Current and temperature driven in-operation cable residual life prediction method and maintenance method

Abstract

The invention discloses a current and temperature driven in-operation cable residual life prediction method and maintenance method in the technical field of reliability engineering, and the method comprises the steps: obtaining the inspection data of an in-operation cable, including cable surface temperature, environment humidity, armoring temperature and load current; inputting the related data into a pre-constructed cable equivalent thermal circuit model for iterative calculation to obtain a cable conductor temperature; calculating a heat loss factor based on a difference value between the temperature of the cable conductor and the temperature of the cable conductor in a preset ideal state, and obtaining the corresponding residual life of the cable in combination with the design life, the actual operation age limit and the heat loss factor of the cable; and establishing a cable residual life data set by using the inspection data and the cable residual life, and inputting the cable residual life data set and the corresponding environment humidity into the gray prediction model by combining the rated current-carrying capacity of the cable in operation to obtain a predicted value of the cable residual life. The cable aging degree can be quantitatively evaluated, and operation and maintenance management is optimized.

Description

Technical Field

[0001] The invention relates to a current and temperature driven remaining life prediction method and a maintenance method for an in-service cable, belonging to the technical field of reliability engineering. Background Art

[0002] With the increasing number of cables put into operation and the increase in the number of years of cable operation, it is necessary to evaluate the condition and predict the life of cross-linked polyethylene cables. At present, the mainstream cable condition evaluation focuses on real-time monitoring of various operating parameters of power cables, such as voltage and temperature, in order to identify potential faults and issue early warnings. Through the diagnostic function of these monitoring systems, necessary reliability and safety measures can be taken after a fault is discovered.

[0003] In addition to the monitoring function, statistical analysis of online monitoring data can provide a more comprehensive understanding of the operating status of the cable and its load characteristics. However, although existing monitoring and analysis methods can help identify faults and ensure operation, there is currently no method that can assess the remaining life of cables in operation. In other words, existing technologies can only monitor the current status, but cannot predict how long the cable can operate safely. Therefore, a method is urgently needed to solve these problems. Summary of the invention

[0004] The purpose of the present invention is to provide a current and temperature driven remaining life prediction method and maintenance method for an in-service cable, which can solve the problems in the prior art of inaccurate assessment of the aging status of the operating cable, lack of quantitative indicators and inability to predict the remaining life in real time.

[0005] In order to solve the above technical problems, the present invention is implemented by adopting the following technical solutions.

[0006] In one aspect, the present invention provides a current and temperature driven method for predicting the remaining service life of an in-service cable, comprising: Obtaining inspection data of the in-service cables, the inspection data including cable surface temperature, ambient humidity, armor temperature and load current; The cable surface temperature, armor temperature and load current are input into a pre-built cable equivalent thermal circuit model for iterative calculation to obtain the cable conductor temperature; Calculating a heat loss factor based on a difference between the cable conductor temperature and the cable conductor temperature under a preset ideal state; The remaining life of the cable corresponding to the inspection data is obtained through the factory design life of the cable, the actual operating life and the heat loss factor; Establishing a cable remaining life data set based on the cable surface temperature, armor temperature, load current and corresponding cable remaining life in the inspection data; Combined with the rated current carrying capacity of the cables in service, the cable remaining life data set and the corresponding ambient humidity are input into a pre-built grey prediction model to obtain the predicted value of the cable remaining life.

[0007] In combination with the first aspect, further, the cable surface temperature, armor temperature and load current are input into a pre-built cable equivalent thermal circuit model for iterative calculation to obtain the cable conductor temperature, including: Based on the cable equivalent thermal circuit model, a temperature difference balance equation among the cable conductor, metal shielding layer, armor layer, cable surface temperature and ambient temperature is established; Solving the temperature difference balance equations simultaneously to obtain parameters related to temperature, wherein the parameters related to temperature include AC resistance per unit length of cable conductor, metal shielding resistance loss factor, armor layer resistance loss factor and air environment thermal resistance; Correcting the temperature-related parameter to obtain a corrected temperature-related parameter; The corrected temperature-related parameters are substituted into the combined temperature difference balance equation, and the cable conductor temperature is updated through iterative calculation until the difference between the cable conductor temperatures of two adjacent iterations is less than a preset convergence judgment threshold, and the final cable conductor temperature is output.

[0008] In combination with the first aspect, further, the expression for establishing the temperature difference balance equation between the cable conductor, the metal shielding layer, the armor layer, the cable surface temperature and the ambient temperature includes: ; ; ; ; in, Indicates the cable conductor temperature; Indicates the temperature of the metal shielding layer; Indicates the armor layer temperature; Indicates the cable surface temperature; Indicates the ambient temperature; Indicates cable conductor loss; Indicates dielectric loss of insulation layer; Indicates the resistance loss factor of the metal shielding layer; Indicates the armor layer resistance loss factor; Indicates the thermal resistance of the insulation layer; Indicates the thermal resistance of the lining; Indicates the thermal resistance of the outer sheath; Represents the air-to-ambient thermal resistance.

[0009] In combination with the first aspect, further, the expression for establishing the temperature difference balance equation between the cable conductor, the metal shielding layer, the armor layer, the cable surface temperature and the ambient temperature includes: ; ; ; ; in, Indicates the cable conductor temperature; Indicates the temperature of the metal shielding layer; Indicates the armor layer temperature; Indicates the cable surface temperature; Indicates the ambient temperature; Indicates cable conductor loss; Indicates dielectric loss of insulation layer; Indicates the resistance loss factor of the metal shielding layer; Indicates the armor layer resistance loss factor; Indicates the thermal resistance of the insulation layer; Indicates the thermal resistance of the lining; Indicates the thermal resistance of the outer sheath; Represents the air-to-ambient thermal resistance.

[0010] In combination with the first aspect, further, the temperature-related parameter is corrected to obtain a corrected temperature-related parameter, including: Use the following expression to correct the AC resistance per unit length of cable conductor: ; in, It represents the corrected AC resistance per unit length of cable conductor; Indicates the resistance temperature coefficient of the cable conductor; f Indicates the power supply frequency; Indicates the axial distance of the cable conductor; Indicates the diameter of the metal shielding layer; Indicates the DC resistance of the cable conductor at 20°C; Indicates the cable conductor temperature; The metal shielding layer resistance loss factor is corrected using the following expression: ; in, It represents the corrected metal shielding layer resistance loss factor; represents the resistivity of metal shielding material; I represents the load current; Indicates the cross-sectional area of ​​the metal shielding layer; It represents the reactance of the metal shield per unit length; Indicates dielectric loss of insulation layer; Indicates the thermal resistance of the insulation layer; Indicates the metal shielding layer temperature; The armor layer resistance loss factor is corrected using the following expression: ; in, Represents the corrected armor layer resistance loss factor; represents the intermediate coefficient; Indicates the thickness of the armor layer; Indicates the diameter of the armor layer; Correct the air-to-ambient thermal resistance using the following expression: ; in, represents the corrected air environment thermal resistance; h represents the heat dissipation coefficient; Indicates the outer diameter of the cable; Indicates the temperature difference between the cable surface temperature and the ambient temperature; Indicates the ambient temperature; Indicates cable conductor loss; Indicates the thermal resistance of the lining; Represents the thermal resistance of the outer sheath.

[0011] In combination with the first aspect, further, substituting the corrected temperature-related parameters into the combined temperature difference balance equations, and updating the cable conductor temperature by iterative calculation, including: Based on the combined temperature balance equation and the corrected temperature-related parameters, the cable conductor temperature is updated using the following expression: ; in, It represents the heat dissipation coefficient; Indicates the outer diameter of the cable; Indicates the cable conductor temperature; Indicates the ambient temperature; Indicates the thermal resistance of the insulation layer; Indicates cable conductor loss; Indicates dielectric loss of insulation layer; Indicates the thermal resistance of the lining; It represents the corrected metal shielding layer resistance loss factor; Represents the corrected armor layer resistance loss factor; Indicates the thermal resistance of the outer sheath; represents the corrected air-to-ambient thermal resistance; Indicates the resistance loss factor of the metal shielding layer; Represents the armor layer resistance loss factor.

[0012] In combination with the first aspect, further, the expression of the heat loss factor is as follows: ; in, represents the heat loss factor; is the cable conductor temperature; is the cable conductor temperature under ideal conditions.

[0013] In combination with the first aspect, further, the rated current carrying capacity of the in-service cable is combined, and the cable remaining life data set and the corresponding ambient humidity are input into a pre-built grey prediction model to obtain a predicted value of the cable remaining life, including: The remaining life of the cable in the remaining life data set of the cable is used as a characteristic data sequence, the surface temperature of the cable, the ambient humidity, the armor temperature, the load current and the rated current carrying capacity are used as a correlation factor sequence, and the characteristic data sequence and the correlation factor sequence are accumulated to obtain an accumulated generated sequence; Selecting the average value of two adjacent terms in the cumulative generated sequence as the background value; According to the cumulative generation sequence and the correlation factor sequence, a white micronization equation between the feature data sequence and the correlation factor sequence is established, and the cumulative generation sequence in the white micronization equation is replaced by the background value to obtain a gray micronization equation; Based on the gray micronization equation, the gray coefficient is solved by the least square method, and a gray prediction model is established; The related factor sequence is input into the grey prediction model to obtain the predicted value of the remaining life of the cable.

[0014] In combination with the first aspect, further, the calculation expression of the background value is: ; in, Represents the background value of the feature data sequence; Indicates the first time step in the cumulative generated sequence. data values; Indicates the first time step in the cumulative generated sequence. data value.

[0015] In combination with the first aspect, further, the calculation expression of the predicted value of the remaining life of the cable includes: ; in, Represents the first time step of the original feature data sequence predicted values; Represents the first time step of the cumulative generated sequence in the feature data sequence predicted values; Represents the first time step of the cumulative generated sequence in the feature data sequence predicted value.

[0016] In a second aspect, a current and temperature driven in-service cable maintenance method comprises: Obtaining a predicted value of the remaining life of the cable using the method described in the first aspect; In response to the predicted value of the remaining life of the cable being between 30% and 45% of the preset cable life limit, attention is paid to the cable in operation; In response to the predicted value of the remaining life of the cable being between 20% and 30% of the preset cable life limit, the in-service cable is monitored and repaired.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The present invention realizes accurate prediction of the remaining service life of in-service cables by integrating the cable surface temperature, ambient humidity, armor temperature and load current in comprehensive inspection data with a pre-built cable equivalent thermal circuit model and a grey prediction model.

[0018] The present invention uses an equivalent thermal circuit model to iteratively calculate the conductor temperature. By dynamically correcting the AC resistance of the conductor per unit length, the metal shielding layer loss factor, the armor layer loss factor and the air environment thermal resistance, it effectively overcomes the error problem caused by the traditional method relying on manual experience, and significantly improves the objectivity and accuracy of temperature calculation. At the same time, by introducing the heat loss factor to quantify the degree of cable aging, combined with the factory design life and the actual operating years, it can intuitively reflect the remaining life of the cable, solving the problem of lack of quantitative evaluation indicators in the prior art. In addition, the gray prediction model constructed based on historical inspection data not only greatly reduces the time for iterative calculation of complex thermal circuit models (such as the time taken by conventional computers is shortened from 20 minutes to real-time prediction), but also further optimizes the reliability of the prediction results through the collaborative analysis of environmental humidity and rated current carrying capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 The figure is a schematic flow chart of a current and temperature driven remaining life prediction method for an in-service cable provided in an embodiment of the present invention; Figure 2 FIG. 1 is a schematic diagram showing the installation position of the RFID temperature measurement chip provided by an embodiment of the present invention; Figure 3 Shown is a schematic diagram of an equivalent thermal circuit model of a three-core cable provided in an embodiment of the present invention; In the figure: 1. Cable conductor; 2. Insulation layer; 3. Metal shielding layer; 4. Filling layer; 5. Armor layer; 6. Outer sheath; 7. RFID temperature measurement chip. DETAILED DESCRIPTION

[0020] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0021] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship.

[0022] At present, the evaluation of the status of power grid cables mainly relies on human experience to judge online monitoring data, such as temperature, current, voltage, etc., which has the following disadvantages: 1. Human experience judgment will cause subjective errors and lack unified, quantitative and objective evaluation indicators; 2. The operation inside the cable well is poor. Factors such as humidity, water accumulation, and high temperature affect the normal operation of the online monitoring equipment, resulting in unreliable online monitoring data, making the existing online monitoring data unable to fully reflect the actual operation conditions inside the cable well.

[0023] Secondly, there are usually daily inspections of cable wells and cable trenches on site, but the data obtained during the cable operation and maintenance inspection, such as temperature, load current, etc., are not fully utilized and cannot be used to directly guide cable operation and maintenance.

[0024] Example 1

[0025] See also Figure 1 , which is a flow chart of a current and temperature driven remaining life prediction method for an in-service cable provided by an embodiment of the present invention. The method provides a scientific basis for the operation and maintenance management of the cable by comprehensively considering the operation status and aging degree of the cable, and includes the following steps: Step S1, obtaining inspection data of the in-service cable, wherein the inspection data includes cable surface temperature, ambient humidity, armor temperature and load current; Step S2, inputting the cable surface temperature, armor temperature and load current into a pre-built cable equivalent thermal circuit model for iterative calculation to obtain the cable conductor temperature; Here, the embodiment of the present invention adopts a three-core cable equivalent thermal circuit model to simulate the heat transfer mechanism inside the cable, including the heat transfer process between the cable conductor 1, the insulation layer 2, the metal shielding layer 3, the filling layer 4, the armor layer 5 and the outer sheath 6. Through the equivalent thermal circuit model, the complex heat transfer process can be simplified into an equivalent circuit. For details, see Figure 3 , where the circuit contains components such as thermal resistance and thermal capacitance, which facilitates mathematical modeling and calculation, thereby accurately simulating the temperature distribution of the cable under different conditions.

[0026] Step S3, calculating a heat loss factor based on a difference between the cable conductor temperature and a preset ideal cable conductor temperature; Here, the heat loss factor is an important indicator to measure the degree of cable aging, reflecting the additional heat loss caused by factors such as aging of insulation materials and increased losses. The introduction of this factor makes the assessment of the cable aging status more quantitative and accurate.

[0027] Step S4, obtaining the remaining life of the cable corresponding to the inspection data through the factory design life of the cable, the actual operating life and the heat loss factor; Step S5, establishing a cable remaining life data set based on the cable surface temperature, armor temperature, load current and corresponding cable remaining life in the inspection data; Step S6: In combination with the rated current-carrying capacity of the in-service cable, the cable remaining life data set and the corresponding ambient humidity are input into a pre-built grey prediction model to obtain a predicted value of the cable remaining life.

[0028] Here, the ambient humidity and rated current carrying capacity are used as auxiliary inputs of the model and input into the pre-built grey prediction model together with the cable remaining life dataset, which further optimizes the reliability of the prediction results.

[0029] In addition, the grey prediction model used in the embodiment of the present invention is the GM (1, n) model, where 1 indicates that there is a characteristic data sequence in the model, such as the remaining life of the cable; n indicates that there are n related factors, such as the cable surface temperature, load current, etc. This model can effectively handle the uncertainty and incompleteness of data, and is particularly suitable for complex prediction problems such as the remaining life of the cable, which is affected by multiple factors.

[0030] To sum up, the embodiment of the present invention not only takes into account the actual operating status of the cable, but also combines the quantitative indicators of the degree of aging, realizes the dynamic evaluation and prediction of the remaining life of the cable, effectively guides the operation and maintenance of the cable, and improves the reliability and safety of the power system.

[0031] Example 2

[0032] In order to improve the accuracy of the input parameters of the remaining life assessment model in Example 1, this embodiment optimizes the collection method of armor temperature data.

[0033] See also Figure 2 , which is a schematic diagram of the installation position of the RFID temperature measuring chip 7 provided in an embodiment of the present invention, the cable conductor temperature is obtained by inputting the armor temperature obtained by the RFID temperature measuring chip 7 built into the armor layer 5 of the cable, the cable surface temperature, and the load current obtained by retrieving the operation data of the control system into the cable equivalent thermal circuit model for iterative calculation.

[0034] The specific steps of obtaining the cable conductor temperature through iterative calculation are as follows: Step S31, based on the cable equivalent thermal circuit model, establishing a temperature difference balance equation among the cable conductor 1, the metal shielding layer 3, the armor layer 5, the cable surface temperature and the ambient temperature; The expression of the temperature difference balance equation is: ; (1) ; (2) ; (3) ; (4) in, Indicates the cable conductor temperature; Indicates the temperature of the metal shielding layer; Indicates the armor layer temperature; Indicates the cable surface temperature; Indicates the ambient temperature; Indicates cable conductor loss; Indicates dielectric loss of insulation layer; Indicates the resistance loss factor of the metal shielding layer; Indicates the armor layer resistance loss factor; Indicates the thermal resistance of the insulation layer; Indicates the thermal resistance of the lining; Indicates the thermal resistance of the outer sheath; Represents the air-to-ambient thermal resistance.

[0035] Due to the bidirectionality of the heat path, the temperature balance equations (1) to (4) are combined to obtain the conductor temperature Armor layer temperature The quantitative relationship between them is the key to evaluating the thermal state and remaining life of the cable, and its expression is: (5) It should be noted that since the metal shielding layer 3 is located outside the insulating layer 2, the heat will pass through the insulating layer when it is transferred from the conductor to the metal shielding layer 3, so the temperature of the metal shielding layer It can indirectly reflect the temperature condition of the insulation layer.

[0036] Step S32: According to the temperature difference balance equation of formula (1) to (4), the temperature-related parameters are solved simultaneously, and the temperature-related parameters include the AC resistance R per unit length of the cable conductor, the metal shielding resistance loss factor , Armor layer resistance loss factor And air-to-ambient thermal resistance ; Step S33: According to the actual operating conditions of the cable, the AC resistance R of the cable conductor per unit length and the metal shielding resistance loss coefficient , Armor layer loss resistance factor And air-to-ambient thermal resistance Perform correction to obtain corrected temperature-related parameters; Among them, the expressions of the corrected temperature-related parameters are: a. Use the following expression to correct the AC resistance per unit length of cable conductor: When calculating the AC resistance of a cable conductor per unit length, the DC resistance The calculation expression of the conductor temperature can be Obtained, its expression is: (6) in, Indicates the DC resistance of the cable conductor; It indicates the DC resistance coefficient of the cable conductor at 20℃; A indicates the cross-sectional area of ​​the cable conductor; Indicates the resistance temperature coefficient of the cable conductor; Indicates the twist coefficient, which is 1.024-1.05 for mobile cables and 1.01-1.012 for fixed cables; is the cabling coefficient, which is 1.029~1.17 for mobile cables and 1.002~1.011 for fixed cables; It is the compression effect coefficient, and the fixed cable installation value is 1.004~1.01.

[0037] Then, after combining formula (6) with the temperature difference balance equations (1) to (4), we get an algebraic expression for R, and the integrated expression is: ; (7) in, It represents the corrected AC resistance per unit length of cable conductor; Indicates the resistance temperature coefficient of the cable conductor; f Indicates the power supply frequency; Indicates the axial distance of the cable conductor; Indicates the diameter of the metal shielding layer; Indicates the DC resistance of the cable conductor at 20°C.

[0038] b. Use the following expression to correct the metal shielding layer resistance loss factor: When calculating the metal shielding layer loss factor, according to the temperature node relationship between different parts of the cable (such as cable conductor 1, metal shielding layer 3, etc.), when the current is known, it can be obtained Indicates the metal shield temperature and conductor temperature The quantitative relationship is expressed as: (8) (9) Combining formula (7) and formula (9), the corrected metal shielding layer resistance loss factor can be obtained: An algebraic expression for is as follows: (10) in, It represents the corrected metal shielding layer resistance loss factor; represents the resistivity of metal shielding material; I represents the load current; Indicates the cross-sectional area of ​​the metal shielding layer; It represents the reactance of the metal shield per unit length; Indicates the load current.

[0039] The armor layer resistance loss factor is corrected using the following expression: Considering that the RFID temperature measurement chip 7 is mounted on the armor layer 5, the parameters of the armor layer 5 need to be corrected to ensure the accuracy of the measurement. Through the corrected parameters, about R An algebraic expression for : (11) in, Represents the corrected armor layer resistance loss factor; represents the intermediate coefficient; Indicates the thickness of the armor layer; Indicates the diameter of the armor layer.

[0040] Air-to-ambient thermal resistance: When calculating the air environment thermal resistance, its definition is There is no way to calculate it directly. By combining formulas (1) to (4), we can get the air-ambient thermal resistance Cable surface temperature rise exceeding the cable surface temperature , which is the difference between the cable surface temperature and the ambient temperature, and its expression is: (12) in, Indicates the difference between the cable surface temperature and the surrounding environment temperature.

[0041] Then, the corrected air-to-ambient thermal resistance is It can be expressed as: (13) in, represents the corrected air environment thermal resistance; h represents the heat dissipation coefficient; Indicates the outer diameter of the cable; Indicates the temperature difference between the cable surface temperature and the ambient temperature.

[0042] It should be noted that due to For a given ambient temperature, are other parameters in the thermal circuit model, which can be calculated from known quantities. The expression of The algebraic expression of .

[0043] Step S34: Substitute the corrected temperature-related parameters into the combined temperature difference balance equations (Formulas (1) to (4)), and update the cable conductor temperature through iterative calculation until the difference between the cable conductor temperatures of two adjacent iterations is less than a preset convergence judgment threshold (the threshold can be 0.1°C), and output the final cable conductor temperature.

[0044] Therefore, the corrected cable conductor AC resistance R per unit length and metal shield resistance loss coefficient are , Armor layer loss resistance factor And air-to-ambient thermal resistance All four variables are affected only by The influence of one variable. Based on this, the equation relationship is established by combining equations (5)-(12), where only one variable is contained. , and finally calculate the conductor temperature , the cable conductor temperature expression includes: (14) Furthermore, in actual long-term operation, due to the continuous effects of thermal and electric fields, material properties will gradually deteriorate, leading to a significant increase in insulation loss and other related losses, which in turn intensifies the heating of the cable and makes the temperature rise more obvious. In order to ensure the stability and safety of the cable system, it is necessary to fully consider the changes in the material in the actual operating environment, especially the impact of the degradation of its physical and electrical properties on the heat generation and temperature rise.

[0045] In order to dynamically and accurately evaluate the impact of changes in these parameters on the current carrying capacity, the embodiment of the present invention obtains a heat loss factor based on the normalized difference between the cable conductor temperature and the cable conductor temperature under a preset ideal state, and uses the heat loss factor as a quantitative indicator of the cable aging degree; The heat loss factor M The calculation expression is: (15) in, represents the heat loss factor; is the cable conductor temperature; The cable conductor temperature under ideal conditions can be taken as 60℃.

[0046] Design life Minus actual operating years , minus the heat loss factor M, the remaining life of the cable corresponding to the inspection data can be obtained, and its expression is: (16) in, It is the design life of the cable when it leaves the factory; The actual service life of the cable; Indicates the remaining life of the cable.

[0047] Example 3

[0048] This embodiment provides a method for predicting the remaining life of an in-service cable, which is based on the same technical concept as Embodiment 1 and Embodiment 2. This embodiment is based on Embodiment 2 and further provides a detailed implementation step for realizing rapid prediction of the remaining life of a cable based on historical inspection data and a grey prediction model, which is as follows: Since the cable conductor temperature calculated in Example 2 needs to be iterated hundreds of times by combining the thermal circuit model with the Newton method, and it takes about 20 minutes to calculate using a conventional computer, in order to achieve a fast and accurate prediction of the future value of the remaining life of the cable and reduce the calculation time, in the embodiment of the present invention, taking at least 100 groups of inspection data as an example, the step of outputting the future predicted value of the remaining life of the cable includes: Step S71, calculating the remaining life of the cable corresponding to the cable surface temperature, armor temperature, and load current in each group of inspection data, to form a remaining life data set containing 100 groups of data; The expression of the remaining life data set is: (17) in, represents the remaining life data set; Indicates the armor layer temperature in the inspection data; Indicates the index of the inspection data group, that is, the 1st to 100th inspection data groups.

[0049] It should be noted that each Contains a set of inspection data (cable surface temperature, load current, etc.) and its corresponding remaining life values, which are used to train the grey model and achieve rapid life prediction.

[0050] Step S72: The remaining life of the cable in the remaining life data set is as a characteristic data sequence; the cable surface temperature, ambient humidity, armor temperature, load current and rated current carrying capacity are respectively used as relevant factor sequences , ; Then the characteristic data sequence and the related factor sequence are accumulated to obtain an accumulated generated sequence; The expression of the cumulative generated sequence is: (18) in, Indicates The feature data sequence is The accumulated value of data points; represents the intermediate index in the accumulation process, that is, the accumulation from the first group of data to the kth group of data; k represents the end point index in the accumulation generated sequence, that is, the 𝑘th accumulated value; Represents the sequence category index, that is is the feature data sequence, is the sequence of related factors; Indicates the total number of inspection data groups; represents the original data sequence; m represents the total number of sequences, including 1 feature data sequence and 5 related factor sequences.

[0051] Step S73, selecting the average value of two adjacent items in the cumulatively generated sequence as the background value; The expression of the background value is: ; (19) in, Represents the background value of the feature data sequence; Indicates the first time step in the cumulative generated sequence. data values; Indicates the first time step in the cumulative generated sequence. data value.

[0052] Step S74, establishing a white micronization equation between the feature data sequence and the correlation factor sequence according to the cumulative generation sequence and the correlation factor sequence, and replacing the cumulative generation sequence in the white micronization equation with the background value to obtain a gray micronization equation; The expression of the white micro-equation is: (20) in, It represents the derivative of the series generated by the accumulation of the main variable with respect to time t; represents the system development coefficient; represents the driving coefficient; Indicates a driver item.

[0053] Furthermore, the gray micro-equation expression obtained after replacing the background value is: (twenty one) in, Indicates the original value of the remaining life of the cable corresponding to the kth group of inspection data.

[0054] Step S75: Based on the gray micronization equation, the gray coefficient is solved by the least square method, and a gray prediction model is established; wherein the gray coefficient includes the system development coefficient and driving coefficient , this coefficient is used to quantify the influence of relevant factors on the characteristic data sequence, that is, if , indicating that the remaining life is decreasing; if , indicating that the remaining life may be extended due to maintenance or load reduction; if , indicating that a related factor has a positive impact on the remaining life, such as increasing the current carrying capacity may extend the life; if , indicating that a related factor has a negative impact on the remaining life, such as high temperature and high humidity that accelerate aging.

[0055] The gray coefficient is A is a vector, denoted by , can be calculated by the following formula (24), the specific steps are as follows: Step S751: construct a data matrix B, which is composed of cumulatively generated series and background values ​​and is used to represent the data relationship between system characteristic factors and related influencing factors. Its form is: (twenty two) Where B represents the data matrix; Indicates the background value corresponding to the second group of inspection data; Indicates the background value corresponding to the third group of inspection data; Indicates the background value corresponding to the nth group of inspection data; The cumulative generated sequence represents the first influencing factor (such as cable surface temperature) of the second group of inspection data; The cumulative generated series represents the first influencing factor (such as cable surface temperature) of the third group of inspection data; It represents the cumulative generated sequence of the first influencing factor (such as cable surface temperature) of the nth group of inspection data; The cumulative generated sequence represents the Nth influencing factor (such as ambient humidity) of the second group of inspection data; The cumulative generated sequence represents the Nth influencing factor (such as ambient humidity) of the third group of inspection data; It represents the cumulatively generated sequence of the Nth influencing factor (such as ambient humidity) of the nth group of inspection data.

[0056] Step S752: Construct a constant term vector , of the form: (twenty three) in, represents the constant term vector; The value of the original data sequence representing the characteristic data sequence (remaining life of the cable) at the second inspection; The value of the original data sequence representing the characteristic data sequence (remaining life of the cable) at the third inspection; Represents the value of the original data sequence of the characteristic data sequence (remaining life of the cable) at the time of the nth inspection.

[0057] Step S753: Calculate the gray coefficient A by using the least square method through matrix operation. The formula is: (twenty four) in, represents the transpose of the data matrix B.

[0058] This step is a key part in the process of establishing a grey prediction model. The model is trained by historical data to obtain a grey coefficient that can be used for prediction.

[0059] Step S76: Substitute the gray coefficient into the gray micronization equation to obtain a gray prediction model, and input the relevant factor sequence into the constructed gray prediction model to obtain the future prediction value of the remaining life of the cable.

[0060] The grey prediction model provided by the embodiment of the present invention, such as the G (1, n) model, can predict the predicted value of the remaining life of the cable by determining the grey coefficient, and its calculation expression is: (25) in, Represents the first time step of the original feature data sequence predicted values; Represents the first time step of the cumulative generated sequence in the feature data sequence predicted values; Represents the first time step of the cumulative generated sequence in the feature data sequence predicted value.

[0061] Example 4

[0062] An embodiment of the present invention provides a current and temperature driven in-service cable maintenance method, comprising: Obtain a predicted value of the remaining life of the cable by using the method described in any one of Embodiments 1 to 3; According to the different ranges of the predicted values, take corresponding maintenance measures for the cables in operation: In response to the predicted value of the remaining life of the cable being between 30% and 45% of the preset cable life limit, it indicates that the cable has not yet reached the level of requiring immediate maintenance, but has entered a stage that requires close attention. At this time, attention measures are taken for the cables in operation, the inspection frequency is increased, and close attention is paid to the operating status and changes in related parameters, so as to promptly discover possible problems and take countermeasures.

[0063] In response to the predicted value of the remaining life of the cable being between 20% and 30% of the preset cable life limit, it indicates that the remaining life of the cable is already low and the potential risk of failure is increasing. At this time, the cables in operation are more strictly monitored and repaired, including detailed inspection of the cables, assessment of their health status, and necessary repairs or replacements based on the inspection results to prevent cable failures from causing serious impacts on the power system.

[0064] Example 5

[0065] In this embodiment, according to the methods described in Embodiments 1 to 4, a certain road cable well is taken as an example to evaluate the life of three cables A, B, and C in the cable well. The calculation process and results are shown in Tables 1 and 2 below: Table 1 Inspection data

[0066] Table 2 Evaluation results

[0067] According to the evaluation results, the service life of cable B is significantly lower than that of cables A and C. On-site maintenance found that this is because cable B has been immersed in water for a long time, causing the insulation layer 2 to become damp and the metal parts to corrode, which accelerates the aging of the cable. At this time, further adverse effects on the cable include: Degradation of insulation performance: moisture intrudes into the cross-linked polyethylene (XLPE) insulation layer, causing partial discharge and electrical tree aging; Increased thermal resistance: Water accumulation hinders heat dissipation, resulting in abnormal cable core temperature (e.g., the surface temperature of cable B is 31.06°C, which is lower than the 32.53°C of cable A / C. This may be due to water accumulation, which prevents heat from being effectively dissipated); Current carrying capacity decreases: The rated current carrying capacity of cable B (633.13A) is significantly lower than that of cable A (674.46A), reflecting that its actual carrying capacity decreases due to aging. Although the humidity of cable B (76.63%) is not much different from that of cable A / C (77.32%) in a single inspection, the GM (1, n) grey prediction model captures the cumulative impact of long-term humidity fluctuations on life through cumulative analysis of historical data.

[0068] For example, periodic humidity peaks caused by water accumulation may be identified by the model in historical data. The cable conductor temperature in the calculation formula of the heat loss factor M is affected by the poor heat dissipation caused by water accumulation, and the actual value deviates from the ideal state ( =60℃), thereby increasing M and shortening the remaining life. The armor temperature of cable B (31.25℃) is lower than that of cable A / C (33.24℃, 33.34℃), which may be due to water accumulation, which hinders heat conduction and distorts the surface temperature. At the same time, its load current (28.18A) is within the normal range, but combined with the decrease in current carrying capacity (633.13A), it shows that the cable can no longer safely carry the design current. The model dynamically adjusts the driving coefficient by inputting multiple parameters such as humidity, temperature, and current. , quantifying the negative impact of water accumulation on life expectancy.

[0069] The remaining life of cable B (26.786 years) is significantly lower than that of cables A / C (27.743 years and 27.673 years), which directly reflects its degree of aging. The model output results provide a clear basis for operation and maintenance, such as giving priority to repairing cable B or improving its operating environment (such as drainage measures).

[0070] In summary, the method of the present invention can quickly identify cable B as a high-risk object, combine the remaining life prediction, formulate a replacement or maintenance plan, and dynamically update the prediction results by regularly inputting new inspection data to achieve preventive maintenance.

[0071] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A current and temperature driven method for predicting the remaining life of an in-service cable, characterized in that: include: Obtaining inspection data of the in-service cables, the inspection data including cable surface temperature, ambient humidity, armor temperature and load current; The cable surface temperature, armor temperature and load current are input into a pre-built cable equivalent thermal circuit model for iterative calculation to obtain the cable conductor temperature; Calculating a heat loss factor based on a difference between the cable conductor temperature and the cable conductor temperature under a preset ideal state; The remaining life of the cable corresponding to the inspection data is obtained through the factory design life of the cable, the actual operating life and the heat loss factor; Establishing a cable remaining life data set based on the cable surface temperature, armor temperature, load current and corresponding cable remaining life in the inspection data; Combined with the rated current carrying capacity of the cables in service, the cable remaining life data set and the corresponding ambient humidity are input into a pre-built grey prediction model to obtain the predicted value of the cable remaining life.

2. The current and temperature driven remaining life prediction method for in-service cables according to claim 1 is characterized in that: The cable surface temperature, armor temperature and load current are input into the pre-built cable equivalent thermal circuit model for iterative calculation to obtain the cable conductor temperature, including: Based on the cable equivalent thermal circuit model, a temperature difference balance equation between the cable conductor (1), the metal shielding layer (3), the armor layer (5), the cable surface temperature and the ambient temperature is established; Solving the temperature difference balance equations simultaneously to obtain parameters related to temperature, wherein the parameters related to temperature include AC resistance per unit length of cable conductor, metal shielding resistance loss factor, armor layer resistance loss factor and air environment thermal resistance; Correcting the temperature-related parameter to obtain a corrected temperature-related parameter; The corrected temperature-related parameters are substituted into the combined temperature difference balance equation, and the cable conductor temperature is updated through iterative calculation until the difference between the cable conductor temperatures of two adjacent iterations is less than a preset convergence judgment threshold, and the final cable conductor temperature is output.

3. The current and temperature driven remaining life prediction method for in-service cables according to claim 2 is characterized in that: The expression for establishing the temperature difference balance equation between the cable conductor (1), the metal shielding layer (3), the armor layer (5), the cable surface temperature and the ambient temperature comprises: ； ； ； ； in, Indicates the cable conductor temperature; Indicates the temperature of the metal shielding layer; Indicates the armor layer temperature; Indicates the cable surface temperature; Indicates the ambient temperature; Indicates cable conductor loss; Indicates dielectric loss of insulation layer; Indicates the resistance loss factor of the metal shielding layer; Indicates the armor layer resistance loss factor; Indicates the thermal resistance of the insulation layer; Indicates the thermal resistance of the lining; Indicates the thermal resistance of the outer sheath; Represents the air-to-ambient thermal resistance.

4. The current and temperature driven remaining life prediction method for in-service cables according to claim 2 is characterized in that: Correcting the temperature-related parameters to obtain corrected temperature-related parameters includes: Use the following expression to correct the AC resistance per unit length of cable conductor: ； in, It represents the corrected AC resistance per unit length of cable conductor; Indicates the resistance temperature coefficient of the cable conductor; f Indicates the power supply frequency; Indicates the axial distance of the cable conductor; Indicates the diameter of the metal shielding layer; Indicates the DC resistance of the cable conductor at 20°C; Indicates the cable conductor temperature; The metal shielding layer resistance loss factor is corrected using the following expression: ； in, It represents the corrected metal shielding layer resistance loss factor; represents the resistivity of metal shielding material; I represents the load current; Indicates the cross-sectional area of ​​the metal shielding layer; It represents the reactance of the metal shield per unit length; Indicates dielectric loss of insulation layer; Indicates the thermal resistance of the insulation layer; Indicates the temperature of the metal shielding layer The armor layer resistance loss factor is corrected using the following expression: ； in, Represents the corrected armor layer resistance loss factor; represents the intermediate coefficient; Indicates the thickness of the armor layer; Indicates the diameter of the armor layer; Correct the air-to-ambient thermal resistance using the following expression: ； in, represents the corrected air environment thermal resistance; h represents the heat dissipation coefficient; Indicates the outer diameter of the cable; Indicates the temperature difference between the cable surface temperature and the ambient temperature; Indicates the ambient temperature; Indicates cable conductor loss; Indicates the thermal resistance of the lining; Indicates the thermal resistance of the outer sheath; Indicates the resistance loss factor of the metal shielding layer; Represents the armor layer resistance loss factor.

5. The current and temperature driven remaining life prediction method for in-service cables according to claim 2 is characterized in that: Substituting the corrected temperature-related parameters into the combined temperature difference balance equation, and updating the cable conductor temperature through iterative calculation, including: Based on the combined temperature balance equation and the corrected temperature-related parameters, the cable conductor temperature is updated using the following expression: ； Where, h represents the heat dissipation coefficient; Indicates the outer diameter of the cable; Indicates the cable conductor temperature; Indicates the ambient temperature; Indicates the thermal resistance of the insulation layer; Indicates cable conductor loss; Indicates dielectric loss of insulation layer; Indicates the thermal resistance of the lining; It represents the corrected metal shielding layer resistance loss factor; Represents the corrected armor layer resistance loss factor; Indicates the thermal resistance of the outer sheath; represents the corrected air-to-ambient thermal resistance.

6. The current and temperature driven remaining service life prediction method for in-service cables according to claim 1, characterized in that: The expression of the heat loss factor is as follows: ； Where M represents the heat loss factor; is the cable conductor temperature; is the cable conductor temperature under ideal conditions.

7. The current and temperature driven remaining service life prediction method for in-service cables according to claim 1, characterized in that: The method combines the rated current carrying capacity of the in-service cable, inputs the cable remaining life data set and the corresponding ambient humidity into a pre-built grey prediction model, and obtains the predicted value of the cable remaining life, including: The remaining life of the cable in the remaining life data set of the cable is used as a characteristic data sequence, the surface temperature of the cable, the ambient humidity, the armor temperature, the load current and the rated current carrying capacity are used as a correlation factor sequence, and the characteristic data sequence and the correlation factor sequence are accumulated to obtain an accumulated generated sequence; Selecting the average value of two adjacent terms in the cumulative generated sequence as the background value; According to the cumulative generation sequence and the correlation factor sequence, a white micronization equation between the feature data sequence and the correlation factor sequence is established, and the cumulative generation sequence in the white micronization equation is replaced by the background value to obtain a gray micronization equation; Based on the gray micronization equation, the gray coefficient is solved by the least square method, and a gray prediction model is established; The related factor sequence is input into the grey prediction model to obtain the predicted value of the remaining life of the cable.

8. The current and temperature driven remaining service life prediction method for an in-service cable according to claim 7, characterized in that: The calculation expression of the background value is: ； in, Represents the background value of the feature data sequence; Indicates the first time step in the cumulative generated sequence. data values; Indicates the first time step in the cumulative generated sequence. data value.

9. The current and temperature driven remaining service life prediction method for in-service cables according to claim 7, characterized in that: The calculation expression of the predicted value of the remaining life of the cable includes: ； in, Represents the first time step of the original feature data sequence predicted values; Represents the first time step of the cumulative generated sequence in the feature data sequence predicted values; Represents the first time step of the cumulative generated sequence in the feature data sequence predicted value.

10. A current and temperature driven cable maintenance method in operation, characterized in that: include: The method according to any one of claims 1 to 9 is used to obtain a predicted value of the remaining life of the cable; In response to the predicted value of the remaining life of the cable being between 30% and 45% of the preset cable life limit, attention is paid to the cable in operation; In response to the predicted value of the remaining life of the cable being between 20% and 30% of the preset cable life limit, the in-service cable is monitored and repaired.

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