Prediction method and system for water content of crosslinked polyethylene material, electronic equipment and medium

Abstract

The invention provides a method and system for predicting the water content of a crosslinked polyethylene material, electronic equipment and a medium, and belongs to the field of materials and electrical engineering. The method comprises the following steps: preparing test samples and reference samples with different water contents; acquiring a time-domain spectrum of the test sample at the current moment by utilizing a terahertz time-domain spectroscopy system, and converting the time-domain spectrum into a frequency-domain spectrum by utilizing Fourier transform; taking a signal corresponding to the reference sample as a reference signal, calculating an absorption coefficient of the test sample at the current moment, obtaining a corresponding absorption spectrum, and determining the water content at the current moment according to a peak value of a characteristic peak in the absorption spectrum; and inputting the data into a prediction model pre-constructed based on a contraction-expansion algorithm to obtain the water content of the crosslinked polyethylene material in the future period. By providing a prediction model suitable for crosslinked polyethylene, the long-time water absorption can be obtained by using shorter experiment time on the premise of ensuring the precision, and the development of technologies such as electrical equipment detection and the like can be further improved.

Description

Technical Field

[0001] The invention relates to the technical field of materials and electrical engineering, and in particular to a method, system, electronic equipment and medium for predicting the moisture content of a cross-linked polyethylene material. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] Polymer insulating materials such as cross-linked polyethylene have high breakdown strength and low dielectric loss, and are widely used in the insulation systems of various power equipment such as transformers, composite insulators, and power cables. Although some cross-linked polyethylene insulation materials have good hydrophobicity and hydrophobicity, moisture in the environment will still enter the cross-linked polyethylene, affecting its basic performance and aging performance, and affecting other insulating components. Moisture intrusion into cross-linked polyethylene (XLPE) will have many effects on its performance, which mainly depends on the degree of moisture intrusion and the use environment of the cross-linked polyethylene.

[0004] Some possible effects of moisture intrusion into cross-linked polyethylene: 1. Electrical performance effects: The presence of moisture will change the dielectric properties of cross-linked polyethylene, resulting in a decrease in its insulation performance. Moisture may cause discharge under the action of an electric field, thereby reducing the working stability and reliability of the insulation system. 2. Mechanical performance effects: Moisture intrusion will reduce the mechanical properties of cross-linked polyethylene, such as tensile strength, elastic modulus, and fracture toughness. This may cause the cross-linked polyethylene material to be prone to breakage or deformation during use, thereby affecting its mechanical stability and durability. 3. Chemical performance effects: The presence of moisture may promote the reaction of cross-linked polyethylene with other chemicals, resulting in changes in its chemical properties. For example, moisture may react with additives in cross-linked polyethylene, resulting in the loss or degradation of additives, thereby affecting the performance of the material. 4. Thermal performance effects: The presence of moisture will affect the thermal properties of cross-linked polyethylene, such as thermal conductivity and thermal expansion coefficient. This may cause the performance of cross-linked polyethylene materials to be unstable or change in high temperature environments. 5. Aging effects: Moisture is a factor that accelerates material aging. Its presence will accelerate the aging process of cross-linked polyethylene materials, resulting in a gradual decrease in the performance of the material.

[0005] Existing characterization methods for water absorption performance of polymer insulating materials such as cross-linked polyethylene (XLPE) are divided into two categories: direct characterization method and indirect characterization method. The direct characterization method, namely the weighing method, has the advantages of being simple and direct, but the time required for organic polymer materials such as cross-linked polyethylene and epoxy resin to reach saturated water absorption is too long, usually more than 50 days, which seriously restricts the application of the moisture absorption method in engineering practice. Moreover, for a certain material, a large number of tests are first required to measure its moisture absorption characteristics at different times, which is a large workload and has poor universality. Summary of the invention

[0006] The purpose of the embodiments of the present invention is to provide a method, system, electronic device and medium for predicting the moisture content of a cross-linked polyethylene material, which are used to completely or at least partially solve the technical problems existing in the above-mentioned prior art.

[0007] In order to achieve the above object, an embodiment of the present invention provides a method for predicting the moisture content of a cross-linked polyethylene material, comprising:

[0008] preparing test samples of cross-linked polyethylene material with different moisture contents and a reference sample of dried cross-linked polyethylene material;

[0009] Using a terahertz time-domain spectroscopy system, obtaining a time-domain spectrum corresponding to the test sample at the current moment, and converting the time-domain spectrum into a frequency-domain spectrum using Fourier transform;

[0010] Based on the frequency domain spectrum, taking the signal corresponding to the reference sample as the reference signal, calculating the absorption coefficient of the test sample of the cross-linked polyethylene material with different water contents at the current moment, obtaining the corresponding absorption spectrum, and determining the water content of the cross-linked polyethylene material at the current moment according to the peak value of the characteristic peak in the absorption spectrum;

[0011] The moisture content of the cross-linked polyethylene material at the current moment is input into the cross-linked polyethylene water absorption prediction model pre-constructed based on the shrinkage-expansion algorithm to obtain the moisture content of the cross-linked polyethylene material in the future period.

[0012] Optionally, the preparation of test samples of cross-linked polyethylene materials with different water contents and reference samples of dried cross-linked polyethylene materials comprises:

[0013] Determining the volume of the polyethylene sheet based on the thickness and the inner circle diameter of the steel mold, and determining the mass of the polyethylene sheet based on the volume and the density of the polyethylene;

[0014] According to the volume and mass of the polyethylene sheet, the corresponding polyethylene and additive mixed raw materials are weighed by an electronic balance to obtain a cross-linked polyethylene sheet sample;

[0015] The cross-linked polyethylene sheet sample is placed in a constant temperature and humidity chamber to perform a water absorption test, and the cross-linked polyethylene sheet samples at different time periods are regularly taken out as test samples with different water contents;

[0016] The cross-linked polyethylene sheet sample is placed in a constant temperature forced air drying oven for drying until the weight no longer changes, thereby obtaining a reference sample.

[0017] Optionally, the terahertz time-domain spectroscopy system includes:

[0018] A terahertz detection module, used for receiving terahertz wave signals using a terahertz detector;

[0019] The terahertz radiation module includes a laser source, a terahertz emitter, and a delayed light path. The laser source is used to irradiate the terahertz emitter to promote photon transition to generate terahertz waves. The terahertz signal of the cross-linked polyethylene test sample is transmitted through the delayed light path to reach the terahertz wave of the detector as a reference signal.

[0020] The sample platform module is used to place the test sample on the sample platform and select the appropriate terahertz wave incident mode according to the material and size characteristics of the test sample.

[0021] Optionally, based on the frequency domain spectrum, taking the signal corresponding to the reference sample as the reference signal, calculating the absorption coefficient of the test sample of the cross-linked polyethylene material with different water contents at the current moment, including: calculating the absorption coefficient of the test sample according to the following formula:

[0022]

[0023] In the formula, α(ω) represents the absorption coefficient, κ(ω) represents the extinction coefficient, c represents the propagation speed of terahertz electromagnetic waves in a vacuum, and ω p represents the plasma oscillation frequency of the substance, γ is the attenuation coefficient of the carrier phase coherence in the substance, δω represents the oscillation frequency of the terahertz electromagnetic wave, ω0 represents the resonant frequency of the terahertz electromagnetic wave, and ω represents the phase of the terahertz electromagnetic wave.

[0024] Optionally, determining the water content of the cross-linked polyethylene material at the current moment according to the peak value of the characteristic peak in the absorption spectrum includes: determining the water content of the cross-linked polyethylene material at the current moment according to the following formula:

[0025] P=aM water +b

[0026] In the formula, P represents the peak value of the characteristic peak in the absorption spectrum, a represents the coefficient, and M water represents water content, and b represents the intercept.

[0027] Optionally, the cross-linked polyethylene water absorption prediction model pre-constructed based on the shrinkage-expansion algorithm is:

[0028]

[0029] In the formula, s represents the sample thickness, ω(t) represents the water absorption percentage of the sample at time t, and ω s represents the saturated water absorption of the sample, D represents the diffusion coefficient, α and β represent the probability of the free state transforming into the bound state and the bound state transforming into the free state, respectively, and y(t) represents Fick's law.

[0030] Optionally, the method for predicting the water content of the cross-linked polyethylene material further comprises:

[0031] Repeatedly measure the moisture content of the cross-linked polyethylene material under the same environmental conditions to obtain an average value, and set the average value as the accuracy threshold;

[0032] The parameters of the cross-linked polyethylene water absorption prediction model are optimized based on the accuracy threshold to obtain a target cross-linked polyethylene water absorption prediction model.

[0033] On the other hand, the present invention also provides a system for predicting the moisture content of a cross-linked polyethylene material, comprising:

[0034] A sample preparation unit, used for preparing test samples of cross-linked polyethylene materials with different water contents and reference samples of dry cross-linked polyethylene materials;

[0035] A spectrum acquisition unit, used to acquire the time domain spectrum corresponding to the test sample at the current moment by using a terahertz time domain spectroscopy system, and convert the time domain spectrum into a frequency domain spectrum by using Fourier transform;

[0036] A determination unit, for calculating the absorption coefficient of the test samples of the cross-linked polyethylene material with different water contents at the current moment based on the frequency domain spectrum and taking the signal corresponding to the reference sample as the reference signal, obtaining the corresponding absorption spectrum, and determining the water content of the cross-linked polyethylene material at the current moment according to the peak value of the characteristic peak in the absorption spectrum;

[0037] The prediction unit is used to input the moisture content of the cross-linked polyethylene material at the current moment into the cross-linked polyethylene water absorption prediction model pre-constructed based on the shrinkage-expansion algorithm to obtain the moisture content of the cross-linked polyethylene material in the future period.

[0038] On the other hand, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for predicting the moisture content of the cross-linked polyethylene material when executing the program.

[0039] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for predicting the moisture content of the cross-linked polyethylene material described above are implemented.

[0040] By proposing a prediction model suitable for cross-linked polyethylene, it is expected that under the premise of ensuring accuracy, the long-term water absorption rate can be obtained with a shorter experimental time, and the test time can be reduced by 98%, which provides a solution for the rapid detection of the moisture absorption performance of cross-linked polyethylene insulation materials. It has good theoretical significance and engineering reference value for laboratory testing, pre-delivery testing, and operation maintenance of cross-linked polyethylene insulation materials, and is conducive to further improving the development of technologies such as power equipment testing.

[0041] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0043] Figure 1 It is an execution flow chart of a method for predicting the moisture content of a cross-linked polyethylene material provided by an embodiment of the present invention;

[0044] Figure 2 is a schematic diagram of a testing device provided by an embodiment of the present invention;

[0045] Figure 3 is a schematic structural diagram of a terahertz time-domain spectroscopy system provided by an embodiment of the present invention;

[0046] Figure 4 is a schematic diagram of a photoconductive sampling antenna technology provided by an embodiment of the present invention;

[0047] Figure 5 is a schematic diagram of a photoconductive antenna method provided by an embodiment of the present invention;

[0048] Figure 6 is a working principle diagram of a terahertz time-domain spectroscopy system provided by an embodiment of the present invention;

[0049] Figure 7 is a terahertz time-domain spectrum diagram of a blank sample provided by an embodiment of the present invention;

[0050] Figure 8 is a terahertz frequency domain spectrum diagram of a blank sample provided by an embodiment of the present invention;

[0051] Fig. 9 is a schematic diagram of THz wave propagation in a cross-linked polyethylene sample provided by an embodiment of the present invention;

[0052] Fig.10 It is a structural schematic diagram of a system for predicting the moisture content of a cross-linked polyethylene material provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0054] See also Figure 1 As shown, it is an execution flow chart of a method for predicting the moisture content of a cross-linked polyethylene material provided by an embodiment of the present invention, comprising the following execution steps:

[0055] Step 100: preparing test samples of cross-linked polyethylene material with different moisture contents and a reference sample of dried cross-linked polyethylene material.

[0056] In some implementations, when executing step 100, the following steps may be specifically performed:

[0057] S1000: Determine the volume of the polyethylene sheet according to the thickness and the inner circle diameter of the steel mold, and determine the mass of the polyethylene sheet based on the volume and the density of the polyethylene.

[0058] Specifically, the volume and mass of the polyethylene sheet are determined using the following formula:

[0059] v=πr 2 h;

[0060] m=vp;

[0061] Wherein, v represents the volume of the polyethylene sheet, h and r represent the thickness and inner circle radius of the steel mold, respectively, and p represents the density of polyethylene.

[0062] S1001: According to the volume and mass of the polyethylene sheet, the corresponding polyethylene and additive mixed raw materials are weighed using an electronic balance to obtain a cross-linked polyethylene sheet sample.

[0063] S1002: placing the cross-linked polyethylene sheet sample in a constant temperature and humidity chamber to conduct a water absorption test, and regularly taking out cross-linked polyethylene sheet samples at different time periods as test samples with different water contents.

[0064] Specifically, the test method of the hygroscopicity test refers to the standard ISO 62-2008 "Plastics-Determination of water absorption". Place the cake-shaped cross-linked polyethylene sheet sample on a hollow iron frame in a constant temperature and humidity chamber and seal it well. A high-precision hygrometer is built into the box to monitor the relative humidity in the box. Before the test, first wipe the sample clean with anhydrous ethanol, and then place it in a constant temperature blast drying oven to dry until the weight no longer changes, then take out the sample and place it in a dryer to cool to room temperature, and record its average weight m0 after drying. Test the constant temperature and humidity chamber, set the parameters to a temperature of 25°C and a relative humidity of 90% (the controlled environmental variables under different factors are different). When the constant temperature and humidity chamber display screen and the built-in thermometer and hygrometer remain unchanged, it is determined that the test environment is good, and the test is carried out. The test device is as follows Figure 2 shown.

[0065] During the test, all dried samples were placed in a constant temperature and humidity chamber to keep the temperature and relative humidity constant. The weight was measured regularly using a high-precision balance (accuracy 1 mg). The samples were put back immediately after the measurement was completed. The test was repeated five times for six samples, and the average value m(t) of the five tests was taken. The water absorption percentage w(t) can be expressed by the following formula.

[0066]

[0067] Where: m(t) is the mass of the sample after the test time t, and m0 is the mass of the dry sample.

[0068] S1003: Place the cross-linked polyethylene sheet sample in a constant temperature forced air drying oven for drying until the weight no longer changes, thereby obtaining a reference sample.

[0069] It should be noted that the steel mold needs to be cleaned, wiped with alcohol and dried before preparation.

[0070] Step 101: using a terahertz time-domain spectroscopy system to obtain a time-domain spectrum corresponding to the test sample at the current moment, and converting the time-domain spectrum into a frequency-domain spectrum using Fourier transform.

[0071] In some embodiments, the terahertz time-domain spectroscopy system comprises:

[0072] The terahertz detection module is used to receive terahertz wave signals using a terahertz detector.

[0073] Specifically, the important task of the terahertz detection module is to realize the reception of terahertz wave signals. The terahertz detector is its core component. In the terahertz detection module, it is mainly divided into a photoconductive sampling method and a free-space electro-optical sampling method. After the detector collects the time domain electric field signal, the time domain electrical signal is converted into a frequency domain signal (amplitude signal and phase signal) by Fourier transform. At the same time, according to the different types of terahertz radiation waves detected, the detection technology can also be divided into two categories: continuous terahertz radiation detection technology and pulsed terahertz radiation detection technology. The detection module in this embodiment adopts photoconductive sampling antenna technology. The microcurrent detector is used to measure the instantaneous photogenerated current between the poles of the photoconductive detection antenna, as shown in the following formula.

[0074] J(t) = eμE(t);

[0075] Among them, e is the electron charge, μ is the electron mobility, and E(t) is the electric field generated by the measured terahertz pulse. According to the formula, it can be seen that the instantaneous photocurrent is positively correlated with the electric field intensity generated by the measured terahertz pulse. Detecting this current is equivalent to detecting the information of the measured terahertz pulse. Using the equivalent time sampling method, samples can be taken at different pulse periods, and the equivalent restored terahertz pulse waveform can be derived in turn. This method can obtain a relatively high signal-to-noise ratio, but due to the influence of the carrier lifetime, the detection bandwidth is relatively narrow.

[0076] The terahertz radiation module includes a laser source, a terahertz emitter, and a delayed light path. The laser source is used to irradiate the terahertz emitter to promote photon transition to generate terahertz waves. The terahertz signal of the cross-linked polyethylene test sample is transmitted through the delayed light path to reach the terahertz wave of the detector as a reference signal.

[0077] The sample platform module is used to place the test sample on the sample platform and select the appropriate terahertz wave incident mode according to the material and size characteristics of the test sample.

[0078] Specifically, the sample platform module is an important component of the terahertz spectroscopy detection system. Its main function is to place the sample to be tested on the platform, design it according to the material, size and other characteristics of the sample, and select the appropriate terahertz wave incidence method based on the characteristics of the sample. Different types of samples require different processing methods, so the material, size and other characteristics of the sample need to be considered when designing the sample platform. This ensures that the sample can be optically measured under appropriate conditions and relevant parameters can be accurately obtained. For solid cross-linked polyethylene samples, their optical properties are relatively stable, and the refractive index in the terahertz frequency band does not change with frequency, so terahertz spectroscopy can be directly detected. In addition, in the terahertz time-domain spectroscopy system, common optical path modes are transmission and reflection.

[0079] In some embodiments, the advantages of the transmission type terahertz time-domain spectroscopy system are reflected in its small error, high precision and strong stability. For the cross-linked polyethylene sample used in this experiment, its thickness meets the use conditions of the transmission type terahertz time-domain spectroscopy system. At the same time, since the water content in the cross-linked polyethylene is less than its own mass, the application of the transmission type terahertz time-domain spectroscopy system can further ensure its accuracy and stability while obtaining the terahertz signal. The structural schematic diagram of the terahertz time-domain spectroscopy system can be seen in Figure 3 As shown in the figure, it is composed of multiple components. The femtosecond laser is one of the core components of the transmission-type terahertz time-domain spectroscopy system. It can generate two mutually perpendicular femtosecond laser pulses, namely pump light and detection light. These two laser beams can be separated by a beam splitter and used to generate and detect terahertz pulses; the beam splitter is an important component that divides the pulsed laser generated by the femtosecond laser into pump light and detection light. The function of the beam splitter is to divide the pulsed laser into two beams, one of which is used to irradiate the terahertz pulse generated by the terahertz generator, and the other is used to detect the terahertz pulse. The photoconductive antenna is a component used to detect terahertz waves. The principle of the photoconductive sampling antenna technology is as shown in Figure 4 As shown, the principle of the photoconductive antenna method can be found in Figure 5 As shown, a fast laser pulse is incident on a photoconductive antenna with a biased electric field, and a terahertz wave is generated by the movement of carriers in the electric field. When the terahertz wave passes through the photoconductive antenna, it generates charges and converts these charges into electrical signals. These electrical signals are converted into digital signals by the digital-to-analog converter and transmitted to the computer for processing and analysis; the time delay control system is a component used to control the delay time of the detection light before it reaches the terahertz detector, which enables the user to accurately control the arrival time of the detection light, thereby ensuring accurate measurement of the terahertz pulse; the parabolic mirror is a component used to focus the terahertz wave on the sample, which enables the user to control the focus of the terahertz wave so that different areas of the sample surface can be scanned; the THz wave detector is a component used to detect terahertz waves. When the terahertz wave passes through the detector, it generates charges and converts these charges into electrical signals. These electrical signals are converted into digital signals by the digital-to-analog converter and transmitted to the computer for processing and analysis; the two-dimensional scanning platform is a component used to scan the sample surface. This component enables the user to control the scanning range and scanning speed of the sample surface, thereby obtaining detailed information about the sample surface; finally, the computer serves as the control center of the entire system and is responsible for data processing and analysis.

[0080] The components of the transmission terahertz time-domain spectroscopy system are coordinated to provide high-precision, high-stability signal acquisition and processing capabilities. Each component plays an important role, and each link requires high precision and coordination to ensure the stability of the entire system and the accuracy and reliability of the results. The working principle of the system is as follows: Figure 6shown.

[0081] It should be noted that the signal in the terahertz band is also very sensitive to the influence of moisture. Therefore, in order to ensure the accuracy of the collected data, the optical path of THz-TDS is generally placed in a closed box and injected with pure nitrogen to keep it dry. This can effectively avoid the influence of moisture on the signal, making the collected terahertz spectrum more accurate and reliable. Because changes in humidity may cause changes in the absorption coefficient of terahertz waves, which in turn affects the intensity and shape of the signal. This influence may mask the inherent characteristic information of the material, resulting in inaccurate or distorted experimental results.

[0082] In some embodiments, by testing the system, the terahertz time and frequency domain spectra of the blank sample can be obtained, such as Figure 7 , 8 As shown. Figure 7 , 8 It can be seen that the femtosecond laser has an effective spectrum range of up to 5.5 THz, which is in line with the requirements of this test and ensures the accuracy and reliability of the data.

[0083] Step 102: Based on the frequency domain spectrum, taking the signal corresponding to the reference sample as the reference signal, the absorption coefficient of the test sample of the cross-linked polyethylene material with different water contents at the current moment is calculated, the corresponding absorption spectrum is obtained, and the water content of the cross-linked polyethylene material at the current moment is determined according to the peak value of the characteristic peak in the absorption spectrum.

[0084] In some embodiments, the terahertz frequency domain spectroscopy analysis of cross-linked polyethylene materials with different water contents is specifically as follows: a transmission THz-TDS system is used to test cross-linked polyethylene samples with different water contents. The cross-linked polyethylene samples used are weighed at different times to obtain their water contents. The cross-linked polyethylene samples with different water contents are analyzed by a parameter extraction method of a terahertz time domain system in transmission mode.

[0085] First, the initial conditions of the experimental process are assumed. The response function of the terahertz time-domain spectroscopy system will not be affected by time changes. At the same time, the structure of the cross-linked polyethylene sample remains uniform, and the ideal electromagnetic interface is always the cross-linked polyethylene model interface. In the Fresnel formula, the main factors for the amplitude change in the first interface are the transmission coefficient and the reflection coefficient, and the corresponding numerical relationship is shown in the following formula.

[0086]

[0087] In the formula, is the incident angle, is the exit angle, is the complex refractive index, r 12pis the reflection coefficient component of the terahertz wave parallel to the incident surface at the interface of medium 1 and medium 2, t 12p is the transmission coefficient component of the terahertz wave parallel to the incident surface at the interface of medium 1 and medium 2. 12s is the reflection coefficient component of the terahertz wave perpendicular to the incident surface at the interface of medium 1 and medium 2, t 12s is the transmission coefficient component of the terahertz wave perpendicular to the incident surface at the interface of medium 1 and medium 2. Therefore, the relationship value at the second interface can be expressed by the following formula.

[0088]

[0089] From the Snell formula we can get The relationship is shown in the following formula.

[0090]

[0091] In the formula, is the complex refractive index. Generally speaking, and It is not a real number and cannot be simply considered as an angle. Only when k2=k3=0, and It is expressed as the refraction angle. When the terahertz wave propagates in the medium, it will experience dispersion and loss. Therefore, the absorption coefficient, reflection coefficient, complex refractive index and extinction coefficient are actually functions of frequency. If the terahertz wave has propagated a distance of L in the medium, the phase and amplitude have changed, and the resulting propagation terahertz wave phase difference σ(ω,L) is shown in the following formula.

[0092]

[0093] In the formula, c represents the propagation speed of terahertz electromagnetic waves in vacuum, and ω represents the phase of terahertz electromagnetic waves.

[0094] The propagation factor p(ω,L) of the terahertz wave is expressed as follows.

[0095]

[0096] In the formula, c represents the propagation speed of terahertz electromagnetic waves in vacuum, and μ represents the phase of terahertz electromagnetic waves. For the experimental measurement process, terahertz wave signals are mostly presented as time domain spectra, which can be converted into frequency domain spectra through digital transformation to determine the relevant amplitude and phase information, so as to analyze the specific situation of terahertz monochromatic plane waves.

[0097] Schematic diagram of THz wave propagation in cross-linked polyethylene sample Fig. 9 As shown, E THz (ω) represents the incident field, Ec (ω) represents the transmission field of the electromagnetic wave after passing through the cross-linked polyethylene sample, E r0 (ω) and E r1 (ω) are the reflected fields reflected from the first and second interfaces of the sample, respectively. The amplitude and phase information of the frequency domain of the time domain pulse measured by the experiment can be obtained through Fourier transform, thereby obtaining the characteristics of its terahertz incident pulse. If multiple reflections in the sample are ignored, the transmission and reflection signals are given by the following formula.

[0098] E c (ω)=E THz (ω)t0t1e -αd / 2 e inωd / c

[0099] E r0 (ω)=E c (ω)r0

[0100] E r1 (ω)=E THz (ω)t0t1t2e -αd / 2 e inωd / c

[0101] In the formula, E THz (ω) represents the incident field, E c (ω) represents the transmission field of the electromagnetic wave after passing through the cross-linked polyethylene sample, E r0 (ω) and E r1 (ω) are the reflected fields reflected from the first interface and the second interface of the sample, c represents the propagation speed of the terahertz electromagnetic wave in a vacuum, μ represents the phase of the terahertz electromagnetic wave, t0 represents the initial transmission coefficient, t1 and t2 represent the transmission coefficient through the first plane and the transmission coefficient through the second plane, d represents the thickness, and r0 represents the THz propagation factor.

[0102] Either transmission or reflection measurements can be used to extract the complex refractive index of cross-linked polyethylene samples.

[0103]

[0104] Wherein, κ(ω) is the extinction coefficient, also called the attenuation coefficient. The relationship between the extinction coefficient κ(ω) and the absorption coefficient α(ω) is shown in the following formula.

[0105]

[0106] In the formula, α(ω) represents the absorption coefficient, κ(ω) is the extinction coefficient, c represents the propagation speed of the terahertz electromagnetic wave in a vacuum, and ω represents the phase of the terahertz electromagnetic wave.

[0107] The mechanism of terahertz absorption spectroscopy originates from the excitation of carriers bound by potential fields (such as electrons in atoms or electrons in potential barriers). When the oscillation frequency of the electromagnetic wave is close to the resonance frequency (i.e., δω=|ω0-ω|<<ω0), the complex refractive index of the material can be approximately expressed as:

[0108]

[0109] In the formula, γ = 1 / τ is the attenuation coefficient of the carrier phase coherence in the material, represents the plasma oscillation frequency of the substance, α(ω) represents the absorption coefficient, κ(ω) is the extinction coefficient, c represents the propagation speed of the terahertz electromagnetic wave in a vacuum, γ is the attenuation coefficient of the carrier phase coherence in the substance, δω represents the oscillation frequency of the terahertz electromagnetic wave, ω0 represents the resonant frequency of the terahertz electromagnetic wave, and ω represents the phase of the terahertz electromagnetic wave.

[0110] Terahertz absorption spectroscopy can determine the energy resonance structure of a substance by analyzing the position of the absorption peak that appears in the spectrum. These resonance structures are related to the vibration of molecules or lattices, so they can provide optical information about molecules or materials, and determine the type of substance contained in the sample by comparing the spectral information. In addition, terahertz absorption spectroscopy can also determine the content of a substance by the height of the characteristic peak. A characteristic peak refers to a strong absorption peak that appears in a spectrum, and its height corresponds to the concentration of the substance. Therefore, by measuring the height of the characteristic peak in the sample, the concentration or content of the substance can be calculated. This reveals the close relationship between the response of the substance and the frequency of the electromagnetic wave. The terahertz time domain signal of the sample is converted into a signal in the frequency domain by Fourier transform. Using dry cross-linked polyethylene as a reference signal, the absorption coefficient of each cross-linked polyethylene sample with different moisture content is calculated, and the corresponding absorption spectrum is plotted.

[0111] Specifically, the water content of the cross-linked polyethylene material at the current moment can be determined according to the following formula:

[0112] P=aM water +b

[0113] In the formula, P represents the peak value of the characteristic peak in the absorption spectrum, a represents the coefficient, and M water represents water content, and b represents the intercept.

[0114] Step 103: input the moisture content of the cross-linked polyethylene material at the current moment into a cross-linked polyethylene water absorption prediction model pre-constructed based on a shrinkage-expansion algorithm to obtain the moisture content of the cross-linked polyethylene material in a future period.

[0115] Specifically, the cross-linked polyethylene water absorption prediction model pre-constructed based on the shrinkage-expansion algorithm is:

[0116]

[0117] In the formula, s represents the sample thickness, ω(t) represents the water absorption percentage of the sample at time t, and ω s represents the saturated water absorption of the sample, D represents the diffusion coefficient, α and β represent the probability of the free state transforming into the bound state and the bound state transforming into the free state, respectively, and y(t) represents Fick's law.

[0118] Specifically, a cross-linked polyethylene system containing water molecules was constructed through molecular dynamics simulation, and simulations were performed at different temperatures and different electric field strengths to analyze and determine the threshold range of the diffusion coefficient D. At the same time, through the results of experiments and literature research, the initial value range of the adsorption coefficient α and the desorption coefficient β was determined, and the initialization research of the rapid prediction model of water absorption of cross-linked polyethylene was realized. The Langmuir equation is highly nonlinear, contains cascade equations and has many parameters, so it is difficult to handle. To describe the diffusion process, it is necessary to optimize the fitting of D, α, β, and w in the Langmuir equation. s Parameter estimation is performed to determine the hygroscopic properties of cross-linked polyethylene materials. The shrink-expansion algorithm is an effective global optimization algorithm that can roam inside and outside the multidimensional starting space to search for the objective function, and adjust the search center and step size through the information fed back from the search process. The algorithm first randomly selects an initial point in the starting space and calculates the value of the objective function. Then, a shrinkage or expansion operation is performed according to the situation of the current search point. If the value of the objective function at the current search point is small, the search center is moved to that point, and the step size is increased to expand the search range; if the value of the objective function at the current search point is large, the search center is moved to the origin, and the step size is reduced to narrow the search range. Since the shrink-expansion algorithm adopts an adaptive strategy, only a few shrink-expansion cycles are needed to approximate the optimal parameter values ​​of a given nonlinear equation, namely D, α, β, w s Compared with other optimization algorithms, the shrink-expansion algorithm has stronger global search capabilities and higher search efficiency. The algorithm does not require the derivative or partial derivative of the equation, which reduces the complexity of the calculation. Therefore, this paper applies the shrink-expansion theory to optimally fit the early water absorption data of cross-linked polyethylene, thereby establishing a cross-linked polyethylene water absorption prediction model.

[0119] The contraction-expansion theory has three stages: first, the step size is continuously reduced in a given search space to make the search space gradually smaller; second, the search with a larger step size is performed; third, the average and standard deviation of the degree points that meet certain requirements are calculated to determine the step size of the next process. Since the initial values ​​of the parameters are all positive numbers greater than 0, they are set to any value greater than 0.

[0120] In some embodiments, the method for predicting the moisture content of the cross-linked polyethylene material further includes: repeatedly measuring the moisture content of the cross-linked polyethylene material under the same environmental conditions and taking an average value, and setting the average value as an accuracy threshold; and optimizing the parameters of the cross-linked polyethylene water absorption prediction model based on the accuracy threshold to obtain a target cross-linked polyethylene water absorption prediction model.

[0121] This application shortens the water absorption test time by 98% through theoretical analysis, numerical simulation and experimental verification, while ensuring that the error does not exceed the accuracy threshold, and provides a simple and easy-to-use moisture testing method.

[0122] See also Fig.10 FIG. 1 is a schematic diagram of a system for predicting the moisture content of a cross-linked polyethylene material provided by an embodiment of the present invention, comprising:

[0123] The sample preparation unit 1000 is used to prepare test samples of cross-linked polyethylene materials with different water contents and reference samples of dried cross-linked polyethylene materials;

[0124] The spectrum acquisition unit 1001 is used to acquire the time domain spectrum corresponding to the test sample at the current moment by using the terahertz time domain spectroscopy system, and convert the time domain spectrum into a frequency domain spectrum by using Fourier transform;

[0125] The determination unit 1002 is used to calculate the absorption coefficient of the test sample of the cross-linked polyethylene material with different water contents at the current moment based on the frequency domain spectrum and taking the signal corresponding to the reference sample as the reference signal, obtain the corresponding absorption spectrum, and determine the water content of the cross-linked polyethylene material at the current moment according to the peak value of the characteristic peak in the absorption spectrum;

[0126] The prediction unit 1003 is used to input the moisture content of the cross-linked polyethylene material at the current moment into the cross-linked polyethylene water absorption prediction model pre-constructed based on the shrinkage-expansion algorithm to obtain the moisture content of the cross-linked polyethylene material in the future period.

[0127] On the other hand, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for predicting the moisture content of the cross-linked polyethylene material described in any one of the above embodiments are implemented.

[0128] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for predicting the moisture content of a cross-linked polyethylene material as described in any of the above embodiments.

[0129] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0130] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0131] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0132] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0133] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0134] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0135] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0136] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0137] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for predicting the water content of a cross-linked polyethylene material, characterized in that: include: preparing test samples of cross-linked polyethylene material with different moisture contents and a reference sample of dried cross-linked polyethylene material; Using a terahertz time-domain spectroscopy system, obtaining a time-domain spectrum corresponding to the test sample at the current moment, and converting the time-domain spectrum into a frequency-domain spectrum using Fourier transform; Based on the frequency domain spectrum, taking the signal corresponding to the reference sample as the reference signal, calculating the absorption coefficient of the test sample of the cross-linked polyethylene material with different water contents at the current moment, obtaining the corresponding absorption spectrum, and determining the water content of the cross-linked polyethylene material at the current moment according to the peak value of the characteristic peak in the absorption spectrum; The moisture content of the cross-linked polyethylene material at the current moment is input into the cross-linked polyethylene water absorption prediction model pre-constructed based on the shrinkage-expansion algorithm to obtain the moisture content of the cross-linked polyethylene material in the future period.

2. The method for predicting the water content of a cross-linked polyethylene material according to claim 1, characterized in that: The method for preparing the test samples of the cross-linked polyethylene material with different water contents and the reference samples of the dried cross-linked polyethylene material comprises: Determining the volume of the polyethylene sheet based on the thickness and the inner circle diameter of the steel mold, and determining the mass of the polyethylene sheet based on the volume and the density of the polyethylene; According to the volume and mass of the polyethylene sheet, the corresponding polyethylene and additive mixed raw materials are weighed by an electronic balance to obtain a cross-linked polyethylene sheet sample; The cross-linked polyethylene sheet sample is placed in a constant temperature and humidity chamber to perform a water absorption test, and the cross-linked polyethylene sheet samples at different time periods are regularly taken out as test samples with different water contents; The cross-linked polyethylene sheet sample is placed in a constant temperature forced air drying oven for drying until the weight no longer changes, thereby obtaining a reference sample.

3. The method for predicting the water content of a cross-linked polyethylene material according to claim 1, characterized in that: The terahertz time-domain spectroscopy system comprises: A terahertz detection module, used for receiving terahertz wave signals using a terahertz detector; The terahertz radiation module includes a laser source, a terahertz emitter, and a delayed light path. The laser source is used to irradiate the terahertz emitter to promote photon transition to generate terahertz waves. The terahertz signal of the cross-linked polyethylene test sample is transmitted through the delayed light path to reach the terahertz wave of the detector as a reference signal. The sample platform module is used to place the test sample on the sample platform and select the appropriate terahertz wave incident mode according to the material and size characteristics of the test sample.

4. The method for predicting the water content of a cross-linked polyethylene material according to claim 1, characterized in that: Based on the frequency domain spectrum, taking the signal corresponding to the reference sample as the reference signal, calculating the absorption coefficient of the test sample of the cross-linked polyethylene material with different water contents at the current moment, including: calculating the absorption coefficient of the test sample according to the following formula: In the formula, α(ω) represents the absorption coefficient, κ(ω) represents the extinction coefficient, c represents the propagation speed of terahertz electromagnetic waves in a vacuum, and ω p represents the plasma oscillation frequency of the substance, γ is the attenuation coefficient of the phase coherence of the carriers in the substance, δω represents the oscillation frequency of the terahertz electromagnetic wave, and ω0 represents the terahertz electromagnetic wave. The resonant frequency of the magnetic wave, ω represents the phase of the terahertz electromagnetic wave.

5. The method for predicting the water content of a cross-linked polyethylene material according to claim 1, characterized in that: Determining the water content of the cross-linked polyethylene material at the current moment according to the peak value of the characteristic peak in the absorption spectrum includes: determining the water content of the cross-linked polyethylene material at the current moment according to the following formula: P=aM water +b; In the formula, P represents the peak value of the characteristic peak in the absorption spectrum, a represents the coefficient, and M water represents water content, and b represents the intercept.

6. The method for predicting the water content of a cross-linked polyethylene material according to claim 1, characterized in that: The water absorption prediction model of cross-linked polyethylene constructed in advance based on the shrinkage-expansion algorithm is: In the formula, s represents the sample thickness, ω(t) represents the water absorption percentage of the sample at time t, and ω s represents the saturated water absorption of the sample, D represents the diffusion coefficient, α and β represent the probability of the free state transforming into the bound state and the bound state transforming into the free state, respectively, and y(t) represents Fick's law.

7. The method for predicting the water content of a cross-linked polyethylene material according to claim 1, characterized in that: The method for predicting the water content of the cross-linked polyethylene material also includes: Repeatedly measure the moisture content of the cross-linked polyethylene material under the same environmental conditions to obtain an average value, and set the average value as the accuracy threshold; The parameters of the cross-linked polyethylene water absorption prediction model are optimized based on the accuracy threshold to obtain a target cross-linked polyethylene water absorption prediction model.

8. A system for predicting the moisture content of a cross-linked polyethylene material, characterized in that: include: A sample preparation unit, used for preparing test samples of cross-linked polyethylene materials with different water contents and reference samples of dry cross-linked polyethylene materials; A spectrum acquisition unit, used to acquire the time domain spectrum corresponding to the test sample at the current moment by using a terahertz time domain spectroscopy system, and convert the time domain spectrum into a frequency domain spectrum by using Fourier transform; A determination unit, for calculating the absorption coefficient of the test samples of the cross-linked polyethylene material with different water contents at the current moment based on the frequency domain spectrum and taking the signal corresponding to the reference sample as the reference signal, obtaining the corresponding absorption spectrum, and determining the water content of the cross-linked polyethylene material at the current moment according to the peak value of the characteristic peak in the absorption spectrum; The prediction unit is used to input the moisture content of the cross-linked polyethylene material at the current moment into the cross-linked polyethylene water absorption prediction model pre-constructed based on the shrinkage-expansion algorithm to obtain the moisture content of the cross-linked polyethylene material in the future period.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for predicting the moisture content of the cross-linked polyethylene material as described in any one of claims 1-7 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for predicting the moisture content of a cross-linked polyethylene material as described in any one of claims 1 to 7 are implemented.

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