Cable fault factor determination system and method based on parameter evolution identification

Abstract

The embodiment of the invention discloses a cable fault factor determination system and method based on parameter evolution identification, and the method comprises the steps: obtaining first parameter data of each first sensor of a to-be-identified cable in preset time, and determining an abnormal comparison value of a first parameter type, determining whether the first parameter data is fault parameter data based on the abnormal comparison value and the plurality of first parameter values, determining a plurality of to-be-selected fault factors based on the fault parameter data and pre-stored matching fault information, and obtaining second parameter data of a second sensor associated with the to-be-selected fault factors within a preset time, and determining a data processing mode of the second parameter data, performing data processing according to the data processing mode of the second parameter data to obtain screening reference data, and performing screening processing on the to-be-selected fault factors according to the screening reference data to obtain final fault factors. According to the scheme, the final cable fault reason can be positioned step by step through different parameter data, and the accuracy of cable fault identification is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of cable fault technology, and in particular, to a system and method for determining cable fault factors based on parameter evolution identification. Background Art

[0002] Electricity is an indispensable part of modern industrial production, and cables, as an important component responsible for transmitting electrical energy in the power system, bear huge responsibilities. However, cables often have various faults during long-term use, and these faults are very likely to cause accidents. Cable failure is a key issue in the power system, which may cause power outages in the power system, causing production stagnation, traffic paralysis, and even endangering personnel safety. Therefore, timely diagnosis of the cause of cable failure can not only avoid the occurrence of these problems, but also improve the stability and reliability of the power system. In addition, fault diagnosis is of great significance for preventing power loss and equipment damage caused by cable failure, saving energy and maintaining the service life of power equipment.

[0003] Most of the existing cable fault identification methods determine the cable fault type and cause based on the detected sensor parameter values, or use on-site fault confirmation. In the above methods, on-site fault confirmation requires manpower costs and is not conducive to the first-time cable fault repair. The sensor value determination method can only determine the approximate cable fault type, which is not accurate enough. Summary of the invention

[0004] The embodiments of the present invention provide a cable fault factor determination system and method based on parameter evolution identification, which solves the problem that on-site fault confirmation in the existing cable fault identification technology requires manpower costs and is not conducive to the first-time cable fault repair, and the sensor value determination method can only determine the approximate cable fault type and has insufficient accuracy. It can gradually locate the final cause of the cable fault through different parameter data, thereby improving the accuracy of cable fault identification.

[0005] In a first aspect, an embodiment of the present invention provides a method for determining cable fault factors based on parameter evolution identification, comprising:

[0006] Acquire first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time;

[0007] Determine the corresponding abnormal comparison value according to the first parameter type, determine whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point, and if the first parameter data is fault parameter data, perform matching processing based on the fault parameter data and pre-stored matching fault information to obtain multiple candidate fault factors of the faulty cable to be identified;

[0008] Obtain second parameter data collected by second sensors respectively associated with each candidate fault factor within a preset time, determine the data type of each second parameter data and the corresponding data processing method, process the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain corresponding screening reference data, and screen each candidate fault factor according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

[0009] Optionally, the determining whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point includes:

[0010] Compare the first parameter value at each time point with the abnormal comparison value, and when there is an abnormal parameter value greater than the abnormal comparison value in the first parameter value, determine the change trend of the first parameter value at each subsequent time point of the time point corresponding to the abnormal parameter value;

[0011] When the change trend is an upward trend, the corresponding first parameter data is determined as fault parameter data.

[0012] Optionally, the pre-stored matching fault information includes multiple matching fault factors and corresponding associated fault parameter types, and the matching processing based on the fault parameter data and the pre-stored matching fault information to obtain multiple candidate fault factors of the faulty cable to be identified includes:

[0013] The fault parameter types in the fault parameter data are matched with the associated fault parameter types of each matching fault factor, and the matching fault factor corresponding to the associated fault parameter type that successfully matches the fault parameter type is determined as the candidate fault factor of the faulty cable to be identified.

[0014] Optionally, the data type includes an image type and a numerical type, and the processing of the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain the corresponding screening reference data includes:

[0015] In the case where the data type is a numerical type, determining a change trend and a change rate of a second parameter value in the second parameter data, and determining the change trend and the change rate as screening reference data for the second parameter data;

[0016] In the case where the data type is an image type, image recognition processing is performed on the images corresponding to each time point in the second parameter data, and the image recognition result is determined as the screening reference data for the second parameter data.

[0017] Optionally, performing image recognition processing on the images corresponding to each time point in the second parameter data includes:

[0018] Determine an identification feature associated with the candidate fault factor corresponding to the second parameter data, and identify whether the identification feature exists in the image corresponding to each time point in the second parameter data.

[0019] Optionally, the screening process of each candidate fault factor according to the screening reference data to obtain the final fault factor of the faulty cable to be identified includes:

[0020] In the case where the screening reference data is a change trend and a change rate, a preset screening condition is determined according to the second parameter type in the second parameter data corresponding to the change trend and the change rate, and in the case where both the change trend and the change rate meet the preset screening condition, the corresponding associated candidate fault factor is determined as the final fault factor;

[0021] In the case where the screening reference data is an image recognition result, the number of feature images having the recognition feature is determined according to the image recognition result, and whether the corresponding associated candidate fault factor is the final fault factor is determined according to the recognition feature and the number of feature images.

[0022] Optionally, determining whether the corresponding associated candidate fault factor is a final fault factor according to the identification feature and the number of feature images includes:

[0023] Determine the preset comparison number associated with the identification feature, compare the feature image number with the preset comparison number, and when the feature image number is greater than the preset comparison number, determine that the corresponding associated candidate fault factor is the final fault factor, otherwise, determine that the corresponding associated candidate fault factor is not the final fault factor.

[0024] In a second aspect, an embodiment of the present invention further provides a cable fault factor determination system based on parameter evolution identification, comprising:

[0025] An acquisition module, used to acquire first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time;

[0026] a fault data determination module, configured to determine a corresponding abnormal comparison value according to the first parameter type, and determine whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point;

[0027] A candidate fault determination module, used for, when the first parameter data is fault parameter data, performing matching processing based on the fault parameter data and pre-stored matching fault information to obtain a plurality of candidate fault factors of the faulty cable to be identified;

[0028] The acquisition module is further used to acquire second parameter data collected by second sensors respectively associated with each of the selected fault factors within a preset time;

[0029] A reference data determination module, used to determine the data type of each second parameter data and the corresponding data processing method, and to process the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain the corresponding screening reference data;

[0030] The final fault determination module is used to screen each candidate fault factor according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

[0031] In a third aspect, an embodiment of the present invention further provides a cable fault factor determination device based on parameter evolution identification, the device comprising:

[0032] one or more processors;

[0033] a storage device for storing one or more programs,

[0034] When the one or more programs are executed by the one or more processors, the one or more processors implement the cable fault factor determination method based on parameter evolution identification described in an embodiment of the present invention.

[0035] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer executable instructions, which, when executed by a computer processor, are used to execute the cable fault factor determination method based on parameter evolution identification described in an embodiment of the present invention.

[0036] In an embodiment of the present invention, first parameter data respectively collected by each first sensor of a faulty cable to be identified within a preset time are obtained, the first parameter data including a first parameter type and a first parameter value at each time point within the preset time, a corresponding abnormal comparison value is determined according to the first parameter type, and whether the first parameter data is fault parameter data is determined based on the abnormal comparison value and the first parameter value at each time point, and when the first parameter data is fault parameter data, matching processing is performed based on the fault parameter data and pre-stored matching fault information to obtain a plurality of candidate fault factors of the faulty cable to be identified, and second parameter data collected by a second sensor respectively associated with each candidate fault factor within the preset time are obtained, and a data type and a corresponding data processing method of each second parameter data are determined, and the second parameter data are processed according to the data processing method corresponding to the data type of each second parameter data to obtain corresponding screening reference data, and each candidate fault factor is screened according to the screening reference data to obtain a final fault factor of the faulty cable to be identified. This solution identifies the final fault factor of the cable through parameter evolution identification, which solves the problem that on-site fault confirmation in existing cable fault identification technology requires manpower costs and is not conducive to the first-time cable fault repair. The sensor value determination method can only determine the approximate cable fault type and is not accurate enough. It can gradually locate the final cause of the cable fault through different parameter data, thereby improving the accuracy of cable fault identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flowchart of a method for determining cable fault factors based on parameter evolution identification provided by an embodiment of the present invention;

[0038] Figure 2 A flowchart of another method for determining cable fault factors based on parameter evolution identification provided by an embodiment of the present invention;

[0039] Figure 3 A flowchart of another method for determining cable fault factors based on parameter evolution identification provided by an embodiment of the present invention;

[0040] Figure 4 A module structure block diagram of a cable fault factor determination system based on parameter evolution identification provided by an embodiment of the present invention;

[0041] Figure 5 A schematic diagram of the structure of a cable fault factor determination device based on parameter evolution identification provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, rather than to limit the embodiments of the present invention. It is also necessary to explain that, for ease of description, only parts related to the embodiments of the present invention are shown in the accompanying drawings, rather than all structures.

[0043] The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and or or" in the specification and claims represents at least one of the connected objects, and the character "or" generally indicates that the objects associated before and after are in an "or" relationship.

[0044] The cable fault factor determination method based on parameter evolution identification provided in the embodiment of the present application can be applied to the scenario of determining cable fault factors. The cable fault factor determination method based on parameter evolution identification provided in the embodiment of the present application, the execution subject of each step can be a computer device, which refers to any electronic device with data calculation, processing and storage capabilities, such as mobile phones, PCs (Personal Computers), tablet computers and other terminal devices, and can also be servers and other devices, which are not limited in the embodiment of the present application.

[0045] Figure 1 A flowchart of a method for determining cable fault factors based on parameter evolution identification provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, specifically including:

[0046] Step S101: acquiring first parameter data respectively collected by each first sensor of a faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time.

[0047] Among them, the faulty cable to be identified is used to characterize the cable waiting for fault identification. The first sensor can be a sensor for collecting data to determine whether the cable has a fault. The preset time is used to characterize the preset time length. The first parameter data is used to characterize the data collected by the first sensor, and the first parameter type can be the classification of the data collected by the first sensor, such as the cable temperature type, the cable humidity type and other parameter types. An exemplary example can be that the first sensor of the faulty cable a to be identified is a cable temperature sensor, a cable humidity sensor and a cable tension sensor, the preset time is 1 hour, and the cable temperature values ​​collected by the cable temperature sensor of the faulty cable a to be identified within 1 hour are 40°C, 43°C, 45°C, 50°C, 55°C, and 60°C, respectively, the cable humidity values ​​are 20%, 24%, 30%, 40%, 50%, and 60%, respectively, and the cable tension values ​​are 30N, 31N, 30N, 28N, 30N, and 30N, respectively.

[0048] Step S102: determining a corresponding abnormal comparison value according to the first parameter type, and determining whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter values ​​at each time point.

[0049] Among them, the abnormal comparison value can be a standard parameter value used to compare whether the first parameter value is abnormal. The fault parameter data can be the first parameter data of the fault. According to the first parameter type of each first sensor of the faulty cable to be identified, the corresponding abnormal comparison value is determined, and each abnormal comparison value is compared with the first parameter value of each corresponding time point, and based on the comparison result, it is determined whether the corresponding first parameter data is fault parameter data. Optionally, a method for determining fault parameter data can be to compare the first parameter value at each time point with the corresponding abnormal comparison value, and when there is an abnormal parameter value greater than the abnormal comparison value in the first parameter value, determine the change trend of the first parameter value at each subsequent time point of the time point corresponding to the abnormal parameter value, and when the change trend is an upward trend, determine the corresponding first parameter data as fault parameter data. An exemplary example may be that the temperature anomaly comparison value associated with the temperature parameter type is 90°C, the preset time is 1 hour, the first sensor collects data every 10 minutes, and the temperature values ​​collected by the cable temperature sensor of the faulty cable a to be identified within 1 hour are 80°C, 86°C, 93°C, 100°C, 105°C, and 107°C, respectively. The temperature value collected at the 30th minute is greater than the temperature anomaly comparison value, and the change trend of the temperature value in the subsequent 30 minutes is an upward trend, then the temperature data of the faulty cable a to be identified is determined as fault parameter data. In another embodiment, the first parameter value at each time point in the first parameter data is compared with the corresponding anomaly comparison value. If there are first parameter values ​​greater than or equal to the preset number in the first parameter data that are greater than the corresponding anomaly comparison value, the first parameter data is determined to be fault parameter data.

[0050] Step S103: When the first parameter data is fault parameter data, a matching process is performed based on the fault parameter data and pre-stored matching fault information to obtain a plurality of candidate fault factors of the faulty cable to be identified.

[0051] Among them, the pre-stored matching fault information can be data information pre-stored to match the fault parameter data. Optionally, the pre-stored matching fault information includes multiple matching fault factors and corresponding associated fault parameter types. A method for determining the selected fault factors can be to match the fault parameter types in the fault parameter data with the associated fault parameter types of each matching fault factor, and determine the matching fault factor corresponding to the associated fault parameter type that successfully matches the fault parameter type as the selected fault factor of the fault cable to be identified. An exemplary example can be that the matching fault factors are excessive current, excessive ambient temperature, damaged insulation layer, and excessive wind force, and the corresponding associated fault parameter types correspond to cable temperature type, cable temperature type, cable humidity type, and cable stress type in sequence. The fault parameter type in the fault parameter data of the fault cable a to be identified is the cable temperature type, and the matching fault factors corresponding to the associated fault parameter type that successfully matches the fault parameter type are excessive current and excessive ambient temperature. Then, excessive current and excessive ambient temperature are determined as the selected fault factors of the fault cable a to be identified. In another embodiment, each fault parameter value in the fault parameter data is compared with each historical fault parameter value in each pre-stored historical fault information for similarity, and the historical fault factor in the pre-stored historical fault information with a similarity greater than a preset similarity is determined as a candidate fault factor for the faulty cable to be identified.

[0052] Step S104, obtaining the second parameter data collected by the second sensors respectively associated with each of the selected fault factors within a preset time, determining the data type of each of the second parameter data and the corresponding data processing method, and processing the second parameter data according to the data processing method corresponding to the data type of each of the second parameter data to obtain corresponding screening reference data.

[0053] Among them, the second sensor is used to characterize the device for collecting the numerical value of the parameter associated with the fault factor. The data type can be a classification of the second parameter data, such as a numerical type, an image type, etc. The data processing method is used to characterize the method of processing the second parameter data. The screening reference data is used to characterize the reference data used when screening whether the candidate fault factor is the final fault factor. In one embodiment, the corresponding trained screening reference data output model is determined according to the data type of each second parameter data, and the second parameter data is input into the screening reference data output model to obtain the corresponding screening reference data. Optionally, the data type includes an image type and a numerical type. A method for determining the screening reference data can be, when the data type of the second parameter data is a numerical type, determining the change trend and change rate of the second parameter value in the second parameter data, determining the change trend and change rate as the screening reference data of the second parameter data, and when the data type of the second parameter data is an image type, performing image recognition processing on the images corresponding to each time point in the second parameter data, and determining the image recognition result as the screening reference data of the second parameter data. By using different processing methods to process different types of second parameter data to obtain screening reference data, the efficiency and rationality of data processing can be improved.

[0054] Step S105: Screening various candidate fault factors according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

[0055] Among them, the final fault factor is used to characterize the factor that is finally determined to cause the fault of the faulty cable to be identified. After determining the screening reference data corresponding to each second parameter data, the corresponding fault factors to be selected are screened according to the screening reference data of each second parameter data to obtain the final fault factor of the faulty cable to be identified. In one embodiment, the screening reference data corresponding to each fault factor to be selected are compared with the corresponding preset comparison data. If the comparison is successful, the corresponding fault factor to be selected is determined as the final fault factor of the faulty cable to be identified. Optionally, in the case where the screening reference data is a change trend and a change rate, the preset screening condition is determined according to the second parameter type in the second parameter data corresponding to the change trend and the change rate. In the case where the change trend and the change rate both meet the preset screening condition, the corresponding associated fault factor to be selected is determined as the final fault factor. In the case where the screening reference data is an image recognition result, the number of feature images with identification features is determined according to the image recognition result, and whether the corresponding associated fault factor to be selected is the final fault factor is determined according to the identification features and the number of feature images. Screening the fault factors to be selected by the change data or image feature data of the second parameter data can improve the rationality and accuracy of the determined cable fault factors.

[0056] As can be seen from the above, the first parameter data collected by each first sensor of the faulty cable to be identified within a preset time are obtained, the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time, the corresponding abnormal comparison value is determined according to the first parameter type, and whether the first parameter data is fault parameter data is determined based on the abnormal comparison value and the first parameter value at each time point. In the case that the first parameter data is fault parameter data, matching processing is performed based on the fault parameter data and pre-stored matching fault information to obtain multiple candidate fault factors of the faulty cable to be identified, and the second parameter data collected by the second sensor associated with each candidate fault factor within the preset time is obtained, the data type of each second parameter data and the corresponding data processing method are determined, the second parameter data is processed according to the data processing method corresponding to the data type of each second parameter data to obtain the corresponding screening reference data, and the candidate fault factors are screened according to the screening reference data to obtain the final fault factor of the faulty cable to be identified. This solution identifies the final fault factor of the cable through parameter evolution identification, which solves the problem that on-site fault confirmation in existing cable fault identification technology requires manpower costs and is not conducive to the first-time cable fault repair. The sensor value determination method can only determine the approximate cable fault type and is not accurate enough. It can gradually locate the final cause of the cable fault through different parameter data, thereby improving the accuracy of cable fault identification.

[0057] Figure 2 A flowchart of another cable fault factor determination method based on parameter evolution identification provided by an embodiment of the present invention provides an optional specific method for determining the screening reference data, such as Figure 2 As shown, specifically including:

[0058] Step S201: acquiring first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time.

[0059] Step S202: determining a corresponding abnormal comparison value according to the first parameter type, and determining whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter values ​​at each time point.

[0060] Step S203: When the first parameter data is fault parameter data, a matching process is performed based on the fault parameter data and pre-stored matching fault information to obtain a plurality of candidate fault factors of the faulty cable to be identified.

[0061] Step S204: obtaining second parameter data collected by second sensors respectively associated with each of the selected fault factors within a preset time, and determining a data type of each of the second parameter data and a corresponding data processing method.

[0062] Step S205: when the data type is a numerical type, determine the change trend and change rate of the second parameter value in the second parameter data, and determine the change trend and the change rate as screening reference data for the second parameter data.

[0063] Among them, the change trend is used to describe the tendency and trend of a thing or phenomenon changing over time, which can be divided into two basic types: an upward trend and a downward trend. The rate of change refers to the speed of a substance changing in a unit time. In the case where the data type of the second parameter data is a numerical type, the change trend and the rate of change of the second parameter value in the second parameter data are determined, and the change trend and the rate of change of the second parameter value are determined as the screening reference data of the second parameter data. An exemplary example can be that the preset time is 1 hour, the second sensor collects the value every ten minutes, the second parameter data is the current parameter data, the current parameter values ​​in the current parameter data are 20A, 23A, 25A, 30A, 35A, 38A, the change trend of the current parameter value is an upward trend, and the change rate of the current parameter value is calculated to be 3A / min, then the upward trend and 0.3A / min are determined as the screening reference data of the current parameter data. In another embodiment, in the case where the data type of the second parameter data is a numerical type, the average value of the second parameter value in the second parameter data is calculated, and it is determined as the screening reference data of the second parameter data.

[0064] Step S206: When the data type is an image type, image recognition processing is performed on the images corresponding to each time point in the second parameter data, and the image recognition results are determined as screening reference data for the second parameter data.

[0065] Wherein, when the data type of the second parameter data is an image type, image recognition processing is performed on the images corresponding to each time point in the second parameter data, and the image recognition result is determined as the screening reference data of the second parameter data. Optionally, an image recognition processing method may be to determine the identification feature associated with the candidate fault factor corresponding to the second parameter data, and identify whether the identification feature exists in the images corresponding to each time point in the second parameter data. An exemplary example may be that the images corresponding to each time point in the second parameter data are image 1, image 2, image 3, image 4, image 5, and image 6 in sequence, the candidate fault factor corresponding to the second parameter data is insulation layer damage, the identification feature associated with insulation layer damage is a damaged insulation layer, and it is identified whether there is a damaged insulation layer in each image in the second parameter data, and the recognition result is that there is a damaged insulation layer in image 3, image 4, image 5, and image 6. In another embodiment, when the data type of the second parameter data is an image type, the images corresponding to each time point in the second parameter data are respectively input into the image recognition model associated with the corresponding candidate fault factor to obtain the image recognition result.

[0066] Step S207: Screening various candidate fault factors according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

[0067] As can be seen from the above, when the data type of the second parameter data is a numerical type, the change trend and change rate of the second parameter value in the second parameter data are determined, and the change trend and change rate of the second parameter value are determined as the screening reference data of the second parameter data. When the data type of the second parameter data is an image type, image recognition processing is performed on the images corresponding to each time point in the second parameter data, and the image recognition result is determined as the screening reference data of the second parameter data. This solution can improve the efficiency and rationality of data processing by using different processing methods to process different types of second parameter data to obtain screening reference data.

[0068] Figure 3 A flowchart of another cable fault factor determination method based on parameter evolution identification provided by an embodiment of the present invention provides an optional specific method for determining the final fault factor, such as Figure 3 As shown, specifically including:

[0069] Step S301: acquiring first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time.

[0070] Step S302: determining a corresponding abnormal comparison value according to the first parameter type, and determining whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter values ​​at each time point.

[0071] Step S303: When the first parameter data is fault parameter data, a matching process is performed based on the fault parameter data and pre-stored matching fault information to obtain a plurality of candidate fault factors of the faulty cable to be identified.

[0072] Step S304, obtain the second parameter data collected by the second sensor associated with each candidate fault factor within a preset time, determine the data type of each second parameter data and the corresponding data processing method, and process the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain corresponding screening reference data.

[0073] Step S305: When the filtering reference data is a change trend and a change rate, determine the preset filtering condition according to the second parameter type in the second parameter data corresponding to the change trend and the change rate; when the change trend and the change rate both meet the preset filtering condition, determine the corresponding associated candidate fault factor as the final fault factor.

[0074] Wherein, when the screening reference data is a change trend and a change rate, a preset screening condition is determined according to the second parameter type in the second parameter data corresponding to the screening reference data, and when both the change trend and the change rate in the screening reference data meet the preset screening condition, the corresponding associated candidate fault factor is determined as the final fault factor. An illustrative example may be that the second parameter type in the second parameter data corresponding to the screening reference data a is a current parameter type, the associated candidate fault factor is current overload, the current change trend is an upward trend, and the current change rate is 3A / min, and the preset screening condition associated with the current parameter type is that the current change trend is an upward trend and the current change rate is greater than 0.1A / min, then the current change trend and the current change rate in the screening reference data a meet the preset screening condition, and the current overload is determined as the final fault factor of the fault current to be identified.

[0075] Step S306: When the screening reference data is an image recognition result, determine the number of feature images having the recognition feature according to the image recognition result, and determine whether the corresponding associated candidate fault factor is the final fault factor according to the recognition feature and the number of feature images.

[0076] Among them, the number of feature images is used to characterize the number of images with identification features in the image recognition result. In the case where the screening reference data is the image recognition result, the number of feature images with the corresponding identification features in the corresponding second parameter data is determined according to the image recognition result, and whether the corresponding associated candidate fault factor is the final fault factor is determined according to the identification feature and the number of feature images. Optionally, a method for determining the final fault factor may be to determine a preset comparison number associated with the identification feature of the image recognition result, compare the number of feature images with the preset comparison number, and when the number of feature images is greater than the preset comparison number, determine the corresponding associated candidate fault factor as the final fault factor, otherwise, determine that the corresponding associated candidate fault factor is not the final fault factor. An exemplary example may be that the reference data b is screened as an image recognition result, the corresponding identification feature is a damaged insulation layer, the corresponding associated candidate fault factor is damaged insulation layer, the image recognition result is that image 1 and image 2 do not have damaged insulation layer, and images 3, 4, 5, and 6 have damaged insulation layer, then the number of feature images with damaged insulation layer in the second parameter data is 4, the preset comparison number associated with damaged insulation layer is 3, and the number of feature images is greater than the preset comparison number, then the damaged insulation layer is determined as the final fault factor of the faulty cable to be identified. In another embodiment, it is determined whether there are continuous identification feature images greater than or equal to the preset number in the second parameter data according to the image recognition result, and if so, the corresponding associated candidate fault factor is determined as the final fault factor.

[0077] As can be seen from the above, when the screening reference data is the change trend and the change rate, the preset screening condition is determined according to the second parameter type in the second parameter data corresponding to the change trend and the change rate. When both the change trend and the change rate meet the preset screening condition, the corresponding associated candidate fault factor is determined as the final fault factor. When the screening reference data is the image recognition result, the number of feature images with identification features is determined according to the image recognition result, and whether the corresponding associated candidate fault factor is the final fault factor is determined according to the identification features and the number of feature images. This solution can improve the rationality and accuracy of the determined cable fault factors by screening the candidate fault factors through the change data or image feature data of the second parameter data.

[0078] Figure 4 The module structure block diagram of a cable fault factor determination system based on parameter evolution identification provided by an embodiment of the present invention is used to execute the cable fault factor determination method based on parameter evolution identification provided by the above embodiment, and has the corresponding functional modules and beneficial effects of the execution method. Figure 4 As shown, the system specifically includes:

[0079] An acquisition module 101 is used to acquire first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time;

[0080] A fault data determination module 102 is used to determine a corresponding abnormal comparison value according to the first parameter type, and determine whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point;

[0081] A candidate fault determination module 103 is used for, when the first parameter data is fault parameter data, performing matching processing based on the fault parameter data and pre-stored matching fault information to obtain a plurality of candidate fault factors of the faulty cable to be identified;

[0082] The acquisition module 101 is further used to acquire second parameter data collected by the second sensor associated with each of the selected fault factors within a preset time;

[0083] The reference data determination module 104 is used to determine the data type of each second parameter data and the corresponding data processing method, and process the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain the corresponding screening reference data;

[0084] The final fault determination module 105 is used to screen various candidate fault factors according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

[0085] It can be seen from the above scheme that the first parameter data collected by each first sensor of the faulty cable to be identified within a preset time are obtained, the first parameter data include a first parameter type and a first parameter value at each time point within the preset time, the corresponding abnormal comparison value is determined according to the first parameter type, and whether the first parameter data is fault parameter data is determined based on the abnormal comparison value and the first parameter value at each time point. In the case that the first parameter data is fault parameter data, matching processing is performed based on the fault parameter data and pre-stored matching fault information to obtain multiple candidate fault factors of the faulty cable to be identified, and the second parameter data collected by the second sensor associated with each candidate fault factor within the preset time is obtained, the data type of each second parameter data and the corresponding data processing method are determined, the second parameter data is processed according to the data processing method corresponding to the data type of each second parameter data to obtain the corresponding screening reference data, and the candidate fault factors are screened according to the screening reference data to obtain the final fault factor of the faulty cable to be identified. This solution identifies the final fault factor of the cable through parameter evolution identification, which solves the problem that on-site fault confirmation in existing cable fault identification technology requires manpower costs and is not conducive to the first-time cable fault repair. The sensor value determination method can only determine the approximate cable fault type and is not accurate enough. It can gradually locate the final cause of the cable fault through different parameter data, thereby improving the accuracy of cable fault identification.

[0086] In a possible embodiment, the fault data determination module 102 is specifically configured to:

[0087] Compare the first parameter value at each time point with the abnormal comparison value, and when there is an abnormal parameter value greater than the abnormal comparison value in the first parameter value, determine the change trend of the first parameter value at each subsequent time point of the time point corresponding to the abnormal parameter value;

[0088] When the change trend is an upward trend, the corresponding first parameter data is determined as fault parameter data.

[0089] In a possible embodiment, the candidate fault determination module 103 is specifically configured to:

[0090] The fault parameter types in the fault parameter data are matched with the associated fault parameter types of each matching fault factor, and the matching fault factor corresponding to the associated fault parameter type that successfully matches the fault parameter type is determined as the candidate fault factor of the faulty cable to be identified.

[0091] In a possible embodiment, the reference data determination module 104 is specifically configured to:

[0092] In the case where the data type is a numerical type, determining a change trend and a change rate of a second parameter value in the second parameter data, and determining the change trend and the change rate as screening reference data for the second parameter data;

[0093] In the case where the data type is an image type, image recognition processing is performed on the images corresponding to each time point in the second parameter data, and the image recognition result is determined as the screening reference data for the second parameter data.

[0094] In a possible embodiment, the reference data determination module 104 is further configured to:

[0095] Determine an identification feature associated with the candidate fault factor corresponding to the second parameter data, and identify whether the identification feature exists in the image corresponding to each time point in the second parameter data.

[0096] In a possible embodiment, the final fault determination module 105 is specifically configured to:

[0097] In the case where the screening reference data is a change trend and a change rate, a preset screening condition is determined according to the second parameter type in the second parameter data corresponding to the change trend and the change rate, and in the case where both the change trend and the change rate meet the preset screening condition, the corresponding associated candidate fault factor is determined as the final fault factor;

[0098] In the case where the screening reference data is an image recognition result, the number of feature images having the recognition feature is determined according to the image recognition result, and whether the corresponding associated candidate fault factor is the final fault factor is determined according to the recognition feature and the number of feature images.

[0099] In a possible embodiment, the final fault determination module 105 is further configured to:

[0100] Determine the preset comparison number associated with the identification feature, compare the feature image number with the preset comparison number, and when the feature image number is greater than the preset comparison number, determine that the corresponding associated candidate fault factor is the final fault factor, otherwise, determine that the corresponding associated candidate fault factor is not the final fault factor.

[0101] Figure 5 A schematic diagram of a cable fault factor determination device based on parameter evolution identification provided by an embodiment of the present invention is shown in FIG. Figure 5 As shown, the device includes a processor 201, a memory 202, an input device 203 and an output device 204; the number of processors 201 in the device can be one or more. Figure 5A processor 201 is taken as an example; the processor 201, memory 202, input device 203 and output device 204 in the device can be connected by a bus or other means. Figure 5 In the example, the connection through the bus is taken. The memory 202, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions or modules corresponding to the cable fault factor determination method based on parameter evolution identification in the embodiment of the present invention. The processor 201 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 202, that is, realizes the above-mentioned cable fault factor determination method based on parameter evolution identification. The input device 203 can be used to receive input digital or character information, and generate key signal input related to user settings and function control of the device. The output device 204 may include a display device such as a display screen.

[0102] The embodiment of the present invention further provides a storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute a method for determining cable fault factors based on parameter evolution identification when executed by a computer processor, the method comprising:

[0103] Acquire first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time;

[0104] Determine the corresponding abnormal comparison value according to the first parameter type, determine whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point, and if the first parameter data is fault parameter data, perform matching processing based on the fault parameter data and pre-stored matching fault information to obtain multiple candidate fault factors of the faulty cable to be identified;

[0105] Obtain second parameter data collected by second sensors respectively associated with each candidate fault factor within a preset time, determine the data type of each second parameter data and the corresponding data processing method, process the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain corresponding screening reference data, and screen each candidate fault factor according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

[0106] It is worth noting that in the above-mentioned embodiment of the cable fault factor determination method system based on parameter evolution identification, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the embodiments of the present invention.

[0107] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the embodiments of the present invention are not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the embodiments of the present invention. Therefore, although the embodiments of the present invention are described in more detail through the above embodiments, the embodiments of the present invention are not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the embodiments of the present invention, and the scope of the embodiments of the present invention is determined by the scope of the appended claims.

Claims

1. A method for determining cable fault factors based on parameter evolution identification, characterized in that: include: Acquire first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time; Determine the corresponding abnormal comparison value according to the first parameter type, determine whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point, and if the first parameter data is fault parameter data, perform matching processing based on the fault parameter data and pre-stored matching fault information to obtain multiple candidate fault factors of the faulty cable to be identified; Obtain second parameter data collected by second sensors respectively associated with each candidate fault factor within a preset time, determine the data type of each second parameter data and the corresponding data processing method, process the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain corresponding screening reference data, and screen each candidate fault factor according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

2. The cable fault factor determination method based on parameter evolution identification according to claim 1 is characterized in that: The determining whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point includes: Compare the first parameter value at each time point with the abnormal comparison value, and when there is an abnormal parameter value greater than the abnormal comparison value in the first parameter value, determine the change trend of the first parameter value at each subsequent time point of the time point corresponding to the abnormal parameter value; When the change trend is an upward trend, the corresponding first parameter data is determined as fault parameter data.

3. The cable fault factor determination method based on parameter evolution identification according to claim 1 is characterized in that: The pre-stored matching fault information includes a plurality of matching fault factors and corresponding associated fault parameter types, and the matching process based on the fault parameter data and the pre-stored matching fault information is performed to obtain a plurality of candidate fault factors of the faulty cable to be identified, including: The fault parameter types in the fault parameter data are matched with the associated fault parameter types of each matching fault factor, and the matching fault factor corresponding to the associated fault parameter type that successfully matches the fault parameter type is determined as the candidate fault factor of the faulty cable to be identified.

4. The cable fault factor determination method based on parameter evolution identification according to any one of claims 1 to 3, characterized in that: The data types include image types and numerical types, and the second parameter data are processed according to the data processing methods corresponding to the data types of the second parameter data to obtain corresponding screening reference data, including: In the case where the data type is a numerical type, determining a change trend and a change rate of a second parameter value in the second parameter data, and determining the change trend and the change rate as screening reference data for the second parameter data; In the case where the data type is an image type, image recognition processing is performed on the images corresponding to each time point in the second parameter data, and the image recognition result is determined as the screening reference data for the second parameter data.

5. The cable fault factor determination method based on parameter evolution identification according to claim 4 is characterized in that: The performing image recognition processing on the images corresponding to each time point in the second parameter data includes: Determine an identification feature associated with the candidate fault factor corresponding to the second parameter data, and identify whether the identification feature exists in the image corresponding to each time point in the second parameter data.

6. The cable fault factor determination method based on parameter evolution identification according to any one of claims 1 to 3, characterized in that: The step of screening each candidate fault factor according to the screening reference data to obtain the final fault factor of the faulty cable to be identified includes: In the case where the screening reference data is a change trend and a change rate, a preset screening condition is determined according to the second parameter type in the second parameter data corresponding to the change trend and the change rate, and in the case where both the change trend and the change rate meet the preset screening condition, the corresponding associated candidate fault factor is determined as the final fault factor; In the case where the screening reference data is an image recognition result, the number of feature images having the recognition feature is determined according to the image recognition result, and whether the corresponding associated candidate fault factor is the final fault factor is determined according to the recognition feature and the number of feature images.

7. The method for determining cable fault factors based on parameter evolution identification according to claim 6, characterized in that: The determining, according to the identification feature and the number of feature images, whether the corresponding associated candidate fault factor is the final fault factor includes: Determine the preset comparison number associated with the identification feature, compare the feature image number with the preset comparison number, and when the feature image number is greater than the preset comparison number, determine that the corresponding associated candidate fault factor is the final fault factor, otherwise, determine that the corresponding associated candidate fault factor is not the final fault factor.

8. A cable fault factor determination system based on parameter evolution identification, characterized in that: include: An acquisition module, used to acquire first parameter data respectively collected by each first sensor of the faulty cable to be identified within a preset time, wherein the first parameter data includes a first parameter type and a first parameter value at each time point within the preset time; a fault data determination module, configured to determine a corresponding abnormal comparison value according to the first parameter type, and determine whether the first parameter data is fault parameter data based on the abnormal comparison value and the first parameter value at each time point; A candidate fault determination module, used for, when the first parameter data is fault parameter data, performing matching processing based on the fault parameter data and pre-stored matching fault information to obtain a plurality of candidate fault factors of the faulty cable to be identified; The acquisition module is further used to acquire second parameter data collected by second sensors respectively associated with each of the selected fault factors within a preset time; A reference data determination module, used to determine the data type of each second parameter data and the corresponding data processing method, and to process the second parameter data according to the data processing method corresponding to the data type of each second parameter data to obtain the corresponding screening reference data; The final fault determination module is used to screen each candidate fault factor according to the screening reference data to obtain the final fault factor of the faulty cable to be identified.

9. A device for determining cable fault factors based on parameter evolution identification, the device comprising: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the cable fault factor determination method based on parameter evolution identification as described in any one of claims 1-7.

10. A storage medium storing computer executable instructions, wherein the computer executable instructions are used to execute the cable fault factor determination method based on parameter evolution identification according to any one of claims 1 to 7 when executed by a computer processor.

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