Online prediction method and device for remaining life of cable based on retention rate of correlation coefficient

Abstract

The present invention discloses an online prediction method and device for the remaining life of a cable based on the retention rate of the correlation coefficient. The method includes: injecting incident signals of the spread spectrum time domain reflectometry method into the cable specimens before and after aging respectively, and collecting the reflected signals; calculating the correlation coefficients of the cable specimens before and after aging according to the incident signals and the reflected signals, wherein the cross-correlation between the incident signal and the noise signal is 0; calculating the actual value of the retention rate of the correlation coefficient according to the correlation coefficients; obtaining the undetermined parameters of the degradation model based on the least squares method according to the time of collecting the reflected signals and the actual values of the corresponding retention rates of the correlation coefficient; and online predicting the remaining life of the cable according to the actual values of the retention rates of the correlation coefficients of the obtained cable specimens, the determined degradation model and the determined cable specimen life termination point. The method provided by the present invention realizes the efficient and rapid online prediction of the remaining life of the cable without damaging the cable.

Description

Technical Field

[0001] The present invention belongs to the field of cable fault diagnosis and life prediction, and particularly relates to an online prediction method and device for the remaining life of a cable based on the retention rate of the correlation coefficient. Background Art

[0002] In a power system, the working environment of a cable is complex and it is often aged under the combined action of environmental factors such as electricity, magnetism, heat, force, and humidity. When the cable serves until the middle and late stages of its life, its insulation performance deteriorates and breakdown is extremely likely to occur. Therefore, the safety of the cable is of crucial importance. Predicting the remaining life of the cable and taking preventive measures before the life is about to end can effectively improve the safety of cable operation. The aging characteristic quantities used in traditional cable life prediction methods include breakdown voltage, elongation at break, hardness, insulation resistance, and dielectric loss, etc. Among them, the detection of breakdown voltage and elongation at break is destructive, the detection of insulation resistance and dielectric loss is non-online detection, and the detection of hardness has the characteristics of non-destructiveness and online detection, but it is not applicable to cables with an outer sheath because the hardness of the main insulation can reflect the true life of the cable. Traditional cable life prediction models include the Arrhenius model, power exponential model, Weibull distribution model, Fallou model, and simoni model, etc. The above models can roughly predict the remaining life of the cable, but cannot predict the cable life online. Currently, there is little research on online and non-destructive characteristic quantities of cables, and there are few reports on the research of online prediction methods for the remaining life of cables based on online and non-destructive characteristic quantities. Summary of the Invention

[0003] In order to solve the above deficiencies of the prior art, the present invention provides an online prediction method and device for the remaining life of a cable based on the retention rate of the correlation coefficient. This method solves the problems of damaging the cable and being unable to predict online existing in traditional cable remaining life prediction methods, and realizes efficient and rapid online prediction of the remaining life of the cable, which is of great significance for cable preventive maintenance.

[0004] The first object of the present invention is to provide an online prediction method for the remaining life of a cable based on the retention rate of the correlation coefficient.

[0005] The second object of the present invention is to provide an online prediction device for the remaining life of a cable based on the retention rate of the correlation coefficient.

[0006] The first object of the present invention can be achieved by adopting the following technical solutions:

[0007] An online prediction method for the remaining life of a cable based on the retention rate of the correlation coefficient, the method comprising:

[0008] Inject incident signals of the spread spectrum time domain reflectometry (SS-TDR) into the cable specimens before and after aging respectively, and collect the reflected signals of the cable specimens; calculate the correlation coefficients of the cable specimens before and after aging corresponding to the time when the reflected signals are collected according to the incident signals and the reflected signals; wherein, the cross-correlation between the incident signal of the spread spectrum time domain reflectometry and the noise signal is 0;

[0009] Calculate the actual value of the correlation coefficient retention rate of the cable specimen according to the correlation coefficients of the cable specimens before and after aging;

[0010] Fit the correlation coefficient retention rate by using a degradation model according to the time of collecting the reflected signal and the actual value of the corresponding correlation coefficient retention rate, obtain the undetermined parameters of the degradation model based on the least square method, and determine the life termination point of the cable specimen;

[0011] Online predict the remaining life of the cable according to the actual value of the correlation coefficient retention rate of the obtained cable specimen, the determined degradation model and the life termination point of the cable specimen.

[0012] Further, the step of injecting incident signals of the spread spectrum time domain reflectometry into the cable specimens before and after aging respectively, and collecting the reflected signals of the cable specimens includes:

[0013] Injecting incident signals of the spread spectrum time domain reflectometry into the cable specimen before aging, and collecting the reflected signal of the cable specimen includes:

[0014] Select the middle part of the cable before aging as the cable specimen, generate the incident signal of the spread spectrum time domain reflectometry by modulating the m-sequence and the sine wave at a ratio of 1:1, and inject the incident signal into the cable specimen by using a signal generator;

[0015] Use an oscilloscope to collect the reflected signal of the cable specimen once every period T;

[0016] Injecting incident signals of the spread spectrum time domain reflectometry into the cable specimen after aging, and collecting the reflected signal of the cable specimen includes:

[0017] Put the middle part of the cable into an aging chamber, while the two ends of the cable are placed outside the aging chamber, and conduct a local accelerated thermal aging test on the cable specimen placed in the aging chamber;

[0018] Generate the incident signal of the spread spectrum time domain reflectometry by modulating the m-sequence and the sine wave at a ratio of 1:1, and inject the incident signal into the cable specimen by using a signal generator;

[0019] Use an oscilloscope to collect the reflected signal of the cable specimen once every period T.

[0020] Further, the step of calculating the correlation coefficients of the cable specimens before and after aging corresponding to the time when the reflected signals are collected according to the incident signals and the reflected signals includes:

[0021] Based on the incident signal and the reflected signal in the cable specimens before and after aging, the correlation coefficients of the cable specimens before and after aging corresponding to different acquisition times of the reflected signal are calculated using the following formula:

[0022]

[0023] where R sx (τ) is the correlation coefficient of the cable specimen, τ is the incident signal shift value, and τ i is the delay time of the reflected signal relative to the incident signal, t is the signal time, s is the incident signal, and a k is the change coefficient of the reflected signal, and n is the noise signal.

[0024] Furthermore, based on the actual values of the acquisition time of the reflected signal and the corresponding retention rate of the correlation coefficient, the degradation model is used to fit the retention rate of the correlation coefficient, and the undetermined parameters of the degradation model are obtained based on the least squares method, including:

[0025] Establish a degradation model for the retention rate of the correlation coefficient during the thermal aging process of the cable:

[0026]

[0027] where F is the retention rate of the correlation coefficient, and a, b, and c are all undetermined parameters, and t a is the acquisition time of the reflected signal;

[0028] The parameter identification method in the degradation model adopts the least squares method, which can quickly obtain the undetermined parameters of the degradation model and minimize the sum of the squares of the errors between the actual value and the predicted value of the retention rate of the correlation coefficient.

[0029] Furthermore, the solution target formula of the least squares method is as follows:

[0030]

[0031] where Q is the sum of the squares of the errors, F i ’ is the predicted value of the retention rate of the correlation coefficient, F i is the actual value of the retention rate of the correlation coefficient, and n is the total number of the actual values of the retention rate of the correlation coefficient.

[0032] Furthermore, calculating the actual value of the retention rate of the correlation coefficient of the cable specimen according to the correlation coefficients of the cable specimens before and after aging includes:

[0033] Calculate the actual value of the retention rate of the correlation coefficient of the cable specimen according to the following formula:

[0034]

[0035] Among them, F i is the actual value of the correlation coefficient retention rate of the cable specimen, H0 is the correlation coefficient of the cable specimen before aging, and H’ is the correlation coefficient of the cable specimen after aging.

[0036] Furthermore, based on the actual value of the correlation coefficient retention rate of the cable specimen obtained, the determined degradation model, and the cable specimen life termination point, online predicting the remaining life of the cable includes:

[0037] Collect the reflection signal of the cable specimen after aging once, and then calculate the actual value of the correlation coefficient retention rate of the cable specimen;

[0038] Substitute the actual value of the correlation coefficient retention rate into the determined degradation model to obtain the aging time;

[0039] Take the cable specimen life termination point as the correlation coefficient retention rate and substitute it into the determined degradation model to obtain the life of the cable specimen;

[0040] Use the life of the cable specimen minus the aging time to obtain the remaining life of the cable specimen.

[0041] The second object of the present invention can be achieved by adopting the following technical solutions:

[0042] An on-line prediction device for the remaining life of a cable based on the correlation coefficient retention rate, the device includes:

[0043] A signal acquisition module, configured to inject incident signals of the spread spectrum time domain reflectometry method into the cable specimens before and after aging respectively, and collect the reflection signals of the cable specimens; wherein, the cross-correlation between the incident signal of the spread spectrum time domain reflectometry method and the noise signal is 0;

[0044] A first calculation module, configured to calculate the correlation coefficients of the cable specimens before and after aging corresponding to the time of collecting the reflection signal according to the incident signal and the reflection signal;

[0045] A second calculation module, configured to calculate the actual value of the correlation coefficient retention rate of the cable specimen according to the correlation coefficients of the cable specimens before and after aging;

[0046] A determination module, configured to fit the correlation coefficient retention rate by using the degradation model according to the time of collecting the reflection signal and the corresponding actual value of the correlation coefficient retention rate, obtain the undetermined parameters of the degradation model based on the least square method, and determine the cable specimen life termination point;

[0047] The remaining life online prediction module is used to online predict the remaining life of the cable according to the actual value of the correlation coefficient retention rate of the obtained cable specimen, the determined degradation model and the cable specimen life termination point.

[0048] Further, the signal acquisition module includes a first signal acquisition unit and a second signal acquisition unit, where:

[0049] The first signal acquisition unit is used to select the middle part of the cable before aging as the cable specimen, generate the incident signal of the spread spectrum time domain reflectometry by modulating the m-sequence and the sine wave 1:1, and inject the incident signal into the cable specimen by using a signal generator; collect the reflected signal of the cable specimen once every period T by using an oscilloscope.

[0050] The second signal acquisition unit is used to place the middle part of the cable in an aging chamber, while the two ends of the cable are placed outside the aging chamber, and perform a local accelerated thermal aging test on the cable specimen placed in the aging chamber; generate the incident signal of the spread spectrum time domain reflectometry by modulating the m-sequence and the sine wave 1:1, and inject the incident signal into the cable specimen by using a signal generator; collect the reflected signal of the cable specimen once every period T by using an oscilloscope.

[0051] Further, the first calculation module includes a first calculation unit and a second calculation unit, where:

[0052] The first calculation unit is used to calculate the correlation coefficient of the cable specimen before aging corresponding to different times of collecting the reflected signal according to the incident signal and the reflected signal in the cable specimen before aging.

[0053] The second calculation unit is used to calculate the correlation coefficient of the cable specimen after aging corresponding to different times of collecting the reflected signal according to the incident signal and the reflected signal in the cable specimen after aging.

[0054] The present invention has the following beneficial effects compared with the prior art:

[0055] The method provided by the present invention can online detect the correlation coefficient of the SSTDR incident signal and the reflected signal without damaging the cable, and realize the online prediction of the remaining life of the cable through the correlation coefficient retention rate degradation model. Description of the Drawings

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the structures shown in these drawings without creative efforts.

[0057] Figure 1 Flow chart of the on - line prediction method for the remaining life of a cable based on the correlation coefficient retention rate in Embodiment 1 of the present invention.

[0058] Figure 2 Original waveform of the SSTDR incident signal in Embodiment 2 of the present invention.

[0059] Figure 3 Correlation coefficient waveform in a normal cable in Embodiment 2 of the present invention.

[0060] Figure 4 Correlation coefficient waveform in a faulty cable in Embodiment 2 of the present invention.

[0061] Figure 5 Degradation curve of the correlation coefficient retention rate in Embodiment 2 of the present invention.

[0062] Figure 6 Structural block diagram of the on - line prediction device for the remaining life of a cable based on the correlation coefficient retention rate in Embodiment 3 of the present invention. Detailed implementation manners

[0063] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts fall within the scope of protection of the present invention. It should be understood that the specific embodiments described are only used to explain the present application and are not used to limit the present application.

[0064] Embodiment 1:

[0065] As Figure 1 shown, the on - line prediction method for the remaining life of a cable based on the correlation coefficient retention rate provided in this embodiment includes the following steps:

[0066] S101. Inject incident signals into the cable specimens before and after aging respectively, and collect the reflected signals of the cable specimens; calculate the correlation coefficients of the cable specimens before and after aging according to the incident signals and the reflected signals.

[0067] Specifically, inject the incident signals of the spread - spectrum time - domain reflectometry method into the cable specimens before and after aging respectively, and collect the reflected signals of the cable specimens; calculate the correlation coefficients of the cable specimens before and after aging through time - domain correlation operation according to the incident signals and the reflected signals.

[0068] Further, step S101 includes:

[0069] (1) Calculate the correlation coefficient H0 of the cable specimen before aging.

[0070] (1-1) Select the middle part of the cable as the cable specimen. Use m-sequence and sine wave to generate the incident signal of the spread-spectrum time-domain reflectometry (SSTDR) by 1:1 modulation. Inject the incident signal into the cable specimen using a signal generator.

[0071] (1-2) Use an oscilloscope to collect the reflected signal at regular intervals. Calculate the correlation coefficient according to the reflected signal of the cable specimen using the following formula (1), so as to obtain the correlation coefficients corresponding to different time nodes t. a The corresponding correlation coefficients.

[0072] (2) Calculate the correlation coefficient H’ of the cable specimen after aging.

[0073] The cable specimen after aging and the cable specimen before aging in this step are of the same cable type.

[0074] (2-1) Place the middle part of the cable in an aging chamber, and place both ends of the cable outside the aging chamber. Conduct a local accelerated thermal aging test on the cable placed in the aging chamber. For the sake of convenience of expression, the cable placed in the aging chamber is simply referred to as the cable specimen.

[0075] (2-2) Use m-sequence and sine wave to generate the incident signal of the spread-spectrum time-domain reflectometry (SSTDR) by 1:1 modulation. Inject the incident signal into the cable specimen using a signal generator.

[0076] (2-3) Use an oscilloscope to collect the reflected signal at regular intervals (the same time interval as that used in step (1-2)). Calculate the correlation coefficient according to the reflected signal at the local aging part of the cable using the following formula (1), so as to obtain the correlation coefficients corresponding to different aging time nodes t. a The corresponding correlation coefficients.

[0077] The calculation formula for the correlation coefficient of the cable specimen is as follows:

[0078]

[0079] In the formula, R sx (τ) is the correlation coefficient, τ is the incident signal shift value, τ i is the delay time of the reflected signal relative to the incident signal, t is the signal time, s is the incident signal, a k is the reflection signal change coefficient, and n is the noise signal.

[0080] In this step, the cross-correlation between the incident signal of the spread-spectrum time-domain reflectometry (SSTDR) and the noise signal is 0, which indicates that SSTDR can perform on-line acquisition of the correlation coefficient.

[0081] S102. Calculate the actual value of the retention rate of the correlation coefficient of the cable specimen according to the correlation coefficients of the cable specimen before and after aging.

[0082] The calculation formula for the actual value of the correlation coefficient retention rate of the cable specimen is as follows:

[0083]

[0084] In the formula, F i is the actual value of the correlation coefficient retention rate of the cable specimen, H0 is the correlation coefficient of the reflected signal before aging, and H’ is the correlation coefficient of the reflected signal after aging.

[0085] S103. According to the actual value of the correlation coefficient retention rate, use the degradation model to fit the correlation coefficient retention rate, obtain the undetermined parameters of the degradation model based on the least squares method, and determine the life termination point of the cable specimen.

[0086] This step establishes a degradation model for the correlation coefficient retention rate during the thermal aging process of the cable based on the least squares method. The definition of the degradation model of the correlation coefficient retention rate is as follows:

[0087]

[0088] In the formula, a, b, and c are all undetermined parameters.

[0089] The parameter identification method in the correlation coefficient retention rate degradation model is the least squares method. The least squares method can quickly obtain the undetermined parameters of the correlation coefficient retention rate degradation model and minimize the sum of the squares of the errors between the actual value of the correlation coefficient retention rate and the predicted value of the degradation model. Its solution target formula is as follows:

[0090]

[0091] In the formula, Q is the sum of the squares of the errors, F i ’ is the predicted value of the correlation coefficient retention rate, and F i is the actual value of the correlation coefficient retention rate.

[0092] In this embodiment, by plotting the scatter diagram of the actual value of the correlation coefficient retention rate and the aging time, and then fitting the scatter diagram through the degradation model of the correlation coefficient retention rate, the undetermined parameters a, b, and c are identified based on the least squares method.

[0093] This step determines the values of the undetermined parameters a, b, and c in the degradation model, that is, determines the degradation model.

[0094] The determined life termination point of the cable specimen is obtained through the statistics of a large number of experimental data. In this embodiment, the value of the life termination point of the cable specimen is 95.5%.

[0095] S104. Based on the actual value of the retention rate of the cable correlation coefficient obtained, the determined degradation model, and the cable specimen life termination point, online predict the remaining life of the cable.

[0096] In this embodiment, the SSTDR is used to obtain the actual value of the retention rate of the correlation coefficient of the cable specimen at a certain aging time, and substitute it into the above-mentioned degradation model with determined relevant undetermined parameters to calculate the used time t of the cable. a ; Take the determined cable specimen life termination point as the retention rate of the correlation coefficient and substitute it into the determined degradation model to obtain the life of the cable specimen; Subtract the used time t from the life of the cable specimen. a , to obtain the remaining life of the cable specimen.

[0097] Embodiment 2:

[0098] Taking the thermal aging life prediction of the RG58 type cable as an example, this embodiment illustrates the online prediction method for the remaining life of the cable based on the retention rate of the correlation coefficient, which specifically includes the following steps:

[0099] (1) Take a 1m long cable from the middle of a cable specimen with a total length of 20m and put it into a thermal aging oven. Set the aging temperature in the oven to 90°C and conduct an accelerated aging test.

[0100] (2) Use the m-sequence and sine wave 1:1 modulation to generate the incident signal of the spread spectrum time domain reflectometry, as Figure 2 shown. Use a signal generator to inject a signal into the cable specimen, and use an oscilloscope to collect the reflected signal in the normal cable. Perform time domain correlation operation on the reflected signal in the normal cable to obtain a correlation waveform as Figure 3 shown.

[0101] (3) At a temperature of 90°C, inject the SSTDR incident signal into the aging cable and collect the reflected signal every 48 hours. The total aging duration is 30 days, so there are a total of 15 groups of reflected signals. Perform time domain correlation operation on the reflected signal in the aging cable to obtain a partial correlation waveform as Figure 4 shown.

[0102] (4) Extract the correlation coefficients corresponding to different aging time nodes through the correlation waveform, and then calculate the retention rates of the correlation coefficients corresponding to different aging time nodes according to the following formula.

[0103]

[0104] In the formula, F is the retention rate of the correlation coefficient, H0 is the correlation coefficient of the reflected signal before aging, and H' is the correlation coefficient of the reflected signal after aging.

[0105] (5) Based on the least squares fitting method, establish a degradation model for the retention rate of the correlation coefficient during the thermal aging process of the cable, as the following formula:

[0106]

[0107] Wherein, a, b, and c are all undetermined parameters, and t a is the aging time.

[0108] The correlation coefficient retention rate F obtained according to the above steps and the corresponding aging time node t a are used to obtain a = 13.94, b = 1458.26, and c = 86.09.

[0109] The determined 95.5% of the cable sample life termination point, that is, the correlation coefficient retention rate F is 95.5%. Using the above degradation model, t a can be calculated. At this time, t a is the life of the cable sample.

[0110] (6) Use the actual detection value of the correlation coefficient retention rate of SSTDR, the correlation coefficient retention rate degradation model, and the cable sample life termination point to perform on-line prediction of the remaining life of the cable.

[0111] When the actual detection value of the correlation coefficient retention rate is 98%, the corresponding t a is calculated according to the degradation model. Subtract t a from the life of the cable sample to obtain the remaining life of the cable as 345 h, as Figure 5 shown.

[0112] Those skilled in the art can understand that all or part of the steps in the method of implementing the above embodiments can be completed by instructing relevant hardware through a program, and the corresponding program can be stored in a computer-readable storage medium.

[0113] It should be noted that although the method operations of the above embodiments are described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. On the contrary, the described steps can be changed in the order of execution. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution.

[0114] Embodiment 3:

[0115] As Figure 6 shown, this embodiment provides an on-line prediction device for the remaining life of a cable based on the correlation coefficient retention rate. The device includes a signal acquisition module 601, a first calculation module 602, a second calculation module 603, a degradation model determination module 604, and an on-line prediction module 605 for the remaining life, where:

[0116] A signal acquisition module 601 is configured to inject incident signals of the spread spectrum time domain reflectometry method into cable specimens before and after aging respectively, and acquire the reflected signals of the cable specimens; wherein, the cross-correlation between the incident signal of the spread spectrum time domain reflectometry method and the noise signal is 0.

[0117] A first calculation module 602 is configured to calculate the correlation coefficients of the cable specimens before and after aging corresponding to the time when the reflected signals are acquired according to the incident signals and the reflected signals.

[0118] A second calculation module 603 is configured to calculate the actual value of the correlation coefficient retention rate of the cable specimen according to the correlation coefficients of the cable specimens before and after aging.

[0119] A determination module 604 is configured to fit the correlation coefficient retention rate by using a degradation model according to the time when the reflected signals are acquired and the actual value of the corresponding correlation coefficient retention rate, obtain the undetermined parameters of the degradation model based on the least squares method, and determine the life termination point of the cable specimen.

[0120] A remaining life online prediction module 605 is configured to online predict the remaining life of the cable according to the actual value of the correlation coefficient retention rate of the cable specimen obtained, the determined degradation model and the life termination point of the cable specimen.

[0121] Wherein:

[0122] The signal acquisition module 601 includes a first signal acquisition unit and a second signal acquisition unit. Among them, the first signal acquisition unit is configured to select the middle part of the cable before aging as the cable specimen, generate the incident signal of the spread spectrum time domain reflectometry method by 1:1 modulation of the m-sequence and the sine wave, inject the incident signal into the cable specimen by using a signal generator; acquire the reflected signal of the cable specimen by using an oscilloscope every period of time T. The second signal acquisition unit is configured to place the middle part of the cable in an aging chamber, while the two ends of the cable are placed outside the aging chamber, and perform a local accelerated thermal aging test on the cable specimen placed in the aging chamber; generate the incident signal of the spread spectrum time domain reflectometry method by 1:1 modulation of the m-sequence and the sine wave, inject the incident signal into the cable specimen by using a signal generator; acquire the reflected signal of the cable specimen by using an oscilloscope every period of time T.

[0123] The first calculation module 602 includes a first calculation unit and a second calculation unit. Among them, the first calculation unit is configured to calculate the correlation coefficients of the cable specimen before aging corresponding to different times when the reflected signals are acquired according to the incident signal and the reflected signal in the cable specimen before aging. The second calculation unit is configured to calculate the correlation coefficients of the cable specimen after aging corresponding to different times when the reflected signals are acquired according to the incident signal and the reflected signal in the cable specimen after aging.

[0124] For the specific implementation of each module in this embodiment, reference can be made to the above-mentioned Embodiment 1, which will not be elaborated herein one by one. It should be noted that the device provided in this embodiment is only illustrated by the above division of each functional module. In practical applications, the above functions can be assigned to different functional modules according to needs, that is, the internal structure is divided into different functional modules to complete all or part of the functions described above.

[0125] In summary, the present invention provides an online prediction method and device for the remaining life of a cable based on the correlation coefficient retention rate. The method first conducts a local accelerated thermal aging test on a cable specimen; then injects an incident signal of the spread spectrum time domain reflectometry (SSTDR) into the cable specimen and collects the reflected signal; then calculates the correlation coefficient using the reflected signals at the local aging points of the cable corresponding to different aging time nodes; then establishes a degradation model of the correlation coefficient retention rate during the cable thermal aging process based on the least squares method and determines the life termination point of the cable specimen; finally, uses the actual detection value of the correlation coefficient retention rate of the SSTDR and the degradation model of the correlation coefficient retention rate to conduct an online prediction of the remaining life of the cable. The present invention solves the problems of damage to the cable and inability to perform online prediction existing in the traditional method for predicting the remaining life of a cable, and efficiently and quickly realizes the online prediction of the remaining life of the cable.

[0126] As described above, only the preferred embodiments of the present invention for patents are provided, but the protection scope of the present invention for patents is not limited thereto. Any person skilled in the art within the scope disclosed by the present invention for patents, according to the technical solution and inventive concept of the present invention for patents, makes equivalent substitutions or changes, all belong to the protection scope of the present invention for patents.

Claims

1. An online prediction method for the remaining life of a cable based on the retention rate of the correlation coefficient, characterized in that The method includes: Injecting incident signals of the spread spectrum time domain reflectometry (SS-TDR) into the cable specimens before and after aging respectively, and collecting the reflected signals of the cable specimens; calculating the correlation coefficients of the cable specimens before and after aging corresponding to the time when the reflected signals are collected according to the incident signals and the reflected signals; wherein, the cross-correlation between the incident signal of the spread spectrum time domain reflectometry and the noise signal is 0; Calculating the actual value of the correlation coefficient retention rate of the cable specimen according to the correlation coefficients of the cable specimens before and after aging; Fitting the correlation coefficient retention rate by using a degradation model according to the time of collecting the reflected signal and the actual value of the corresponding correlation coefficient retention rate, obtaining the undetermined parameters of the degradation model based on the least square method, and determining the life termination point of the cable specimen; Online predicting the remaining life of the cable according to the actual value of the correlation coefficient retention rate of the obtained cable specimen, the determined degradation model and the life termination point of the cable specimen; Wherein, injecting the incident signals of the spread spectrum time domain reflectometry into the cable specimens before and after aging respectively, and collecting the reflected signals of the cable specimens includes: Injecting the incident signals of the spread spectrum time domain reflectometry into the cable specimen before aging, and collecting the reflected signals of the cable specimen includes: Selecting the middle part of the cable before aging as the cable specimen, generating the incident signals of the spread spectrum time domain reflectometry by modulating the m-sequence and the sine wave in a 1:1 ratio, and injecting the incident signals into the cable specimen by using a signal generator; Use an oscilloscope to collect the reflection signal of the cable specimen every once in a while T Collect the reflection signal of the cable specimen once Injecting the incident signals of the spread spectrum time domain reflectometry into the cable specimen after aging, and collecting the reflected signals of the cable specimen includes: Putting the middle part of the cable into an aging chamber, while placing both ends of the cable outside the aging chamber, and performing a local accelerated thermal aging test on the cable specimen placed in the aging chamber; Generating the incident signals of the spread spectrum time domain reflectometry by modulating the m-sequence and the sine wave in a 1:1 ratio, and injecting the incident signals into the cable specimen by using a signal generator; Use an oscilloscope to collect the reflection signal of the cable specimen at regular intervals. T Collect the reflection signal of the cable specimen once.

2. The online prediction method for the remaining life of a cable according to claim 1, characterized in that The calculating the correlation coefficients of the cable specimens before and after aging corresponding to the time when the reflected signals are collected according to the incident signals and the reflected signals includes: Calculating the correlation coefficients of the cable specimens before and after aging corresponding to different times of collecting the reflected signals according to the incident signals and the reflected signals in the cable specimens before and after aging by using the following formula: Among them, R sx ( τ ) is the correlation coefficient of the cable specimen, τ is the incident signal shift value, τ i is the delay time of the reflected signal relative to the incident signal, t is the signal time, s is the incident signal, a k is the reflected signal change coefficient, n ( t ) is t the noise signal at the moment.

3. The online prediction method for the remaining life of a cable according to claim 1, characterized in that, The fitting the correlation coefficient retention rate by using a degradation model according to the time of collecting the reflected signal and the actual value of the corresponding correlation coefficient retention rate, and obtaining the undetermined parameters of the degradation model based on the least square method includes: Establishing a degradation model of the correlation coefficient retention rate during the thermal aging process of the cable; Among them, F is the retention rate of the correlation coefficient, a , b , c are all undetermined parameters, t a is the time for collecting the reflected signal; The parameter identification method in the degradation model adopts the least square method, and the least square method can quickly obtain the undetermined parameters of the degradation model and minimize the sum of the squares of the errors between the actual value and the predicted value of the correlation coefficient retention rate.

4. The online prediction method for the remaining life of a cable according to claim 3, wherein The solution target formula of the least square method is as follows: Among them, Q is the sum of squared errors, F i ’ is the predicted value of the retention rate of the correlation coefficient, F i is the actual value of the retention rate of the correlation coefficient, n is the total number of the actual values of the retention rate of the correlation coefficient.

5. The online prediction method for the remaining life of a cable according to any one of claims 1 to 4, characterized in that, The calculating the actual value of the correlation coefficient retention rate of the cable specimen according to the correlation coefficients of the cable specimens before and after aging includes: Calculating the actual value of the correlation coefficient retention rate of the cable specimen according to the following formula: Among them, F i is the actual value of the retention rate of the correlation coefficient of the cable specimen, H 0 is the correlation coefficient of the cable specimen before aging, H ’ is the correlation coefficient of the cable specimen after aging.

6. The on-line prediction method for the remaining life of a cable according to any one of claims 1 to 4, characterized in that Online predicting the remaining life of a cable based on the actual value of the correlation coefficient retention rate of the obtained cable specimen, the determined degradation model, and the cable specimen life termination point, including: Collecting the reflection signal of the cable specimen after one-time aging, and then calculating the actual value of the correlation coefficient retention rate of the cable specimen; Substituting the actual value of the correlation coefficient retention rate into the determined degradation model to obtain the aging time; Taking the cable specimen life termination point as the correlation coefficient retention rate and substituting it into the determined degradation model to obtain the life of the cable specimen; Subtracting the aging time from the life of the cable specimen to obtain the remaining life of the cable specimen.

7. An on-line prediction device for the remaining life of a cable based on the retention rate of the correlation coefficient, characterized in that, The device includes: A signal acquisition module, configured to inject incident signals of the spread spectrum time domain reflectometry method into the cable specimens before and after aging respectively, and collect the reflection signals of the cable specimens; wherein, the cross-correlation between the incident signal of the spread spectrum time domain reflectometry method and the noise signal is 0; A first calculation module, configured to calculate the correlation coefficients of the cable specimens before and after aging corresponding to the time of collecting the reflection signals according to the incident signals and the reflection signals; A second calculation module, configured to calculate the actual value of the correlation coefficient retention rate of the cable specimen according to the correlation coefficients of the cable specimens before and after aging; A determination module, configured to fit the correlation coefficient retention rate using the degradation model based on the time of collecting the reflection signals and the corresponding actual value of the correlation coefficient retention rate, obtain the undetermined parameters of the degradation model based on the least squares method, and determine the cable specimen life termination point; A remaining life online prediction module, configured to online predict the remaining life of the cable according to the actual value of the correlation coefficient retention rate of the obtained cable specimen, the determined degradation model, and the cable specimen life termination point; Wherein, the signal acquisition module includes a first signal acquisition unit and a second signal acquisition unit, wherein: The first signal acquisition unit is used to select the middle part of the cable before aging as the cable specimen, generate an incident signal of the spread spectrum time domain reflectometry method by modulating the m-sequence and the sine wave in a 1:1 ratio, and inject the incident signal into the cable specimen by using a signal generator; use an oscilloscope to collect the reflected signal of the cable specimen every once in a while T collect the reflected signal of the cable specimen once; The second signal acquisition unit is used to place the middle part of the cable in the aging chamber while leaving both ends of the cable outside the aging chamber, and conduct a local accelerated thermal aging test on the cable specimen placed in the aging chamber; generate an incident signal for the spread spectrum time domain reflectometry by modulating the m-sequence and sine wave in a 1:1 ratio, and inject the incident signal into the cable specimen using a signal generator; use an oscilloscope to collect the reflected signal of the cable specimen T once every certain period of time.

8. The on-line prediction device for the remaining life of a cable according to claim 7, characterized in that, The first calculation module includes a first calculation unit and a second calculation unit, wherein: The first calculation unit is configured to calculate the correlation coefficients of the cable specimen before aging corresponding to different times of collecting the reflection signals according to the incident signal and the reflection signal in the cable specimen before aging; The second calculation unit is configured to calculate the correlation coefficients of the cable specimen after aging corresponding to different times of collecting the reflection signals according to the incident signal and the reflection signal in the cable specimen after aging.

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