to claim 1, characterized in that, The method for performing molecular simulations on the main components of silicone rubber samples is the B3LYP method in density functional theory.

5. The method for detecting the silicone rubber content according to claim 1, characterized in that, The molecular simulation of the main components in the silicone rubber sample yielded the vibrational characteristic frequency of polydimethylsiloxane in the silicone rubber sample at 1.9 terahertz, specifically including: The vibration characteristic frequency analysis within the optimized and defined range was performed using Gaussian09 software. The M06-2X / 6-31+G(d,p) function with corrected mixing was used for optimization and dispersion analysis of vibration characteristic frequencies.

6. A silicone rubber content detection device, used to implement the silicone rubber content detection method according to any one of claims 1-5, characterized in that, The silicone rubber content detection equipment includes: The silicone rubber sample acquisition module is used to acquire silicone rubber samples with different silicone rubber formulations. The terahertz signal determination module is used to perform terahertz detection on the silicone rubber sample and obtain the terahertz signal corresponding to the silicone rubber sample. The absorption rate determination module is used to determine the corresponding absorption rate based on the terahertz signal corresponding to the silicone rubber sample. The molecular simulation module is used to perform molecular simulations on the main components in the silicone rubber sample to obtain the vibrational characteristic frequency of polydimethylsiloxane in the silicone rubber sample at a frequency of 1.9 terahertz. The module for determining the rubber content regression function is used to determine the rubber content regression function based on the vibrational characteristic frequency of polydimethylsiloxane in the silicone rubber sample at 1.9 terahertz and the corresponding absorption rate. The rubber content determination module is used to obtain the absorption rate of the silicone rubber to be tested and to determine the rubber content of the silicone rubber using a regression function.

7. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for detecting the silicone rubber content according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for detecting the silicone rubber content as described in any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for detecting the silicone rubber content as described in any one of claims 1-5.

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