A method for monitoring the temperature of a cable joint and the cable joint itself.

Abstract

This invention relates to the field of cable monitoring technology, and discloses a method for temperature monitoring of cable joints and a cable joint itself. The method includes: acquiring real-time insulation layer temperature data of the cable joint based on a miniature temperature sensor, and acquiring real-time environmental data of the cable joint based on an auxiliary sensor; comparing the real-time insulation layer temperature data with the real-time ambient temperature value to determine the direction of heat radiation from the cable joint; determining the temperature difference between the real-time insulation layer temperature data and the real-time ambient temperature value, and determining a predicted temperature value for the conductor crimping layer based on the direction of heat radiation and the temperature difference; determining a predicted temperature change rate for the conductor crimping layer based on the predicted temperature value; acquiring the real-time load current of the cable joint and determining the real-time temperature change rate; determining the ratio of the difference between the predicted temperature change rate and the real-time temperature change rate, and judging whether the cable joint exhibits a temperature monitoring anomaly. This invention achieves accurate temperature prediction and reliable anomaly detection for cable joints.

Description

Technical Field

[0001] This invention relates to the field of cable monitoring technology, and in particular to a method for monitoring the temperature of a cable joint and the cable joint itself. Background Technology

[0002] With the continuous expansion of power system scale and the increasing complexity of transmission and distribution networks, cable joints, as key connecting components in power transmission systems, directly affect the safety and stability of the entire power grid. In actual operation, cable joints are prone to localized overheating due to factors such as increased contact resistance, poor crimping, insulation aging, or changes in the external environment, which can lead to serious accidents such as insulation breakdown, short circuits, or even fires.

[0003] Currently, monitoring the temperature of cable joints relies heavily on infrared thermometry, fiber optic thermometry, or external temperature sensors. However, these methods generally suffer from problems such as response lag, inaccurate measurement location, and susceptibility to environmental interference, making it difficult to accurately reflect the actual temperature changes of the conductor crimping layer inside the cable joint. In particular, since the conductor crimping layer is encased in multiple layers of insulation and shielding structures, traditional external temperature measurement methods cannot directly obtain its temperature information, resulting in insufficient early warning capabilities for potential thermal faults. Furthermore, even when using embedded temperature sensors, existing technologies often only focus on temperature data from a single location, failing to fully consider the impact of ambient temperature and humidity on the insulation layer temperature readings, and lacking dynamic prediction and anomaly detection mechanisms for the conductor crimping layer temperature, thus limiting the accuracy and intelligence level of the temperature monitoring system.

[0004] Therefore, there is an urgent need for a monitoring method that can comprehensively consider environmental factors, load current and temperature change characteristics to achieve accurate prediction of conductor crimp layer temperature and reliable judgment of anomalies. Summary of the Invention

[0005] The purpose of this invention is to provide a method for monitoring the temperature of cable joints and a cable joint itself, aiming to solve one or more of the following problems in existing cable joint temperature monitoring technologies: inability to accurately obtain the true temperature of the conductor crimping layer, susceptibility of insulation layer temperature data to environmental interference, lack of effective prediction and anomaly identification mechanisms for temperature change trends, and lack of dynamic correction and reliability assessment of temperature monitoring results.

[0006] This invention provides a method for monitoring the temperature of a cable joint, comprising:

[0007] Several miniature temperature sensors are pre-embedded at different positions within the insulation layer of the cable joint. Real-time insulation layer temperature data of the cable joint is obtained based on the miniature temperature sensors. An auxiliary sensor is deployed in the external environment of the cable joint to obtain real-time environmental data of the cable joint based on the auxiliary sensor. The real-time environmental data includes real-time environmental temperature value and real-time environmental humidity value.

[0008] The real-time insulation layer temperature data and real-time environmental data are time-synchronized, and after processing, the real-time insulation layer temperature data is compared with the real-time environmental temperature value. The direction of heat radiation of the cable joint is determined based on the comparison result.

[0009] The temperature difference between the real-time insulation layer temperature data and the real-time ambient temperature value is determined. Based on the direction of thermal radiation, the real-time insulation layer temperature data is adjusted according to the temperature difference to determine the predicted temperature value of the conductor crimping layer of the cable joint.

[0010] The predicted temperature change rate of the conductor crimping layer is determined based on the predicted temperature value; the real-time load current of the cable joint is obtained, and the real-time temperature change rate of the conductor crimping layer is determined based on the real-time load current.

[0011] Determine the ratio of the difference between the predicted temperature change rate and the real-time temperature change rate, and determine whether the cable joint is abnormal in temperature monitoring based on the ratio of the difference.

[0012] Preferably, before comparing the real-time insulation layer temperature data with the real-time ambient temperature value, the method further includes:

[0013] The ambient humidity value is compared with the preset humidity value. If the ambient humidity value is greater than or equal to the preset humidity value, the reliability of the real-time insulation layer temperature data and the real-time ambient temperature value is verified.

[0014] Otherwise, no credibility check will be performed;

[0015] The reliability test is carried out by comparing the detection data of the miniature temperature sensor or auxiliary sensor with the detection data of the adjacent sensor to determine the degree of temperature deviation. If the degree of temperature deviation is greater than the preset deviation, the corresponding real-time insulation layer temperature data or real-time ambient temperature value is determined to be unreliable and is discarded.

[0016] Preferably, the real-time insulation layer temperature data is compared with the real-time ambient temperature value, and the direction of heat radiation from the cable joint is determined based on the comparison result. Specifically:

[0017] The real-time insulation layer temperature data is compared with the real-time ambient temperature value. If the real-time insulation layer temperature data is greater than or equal to the real-time ambient temperature value, the heat radiation direction of the cable joint is determined to be the positive heat radiation direction.

[0018] If the real-time insulation layer temperature data is less than the real-time ambient temperature value, then the heat radiation direction of the cable joint is determined to be the negative heat radiation direction.

[0019] Wherein, the positive direction of thermal radiation is the transfer of heat from the cable joint to the environment, and the negative direction of thermal radiation is the transfer of heat from the environment to the cable joint.

[0020] Preferably, the real-time insulation layer temperature data is adjusted based on the thermal radiation direction and the temperature difference, specifically as follows:

[0021] If the direction of thermal radiation is the positive direction of thermal radiation, then the real-time insulation layer temperature data is adjusted positively based on the temperature difference.

[0022] If the direction of thermal radiation is the negative direction of thermal radiation, then the real-time insulation layer temperature data is adjusted negatively based on the temperature difference.

[0023] Preferably, based on the direction of thermal radiation, the real-time insulation layer temperature data is adjusted according to the temperature difference to determine the predicted temperature value of the conductor crimping layer of the cable joint, specifically as follows:

[0024] If the direction of thermal radiation is the positive direction of thermal radiation, then the predicted temperature value of the conductor crimping layer = real-time insulation layer temperature data + temperature difference × k1;

[0025] If the direction of thermal radiation is the negative direction of thermal radiation, then the predicted temperature value of the conductor crimping layer = real-time insulation layer temperature data - temperature difference × k2;

[0026] Where k1 represents the positive direction adjustment coefficient of thermal radiation and k2 represents the negative direction adjustment coefficient of thermal radiation, and the values ​​of k1 and k2 are both in the range of 0-0.2.

[0027] Preferably, when determining the predicted temperature change rate of the conductor crimping layer based on the predicted temperature value, the predicted temperature change rate is determined according to the following formula:

[0028] ΔTp=(Tp t -Tp t-1 ) / Δt;

[0029] Where ΔTp represents the predicted rate of temperature change, Tp t Tp represents the predicted temperature value at time t. t-1 Δt represents the predicted temperature value at time t-1, and Δt represents the time interval.

[0030] Preferably, the real-time temperature change rate of the conductor crimping layer is determined based on the real-time load current, specifically as follows:

[0031] Calculate the square of the real-time current at the cable joint based on the real-time load current.

[0032] The real-time temperature change rate of the conductor crimping layer is determined based on the square of the real-time current.

[0033] The real-time temperature change rate is determined according to the following formula:

[0034] ΔTr=KI 2 ;

[0035] Where ΔTr represents the real-time temperature change rate, K represents the real-time temperature change rate adjustment coefficient, and I represents the real-time load current.

[0036] Preferably, when determining the ratio of the difference between the predicted temperature change rate and the real-time temperature change rate, the ratio of the difference is determined according to the following formula:

[0037] B = |Predicted temperature change rate - Real-time temperature change rate| / Real-time temperature change rate;

[0038] Where B represents the difference ratio.

[0039] Preferably, the determination of whether the cable joint is abnormal in temperature monitoring is based on the difference ratio, specifically as follows:

[0040] A first difference ratio and a second difference ratio are preset, wherein the first difference ratio is less than the second difference ratio;

[0041] The relationship between the stated difference ratio and the first and second difference ratios determines whether the cable joint has an abnormal temperature monitoring and determines the level of abnormality.

[0042] If the difference ratio is less than or equal to the first difference ratio, then the cable joint temperature is determined to be normal.

[0043] If the difference ratio is greater than the first difference ratio and the difference ratio is less than or equal to the second difference ratio, then the cable joint temperature monitoring is determined to be slightly abnormal.

[0044] If the difference ratio is greater than the second difference ratio, then the cable joint temperature monitoring is determined to be severely abnormal.

[0045] The present invention also discloses a cable connector, which can be used to monitor temperature using the above-mentioned cable connector temperature monitoring method. The cable connector includes, from the inside out, a conductor crimping layer, an insulation layer, a shielding layer and a sealing protection layer, and a plurality of miniature temperature sensors are embedded in the insulation layer.

[0046] Compared with the prior art, the beneficial effect of the present invention is that it proposes a method for monitoring the temperature of cable joints. By pre-embedding multiple miniature temperature sensors in the insulation layer and combining them with external environmental auxiliary sensors (collecting ambient temperature and humidity), it achieves accurate perception and intelligent analysis of the internal thermal state of the cable joint.

[0047] This invention determines the direction of thermal radiation by comparing the insulation layer temperature with the ambient temperature, and dynamically adjusts the insulation layer temperature data based on this direction and the temperature difference. This effectively compensates for energy loss or gain in the heat conduction path, thereby calculating a more accurate predicted temperature value for the conductor crimping layer. An ambient humidity threshold judgment mechanism is introduced to verify the reliability of sensor data and eliminate anomalies under high humidity conditions, avoiding false high-temperature signals caused by condensation, water vapor penetration, etc., significantly improving the system's reliability under harsh operating conditions. Furthermore, by continuously predicting the temperature value and calculating the predicted temperature change rate, and by calculating the real-time temperature change rate based on the square relationship of the real-time load current, the difference ratio formed by comparing the two can effectively identify whether temperature anomalies originate from changes in electrical load or internal faults, avoiding false alarms or missed alarms. Finally, based on preset two-level difference ratio thresholds, the system can automatically distinguish between "normal," "mildly abnormal," and "severely abnormal" states, providing maintenance personnel with clear decision-making basis and supporting preventative maintenance and rapid fault response. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0049] Figure 1 This is a schematic flowchart of a temperature monitoring method for a cable joint according to the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0051] like Figure 1 As shown, the present invention provides a method for monitoring the temperature of a cable joint, comprising:

[0052] Several miniature temperature sensors are pre-embedded at different positions within the insulation layer of the cable joint. Real-time insulation layer temperature data of the cable joint is obtained based on the miniature temperature sensors. An auxiliary sensor is deployed in the external environment of the cable joint to obtain real-time environmental data of the cable joint based on the auxiliary sensor. The real-time environmental data includes real-time environmental temperature value and real-time environmental humidity value.

[0053] The real-time insulation layer temperature data and real-time environmental data are time-synchronized, and after processing, the real-time insulation layer temperature data is compared with the real-time environmental temperature value. The direction of heat radiation of the cable joint is determined based on the comparison result.

[0054] The temperature difference between the real-time insulation layer temperature data and the real-time ambient temperature value is determined. Based on the direction of thermal radiation, the real-time insulation layer temperature data is adjusted according to the temperature difference to determine the predicted temperature value of the conductor crimping layer of the cable joint.

[0055] The predicted temperature change rate of the conductor crimping layer is determined based on the predicted temperature value; the real-time load current of the cable joint is obtained, and the real-time temperature change rate of the conductor crimping layer is determined based on the real-time load current.

[0056] Determine the ratio of the difference between the predicted temperature change rate and the real-time temperature change rate, and determine whether the cable joint is abnormal in temperature monitoring based on the ratio of the difference.

[0057] This invention achieves accurate prediction of the temperature of the core heat-generating area (conductor crimping layer) inside a cable joint by combining a miniature temperature sensor embedded within the insulation layer with an externally deployed auxiliary sensor. The miniature temperature sensor directly senses the temperature at different locations within the insulation layer, providing raw data for internal temperature field analysis. The ambient temperature and humidity data collected by the auxiliary sensor, especially the ambient temperature value consistent with the detection location of the miniature temperature sensor, provides crucial evidence for eliminating interference from environmental factors in the insulation layer temperature measurement. Time synchronization processing ensures consistency between temperature and environmental data over time, laying a reliable foundation for subsequent comparative analysis. By comparing real-time insulation layer temperature data with ambient temperature values ​​to determine the direction of thermal radiation, and adjusting the insulation layer temperature data based on the temperature difference, the influence of external environmental thermal or cold radiation on the measurement results can be effectively eliminated. This allows for a more accurate calculation of the predicted temperature value of the conductor crimping layer, overcoming the shortcomings of traditional external temperature measurement methods that struggle to reflect the true internal temperature. Furthermore, by introducing a differential ratio analysis between the predicted temperature change rate and the real-time temperature change rate determined based on the real-time load current, not only is the static value of temperature considered, but also the dynamic trend of temperature change over time and its correlation with the load current. This allows for more sensitive detection of early temperature anomalies caused by potential faults such as increased contact resistance in cable joints. This enables multi-dimensional and high-precision monitoring of the temperature status of cable joints, which helps to promptly identify potential safety hazards and improve the safety and reliability of power system operation.

[0058] Specifically, several miniature temperature sensors are pre-embedded at different locations within the insulation layer. This refers to embedding tiny, high-voltage-resistant, and aging-resistant temperature sensing elements (such as thermistors, digital temperature chips, or fiber Bragg grating sensors) into multiple key areas within the insulation layer during the cable joint manufacturing or installation process. These areas include the inner side near the conductor crimping layer, the middle of the insulation layer, and the outer side near the shielding layer. This distributed deployment captures the radial or axial temperature gradient distribution of the insulation layer, avoiding information loss due to single-point measurements. Acquiring real-time insulation layer temperature data involves continuously collecting temperature signals output by each miniature sensor via wired or wireless methods (such as radio frequency, near-field communication, or embedded bus), forming a time-series data stream at a set sampling frequency (such as once per second or multiple times per minute). Deploying auxiliary sensors in the external environment of the cable joint involves fixing environmental temperature and humidity sensors near the cable joint housing, on the mounting bracket, or in the surrounding air to synchronously monitor the thermal and humidity conditions of the external space where the joint is located. This deployment should ensure that the sensors are not subjected to extreme interference such as direct sunlight or rain immersion, but can accurately reflect the operating environment of the joint. Real-time environmental data includes real-time ambient temperature and humidity values, emphasizing the completeness of environmental parameters. Humidity information is used not only to assess the risk of condensation but also as a key input for subsequent data reliability verification, while ambient temperature is used to compare with the insulation layer temperature to determine the direction of heat flow.

[0059] For example, taking a 10kV cross-linked polyethylene (XLPE) power cable intermediate joint as an example: Four miniature digital temperature sensors (such as the improved DS18B20 package) are evenly embedded circumferentially within the insulation layer, located at radial depths of 2mm, 5mm, 8mm, and 10mm from the conductor crimping layer surface, respectively; simultaneously, one sensor is arranged at each of the axial ends, for a total of six measuring points, covering areas prone to hotspots. An integrated temperature and humidity sensor module (such as SHT35) is installed in the air approximately 5cm outside the external metal shielding layer of the joint. This module is encapsulated with a waterproof and breathable membrane and fixed to the inner wall of the joint's protective box to avoid direct contact with the metal surface, which could lead to thermal conduction distortion. The system synchronously collects data from all seven sensors every 10 seconds: six insulation layer temperatures (e.g., 68.2℃, 65.5℃, 62.1℃, 60.3℃, 63.7℃, and 61.9℃) and one set of environmental data (e.g., ambient temperature 32.5℃, relative humidity 78%). These data are then sent to the central processing unit for time alignment, determination of thermal radiation direction, and subsequent prediction model calculations.

[0060] Specifically, miniature temperature sensors can employ any miniature temperature sensing element suitable for high-voltage insulation environments, such as thermocouples, thermistors, silicon-based integrated circuit temperature sensors, or fiber Bragg grating (FBG) sensors. Their encapsulation materials can be epoxy resin, silicone rubber, or ceramic to ensure compatibility with the insulation material and to avoid affecting dielectric properties. The pre-embedded locations can be adaptively deployed based on the cable joint structure (e.g., straight-through, T-branch), conductor cross-sectional area, crimping process, or historical fault statistics. For example, they can be densely deployed near the crimped end face, stress cone areas, or weak points in the insulation. Auxiliary sensors can be deployed on the surface of the cable joint body (non-conductive areas), in the air inside the joint well, near the tunnel wall, or integrated into the housing of a smart terminal. Alternatively, multiple auxiliary sensors can be used to form an environmental monitoring array, taking average or master values ​​to improve the representativeness of the environmental data. Miniature sensors can be led out to the connector tail interface via embedded wires, or they can use passive wireless methods (such as LC resonance, RFID temperature tags) to achieve contactless transmission of energy and data; auxiliary sensors can upload data via wired connection or low power wide area network (such as LoRa, NB-IoT), as long as they can achieve time synchronization with the insulation layer temperature data.

[0061] Specifically, because miniature temperature sensors and auxiliary environmental sensors may use different acquisition frequencies, communication paths, or processing delays, their raw data may have misalignments on the timeline ranging from microseconds to seconds. Time synchronization processing refers to unifying the two types of data to the same time base through hardware triggering (such as sharing a clock source), software interpolation (such as linear or spline interpolation), or timestamp alignment, ensuring that the data points used for subsequent comparative analysis correspond to the same physical moment. This processing can be completed by a local edge computing unit or a remote monitoring platform. The direction of thermal radiation here broadly refers to the direction of net heat flow, i.e., whether heat is transferred from the inside of the cable joint to the external environment (positive) or from the environment to the inside of the joint (negative). This judgment is based on the fundamental thermodynamic principle that heat spontaneously flows from a high-temperature object to a low-temperature object. Therefore, if the insulation temperature is higher than the ambient temperature, it is determined to be in the "positive direction of thermal radiation"; otherwise, it is in the "negative direction of thermal radiation." This directional information directly determines whether positive or negative compensation should be used in the subsequent temperature adjustment model.

[0062] For example, in a 110kV cable terminal joint monitoring system, during a certain monitoring cycle: at t=10:00:00, the insulation layer temperatures reported by the miniature sensor are 72.3℃, 68.9℃, and 65.1℃, respectively; the auxiliary sensor reports an ambient temperature of 31.8℃ at t=10:00:01 and 31.5℃ at t=09:59:55; the system uses linear interpolation to calculate that the ambient temperature at t=10:00:00 is approximately 31.75℃; comparing the highest insulation layer temperature of 72.3℃ with 31.75℃, since 72.3℃ > 31.75℃, the current direction of heat radiation is determined to be positive, meaning heat is dissipating from the cable joint into the environment. This judgment will be used in the next step: applying a positive adjustment (such as adding the temperature difference × k1) to the insulation layer temperature value of 72.3℃ to estimate a predicted value closer to the actual temperature of the conductor crimping layer.

[0063] Specifically, time synchronization can be achieved using any technique that enables data time alignment, such as hardware synchronization (e.g., shared crystal oscillator, synchronization pulse triggering), software synchronization (timestamp calibration based on NTP / PTP protocol), or data post-processing synchronization (e.g., sliding window matching, dynamic time warping (DTW) algorithm). The key is to ensure that the data used for comparison belongs to the same physical moment. When comparing insulation layer temperature data, single-point temperature (e.g., reading from the sensor closest to the conductor), multi-point average, weighted average (weighted by radial depth), or maximum / minimum values ​​can be used. Specific strategies can be dynamically selected based on the joint structure, historical heat distribution characteristics, or safety margin requirements; all of these are reasonable applications of this solution. If multiple auxiliary temperature sensors are deployed (e.g., one each on the top, bottom, left, and right sides of the joint), their readings can be filtered, outliers removed, and the average taken as the final ambient temperature value to improve the reliability of the comparison benchmark. This approach is still within the reasonable scope of this step.

[0064] Specifically, based on the direction of thermal radiation, the real-time insulation layer temperature data is adjusted according to the temperature difference. If the thermal radiation is in a positive direction (heat transfer from the joint to the environment), the conductor crimping layer temperature should be higher than the insulation layer temperature, thus requiring an upward correction based on the insulation layer temperature. Conversely, if it is in a negative direction (heat transfer from the environment to the joint), the conductor crimping layer temperature is lower than the insulation layer temperature, requiring a downward correction. This direction-sensitive adjustment mechanism avoids systematic deviations caused by indiscriminate compensation.

[0065] Specifically, the predicted temperature change rate of the conductor crimp layer is determined based on the predicted temperature value. Here, the "predicted temperature value" is the estimated temperature of the conductor crimp layer obtained in the previous step after correction based on the insulation layer temperature and ambient temperature. The predicted temperature change rate reflects the time derivative of the actual heat accumulation or dissipation process, i.e., the rate of increase or decrease of the predicted temperature per unit time, demonstrating the system's ability to perceive the historical evolution of the thermal state. Real-time load current can be obtained through conventional power monitoring equipment such as current transformers (CTs), Hall sensors, or smart meters, representing the actual current flowing through the cable joint conductor. This current is the fundamental cause of conductor heating, and its square value is proportional to the Joule thermal power.

[0066] Specifically, the real-time load current can come from local sensors, the SCADA system of the upstream substation, the communication interface of the smart terminal, or the cloud dispatching platform, as long as it can be ensured that it is aligned with the temperature data in time and represents the actual current flowing through the connector.

[0067] In some embodiments of this application, before comparing the real-time insulation layer temperature data with the real-time ambient temperature value, the method further includes: comparing the ambient humidity value with a preset humidity value; if the ambient humidity value is greater than or equal to the preset humidity value, then a reliability check is performed on the real-time insulation layer temperature data and the real-time ambient temperature value; otherwise, no reliability check is performed; the reliability check specifically involves: comparing the detection data of the miniature temperature sensor or auxiliary sensor with the detection data of adjacent sensors to determine the degree of temperature deviation; if the degree of temperature deviation is greater than a preset deviation, then the corresponding real-time insulation layer temperature data or real-time ambient temperature value is determined to be unreliable and is discarded.

[0068] Specifically, this solution aims to improve the reliability of temperature monitoring data in high-humidity environments. Since excessively high humidity can cause condensation on sensor surfaces, moisture absorption by insulating materials, or dampness in measurement circuits, leading to temperature reading drift or distortion, this invention introduces a humidity threshold judgment mechanism: the reliability check of temperature data is only initiated when the ambient humidity reaches or exceeds a preset value, avoiding unnecessary computational overhead in dry environments; while under high-humidity conditions, data consistency verification between sensors promptly identifies and eliminates abnormal measurement points, ensuring the accuracy and validity of the data relied upon for subsequent thermal radiation direction determination and temperature prediction.

[0069] Specifically, before comparing the real-time insulation layer temperature data with the real-time ambient temperature value, the real-time ambient humidity value collected by the auxiliary sensor is first obtained and compared with a preset humidity threshold (e.g., 70% RH). If the real-time ambient humidity value is less than the preset humidity value, it indicates that the current environment is relatively dry, the risk of sensor moisture damage is low, and the data is highly reliable. In this case, the subsequent temperature comparison step can be directly performed without additional verification. If the real-time ambient humidity value is greater than or equal to the preset humidity value, it is considered that there is a possibility of inaccurate temperature measurement due to moisture interference, and the relevant temperature data needs to be verified for reliability.

[0070] The reliability verification method is as follows: For each miniature temperature sensor or auxiliary temperature sensor, its currently detected temperature data is compared horizontally with the detection data of other sensors of the same type and spatially adjacent to it. For example, the reading of a miniature temperature sensor within an insulating layer should be similar to the readings of other miniature temperature sensors in adjacent locations within the same insulating layer; similarly, the reading of an auxiliary ambient temperature sensor should be basically consistent with the readings of other auxiliary temperature sensors deployed nearby. The system calculates the deviation (i.e., the degree of temperature deviation) between the sensor reading and the readings of adjacent sensors of the same type. If the deviation exceeds a pre-set allowable range (e.g., ±3℃), the current output data of the sensor is deemed unreliable and is discarded or marked as invalid in subsequent processing, no longer participating in the determination of thermal radiation direction and temperature adjustment calculations. Through this mechanism, the risk of misjudgment caused by individual sensor failures or interference in high humidity environments is effectively suppressed, ensuring the robustness and accuracy of the entire temperature monitoring method.

[0071] Understandably, by introducing a preset threshold for ambient humidity, dynamic triggering of temperature data reliability checks is achieved. When the ambient humidity reaches or exceeds the preset value, it indicates a high moisture content, which may cause condensation on the sensor surface or dampness in the insulation layer, thus affecting the accuracy of temperature measurements. Initiating the reliability check process at this time allows for targeted screening of abnormal data. In low-humidity environments, environmental factors have less interference with the sensor, allowing the check to be skipped to improve data processing efficiency. The reliability check compares the detection data from the same sensor with data from adjacent sensors of the same type, using spatial correlation to determine the degree of temperature deviation. If the deviation exceeds a preset range, the data is deemed unreliable and discarded, effectively preventing abnormal data caused by single sensor failures or sudden changes in local environment from entering subsequent analysis processes, thus improving the reliability of the raw data.

[0072] In some embodiments of this application, the real-time insulation layer temperature data is compared with the real-time ambient temperature value, and the heat radiation direction of the cable joint is determined based on the comparison result. Specifically, the real-time insulation layer temperature data is compared with the real-time ambient temperature value. If the real-time insulation layer temperature data is greater than or equal to the real-time ambient temperature value, the heat radiation direction of the cable joint is determined to be the positive heat radiation direction; if the real-time insulation layer temperature data is less than the real-time ambient temperature value, the heat radiation direction of the cable joint is determined to be the negative heat radiation direction. The positive heat radiation direction refers to the cable joint transferring heat to the environment, and the negative heat radiation direction refers to the environment transferring heat to the cable joint.

[0073] Specifically, this scheme aims to accurately determine the direction of net heat flow between the cable joint and the surrounding environment, providing a physical basis for subsequent directional correction of the insulation temperature data. Since the actual temperature of the conductor crimp layer cannot be directly measured, and there is a thermal conduction relationship between it and the insulation layer, only by clarifying whether the heat is dissipated from the inside of the joint to the outside or transferred from the external environment to the inside of the joint can we reasonably infer whether the temperature of the conductor crimp layer is higher or lower than the insulation temperature, thereby determining the direction of temperature compensation.

[0074] Specifically, after synchronizing the real-time insulation layer temperature data with the real-time ambient temperature value, the system compares the two values. The "real-time insulation layer temperature data" typically refers to the temperature value obtained from a miniature temperature sensor embedded in the insulation layer, which can be the highest value at a single point, a value at a specific location, or a representative value from multiple measuring points. The "real-time ambient temperature value" comes from an auxiliary temperature sensor deployed in the external environment of the cable joint. If the real-time insulation layer temperature data is greater than or equal to the real-time ambient temperature value, it indicates that the internal temperature of the cable joint is higher than the external environment, and heat naturally flows from the high-temperature area to the low-temperature area, i.e., it is transferred from the cable joint to the surrounding environment. In this case, the direction of heat radiation is determined to be the positive direction of heat radiation. Conversely, if the real-time insulation layer temperature data is less than the real-time ambient temperature value, it indicates that the ambient temperature is higher, and heat may be transferred from the environment back to the cable joint. In this case, the direction of heat radiation is determined to be the negative direction of heat radiation.

[0075] In this context, positive thermal radiation is defined as the process of heat transfer from the cable joint to the environment, corresponding to a conductor crimping layer temperature that should be higher than the insulation layer temperature. Negative thermal radiation is defined as the process of heat transfer from the environment to the cable joint, corresponding to a conductor crimping layer temperature that may be lower than or close to the insulation layer temperature. This direction determination is directly used in subsequent steps to select the adjustment method (positive compensation or negative compensation) for the insulation layer temperature data, and is a key prerequisite for achieving accurate estimation of the conductor crimping layer predicted temperature.

[0076] Understandably, by directly comparing real-time insulation temperature data with real-time ambient temperature values, a criterion for determining the direction of thermal radiation was proposed, clearly defining the positive direction of thermal radiation (heat transfer from the cable joint to the environment) and the negative direction of thermal radiation (heat transfer from the environment to the cable joint). This distinction intuitively reflects the state of heat exchange between the cable joint and the environment.

[0077] In some embodiments of this application, the real-time insulation layer temperature data is adjusted based on the temperature difference according to the direction of thermal radiation. Specifically, if the direction of thermal radiation is positive, the real-time insulation layer temperature data is adjusted positively according to the temperature difference; if the direction of thermal radiation is negative, the real-time insulation layer temperature data is adjusted negatively according to the temperature difference.

[0078] Specifically, this scheme aims to provide physically grounded compensation for insulation temperature data based on the direction of heat flow, thereby more accurately estimating the actual temperature of the conductor crimping layer encased in insulation. When the joint heats up, the conductor temperature is higher than that of the insulation layer; when the ambient temperature is even higher, the insulation layer temperature may temporarily be higher than or close to that of the conductor. Therefore, the measured insulation temperature must be directionally adjusted according to the direction of heat radiation to avoid indiscriminate corrections that could lead to prediction errors.

[0079] After determining the direction of thermal radiation and calculating the temperature difference between the real-time insulation temperature and the ambient temperature, the system selects an appropriate adjustment method based on the direction of thermal radiation. If the direction of thermal radiation is positive (i.e., insulation temperature ≥ ambient temperature, heat is transferred from the cable joint to the environment), it indicates that the conductor crimp layer, as a heat source, should have a higher temperature than the insulation layer. Therefore, a positive adjustment needs to be made based on the real-time insulation temperature data, i.e., adding a compensation amount related to the temperature difference to make the predicted result closer to the actual conductor temperature. If the direction of thermal radiation is negative (i.e., insulation temperature < ambient temperature, heat is transferred from the environment to the cable joint), the conductor crimp layer may be in a cooled state or less affected by ambient heating, and its temperature may be lower than or equal to the insulation layer temperature. In this case, a negative adjustment should be made to the real-time insulation temperature data, i.e., subtracting a compensation amount related to the temperature difference to avoid overestimating the conductor temperature. This adjustment mechanism ensures that the predicted temperature value always conforms to the basic physical laws of heat conduction, improving the accuracy of subsequent temperature change rate calculations and anomaly detection.

[0080] Understandably, by making targeted positive or negative adjustments to the real-time insulation temperature data based on the direction of thermal radiation, deviations caused by environmental factors and the direction of heat transfer can be effectively corrected. When the direction of thermal radiation is positive, it indicates that the cable joint itself generates heat, and positive adjustments using the temperature difference (the difference between the real-time insulation temperature data and the real-time ambient temperature) can more accurately reflect the contribution of the actual heat accumulation caused by the internal losses of the joint to the insulation temperature. Conversely, when the direction of thermal radiation is negative, heat is transferred from the environment to the cable joint, and negative adjustments using the temperature difference can better offset the superimposed effect of high ambient temperature on the insulation temperature, making the adjusted insulation temperature data closer to its intrinsic temperature state under conditions unaffected by external dominant heat transfer. This direction-based dynamic adjustment mechanism further optimizes the quality of temperature parameters used as input for subsequent prediction models, providing a more reliable data foundation for improving the accuracy of conductor crimping layer temperature prediction, and ensuring the scientific validity and effectiveness of temperature data preprocessing under complex and variable heat exchange conditions.

[0081] In some embodiments of this application, the real-time insulation layer temperature data is adjusted based on the thermal radiation direction and the temperature difference to determine the predicted temperature value of the conductor crimping layer of the cable joint. Specifically: if the thermal radiation direction is positive, the predicted temperature value of the conductor crimping layer = real-time insulation layer temperature data + temperature difference × k1; if the thermal radiation direction is negative, the predicted temperature value of the conductor crimping layer = real-time insulation layer temperature data - temperature difference × k2; where k1 represents the adjustment coefficient for the positive thermal radiation direction, k2 represents the adjustment coefficient for the negative thermal radiation direction, and the values ​​of k1 and k2 are both in the range of 0-0.2.

[0082] Specifically, based on a clear understanding of the heat flow direction, this application introduces a proportionality coefficient that matches the physical properties to quantitatively compensate for the temperature of the insulation layer, thereby obtaining a predicted value that is closer to the true temperature of the conductor crimping layer.

[0083] After determining the direction of thermal radiation and the temperature difference (i.e., the absolute value of the difference between the real-time insulation temperature and the real-time ambient temperature), the system uses different calculation formulas to determine the predicted temperature value of the conductor crimp layer based on the direction of thermal radiation. When the direction of thermal radiation is positive, it indicates that the cable joint generates heat internally and dissipates it externally. The temperature of the conductor crimp layer should be higher than the temperature of the insulation layer. In this case, the predicted temperature value equals the real-time insulation temperature data plus the product of the temperature difference and the positive adjustment coefficient k1. When the direction of thermal radiation is negative, it indicates that the ambient temperature is higher than the insulation layer, and heat may be transferred from the outside. The temperature of the conductor crimp layer may be lower than the temperature of the insulation layer. In this case, the predicted temperature value equals the real-time insulation temperature data minus the product of the temperature difference and the negative adjustment coefficient k2. Here, k1 and k2 are dimensionless empirical coefficients, with a value range limited to 0 to 0.2. This range is a reasonable interval determined based on a large amount of experimental data and engineering experience, and can effectively reflect the typical temperature difference ratio between the conductor and the insulation layer under different cable joint structures. The specific values ​​of k1 and k2 need to be determined in advance through laboratory temperature rise tests or on-site calibration, based on factors such as the thermal conductivity of the insulation material used in the cable joint, the thickness of the insulation layer, and the crimping structure. Different coefficient sets can be configured for different types of joints. This parameterized adjustment method based on physical characteristics ensures the universality of the prediction model.

[0084] Understandably, by introducing thermal radiation direction adjustment coefficients k1 and k2, and combining them with the temperature difference to construct a specific formula for calculating the predicted temperature, a quantitative prediction of the conductor crimping layer temperature is achieved. When the thermal radiation direction is positive, a positive adjustment formula of "real-time insulation layer temperature data + temperature difference × k1" is used, where k1, as the positive adjustment coefficient, can proportionally map the portion of the heat accumulated in the insulation layer dominated by internal joint losses to the conductor crimping layer temperature based on the thermal conductivity characteristics of the insulation material (such as thermal conductivity and thickness), ensuring accurate quantification of the contribution of internal heat sources to the crimping layer temperature. When the thermal radiation direction is negative, a negative adjustment formula of "real-time insulation layer temperature data - temperature difference × k2" is used, where k2, as the negative adjustment coefficient, can proportionally deduct the heat transferred from the environment to the joint from the insulation layer temperature based on the insulation material parameters, thereby eliminating the interference of environmental heat input on the intrinsic temperature of the crimping layer. The values ​​of k1 and k2 are limited to the range of 0-0.2 and calibrated experimentally. This avoids prediction distortion caused by over-adjustment and allows for personalized adaptation based on the physical characteristics of different cable joints, making the prediction formula both universal and specific. This dual quantitative adjustment based on direction and coefficients transforms the abstract influence of heat transfer into a calculable mathematical model, providing a standardized and operable implementation path for accurate prediction of conductor crimp layer temperature.

[0085] In some embodiments of this application, when determining the predicted temperature change rate of the conductor crimping layer based on the predicted temperature value, the predicted temperature change rate is determined according to the following formula: ΔTp = (Tp t -Tp t-1 ) / Δt; where ΔTp represents the predicted temperature change rate, Tpt represents the predicted temperature value at time t, Tpt-1 represents the predicted temperature value at time t-1, and Δt represents the time interval.

[0086] Specifically, this application quantifies the temperature change trend of the conductor press-fit layer over time by using predicted temperature values ​​at continuous intervals, thereby obtaining a predicted temperature change rate that reflects its actual thermal dynamic behavior. This change rate is compared with the theoretical temperature rise rate calculated based on current, and is a key basis for subsequent judgment on whether there are unexpected thermal anomalies.

[0087] Specifically, after obtaining the predicted temperature value Tpt of the conductor crimp layer at the current time t and the predicted temperature value Tpt-1 at the previous time t-1, the system calculates the rate of increase or decrease of the predicted temperature per unit time, i.e., the predicted temperature change rate ΔTp, by dividing the difference between the two by the corresponding time interval Δt. Here, Tpt and Tpt-1 are both estimated values ​​of the conductor crimp layer temperature after correction in the aforementioned steps, and Δt is the time interval between two temperature predictions, usually determined by the system sampling period (e.g., 30 seconds, 1 minute, etc.).

[0088] Understandably, by constructing the formula "ΔTp = (Tpt - Tpt-1) / Δt" to calculate the predicted temperature change rate, a quantitative characterization of the dynamic trend of the conductor crimp layer temperature is achieved. In the formula, Tpt and Tpt-1 represent the predicted temperature values ​​at two consecutive moments (time t and time t-1), respectively. The difference between the two directly reflects the absolute change in temperature within a unit time interval Δt. By comparing it with the time interval Δt, the temperature change is transformed from a "static value" into a "dynamic rate" indicator. This time-series-based rate of change calculation can keenly capture the instantaneous rise and fall trend of the conductor crimp layer temperature. For example, when ΔTp is positive and has a large absolute value, it indicates that the crimp layer temperature is in a rapid rising phase, which may indicate an increase in the internal contact resistance of the joint or an increased risk of local overheating. When ΔTp is negative, it reflects that the temperature is gradually decreasing, and it can be combined with environmental conditions to determine whether it is a normal heat dissipation process or an abnormal cooling phenomenon. Compared to a single temperature threshold judgment, predicting the temperature change rate ΔTp better reflects the "acceleration" characteristic of temperature change, providing a key dynamic basis for early fault warning. By continuously monitoring the change rate and setting thresholds (such as triggering an early warning when a certain safe change rate threshold is exceeded), the development trend of potential thermal hazards can be identified in advance before the temperature reaches an absolute danger value, giving maintenance personnel more time to deal with the situation.

[0089] In some embodiments of this application, the real-time temperature change rate of the conductor crimping layer is determined based on the real-time load current, specifically by: calculating the square of the real-time current of the cable joint based on the real-time load current; and determining the real-time temperature change rate of the conductor crimping layer based on the square of the real-time current; wherein the real-time temperature change rate is determined according to the following formula: ΔTr=KI 2 Where ΔTr represents the real-time temperature change rate, K represents the real-time temperature change rate adjustment coefficient, and I represents the real-time load current.

[0090] Specifically, this application, based on the Joule heating principle, establishes a theoretical temperature rise rate model of the conductor press-fit layer under ideal normal conditions using real-time load current, serving as a benchmark for determining whether abnormal heating exists. Since conductor heating is mainly generated by current passing through resistance, and its thermal power is proportional to the square of the current, the theoretically expected temperature change trend can be derived from the current, which can then be compared with the actual observed thermal response.

[0091] Specifically, the real-time load current I flowing through the cable joint is first obtained, and its square value I² is calculated. According to Joule's law, the heat power generated by the conductor is proportional to I², while the rate of temperature change depends on the relationship between this heat power and the conductor's heat capacity. Based on this, a comprehensive adjustment coefficient K is introduced to convert the square of the current into the real-time temperature change rate ΔTr of the conductor crimp layer, calculated as ΔTr = K·I². Here, K is a parameter related to the conductor's physical properties, its value determined by the effective resistance, mass, and specific heat capacity of the conductor crimp layer, reflecting the rate of temperature rise caused by unit Joule heat. This coefficient can be predetermined through theoretical calculation or experimental calibration and can be configured for cable joints of different specifications or materials.

[0092] Specifically, according to the two known heat formulas Q=I 2 Rt and Q = mcΔT, the rate of change of temperature is related to the rate of change of the square of the current multiplied by the time. Q is heat, I is current, R is resistance, t is the time of current flow, m represents mass in kilograms (kg), c represents specific heat capacity, and ΔT represents the change in temperature.

[0093] Combining the two formulas, we get:

[0094] .

[0095] Differentiating with respect to time to obtain the rate of temperature change:

[0096] ;

[0097] Therefore, it can be seen that the real-time temperature change rate adjustment coefficient is related to the cable resistance, cable quality, and cable specific heat capacity.

[0098] Understandably, by establishing a real-time temperature change rate calculation model of "ΔTr=KI²", a direct correlation and quantification of the dynamic temperature change of the conductor crimp layer based on the real-time load current is achieved. In the formula, I represents the real-time load current, and its square term I² is directly related to the Joule heat loss of the cable joint (Q=I²Rt), which is the core driving factor causing the temperature change of the conductor crimp layer. K, as the real-time temperature change rate adjustment coefficient, comprehensively considers the influence of key physical parameters such as the resistance, mass m, and specific heat capacity c of the conductor crimp layer on the temperature change rate. Resistance determines the heat generated per unit time, while mass and specific heat capacity jointly determine the ease with which the temperature rises after an object absorbs heat. Therefore, the introduction of the K value enables the model to more accurately match the thermal characteristics of cable joints of different materials and structures. This calculation method, which directly links real-time load current to the rate of temperature change, can quickly respond to the immediate impact of current fluctuations on the temperature of the press-fit layer: when the load current I increases, I² increases quadratically, and ΔTr also increases significantly, intuitively reflecting the rapid temperature rise trend that may be caused by sudden current changes; conversely, when the current decreases, ΔTr also decreases accordingly.

[0099] In some embodiments of this application, when determining the ratio of the difference between the predicted temperature change rate and the real-time temperature change rate, the ratio of the difference is determined according to the following formula: B = |predicted temperature change rate - real-time temperature change rate| / real-time temperature change rate; where B represents the ratio of the difference.

[0100] Understandably, by introducing the formula for calculating the difference ratio B, a quantitative assessment of the deviation between the predicted temperature change rate and the real-time temperature change rate is achieved. In the formula, the numerator "|predicted temperature change rate - real-time temperature change rate|" represents the absolute difference between the two, clearly reflecting the deviation between the predicted and real-time values. The denominator uses the real-time temperature change rate ΔTr as a benchmark for normalization, allowing the B value to eliminate the influence of the magnitude of the temperature change rate itself, and more objectively measure the degree of relative deviation. For example, when the real-time temperature change rate ΔTr is large (such as during a rapid temperature rise due to a sudden increase in current), even if the absolute difference is large, a small B value still indicates a high degree of fit between the prediction model and the actual situation; conversely, if ΔTr is small but the B value is significant, it suggests a large relative error in the prediction. This quantification of relative deviation provides a clear indicator for judging the accuracy and reliability of the prediction model: when the B value is within the preset threshold range, it indicates that the predicted temperature change rate can follow the real-time temperature change rate well, and the model has high effectiveness; when the B value exceeds the threshold, it indicates that there is a significant deviation in the prediction, which may be due to factors such as model parameter drift, external environmental interference, or changes in the characteristics of the cable joint itself. At this time, the system can trigger a calibration mechanism for the prediction model or issue an early warning signal. Compared with simply comparing absolute differences, the design of this difference ratio B is more practical for engineering, and can adapt to the dynamic range of temperature change rates under different load conditions. This provides an important guarantee for the accuracy of subsequent fault early warning based on predicted temperature, and helps maintenance personnel to more accurately identify potential risks.

[0101] In some embodiments of this application, determining whether a cable joint has an abnormal temperature monitoring based on the difference ratio specifically involves: pre-setting a first difference ratio and a second difference ratio, wherein the first difference ratio is less than the second difference ratio; determining whether a cable joint has an abnormal temperature monitoring based on the relationship between the difference ratio and the first and second difference ratios, and determining the abnormality level; if the difference ratio is less than or equal to the first difference ratio, then determining that the cable joint temperature is normal; if the difference ratio is greater than the first difference ratio and the difference ratio is less than or equal to the second difference ratio, then determining that the cable joint temperature monitoring is slightly abnormal; if the difference ratio is greater than the second difference ratio, then determining that the cable joint temperature monitoring is severely abnormal.

[0102] In this embodiment, the first difference ratio and the second difference ratio are not set arbitrarily, but can be determined based on the following criteria and engineering practice.

[0103] For example, based on the normal thermo-electric characteristic calibration data of cable joints: temperature rise tests are conducted on cable joints of the same type and specification in the laboratory or on-site under standard operating conditions (such as rated current, ambient temperature and humidity, and good crimping condition). A large amount of comparative data between the "predicted temperature change rate" and the "real-time temperature change rate calculated based on current" is collected, and the distribution range of the difference ratio during normal operation is statistically analyzed. The first difference ratio is usually set near the upper limit of this distribution (e.g., 95% confidence interval) to cover normal fluctuations.

[0104] Alternatively, thresholds can be set based on simulation test results of typical failure modes: for common abnormal situations (such as loose crimping, contact surface oxidation, partial discharge, etc.), mild and severe failure samples are artificially constructed, and the evolution characteristics of the difference ratio during operation are recorded. The second difference ratio is then set at a clear dividing point between mild and severe anomalies to ensure effective differentiation of different risk levels.

[0105] Furthermore, thresholds can be determined based on power equipment operation safety regulations and maintenance experience. Referring to relevant national or industry standards (such as DL / T and IEC regulations regarding cable joint temperature rise limits and fault warning thresholds), and combining this with fault cases and handling thresholds accumulated by power grid companies in long-term operation and maintenance, the ratio of the first and second differences can be calibrated to ensure it meets the acceptable risk control level for actual engineering projects.

[0106] Understandably, by setting two thresholds—a first difference ratio and a second difference ratio—and comparing the difference ratio B with these two thresholds, a graded judgment of the degree of abnormality in cable joint temperature monitoring is achieved. This grading mechanism first clarifies the standard for judging normal temperature by stating that "the difference ratio is less than or equal to the first difference ratio," providing a benchmark for stable system operation. Then, when "the difference ratio is greater than the first difference ratio and less than or equal to the second difference ratio," it is defined as "mild anomaly," meaning that the prediction model has deviated somewhat from the actual situation, but has not yet reached a severe level. This provides early warning for maintenance personnel, facilitating timely preliminary investigation and model fine-tuning to prevent further escalation of the anomaly. When "the difference ratio is greater than the second difference ratio," it is judged as "severe anomaly," indicating that the deviation between prediction and reality is quite significant, potentially suggesting a serious risk of failure in the cable joint or a major problem with the prediction model, requiring immediate triggering of a high-level warning and emergency handling measures. This multi-level anomaly classification method, compared to the simple binary judgment of "normal / abnormal", can more accurately reflect the complex situation of temperature changes, making operation and maintenance decisions more hierarchical and targeted. It avoids overreacting to minor deviations and ensures timely response to serious anomalies.

[0107] The present invention also discloses a cable connector, which can be used to monitor temperature using the above-mentioned cable connector temperature monitoring method. The cable connector includes, from the inside out, a conductor crimping layer, an insulation layer, a shielding layer and a sealing protection layer, and a plurality of miniature temperature sensors are embedded in the insulation layer.

[0108] This invention provides a cable connector structure adapted to the aforementioned temperature monitoring method, enabling temperature monitoring at the physical level. Since the conductor crimping layer is encased in multiple layers of material, direct external temperature measurement is impossible. Sensors must be integrated into critical locations during manufacturing or installation to obtain effective data reflecting the internal thermal state. By pre-embedding miniature temperature sensors within the insulation layer and clearly defining the arrangement order of each functional layer, the sensing element is ensured to be in a suitable position that can detect conductor heating without affecting electrical insulation performance, providing the hardware foundation for the entire monitoring method.

[0109] This cable joint employs a typical multi-layered concentric structure, comprising, from the inside out, a conductor crimping layer, an insulation layer, a shielding layer, and a sealing protective layer. The conductor crimping layer provides the electrical connection between the two cable conductors; the insulation layer covers the conductor crimping layer and serves as the primary insulation; the shielding layer provides a uniform electric field and a grounding path; and the sealing protective layer protects the internal structure from external environmental factors such as moisture and dust. During manufacturing, several miniature temperature sensors are embedded in different locations within the insulation layer, such as near the inner region of the conductor crimping layer or in key hot spots distributed along the axial direction. These sensors are small, high-voltage resistant, and compatible with the insulation material, enabling real-time acquisition of temperature data within the insulation layer without affecting the electrical performance and mechanical strength of the cable joint. This structural design provides a reliable source for the "real-time insulation layer temperature data" required in the aforementioned temperature monitoring methods, thus achieving indirect but effective monitoring of the conductor crimping layer temperature.

[0110] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for monitoring the temperature of a cable joint, characterized in that, include: Several miniature temperature sensors are pre-embedded at different positions within the insulation layer of the cable joint. Real-time insulation layer temperature data of the cable joint is obtained based on the miniature temperature sensors. An auxiliary sensor is deployed in the external environment of the cable joint to obtain real-time environmental data of the cable joint based on the auxiliary sensor. The real-time environmental data includes real-time environmental temperature value and real-time environmental humidity value. The real-time insulation layer temperature data and real-time environmental data are time-synchronized, and after processing, the real-time insulation layer temperature data is compared with the real-time environmental temperature value. The direction of heat radiation of the cable joint is determined based on the comparison result. The temperature difference between the real-time insulation layer temperature data and the real-time ambient temperature value is determined. Based on the direction of thermal radiation, the real-time insulation layer temperature data is adjusted according to the temperature difference to determine the predicted temperature value of the conductor crimping layer of the cable joint. The predicted temperature change rate of the conductor crimping layer is determined based on the predicted temperature value; the real-time load current of the cable joint is obtained, and the real-time temperature change rate of the conductor crimping layer is determined based on the real-time load current. Determine the ratio of the difference between the predicted temperature change rate and the real-time temperature change rate, and determine whether the cable joint is abnormal in temperature monitoring based on the ratio of the difference; Before comparing the real-time insulation layer temperature data with the real-time ambient temperature value, the process also includes: The ambient humidity value is compared with the preset humidity value. If the ambient humidity value is greater than or equal to the preset humidity value, the reliability of the real-time insulation layer temperature data and the real-time ambient temperature value is verified. Otherwise, no credibility check will be performed; The credibility test is carried out by comparing the detection data of the miniature temperature sensor or auxiliary sensor with the detection data of the adjacent sensor to determine the degree of temperature deviation. If the degree of temperature deviation is greater than the preset deviation, the corresponding real-time insulation layer temperature data or real-time ambient temperature value is determined to be unreliable and is rejected. The real-time insulation layer temperature data is compared with the real-time ambient temperature value, and the direction of heat radiation from the cable joint is determined based on the comparison result. Specifically: The real-time insulation layer temperature data is compared with the real-time ambient temperature value. If the real-time insulation layer temperature data is greater than or equal to the real-time ambient temperature value, the heat radiation direction of the cable joint is determined to be the positive heat radiation direction. If the real-time insulation layer temperature data is less than the real-time ambient temperature value, then the heat radiation direction of the cable joint is determined to be the negative heat radiation direction. Wherein, the positive direction of thermal radiation is the transfer of heat from the cable joint to the environment, and the negative direction of thermal radiation is the transfer of heat from the environment to the cable joint; Based on the direction of thermal radiation, the real-time insulation layer temperature data is adjusted according to the temperature difference, specifically as follows: If the direction of thermal radiation is the positive direction of thermal radiation, then the real-time insulation layer temperature data is adjusted positively based on the temperature difference. If the direction of thermal radiation is the negative direction of thermal radiation, then the real-time insulation layer temperature data is adjusted negatively according to the temperature difference. Based on the direction of thermal radiation, the real-time insulation layer temperature data is adjusted according to the temperature difference to determine the predicted temperature value of the conductor crimping layer of the cable joint, specifically: If the direction of thermal radiation is the positive direction of thermal radiation, then the predicted temperature value of the conductor crimping layer = real-time insulation layer temperature data + temperature difference × k1; If the direction of thermal radiation is the negative direction of thermal radiation, then the predicted temperature value of the conductor crimping layer = real-time insulation layer temperature data - temperature difference × k2; Where k1 represents the positive direction adjustment coefficient of thermal radiation and k2 represents the negative direction adjustment coefficient of thermal radiation, and the values ​​of k1 and k2 are both in the range of 0-0.

2.

2. The temperature monitoring method for cable joints according to claim 1, characterized in that, When determining the predicted temperature change rate of the conductor crimping layer based on the predicted temperature value, the predicted temperature change rate is determined according to the following formula: ΔTp=(Tp t -Tp t-1 ) / Δt; Where ΔTp represents the predicted rate of temperature change, Tp t Tp represents the predicted temperature value at time t. t-1 Δt represents the predicted temperature value at time t-1, and Δt represents the time interval.

3. The temperature monitoring method for cable joints according to claim 1, characterized in that, The real-time temperature change rate of the conductor crimping layer is determined based on the real-time load current, specifically as follows: Calculate the square of the real-time current at the cable joint based on the real-time load current. The real-time temperature change rate of the conductor crimping layer is determined based on the square of the real-time current. The real-time temperature change rate is determined according to the following formula: ΔTr=KI 2 ; Where ΔTr represents the real-time temperature change rate, K represents the real-time temperature change rate adjustment coefficient, and I represents the real-time load current.

4. The method for monitoring the temperature of a cable joint according to claim 1, characterized in that, When determining the ratio of the difference between the predicted temperature change rate and the real-time temperature change rate, the ratio of the difference is determined according to the following formula: B = |Predicted temperature change rate - Real-time temperature change rate| / Real-time temperature change rate; Where B represents the difference ratio.

5. The method for monitoring the temperature of a cable joint according to claim 1, characterized in that, The cable joint is determined to be abnormal in temperature monitoring based on the aforementioned difference ratio, specifically as follows: A first difference ratio and a second difference ratio are preset, wherein the first difference ratio is less than the second difference ratio; The relationship between the stated difference ratio and the first and second difference ratios determines whether the cable joint has an abnormal temperature monitoring and determines the level of abnormality. If the difference ratio is less than or equal to the first difference ratio, then the cable joint temperature is determined to be normal. If the difference ratio is greater than the first difference ratio and the difference ratio is less than or equal to the second difference ratio, then the cable joint temperature monitoring is determined to be slightly abnormal. If the difference ratio is greater than the second difference ratio, then the cable joint temperature monitoring is determined to be severely abnormal.

6. A cable connector, said cable connector being used for temperature monitoring using the temperature monitoring method for cable connectors as described in any one of claims 1-5, characterized in that, The cable connector includes, from the inside out, a conductor crimping layer, an insulation layer, a shielding layer, and a sealing protective layer, with several miniature temperature sensors embedded in the insulation layer.

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