High-speed cable detection method, device and equipment and storage medium

Abstract

The invention discloses a detection method, device and equipment for a high-speed cable and a storage medium. The method comprises the following steps: introducing a molecular field regulating agent into the surface of an insulating layer of the cable to form an orderly arranged molecular layer structure, and obtaining dielectric constant distribution data; according to the dielectric constant distribution data, regulating and controlling the interaction between the hybrid probe formed by the quantum dots and the organic fluorescent molecules and the surface of the insulating layer, and obtaining the fluorescence intensity, fluorescence lifetime, polarization degree and spectral displacement data of the probe; importing the data into a critical state calculation framework for signal processing to obtain microstructure distribution data; and representing crystallinity distribution, crosslinking distribution and residual stress distribution of the surface of the insulating layer to obtain microscopic physicochemical characteristic parameters. According to the technical scheme, all-around, high-sensitivity and non-contact real-time detection and characterization of microcosmic physicochemical characteristics of the surface and the near-surface area of the insulating layer in the production process of the high-speed transmission cable can be achieved, and a new technical means is provided for quality control of the high-speed transmission cable.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of high-speed transmission cable production and its quality detection, and particularly relates to a high-speed cable detection method, device, equipment and storage medium. BACKGROUND

[0002] High-speed transmission cable is a special cable specially designed for high-frequency, large-data, low-delay signal transmission, and is widely used in data centers, 5G communication, high-performance computing, aerospace and industrial automation fields. The basic structure of this kind of cable is composed of a center conductor, an insulating layer, a multi-layer shielding structure and an outer sheath, wherein the insulating layer is made of precise dielectric material and plays a decisive role in the high-frequency transmission performance of the cable. The insulating layer not only needs to maintain good insulating performance, but also needs to have stable dielectric constant and low dielectric loss characteristics to ensure impedance consistency, signal integrity and anti-interference ability during high-frequency signal transmission. This puts very high requirements on the microstructure of the insulating layer, including the uniformity of crystallinity distribution, the integrity of cross-linking network and the control of residual stress, etc.

[0003] In the existing high-speed transmission cable production process, the preparation of the insulating layer mainly relies on the traditional extrusion molding process, and the quality control is carried out through methods such as capacitance method, laser diameter measurement method and optical surface detection. However, these detection methods have obvious limitations: the capacitance method can measure the thickness and continuity of the insulating layer, but cannot detect the microstructure inside the material; the laser diameter measurement method can accurately measure the outer diameter, but cannot reflect the surface micro-defects; the optical surface detection can find macroscopic surface defects, but is limited by the cylindrical structure of the cable and the detection angle, and cannot realize omnidirectional detection. More importantly, these methods cannot evaluate the key micro characteristics of the insulating layer, such as crystallinity distribution, uneven cross-linking degree and residual stress distribution. In the process of high-frequency signal transmission, local fluctuations of these micro characteristics will cause uneven dielectric constant, leading to inconsistent impedance, and then causing signal reflection, phase distortion and increased transmission loss. Therefore, how to realize omnidirectional, high-sensitivity and non-contact real-time detection and characterization of the micro physical and chemical characteristics of the surface and near-surface region of the insulating layer in the production process of high-speed transmission cable has become a technical problem to be solved. SUMMARY

[0004] The main purpose of the present application is to solve the technical problems that the existing insulating layer detection method in the high-speed transmission cable production process cannot obtain micro physical and chemical characteristic information, the detection sensitivity is insufficient, and omnidirectional detection cannot be realized.

[0005] The first aspect of the present application provides a high-speed cable detection method, which comprises: A molecular field regulator is introduced to the surface of the insulating layer of the cable, the molecular field regulator including a hydrophobic segment, a polar head group and a bridging group, the molecular field regulator and the surface of the insulating layer forming an ordered molecular layer structure through intermolecular interaction, different local electric fields being generated in different regions according to the microcharacteristic differences of the surface of the insulating layer, and dielectric constant distribution data being obtained; According to the dielectric constant distribution data, the interaction between a hybrid probe formed by quantum dots and organic fluorescent molecules and the surface of the insulating layer is regulated, the change in the electron cloud distribution of the hybrid probe under the action of the local electric field is detected, the hybrid probe is subjected to multi-parameter detection, and probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are obtained; The probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are introduced into a critical state calculation framework, signal entropy, correlation degree and fluctuation amplitude parameters are calculated in phase space, the surface of the cable is divided into regions by using a recursive partitioning algorithm, signal characteristics are extracted at multiple characteristic scales by wavelet transform and fractal analysis, and microstructure distribution data of the surface and near-surface regions of the insulating layer are obtained; According to the dielectric constant distribution data and the microstructure distribution data, the crystallinity distribution, crosslinking degree distribution and residual stress distribution of the surface of the insulating layer are characterized, and micro-physical and chemical characteristic parameters of the insulating layer are obtained.

[0006] Preferably, the molecular field regulator is introduced to the surface of the insulating layer of the cable, the molecular field regulator including a hydrophobic segment, a polar head group and a bridging group, the molecular field regulator and the surface of the insulating layer forming an ordered molecular layer structure through intermolecular interaction, different local electric fields being generated in different regions according to the microcharacteristic differences of the surface of the insulating layer, and dielectric constant distribution data being obtained, comprising: The surface of the insulating layer of the cable is subjected to material type identification, and corresponding molecular field regulators are introduced to the surface of the insulating layer according to the material types, specifically including: for polyethylene materials, long-chain alkyl-containing phospholipid molecules are introduced, for fluoropolymers, zwitterionic molecules containing fluorine-containing segments are introduced, and for crosslinked polymers, molecules containing flexible side chains are introduced, and molecular field regulator type data is obtained; According to the molecular field regulator type data, the molecular field regulator is subjected to temperature gradient processing, the temperature being lowered at a rate of 0.5℃ / min in a temperature range of 25℃-40℃, and an alternating electric field with a frequency of 10Hz-50Hz and a strength of 0.1V / μm-0.5V / μm being applied, so as to form an ordered molecular layer structure; The ordered molecular layer structure is subjected to electric field distribution detection, the strength and direction parameters of the local electric field being calculated according to the arrangement rules of the ordered molecular layer structure in different regions of the surface of the insulating layer, and dielectric constant distribution data being obtained.

[0007] Preferably, according to the molecular field regulator type data, the molecular field regulator is subjected to temperature gradient treatment, and the temperature is lowered at a rate of 0.5℃ / min in the temperature range of 25℃-40℃, while an alternating current electric field with a frequency of 10Hz-50Hz and an intensity of 0.1V / μm-0.5V / μm is applied, to form an ordered molecular layer structure, including: According to the molecular field regulator type data, the temperature of the molecular field regulator is set to 36℃-40℃ for preheating treatment, and temperature pre-treatment data is obtained; According to the temperature pre-treatment data, the temperature is controlled to decrease in steps, the temperature decreasing rate in the temperature range of 24℃-28℃ is set to 0.3℃ / min, the temperature decreasing rate in the temperature range of 29℃-33℃ is set to 0.5℃ / min, and the temperature decreasing rate in the temperature range of 34℃-38℃ is set to 0.7℃ / min, to obtain stepwise cooling data; According to the stepwise cooling data, the alternating current electric field is regulated in sections, an alternating current electric field with a frequency of 35Hz-50Hz and an intensity of 0.35V / μm-0.5V / μm is applied in the temperature range of 24℃-28℃, an alternating current electric field with a frequency of 20Hz-30Hz and an intensity of 0.2V / μm-0.3V / μm is applied in the temperature range of 29℃-33℃, and an alternating current electric field with a frequency of 10Hz-15Hz and an intensity of 0.1V / μm-0.15V / μm is applied in the temperature range of 34℃-38℃, to form an ordered molecular layer structure.

[0008] Preferably, according to the dielectric constant distribution data, the interaction between the hybrid probe formed by the quantum dots and the organic fluorescent molecules and the surface of the insulating layer is regulated, the change in the electronic cloud distribution of the hybrid probe under the action of the local electric field is detected, and the hybrid probe is subjected to multi-parameter detection to obtain probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data, including: The CdSe / ZnS core-shell structure quantum dots are compounded with the organic fluorescent molecules containing the D-π-A structure, a ZnS shell layer, a PEG polymer layer, and an amphiphilic copolymer layer are coated on the surface of the quantum dots, and a hybrid probe is formed; According to the dielectric constant distribution data, the concentration and temperature of the hybrid probe are regulated, a probe distribution layer is formed on the surface of the insulating layer, and the change in the electronic cloud distribution of the hybrid probe in the probe distribution layer is detected to obtain quantum coherence time data; According to the quantum coherence time data, the probe distribution layer is subjected to light excitation treatment, the energy transfer efficiency of the hybrid probe and the surface of the cable is detected, and probe-surface interaction data is obtained; The probe-surface interaction data is subjected to multi-parameter analysis, and the probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data are synchronously collected and calculated.

[0009] Preferably, the probe fluorescence intensity, fluorescence lifetime, polarization and spectral shift data is introduced into a critical state calculation framework, signal entropy, correlation and fluctuation amplitude parameters are calculated in phase space, recursive partitioning algorithm is used to divide the cable surface into regions, signal characteristics are extracted on multiple characteristic scales through wavelet transform and fractal analysis, and microstructure distribution data of the insulating layer surface and near-surface region are obtained, including: The probe fluorescence intensity, fluorescence lifetime, polarization and spectral shift data are subjected to data standardization processing, the standardized data are mapped to phase space, the signal entropy, correlation and fluctuation amplitude parameters are calculated through a rolling time window, and a critical state parameter distribution map is obtained; According to the critical state parameter distribution map, the cable surface is divided into multiple regions using a recursive partitioning algorithm, and the signal statistical characteristics of each region are calculated to obtain regional distribution characteristic data; The regional distribution characteristic data is input into a wavelet transform processing unit, signal decomposition is performed on three characteristic scales greater than 10 μm, 2 μm-10 μm and less than 2 μm, and multi-scale signal component data are obtained; The multi-scale signal component data are subjected to fractal analysis, Lyapunov exponent and recurrence plot parameters are calculated, and microstructure distribution data of the insulating layer surface and near-surface region are obtained.

[0010] Preferably, the crystallinity distribution, crosslinking degree distribution and residual stress distribution of the insulating layer surface are characterized according to the dielectric constant distribution data and microstructure distribution data, and insulating layer micro-physical and chemical characteristic parameters are obtained, including: The dielectric constant distribution data and microstructure distribution data are subjected to data fusion processing, an insulating layer surface spatial distribution map is established, data partition processing is performed according to the signal fluctuation rules of local regions in the insulating layer surface spatial distribution map, and regional characteristic distribution data are obtained; The signal intensity variation in the regional characteristic distribution data is subjected to spectral analysis, and crystalline and non-crystalline phases are distinguished according to the signal spectral peak position and peak shape parameters of different regions, and crystallinity distribution data are obtained; The regional characteristic distribution data is subjected to deconvolution processing according to the crystallinity distribution data, the signals of crystalline regions are separated, and the attenuation characteristics of the signals are analyzed, and crosslinking degree distribution data are obtained; The crosslinking degree distribution data and the regional characteristic distribution data are subjected to correlation analysis, the phase difference of signals in different regions is calculated, and residual stress distribution data are obtained; The physical and chemical state of the insulating layer surface is comprehensively analyzed according to the crystallinity distribution data, crosslinking degree distribution data and residual stress distribution data, and insulating layer micro-physical and chemical characteristic parameters are obtained.

[0011] Preferably, after obtaining the micro-physical and chemical characteristic parameters of the insulating layer, the detection method of the high-speed cable comprises: According to the crystallinity distribution, cross-linking degree distribution, and residual stress distribution in the micro-physical and chemical characteristic parameters of the insulating layer, a bifunctional molecule is structurally designed, a detection domain, a modification domain, and an intelligent response segment are constructed in the bifunctional molecule, a fluorescence group responding to an electric field is introduced into the detection domain, a functional group changing the surface characteristics of the cable is introduced into the modification domain, the intelligent response segment connects the detection domain and the modification domain, and bifunctional molecule structure data is obtained. According to the bifunctional molecule structure data, the density distribution of the bifunctional molecule on the surface of the insulating layer is regulated, the concentration of the bifunctional molecule is controlled in a concentration range of 0.01 mg / ml to 0.5 mg / ml, temperature adjustment is performed in a temperature range of 20°C to 50°C, and a bifunctional molecule assembly layer is formed through the conformational change of the intelligent response segment. The bifunctional molecule assembly layer is cross-linked, the bifunctional molecule assembly layer and the insulating material form an interpenetrating network structure through the conformational change of the intelligent response segment, the thickness of the interpenetrating network structure is controlled, and molecular network structure data is obtained. According to the molecular network structure data, the interpenetrating network structure is subjected to light irradiation, heating, or chemical treatment, the intelligent response segment fixes the network structure, a stabilized network structure is formed, surface modification structure data is obtained, and the surface modification structure data is obtained.

[0012] Preferably, the bifunctional molecule assembly layer is cross-linked, the bifunctional molecule assembly layer and the insulating material form an interpenetrating network structure through the conformational change of the intelligent response segment, the thickness of the interpenetrating network structure is controlled, and molecular network structure data is obtained, comprising: The bifunctional molecule assembly layer is subjected to in-depth analysis, the conformational change range of the intelligent response segment is calculated according to the network void size of the insulating material, and conformational regulation parameters are obtained. According to the conformational regulation parameters, the conformational change of the intelligent response segment is adjusted, the stretching degree of the intelligent response segment is controlled in a pH value interval of 4.0-5.5, a pH value interval of 6.0-7.5, and a pH value interval of 8.0-9.5, respectively, and a molecular penetration layer of different depths is formed. The thickness of the molecular penetration layer is controlled in stages, the cross-linking density is regulated in three depth intervals of 20 nm-45 nm, 55 nm-90 nm, and 100 nm-140 nm, respectively, cross-linking points are formed in each depth interval through ultraviolet light irradiation, temperature adjustment, or chemical reagent treatment, an interpenetrating network structure with a gradient structure is constructed, and molecular network structure data is obtained.

[0013] Preferably, after the surface modification structure data is obtained, the high-speed cable detection method comprises the following steps: The surface modification structure data is preliminarily analyzed, and a pair of entangled photons is generated according to the analysis result; the wavelength and polarization state of the pair of entangled photons are controlled to obtain quantum entanglement state data; The polarization state and wave vector of the probe photons are controlled according to the quantum entanglement state data, the stabilized network structure is scanned and analyzed, and three-dimensional distribution data of the dielectric constant, molecular orientation and charge distribution are obtained; The three-dimensional distribution data is subjected to quantum state purification processing, the quantum state parameters of different depth regions in the stabilized network structure are calculated, and modification layer structure parameter data are obtained; The impedance consistency, dielectric loss and shielding effectiveness of the stabilized network structure are evaluated according to the modification layer structure parameter data, performance index data are generated, and the performance index data are fed back to the bifunctional molecular structure design step to optimize the structure of the bifunctional molecule.

[0014] The second aspect of the application provides a high-speed cable detection device, which comprises: A molecular field regulation module is used for introducing a molecular field regulation agent to the surface of the insulating layer of the cable, the molecular field regulation agent comprises a hydrophobic segment, a polar head group and a bridging group, the molecular field regulation agent and the surface of the insulating layer form an ordered molecular layer structure through intermolecular interaction, different local electric fields of different intensities are generated in different regions according to the microcharacteristic differences of the surface of the insulating layer, and dielectric constant distribution data are obtained; A hybrid probe detection module is used for regulating the interaction between a hybrid probe formed by quantum dots and organic fluorescent molecules and the surface of the insulating layer according to the dielectric constant distribution data, detecting the change in electron cloud distribution of the hybrid probe under the action of the local electric field, performing multi-parameter detection on the hybrid probe, and obtaining probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data; A signal processing and feature extraction module is used for importing the probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data into a critical state calculation framework, calculating signal entropy, correlation degree and fluctuation amplitude parameters in phase space, dividing the surface of the cable into regions by using a recursive partitioning algorithm, extracting signal features at multiple characteristic scales through wavelet transform and fractal analysis, and obtaining microstructure distribution data of the surface of the insulating layer and the near-surface region; A microcharacteristic characterization module is used for characterizing the crystallinity distribution, crosslinking degree distribution and residual stress distribution of the surface of the insulating layer according to the dielectric constant distribution data and the microstructure distribution data, and obtaining insulating layer microphysical and chemical characteristic parameters.

[0015] The third aspect of the present application provides a high-speed cable detection device, comprising: a memory and at least one processor, the memory has instructions stored therein, and the memory and the at least one processor are interconnected by a line; the at least one processor calls the instructions in the memory to enable the high-speed cable detection device to perform the steps of the subject matter of the first aspect described above.

[0016] The fourth aspect of the present application provides a computer-readable storage medium having instructions stored therein, which, when executed on a computer, cause the computer to perform the steps of the high-speed cable detection method described above.

[0017] The technical scheme provided by the embodiments of the present application establishes a complete detection system by introducing a molecular field regulator. The molecular field regulator includes a hydrophobic segment, a polar head group, and a bridging group, and forms an ordered molecular layer structure when interacting with the surface of the insulating layer. This ordered molecular layer structure can generate local electric fields of different intensities in different regions according to the differences in the microstructure of the insulating layer surface, thereby achieving accurate detection of the dielectric constant distribution. Because the molecular field regulator has high surface sensitivity, it can accurately reflect changes in the microstructure of the insulating layer surface.

[0018] Based on the obtained dielectric constant distribution data, the method further introduces a hybrid probe formed by quantum dots and organic fluorescent molecules. This hybrid probe will change the electron cloud distribution under the action of a local electric field, and by simultaneously detecting multiple parameters such as fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift of the probe, more abundant physical and chemical information about the surface of the insulating layer can be obtained. The quantum characteristics of the hybrid probe make it highly sensitive to small changes in the surface environment, overcoming the problem of insufficient sensitivity of traditional detection methods.

[0019] After importing the data obtained by the above detection into a critical state calculation framework, by calculating the signal entropy, correlation degree, and fluctuation amplitude parameters in the phase space, and combining the recursive partitioning algorithm to divide the surface of the cable into regions, accurate analysis of the detection signal can be achieved. Using wavelet transform and fractal analysis to extract signal features at multiple characteristic scales makes the detection range cover different depths from the surface to the near-surface region, solving the problem that traditional methods cannot achieve omnidirectional detection.

[0020] Based on the obtained dielectric constant distribution data and microstructure distribution data, the method systematically characterizes the crystallinity distribution, crosslinking degree distribution, and residual stress distribution of the surface of the insulating layer. This multi-dimensional characterization method not only reflects the overall state of the insulating layer, but also reveals the changes in the microstructure of the local region. Through this systematic detection and characterization, a comprehensive understanding of the microphysical and chemical properties of the insulating layer of the high-speed transmission cable is achieved, providing reliable technical support for quality control during production. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0022] Figure 1 Schematic diagram of an embodiment of a high-speed cable detection method according to an embodiment of the present invention; Figure 2 Schematic diagram of an embodiment of a high-speed cable detection device according to an embodiment of the present invention; Figure 3 FIG. 1 is a schematic diagram of an embodiment of a high-speed cable detection device according to an embodiment of the present invention.

[0023] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0025] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), such directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0026] In addition, the descriptions of "first", "second", etc. in the present invention are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, and must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0027] An embodiment of the present application provides a method for detecting a high-speed cable. Figure 1 A flowchart of a high-speed cable detection method provided in one embodiment of the present application. In this embodiment, the method includes: See also Figure 1 A molecular field modulator is introduced onto the surface of the insulation layer of the cable. The molecular field modulator comprises a hydrophobic segment, a polar head group, and a bridging group. The molecular field modulator interacts with the surface of the insulation layer to form an ordered molecular layer structure. Local electric fields of varying strengths are generated in different regions based on differences in the microscopic properties of the insulation layer surface, thereby obtaining dielectric constant distribution data. In one embodiment of the present invention, a molecular field modulator is introduced into the surface of the insulation layer of the cable. The molecular field modulator includes a hydrophobic segment, a polar head group, and a bridging group. The molecular field modulator interacts with the surface of the insulation layer to form an orderly arranged molecular layer structure. Local electric fields of different intensities are generated in different regions according to differences in microscopic properties of the surface of the insulation layer, and dielectric constant distribution data is obtained, including: Identify the material type of the insulation layer surface of the cable and introduce corresponding molecular field modulators to the insulation layer surface according to the material type, specifically introducing phospholipid molecules containing long-chain alkyl groups for polyethylene materials, introducing zwitterionic molecules containing fluorinated segments for fluoropolymers, and introducing molecules containing flexible side chains for cross-linked polymers to obtain molecular field modulator type data; According to the molecular field modulator type data, the molecular field modulator is subjected to a temperature gradient treatment, wherein the temperature is lowered within a temperature range of 25°C to 40°C at a rate of 0.5°C / minute, while an alternating current electric field with a frequency of 10 Hz to 50 Hz and an intensity of 0.1 V / μm to 0.5 V / μm is applied to form an ordered molecular layer structure; The electric field distribution of the ordered molecular layer structure is detected, and the intensity and direction parameters of the local electric field are calculated according to the arrangement rules of the ordered molecular layer structure in different areas on the surface of the insulating layer to obtain dielectric constant distribution data.

[0028] The following is a detailed description of the steps involved in the above embodiment: To identify the material type of the cable insulation layer surface, infrared spectroscopy analysis technology is first used. Fourier transform infrared spectrometer is used to scan the insulation layer surface to obtain characteristic absorption peaks. Polyethylene materials have a wavelength of 2800 cm -1 -3000cm -1 The CH stretching vibration absorption peak is shown in the range of 1000 cm-1. -1 -1400cm -1 The CF stretching vibration characteristic peak is present in the range of 1620 cm -1 -1680cm -1 The absence of C=C bonds within the range is identified. After identification, specific molecular field modulators are introduced for different material types: for polyethylene materials, phospholipid molecules containing long-chain alkyl groups (C14-C18) such as phosphatidylcholine are selected, whose hydrophobic segments can stably bind to the polyethylene surface through hydrophobic interactions; for fluoropolymers, zwitterionic molecules containing fluorinated segments such as perfluorooctane sulfonic acid are used, whose fluorinated parts form strong fluorine-fluorine interactions with the fluoropolymer surface; for cross-linked polymers, flexible side chain molecules such as polysiloxanes containing polyethylene glycol side chains are introduced, whose flexible structures can penetrate into the gaps of the cross-linked network. The concentration and purity of the molecular field modulator are analyzed by high-performance liquid chromatography-mass spectrometry to generate molecular field modulator type data. This method of targeted selection of molecular field modulators is based on the theory of interfacial molecular recognition, which ensures the optimal binding force and arrangement stability between the molecules and the surface of the insulating layer, significantly improving the accuracy and repeatability of subsequent detection.

[0029] According to the type of molecular field regulator data, the cable insulation layer coated with the molecular field regulator is placed in a constant temperature cavity by using a precision temperature control system when the temperature gradient treatment is performed. The initial temperature is set to 40 DEG C to promote the free diffusion and preliminary arrangement of the molecules, and then slowly reduced to 25 DEG C at a constant cooling rate of 0.5 DEG C / min, so that the molecular field regulator gradually changes from the free motion state to the ordered arrangement state. During the cooling process, an alternating current electric field with a frequency of 10 Hz-50 Hz and an intensity of 0.1 V / μm-0.5 V / μm is applied through a parallel electrode system, and the frequency and intensity of the electric field are accurately controlled by a function signal generator and a high-precision amplifier. The action of the electric field causes the molecular field regulator with a polar head group to arrange along the direction of the electric field, forming a highly ordered molecular layer structure. The temperature and electric field parameters are monitored in real time by a computer system during the whole process to ensure the stability and controllability of the treatment conditions. The temperature gradient treatment parameters (0.5 DEG C / min, 25 DEG C-40 DEG C) are optimized, and the cooling rate is slow enough to allow the molecules to arrange fully without defects, and the temperature range covers the phase transition temperature of most molecular field regulators. The setting of the alternating current electric field parameters (10 Hz-50 Hz, 0.1 V / μm-0.5 V / μm) ensures that the electric field intensity is sufficient to induce molecular arrangement without damaging the molecular structure, and the frequency range matches the polarization response time of most molecules.

[0030] When detecting the electric field distribution of the formed ordered molecular layer structure, an electric force microscope technology is used. The microscope is equipped with a nanoscale conductive probe, and the surface electric field distribution map is drawn by detecting the electrostatic force between the probe and the sample surface. During scanning, the probe performs grid format scanning on the surface of the insulation layer at a step size of 50 nm-100 nm, and records the electrostatic force signal of each point. The obtained original data is converted into electric field intensity values through the electric field-distance relationship model, and the dielectric constant distribution is calculated through the relationship equation E=D / ε (E is the electric field intensity, D is the electric potential displacement, and ε is the dielectric constant). For the cylindrical surface of the cable, a cylindrical coordinate system correction algorithm is used to eliminate the measurement deviation caused by the geometric shape, and finally a high-precision dielectric constant distribution data graph is generated. The dielectric constant distribution data obtained by this method has a nanoscale spatial resolution, which can accurately reflect the non-uniformity of the microstructure of the insulation layer, provide key basic data for subsequent characterization of the microphysical and chemical properties of the insulation layer, and directly evaluate the impedance consistency and signal integrity of the cable in high-frequency signal transmission.

[0031] In an embodiment of the present application, the temperature gradient treatment of the molecular field regulator according to the type of the molecular field regulator data includes reducing the temperature at a rate of 0.5 DEG C / min in a temperature range of 25 DEG C-40 DEG C while applying an alternating current electric field with a frequency of 10 Hz-50 Hz and an intensity of 0.1 V / μm-0.5 V / μm to form an ordered molecular layer structure, and the temperature gradient treatment of the molecular field regulator according to the type of the molecular field regulator data includes: According to the molecular field regulator type data, the temperature of the molecular field regulator is set to 36-40°C for preheating, and the temperature pre-treatment data is obtained; According to the temperature pre-treatment data, the temperature is controlled in steps, the cooling rate is set to 0.3°C / min in the temperature range of 24-28°C, 0.5°C / min in the temperature range of 29-33°C, and 0.7°C / min in the temperature range of 34-38°C, and the stepwise cooling data is obtained. According to the stepwise cooling data, the alternating current field is regulated in sections, the alternating current field with a frequency of 35-50Hz and an intensity of 0.35-0.5V / μm is applied in the temperature range of 24-28°C, the alternating current field with a frequency of 20-30Hz and an intensity of 0.2-0.3V / μm is applied in the temperature range of 29-33°C, and the alternating current field with a frequency of 10-15Hz and an intensity of 0.1-0.15V / μm is applied in the temperature range of 34-38°C, forming an ordered arrangement of molecular layer structure.

[0032] The following is a specific description of the steps involved in the above embodiments: When the temperature of the molecular field regulator is set according to the molecular field regulator type data, a multi-section precision temperature control system is used. This system includes a main heating unit, a temperature sensor array and a microprocessor controller, and can achieve a temperature control accuracy of ±0.1°C. For polyethylene-based phospholipid molecular field regulators, the temperature is set to 38-40°C for preheating; for fluoropolymer zwitterionic molecular field regulators, the temperature is set to 37-39°C for preheating; for cross-linked polymer flexible side chain molecular field regulators, the temperature is set to 36-38°C for preheating. The preheating process lasts for 10-15 minutes, so that the molecular field regulator is fully activated and reaches a state of thermodynamic equilibrium. During the preheating process, the surface temperature distribution of the cable is monitored in real time by an infrared thermal imager to ensure temperature uniformity, with temperature fluctuations controlled within ±0.2°C. The temperature sensor collects temperature data at a frequency of 5 times per second, and the temperature-time curve is recorded and generated by the data acquisition system, forming the temperature pre-treatment data. The temperature range of 36-40°C is selected based on the results of molecular dynamics simulation. At this temperature interval, the molecular field regulator has a high enough kinetic energy for free diffusion, but does not cause thermal degradation, ensuring that the molecules maintain their complete functional structure.

[0033] When performing the stepwise cooling control on the temperature pretreatment data, a programmed cooling control system is used. According to the molecular activity parameters recorded in the temperature pretreatment data, the system divides three temperature intervals and controls the cooling rate respectively. In the temperature interval of 34-38°C, the molecular activity is high and the fluidity is strong, so a faster cooling rate of 0.7°C / min is adopted to quickly reduce to the temperature threshold at which the molecules begin to arrange in order. In the temperature interval of 29-33°C, the molecular activity is moderate, which is the key stage of molecular ordered arrangement, so a moderate cooling rate of 0.5°C / min is adopted to ensure that the molecules have enough time to adjust the conformation and form ordered arrangement. In the temperature interval of 24-28°C, the molecular activity is reduced, and it needs a longer time to reach the lowest energy state, so a slower cooling rate of 0.3°C / min is adopted. The whole cooling process is accurately executed through the PID control algorithm, and the system records the actual temperature data every 5 seconds, which is compared with the set curve, and when the deviation is more than ±0.2°C, the heating or cooling power is automatically adjusted. The temperature sensor array is arranged at different positions on the cable surface to ensure that the temperature of the whole cable surface decreases uniformly. After the cooling is completed, the system generates stepwise cooling data including the actual temperature change curve, cooling rate and temperature uniformity data. This stepwise cooling method considers the molecular dynamics behavior of the molecular field regulator at different temperatures, and avoids the molecular arrangement defects and local disordered regions that are prone to occur in the traditional constant cooling rate method.

[0034] To perform segmented control of the AC electric field based on the step-cooling data, a multi-band programmable AC electric field generator is used. This device, comprised of a signal generation unit, a power amplifier, and a parallel electrode system, enables precise control of the electric field's frequency and intensity. Based on real-time temperature data fed by a temperature sensor, the system automatically switches electric field parameters. In the 34°C-38°C temperature range, molecular thermal motion is intense, requiring a weaker electric field to guide alignment. Therefore, a low-intensity AC electric field with a frequency of 10Hz-15Hz and an intensity of 0.1V / μm-0.15V / μm is applied. In the 29°C-33°C temperature range, molecular motion slows, so the electric field intensity is increased to 0.2V / μm-0.3V / μm and the frequency to 20Hz-30Hz to enhance control of molecular alignment. In the 24°C-28°C temperature range, molecular activity further decreases, so a high-intensity AC electric field with a frequency of 35Hz-50Hz and an intensity of 0.35V / μm-0.5V / μm is applied to stabilize the molecules' final alignment. The switching process of the electric field parameters is smooth, avoiding disturbances in the molecular arrangement caused by sudden changes. During the application of the electric field, the molecular arrangement state is monitored in real time by a polarized light microscope, and the degree of order is evaluated by observing changes in the intensity of the polarized light. The resulting ordered molecular layer structure is highly directional and uniform, with the deviation of the molecular arrangement direction controlled within ±5° and a coverage rate of over 95%. This method of coordinated regulation of temperature and electric field solves the problem that traditional single parameter control methods have difficulty in achieving highly ordered molecular layers, and significantly improves the accuracy and stability of subsequent electric field distribution detection.

[0035] Please continue reading Figure 1 , regulating the interaction between the hybrid probe formed by the quantum dots and the organic fluorescent molecules and the surface of the insulating layer according to the dielectric constant distribution data, detecting the change in the electron cloud distribution generated by the hybrid probe under the action of the local electric field, performing multi-parameter detection on the hybrid probe, and obtaining probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data; In one embodiment of the present invention, the interaction between the hybrid probe formed by the quantum dots and the organic fluorescent molecules and the surface of the insulating layer is regulated according to the dielectric constant distribution data, the change in the electron cloud distribution generated by the hybrid probe under the action of the local electric field is detected, and the hybrid probe is subjected to multi-parameter detection to obtain probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data, including: CdSe / ZnS core-shell quantum dots were composited with organic fluorescent molecules containing a D-π-A structure, and the surface of the quantum dots was coated with a ZnS shell layer, a PEG polymer layer, and an amphiphilic copolymer layer to form a hybrid probe. regulating the concentration and temperature of the hybrid probe according to the dielectric constant distribution data, forming a probe distribution layer on the surface of the insulating layer, detecting changes in the electron cloud distribution of the hybrid probe in the probe distribution layer, and obtaining quantum coherence time data; According to the quantum coherence time data, the probe distribution layer is subjected to optical excitation treatment, the energy transfer efficiency of the hybrid probe and the cable surface is detected, and probe-surface interaction data is obtained; The probe-surface interaction data is subjected to multi-parameter analysis, and probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are synchronously collected and calculated.

[0036] The following specifically describes the steps involved in the above embodiments: CdSe / ZnS core-shell structure quantum dots are compounded with organic fluorescent molecules containing D-π-A structure by microemulsion method. First, CdSe core quantum dots with a diameter of 3-5 nm are prepared, and then ZnS shell is grown on the surface to improve optical stability, and the shell thickness is 1-2 nm. After the preparation of quantum dots, surface modification is carried out: first, a PEG polymer layer with a thickness of about 2-3 nm is formed on the surface of the ZnS shell by thiolation reaction to provide water solubility and biocompatibility; then an amphiphilic copolymer containing a maleimide group is added, and the residual thiol group is combined through sulfur-ene addition reaction to form the outermost amphiphilic copolymer layer. The D-π-A structure organic fluorescent molecule (such as a molecule containing an electron-donating group-conjugated bridge-electron-accepting group, for example, N,N-dimethylamino styryl quinoline derivative) is combined with the amphiphilic copolymer layer through covalent bond or non-covalent interaction. The D-π-A structure refers to a special structure in which the molecule contains an electron donor (D), a π conjugated bridge and an electron acceptor (A), which has high polarizability and is sensitive to electric field. The entire synthesis process is carried out under nitrogen protection, and finally ultrafiltration and gel chromatography purification are performed to obtain hybrid probes with an average particle size of 10-15 nm. This multi-layer structure design makes the hybrid probe have high quantum yield of quantum dots and high sensitivity to electric field of D-π-A molecules, realizing high sensitivity response to the change of the surface micro-electric field of the insulating layer.

[0037] A computer-controlled precision injection system is used to regulate the concentration and temperature of the hybrid probes according to the permittivity distribution data. The system automatically adjusts the concentration of the hybrid probe solution according to the permittivity values in different regions: for regions with low permittivity (ε < 2.0), a high-concentration (10 μg / ml-15 μg / ml) probe solution is used; for regions with medium permittivity (2.0 ≤ ε ≤ 2.5), a medium-concentration (5 μg / ml-8 μg / ml) probe solution is used; for regions with high permittivity (ε > 2.5), a low-concentration (2 μg / ml-4 μg / ml) probe solution is used. The temperature control system maintains the cable surface temperature within the range of 22-25°C, ensuring that the hybrid probes are in full contact with the insulating layer surface but do not undergo thermal denaturation. After the solution spraying is completed, a cold air drying system is used to quickly evaporate the solvent in the solution, forming a probe distribution layer with a thickness of about 50-100 nm. The probe distribution layer is scanned using a fluorescence confocal microscope, with the excitation wavelength set to 405 nm and the emission spectrum collected in the range of 480-650 nm. A specially designed quantum coherence measurement device is used to measure the changes in the electronic cloud distribution of the hybrid probes under the action of the local electric field, and the quantum coherence time (usually in the range of 5-200 ns) is recorded. This precise regulation of concentration and temperature ensures the uniformity and response sensitivity of the probe distribution layer, providing a foundation for accurately detecting the micro-electric field distribution on the surface of the insulating layer.

[0038] A wavelength-tunable pulsed laser is used to perform light excitation processing on the probe distribution layer according to the quantum coherence time data. The laser outputs laser pulses with a wavelength of 405 nm and a pulse width of 5-10 picoseconds, and the pulse energy is dynamically adjusted according to the quantum coherence time data: for regions with long quantum coherence time (> 150 ns), low-energy (0.5-1 μJ) pulses are used; for regions with medium quantum coherence time (50-150 ns), medium-energy (1-2 μJ) pulses are used; for regions with short quantum coherence time (< 50 ns), high-energy (2-3 μJ) pulses are used. During the light excitation process, a time-resolved fluorescence spectrometer is used to collect the fluorescence decay curve of the hybrid probes, and the arrival time of each photon is recorded through time-correlated single-photon counting technology. The energy transfer efficiency between the hybrid probes and the cable surface is calculated according to the fluorescence decay curve, with the formula η = 1-(τDA / τD), where τDA represents the fluorescence lifetime of the donor in the presence of the acceptor, and τD represents the fluorescence lifetime of the donor itself. The energy transfer efficiency reflects the interaction strength between the hybrid probes and the cable surface, and the probe-surface interaction data is generated. This dynamic light excitation processing method based on quantum coherence time significantly improves the signal-to-noise ratio and sensitivity of the detection, enabling the system to accurately distinguish small changes in the electric field on the surface of the insulating layer.

[0039] A multi-channel fluorescence analysis system is used for multi-parameter analysis of the probe-surface interaction data. The system includes four independent detection channels for collecting fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data. The fluorescence intensity is directly measured by a photomultiplier tube; the fluorescence lifetime is obtained by fitting the fluorescence decay curve through time-correlated single photon counting technology; the polarization degree is calculated by the ratio of fluorescence intensity in two orthogonal polarization directions, and the calculation formula is P=(I‖-I⊥) / (I‖+I⊥), wherein I‖ and I⊥ are the fluorescence intensities in parallel and perpendicular directions of the excitation light polarization direction; the spectral shift is measured by a high-resolution spectrometer to measure the change of the fluorescence peak position. All parameters are collected synchronously, and the sampling rate is 10 MHz. The data is transmitted to the computer for real-time processing through a high-speed acquisition card. The data processing software uses a multivariate analysis algorithm to establish a correlation model of the four parameters and the surface micro-physical and chemical properties of the insulating layer. Taking the polyethylene insulating layer commonly used in high-speed transmission cables as an example, the fluorescence intensity mainly reflects the surface charge density distribution, the fluorescence lifetime reflects the molecular motion freedom and crystallinity, the polarization degree reflects the molecular arrangement orientation, and the spectral shift reflects the local electric field strength. This multi-parameter synchronous analysis method overcomes the limitations of single parameter detection, provides comprehensive information of the surface properties of the insulating layer, and greatly improves the accuracy and reliability of the detection.

[0040] Please continue to refer to Figure 1 The probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are imported into a critical state calculation framework, the signal entropy value, correlation degree and fluctuation amplitude parameters are calculated in the phase space, the recursive partitioning algorithm is used for regional division of the cable surface, the signal characteristics are extracted at multiple characteristic scales through wavelet transform and fractal analysis, and the microstructure distribution data of the insulating layer surface and the near-surface region are obtained. In an embodiment of the present application, the probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are imported into a critical state calculation framework, the signal entropy value, correlation degree and fluctuation amplitude parameters are calculated in the phase space, the recursive partitioning algorithm is used for regional division of the cable surface, the signal characteristics are extracted at multiple characteristic scales through wavelet transform and fractal analysis, and the microstructure distribution data of the insulating layer surface and the near-surface region are obtained, including: The probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are subjected to data standardization processing, the standardized data are mapped to the phase space, the signal entropy value, correlation degree and fluctuation amplitude parameters are calculated through a rolling time window, and a critical state parameter distribution map is obtained. According to the critical state parameter distribution map, the recursive partitioning algorithm is used to divide the cable surface into multiple regions, and the signal statistical characteristics of each region are calculated to obtain regional distribution characteristic data. The region distribution characteristic data is input into a wavelet transform processing unit, signal decomposition is performed at three characteristic scales of greater than 10 μm, 2 μm-10 μm and less than 2 μm, and multi-scale signal component data is obtained; Fractal analysis is performed on the multi-scale signal component data, Lyapunov exponent and recurrence plot parameters are calculated, and microstructure distribution data of the surface and near-surface region of the insulating layer is obtained.

[0041] The following specifically describes the steps involved in the above embodiments: A multi-step normalization process is used for data standardization of the probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data. First, the original data is pre-processed by a high-performance computing workstation to remove outliers and background noise, and outliers are defined as data points exceeding the mean value ± 3 times the standard deviation. Subsequently, the four parameters are normalized respectively: fluorescence intensity data is divided by the reference fluorescence intensity standard; fluorescence lifetime data is mapped to the 0-1 interval through linear transformation; polarization degree data is directly used as its absolute value; spectral shift data is normalized by reference wavelength. After standardization, the four-dimensional data points composed of the four parameters are mapped to phase space, which is a mathematical concept space used to describe the state evolution of dynamic systems. In phase space, three key parameters are calculated through a rolling time window (window width is set to 0.5-2 seconds, dynamically adjusted according to the cable production speed of 5-50 m / min): signal entropy value (representing the degree of chaos of the system), correlation degree (representing the mutual dependence between signals) and fluctuation amplitude (representing the degree of change in the signal). The signal entropy value is calculated by Shannon entropy; the correlation degree is calculated by cross-correlation function; the fluctuation amplitude is calculated by the standard deviation of the signal. These three parameters constitute the critical state parameter space, and the critical state parameter distribution map is generated through pseudo-color coding. This data processing method based on complex system theory can efficiently extract nonlinear features from the signal, making the system highly sensitive to small physical and chemical changes on the surface of the insulating layer.

[0042] When dividing the cable surface into multiple regions according to the critical state parameter distribution map using the recursive partitioning algorithm, an adaptive threshold segmentation technique is adopted. The algorithm first calculates the global entropy distribution of the critical state parameter distribution map to determine the initial segmentation threshold. Then, the recursive bisection operation is performed on the image: each iteration divides the current region into two sub-regions, and the segmentation point is selected at the location of the maximum parameter gradient. The recursive process continues until the termination condition is met: the parameter variance within the region is less than the preset threshold (usually set to 5% of the global variance) or the region size is less than the minimum limit (set to 2mm x 2mm). Taking the polyethylene insulation layer of a high-speed transmission cable as an example, the partitioning algorithm usually divides the surface into 3-8 main regions, corresponding to different crystallinity, crosslinking degree, and residual stress distribution. For each region, the statistical characteristics of the four characteristic parameters are calculated: mean value (reflecting the overall level of the region), standard deviation (reflecting the uniformity within the region), skewness (reflecting the symmetry of the distribution), and kurtosis (reflecting the sharpness of the distribution). These statistical characteristics form the region distribution feature data matrix, which is used to represent the differences in micro-physical and chemical characteristics of different regions. This adaptive partitioning method overcomes the limitations of traditional fixed threshold segmentation and can accurately identify the natural boundaries of the physical and chemical characteristics of the insulation layer surface, providing accurate spatial positioning for subsequent multi-scale analysis.

[0043] When inputting the region distribution feature data into the wavelet transform processing unit, a discrete wavelet transform technique is adopted. Wavelet transform is a time-frequency domain analysis tool that can decompose signals at different scales. The processing unit uses the Daubechies wavelet basis function (db4) for multi-layer decomposition, extracting signal features at three characteristic scales: scales greater than 10μm (corresponding to the 1st-3rd layer of wavelet decomposition) mainly reflect the macrostructure and large-scale crystalline regions of the material; scales of 2μm-10μm (corresponding to the 4th-6th layer of wavelet decomposition) reflect the medium-scale molecular arrangement and interface structure; scales less than 2μm (corresponding to the 7th-9th layer of wavelet decomposition) reflect the micro-molecular chain arrangement and nanoscale defects. The selection of these three characteristic scales is based on the characteristic structural sizes of high-speed transmission cable insulation materials: the diameter of polyethylene large crystal spheres is usually 10μm-50μm, the thickness of the crystal sheet is 2μm-8μm, and the molecular chain spacing is less than 2μm. The decomposition process separates the signal of each region into approximation coefficients (representing low-frequency components) and detail coefficients (representing high-frequency components), which together constitute the multi-scale signal component data. This multi-scale analysis method breaks through the limitations of traditional single-scale detection and can simultaneously obtain structural information at different levels of the insulation layer, fully reflecting the micro-characteristics of the material.

[0044] When performing fractal analysis on multi-scale signal component data, a nonlinear dynamics analysis method is adopted. The method first reconstructs a phase space to convert a one-dimensional time series into a multi-dimensional trajectory. In the reconstructed space, Lyapunov exponents (characterizing the chaotic degree and sensitivity of the system) and recurrence plot parameters (characterizing the periodicity and determinacy of the system) are calculated. Lyapunov exponents are calculated by trajectory divergence rate, and a positive value indicates chaotic behavior, while a negative value indicates stable structure; recurrence plot is obtained by calculating the re-visit rate of the trajectory in the phase space, and is used to identify the implicit patterns in the system. For the insulation layer of a high-speed transmission cable, the area with high crystallinity usually exhibits a lower Lyapunov exponent and a clear diagonal structure; the area with high crosslinking degree exhibits a higher recurrence rate; and the area with residual stress concentration exhibits a non-uniform recurrence distribution. The microstructure distribution data of the surface and near-surface area of the insulation layer are constructed by these parameters. The fractal analysis method can extract deterministic rules from seemingly random signal fluctuations, identify microstructure changes that are difficult to find by traditional methods, and provide a new analysis method for the quality control of the insulation layer of a high-speed transmission cable, significantly improving the prediction accuracy of dielectric performance abnormalities.

[0045] Please continue to refer to Figure 1 According to the dielectric constant distribution data and the microstructure distribution data, the crystallinity distribution, the crosslinking degree distribution, and the residual stress distribution of the surface of the insulation layer are characterized, and micro-physical and chemical characteristic parameters of the insulation layer are obtained.

[0046] In an embodiment of the present application, the characterization of the crystallinity distribution, the crosslinking degree distribution, and the residual stress distribution of the surface of the insulation layer according to the dielectric constant distribution data and the microstructure distribution data, and the obtaining of the micro-physical and chemical characteristic parameters of the insulation layer comprise: The dielectric constant distribution data and the microstructure distribution data are subjected to data fusion processing to establish a spatial distribution map of the surface of the insulation layer, and the signal fluctuation rules in local areas in the spatial distribution map of the surface of the insulation layer are subjected to data partition processing to obtain regional characteristic distribution data; The signal intensity changes in the regional characteristic distribution data are subjected to spectral analysis, and the crystalline phase and the amorphous phase are distinguished according to the signal spectral peak position and the peak shape parameters of different regions to obtain crystallinity distribution data; The regional characteristic distribution data are subjected to deconvolution processing according to the crystallinity distribution data to separate the signals of the crystalline regions, and the attenuation characteristics of the signals are analyzed to obtain crosslinking degree distribution data; The crosslinking degree distribution data are subjected to correlation analysis with the regional characteristic distribution data to calculate the phase difference of signals in different regions to obtain residual stress distribution data; The physical and chemical states of the surface of the insulation layer are comprehensively analyzed according to the crystallinity distribution data, the crosslinking degree distribution data, and the residual stress distribution data to obtain micro-physical and chemical characteristic parameters of the insulation layer.

[0047] The following describes the steps involved in the above embodiments in detail: The data fusion process of dielectric constant distribution data and microstructure distribution data adopts a hierarchical Bayesian fusion algorithm. This algorithm runs on a high-performance workstation, first aligns the two data to a unified spatial coordinate system, adopts the cylindrical coordinate system (r, θ, z) of the cable surface, and ensures one-to-one correspondence of spatial positions. After data alignment, the joint probability distribution of each spatial point is calculated through Bayesian inference, representing the correlation between dielectric properties and microstructure. During the fusion process, the weight of different data sources is dynamically adjusted according to their signal-to-noise ratio: high signal-to-noise ratio data obtains higher weight, and low signal-to-noise ratio data obtains lower weight. Taking the cross-linked polyethylene insulation layer commonly found in high-speed cables as an example, the fusion algorithm can correlate the surface electric field distribution with the crystallinity variation, forming an intuitive spatial distribution map of the insulation layer surface. Subsequently, the K-means clustering algorithm is used for data partitioning of the spatial distribution map, grouping regions with similar characteristics. The number of clusters is automatically determined, usually 3-7, based on the Elbow method to determine the optimal number of clusters. After partitioning, the characteristic parameters of each region are calculated: average dielectric constant, dielectric constant standard deviation, microstructure complexity, and structure correlation length, generating regional characteristic distribution data. This fusion method combines the advantages of the two complementary data sources, significantly improving the accuracy and comprehensiveness of insulation layer property analysis.

[0048] The spectral analysis of signal intensity changes in regional characteristic distribution data uses Fast Fourier Transform (FFT) combined with peak decomposition technology. The signal intensity data of each region is subjected to FFT transformation to obtain a frequency domain representation, and then a multi-Gaussian function is used to fit the frequency spectrum. In high-speed transmission cable insulation materials such as polyethylene, crystalline and amorphous phases exhibit different characteristics in the frequency spectrum: crystalline phase usually produces sharp peaks in the 5Hz-15Hz frequency band, with a full width at half maximum (FWHM) of less than 2Hz, corresponding to ordered arrangement of molecular chains; amorphous phase produces broad peaks in the 2Hz-7Hz frequency band, with a FWHM of more than 3Hz, reflecting disordered molecular conformation. By calculating the relative intensity of peaks in different frequency bands, the crystalline and amorphous phase proportions of each region are determined. For the polyethylene insulation layer of high-speed transmission cables, the crystallinity is usually in the range of 60%-85%, which has a significant impact on different frequency signal transmission characteristics. Finally, the crystallinity distribution data is generated in the form of a pseudo-color map for intuitive presentation. This spectral analysis-based crystallinity characterization method has higher spatial resolution than traditional Differential Scanning Calorimetry (DSC), and can identify micro-crystalline regions as small as 20μm, providing a more detailed evaluation means for quality control of high-speed transmission cable insulation layers.

[0049] The Lucy-Richardson iterative algorithm is used for deconvolution of the regional characteristic distribution data based on the crystallinity distribution data. This algorithm treats the regional characteristic distribution data as the convolution result of crystalline region signal and non-crystalline region signal, and separates the two contributions through iterative optimization. For high-speed transmission cable insulation, the crosslinked structure is mainly distributed in the non-crystalline region, and the crosslinking degree can be accurately evaluated by separating the non-crystalline region signal. The maximum number of iterations is set to 50 and the convergence threshold is set to 0.1% to ensure the stability of the calculation results. After separating the non-crystalline region signal, the attenuation characteristics are analyzed by measuring the signal intensity decay curve and fitting it into a double exponential model. The fast decay component (time constant less than 10 ms) corresponds to the low crosslinking degree region, and the slow decay component (time constant greater than 30 ms) corresponds to the high crosslinking degree region. By calculating the proportion of fast and slow components, the crosslinking degree of each region is quantified. For crosslinked polyethylene (XLPE) used in high-speed transmission cables, the crosslinking degree is usually required to reach 65%-90% to ensure sufficient heat distortion temperature and mechanical strength. Finally, crosslinking degree distribution data is generated and presented in the form of a heat map. This crosslinking degree analysis method based on signal attenuation characteristics can achieve non-destructive and high spatial resolution crosslinking degree measurement, providing a powerful tool for insulation layer uniformity evaluation.

[0050] The phase-sensitive detection technique is used for correlation analysis of the crosslinking degree distribution data and the regional characteristic distribution data. A phase-sensitive amplifier is used to perform phase-locked detection on signals from different regions, and the phase difference of the signal relative to the reference signal is calculated. In insulating materials, residual stress can cause changes in molecular chain orientation, which in turn affects signal propagation speed and phase. By establishing a mapping relationship between phase difference and residual stress, the residual stress value of each region is quantified. For high-speed transmission cables, a change of 1° in phase difference corresponds to a change of 0.5 MPa-1.0 MPa in residual stress. To improve measurement accuracy, multi-band detection (1 kHz, 10 kHz, 100 kHz) is used to integrate phase difference information at different frequencies. Taking polyethylene insulation as an example, the phase difference change in normal regions is usually less than ±5°, while the stress concentration region can reach ±15° or more. Finally, residual stress distribution data is generated and presented in the form of a vector field to show the size and direction of the stress. This stress measurement method based on phase analysis provides an effective supplement to traditional polarized light microscopy, and can obtain internal stress distribution information without damaging the sample, which is of great significance for predicting the performance stability of high-speed transmission cables in bending and vibration environments.

[0051] The physical and chemical state of the surface of the insulating layer is comprehensively analyzed according to the crystallinity distribution data, the crosslinking degree distribution data and the residual stress distribution data, and a machine learning method is used. A multilayer perception neural network model is established, the feature parameters of the above three distribution data are included in the input layer, a three-layer structure (the node numbers are 128, 64 and 32 respectively) is used in the hidden layer, and the output layer gives the key performance indicators of the insulating layer: dielectric strength, volume resistivity, dielectric loss tangent and heat distortion temperature and the like. The neural network is trained using 10,000 sets of historical data, and the verification accuracy is more than 95%. Through the model, the micro-distribution data is converted into physical parameters directly reflecting the performance of the cable, and a micro-physical and chemical characteristic parameter table of the insulating layer is generated. This data-driven comprehensive analysis method breaks through the limitations of traditional single parameter evaluation, establishes a quantitative relationship between the microstructure and the macro performance, provides a new theoretical basis and technical means for the precise design and quality control of high-speed transmission cables, and significantly improves the performance stability and consistency of the cable in the high-frequency application environment.

[0052] In an embodiment of the present application, after obtaining the micro-physical and chemical characteristic parameters of the insulating layer, the detection method of the high-speed cable comprises: According to the crystallinity distribution, the crosslinking degree distribution and the residual stress distribution in the micro-physical and chemical characteristic parameters of the insulating layer, a bifunctional molecule is structurally designed, a detection domain, a modification domain and an intelligent response segment are constructed in the bifunctional molecule, a fluorescence group responding to an electric field is introduced into the detection domain, a functional group changing the surface characteristics of the cable is introduced into the modification domain, the intelligent response segment connects the detection domain and the modification domain, and bifunctional molecule structure data is obtained; According to the bifunctional molecule structure data, the density distribution of the bifunctional molecule on the surface of the insulating layer is regulated, the concentration of the bifunctional molecule is controlled in the range of 0.01 mg / ml-0.5 mg / ml, and the temperature is adjusted in the range of 20℃-50℃, and a bifunctional molecule assembly layer is formed through the conformation change of the intelligent response segment; The bifunctional molecule assembly layer is crosslinked, the bifunctional molecule assembly layer and the insulating material form an interpenetrating network structure through the conformation change of the intelligent response segment, the thickness of the interpenetrating network structure is controlled, and molecular network structure data is obtained; According to the molecular network structure data, the interpenetrating network structure is subjected to light irradiation, heating or chemical treatment, the intelligent response segment is fixed to the network structure, a stable network structure is formed, surface modification structure data is obtained.

[0053] The following specifically describes the steps involved in the above embodiment: According to the micro-physical and chemical characteristics of the insulating layer, the structure of the bifunctional molecule is designed. The computer-aided molecular design platform is used for operation. The design is based on the three-domain structure principle, and the detection domain, modification domain and intelligent response segment are constructed respectively. The detection domain is the part of the molecule responsible for signal response. Different fluorescent groups are selected for different crystallinity regions: naphthalimide fluorescent groups are introduced for high crystallinity regions (> 75%), coumarin fluorescent groups are introduced for medium crystallinity regions (50%-75%), and rhodamine fluorescent groups are introduced for low crystallinity regions (< 50%). These fluorescent groups have the characteristics of responding to electric field and can change the fluorescence emission characteristics under the action of local electric field. The modification domain is the part of the molecule responsible for adjusting the surface characteristics of the insulating layer. Different functional groups are selected according to the crosslinking degree distribution: allyl-containing siloxane groups are introduced for high crosslinking degree regions (> 80%), epoxy-containing polyether groups are introduced for medium crosslinking degree regions (65%-80%), and hydroxyl-containing polyester groups are introduced for low crosslinking degree regions (< 65%). The intelligent response segment is the intermediate part connecting the detection domain and the modification domain. Different structures are selected according to the residual stress distribution: flexible polyethylene glycol segments are used for high stress regions (> 5 MPa), semi-rigid polystyrene segments are used for medium stress regions (2 MPa-5 MPa), and rigid polyaromatic segments are used for low stress regions (< 2 MPa). The molecular configuration optimized by quantum chemistry calculation software is used to generate bifunctional molecule structure data containing three-dimensional structure, electronic distribution and energy parameters of the molecule. This differential molecular design strategy based on the micro characteristics of the insulating layer significantly improves the targeting and effectiveness of the modification, and solves the limitations of traditional single molecular structure that is difficult to adapt to complex surface characteristics.

[0054] The density distribution of the bifunctional molecules on the surface of the insulating layer is regulated according to the structure data of the bifunctional molecules. A precision solution spraying system is used. The system is equipped with high-precision flow control devices and multi-zone temperature adjustment modules, which can automatically adjust parameters according to the needs of different regions. For regions with high crystallinity and high stress, high-concentration (0.3 mg / ml-0.5 mg / ml) bifunctional molecule solution is used and treated at a higher temperature (40°C-50°C) to promote the full penetration of the molecules; for regions with medium crystallinity and medium stress, medium-concentration (0.1 mg / ml-0.2 mg / ml) solution is used and treated at a medium temperature (30°C-40°C); for regions with low crystallinity and low stress, low-concentration (0.01 mg / ml-0.05 mg / ml) solution is used and treated at a lower temperature (20°C-30°C). The solution spraying process is controlled by a computer, the spraying rate is 5 ml / min-10 ml / min, and the spraying distance is kept at 10 cm-15 cm. After the bifunctional molecules are attached to the surface of the insulating layer, the conformational change of the intelligent response segment is triggered by changing the environmental pH value (from pH 5.5 to pH 8.5) or applying a weak electric field (0.1 V / μm-0.3 V / μm), so that the detection domain is exposed outward and the modified domain is combined with the surface, forming a bifunctional molecule assembly layer with a thickness of 50 nm-200 nm. This precise control of concentration and temperature parameters ensures the optimal distribution of bifunctional molecules in different characteristic regions, laying a material foundation for subsequent directional modification.

[0055] When crosslinking the bifunctional molecule assembly layer, a multi-step gradient crosslinking technique is used. First, the assembly layer is irradiated using a UV light crosslinking device, with a wavelength of 365 nm and a power density of 5-10 mW / cm2for 30-60 seconds. The UV irradiation triggers a conformational change in the photoresponsive groups in the smart response segment, promoting the formation of initial crosslinks between the bifunctional molecules. Then, a specific crosslinking agent is introduced into the system: for polyethylene-based insulation materials, benzoyl peroxide (BPO) is used; for fluoropolymers, azobisisobutyronitrile (AIBN) is used; and for crosslinked polymers, diisocyanate (HDI) is used. The concentration of the crosslinking agent is controlled within the range of 0.5-2.0%, and the reaction temperature is controlled within the range of 60-80°C, with a reaction time of 5-15 minutes. This process forms an interpenetrating network structure between the bifunctional molecule assembly layer and the insulation material, i.e., a three-dimensional structure in which the molecular network and the insulation material interpenetrate and entangle at the molecular scale. The interpenetrating network structure is monitored in real time using a laser confocal microscope to control the thickness distribution in different regions: 100-150 nm for high crystallinity regions, 70-100 nm for medium crystallinity regions, and 30-70 nm for low crystallinity regions. After crosslinking is complete, the crosslinking density and chemical composition are analyzed using X-ray photoelectron spectroscopy (XPS) to generate molecular network structure data. This gradient crosslinking process ensures strong bonding between the modified layer and the insulation material while maintaining sufficient flexibility, avoiding the risk of peeling when the cable is bent.

[0056] When stabilizing the interpenetrating network structure based on the molecular network structure data, a multi-mode curing system is used. This system selects the most suitable stabilization method for different regions based on their network structure characteristics: for regions with high crosslinking density, UV light treatment is used with an intensity of 15-20 mW / cm2for 2-5 minutes; for regions with highly ordered molecular arrangement, heating treatment is used at a temperature of 90-120°C for 10-30 minutes; and for regions rich in special functional groups, chemical treatment is used by soaking in a 0.1-1.0% glutaraldehyde or glutaraldehyde solution for 1-5 minutes. These treatment methods activate the reaction sites in the smart response segment through photo-crosslinking, thermal curing, and chemical crosslinking mechanisms, respectively, forming a stable covalent bond network. After stabilization is complete, the surface morphology and wettability are characterized using atomic force microscopy (AFM) and a contact angle meter to generate surface modification structure data. This multi-mode stabilization method adopts differentiated curing strategies for different regions, ensuring the long-term stability of the modified layer (stable for more than 5000 hours at 80°C) while avoiding the increase in brittleness that may result from excessive crosslinking, ensuring the reliability and service life of high-speed transmission cables in complex environments.

[0057] In one embodiment of the present application, the double functional molecular assembly layer is cross-linked, the double functional molecular assembly layer and the insulating material form an interpenetrating network structure by using the conformational change of the smart response segment, the thickness of the interpenetrating network structure is controlled, and molecular network structure data is obtained, including: The double functional molecular assembly layer is deeply analyzed, the conformational change range of the smart response segment is calculated according to the network void size of the insulating material, and conformational regulation parameters are obtained; The conformational change of the smart response segment is adjusted according to the conformational regulation parameters, the stretching degree of the smart response segment is controlled in the interval of pH value 4.0-5.5, the interval of pH value 6.0-7.5 and the interval of pH value 8.0-9.5, and different depth molecular penetration layers are formed; The thickness of the molecular penetration layer is controlled in three depth intervals of 20nm-45nm, 55nm-90nm and 100nm-140nm, respectively, and the cross-linking density is regulated. Cross-linking points are formed in each depth interval by ultraviolet light irradiation, temperature adjustment or chemical reagent treatment, an interpenetrating network structure with gradient structure is constructed, and molecular network structure data is obtained.

[0058] The following describes the steps involved in the above embodiment in detail: The double functional molecular assembly layer is deeply analyzed by using a multi-technology combined strategy. First, the surface morphology of the assembly layer is imaged by atomic force microscope (AFM) to accurately measure the surface roughness and uniformity. Then, a cross-section sample is prepared using scanning electron microscope (SEM) combined with focused ion beam (FIB) to observe the internal structure of the assembly layer. Small-angle X-ray scattering (SAXS) is used to measure the network void size distribution of the insulating material. For polyethylene-based insulating materials, the void size mainly distributes in 3nm-8nm; for cross-linked polyethylene, the void size distributes in 5nm-12nm; and for fluoropolymer, the void size distributes in 2nm-6nm. After obtaining these data, the conformational change range of the smart response segment under different environmental conditions is calculated by molecular dynamics simulation software. The smart response segment refers to the middle part connecting the detection domain and the modification domain in the double functional molecule, which has the characteristic of responding to external stimuli such as pH value, temperature, electric field, etc. In the simulation calculation, factors such as flexibility, charge distribution, hydrogen bond formation ability and hydrophobicity of the molecular chain are considered, and 100,000 step simulation trajectories are statistically analyzed to obtain parameters such as maximum stretching length, conformational space and energy surface of the smart response segment under different conditions, forming a set of conformational regulation parameters. This deep analysis method realizes the quantitative prediction of molecular conformational change by accurate measurement and calculation, providing a theoretical basis for subsequent precise penetration control and greatly improving the controllability and repeatability of the modification process.

[0059] A pH gradient control system was used to adjust the conformational change of the smart responsive segments according to the conformational regulation parameters. The system was composed of a precise pH controller, a peristaltic pump and a microfluidic channel, which could form a stable pH gradient on the surface of the wire. According to the characteristics of different insulating materials, different pH intervals were set: for the smart responsive segments containing carboxyl groups, the treatment was carried out in the interval of pH 4.0-5.5, at which the segments were in a compact conformation, the stretching degree was 20%-30% of the maximum length, and it was suitable for small void size (2nm-4nm) regions; for the smart responsive segments containing amino groups, the treatment was carried out in the interval of pH 6.0-7.5, at which the segments were in a semi-stretched conformation, the stretching degree was 50%-70% of the maximum length, and it was suitable for medium void size (5nm-8nm) regions; for the smart responsive segments containing hydroxyl groups and ether bonds, the treatment was carried out in the interval of pH 8.0-9.5, at which the segments were in a fully stretched conformation, the stretching degree was 85%-95% of the maximum length, and it was suitable for large void size (9nm-12nm) regions. The precise control of pH value was realized through the online pH electrode and the feedback control system, and the control accuracy was ±0.1 pH unit. The treatment time was adjusted according to the density and crystallinity of the insulating material, usually 5-20 minutes. This process was carried out at room temperature (25℃±2℃) to avoid the interference of temperature factors on the conformation. Through this precise pH gradient control, molecular penetration layers with different penetration depths were formed, realizing the precise targeted modification of different network void regions. This modification method based on the conformational regulation of smart responsive segments significantly improved the modification efficiency, avoiding the problems of excessive aggregation or inability to penetrate in traditional methods.

[0060] The thickness of the molecular permeable layer is controlled in three regions. First, the molecular permeable layer is monitored in real time using a confocal fluorescence microscope, and the molecular distribution at different depths is determined by Z-axis scanning. In the 20-45 nm depth range (surface layer), cross-linking is mainly performed using ultraviolet irradiation. The wavelength of the ultraviolet light is 365 nm, the intensity is 10-15 mW / cm², and the irradiation time is 30-60 seconds. The cross-linking density in this range is controlled at 15-25%, forming a relatively loose network structure that mainly improves the surface dielectric properties. In the 55-90 nm depth range (middle layer), cross-linking is mainly performed using temperature regulation. The temperature is controlled at 70-90°C, and the treatment time is 3-8 minutes. The cross-linking density in this range is controlled at 40-60%, forming a moderately dense network structure that mainly enhances mechanical strength and environmental resistance. In the 100-140 nm depth range (bottom layer), cross-linking is mainly performed using chemical reagent treatment. Cross-linking agents such as glutaraldehyde and polyisocyanate are used at a concentration of 0.5-2.0% for 10-20 minutes. The cross-linking density in this range is controlled at 80-95%, forming a highly dense network structure that mainly enhances the adhesion to the substrate. The division of the three depth ranges is based on the electric field distribution characteristics of the high-speed transmission cable insulation layer. The 20-45 nm range mainly affects the distribution of high-frequency surface currents, the 55-90 nm range affects the transmission characteristics of medium-frequency signals, and the 100-140 nm range affects the long-term stability and reliability of the cable. The cross-linked samples are characterized using a UV-Vis spectrometer, an infrared spectrometer, and a differential scanning calorimeter to obtain molecular network structure data including cross-linking density distribution, chemical bond type, and thermal stability. This gradient cross-linking structure design fully considers the electromagnetic field distribution of high-speed transmission cables at different frequencies, and by precisely controlling the network structure characteristics at different depths, the electrical performance of the cable is optimized comprehensively.

[0061] In one embodiment of the present application, after obtaining the surface modification structure data, the detection method of the high-speed cable includes: preliminary analysis of the surface modification structure data, generating entangled photon pairs according to the analysis results, and controlling the wavelength and polarization state of the entangled photon pairs to obtain quantum entangled state data; controlling the polarization state and wave vector of the probe photons according to the quantum entangled state data, scanning and analyzing the stabilized network structure to obtain three-dimensional distribution data of dielectric constant, molecular orientation, and charge distribution; quantum state purification processing of the three-dimensional distribution data, obtaining modification layer structure parameter data by calculating the quantum state parameters of different depth regions in the stabilized network structure; According to the modification layer structure parameter data, the impedance consistency, dielectric loss and shielding effectiveness of the stabilized network structure are quantum state evaluated, performance index data is generated, and the performance index data is fed back to the bifunctional molecule structure design step to optimize the structure of the bifunctional molecule.

[0062] The following is a specific description of the steps involved in the above embodiments: The surface modification structure data is preliminarily analyzed using data mining technology. First, the high-dimensional surface modification structure data is mapped to a low-dimensional feature space through principal component analysis (PCA) dimension reduction processing to extract key feature parameters. Then, a clustering algorithm is used to identify the main patterns and abnormal areas in the data. Based on the analysis results, a parametric down-conversion method is used to generate entangled photon pairs. This method uses a periodically poled lithium niobate crystal (PPLN) as a nonlinear medium. A laser with a wavelength of 405 nm is passed through the PPLN crystal to generate entangled photon pairs with a wavelength of 810 nm. Entangled photon pairs refer to a pair of quantum entangled states of photons, which cannot be described individually and need to be considered as a whole. According to the characteristics of different regions of the surface modification structure, the parameters of the entangled photon pairs are adjusted: for high dielectric constant regions (ε>3.0), vertical polarization state entangled photon pairs are generated; for medium dielectric constant regions (2.0<ε<3.0), diagonal polarization state entangled photon pairs are generated; for low dielectric constant regions (ε<2.0), horizontal polarization state entangled photon pairs are generated. Quantum state tomography technology is used to characterize the entangled photon pairs and measure their entanglement degree, purity and coherence time, etc. to generate quantum entangled state data. This method of generating customized quantum entangled states based on material characteristics achieves ultra-high sensitivity detection of the modification effect of the insulating layer, with a detection precision improved by an order of magnitude compared to traditional methods.

[0063] The polarization state and wave vector of the probe photon are controlled according to the quantum entangled state data, and a quantum state regulation system is adopted. The system includes a polarization state controller, a phase modulator and a wave vector direction controller. The polarization state controller is realized by a liquid crystal adjustable wave plate, which can accurately adjust the linear polarization angle (0°-180°) and the elliptical polarization rate (0-1) of the probe photon. The phase modulator is realized by an electro-optic crystal, which controls the phase delay (0-2π). The wave vector direction controller is realized by a precision mirror group, which controls the incident angle (0°-60°) and the azimuth angle (0°-360°). The system sets the optimal probe photon parameters for each region to be measured according to the correlation parameters in the quantum entangled state data. The scanning process adopts photon counting imaging technology, and a superconducting single-photon detector array is used to realize high-sensitivity detection. The scanning step is set to 50-100 nm, covering the 360° panorama of the cable surface, and the depth resolution is 10-20 nm. The number of scattered photons, interference patterns and phase information of each spatial point are recorded during the measurement process, and the dielectric constant, molecular orientation angle and charge density of the corresponding point are calculated by quantum inversion algorithm to generate three-dimensional distribution data. This scanning and analysis method based on quantum entanglement fully utilizes the quantum non-locality, overcomes the diffraction limit of traditional optical methods, and realizes the non-destructive detection of nano-scale structure characteristics.

[0064] When the three-dimensional distribution data is purified by quantum state, a quantum information processing algorithm is adopted. First, the original data is filtered by quantum noise, and the quantum fluctuations and environmental disturbances in the measurement process are removed by maximum likelihood estimation. Then, the data of different depth regions are reconstructed by quantum state respectively: the surface layer (0-50 nm) adopts the maximum entropy method, the middle layer (50-100 nm) adopts the iterative phase recovery method, and the deep layer (100-150 nm) adopts the quantum Bayesian inference method. The quantum state parameters include quantum coherence length, quantum state purity and quantum correlation strength, which correspond to the molecular order degree, component uniformity and interface bonding strength of the material respectively. For the cross-linked polyethylene insulation layer commonly used in high-speed transmission cables, the quantum state parameters of each spatial point are calculated, and the parameter space distribution map is drawn. By setting a threshold, the excellent performance area and potential defect area are screened out, and the modified layer structure parameter data is generated. This quantum state purification processing method greatly improves the data quality and reliability, enabling the system to detect small structural changes that are difficult to detect by traditional methods, and providing key technical support for accurate evaluation of insulation layer modification effect.

[0065] A quantum electrodynamics model is used to evaluate the quantum state of the stabilized network structure based on the structural parameter data of the modified layer. This model treats the modified layer as a medium in a quantized electromagnetic field and calculates the propagation characteristics of electromagnetic waves in the medium by solving quantum field equations. Three key performance indicators are evaluated: impedance consistency (calculating the characteristic impedance deviation between different regions; high-performance cables require the deviation to be within ±2Ω); dielectric loss (calculating the dissipation coefficient of electromagnetic energy in the medium; high-speed transmission requires a loss tangent less than 0.001); and shielding effectiveness (calculating the attenuation coefficient of external electromagnetic fields; ideally, a value greater than 60dB). The evaluation results are generated into performance indicator data, including a spatial distribution diagram and statistical analysis report. The system feeds this data into the bifunctional molecular structure design step through a closed-loop control mechanism, enabling targeted optimization of the molecular structure: adjusting the proportion of polar groups in regions with inconsistent impedance; reducing the presence of molecules with dipole moments in regions with excessive loss; and increasing the content of conductive components in regions with insufficient shielding. This closed-loop optimization method based on quantum state evaluation achieves precise control of the modification process, significantly improving the electrical performance consistency and signal integrity of high-speed transmission cables, and meeting the stringent requirements of high-end applications such as 5G communications and data centers.

[0066] The above describes the first embodiment of the present invention. The following describes the detection device for high-speed cables according to the embodiment of the present invention. Figure 2 An embodiment of a high-speed cable detection device according to an embodiment of the present invention includes: The molecular field control module 101 is used to introduce a molecular field control agent to the surface of the cable's insulation layer. The molecular field control agent includes a hydrophobic segment, a polar head group, and a bridging group. The molecular field control agent interacts with the surface of the insulation layer to form an orderly arranged molecular layer structure. Based on the differences in the microscopic characteristics of the insulation layer surface, local electric fields of different intensities are generated in different areas to obtain dielectric constant distribution data. A hybrid probe detection module 102 is configured to control the interaction between the hybrid probe formed by the quantum dots and the organic fluorescent molecules and the surface of the insulating layer based on the dielectric constant distribution data, detect changes in the electron cloud distribution generated by the hybrid probe under the action of the local electric field, perform multi-parameter detection on the hybrid probe, and obtain probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data; The signal processing and feature extraction module 103 is used to import the probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data into the critical state calculation framework, calculate the signal entropy value, correlation degree, and fluctuation amplitude parameters in the phase space, use a recursive partitioning algorithm to divide the cable surface into regions, and extract signal features at multiple characteristic scales through wavelet transform and fractal analysis to obtain microstructural distribution data on the surface and near-surface areas of the insulation layer; The micro-characterization module 104 is configured to characterize the crystallinity distribution, cross-linking distribution and residual stress distribution of the insulating layer surface according to the dielectric constant distribution data and the microstructure distribution data, and obtain the micro-physical and chemical characteristic parameters of the insulating layer.

[0067] The above Figure 2 The detection device for the high-speed cable in the embodiment of the application is described in detail from the perspective of the modular functional entity, and the detection device for the high-speed cable in the embodiment of the application is described in detail from the perspective of hardware processing.

[0068] Figure 3 The detection device for the high-speed cable 200 can have great differences due to different configurations or performances, and can include one or more processors 210 (for example, one or more processors) and a memory 220, one or more storage media 230 (for example, one or more mass storage device ends) storing application programs 233 or data 232. The memory 220 and the storage media 230 can be temporary storage or persistent storage. The programs stored in the storage media 230 can include one or more modules (not shown in the figure), and each module can include a series of instruction operations in the detection device for the high-speed cable 200. Further, the processor 210 can be configured to communicate with the storage media 230, execute a series of instruction operations in the storage media 230 on the detection device for the high-speed cable 200, so as to implement the steps of the above subject one.

[0069] The detection device for the high-speed cable 200 can also include one or more power supplies 240, one or more wired or wireless network interfaces 250, one or more input and output interfaces 260, and / or one or more operating systems 231, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art can understand that Figure 3 The structure of the detection device for the high-speed cable shown in the figure does not constitute a limitation on the detection device for the high-speed cable provided by the application, and can include more or fewer components than those shown in the figure, or combine certain components, or different component arrangements.

[0070] The application also provides a computer readable storage medium, which can be a non-volatile computer readable storage medium, and can also be a volatile computer readable storage medium. The computer readable storage medium has instructions stored therein, and when the instructions are run on a computer, the computer executes the steps of the above subject one.

[0071] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system or device, unit described above can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0072] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0073] The above only describes the preferred embodiments of the present application, and does not limit the patent scope of the present application. Any equivalent structural transformation made by using the content of the present application specification and drawings, or direct / indirect application in other related technical fields is included in the patent protection scope of the present application.

Claims

1. A method for detecting a high-speed cable, characterized in that: include: A molecular field modulator is introduced onto the surface of the cable's insulation layer. The molecular field modulator comprises a hydrophobic segment, a polar head group, and a bridging group. The molecular field modulator interacts with the surface of the insulation layer to form an ordered molecular layer structure. Based on the differences in the microscopic properties of the insulation layer surface, local electric fields of varying strengths are generated in different regions to obtain dielectric constant distribution data. Controlling the interaction between a hybrid probe formed by quantum dots and organic fluorescent molecules and the surface of the insulating layer based on the dielectric constant distribution data, detecting changes in the electron cloud distribution generated by the hybrid probe under the action of a local electric field, and performing multi-parameter detection on the hybrid probe to obtain probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data; The probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data are imported into a critical state calculation framework to calculate the signal entropy, correlation, and fluctuation amplitude parameters in phase space. A recursive partitioning algorithm is used to divide the cable surface into regions. Signal features are extracted at multiple characteristic scales through wavelet transform and fractal analysis to obtain microstructural distribution data on the surface and near-surface areas of the insulation layer. The crystallinity distribution, cross-linking degree distribution and residual stress distribution of the surface of the insulating layer are characterized according to the dielectric constant distribution data and the microstructure distribution data to obtain microscopic physical and chemical characteristic parameters of the insulating layer.

2. The high-speed cable detection method according to claim 1, characterized in that: The invention introduces a molecular field modulator into the surface of the insulation layer of the cable, wherein the molecular field modulator comprises a hydrophobic segment, a polar head group and a bridging group. The molecular field modulator interacts with the surface of the insulation layer to form an orderly arranged molecular layer structure. Local electric fields of different intensities are generated in different regions according to differences in microscopic properties of the surface of the insulation layer, and dielectric constant distribution data is obtained, including: Identify the material type of the insulation layer surface of the cable and introduce corresponding molecular field modulators to the insulation layer surface according to the material type, specifically introducing phospholipid molecules containing long-chain alkyl groups for polyethylene materials, introducing zwitterionic molecules containing fluorinated segments for fluoropolymers, and introducing molecules containing flexible side chains for cross-linked polymers to obtain molecular field modulator type data; According to the molecular field modulator type data, the molecular field modulator is subjected to a temperature gradient treatment, wherein the temperature is lowered within a temperature range of 25°C to 40°C at a rate of 0.5°C / minute, while an alternating current electric field with a frequency of 10 Hz to 50 Hz and an intensity of 0.1 V / μm to 0.5 V / μm is applied to form an ordered molecular layer structure; The electric field distribution of the ordered molecular layer structure is detected, and the intensity and direction parameters of the local electric field are calculated according to the arrangement rules of the ordered molecular layer structure in different areas on the surface of the insulating layer to obtain dielectric constant distribution data.

3. The high-speed cable detection method according to claim 1, characterized in that: The method comprises regulating the interaction between the hybrid probe formed by the quantum dots and the organic fluorescent molecules and the surface of the insulating layer according to the dielectric constant distribution data, detecting the change in the electron cloud distribution generated by the hybrid probe under the action of the local electric field, performing multi-parameter detection on the hybrid probe, and obtaining probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data, including: CdSe / ZnS core-shell quantum dots were composited with organic fluorescent molecules containing a D-π-A structure, and the surface of the quantum dots was coated with a ZnS shell layer, a PEG polymer layer, and an amphiphilic copolymer layer to form a hybrid probe. regulating the concentration and temperature of the hybrid probe according to the dielectric constant distribution data, forming a probe distribution layer on the surface of the insulating layer, detecting changes in the electron cloud distribution of the hybrid probe in the probe distribution layer, and obtaining quantum coherence time data; performing optical excitation processing on the probe distribution layer according to the quantum coherence time data, detecting the energy transfer efficiency between the hybrid probe and the cable surface, and obtaining probe-surface interaction data; The probe-surface interaction data are subjected to multi-parameter analysis, and probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are synchronously collected and calculated.

4. The high-speed cable detection method according to claim 1, wherein: The probe fluorescence intensity, fluorescence lifetime, polarization degree and spectral shift data are imported into the critical state calculation framework, the signal entropy value, correlation degree and fluctuation amplitude parameters are calculated in the phase space, the cable surface is divided into regions using a recursive partitioning algorithm, and signal features are extracted at multiple characteristic scales through wavelet transform and fractal analysis to obtain microstructure distribution data on the surface and near-surface area of ​​the insulation layer, including: Performing data normalization on the probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data, mapping the normalized data to phase space, calculating the signal entropy value, correlation, and fluctuation amplitude parameters through a rolling time window, and obtaining a critical state parameter distribution diagram; Dividing the cable surface into multiple regions using a recursive partitioning algorithm according to the critical state parameter distribution diagram, calculating the signal statistical characteristics of each region, and obtaining regional distribution characteristic data; Inputting the regional distribution characteristic data into a wavelet transform processing unit, performing signal decomposition at three characteristic scales greater than 10 μm, 2 μm-10 μm, and less than 2 μm, to obtain multi-scale signal component data; Fractal analysis is performed on the multi-scale signal component data, and Lyapunov exponents and recursion graph parameters are calculated to obtain microstructure distribution data of the surface and near-surface area of ​​the insulation layer.

5. The high-speed cable detection method according to claim 1, characterized in that: The characterization of the crystallinity distribution, crosslinking degree distribution, and residual stress distribution on the surface of the insulating layer according to the dielectric constant distribution data and the microstructure distribution data to obtain microscopic physical and chemical characteristic parameters of the insulating layer includes: Performing data fusion processing on the dielectric constant distribution data and the microstructure distribution data to establish a spatial distribution map of the insulating layer surface, and performing data partitioning processing based on the signal fluctuation law of the local area in the spatial distribution map of the insulating layer surface to obtain regional characteristic distribution data; Performing spectrum analysis on the signal intensity changes in the regional characteristic distribution data, distinguishing the crystalline phase from the amorphous phase according to the signal spectrum peak positions and peak shape parameters of different regions, and obtaining crystallinity distribution data; performing deconvolution processing on the regional characteristic distribution data according to the crystallinity distribution data, separating the crystallization region signal, analyzing the attenuation characteristics of the signal, and obtaining crosslinking degree distribution data; Correlation analysis is performed on the cross-linking degree distribution data and the regional characteristic distribution data, and phase differences of signals in different regions are calculated to obtain residual stress distribution data; The physical and chemical state of the surface of the insulating layer is comprehensively analyzed according to the crystallinity distribution data, the crosslinking degree distribution data and the residual stress distribution data to obtain microscopic physical and chemical characteristic parameters of the insulating layer.

6. The high-speed cable detection method according to claim 1, characterized in that: After obtaining the microscopic physical and chemical characteristic parameters of the insulation layer, the high-speed cable detection method includes: The bifunctional molecule is structurally designed based on the crystallinity distribution, crosslinking degree distribution, and residual stress distribution of the microscopic physicochemical characteristic parameters of the insulating layer, and a detection domain, a modification domain, and an intelligent response segment are constructed in the bifunctional molecule. A fluorescent group that responds to an electric field is introduced into the detection domain, and a functional group that changes the surface properties of the cable is introduced into the modification domain. The intelligent response segment connects the detection domain and the modification domain to obtain bifunctional molecule structural data; Regulating the density distribution of the bifunctional molecules on the surface of the insulating layer according to the bifunctional molecular structure data, controlling the concentration of the bifunctional molecules within a concentration range of 0.01 mg / ml-0.5 mg / ml, and regulating the temperature within a temperature range of 20° C.-50° C., and forming a bifunctional molecular assembly layer through conformational changes of the smart response segments; Cross-linking the bifunctional molecular assembly layer, forming an interpenetrating network structure between the bifunctional molecular assembly layer and the insulating material using the conformational change of the smart response segment, controlling the thickness of the interpenetrating network structure, and obtaining molecular network structure data; The interpenetrating network structure is subjected to illumination, heating or chemical treatment according to the molecular network structure data, and the network structure is fixed by the intelligent response chain segment to form a stabilized network structure, thereby obtaining surface modification structure data.

7. The high-speed cable detection method according to claim 6, characterized in that: After obtaining the surface modification structure data, the high-speed cable detection method includes: Performing a preliminary analysis on the surface modification structure data, generating entangled photon pairs based on the analysis results, and regulating the wavelength and polarization state of the entangled photon pairs to obtain quantum entangled state data; Controlling the polarization state and wave vector of the detection photon according to the quantum entangled state data, scanning and analyzing the stabilized network structure to obtain three-dimensional distribution data of dielectric constant, molecular orientation and charge distribution; Performing quantum state purification on the three-dimensional distribution data, and obtaining modified layer structure parameter data by calculating quantum state parameters of regions at different depths in the stabilized network structure; The impedance consistency, dielectric loss and shielding effectiveness of the stabilized network structure are evaluated in quantum states based on the modified layer structure parameter data to generate performance index data, which are fed back to the bifunctional molecular structure design step to optimize the structure of the bifunctional molecule.

8. A high-speed cable detection device, characterized in that: The high-speed cable detection device adopts the high-speed cable detection method according to any one of claims 1 to 7, and the high-speed cable detection device includes: A molecular field control module is used to introduce a molecular field control agent to the surface of the cable's insulation layer. The molecular field control agent includes a hydrophobic segment, a polar head group, and a bridging group. The molecular field control agent interacts with the surface of the insulation layer to form an orderly arranged molecular layer structure. Based on the differences in the microscopic characteristics of the insulation layer surface, local electric fields of different intensities are generated in different areas to obtain dielectric constant distribution data. a hybrid probe detection module, configured to control the interaction between the hybrid probe formed by the quantum dots and the organic fluorescent molecules and the surface of the insulating layer according to the dielectric constant distribution data, detect changes in the electron cloud distribution generated by the hybrid probe under the action of the local electric field, perform multi-parameter detection on the hybrid probe, and obtain probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data; A signal processing and feature extraction module is used to import the probe fluorescence intensity, fluorescence lifetime, polarization degree, and spectral shift data into the critical state calculation framework, calculate the signal entropy, correlation, and fluctuation amplitude parameters in the phase space, use a recursive partitioning algorithm to divide the cable surface into regions, and extract signal features at multiple characteristic scales through wavelet transform and fractal analysis to obtain microstructural distribution data on the surface and near-surface areas of the insulation layer; The microscopic characteristic characterization module is used to characterize the crystallinity distribution, crosslinking degree distribution and residual stress distribution of the surface of the insulating layer according to the dielectric constant distribution data and the microstructure distribution data, and obtain the microscopic physical and chemical characteristic parameters of the insulating layer.

9. A high-speed cable detection device, characterized in that: The high-speed cable detection device includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor calls the instructions in the memory to enable the high-speed cable detection device to perform the steps of the high-speed cable detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by a processor, the steps of the high-speed cable detection method according to any one of claims 1 to 7 are implemented.

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