Thermomagnetic noise signal-based cable intermediate joint temperature measurement method and system

Abstract

The application discloses a kind of cable intermediate joint temperature measurement method and system based on thermomagnetic noise signal, it is related to cable joint temperature measurement field, the precision and stability of existing temperature measurement method under complex environment are influenced by external factors, it is easy to cause measurement error.The present application comprises the following steps: obtaining the material information and physical size of the shielding layer of cable joint;Establish the relationship model between the intensity level of thermomagnetic noise and temperature;The magnetic field intensity signals B1, B2 at the center of the shielding layer are obtained by measuring with two magnetometers;The intensity of thermomagnetic noise signal at the center is obtained;According to the obtained thermomagnetic noise signal intensity, according to the model, the temperature under the corresponding thermomagnetic noise signal intensity is calculated, and the cable joint temperature data T is obtained.The technical scheme compared with traditional measurement method has the advantages of high precision, not sensitive to environmental changes and suitable for long-term stable operation scene.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of cable joint temperature measurement, and in particular to a cable intermediate joint temperature measurement method based on thermomagnetic noise signals. BACKGROUND

[0002] Cables are important power transmission facilities that connect power grids and are crucial to energy supply in modern society. Cable intermediate joints are key devices that connect two cables. When the installation of the intermediate joint is improper or the insulation layer is aging, it often causes serious discharge phenomena accompanied by a sharp rise in temperature. If these problems are not discovered and addressed in a timely manner, it may lead to more serious fire accidents, causing incalculable 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. The 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 precision and does not require an external power source. However, this sensor is susceptible to external physical factors such as pressure and humidity, which can lead to a decrease in measurement accuracy and stability.

[0004] Utility model patent CN202220468635.4 proposes a cable intermediate joint temperature measurement device based on multi-core photonic crystal infrared temperature sensors. 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 on the outer layer. This point array distribution aims 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 a possible decrease in sensitivity of the multi-core photonic crystal sensors and an increase in measurement error, which limits its application in long-term stable operation scenarios. In addition, the performance of the multi-core photonic crystal sensors can be significantly affected in certain extreme environments (such as high temperature, high pressure, strong magnetic field, etc.). SUMMARY

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

[0006] A cable intermediate joint temperature measurement method based on thermomagnetic noise signals, comprising the following steps:

[0007] 1) Obtain the material information and physical dimensions of the cable joint shielding layer;

[0008] 2) Establish a relationship model between the thermal magnetic noise intensity and the temperature;

[0009] 3) Measure the magnetic field intensity signals B1 and B2 at the center of the shielding layer using two magnetometers;

[0010] 4) Calculate the thermal magnetic noise signal intensity at the center according to the magnetic field intensity signals B1 and B2;

[0011] 5) According to the obtained thermal magnetic noise signal intensity, according to the relationship model in step 2), calculate the temperature corresponding to the thermal magnetic noise signal intensity, and obtain the cable joint temperature data.

[0012] The working mechanism of the technical solution is: in the multi-layer metal magnetic shielding layer, the thermal magnetic noise of the outer layer 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 pipe, and the relationship model between the thermal magnetic noise intensity and the temperature is established by measuring its physical dimensions. The magnetic field intensity data at the center of the cylindrical metal pipe is recorded by using two magnetometers, 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.

[0013] The 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 precision. The thermal magnetic noise intensity level is only related to the environmental temperature, the shielding layer material and the physical dimensions, so the temperature measurement scheme is not much affected by other external physical factors such as pressure and humidity. The shielding layer material properties and physical dimensions can be measured in situ, so the measurement scheme can realize in-situ calibration without disassembly and calibration. Since the shielding layer conductivity and physical dimensions are stable for a long time, the corresponding calibration frequency of the measurement scheme can also be reduced to meet the needs of long-term stable application scenarios. 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, so only the thermal magnetic noise intensity generated by the inner shielding layer needs to be calculated.

[0014] The method has the characteristics of high precision, insensitivity to environmental changes and applicability to long-term stable operation scenarios. Compared with patent CN202010485226.0, the technical solution can realize accurate temperature measurement in complex environments and reduce the influence of external physical factors on measurement. At the same time, in view of the shortcomings of patent CN202220468635.4, the measurement influencing factors of the scheme are fewer, only related to the temperature to be measured and the material and size of the cable intermediate joint shielding layer, and the in-situ calibration of the sensor can be realized, which is suitable for application scenarios that need long-term stable operation.

[0015] As a preferred technical means: the time duration of the magnetometer measuring the magnetic field intensity signal at the center of the shielding layer is greater than 3 minutes.

[0016] Extending the measurement time of the magnetometer to more than 3 minutes helps to 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 transient fluctuations on the results, ensuring the reliability of temperature measurement. By extending the measurement time, the influence of external interference factors (such as electromagnetic interference) can be effectively reduced, further enhancing the anti-interference ability of the system.

[0017] As a preferred technical means: in step 4), the magnetic field intensity 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 common-mode signals.

[0018] Through differential processing, the common-mode signal can be effectively removed, improving the signal-to-noise ratio of the thermal magnetic noise signal and ensuring more accurate measurement results. The differential method makes the small thermal magnetic noise signal more obvious, enhancing the sensitivity to temperature changes and improving the measurement accuracy. The change of common-mode signal caused by environmental factors is eliminated, enhancing the stability and reliability of the system under various working conditions. Differential processing enables the method to maintain good performance in a more complex electromagnetic environment, making it more adaptable. By reducing the influence of external interference on measurement, measurement errors caused by environmental changes can be reduced, ensuring the authenticity and reliability of the data.

[0019] As a preferred technical means: the thermal magnetic noise signal B3 is processed to obtain the thermal magnetic noise power spectral density, and the signal is averaged in its frequency range to calculate the thermal magnetic noise power level, and the square root of the thermal magnetic noise power level is taken to obtain the final thermal magnetic noise signal intensity.

[0020] 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 in the frequency range effectively reduces the influence of random noise, improving the quality and usability of the signal. By taking the square root to calculate the thermal magnetic noise power level, the thermal magnetic noise signal intensity obtained is more stable, reducing measurement errors caused by transient fluctuations. This method can adapt to the characteristics of thermal magnetic noise in different environments, ensuring accurate measurement under complex conditions.

[0021] As a preferred technical means: in step 2), the relationship model between the thermal magnetic noise intensity generated by the intermediate joint and the temperature is represented as:

[0022]

[0023] wherein, where I is the thermomagnetic noise intensity, 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.

[0024] The model of the technical solution can be adjusted according to different materials and structural parameters (such as conductivity, radius, and thickness) to be suitable for various types of cable intermediate joints. Through the model, the corresponding temperature can be accurately derived from the measured thermomagnetic 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 cost and complexity, and improves efficiency. Moreover, the model has small calculation amount, making real-time monitoring possible, which can timely reflect the temperature change of the intermediate joint, enhancing the response capability and safety of the system.

[0025] Another object of the present application is to provide a cable intermediate joint temperature measurement system based on thermomagnetic noise signals, which comprises:

[0026] An information acquisition module for acquiring material information and physical dimensions of the cable joint shielding layer;

[0027] A relationship model establishment module for establishing a relationship model between thermomagnetic noise intensity and temperature;

[0028] A magnetometer measurement module comprising at least two magnetometers for measuring magnetic field intensity signals B1 and B2 at the center of the shielding layer, and the measurement time lasts more than 3 minutes;

[0029] A thermomagnetic noise signal intensity calculation module for calculating the thermomagnetic noise signal intensity at the center according to the magnetic field intensity signals B1 and B2;

[0030] A temperature calculation module for calculating the temperature under the corresponding thermomagnetic noise signal intensity according to the relationship model based on the obtained thermomagnetic noise signal intensity, thereby obtaining the cable joint temperature data.

[0031] The technical solution combines magnetometer measurement and thermomagnetic noise signal processing to achieve high-precision temperature measurement and ensure the accuracy of the monitoring results. Through long-time (more than 3 minutes) measurement, the influence of transient interference and noise on the results is significantly reduced, improving the reliability of the data. The establishment of the relationship model makes the temperature prediction more scientific and convenient for application in different materials and environments. Moreover, through the relationship model, the calculation is fast, enabling the system to acquire, process, and output data in real time, achieving immediate monitoring of the cable joint temperature and improving safety and response capability. The technical solution can adapt to various complex environmental factors, ensuring that the system can still operate stably under different conditions. The automated data processing and calculation process reduces the need for human intervention, improving measurement efficiency and accuracy.

[0032] As a preferred technical means: the relationship model between the thermal magnetic noise intensity and the temperature in the relationship model establishing module is represented as:

[0033]

[0034] wherein, is the thermal magnetic noise intensity, 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.

[0035] As a preferred technical means: the thermal magnetic noise signal intensity calculation module differentiates the magnetic field intensity 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.

[0036] 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 spectral density, averages the signal in its frequency range to calculate the thermal magnetic noise power level, and further takes the square root of the thermal magnetic noise power level to obtain the final thermal magnetic noise signal intensity.

[0037] As a preferred technical means: it further includes a data storage module for storing the material information of the cable joint shielding layer, the physical size of the cable joint, the measured magnetic field intensity signal, the database generated according to the relationship model, the calculated thermal magnetic noise signal intensity, and the final temperature data; wherein the temperature calculation module calls the database generated according to the relationship model according to the thermal magnetic noise signal intensity to obtain the corresponding cable joint temperature. The temperature calculation module calls the database according to the thermal magnetic noise signal intensity, which can realize the calculation of temperature by using the table lookup scheme, so that the calculation process is rapid and efficient, and the temperature change of the cable joint can be reflected in time. And ensure the accuracy and consistency of the temperature calculation process, reduce human error. In addition, the data storage module can provide a basis for subsequent intelligent analysis, support intelligent decision-making and optimization based on data. The table lookup data in the database can be updated and stored as needed, which is convenient for system maintenance and performance optimization.

[0038] Beneficial effects:

[0039] One, high measurement accuracy: compared with the traditional contact type temperature measurement method (such as thermistor), the latter needs to embed the sensor into the measurement system, which may interfere with the measurement result, thereby reducing the accuracy. This scheme reflects the temperature by measuring the thermal magnetic noise intensity level, avoiding the influence of the measurement system itself on the result, thereby realizing higher measurement accuracy.

[0040] II. Less affected by environmental factors: The intensity level of thermomagnetic noise is mainly affected by environmental temperature, shielding layer material and physical size, and is relatively less affected by other external physical factors (such as pressure, humidity, etc.). This makes the scheme have better stability under different environmental conditions.

[0041] III. Suitable for long-term stable application: The shielding layer material and physical size can be measured in situ, ensuring the convenience of calibration without disassembly. In addition, since the conductivity and physical size of the shielding layer are relatively stable during long-term use, the calibration frequency of the scheme is reduced, meeting the application requirements of long-term stable operation. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 is a schematic diagram of the thermomagnetic noise temperature measurement method of the present application.

[0043] Figure 2 is a workflow diagram of the thermomagnetic noise temperature measurement method of the present application.

[0044] Figure 3 is a diagram of the thermomagnetic noise signal intensity generated at different temperatures of the present application.

[0045] In the figure: 1, magnetometer; 2, inner shielding layer; 3, outer shielding layer. DETAILED DESCRIPTION

[0046] The technical scheme of the present application will be further described in detail below in conjunction with the drawings of the specification.

[0047] Example 1:

[0048] As shown in Figure 2 , the present application comprises the following steps:

[0049] S1: Obtain the material information and physical size of the cable joint shielding layer.

[0050] First, determine the material of the shielding layer, and determine the electrical conductivity according to the material of the shielding layer. In this embodiment, the cable joint shielding layer is a copper shielding layer, and by querying, the electrical conductivity of the copper shielding layer can be obtained σ=59.

[0051] Use a vernier caliper to measure the cable shielding layer. As shown in Figure 1 , the cable joint has an inner shielding layer 2 and an outer shielding layer 3, and in this embodiment, only the inner diameter and outer diameter of the annular inner shielding layer 2 need to be measured to 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 the vernier caliper.

[0052] In this embodiment, the inner radius a of the inner shielding layer 2 is measured to be 0.001 m, and the thickness t of the inner shielding layer 2 is measured to be 0.01 m.

[0053] The acquired material information and physical dimensions are stored in a data recording module for subsequent calculation and modeling.

[0054] S2: Establishing the relationship model between thermal magnetic noise intensity and temperature

[0055] According to the actual material characteristics and physical dimensions of the embodiment, the relationship between the thermal magnetic noise intensity of the copper shielding layer at the center of the cable and the environmental temperature T is established.

[0056] Using the thermal magnetic noise theory, combined with experimental data, the relationship curve is drawn through data fitting technology, as shown in Figure 3 .

[0057] In this embodiment, the relationship model is represented as:

[0058]

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

[0060] The data generated by the relationship model is plotted into a chart and placed in a database for easy reference and use.

[0061] S3: Measurement of magnetic field intensity signal

[0062] Device preparation:

[0063] Place two high-precision atomic magnetometers 1 at the center of the cable.

[0064] Ensure that the installation position of the magnetometer 1 is stable to reduce the influence of external interference on the measurement results.

[0065] Signal recording:

[0066] Set the magnetometer 1 to record the magnetic field intensity signals B1 and B2, and ensure that the measurement time exceeds 3 minutes to reduce the uncertainty of the thermal magnetic noise level.

[0067] Monitor the working state of the magnetometer 1 during recording to ensure the continuity and accuracy of data acquisition.

[0068] Data storage: Store the recorded magnetic field intensity data B1 and B2 into the data storage module to ensure the integrity of the data and the feasibility of subsequent analysis.

[0069] S4: Processing of thermal magnetic noise signal

[0070] Difference processing:

[0071] The measured magnetic field intensity signals B1 and B2 are differentially processed to calculate the thermomagnetic noise signal B3; this step can effectively eliminate the influence of common-mode signals and improve the accuracy of measurement.

[0072] Signal analysis:

[0073] Using data processing software such as Origin, the thermomagnetic noise signal B3 is analyzed for power spectral density to obtain its power spectral density .

[0074] Calculate the thermomagnetic noise power level, and perform signal averaging processing in the frequency range to obtain the thermomagnetic noise power level .

[0075] Signal strength calculation:

[0076] The obtained thermomagnetic noise power level is square root processed to obtain the final thermomagnetic noise signal strength .

[0077] S5: Temperature calculation

[0078] According to the relationship model established in step S2 and the table lookup method, the thermomagnetic noise signal strength is used to obtain the corresponding temperature data.

[0079] Since the relationship model is a monotonically increasing function, the corresponding ambient temperature T can be directly found according to the thermomagnetic noise strength .

[0080] The obtained temperature data is recorded in the data storage module for subsequent analysis and recording.

[0081] Combined with time series analysis, monitor the temperature change trend to identify potential abnormal situations.

[0082] Example two:

[0083] A cable intermediate joint temperature measurement system mainly includes the following modules:

[0084] 1. Information acquisition module

[0085] This module is responsible for acquiring the material information and physical dimensions of the cable joint shielding layer. By consulting relevant materials, the system can automatically identify the material of the shielding layer and obtain its electrical conductivity. For example, if the shielding layer is copper, the electrical conductivity σ = 59. At the same time, the module uses vernier caliper and other measuring tools to obtain the inner diameter and outer diameter of the inner shielding layer 2, and thus calculates the inner radius a and thickness t. All the acquired information will be stored in the data recording module for subsequent processing.

[0086] 2. Relationship model establishment module

[0087] The module establishes a relationship model between the thermomagnetic noise intensity and the temperature according to the material properties and physical dimensions of the shielding layer. The relationship model can be expressed as:

[0088]

[0089] wherein, is the thermomagnetic noise intensity, T is the temperature, μ0 is the vacuum permeability, k is the Boltzmann constant, σ is the electrical 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.

[0090] Through data fitting and experimental analysis, the relationship model generated by the module will be stored in the database for quick reference.

[0091] 3. Magnetometer 1 measurement module

[0092] This module contains at least two high-precision magnetometers 1 placed at the center of the cable joint to record the magnetic field intensity 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 data integrity and reliability for subsequent analysis.

[0093] 4. Thermomagnetic noise signal intensity calculation module

[0094] In this module, the signals B1 and B2 measured by the magnetometer 1 are differentially processed to obtain the thermomagnetic noise signal B3, thereby eliminating the influence of common-mode signals. Then, the signal B3 is analyzed for power spectral density using data processing software such as Origin, the power level is calculated, and the thermomagnetic noise signal intensity is obtained by taking the square root of the power level. The processing process of this module ensures high-precision temperature measurement.

[0095] 5. Temperature calculation module

[0096] This module calls the relationship model database according to the obtained thermomagnetic noise signal intensity to quickly calculate the corresponding cable joint temperature. The temperature calculation is realized through table lookup, ensuring quick and efficient calculation process, timely reflecting the temperature change of the cable joint, and reducing human error. At the same time, the temperature data will be recorded in the data storage module to provide support for subsequent analysis.

[0097] 6. Data storage module

[0098] This module is used to store the material information of the cable joint shielding layer, the physical size of the cable joint, the measured magnetic field strength signal, the generated database according to the relationship model, the calculated thermomagnetic noise signal strength, and the final temperature data. The data storage module supports subsequent intelligent analysis, promotes data-based intelligent decision-making and system optimization. The lookup table data in the database can be updated as needed to improve system performance.

[0099] The system can combine with the Internet of Things technology to realize remote monitoring and automatic alarm functions, further improving the intelligent degree and application range of the system. In addition, with the progress of material science and data analysis technology, the relationship model can be continuously optimized to improve the measurement accuracy.

[0100] The cable intermediate joint temperature measurement method and system based on thermomagnetic noise signal shown above are specific embodiments of the present application, which have embodied the essential characteristics and progress of the present application. According to the actual use needs, equivalent modifications can be made under the inspiration of the present application, which are all within the protection scope of the present application.

Claims

1. A method for measuring the temperature of a cable joint based on thermomagnetic noise signals, characterized in that... Includes the following steps: 1) Obtain the material information and physical dimensions of the inner shielding layer in the multilayer metal magnetic shielding layer of the cable joint, including the conductivity σ, the inner radius a of the inner shielding layer, and the thickness t of the inner shielding layer; 2) Treating the inner shielding layer as an infinitely long cylindrical metal tube, a relationship model between thermomagnetic noise intensity and temperature is established. This relationship model is expressed as: in, Where is the thermomagnetic noise intensity, T is the temperature, μ0 is the free permeability, and k is the Boltzmann constant; 3) Use two magnetometers to measure the magnetic field strength signals B1 and B2 at the center of the shielding layer; 4) Differential processing is performed on the magnetic field strength signals B1 and B2 measured by the two magnetometers to obtain the thermomagnetic noise signal B3, thereby eliminating the influence of the common-mode signal; then the thermomagnetic noise signal B3 is processed to obtain the thermomagnetic noise power spectral density, and the signal is averaged within its frequency range to calculate the thermomagnetic noise signal intensity at the center. 5) Based on the obtained thermomagnetic noise signal intensity, and according to the relationship model in step 2), calculate the temperature under the corresponding thermomagnetic noise signal intensity to obtain the cable joint temperature data.

2. The method for measuring the temperature of a cable joint based on thermomagnetic noise signals 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 joint based on thermomagnetic noise signals according to claim 1, characterized in that: The thermomagnetic noise signal B3 is processed to obtain the thermomagnetic noise power spectral density, and the signal is averaged within its frequency range to calculate the thermomagnetic noise power level. The square root of the thermomagnetic noise power level is then taken to obtain the final thermomagnetic noise signal intensity.

4. A cable joint temperature measurement system based on thermomagnetic noise signals, characterized in that, For performing the cable joint temperature measurement method based on thermomagnetic noise signal as described in any one of claims 1-3, the system comprises: The information acquisition module is used to acquire material information and physical dimensions of the cable connector shielding layer; The relational model building module is used to establish a relationship model between thermomagnetic noise intensity and temperature; The magnetometer measurement module contains at least two magnetometers for measuring the magnetic field strength signals B1 and B2 at the center of the shielding layer, and the measurement time lasts for more than 3 minutes. The thermomagnetic noise signal intensity calculation module is used to calculate the thermomagnetic noise signal intensity at the center based on the magnetic field intensity signals B1 and B2. The temperature calculation module calculates the temperature at the corresponding thermomagnetic noise signal intensity based on the obtained thermomagnetic noise signal intensity and a relational model, thereby obtaining the cable joint temperature data.

5. The cable joint temperature measurement system based on thermomagnetic noise signal according to claim 4, characterized in that: The relationship model between thermomagnetic noise intensity and temperature in the relationship model building module is expressed as follows: in, denoted as thermomagnetic noise intensity, T as temperature, μ0 as vacuum permeability, k as Boltzmann constant, σ as conductivity of the metal shielding layer, a as inner radius of the inner shielding layer, and t as thickness of the inner shielding layer.

6. The cable joint temperature measurement system based on thermomagnetic noise signal according to claim 4, characterized in that: The thermomagnetic noise signal intensity calculation module performs differential processing on the magnetic field intensity signals B1 and B2 measured by the two magnetometers to obtain the thermomagnetic noise signal B3, thereby eliminating the influence of the common-mode signal.

7. The cable joint temperature measurement system based on thermomagnetic noise signal according to claim 4, characterized in that: The thermomagnetic noise signal intensity calculation module processes the thermomagnetic noise signal B3 to obtain the thermomagnetic noise power spectral density, and averages the signal within its frequency range to calculate the thermomagnetic noise power level. It then takes the square root of the thermomagnetic noise power level to obtain the final thermomagnetic noise signal intensity.

8. The cable joint temperature measurement system based on thermomagnetic noise signal according to claim 4, characterized in that: It also includes a data storage module for storing material information of the cable joint shielding layer, physical dimensions of the cable joint, measured magnetic field strength signals, a database generated based on a relational model, calculated thermomagnetic noise signal intensity, and final temperature data; wherein, the temperature calculation module calls the database generated by the relational model based on the thermomagnetic noise signal intensity to obtain the corresponding cable joint temperature.

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