Image acquisition period determination method, system, device and medium for long-distance cable

Abstract

This invention relates to the field of cable image acquisition technology, and discloses a method, system, device, and medium for determining the image acquisition cycle of long-distance cables. Based on acquired environmental data of the target long-distance cable, the cable is divided into multiple cable sub-segments. Based on acquired cable attribute information and actual usage time, the theoretical remaining service life of each cable sub-segment is determined. Based on the environmental data, a lifespan impact correction value is calculated for each cable sub-segment, including correction values ​​for temperature, humidity, wind speed, and illumination. The theoretical remaining service life is first-level corrected based on the lifespan impact correction value, and second-level corrected based on acquired fault data. Based on the actual remaining service life obtained after the second-level correction and a preset threshold, the image acquisition cycle of each cable sub-segment is determined. The method of this application ensures the timeliness and efficiency of long-distance cable image acquisition.

Description

Technical Field

[0001] This invention relates to the field of cable image acquisition technology, and in particular to a method, system, device and medium for determining the image acquisition period of long-distance cables. Background Technology

[0002] Cables, as commonly used power transmission equipment, play a crucial role in power transmission systems. During actual operation, cables face a variety of complex operating conditions and environmental factors. Due to material defects, human damage, aging, and corrosion, localized defects may appear inside the cable. If these localized defects are not detected and addressed in a timely manner, they may cause leakage current, and in severe cases, even lead to cable fires, posing a significant threat to the stability and safety of power supply. Therefore, accurate and timely location and identification of localized defects in cables is of paramount importance.

[0003] Currently, image recognition methods are widely used in the field of cable local defect location and identification. The basic principle is to acquire images of the cable and then use image processing and analysis techniques to deeply analyze the images, thereby identifying local defects within the cable. Given that cables are mostly used in outdoor environments, to ensure the long-term stable operation of the cables, it is necessary to periodically use image recognition methods to locate and identify local defects.

[0004] However, existing fixed-cycle image acquisition methods have significant limitations for long-distance cables. Due to the extreme length of long-distance cables, a short fixed image acquisition cycle, while providing timely images for local defect identification, results in a huge workload for image acquisition, and subsequent processing and analysis of massive amounts of image data is time-consuming and laborious. Conversely, a long fixed image acquisition cycle, while reducing workload, can easily lead to untimely image acquisition, making it impossible to identify local defects in the cable in a timely manner.

[0005] Therefore, determining the appropriate image acquisition cycle for long-distance cables has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] This invention provides a method, system, device, and medium for determining the image acquisition period of long-distance cables, in order to solve the technical problem of how to determine a suitable image acquisition period for long-distance cables, and to achieve the effect of providing a suitable image acquisition period for long-distance cables to perform efficient and timely local defect detection.

[0007] In a first aspect, the present invention provides a method for determining the image acquisition period of a long-distance cable, the method comprising:

[0008] Based on the environmental data of the target long-distance cable, the target long-distance cable is divided into multiple cable sub-segments;

[0009] Based on the cable attribute information and actual usage time of each cable sub-section, the theoretical remaining service life of each cable sub-section is determined.

[0010] Based on the environmental data corresponding to each cable sub-section, a lifespan impact correction value is calculated for each cable sub-section. The lifespan impact correction value includes: a temperature impact correction value, a humidity impact correction value, a wind speed impact correction value, and a light intensity impact correction value. The temperature impact correction value and the humidity impact correction value are calculated based on a first preset rule, and the wind speed impact correction value and the light intensity impact correction value are calculated based on a second preset rule. The first preset rule is calculated based on the deviation between the environmental data and the corresponding optimal usage value, and the second preset rule is calculated based on the influence relationship between the environmental data and the theoretical remaining service life.

[0011] The theoretical remaining service life of the corresponding cable sub-section is corrected firstly based on the life impact correction value of each cable sub-section, and the theoretical remaining service life after the first correction is corrected secondly based on the fault data of the target long-distance cable, so as to obtain the actual remaining service life of each cable sub-section.

[0012] The image acquisition cycle for each cable sub-segment is determined based on the relationship between the actual remaining service life of each cable sub-segment and a preset threshold.

[0013] Preferably, the step of dividing the target long-distance cable into multiple cable sub-segments based on the acquired environmental data of the target long-distance cable includes:

[0014] Based on the laying time of the target long-distance cable, the target long-distance cable is first segmented to obtain several first cable segments.

[0015] Based on a preset basic length unit, each of the first cable segments is subjected to a second segmentation process to obtain several second cable segments.

[0016] Based on the acquired environmental data of the target long-distance cable, the environmental deviation value between two adjacent cable segments is calculated, and it is determined whether the environmental deviation value is less than a preset threshold. If so, the two adjacent second cable segments are assigned to the same cable sub-segment; otherwise, the two adjacent second cable segments are assigned to different cable sub-segments, so as to divide the target long-distance cable into multiple cable sub-segments.

[0017] Preferably, the formula for calculating the environmental deviation value is:

[0018]

[0019] in: for Second cable segment and Environmental deviation values ​​between the second cable sections for The second cable section The average temperature of the quarter, for The second cable section The average temperature of the quarter, This is the temperature influence coefficient. for The second cable section Average humidity of the quarter for The second cable section Average humidity of the quarter Humidity influence coefficient for The second cable section The average wind speed of the quarter, for The second cable section The average wind speed of the quarter, The mechanical fatigue coefficient, for The second cable section Average light intensity per quarter for The second cable section Average light intensity per quarter This represents the influence coefficient of light intensity.

[0020] Preferably, determining the theoretical remaining service life of each cable sub-segment based on the acquired cable attribute information and actual usage time includes:

[0021] Obtain cable attribute information and actual usage time for all cable models. Based on the cable attribute information, conduct a service life simulation test on all cable models. Based on the service life simulation test results, obtain the relationship between cable attribute information and cable reference service life. The cable attribute information includes: rated voltage, rated current, insulation material, conductor cross-sectional area, cable structure information, laying method, and installation height.

[0022] Based on the aforementioned relationship, a cable reference service life prediction model is constructed, and the cable attribute information corresponding to each cable sub-segment is input into the cable reference service life prediction model to obtain the cable reference service life of each cable sub-segment.

[0023] The remaining service life of each cable sub-section is obtained based on the cable reference service life of each cable sub-section and the actual service time of the corresponding cable sub-section.

[0024] Preferably, the formula for calculating the temperature effect correction value is:

[0025]

[0026] in, This is a correction value for the effect of temperature. and As a preset constant, For optimal operating temperature;

[0027] The formula for calculating the humidity effect correction value is as follows:

[0028]

[0029] in, This is a correction value for the effect of humidity. and As a preset constant, For optimal operating humidity;

[0030] The formula for calculating the wind speed influence correction value is as follows:

[0031]

[0032] in, This is a correction value for the impact of wind speed. , and This is a preset constant;

[0033] The formula for calculating the illumination effect correction value is as follows:

[0034]

[0035] in, This is the correction value for the effect of illumination. , and This is a preset constant.

[0036] Preferably, the step of performing a first-level correction on the theoretical remaining service life of the corresponding cable sub-segment based on the service life impact correction value of each cable sub-segment includes:

[0037] Calculate the weighted sum of the temperature influence correction value, humidity influence correction value, wind speed influence correction value and light influence correction value corresponding to each cable sub-section to obtain the comprehensive correction value for each cable sub-section;

[0038] The theoretical remaining service life of each cable sub-section is obtained by comparing the theoretical remaining service life of each sub-section with the comprehensive correction value of the corresponding sub-section.

[0039] Preferably, the method further includes:

[0040] Based on the image acquisition cycle of each cable sub-segment, cable image data of each cable sub-segment are acquired respectively;

[0041] A preset cable local defect identification method is used to identify local defects in the cable image data, and the local defect identification results for each cable sub-segment are obtained.

[0042] Secondly, the present invention also provides an image acquisition cycle determination system for long-distance cables, used to implement the image acquisition cycle determination method for long-distance cables described above. The system includes: a cable sub-segment division unit, a theoretical remaining service life determination unit, an influence correction value calculation unit, a remaining service life correction unit, and an image acquisition cycle determination unit.

[0043] The cable sub-segment division unit is used to divide the target long-distance cable into multiple cable sub-segments based on the acquired environmental data of the target long-distance cable.

[0044] The theoretical remaining service life determination unit is used to determine the theoretical remaining service life of each cable sub-section based on the obtained cable attribute information and actual usage time corresponding to each cable sub-section.

[0045] The influence correction value calculation unit is used to calculate the lifespan influence correction value for each cable sub-section based on the environmental data corresponding to each cable sub-section. The lifespan influence correction value includes: temperature influence correction value, humidity influence correction value, wind speed influence correction value, and illumination influence correction value. The temperature influence correction value and the humidity influence correction value are calculated based on a first preset rule, and the wind speed influence correction value and the illumination influence correction value are calculated based on a second preset rule. The first preset rule is calculated based on the deviation between the environmental data and the corresponding optimal usage value, and the second preset rule is calculated based on the influence relationship between the environmental data and the theoretical remaining service life.

[0046] The remaining service life correction unit is used to perform a first-level correction on the theoretical remaining service life of the corresponding cable sub-section based on the service life impact correction value of each cable sub-section, and to perform a second-level correction on the theoretical remaining service life after the first-level correction based on the obtained fault data of the target long-distance cable, so as to obtain the actual remaining service life of each cable sub-section.

[0047] The image acquisition cycle determination unit is used to determine the image acquisition cycle of each cable sub-segment based on the relationship between the actual remaining service life of each cable sub-segment and a preset threshold.

[0048] Thirdly, the present invention also provides a computer device, the computer device including a memory, a processor and a transceiver, which are connected to each other via a bus; the memory is used to store a set of computer program instructions and data, and to transmit the stored data to the processor, the processor executes the program instructions stored in the memory to execute the image acquisition period determination method for long-distance cables described above.

[0049] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program that, when executed, implements the above-described method for determining the image acquisition period of a long-distance cable.

[0050] This application provides a method, system, device, and medium for determining the image acquisition period of a long-distance cable. Compared with the prior art, the beneficial effects of the embodiments of this application are as follows:

[0051] The image acquisition cycle determination method for long-distance cables disclosed in this application can accurately divide long-distance cables into sections and calculate their actual remaining service life. Based on the remaining service life, different image acquisition cycles are divided for each cable sub-section, ensuring the efficiency and timeliness of long-distance cable image acquisition, thereby ensuring the efficiency and timeliness of local defect identification in long-distance cables. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the steps of a method for determining the image acquisition period of a long-distance cable according to a preferred embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram of a system for determining the image acquisition period of a long-distance cable according to a preferred embodiment of the present invention;

[0054] Figure 3 This is an internal structural diagram of the computer device in an embodiment of the present invention;

[0055] Figure label:

[0056] 1-Cable sub-segment division unit, 2-Theoretical remaining service life determination unit, 3-Influence correction value calculation unit, 4-Remaining service life correction unit, 5-Image acquisition cycle determination unit. Detailed Implementation

[0057] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are provided for illustrative purposes only and should not be construed as limiting the invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of protection of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of this invention. In the description of this invention, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0058] In the description of this invention, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to communication within two components. The terms "vertical," "horizontal," "left," "right," "upper," "lower," and similar expressions used herein are for illustrative purposes only and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0059] In the description of this invention, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0060] Please see Figure 1 In an embodiment of the present invention, a method for determining the image acquisition period of a long-distance cable is provided, the method comprising:

[0061] S1. Based on the acquired environmental data of the target long-distance cable, the target long-distance cable is divided into multiple cable sub-segments; the long-distance cable generally refers to inter-provincial and inter-city cables, characterized by long distances and variable surrounding environments; the environmental data includes at least: quarterly average temperature data, quarterly average humidity data, quarterly average wind speed data, and quarterly average light intensity data; generally, by collecting historical daily temperature data, historical daily humidity data, historical daily wind speed data, and historical daily light intensity data of the previous year, and calculating the quarterly average values ​​of the historical daily temperature data, historical daily humidity data, historical daily wind speed data, and historical daily light intensity data respectively, the corresponding quarterly average temperature data, quarterly average humidity data, quarterly average wind speed data, and quarterly average light intensity data are obtained. Specifically, meteorological data for the previous year for each section along the target long-distance cable is obtained from meteorological units, websites, or apps. Historical daily temperature, humidity, wind speed, and solar irradiance data are then extracted from this data to calculate the quarterly average temperature, humidity, wind speed, and solar irradiance. This application fully considers the characteristic that environmental data for the same location in the same quarter is similar, but environmental data varies significantly across different quarters. By selecting quarterly average temperature, humidity, wind speed, and solar irradiance data as environmental data, it avoids computational inefficiency due to large data volumes and also prevents annual average data from failing to accurately reflect changes in the surrounding environment, thus avoiding inaccurate cable sub-segment division. In this application, the target long-distance cable is divided into multiple cable sub-segments. The division of these sub-segments considers not only the distance and cable laying time but also the surrounding environment of the target long-distance cable. Specifically, based on the laying time of the target long-distance cable, the cable is first segmented, dividing cables laid at the same time into the same segment to eliminate the impact of laying time on the service life of the target long-distance cable, resulting in several first cable segments. Further, a basic length unit is set, and each first cable segment is segmented according to this basic length unit, resulting in several second cable segments. The basic length unit should be less than a preset threshold, which can be preset to a certain value, such as 1000m, or set as a preset proportion of the total length, such as 2.5% of the total length. This segmentation process is equivalent to gridding the target long-distance cable, facilitating refined management of the cable.

[0062] Due to the excessive length of long-distance cables, each cable segment often faces different surrounding environments. Therefore, after segmenting the target long-distance cable, environmental data corresponding to each second cable segment is obtained from the environmental data of the target long-distance cable. For each second cable segment, there may be adjacent second cable segments with similar temperature, humidity, wind speed, and light intensity, but they are classified as different second cable segments, resulting in a large number of second cable segments and low computational efficiency. In one embodiment of this application, for two adjacent second cable segments, based on the environmental data corresponding to each cable segment, the environmental deviation value between the two adjacent second cable segments is calculated. It is then determined whether the environmental deviation value is less than a pre-set environmental deviation threshold. If so, it indicates that the average quarterly temperature, average quarterly humidity, average quarterly wind speed, and average quarterly light intensity of these two adjacent second cable segments have a comparable impact on their cable lifespan, and thus these two adjacent second cable segments are classified into the same cable sub-segment. If not, it indicates that the average quarterly temperature, average quarterly humidity, average quarterly wind speed, and average quarterly light intensity of these two adjacent second cable segments have significantly different impacts on their cable lifespan, and thus they cannot be classified into the same cable sub-segment, and thus these two adjacent second cable segments are classified into different cable sub-segments. Finally, the target long-distance cable is divided into multiple cable sub-segments. The formula for calculating the environmental deviation value is:

[0063]

[0064] in: for Second cable segment and Environmental deviation values ​​between the second cable sections for The second cable section The average temperature of the quarter, for The second cable section The average temperature of the quarter, This is the temperature influence coefficient. for The second cable section Average humidity of the quarter for The second cable section Average humidity of the quarter Humidity influence coefficient for The second cable section The average wind speed of the quarter, for The second cable section The average wind speed of the quarter, The mechanical fatigue coefficient, for The second cable section Average light intensity per quarter for The second cable section Average light intensity per quarter This represents the influence coefficient of light intensity.

[0065] In another embodiment of this application, after obtaining several second cable segments, the second cable segments are further processed using a comprehensive cable influence value. This comprehensive cable influence value is set to reflect the combined effects of temperature, humidity, wind speed, and sunlight on the target long-distance cable. The comprehensive cable influence value for each second cable segment is calculated using the following formula:

[0066]

[0067] in, for The overall impact value of the cable in the second cable segment. The fitted temperature influence factor, Boltzmann's constant, The activation energy of cable materials, The humidity influence factor is the fitted value. The fitted wind speed influence factor is... The fitted light intensity influence factor is .

[0068] Overall impact value of cables The magnitude of the value reflects the impact of the quarterly average temperature, humidity, wind speed, and light intensity of the second cable segment on its cable lifespan. For example, the larger the overall impact value of the second cable segment, the greater the impact of these factors on its cable lifespan; conversely, the smaller the overall impact value, the smaller the impact of these factors on its cable lifespan.

[0069] After obtaining the comprehensive influence value of each cable segment, the influence deviation value between two adjacent second cable segments is calculated. It is then determined whether the influence deviation value is less than the preset comprehensive influence deviation value threshold. If so, the two adjacent second cable segments are assigned to the same cable sub-segment. If not, the two adjacent second cable segments are assigned to different cable sub-segments. Finally, the target long-distance cable is divided into multiple cable sub-segments.

[0070] For example, the comprehensive impact value of a certain second cable segment is The combined impact value of its adjacent second cable segment is At this time, the influence deviation value between the two second cable segments is If the deviation value is less than the threshold value of the comprehensive influence deviation value, it means that the average temperature, average humidity, average wind speed, and average light intensity of each quarter of these two adjacent second cable segments have a similar impact on the lifespan of these two adjacent second cable segments, and they can be classified into the same cable sub-segment. Conversely, if the deviation value is less than the threshold value of the comprehensive influence deviation value, it means that the average temperature, average humidity, average wind speed, and average light intensity of each quarter of these two adjacent second cable segments have a significantly different impact on the lifespan of these two adjacent second cable segments, and they cannot be classified into the same cable sub-segment. In this way, the long-distance cable can be more reasonably divided into multiple cable sub-segments.

[0071] S2. Based on the obtained cable attribute information and actual usage time of each cable sub-segment, determine the theoretical remaining service life of each cable sub-segment. The theoretical remaining service life of the cable is related to the cable's baseline service life and actual usage time. The cable's baseline service life reflects the cable's service life under ideal usage conditions and is generally obtained through service life simulation tests. Service life simulation tests include two types: one is a laboratory test where certain test parameters are set to simulate the service life of the cable sample, thereby determining the baseline service life of the cable sample; the other is a simulation test conducted in a computing device using a simulation environment to simulate real test parameters, thereby determining the baseline service life of the cable sample.

[0072] The baseline service life of a cable is related not only to its rated voltage, rated current, insulation material, conductor cross-sectional area, and cable structure information, but also to its laying method and installation height. In one embodiment of this application, a cable baseline service life prediction model is constructed based on the results of service life simulation tests. This model is then used to predict the baseline service life of cables of different models and laying methods. Specifically, based on the obtained cable attribute information for all cable models, including at least: rated voltage, rated current, insulation material, conductor cross-sectional area, cable structure information, laying method, and installation height, service life simulation tests are conducted on all cable models. Based on the results of the service life simulation tests, the relationship between cable attribute information and the cable baseline service life is obtained. Based on this relationship, a cable baseline service life prediction model is constructed. For each sub-segment of the target long-length cable, its corresponding cable attribute information is input into the cable baseline service life prediction model to obtain the cable baseline service life of each sub-segment.

[0073] Furthermore, the difference between the reference service life of the cable and the actual service life of each cable sub-section is calculated, and this difference is the theoretical remaining service life of that cable sub-section.

[0074] S3. Based on the environmental data corresponding to each cable sub-segment, calculate the lifespan impact correction value for each cable sub-segment. The lifespan impact correction value includes: temperature impact correction value, humidity impact correction value, wind speed impact correction value, and light impact correction value. The temperature impact correction value and the humidity impact correction value are calculated based on a first preset rule, and the wind speed impact correction value and the light impact correction value are calculated based on a second preset rule. The first preset rule is calculated based on the deviation between the environmental data and the corresponding optimal usage value, and the second preset rule is calculated based on the influence relationship between the environmental data and the theoretical remaining service life. Since the cable baseline service life obtained through service life simulation test is obtained under ideal usage conditions, while the actual use of cables is usually in outdoor environments, the outdoor environment is relatively more complex and variable. Especially for the long-distance cables in this application, it may involve cross-province and cross-city scenarios, and the outdoor environment of each cable sub-segment is not the same. The difference in outdoor environment will obviously affect the service life of the cable. In this application, the impact of environmental data on the theoretical remaining service life of the target long-distance cable is converted into temperature impact correction values, humidity impact correction values, wind speed impact correction values, and light impact correction values ​​to correct the theoretical remaining service life.

[0075] Temperature, humidity, and light intensity all affect the oxidation rate of cable materials. Generally, higher temperatures, humidity, and light intensity lead to faster oxidation and consequently reduced lifespan. Wind speed primarily affects cable lifespan through mechanical wear; for example, higher wind speeds subject long-distance cables to greater tensile forces, resulting in more wear and tear and a greater impact on their lifespan. This application uses quarterly averages of temperature, humidity, wind speed, and light intensity to calculate the correction values ​​for each effect. Quarterly averages, compared to monthly or daily averages, significantly reduce computational load and avoid inaccuracies in reflecting the true impact of temperature, humidity, wind speed, and light intensity on cable lifespan. This improves the accuracy of determining the image acquisition cycle for long-distance cables while simultaneously increasing computational efficiency.

[0076] In a preferred embodiment of this application, the temperature effect correction value and the humidity effect correction value are calculated based on a first preset rule. The first preset rule is calculated based on the deviation between environmental data and the corresponding optimal usage value. Through simulation studies on cable service life, it was found that the effect of temperature on cable service life can be divided into linear and nonlinear parts. The nonlinear part can be fitted to the natural logarithm to a certain extent. Therefore, based on the deviation between the average temperature of each quarter and the optimal usage temperature, the temperature effect correction value for the theoretical remaining service life of the target long-distance cable is determined. The calculation formula for the temperature effect correction value is as follows:

[0077]

[0078] in, This is a correction value for the effect of temperature. and This is a preset constant that can be obtained through experimentation. The optimal operating temperature.

[0079] Through simulation studies on cable service life, it was found that the impact of humidity on cable service life also consists of two parts: a linear part and a curved part. The curved part can be fitted to a certain extent using trigonometric functions. Therefore, based on the deviation between the average humidity of each quarter and the optimal operating humidity, the humidity impact correction value for the theoretical remaining service life of the target long-distance cable is determined. The formula for calculating the humidity impact correction value is as follows:

[0080]

[0081] in, This is a correction value for the effect of humidity. and This is a preset constant that can be obtained through experimentation. For optimal operating humidity.

[0082] The wind speed and illumination impact correction values ​​are calculated based on a second preset rule. This second preset rule is set based on the relationship between environmental data and the theoretical remaining service life. Since wind speed typically has a negative impact on cable lifespan, unlike the effects of temperature and humidity, the impact of temperature decreases as the temperature approaches the optimal operating temperature, and the same applies to humidity and temperature. However, lower wind speeds have a smaller negative impact on cable lifespan. Therefore, wind speed and the wind speed impact correction value are positively correlated; that is, the higher the quarterly average wind speed, the larger the wind speed impact correction value needs to be. In practical applications, simulation studies show that the relationship between the two is roughly a polynomial. Therefore, the wind speed impact correction value for the theoretical remaining service life of the target long-distance cable is determined based on the quarterly average wind speed. The calculation formula for the wind speed impact correction value is as follows:

[0083]

[0084] in, This is a correction value for the impact of wind speed. , and This is a preset constant that can be obtained through experimentation.

[0085] Since the impact of sunlight on cable lifespan is generally negative, similar to the impact of wind speed, lower sunlight intensity has a smaller negative impact on cable lifespan. Therefore, there is a positive correlation between sunlight intensity and the sunlight impact correction value; that is, the higher the quarterly average sunlight intensity, the larger the required correction value. In practical applications, simulation studies show that the relationship between the two is roughly a polynomial relationship. Therefore, the sunlight impact correction value for the theoretical remaining lifespan of the target long-distance cable is determined based on the quarterly average sunlight intensity. The formula for calculating the sunlight impact correction value is as follows:

[0086]

[0087] in, This is the correction value for the effect of illumination. , and This is a preset constant that can be obtained through experimentation.

[0088] S4. Based on the lifespan impact correction value of each cable sub-section, perform a first-level correction on the theoretical remaining lifespan of the corresponding cable sub-section, and perform a second-level correction on the theoretical remaining lifespan after the first-level correction based on the obtained fault data of the target long-distance cable, to obtain the actual remaining lifespan of each cable sub-section; after obtaining the temperature impact correction value, humidity impact correction value, wind speed impact correction value, and light impact correction value of each cable sub-section, perform a first-level correction on the theoretical remaining lifespan of each cable sub-section using the corresponding temperature impact correction value, humidity impact correction value, wind speed impact correction value, and light impact correction value, to obtain the theoretical remaining lifespan after the first-level correction for each cable sub-section. Specifically, the weighted sum of the temperature, humidity, wind speed, and illumination correction values ​​for each cable sub-segment is calculated to obtain the comprehensive correction value for each cable sub-segment. The first difference between the theoretical remaining service life of each cable sub-segment and the corresponding comprehensive correction value is then calculated; this first difference represents the theoretical remaining service life of that cable sub-segment after the first-level correction. The weights of the temperature, humidity, wind speed, and illumination correction values ​​are fitted using simulation experiments.

[0089] In one embodiment of this application, after performing a first-level correction on the theoretical remaining service life using correction values ​​for temperature, humidity, wind speed, and illumination, a second-level correction is required using fault data for each cable sub-segment. Cable fault repair directly impacts the theoretical remaining service life of the cable. Different fault frequencies can be fitted to specific cable service life impact years. Based on these impact years, the theoretical remaining service life after the first-level correction is further corrected using a second-level correction to obtain the final actual remaining service life for each cable sub-segment. Specifically, the second difference between the theoretical remaining service life after the first-level correction and the cable service life impact years is calculated; this second difference represents the actual remaining service life corresponding to that cable sub-segment.

[0090] S5. Determine the image acquisition cycle for each cable sub-segment based on the relationship between the actual remaining service life of each cable sub-segment and a preset threshold. In one embodiment of this application, a preset threshold is used to determine the actual remaining service life of each cable sub-segment. If the actual remaining service life of the cable sub-segment is greater than the preset threshold, then a first image acquisition cycle is used to acquire images of the cable sub-segment. If the actual remaining service life of the cable sub-segment is less than or equal to the preset threshold, then a second image acquisition cycle is used to acquire images of the cable sub-segment, wherein the first image acquisition cycle is greater than the second image acquisition cycle. Similarly, the image acquisition cycle can also be determined by interval mapping. A mapping table between different actual remaining service life intervals and image acquisition cycles is pre-constructed. The actual remaining service life of a certain cable sub-segment is compared with the constructed mapping table to see which actual remaining service life interval the cable sub-segment falls within. The image acquisition cycle corresponding to this actual remaining service life interval is the image acquisition cycle of the cable sub-segment.

[0091] Each cable sub-segment has a corresponding image acquisition cycle. Images of the corresponding cable sub-segment are periodically acquired according to this cycle to obtain cable image data. Further, a pre-defined cable local defect identification method is used to identify local defects in the cable image data, yielding the local defect identification results for each cable sub-segment. Regarding the selection of the cable local defect identification method, a pre-built and trained image recognition model can be used to analyze the cable image data to identify whether local defects exist in the cable sub-segment. Other methods can also be used for local defect identification. No specific limitation is made on which local defect identification method is used for the cable image data; therefore, this application can be combined with any local defect identification method, making it widely applicable.

[0092] In a preferred embodiment of the present invention, the target long-distance cable is divided into multiple cable sub-segments based on the acquired environmental data of the target long-distance cable; the theoretical remaining service life of each cable sub-segment is determined based on the acquired cable attribute information and actual usage time corresponding to each cable sub-segment; and a lifespan impact correction value is calculated for each cable sub-segment based on the environmental data corresponding to each cable sub-segment. The lifespan impact correction value includes: temperature impact correction value, humidity impact correction value, wind speed impact correction value, and illumination impact correction value. The temperature impact correction value and humidity impact correction value are calculated based on a first preset rule, and the wind speed impact correction value and illumination impact correction value are calculated based on a first preset rule. The calculation is based on a second preset rule; the first preset rule is based on the deviation between environmental data and the corresponding optimal usage value, and the second preset rule is based on the influence relationship between environmental data and theoretical remaining service life; the theoretical remaining service life of the corresponding cable sub-segment is corrected firstly according to the life influence correction value of each cable sub-segment, and then corrected secondly according to the fault data of the acquired target long-distance cable, to obtain the actual remaining service life of each cable sub-segment; the image acquisition cycle of each cable sub-segment is determined according to the relationship between the actual remaining service life of each cable sub-segment and a preset threshold. The image acquisition cycle determination method for long-distance cables disclosed in this application can accurately divide long-distance cables into segments and calculate the actual remaining service life, and divide each cable sub-segment into different image acquisition cycles based on the remaining service life, ensuring the timeliness and efficiency of long-distance cable image acquisition.

[0093] Accordingly, such as Figure 2 As shown, based on a method for determining the image acquisition period of a long-distance cable, this embodiment of the invention also provides a system for determining the image acquisition period of a long-distance cable, which implements the method for determining the image acquisition period of a long-distance cable disclosed in this embodiment of the invention. The system includes: a cable sub-segment division unit 1, a theoretical remaining service life determination unit 2, an influence correction value calculation unit 3, a remaining service life correction unit 4, and an image acquisition period determination unit 5.

[0094] The cable sub-segment division unit 1 is used to divide the target long-distance cable into multiple cable sub-segments based on the acquired environmental data of the target long-distance cable.

[0095] The theoretical remaining service life determination unit 2 is used to determine the theoretical remaining service life of each cable sub-section based on the obtained cable attribute information and actual usage time corresponding to each cable sub-section.

[0096] The influence correction value calculation unit 3 is used to calculate the life influence correction value of each cable sub-section based on the environmental data corresponding to each cable sub-section. The life influence correction value includes: temperature influence correction value, humidity influence correction value, wind speed influence correction value and light influence correction value. The temperature influence correction value and the humidity influence correction value are set as the deviation between the corresponding average value and the optimal use value. The wind speed influence correction value and the light influence correction value are set as the influence of the corresponding average value on the theoretical remaining service life.

[0097] The remaining service life correction unit 4 is used to perform a first-level correction on the theoretical remaining service life of the corresponding cable sub-section based on the service life impact correction value of each cable sub-section, and to perform a second-level correction on the theoretical remaining service life after the first-level correction based on the fault data of the target long-distance cable, so as to obtain the actual remaining service life of each cable sub-section.

[0098] The image acquisition cycle determination unit 5 is used to determine the image acquisition cycle of each cable sub-section based on the relationship between the actual remaining service life of each cable sub-section and a preset threshold.

[0099] Specific limitations regarding the image acquisition period determination system for long-distance cables can be found in the aforementioned limitations regarding the image acquisition period determination method for long-distance cables, and will not be repeated here. Those skilled in the art will recognize that the various modules and steps described in conjunction with the embodiments disclosed in this invention can be implemented in hardware, software, or a combination of both. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0100] like Figure 3 As shown, an embodiment of the present invention provides a computer device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps in the above embodiment of the method for determining the image acquisition period of a long-distance cable, for example... Figure 1 Steps S1 to S5 as described above.

[0101] Those skilled in the art will understand that the illustrations Figure 3 This is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the computer device may also include input / output devices, network access devices, buses, etc.

[0102] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the computer device, connecting various parts of the computer device via various interfaces and lines.

[0103] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0104] If the modules integrated into the computer device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0105] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0106] Accordingly, embodiments of the present invention provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform steps as described in the above-described embodiment of the image acquisition period determination method for long-distance cables, for example... Figure 1 Steps S1 to S5 as described above.

[0107] In summary, the embodiments of this application provide a method, system, device, medium for determining the image acquisition period of long-distance cables, and a corresponding method for identifying local defects in long-distance cables, addressing the technical problem of improving the integrity and intelligent management level of data in the new energy industry. The method includes: dividing the target long-distance cable into multiple cable sub-segments based on acquired environmental data; determining the theoretical remaining service life of each cable sub-segment based on the acquired cable attribute information and actual usage time; and calculating the lifespan impact correction value for each cable sub-segment based on the environmental data corresponding to each cable sub-segment. The lifespan impact correction value includes: temperature impact correction value, humidity impact correction value, wind speed impact correction value, and illumination impact correction value. The impact correction values ​​for wind speed and humidity are calculated based on a first preset rule, while the impact correction values ​​for wind speed and illumination are calculated based on a second preset rule. The first preset rule is based on the deviation between environmental data and the corresponding optimal usage value, and the second preset rule is based on the influence relationship between environmental data and the theoretical remaining service life. The theoretical remaining service life of each cable sub-segment is first-level corrected based on its lifespan impact correction value, and then second-level corrected based on the acquired fault data of the target long-distance cable, resulting in the actual remaining service life of each cable sub-segment. The image acquisition cycle for each cable sub-segment is determined based on the relationship between its actual remaining service life and a preset threshold. This application discloses a method for determining the image acquisition cycle of long-distance cables, which enables accurate segmentation and calculation of the actual remaining service life of long-distance cables, and allows for different image acquisition cycles for each cable sub-segment based on its remaining service life, ensuring the timeliness and efficiency of long-distance cable image acquisition.

[0108] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0109] The embodiments described above are merely preferred embodiments of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application. Therefore, the scope of protection of this patent application should be determined by the scope of the claims.

Claims

1. A method for determining the image acquisition period of a long-distance cable, characterized in that, The method includes: Based on the environmental data of the target long-distance cable, the target long-distance cable is divided into multiple cable sub-segments; Based on the cable attribute information and actual usage time of each cable sub-section, the theoretical remaining service life of each cable sub-section is determined. Based on the environmental data corresponding to each cable sub-section, a lifespan impact correction value is calculated for each cable sub-section. The lifespan impact correction value includes: a temperature impact correction value, a humidity impact correction value, a wind speed impact correction value, and a light intensity impact correction value. The temperature impact correction value and the humidity impact correction value are calculated based on a first preset rule, and the wind speed impact correction value and the light intensity impact correction value are calculated based on a second preset rule. The first preset rule is calculated based on the deviation between the environmental data and the corresponding optimal usage value, and the second preset rule is calculated based on the influence relationship between the environmental data and the theoretical remaining service life. The theoretical remaining service life of the corresponding cable sub-section is corrected firstly based on the life impact correction value of each cable sub-section, and the theoretical remaining service life after the first correction is corrected secondly based on the fault data of the target long-distance cable, so as to obtain the actual remaining service life of each cable sub-section. The image acquisition cycle for each cable sub-segment is determined based on the relationship between the actual remaining service life of each cable sub-segment and a preset threshold. The formula for calculating the temperature effect correction value is as follows: wherein, is a temperature influence correction value, and is a preset constant, is an optimal use temperature; The formula for calculating the humidity effect correction value is as follows: wherein, is a humidity influence correction value, and is a preset constant, is the optimal use humidity; The formula for calculating the wind speed influence correction value is as follows: wherein, is a wind speed influence correction value, , and is a preset constant; The formula for calculating the correction value for the illumination effect is: wherein, is a light influence correction value, , and is a preset constant.

2. The method of claim 1, wherein, The step of dividing the target long-distance cable into multiple cable sub-segments based on the acquired environmental data of the target long-distance cable includes: Based on the obtained laying time of the target long-distance cable, the target long-distance cable is subjected to a first segmentation process to obtain several first cable segments. Based on a preset basic length unit, each of the first cable segments is subjected to a second segmentation process to obtain several second cable segments. Based on the acquired environmental data of the target long-distance cable, the environmental deviation value between two adjacent second cable segments is calculated. It is determined whether the environmental deviation value is less than a preset environmental deviation threshold. If so, the two adjacent second cable segments are assigned to the same cable sub-segment. If not, the two adjacent second cable segments are assigned to different cable sub-segments, so as to divide the target long-distance cable into multiple cable sub-segments.

3. The method of claim 2, wherein the image acquisition period is determined based on the distance between the camera and the object. The formula for calculating the environmental deviation value is: in: for Second cable segment and Environmental deviation values ​​between the second cable sections for The second cable section The average temperature of the quarter, for The second cable section The average temperature of the quarter, This is the temperature influence coefficient. for The second cable section Average humidity of the quarter for The second cable section Average humidity of the quarter Humidity influence coefficient for The second cable section The average wind speed of the quarter, for The second cable section The average wind speed of the quarter, The mechanical fatigue coefficient, for The second cable section Average light intensity per quarter for The second cable section Average light intensity per quarter This represents the influence coefficient of light intensity.

4. The method for determining the image acquisition period of a long-distance cable as described in claim 1, characterized in that, The determination of the theoretical remaining service life of each cable sub-segment based on the acquired cable attribute information and actual usage time includes: Obtain cable attribute information and actual usage time for all cable models, and conduct service life simulation tests on all cable models based on the cable attribute information. According to the service life simulation test results, obtain the relationship between cable attribute information and cable reference service life. The cable attribute information includes: rated voltage, rated current, insulation material, conductor cross-sectional area, cable structure information, laying method and erection height. Based on the aforementioned relationship, a cable reference service life prediction model is constructed, and the cable attribute information corresponding to each cable sub-segment is input into the cable reference service life prediction model to obtain the cable reference service life of each cable sub-segment. The remaining service life of each cable sub-section is obtained based on the cable reference service life of each cable sub-section and the actual service time of the corresponding cable sub-section.

5. The method of claim 1, wherein, The step of performing a first-level correction on the theoretical remaining service life of the corresponding cable sub-section based on the service life impact correction value of each cable sub-section includes: Calculate the weighted sum of the temperature influence correction value, humidity influence correction value, wind speed influence correction value and light influence correction value corresponding to each cable sub-section to obtain the comprehensive correction value for each cable sub-section; The theoretical remaining service life of each cable sub-section is obtained by comparing the theoretical remaining service life of each sub-section with the comprehensive correction value of the corresponding sub-section.

6. The method of claim 1, wherein, The method further includes: Based on the image acquisition cycle of each cable sub-segment, cable image data of each cable sub-segment are acquired respectively; A preset cable local defect identification method is used to identify local defects in the cable image data, and the local defect identification results for each cable sub-segment are obtained.

7. A system for determining an image acquisition period for a long-range cable for implementing the method of determining an image acquisition period for a long-range cable according to any one of claims 1 to 6, characterized in that The system includes: a cable sub-segment division unit, a theoretical remaining service life determination unit, an impact correction value calculation unit, a remaining service life correction unit, and an image acquisition cycle determination unit; The cable sub-segment division unit is used to divide the target long-distance cable into multiple cable sub-segments based on the acquired environmental data of the target long-distance cable. The theoretical remaining service life determination unit is used to determine the theoretical remaining service life of each cable sub-section based on the obtained cable attribute information and actual usage time corresponding to each cable sub-section. The influence correction value calculation unit is used to calculate the lifespan influence correction value for each cable sub-section based on the environmental data corresponding to each cable sub-section. The lifespan influence correction value includes: temperature influence correction value, humidity influence correction value, wind speed influence correction value, and illumination influence correction value. The temperature influence correction value and the humidity influence correction value are calculated based on a first preset rule, and the wind speed influence correction value and the illumination influence correction value are calculated based on a second preset rule. The first preset rule is calculated based on the deviation between the environmental data and the corresponding optimal usage value, and the second preset rule is calculated based on the influence relationship between the environmental data and the theoretical remaining service life. The remaining service life correction unit is used to perform a first-level correction on the theoretical remaining service life of the corresponding cable sub-section based on the service life impact correction value of each cable sub-section, and to perform a second-level correction on the theoretical remaining service life after the first-level correction based on the obtained fault data of the target long-distance cable, so as to obtain the actual remaining service life of each cable sub-section. The image acquisition cycle determination unit is used to determine the image acquisition cycle of each cable sub-section based on the relationship between the actual remaining service life of each cable sub-section and a preset threshold. The formula for calculating the temperature effect correction value is as follows: wherein, is a temperature influence correction value, and is a preset constant, is an optimal use temperature; The formula for calculating the humidity effect correction value is as follows: wherein, is a humidity influence correction value, and is a preset constant, is an optimal use humidity; The formula for calculating the wind speed influence correction value is as follows: in, This is a correction value for the impact of wind speed. , and This is a preset constant; The formula for calculating the illumination effect correction value is as follows: wherein, is a light influence correction value, , and is a preset constant.

8. A computer device, comprising: The computer device includes a memory, a processor, and a transceiver, which are connected to each other via a bus; the memory is used to store a set of computer program instructions and data, and to transmit the stored data to the processor, and the processor executes the program instructions stored in the memory to perform the image acquisition period determination method for long-distance cables as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program that, when executed, implements the method for determining the image acquisition period of a long-distance cable as described in any one of claims 1 to 6.

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