A method for monitoring the thermal response characteristics of a cable branch box joint and early warning of local deterioration

Abstract

The application discloses a kind of cable branch box joint thermal response characteristic monitoring and local deterioration early warning method, belong to power equipment state monitoring and fault early warning technical field, when the temperature time series of each joint is collected when load disturbance event occurs, respectively using exponential fitting model to carry out fitting to the temperature rising process and temperature falling process, extract temperature rising time constant, temperature falling time constant, thermal response lag time, thermal recovery rate and multi-dimensional thermal response characteristic parameters such as overshoot, and according to the abnormal deviation of each parameter, the health status of joint is comprehensively evaluated;The application can effectively identify early abnormal state such as contact degradation, provide reliable technical support for the state monitoring and fault early warning of cable branch box, further through the horizontal comparison of the offset index of multiple joints in the same box, relative diagnosis is carried out with median in the same box as reference benchmark, effectively eliminate the common mode influence of ambient temperature and load fluctuation.

Description

Technical Field

[0001] This invention belongs to the field of power equipment condition monitoring and fault early warning technology. Specifically, it relates to a method for monitoring the thermal response characteristics of cable branch box joints and providing early warning of local degradation. Background Technology

[0002] Cable distribution boxes are widely used in power distribution networks to realize line branching, connection, and power distribution. Multiple cable joints are typically installed inside cable distribution boxes. During long-term operation, these joints are susceptible to localized heating due to factors such as changes in contact resistance, loose crimping, oxidation and corrosion, insulation aging, changes in environmental heat dissipation conditions, and load fluctuations.

[0003] Existing cable joint monitoring methods mainly include temperature threshold alarms, predictive analysis based on temperature rise models, and manual inspections. These methods have the following shortcomings: First, the simple temperature threshold method is easily affected by ambient temperature and load fluctuations, resulting in numerous false alarms and missed alarms. Second, temperature rise models often rely on absolute temperature deviation as the primary criterion, making it difficult to accurately characterize the thermal inertia and response characteristics of the joint under dynamic load disturbances. Third, manual inspections suffer from poor real-time performance and struggle to continuously and synchronously identify the status of multiple joints.

[0004] Therefore, there is an urgent need for a technical solution that can accurately identify and provide graded early warning of localized degradation by starting from dynamic thermal response characteristics and combining the relative differences of multiple joints in the same enclosure. Summary of the Invention

[0005] To address the above deficiencies, this invention provides a method for monitoring the thermal response characteristics of cable branch box joints and providing early warning of localized degradation, comprising the following steps:

[0006] S1. Collect operational data

[0007] Collect operational data from multiple cable joints within the cable branch box. The operational data includes at least the joint surface temperature, ambient temperature, and line current.

[0008] The operational data is continuously collected according to a preset sampling period to form a time series dataset.

[0009]

[0010] in, Indicates the first Surface temperature of each cable joint Indicates ambient temperature. Indicates the line current;

[0011] S2, Identify Load Disturbance Window

[0012] Based on the aforementioned operational data, a load disturbance window is identified. When the change in line current and / or its rate of change meets a preset threshold condition, it is determined that the system has entered the load disturbance window, which can be expressed as follows:

[0013]

[0014] And / or:

[0015]

[0016] in, The threshold for the change in current. The threshold for the rate of change of current. The sampling interval;

[0017] Furthermore, it can also be confirmed by combining the duration condition, that is, when the above conditions are met continuously for more than the preset duration, the corresponding time period is determined as the effective load disturbance window;

[0018] S3. Extract thermal response features and construct thermal response feature vector.

[0019] The thermal response features of each cable joint are extracted within the load disturbance window. The thermal response features include one or more of the following: initial temperature rise slope, temperature rise amplitude, thermal response hysteresis time, temperature rise time constant, cooling time constant, thermal recovery rate, overshoot, and response inflection point position. A thermal response feature vector is constructed.

[0020] Among them, the The thermal response feature vector of a single joint can be represented as:

[0021]

[0022] in, Indicates the first Thermal response characteristics;

[0023] Furthermore, the thermal response characteristics are as follows:

[0024] Initial heating slope It can be represented as:

[0025]

[0026] in, These are the two sampling times at the initial stage of the disturbance;

[0027] Temperature rise It can be represented as:

[0028]

[0029] in, The temperature peak within the disturbance window, The reference temperature before the disturbance;

[0030] Thermal response hysteresis time can be defined as the time difference between the moment when the line current is disturbed and the moment when the joint temperature begins to deviate significantly:

[0031]

[0032] in, This represents the initial moment of the current disturbance. for The moment when the connector temperature begins to respond;

[0033] Under the exponential fitting model, as the load increases, the joint temperature rises exponentially, and the heating process can be expressed as:

[0034]

[0035] in, For the exponential decay term of a first-order thermal system, Self-heating start time The time elapsed since then The heating time constant (physically reflecting the product of the joint's heat capacity and thermal resistance, determining the rate of temperature rise response) is when... At that time, the temperature rise reaches the final temperature rise value. Approximately 63.2%, The smaller the value, the faster the joint's thermal response and the steeper the heating process. (The entire bracketed term...) The normalized first-order step response has a value from Monotonically increasing, approaching 1.

[0036] After the load decreases, the joint temperature decays exponentially, and the cooling process can be represented as:

[0037]

[0038] in, For connector peak temperature, At peak time, The cooling time constant;

[0039] It should be noted that the exponential fitting model is based on the principle of thermal equivalent circuit, treating the cable joint as a first-order thermal system, and the thermal resistance of the joint... With heat capacity The RC circuit is formed, and its temperature response to a step thermal excitation follows a first-order exponential function law, with the corresponding thermal time constant being... .

[0040] The thermal recovery rate can be expressed as:

[0041]

[0042] in, The measured temperature of the joint at that moment. For a fixed reference time, and To ensure consistent comparison benchmarks, a uniform value is used for each connector to set the preset time window length.

[0043] Overshoot can be expressed as:

[0044]

[0045] in, The steady-state temperature after the disturbance has stabilized. The steady-state temperature before the disturbance;

[0046] Response inflection point position For the connector within the load disturbance window During the temperature rise process, the moment when the temperature increment between adjacent sampling times changes from increasing to decreasing. The temperature increment between adjacent sampling times is defined as:

[0047]

[0048] in, The connector collected in S1 Temperature data; when both conditions are met, and hour, This refers to the inflection point of the response, reflecting the time point at which the temperature rise rate reaches its peak. For joints with good contact, the inflection point appears earlier and is less pronounced, while for joints with loose structures, the inflection point is delayed and its amplitude increases due to fluctuations in thermal resistance.

[0049] S4. Establish a health baseline model

[0050] Based on historical normal operation data, a health baseline model is established for each cable joint. The mean and standard deviation of each thermal response characteristic are statistically analyzed to form:

[0051]

[0052] in, The mean, The standard deviation is... Indicates the first The baseline mean of class features, Its corresponding standard deviation;

[0053] Furthermore, the health baseline model can be updated using a sliding window approach to adapt to the slow changes in the normal state during long-term operation;

[0054] S5. Calculate the thermal response offset index.

[0055] The current thermal response characteristics are compared with the healthy baseline model to calculate the thermal response offset index, where the offset of each characteristic is:

[0056]

[0057] in, This represents the current thermal response characteristic value. It is a very small positive number, used to avoid the denominator being zero;

[0058] The weighted summation of each feature offset yields the comprehensive thermal response offset index, which is:

[0059]

[0060] in, Indicates the first The weights corresponding to the heat response features, and satisfying the following:

[0061]

[0062] Furthermore, the weights can be pre-set based on the importance of the features in identifying degradation, or obtained through training with historical samples;

[0063] S6. Perform in-box relative diagnostics

[0064] The thermal response offset indices of multiple cable joints within the same cable branch box are compared, preferably using the median, mean, or reference joint as a benchmark to calculate the relative offset value.

[0065]

[0066] in, The reference benchmark value can be the median, mean, or offset index corresponding to the healthy connector;

[0067] When the relative offset value of a certain connector is significantly higher than that of other connectors in the same box, the connector is judged as an abnormal connector to reduce misjudgment caused by common mode factors such as changes in ambient temperature and overall load fluctuations.

[0068] S7. Identify localized degradation conditions

[0069] Local degradation states are identified based on thermal response offset index and relative diagnostic results within the same enclosure. These local degradation states include one or more of the following: contact degradation type local degradation, heat dissipation obstruction type local degradation, structural loosening type local degradation, and continuous evolution type local degradation.

[0070] Classification can be made based on the direction of thermal response characteristic offset:

[0071] When the initial heating slope increases, the thermal response hysteresis time decreases, and the temperature rise amplitude increases, it is determined to be a contact degradation type of localized deterioration.

[0072] When the cooling time constant increases and the thermal recovery rate decreases, it is determined to be a localized degradation due to impeded heat dissipation.

[0073] When the thermal response curve shows increased fluctuations, increased overshoot, or significant shift in the response inflection point, it can be identified as localized deterioration due to structural loosening.

[0074] When the offset index continues to increase within multiple consecutive load disturbance windows, it can be identified as a continuously evolving type of local degradation.

[0075] Furthermore, the confidence level of the degradation type can be output by combining threshold rules or classification models;

[0076] S8, Output graded local degradation early warning results

[0077] The warning results are output based on the local degradation status. These warning results include at least five levels: normal, slightly abnormal, moderately abnormal, severely abnormal, and requiring immediate review. The levels are determined based on the comprehensive thermal response offset index, relative offset value, and trend changes across multiple consecutive load disturbance windows. For example, if a joint meets any of the following conditions, its warning level can be increased:

[0078] 1) The overall thermal response offset index exceeds the corresponding threshold;

[0079] 2) The relative offset value exceeds the in-box anomaly threshold;

[0080] 3) The offset index continues to rise within multiple consecutive load disturbance windows;

[0081] 4) The same degradation judgment result appears continuously in multiple windows.

[0082] Compared with the prior art, the present invention has the following advantages:

[0083] 1. The joint thermal response feature vector can be extracted based on the load disturbance process to reflect the differences in dynamic thermal behavior;

[0084] 2. Improve the sensitivity of abnormal state identification by using a healthy baseline model and standardized offset calculation;

[0085] 3. Reduce environmental and load common-mode interference through co-chamber-based diagnostics, thereby reducing false alarms;

[0086] 4. Improve the targeted nature of operation and maintenance by identifying and classifying degradation types and providing early warnings;

[0087] 5. Improve the stability and reliability of early warning by fusing trends through continuous load disturbance windows. Detailed Implementation

[0088] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0089] Example 1

[0090] This embodiment provides a method for monitoring the thermal response characteristics of cable branch box joints and providing early warning of local degradation. It is based on a 10kV distribution line three-joint branch box and is tested during the load rise disturbance process. It is used to identify contact degradation-type local degradation and includes the following steps (it should be noted that, in order to avoid redundant description, when referring to the above corresponding formulas, the formula content is not repeated, but the data is directly substituted into the formula for calculation):

[0091] S1. Collect operational data

[0092] Three cable joints, designated Joint A, Joint B, and Joint C, are installed inside the cable branch box of a 10kV distribution line. Surface temperature sensors are installed on all three joints. An ambient temperature sensor is installed inside the branch box. A current acquisition module is installed on the incoming line side. The system sampling period is set to 5 seconds. During operation from 08:10 to 09:30 on March 18, 2025, the system continuously collected operational data according to the preset sampling period, forming a time-series dataset.

[0093]

[0094] Among them, ambient temperature Maintaining the temperature between 18.2℃ and 19.0℃, the line current... It gradually increased from 122A to 178A.

[0095] S2, Identify Load Disturbance Window

[0096] The system monitors the line current time series in real time and calculates the current change at adjacent sampling times:

[0097]

[0098] At 08:42, the line current showed a significant step increase, with both the amount and rate of change exceeding the preset threshold. This condition was met for approximately 12 minutes, satisfying the confirmation criteria for the effective load disturbance window. The system determined the period from 08:42 to 08:54 as the effective load disturbance window for this time.

[0099] S3. Extract thermal response features and construct thermal response feature vector.

[0100] Within the aforementioned load disturbance window, the system extracts thermal response features from joints A, B, and C respectively, and constructs thermal response feature vectors, as detailed below:

[0101] P1, Initial heating slope

[0102] Within the initial 180 seconds of the disturbance, the temperatures of the three joints rose from 34.6℃ to 38.0℃ at joint A, from 35.1℃ to 38.7℃ at joint B, and from 35.0℃ to 42.7℃ at joint C. Substituting these values ​​into...

[0103]

[0104]

[0105]

[0106] The initial heating slope of joint C is about 2.2 times that of joints A and B, indicating that its thermal response rate is significantly higher.

[0107] P2, temperature rise value

[0108] According to equation (2), calculate the temperature rise of each joint:

[0109]

[0110]

[0111]

[0112] P3, Thermal response hysteresis time

[0113] Set temperature response threshold Taking the disturbance initiation time t0 (08:42) as the zero point, the temperature time series of each joint is retrieved point by point, and the temperature rise of each joint is recorded as first satisfying the condition. The moment ;

[0114] Connector A: Response judgment temperature is Temperature time series shows that connector A is in When this temperature is first reached, then Substitute get:

[0115]

[0116] Similarly, for connector B: the response determination temperature is... ,exist When this temperature is first reached, then Substitute get:

[0117]

[0118] Connector C: Response determination temperature is ,exist When this temperature is first reached, then Substitute get:

[0119]

[0120] It can be seen that the hysteresis time of joint C is significantly shorter than that of joints A and B, indicating that its thermal inertia is significantly reduced.

[0121] P4. Heating time constant and cooling time constant

[0122] Substitution The fitting results for the three connectors are as follows:

[0123] Heating process:

[0124]

[0125]

[0126]

[0127] Cooling process:

[0128]

[0129]

[0130]

[0131] The heating time constant (118s) and cooling time constant (174s) of joint C are significantly lower than those of joints A and B, indicating that its heat capacity is significantly reduced.

[0132] P5, thermal recovery rate

[0133] According to equation (6), take The thermal recovery rates of the three joints are calculated as follows:

[0134]

[0135]

[0136]

[0137] It can be seen that the heat recovery rate of connector C is only about one-third that of connectors A and B, indicating that its heat dissipation capacity has decreased significantly.

[0138] P6, Overshoot

[0139] according to The overshoot of the three connectors is calculated as follows:

[0140]

[0141]

[0142]

[0143] in, Take the average value when the temperature curve tends to stabilize after the disturbance ends. In this embodiment, let formula (4) set... To obtain, that is ;

[0144] Based on the characteristics of P1-P6 mentioned above, a thermal response feature vector for each joint is constructed. Used for subsequent offset index calculation.

[0145] S4. Establish a health baseline model

[0146] The system retrieved historical data from joints A, B, and C during the previous 21 consecutive days of normal operation. After removing periods of maintenance and abnormal fluctuations, the mean and standard deviation of each thermal response characteristic were statistically analyzed to establish a health baseline model. The main health baseline parameters for the three connectors are as follows:

[0147] Connector A health baseline:

[0148]

[0149] Connector B health baseline:

[0150]

[0151] Connector C health baseline:

[0152]

[0153] S5. Calculate the thermal response offset index.

[0154] In this embodiment, for the load increase process, five core thermal response features are selected in the heating stage to participate in the offset index calculation (i.e., D1 initial heating slope, D2 temperature rise value, D3 thermal response lag time, D4 ​​heating time constant and D5 thermal recovery rate). The cooling time constant and overshoot are used as auxiliary verification features for the degradation type determination in step S7.

[0155] The five currently selected thermal response characteristics are compared with the healthy baseline model, according to... Calculate the standardized offset of each feature:

[0156] The offsets of each feature of connector A are calculated as follows:

[0157]

[0158]

[0159]

[0160]

[0161]

[0162] The offsets of each feature of connector B are calculated as follows:

[0163]

[0164]

[0165]

[0166]

[0167]

[0168] The offsets of each feature of connector C are calculated as follows:

[0169]

[0170]

[0171]

[0172]

[0173]

[0174] The weights of the five thermal response features are respectively:

[0175]

[0176] And it satisfies:

[0177]

[0178] The comprehensive thermal response offset index is calculated according to formula (10). The comprehensive thermal response offset index of the three joints is calculated as follows:

[0179]

[0180]

[0181]

[0182]

[0183]

[0184] S6. Perform in-box relative diagnostics

[0185] The median value of the combined thermal response offset index of the three joints in the same enclosure is taken as the reference benchmark:

[0186]

[0187] The relative offset value of connector C is:

[0188]

[0189] Set relative anomaly threshold The relative offset value of connector C is 5.50, exceeding the threshold, therefore connector C is determined to be an abnormal connector within the same box. The relative offset values ​​of connectors A and B are -0.08 and 0.00 respectively, both within the limits, and are therefore considered normal.

[0190] S7. Identify localized degradation conditions

[0191] Degradation type determination based on the offset direction of thermal response characteristics of composite joint C:

[0192] The initial heating rate increased significantly from the baseline average of 0.021℃ / s to 0.044℃ / s.

[0193] The temperature rise increased significantly from the baseline average of 3.6℃ to 7.7℃.

[0194] The thermal response hysteresis time was significantly reduced from the baseline mean of 47s to 21s.

[0195] The heating time constant decreased significantly from the baseline mean of 258 s to 118 s.

[0196] The thermal recovery rate decreased significantly from the baseline mean of 0.011℃ / s to 0.004℃ / s.

[0197] The above combination of features conforms to the judgment rules for contact degradation type local deterioration, and therefore it is determined that joint C has contact degradation type local deterioration.

[0198] S8, Output graded local degradation early warning results

[0199] Comprehensive thermal response offset index Relative offset value In addition to the trend changes within multiple consecutive load disturbance windows, the system outputs a warning level of moderate to severe anomaly, and prompts maintenance personnel to focus on checking the crimping quality of connector C, the oxidation status of the conductor contact surface, and the tightness of the connection.

[0200] Example 2

[0201] The difference between this embodiment and Embodiment 1 is that this embodiment is based on a 35kV substation three-connector branch box and is tested during the load drop disturbance process. It is used to identify localized degradation due to heat dissipation obstruction (i.e., this embodiment focuses on verifying the ability of the present invention to identify localized degradation due to heat dissipation obstruction under load drop conditions), and includes the following steps:

[0202] S1. Collect operational data

[0203] Three cable joints, designated Joint A, Joint B, and Joint C, are installed inside the cable branch box of a 35kV substation. Each joint is equipped with a surface temperature sensor. An ambient temperature sensor is installed inside the branch box, and a current acquisition module is installed on the incoming line side. The system sampling period is set to 5 seconds. During operation from 14:20 to 15:40 on April 12, 2025, the system continuously collected operational data according to the preset sampling period, forming a time-series dataset.

[0204]

[0205] Among them, ambient temperature Maintaining the temperature between 24.1℃ and 25.3℃, the line current... It gradually increased from 186A to 132A.

[0206] S2, Identify Load Disturbance Window

[0207]

[0208] At 14:58, the line current showed a significant step drop, with both the amount and rate of change exceeding the preset thresholds. This condition was met for approximately 15 minutes, satisfying the confirmation criteria for the effective load disturbance window. The system then determined the period from 14:58 to 15:13 as the effective load disturbance window for this instance.

[0209] S3. Extract thermal response features and construct thermal response feature vector.

[0210] Within the aforementioned load disturbance window, the system extracts thermal response features from joints D, E, and F respectively, constructing thermal response feature vectors. Unlike Example 1, this example focuses on the cooling process after the load recedes; therefore, it primarily analyzes cooling-related features and makes a comprehensive judgment based on the characteristics of the heating stage.

[0211] For example, the three joints exhibited the following thermal responses after the load was removed: the temperature of joint D dropped from 41.2℃ to 37.6℃, joint E from 40.8℃ to 37.9℃, and joint F from 43.6℃ to 41.9℃. Substituting these values ​​into equations (4), (5), and (6), respectively, we can obtain the heating time constant, cooling time constant, and thermal recovery rate of each joint. Specifically, the cooling time constants of joints D and E are approximately 182s and 195s, respectively, and the thermal recovery rates are approximately 0.015℃ / s and 0.014℃ / s, respectively. However, the cooling time constant of joint F increases to 346s, and the thermal recovery rate decreases to 0.006℃ / s, indicating a significant decrease in its heat dissipation capacity.

[0212] Based on the above thermal response characteristics, thermal response feature vectors for each joint are constructed. This is used for subsequent offset exponent calculations.

[0213] S4. Establish a health baseline model

[0214] The system retrieves historical data from joints D, E, and F during the previous 20 consecutive days of normal operation. After removing maintenance periods and periods of abnormal fluctuations, the mean and standard deviation of each thermal response characteristic are statistically analyzed to establish a healthy baseline model. The baseline parameters can be obtained from the historical normal operation data of the corresponding joints, and their establishment method is the same as in Example 1, and will not be repeated here.

[0215] S5. Calculate the thermal response offset index.

[0216] In this embodiment, the core thermal response characteristics of the cooling phase are selected for the load reduction process to participate in the offset index calculation. Among them, the cooling time constant and thermal recovery rate are the main discriminant characteristics, and the heating-related characteristics are combined for auxiliary analysis when necessary. The currently selected thermal response characteristics are compared with the healthy baseline model, and the standardized offset of each characteristic is calculated according to Equation (9), and the comprehensive thermal response offset index is calculated according to Equation (10). The calculation method is the same as in Embodiment 1, and the formula derivation will not be repeated here.

[0217] The calculation results show that the comprehensive thermal response deviation index of joint F is significantly higher than that of joints D and E, indicating that its thermal response behavior deviates significantly from the healthy state.

[0218] S6. Perform in-box relative diagnostics

[0219] The median value of the combined thermal response offset index of the three joints in the same enclosure was used as a reference benchmark to calculate the relative offset value of each joint. The results showed that the relative offset value of joint F exceeded the preset threshold, while that of joints D and E did not exceed the limit. Therefore, joint F was determined to be an abnormal joint in the same enclosure.

[0220] S7. Identify localized degradation conditions

[0221] The degradation type of the composite joint F was determined by the direction of thermal response characteristic shift during the load drop process: its cooling time constant increased significantly, the thermal recovery rate decreased significantly, the temperature drop was delayed and the duration of high temperature was prolonged, which meets the judgment rules of heat dissipation obstruction type local degradation. Therefore, it is determined that the joint F has heat dissipation obstruction type local degradation.

[0222] S8, Output graded local degradation early warning results

[0223] Based on the combined thermal response offset index, relative offset value, and trend changes within multiple consecutive load disturbance windows, the system outputs a warning level of moderate to severe anomaly, and prompts maintenance personnel to focus on checking the ventilation conditions, covering structure, heat dissipation channels, and heat accumulation around connector F.

[0224] It should be noted that the structure described in this invention can be implemented in many different forms and is not limited to the embodiments described. Any equivalent transformations made by those skilled in the art based on the content of this specification, or direct or indirect applications in other related technical fields, such as the loading and unloading of other items, are included within the protection scope of this invention.

Claims

1. A method for monitoring the thermal response characteristics of cable branch box joints and providing early warning of localized degradation, characterized in that, Includes the following steps: S1. Collect operating data of multiple cable joints in the cable branch box. The operating data includes at least the joint surface temperature, ambient temperature, and line current. S2. Identify the load disturbance window based on the operating data; S3. Extract the thermal response characteristics of each cable joint within the load disturbance window and construct a thermal response feature vector; S4. Establish a health baseline model for each cable joint based on historical normal operation data; S5. Compare the current thermal response characteristics with the health baseline model and calculate the thermal response offset index; S6. Compare the thermal response offset indices of multiple cable joints in the same cable branch box and perform relative diagnosis within the same box. S7. Identify localized degradation states based on thermal response offset index and relative diagnostic results within the same chamber; S8. Output graded local degradation early warning results.

2. The method for monitoring the thermal response characteristics and providing early warning of local degradation of cable branch box joints as described in claim 1, characterized in that: The thermal response characteristics include one or more of the following: initial heating slope, temperature rise amplitude, thermal response lag time, heating time constant, cooling time constant, thermal recovery rate, overshoot, and response inflection point location.

3. The method for monitoring the thermal response characteristics and providing early warning of local degradation of cable branch box joints as described in claim 1, characterized in that: The load disturbance window is identified based on the following conditions: When the change in line current meets the preset threshold condition and / or the rate of change of line current meets the preset threshold condition, it is determined to enter the load disturbance window.

4. The method for monitoring the thermal response characteristics of cable branch box joints and providing early warning of local degradation as described in claim 1, characterized in that: The calculation of the thermal response offset index includes: standardizing and comparing the current thermal response features with the corresponding features in the healthy baseline model to obtain the offset of each feature, and then weighting and summing the offsets of each feature to obtain the comprehensive thermal response offset index.

5. The method for monitoring the thermal response characteristics and providing early warning of local degradation of cable branch box joints as described in claim 4, characterized in that: The standardized comparison uses the following expression: in, This represents the current characteristic value of the thermal response. The mean of the healthy baseline, The standard deviation of the healthy baseline, It is a very small positive number.

6. The method for monitoring the thermal response characteristics and providing early warning of local degradation of cable branch box joints as described in claim 1, characterized in that: The in-box relative diagnosis includes: Using the median, mean, or reference joint value of the comprehensive thermal response offset index of multiple cable joints in the same cable branch box as a benchmark, the relative offset value of each cable joint is calculated, and abnormal joints are identified based on the relative offset value.

7. The method for monitoring the thermal response characteristics and providing early warning of local degradation of cable branch box joints as described in claim 1, characterized in that: The localized degradation state includes one or more of the following: contact degradation type localized degradation, heat dissipation obstruction type localized degradation, structural loosening type localized degradation, and continuous evolution type localized degradation.

8. The method for monitoring the thermal response characteristics and providing early warning of local degradation of cable branch box joints as described in claim 7, characterized in that: The degradation type is determined as follows: When the initial heating slope increases, the thermal response hysteresis time decreases, and the temperature rise amplitude increases, it is determined to be a contact degradation type of localized deterioration. When the cooling time constant increases and the thermal recovery rate decreases, it is determined to be a localized degradation due to impeded heat dissipation. When the thermal response curve shows increased fluctuations, increased overshoot, and a clear inflection point, it is determined to be a localized deterioration due to structural loosening. When the comprehensive thermal response offset index continues to increase monotonically within multiple consecutive load disturbance windows, it is determined to be a continuously evolving type of local degradation.

9. The method for monitoring the thermal response characteristics of cable branch box joints and providing early warning of local degradation as described in claim 1, characterized in that: The graded local degradation early warning results include at least five levels: normal, slightly abnormal, moderately abnormal, severely abnormal, and requiring immediate review. The level is determined based on the comprehensive thermal response offset index and continuous monitoring results.

10. The method for monitoring the thermal response characteristics of cable branch box joints and providing early warning of local degradation as described in claim 1, characterized in that: Trend fusion is performed on the diagnostic results of multiple consecutive load disturbance windows. When the same connector shows an abnormal offset trend in multiple consecutive load disturbance windows, its warning level is increased.

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