Cable intermediate joint temperature measurement method and system based on thermomagnetic noise signal

Abstract

The invention discloses a cable intermediate joint temperature measurement method and system based on a thermomagnetic noise signal, relates to the field of cable joint temperature measurement, and aims to solve the problem that the precision and stability of an existing temperature measurement method in a complex environment are affected by external factors and are easy to cause measurement errors. The method comprises the following steps: acquiring material information and physical size of a cable joint shielding layer; establishing a relation model of the thermomagnetic noise intensity level and the temperature; two magnetometers are used for measuring and obtaining magnetic field intensity signals B1 and B2 at the center of the shielding layer; obtaining the signal intensity of the thermomagnetic noise at the center; and calculating the temperature under the corresponding thermomagnetic noise signal intensity according to the obtained thermomagnetic noise signal intensity and a model, and obtaining the temperature data T of the cable joint. Compared with a traditional measurement method, the technical scheme has the advantages of being high in precision, insensitive to environmental change influences and suitable for scenes needing long-term stable operation.

Description

Technical Field

[0001] The invention relates to the field of cable joint temperature measurement, and in particular to a cable intermediate joint temperature measurement method based on thermal magnetic noise signals. Background Art

[0002] As an important power transmission facility connecting the power grid, cables are vital to the energy supply of modern society. The cable intermediate joint is a key device connecting two cables. When the intermediate joint is improperly installed or the insulation layer is aged, it often causes serious discharge, accompanied by a sharp rise in temperature. If these problems are not discovered and handled in time, more serious fire accidents may occur, causing immeasurable losses. Therefore, monitoring the temperature of the cable intermediate joint is of great significance to ensure the safe and stable operation of the cable.

[0003] Patent CN202010485226.0 discloses an intelligent cable intermediate joint temperature measurement system, in which a temperature measurement device is fixedly bonded to the outer surface of the aluminum heat dissipation layer. The temperature sensor used is a surface acoustic wave (SAW) temperature sensor, which has the advantages of high accuracy and no need for external power supply. However, this sensor is easily affected by external physical factors such as pressure and humidity, resulting in reduced measurement accuracy and stability.

[0004] Utility model patent CN202220468635.4 proposes a cable intermediate joint temperature measurement device based on a multi-core photonic crystal infrared temperature sensor. In this device, multiple multi-core photonic crystal temperature sensors are placed in each layer inside the cable intermediate joint, and multiple sensors are also installed in the outer layer. This dot matrix distribution layout is designed to comprehensively and accurately monitor the temperature distribution on the outer surface of the cable intermediate joint while using as few sensors as possible. However, this temperature measurement method has shortcomings in long-term use, such as the sensitivity of the multi-core photonic crystal sensor may decrease and the measurement error may increase, which limits its application in long-term stable operation scenarios. In addition, in certain extreme environments (such as high temperature, high pressure, strong magnetic field, etc.), the performance of the multi-core photonic crystal sensor will also be significantly affected. Summary of the invention

[0005] The technical problem to be solved and the technical task proposed by the present invention are to improve and perfect the existing technical solutions, and provide a cable intermediate joint temperature measurement method and system based on thermal magnetic noise signals, so as to achieve high-precision, strong environmental adaptability and long-term stable operation of temperature monitoring. To this end, the present invention adopts the following technical solutions.

[0006] A method for measuring the temperature of a cable intermediate joint based on a thermal magnetic noise signal comprises the following steps: 1) Obtain the material information and physical dimensions of the cable connector shielding layer; 2) Establish a model for the relationship between thermal magnetic noise intensity and temperature; 3) Use two magnetometers to measure the magnetic field strength signals B1 and B2 at the center of the shielding layer; 4) Calculate the thermal magnetic noise signal intensity at the center based on the magnetic field strength signals B1 and B2; 5) According to the obtained thermal magnetic noise signal intensity, the temperature under the corresponding thermal magnetic noise signal intensity is calculated according to the relationship model in step 2), so as to obtain the cable joint temperature data.

[0007] The working mechanism of this technical solution is: in the multi-layer metal magnetic shielding layer, the outer thermal magnetic noise is shielded by the innermost layer, so the internal thermal magnetic noise is only generated by the inner shielding layer. The inner shielding layer metal of the cable intermediate joint is regarded as an infinitely long cylindrical metal tube. By measuring its physical dimensions, a relationship model between the thermal magnetic noise intensity and temperature is established. Two magnetometers are used to record the magnetic field intensity data at the center of the cylindrical metal tube, and the two sets of magnetic field intensity data are differentially processed to obtain the intensity level of the thermal magnetic noise. According to the established relationship model and the obtained thermal magnetic noise intensity level, the ambient temperature can be uniquely determined.

[0008] This method converts the measurement of temperature into the measurement of thermal magnetic noise, avoiding the influence of the measurement system itself on the measurement, and has higher accuracy. The intensity level of thermal magnetic noise is only related to the ambient temperature, the shielding layer material and the physical size, so this temperature measurement scheme has little effect on other external physical factors such as pressure and humidity. The material properties and physical dimensions of the shielding layer can be measured in situ, so this measurement scheme can achieve in-situ calibration without disassembly and calibration. Since the conductivity and physical dimensions of the shielding layer are stable over a long period of time, the corresponding calibration frequency of this measurement scheme can also be reduced to meet the requirements of long-term stable application sites. In the multi-layer metal magnetic shielding layer, the thermal magnetic noise of the outer layer is shielded by the innermost layer, and the internal thermal magnetic noise is only generated by the inner shielding layer. It is only necessary to calculate the thermal magnetic noise intensity generated by the inner shielding layer.

[0009] This method has the characteristics of high precision, insensitivity to environmental changes, and suitability for scenarios that require long-term stable operation. Compared with patent CN202010485226.0, this technical solution can achieve accurate temperature measurement in complex environments, reducing the impact of external physical factors on the measurement; at the same time, in view of the shortcomings of patent CN202220468635.4, this solution has fewer measurement influencing factors, which are only related to the temperature to be measured and the material and size of the shielding layer of the cable intermediate connector, and can realize in-situ calibration of the sensor, which is suitable for application scenarios that require long-term stable operation.

[0010] As a preferred technical means: the time for the magnetometer to measure the magnetic field strength signal at the center of the shielding layer lasts for more than 3 minutes.

[0011] Extending the measurement time of the magnetometer to more than 3 minutes helps reduce the uncertainty of the thermal magnetic noise level, thereby improving the accuracy of the measurement results. The data acquisition process is more stable, reducing the impact of instantaneous fluctuations on the results and ensuring the reliability of temperature measurement. By extending the measurement time, the impact of external interference factors (such as electromagnetic interference) can be effectively reduced, further enhancing the system's anti-interference ability.

[0012] As a preferred technical means: in step 4), the magnetic field strength signals B1 and B2 measured by the two magnetometers are differentially processed to obtain the thermal magnetic noise signal B3, thereby eliminating the influence of the common mode signal.

[0013] Through differential processing, the common mode signal can be effectively removed, the signal-to-noise ratio of the thermal magnetic noise signal can be improved, and the measurement results can be ensured to be more accurate. The differential method makes the tiny thermal magnetic noise signal more obvious, enhances the sensitivity to temperature changes, and improves the measurement accuracy. The common mode signal changes caused by environmental factors are eliminated, and the stability and reliability of the system under various working conditions are enhanced. Differential processing enables this method to maintain good performance in a more complex electromagnetic environment and is more adaptable. By reducing the impact of external interference on the measurement, the measurement error caused by environmental changes can be reduced, ensuring the authenticity and reliability of the data.

[0014] As a preferred technical means: the thermal magnetic noise signal B3 is processed to obtain the thermal magnetic noise power spectrum density, and the signal is averaged within its frequency range to calculate the thermal magnetic noise power level, and the thermal magnetic noise power level is further squared to obtain the final thermal magnetic noise signal intensity.

[0015] By performing power spectral density analysis on the thermal magnetic noise signal B3, the characteristics of the thermal magnetic noise can be more accurately characterized, providing a more reliable basis for temperature measurement. Averaging the signal within the frequency range effectively reduces the impact of random noise and improves the quality and availability of the signal. By calculating the thermal magnetic noise power level by square root, the obtained thermal magnetic noise signal intensity is more stable, reducing the measurement error caused by instantaneous fluctuations. This method can adapt to the characteristics of thermal magnetic noise in different environments, ensuring accurate measurement under complex conditions.

[0016] As a preferred technical means: in step 2), the relationship model between the intensity of the thermal magnetic noise generated by the intermediate joint and the temperature is expressed as:

[0017] in, is the intensity of thermal magnetic noise, T is the temperature, μ0 is the vacuum permeability, k is the Boltzmann constant, σ is the conductivity of the metal shielding layer, a is the inner radius of the inner shielding layer, and t is the thickness of the inner shielding layer.

[0018] The model of this technical solution can be adjusted according to different material and structural parameters (such as conductivity, radius and thickness), making it suitable for various types of cable intermediate joints. Through the model, the corresponding temperature can be accurately derived from the measured thermal magnetic noise intensity, providing a high-precision basis for temperature monitoring. The theoretical model reduces the need for a large amount of experimental data, reduces experimental costs and complexity, and improves efficiency. In addition, the model has a small amount of calculation, making real-time monitoring possible, which can timely reflect the temperature changes of the intermediate joints and enhance the responsiveness and safety of the system.

[0019] Another object of the present invention is to provide a cable intermediate joint temperature measurement system based on thermal magnetic noise signals, the cable intermediate joint temperature measurement system comprising: An information acquisition module, used to obtain material information and physical dimensions of the cable connector shielding layer; A relationship model building module is used to build a relationship model between thermal magnetic noise intensity and temperature; A magnetometer measurement module, comprising at least two magnetometers, for measuring magnetic field strength signals B1 and B2 at the center of the shielding layer, and the measurement time lasts for more than 3 minutes; A thermal magnetic noise signal strength calculation module is used to calculate the thermal magnetic noise signal strength at the center according to the magnetic field strength signals B1 and B2; The temperature calculation module calculates the temperature under the corresponding thermal magnetic noise signal intensity according to the obtained thermal magnetic noise signal intensity and the relationship model, thereby obtaining the cable joint temperature data.

[0020] This technical solution combines magnetometer measurement and thermal magnetic noise signal processing to achieve high-precision temperature measurement and ensure the accuracy of monitoring results. Through long-term measurement (greater than 3 minutes), the impact of instantaneous interference and noise on the results is significantly reduced, and the reliability of the data is improved. The establishment of a relational model makes temperature prediction more scientific and convenient for measurement under different materials and environments. And through the relational model, the calculation is fast, enabling the system to acquire, process and output data in real time, realize real-time monitoring of cable joint temperature, and improve safety and responsiveness. This technical solution can adapt to a variety of complex environmental factors to ensure that the system can still operate stably under different conditions. The automated data processing and calculation process reduces the need for manual intervention and improves measurement efficiency and accuracy.

[0021] As a preferred technical means: the relationship model between the thermal magnetic noise intensity and the temperature in the relationship model building module is expressed as:

[0022] in, is the intensity of thermal magnetic noise, T is the temperature, μ0 is the vacuum permeability, k is the Boltzmann constant, σ is the conductivity of the metal shielding layer, a is the inner radius of the inner shielding layer, and t is the thickness of the inner shielding layer.

[0023] As a preferred technical means: the thermal magnetic noise signal strength calculation module performs differential processing on the magnetic field strength signals B1 and B2 measured by the two magnetometers to obtain the thermal magnetic noise signal B3, thereby eliminating the influence of the common mode signal.

[0024] As a preferred technical means: the thermal magnetic noise signal intensity calculation module processes the thermal magnetic noise signal B3 to obtain the thermal magnetic noise power spectrum density, and averages the signal within its frequency range to calculate the thermal magnetic noise power level, and further squares the thermal magnetic noise power level to obtain the final thermal magnetic noise signal intensity.

[0025] As a preferred technical means: it also includes a data storage module for storing the material information of the cable connector shielding layer, the physical dimensions of the cable connector, the measured magnetic field strength signal, the database generated according to the relational model, the calculated thermal magnetic noise signal strength and the final temperature data; wherein the temperature calculation module calls the database generated by the relational model according to the thermal magnetic noise signal strength to obtain the corresponding cable connector temperature. The temperature calculation module calls the database according to the thermal magnetic noise signal strength, and can use a table lookup scheme to calculate the temperature, so that the calculation process is fast and efficient, and can reflect the temperature changes of the cable connector in a timely manner. And ensure the accuracy and consistency of the temperature calculation process to reduce human errors. In addition, the data storage module can provide a basis for subsequent intelligent analysis and support data-based intelligent decision-making and optimization. The table lookup data in the database can be updated and stored as needed to facilitate system maintenance and performance optimization.

[0026] Beneficial effects: 1. High measurement accuracy: Compared with traditional contact temperature measurement methods (such as thermistors), which require the sensor to be embedded in the measurement system, which may interfere with the measurement results and reduce the accuracy. This solution reflects the temperature by measuring the intensity level of thermal magnetic noise, avoiding the influence of the measurement system itself on the results, thereby achieving higher measurement accuracy.

[0027] Second, the environmental factors have little impact: The intensity level of thermal magnetic noise is mainly affected by the ambient temperature, shielding layer material and physical size, and is relatively less affected by other external physical factors (such as pressure, humidity, etc.). This makes this solution more stable under different environmental conditions.

[0028] 3. Suitable for long-term stable applications: The shielding layer material and physical dimensions can be measured in situ, ensuring the convenience of calibration without disassembly. In addition, since the conductivity and physical dimensions of the shielding layer are relatively stable in long-term use, the calibration frequency of this solution can be reduced, meeting the application requirements of long-term stable operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Schematic diagram of the thermal magnetic noise temperature measurement method of the present invention.

[0030] Figure 2 The figure is a working flow chart of the thermal magnetic noise temperature measurement method of the present invention.

[0031] Figure 3 This is a graph of the thermal magnetic noise signal intensity generated at different temperatures according to the present invention.

[0032] In the figure: 1. magnetometer; 2. inner shielding layer; 3. outer shielding layer. DETAILED DESCRIPTION

[0033] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings.

[0034] Embodiment 1: like Figure 2 As shown, the present invention comprises the following steps: S1: Get the material information and physical dimensions of the cable connector shield.

[0035] First, the material of the shielding layer is determined, and the conductivity is determined according to the material of the shielding layer. In this embodiment, the shielding layer of the cable connector is a copper shielding layer, and through query, the conductivity of the copper shielding layer can be obtained as σ=59.

[0036] Use a vernier caliper to measure the cable shield. Figure 1 As shown, the cable connector has an inner shielding layer 2 and an outer shielding layer 3. In this embodiment, it is only necessary to measure the inner diameter and outer diameter of the annular inner shielding layer 2, and calculate the inner radius a of the inner shielding layer 2 and the thickness t of the inner shielding layer 2. Of course, the thickness t of the inner shielding layer 2 can also be directly measured by a vernier caliper.

[0037] In this embodiment, it is measured that the inner radius a of the inner shielding layer 2 is 0.001 m, and the thickness t of the inner shielding layer 2 is 0.01 m.

[0038] The acquired material information and physical dimensions are stored in the data recording module to facilitate subsequent calculations and modeling.

[0039] S2: Establish a model for the relationship between thermal magnetic noise intensity and temperature According to the characteristics and physical dimensions of the actual materials of this embodiment, the relationship between the thermal magnetic noise intensity of the copper shielding layer at the center of the cable and the ambient temperature T is established.

[0040] Using the theory of thermal magnetic noise, combined with experimental data, the relationship curve is drawn through data fitting technology, such as Figure 3 shown.

[0041] In this embodiment, the adopted relational model is expressed as:

[0042] in, is the intensity of thermal magnetic noise, T is the temperature, μ0 is the vacuum permeability, k is the Boltzmann constant, σ is the conductivity of the metal shielding layer, a is the inner radius of the inner shielding layer, and t is the thickness of the inner shielding layer.

[0043] The data generated by the relational model is plotted into a chart and placed in the database for easy reference and use.

[0044] S3: Measurement of magnetic field strength signal Equipment preparation: Two high-precision atomic magnetometers 1 are placed at the center of the cable.

[0045] Ensure that the installation position of the magnetometer 1 is stable to reduce the influence of external interference on the measurement results.

[0046] Signal recording: Set up magnetometer 1 to record magnetic field strength signals B1 and B2, ensuring that the measurement time is more than 3 min to reduce the uncertainty in the thermal magnetic noise level.

[0047] During the recording period, the working status of the magnetometer 1 was monitored to ensure the continuity and accuracy of data collection.

[0048] Data storage: The recorded magnetic field strength data B1 and B2 are stored in the data storage module to ensure the integrity of the data and the feasibility of subsequent analysis.

[0049] S4: Processing of thermal magnetic noise signals Differential processing: The measured magnetic field strength signals B1 and B2 are differentially processed to calculate the thermal magnetic noise signal B3; this step can effectively eliminate the influence of common mode signals and improve the measurement accuracy.

[0050] Signal analysis: Use Origin and other data processing software to perform power spectral density analysis on the thermal magnetic noise signal B3 to obtain its power spectral density .

[0051] Calculate the thermal magnetic noise power level and perform signal averaging within the frequency range to obtain the thermal magnetic noise power level .

[0052] Signal strength calculation: The thermal magnetic noise power level obtained Perform square root processing to obtain the final thermal magnetic noise signal intensity .

[0053] S5: Calculation of temperature According to the relationship model and table lookup method established in step S2, the corresponding temperature data is obtained using the intensity of the thermal magnetic noise signal.

[0054] Since the relationship model is a monotonically increasing function, it can be directly calculated based on the thermal magnetic noise intensity. Find the corresponding ambient temperature T.

[0055] The obtained temperature data is recorded in the data storage module for subsequent analysis and recording.

[0056] Combined with time series analysis, temperature trends are monitored to identify potential anomalies.

[0057] Embodiment 2: A cable intermediate joint temperature measurement system mainly includes the following modules: 1. Information acquisition module This module is responsible for obtaining the material information and physical dimensions of the cable connector shielding layer. By consulting relevant information, the system can automatically identify the material of the shielding layer and obtain its conductivity. For example, if the shielding layer is copper, the conductivity σ=59. At the same time, the module uses measuring tools such as vernier calipers to obtain the inner diameter and outer diameter of the inner shielding layer 2, thereby calculating its inner radius a and thickness t. All the information obtained will be stored in the data recording module for subsequent processing.

[0058] 2. Relationship model building module This module establishes a relationship model between thermal magnetic noise intensity and temperature based on the material properties and physical dimensions of the shielding layer. The relationship model can be expressed as:

[0059] in, is the intensity of thermal magnetic noise, T is the temperature, μ0 is the vacuum permeability, k is the Boltzmann constant, σ is the conductivity of the metal shielding layer, a is the inner radius of the inner shielding layer, and t is the thickness of the inner shielding layer.

[0060] Through data fitting and experimental analysis, the relationship model generated by this module will be stored in the database for quick reference.

[0061] 3. Magnetometer 1 measurement module The module contains at least two high-precision magnetometers 1, which are placed at the center of the cable connector to record the magnetic field strength signals B1 and B2 at the center of the shielding layer. The measurement duration is greater than 3 minutes to reduce the impact of transient interference and noise on the results. The recorded data will be stored in the data storage module to ensure the integrity of the data and the reliability of subsequent analysis.

[0062] 4. Thermal magnetic noise signal strength calculation module In this module, the signals B1 and B2 measured by magnetometer 1 are differentially processed to obtain the thermal magnetic noise signal B3, thereby eliminating the influence of the common mode signal. Then, the power spectrum density of signal B3 is analyzed using data processing software such as Origin to calculate its power level, and the thermal magnetic noise signal strength is obtained by taking the square root of the power level. The processing process of this module ensures high-precision temperature measurement.

[0063] 5. Temperature calculation module This module calls the relational model database based on the obtained thermal magnetic noise signal strength to quickly calculate the corresponding cable joint temperature. The temperature calculation is realized by table lookup, ensuring that the calculation process is fast and efficient, and can reflect the temperature changes of the cable joint in time to reduce human errors. At the same time, the temperature data will be recorded in the data storage module to provide support for subsequent analysis.

[0064] 6. Data storage module This module is used to store the material information of the cable connector shielding layer, the physical dimensions of the cable connector, the measured magnetic field strength signal, the database generated according to the relational model, the calculated thermal magnetic noise signal strength, and the final temperature data. The data storage module supports subsequent intelligent analysis and promotes data-based intelligent decision-making and system optimization. The table lookup data in the database can be updated as needed to improve system performance.

[0065] This system can be combined with Internet of Things technology to realize remote monitoring and automatic alarm functions, further improving the intelligence level and application scope of the system. In addition, with the advancement of materials science and data analysis technology, the relationship model can be continuously optimized to improve measurement accuracy.

[0066] The above-mentioned cable intermediate joint temperature measurement method and system based on thermal magnetic noise signal is a specific embodiment of the present invention, which has embodied the substantial characteristics and progress of the present invention. According to actual use needs and under the guidance of the present invention, equivalent modifications can be made to it, which are all within the protection scope of this scheme.

Claims

1. A method for measuring the temperature of a cable intermediate joint based on a thermal magnetic noise signal, characterized in that The following steps are involved: 1) Obtain the material information and physical dimensions of the cable connector shielding layer; 2) Establish a model for the relationship between thermal magnetic noise intensity and temperature; 3) Use two magnetometers to measure the magnetic field strength signals B1 and B2 at the center of the shielding layer; 4) Calculate the intensity of the thermal magnetic noise signal at the center based on the magnetic field strength signals B1 and B2; 5) According to the obtained thermal magnetic noise signal intensity, the temperature under the corresponding thermal magnetic noise signal intensity is calculated according to the relationship model in step 2), so as to obtain the cable joint temperature data.

2. A cable intermediate joint temperature measurement method based on thermal magnetic noise signal according to claim 1, characterized in that: The magnetometer measures the magnetic field strength signal at the center of the shielding layer for more than 3 minutes.

3. The method for measuring the temperature of a cable intermediate joint based on a thermal magnetic noise signal according to claim 1, characterized in that: In step 4), the magnetic field strength signals B1 and B2 measured by the two magnetometers are differentially processed to obtain a thermal magnetic noise signal B3, thereby eliminating the influence of the common mode signal.

4. A cable intermediate joint temperature measurement method based on thermal magnetic noise signal according to claim 3, characterized in that: The thermal magnetic noise signal B3 is processed to obtain the thermal magnetic noise power spectrum density, and the signal is averaged within its frequency range to calculate the thermal magnetic noise power level, and the thermal magnetic noise power level is further squared to obtain the final thermal magnetic noise signal intensity.

5. The method for measuring the temperature of a cable intermediate joint based on a thermal magnetic noise signal according to claim 1, characterized in that: In step 2), the relationship between the thermal magnetic noise intensity and temperature generated by the intermediate joint is expressed as: in, is the intensity of thermal magnetic noise, T is the temperature, μ0 is the vacuum permeability, k is the Boltzmann constant, σ is the conductivity of the metal shielding layer, a is the inner radius of the inner shielding layer, and t is the thickness of the inner shielding layer.

6. A cable intermediate joint temperature measurement system based on thermal magnetic noise signal, characterized in that include: An information acquisition module, used to obtain material information and physical dimensions of the cable connector shielding layer; A relationship model building module is used to build a relationship model between thermal magnetic noise intensity and temperature; A magnetometer measurement module, comprising at least two magnetometers, for measuring magnetic field strength signals B1 and B2 at the center of the shielding layer, and the measurement time lasts for more than 3 minutes; A thermal magnetic noise signal strength calculation module is used to calculate the thermal magnetic noise signal strength at the center according to the magnetic field strength signals B1 and B2; The temperature calculation module calculates the temperature under the corresponding thermal magnetic noise signal intensity according to the obtained thermal magnetic noise signal intensity and the relationship model, thereby obtaining the cable joint temperature data.

7. The cable intermediate joint temperature measurement system based on thermal magnetic noise signal according to claim 6, characterized in that: The relationship model between the thermal magnetic noise intensity and temperature in the relationship model building module is expressed as: in, is the intensity of thermal magnetic noise, T is the temperature, μ0 is the vacuum permeability, k is the Boltzmann constant, σ is the conductivity of the metal shielding layer, a is the inner radius of the inner shielding layer, and t is the thickness of the inner shielding layer.

8. The cable intermediate joint temperature measurement system based on thermal magnetic noise signal according to claim 6, characterized in that: The thermal magnetic noise signal strength calculation module performs differential processing on the magnetic field strength signals B1 and B2 measured by the two magnetometers to obtain the thermal magnetic noise signal B3, thereby eliminating the influence of the common mode signal.

9. The cable intermediate joint temperature measurement system based on thermal magnetic noise signal according to claim 6, characterized in that: The thermal magnetic noise signal strength calculation module processes the thermal magnetic noise signal B3 to obtain the thermal magnetic noise power spectrum density, and averages the signal within its frequency range to calculate the thermal magnetic noise power level, and further squares the thermal magnetic noise power level to obtain the final thermal magnetic noise signal strength.

10. The cable intermediate joint temperature measurement system based on thermal magnetic noise signal according to claim 6, characterized in that: It also includes a data storage module for storing material information of the cable connector shielding layer, the physical size of the cable connector, the measured magnetic field strength signal, a database generated according to the relational model, the calculated thermal magnetic noise signal strength and the final temperature data; wherein the temperature calculation module calls the database generated by the relational model according to the thermal magnetic noise signal strength to obtain the corresponding cable connector temperature.

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