Cable joint partial discharge signal magnetic sensing method and device based on tunneling magnetoresistance effect

Abstract

The application relates to a cable joint partial discharge signal magnetic sensing method and device based on a tunneling magnetoresistance effect, and the method comprises the following steps: a plurality of flexible installation monitoring points are arranged on a shielding layer of a high-voltage cable joint to be measured, and TIT sensing modules are respectively arranged; a tunneling magnetoresistance effect sensing unit respectively senses a partial discharge pulse voltage signal; a position information acquisition unit respectively acquires position information; after signal processing is performed on the partial discharge pulse voltage signal, a plurality of digital signals are obtained, differential and combined calculation is respectively performed on the plurality of digital signals to generate a graph and a differential signal, and the graph and the differential signal are input into a neural network model to obtain a discharge fault type result; and position information is processed according to a position amplitude weighting algorithm to obtain a discharge fault position result. Compared with the prior art, the application has the advantages of integration, small power consumption, strong anti-interference capability, accurate result and the like, and is very suitable for online measurement and positioning of partial discharge defects at a high-voltage cable joint in an outdoor environment.

Description

Technical Field

[0001] This invention relates to the field of cable joint fault monitoring technology, and in particular to a method and apparatus for magnetic sensing of partial discharge signals of cable joints based on the tunneling magnetoresistance effect. Background Technology

[0002] With the increasing number of high-voltage cable installations and the ever-increasing demands for power supply stability, effectively reducing the frequency and duration of power outages has become a key task in ensuring power supply quality. To achieve this goal, real-time monitoring and evaluation of cable insulation is crucial, involving the collection and analysis of substantial amounts of online detection data. During cable operation, cables are subjected to various electrical, mechanical, and thermal stresses, which can induce partial discharge. Partial discharge is a major cause of insulation degradation in cables and their joints; failure to detect and address it promptly can lead to insulation failure and ultimately, sudden power outages. Therefore, accurately conducting partial discharge detection on high-voltage cable insulation and effectively identifying and determining defect types are of paramount importance for ensuring the safe and stable operation of cable installations.

[0003] Currently, high-frequency current sensors are widely used to acquire pulse current signals in the partial discharge detection of high-voltage cables. This method has become one of the mainstream detection methods due to its advantages such as simple signal acquisition, strong anti-interference ability, and ease of subsequent analysis and processing. Current partial discharge identification methods mainly involve constructing discharge modes that characterize the properties of different types of discharge sources, extracting effective feature parameters from them, and training them using appropriate classification algorithms to achieve the identification of discharge source types. For example, the invention disclosed in publication number CN120044297A is a comprehensive monitoring method for the operating status of high-voltage cables based on a TMR magnetic sensor.

[0004] However, most of these methods are based on experimental studies under single-defect conditions. When faced with situations where cables may have multiple coexisting defects in actual operation, their identification accuracy decreases. Due to the complexity of manufacturing and operating environments, cables are often affected by multiple factors simultaneously, leading to multiple defects jointly triggering partial discharges. The measured discharge waveform is often a superposition of multiple discharge signals. Existing identification methods struggle to accurately distinguish between various defects under such multi-source mixed discharge conditions, severely impacting the accuracy of diagnostic results. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art by providing a method and device for magnetic sensing of partial discharge signals of cable joints based on the tunneling magnetoresistance effect, so as to achieve accurate measurement and location of cable joint fault types and fault locations.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A magnetic sensing method for partial discharge signals of cable joints based on tunneling magnetoresistance effect includes the following steps: setting multiple flexibly installed monitoring points on the shielding layer of the high-voltage cable joint under test, and installing TIT sensing modules on each of them. Each TIT sensing module integrates a tunneling magnetoresistance effect sensing unit and an inertial navigation sensing unit.

[0008] The partial discharge pulse voltage signal is sensed by the tunneling magnetoresistance effect sensing unit in each TIT sensing module, and the position information of the current flexibly installed monitoring point is obtained by the inertial navigation sensing unit in each TIT sensing module.

[0009] After signal processing of each partial discharge pulse voltage signal, multiple digital signals are obtained. Differential and combined calculations are performed on each digital signal to generate a spectrum and differential signal, which are then input into a pre-trained neural network model to obtain the discharge fault type result. The position information is processed according to the position amplitude weighting algorithm to obtain the discharge fault location result of the cable joint.

[0010] Furthermore, the tunneling magnetoresistive effect sensing unit includes a TMR magnetic sensor, an instrumentation amplifier, an operational amplifier, and a resistor connected in sequence. The resistor is used to eliminate zero drift in the circuit of the tunneling magnetoresistive effect sensing unit. The output voltage signal of the TMR magnetic sensor is amplified by the instrumentation amplifier and then output as a partial discharge pulse voltage signal by the operational amplifier.

[0011] Furthermore, the inertial navigation sensing unit includes a GNSS dual antenna, a three-axis MEMS gyroscope, and a three-axis accelerometer sensor. The GNSS dual antenna is used to acquire latitude, longitude, and azimuth. The three-axis MEMS gyroscope and the three-axis accelerometer sensor are used to acquire pitch and roll information of the attitude parameters of the TIT sensing module. Finally, the latitude, longitude, azimuth, pitch, and roll information are integrated to output position information.

[0012] Furthermore, the position magnitude weighting algorithm is specifically as follows:

[0013] The latitude, longitude, and altitude of each TIT sensing module are converted into a three-dimensional Cartesian coordinate system to obtain the corresponding position coordinates;

[0014] Based on the amplitude of each differential signal and the number of time-domain sampling points of a single differential signal, calculate the distance between the current TIT sensing module and the location of the discharge fault.

[0015] Calculate the direction vector of each TIT sensor module based on its azimuth and pitch angles;

[0016] Based on the position coordinates of each TIT sensing module, the distance between it and the discharge fault location, and the direction vector, the coordinate solution of the discharge fault location of the cable joint is obtained by using the least squares method.

[0017] Furthermore, the calculation expression for the solution process of the least squares method is as follows:

[0018]

[0019] In the formula, These are the three-dimensional coordinates of the discharge fault. n The number of TIT sensor modules, For the first j The position coordinates of each TIT sensor module For the first j The distance between each TIT sensor module and the location of the discharge fault. Let j be the direction vector of the j-th TIT sensing module. and These are the distance error weights and the direction error weights, respectively.

[0020] Furthermore, the expression for calculating the distance between the current TIT sensing module and the discharge fault location is as follows:

[0021]

[0022] In the formula, For the first j The distance between each TIT sensor module and the location of the discharge fault. It is a proportionality constant. V represents the number of time-domain sampling points for a single differential signal, and V is the amplitude of the differential signal. i For the current sampling point, Sampling points i The amplitude of the differential signal.

[0023] Furthermore, the expression for calculating the direction vector of the TIT sensing module is as follows:

[0024]

[0025] In the formula, Let j be the direction vector of the j-th TIT sensing module. and The first j The azimuth and pitch angles of each TIT sensor module.

[0026] Furthermore, the signal processing for each partial discharge pulse voltage signal is as follows:

[0027] Each partial discharge pulse voltage signal is filtered, the filtered partial discharge pulse voltage signal is converted into a digital signal, and the digital signal is denoised to obtain the final digital signal for output.

[0028] The present invention also provides a magnetic sensing device for partial discharge signals of cable joints that implements the magnetic sensing method for partial discharge signals of cable joints based on the tunneling magnetoresistance effect as described above, comprising:

[0029] Multiple TIT sensing modules are installed on various flexible installation monitoring points set on the shielding layer of the high-voltage cable joint under test. Each TIT sensing module integrates a tunneling magnetoresistive effect sensing unit and an inertial navigation sensing unit. The tunneling magnetoresistive effect sensing unit is used to sense the partial discharge pulse voltage signal, and the inertial navigation sensing unit is used to obtain the position information of the current flexible installation monitoring point.

[0030] The signal conditioning module is used to process the voltage signals of each partial discharge pulse to obtain multiple digital signals;

[0031] The signal encapsulation module is used to frame the multiple digital signals output by the signal conditioning module and the position information output by each TIT sensor module and then transmit them to the signal processing module.

[0032] The signal processing module is used to deframe the framing results of the signal encapsulation module, perform differential and combining calculations on each digital signal to generate a spectrum and differential signal, and input them into a pre-trained neural network model to obtain the discharge fault type result. Based on the position amplitude weighting algorithm, the position information is processed to obtain the discharge fault location result of the cable joint.

[0033] Furthermore, the framing format of the signal encapsulation module includes sequentially distributed frame header bits, digital signal bits, position information bits, frame tail bits, time stamp bits, and reserved bits. The digital signal bits are used to store digital signals, and the position information bits are used to store position information.

[0034] Compared with the prior art, the present invention has the following advantages:

[0035] (1) This invention sets up multiple flexible monitoring points on the shielding layer of the cable joint, and installs TIT sensing modules composed of tunneling magnetoresistance effect sensing units and inertial navigation sensing units respectively. The TIT sensing modules collect partial discharge pulse voltage signals and the location information of the monitoring points respectively. The digital signals after processing the multi-channel partial discharge pulse voltage signals are differentially and combined to generate a spectrum and differential signals. The neural network model and the position amplitude weighting algorithm realize the accurate positioning of partial discharge and defect type identification of high-voltage cable joints based on the differential signals. It performs well, especially in the scenario of multiple defects coexisting, and provides a reliable technical guarantee for the safe operation of high-voltage cable devices.

[0036] This invention has the advantages of integration, low power consumption, strong anti-interference ability, and accurate results, making it very suitable for online measurement and location of partial discharge defects at high-voltage cable joints in outdoor environments.

[0037] (2) In the process of solving the fault location, the present invention uses the least squares method to find the optimal coordinate solution that satisfies the shortest distance between the fault location and the position coordinates of each TIT sensing module and the current TIT sensing module and the discharge fault location, and also satisfies the minimum value of the direction vector of the distance between the fault location and the position coordinates of each TIT sensing module, thus realizing a more accurate and reliable fault location calculation. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating a method for magnetic sensing of partial discharge signals in cable joints based on the tunneling magnetoresistance effect, provided in an embodiment of the present invention.

[0039] Figure 2 This is a flowchart illustrating a position magnitude weighting algorithm provided in an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the structure of a magnetic sensing device for partial discharge signals of a cable joint provided in an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram of the structure of a TIT sensing module provided in an embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram of the structure of a signal conditioning module provided in an embodiment of the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0044] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0045] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0046] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of this invention is usually placed during use. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0047] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0048] Furthermore, terms such as "horizontal" and "vertical" do not imply that components must be absolutely horizontal or suspended, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0049] Example 1

[0050] like Figure 1 As shown, this embodiment provides a magnetic sensing method for partial discharge signals of cable joints based on the tunneling magnetoresistance effect, including the following steps:

[0051] S1: Multiple flexible monitoring points are set up on the shielding layer of the high-voltage cable joint under test, and TIT sensing modules are installed on each of them. Each TIT sensing module integrates a tunneling magnetoresistance effect sensing unit and an inertial navigation sensing unit.

[0052] S2: The partial discharge pulse voltage signal is sensed by the tunneling magnetoresistance effect sensing unit in each TIT sensing module, and the position information of the current flexibly installed monitoring point is obtained by the inertial navigation sensing unit in each TIT sensing module.

[0053] S3: After signal processing of each partial discharge pulse voltage signal, multiple digital signals are obtained;

[0054] S4: Perform differential and combined calculations on each digital signal to generate a spectrum and differential signal, and input them into a pre-trained neural network model to obtain the discharge fault type result. Process the position information according to the position amplitude weighting algorithm to obtain the cable joint discharge fault location result.

[0055] In step S1, the tunneling magnetoresistive effect sensing unit includes a TMR magnetic sensor, an instrumentation amplifier, an operational amplifier, and a resistor connected in sequence. The resistor is used to eliminate zero drift in the circuit of the tunneling magnetoresistive effect sensing unit. The output voltage signal of the TMR magnetic sensor is amplified by the instrumentation amplifier and then output as a partial discharge pulse voltage signal through the operational amplifier.

[0056] The inertial navigation sensing unit includes a GNSS dual antenna, a three-axis MEMS gyroscope, and a three-axis accelerometer sensor. The GNSS dual antenna is used to acquire latitude, longitude, and azimuth. The three-axis MEMS gyroscope and the three-axis accelerometer sensor are used to acquire pitch and roll information of the attitude parameters of the TIT sensing module. Finally, the latitude, longitude, azimuth, pitch, and roll information are integrated to output position information.

[0057] In this embodiment, four TIT sensing modules are installed at four flexible installation monitoring points on the shielding layer of the high-voltage cable connector under test.

[0058] The tunneling magnetoresistive effect sensing unit is used to sense the partial discharge pulse voltage signal released at the grounding wire of the shield layer of the high-voltage cable joint. It includes one TMR magnetic sensor, one instrumentation amplifier, one operational amplifier and four resistors. The TMR magnetic sensor is model TMR2003, the instrumentation amplifier is model AD620 and the operational amplifier is model LM741.

[0059] Four resistors are used to eliminate zero drift in the op-amp circuit, among which the full-scale 10kΩ resistor is adjusted to make the output voltage of the instrumentation amplifier AD620 zero; after eliminating zero drift, the differential output voltage signal of the TMR magnetic sensor is amplified and output by the instrumentation amplifier AD620.

[0060] The inertial navigation sensing unit is used to output the current position information of the monitoring point and includes a GNSS dual antenna, a three-axis MEMS gyroscope and a three-axis accelerometer sensor.

[0061] The dual GNSS antennas are used to acquire high-precision latitude, longitude, and azimuth; the three-axis MEMS gyroscope and three-axis accelerometer sensor are used to process and filter the sensed signals to obtain pitch and roll information of attitude parameters, and finally output position information.

[0062] In step S3, the signal processing for each partial discharge pulse voltage signal is as follows:

[0063] Each partial discharge pulse voltage signal is filtered, the filtered partial discharge pulse voltage signal is converted into a digital signal, and the digital signal is denoised to obtain the final digital signal for output.

[0064] In this embodiment, the partial discharge pulse voltage signals output by the four TIT sensing modules are filtered, converted by AD, and denoised to output four digital signals.

[0065] In step S4, the difference calculation is performed by subtracting paired signals to extract the difference information.

[0066] In this embodiment, for four digital signals , , and Perform pairwise subtraction to obtain the differential signal. , , and .

[0067] The combined signal calculation is to combine multiple signals into a single composite signal, that is, to superimpose or weight and fuse the signals in the digital domain, so as to facilitate the prediction of the subsequent neural network model.

[0068] like Figure 2 As shown, the position magnitude weighting algorithm is as follows:

[0069] S401: Convert the latitude, longitude, and altitude of each TIT sensor module into a three-dimensional Cartesian coordinate system to obtain the corresponding position coordinates;

[0070] S402: Based on the amplitude of each differential signal and the number of time-domain sampling points of a single differential signal, calculate the distance between the current TIT sensing module and the discharge fault location. The corresponding calculation expression is:

[0071]

[0072] In the formula, For the first j The distance between each TIT sensor module and the location of the discharge fault. It is a proportionality constant. V represents the number of time-domain sampling points for a single differential signal, and V is the amplitude of the differential signal. i For the current sampling point, Sampling points i The amplitude of the differential signal;

[0073] S403: Calculate the direction vector of each TIT sensor module based on its azimuth and elevation angles. The corresponding calculation expression is:

[0074]

[0075] In the formula, Let j be the direction vector of the j-th TIT sensing module. and The first j The azimuth and pitch angles of each TIT sensor module.

[0076] S404: Based on the position coordinates of each TIT sensor module, the distance between it and the discharge fault location, and the direction vector, the coordinate solution of the discharge fault location of the cable joint is obtained by using the least squares method.

[0077] The calculation expression for the least squares method is as follows:

[0078]

[0079] In the formula, These are the three-dimensional coordinates of the discharge fault. n The number of TIT sensor modules, For the first j The position coordinates of each TIT sensor module For the first j The distance between each TIT sensor module and the location of the discharge fault. Let j be the direction vector of the j-th TIT sensing module. and These are the distance error weights and the direction error weights, respectively.

[0080] In this embodiment, the process of the position amplitude weighting algorithm processing the four differential signals is as follows:

[0081] 1) Convert the latitude, longitude, and altitude of the four TIT sensor modules into a three-dimensional Cartesian coordinate system. The position coordinates of the four TIT sensor modules are defined as follows:

[0082]

[0083] in, ~ The position coordinates of the four TIT sensor modules, ~ These are the three-dimensional position coordinates of the four TIT sensing modules.

[0084] 2) Calculate the relationship between the amplitude of the four differential signals and the distance between the current TIT sensor module and the discharge fault location using the following formula:

[0085]

[0086] Where N is the number of time-domain sampling points for a single differential signal, V is the amplitude of the differential signal, i is the current sampling point, and k is a scaling constant. This represents the distance between the current TIT sensing module and the location of the discharge fault.

[0087] 3) Calculate the direction vectors pointed to by the four TIT sensor modules based on their azimuth and elevation angles:

[0088]

[0089] in, Let j be the direction vector of the j-th TIT sensing module. and These are the azimuth and elevation angles of the j-th TIT sensor module, respectively.

[0090] 4) Establish the following objective function and use the least squares method to find the coordinate solution of the discharge fault location.

[0091]

[0092] in, and These are the error weights for distance and direction, respectively. These are the three-dimensional coordinates of the discharge fault. Let j be the direction vector of the j-th TIT sensing module. Let J be the position coordinates of the j-th TIT sensor module. Let j be the distance between the j-th TIT sensing module and the location of the discharge fault.

[0093] Example 2

[0094] This embodiment provides a cable joint partial discharge signal magnetic sensing device for implementing the cable joint partial discharge signal magnetic sensing method based on tunneling magnetoresistance effect of Embodiment 1, comprising:

[0095] Multiple TIT sensing modules are installed on various flexible installation monitoring points set on the shielding layer of the high-voltage cable joint under test. Each TIT sensing module integrates a tunneling magnetoresistive effect sensing unit and an inertial navigation sensing unit. The tunneling magnetoresistive effect sensing unit is used to sense the partial discharge pulse voltage signal, and the inertial navigation sensing unit is used to obtain the position information of the current flexible installation monitoring point.

[0096] The signal conditioning module is used to process the voltage signals of each partial discharge pulse to obtain multiple digital signals;

[0097] The signal encapsulation module is used to frame the multiple digital signals output by the signal conditioning module and the position information output by each TIT sensor module and then transmit them to the signal processing module.

[0098] The signal processing module is used to deframe the framing results of the signal encapsulation module, perform differential and combining calculations on each digital signal to generate a spectrum and differential signal, and input them into a pre-trained neural network model to obtain the discharge fault type result. Based on the position amplitude weighting algorithm, the position information is processed to obtain the discharge fault location result of the cable joint.

[0099] In this embodiment, as Figure 3 As shown, the magnetic sensing device for partial discharge signals of cable joints has four TIT sensing modules. The four TIT sensing modules are deployed at four flexibly installed monitoring points on the shielding layer of the high-voltage cable joint and are respectively connected to the signal conditioning module and the signal encapsulation module. The signal conditioning module and the signal encapsulation module are connected, and the signal encapsulation module is connected to the signal processing module.

[0100] like Figure 4 As shown, each TIT sensing module includes a tunneling magnetoresistive effect sensing unit (TMR) and an inertial navigation sensing unit (IMU).

[0101] The signal conditioning module is used to filter, perform AD conversion, and denoise the partial discharge pulse voltage signals output by the four TIT sensor modules, and output four digital voltage signals to the signal packaging module.

[0102] like Figure 5 As shown, the signal conditioning module specifically includes a filtering unit, an AD conversion unit, and a denoising unit. The filtering unit includes a charge conversion circuit, an active filter circuit, and an output amplifier circuit. The AD conversion unit converts the filtered partial discharge pulse voltage signal into a digital signal for automatic acquisition. The denoising unit denoises the digital signal and outputs the denoised digital signal to the signal encapsulation module.

[0103] The signal encapsulation module is used to frame the four digital signals output by the signal conditioning module and the position information, and then output them to the signal processing module.

[0104] The framing format of the signal encapsulation module includes sequentially distributed frame header bits, digital signal bits, position information bits, frame tail bits, time stamp bits, and reserved bits. The digital signal bits are used to store digital signals, and the position information bits are used to store position information.

[0105] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A magnetic sensing method for partial discharge signals of cable joints based on tunneling magnetoresistance effect, characterized in that, Includes the following steps: Multiple flexible monitoring points are set up on the shielding layer of the high-voltage cable joint under test, and TIT sensing modules are installed on each of them. Each TIT sensing module integrates a tunneling magnetoresistance effect sensing unit and an inertial navigation sensing unit. The partial discharge pulse voltage signal is sensed by the tunneling magnetoresistance effect sensing unit in each TIT sensing module, and the position information of the current flexibly installed monitoring point is obtained by the inertial navigation sensing unit in each TIT sensing module. After signal processing of each partial discharge pulse voltage signal, multiple digital signals are obtained. Differential and combined calculations are performed on each digital signal to generate a spectrum and differential signal, which are then input into a pre-trained neural network model to obtain the discharge fault type result. The position information is processed according to the position amplitude weighting algorithm to obtain the discharge fault location result of the cable joint.

2. The method for magnetic sensing of partial discharge signals in cable joints based on tunneling magnetoresistance effect according to claim 1, characterized in that, The tunneling magnetoresistive effect sensing unit includes a TMR magnetic sensor, an instrumentation amplifier, an operational amplifier, and a resistor connected in sequence. The resistor is used to eliminate zero drift in the circuit of the tunneling magnetoresistive effect sensing unit. The output voltage signal of the TMR magnetic sensor is amplified by the instrumentation amplifier and then output as a partial discharge pulse voltage signal by the operational amplifier.

3. The method for magnetic sensing of partial discharge signals in cable joints based on tunneling magnetoresistance effect according to claim 1, characterized in that, The inertial navigation sensing unit includes a GNSS dual antenna, a three-axis MEMS gyroscope, and a three-axis accelerometer sensor. The GNSS dual antenna is used to acquire latitude, longitude, and azimuth. The three-axis MEMS gyroscope and the three-axis accelerometer sensor are used to acquire pitch and roll information of the attitude parameters of the TIT sensing module. Finally, the latitude, longitude, azimuth, pitch, and roll information are integrated to output position information.

4. The method for magnetic sensing of partial discharge signals in cable joints based on tunneling magnetoresistance effect according to claim 1, characterized in that, The specific location magnitude weighting algorithm is as follows: The latitude, longitude, and altitude of each TIT sensing module are converted into a three-dimensional Cartesian coordinate system to obtain the corresponding position coordinates; Based on the amplitude of each differential signal and the number of time-domain sampling points of a single differential signal, calculate the distance between the current TIT sensing module and the location of the discharge fault. Calculate the direction vector of each TIT sensor module based on its azimuth and elevation angles; Based on the position coordinates of each TIT sensing module, the distance between it and the discharge fault location, and the direction vector, the coordinate solution of the discharge fault location of the cable joint is obtained by using the least squares method.

5. The method for magnetic sensing of partial discharge signals in cable joints based on tunneling magnetoresistance effect according to claim 4, characterized in that, The calculation expression for the solution process of the least squares method is as follows: In the formula, These are the three-dimensional coordinates of the discharge fault. n The number of TIT sensor modules, For the first j The position coordinates of each TIT sensor module For the first j The distance between each TIT sensor module and the location of the discharge fault. Let j be the direction vector of the j-th TIT sensing module. and These are the distance error weights and the direction error weights, respectively.

6. The method for magnetic sensing of partial discharge signals of cable joints based on tunneling magnetoresistance effect according to claim 4, characterized in that, The formula for calculating the distance between the current TIT sensing module and the location of the discharge fault is: In the formula, For the first j The distance between each TIT sensor module and the location of the discharge fault. It is a proportionality constant. V represents the number of time-domain sampling points for a single differential signal, and V is the amplitude of the differential signal. i For the current sampling point, Sampling points i The amplitude of the differential signal.

7. The method for magnetic sensing of partial discharge signals in cable joints based on tunneling magnetoresistance effect according to claim 4, characterized in that, The expression for calculating the direction vector of the TIT sensing module is as follows: In the formula, Let j be the direction vector of the j-th TIT sensing module. and The first j The azimuth and pitch angles of each TIT sensor module.

8. The method for magnetic sensing of partial discharge signals in cable joints based on tunneling magnetoresistance effect according to claim 1, characterized in that, The specific signal processing for each partial discharge pulse voltage signal is as follows: Each partial discharge pulse voltage signal is filtered, the filtered partial discharge pulse voltage signal is converted into a digital signal, and the digital signal is denoised to obtain the final digital signal for output.

9. A magnetic sensing device for partial discharge signals of cable joints, implementing the magnetic sensing method for partial discharge signals of cable joints based on the tunneling magnetoresistance effect as described in any one of claims 1-8, characterized in that, include: Multiple TIT sensing modules are installed on various flexible installation monitoring points set on the shielding layer of the high-voltage cable joint under test. Each TIT sensing module integrates a tunneling magnetoresistive effect sensing unit and an inertial navigation sensing unit. The tunneling magnetoresistive effect sensing unit is used to sense the partial discharge pulse voltage signal, and the inertial navigation sensing unit is used to obtain the position information of the current flexible installation monitoring point. The signal conditioning module is used to process the voltage signals of each partial discharge pulse to obtain multiple digital signals; The signal encapsulation module is used to frame the multiple digital signals output by the signal conditioning module and the position information output by each TIT sensor module and then transmit them to the signal processing module. The signal processing module is used to deframe the framing results of the signal encapsulation module, perform differential and combining calculations on each digital signal to generate a spectrum and differential signal, and input them into a pre-trained neural network model to obtain the discharge fault type result. Based on the position amplitude weighting algorithm, the position information is processed to obtain the discharge fault location result of the cable joint.

10. The apparatus according to claim 9, characterized in that, The framing format of the signal encapsulation module includes a frame header, digital signal bits, position information bits, frame tail bits, time stamp bits, and reserved bits arranged in sequence. The digital signal bits are used to store digital signals, and the position information bits are used to store position information.

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