Intelligent cable monitoring method and device based on image data

Abstract

The embodiment of the present invention discloses an intelligent cable monitoring method based on image data, which includes: acquiring image data collected by each monitoring and acquisition node at fixed preset periods, identifying the image data respectively to obtain cable data information of the corresponding monitoring and acquisition node; determining the cable failure rate of the monitoring cable area in the corresponding monitoring and acquisition node according to the cable data information, and adjusting the fixed preset period corresponding to each monitoring and acquisition node according to the cable failure rate; collecting image data for each monitoring and acquisition node in the respective adjusted periods, and generating alarm information when it is determined that the collected image data meets the fault alarm condition. This solution solves the problem of single cable monitoring mode and low efficiency in the prior art, while ensuring the low power consumption operation of the monitoring equipment.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of cables, and in particular to an intelligent cable monitoring method and device based on image data. Background Art

[0002] In order to ensure the normal operation of the cable, various sensors are usually installed to realize real-time monitoring of cable parameters, and displayed through a big data platform to ensure that the fault point and cause of the fault can be identified in the first time when a cable fault occurs.

[0003] Most existing smart cables are equipped with temperature sensors to monitor their temperature. The cable safety is monitored by comparing the acquired temperature with a preset threshold. This monitoring method has relatively single monitoring parameters and cannot detect hidden dangers of other methods. Summary of the invention

[0004] The embodiments of the present invention provide an intelligent cable monitoring method and device based on image data, which solve the problem of single cable monitoring mode and low efficiency in the prior art, and at the same time ensure low power consumption operation of the monitoring equipment.

[0005] In a first aspect, an embodiment of the present invention provides an intelligent cable monitoring method based on image data, the method comprising:

[0006] Acquire pre-recorded cable areas of different sections, and determine the cable parameter monitoring nodes contained in the cable areas;

[0007] Determine the wake-up period, data acquisition parameters and data reporting period of the cable parameter monitoring node according to the type of the cable parameter monitoring node, the fault information of the cable area and the environmental parameters of the external environment of the cable area;

[0008] The cable parameter monitoring node is controlled to collect the determined data collection parameters after being awakened in the awakening period, and the cable parameter monitoring node is controlled to report data in the determined data reporting period.

[0009] Optionally, the identifying the image data respectively to obtain the cable data information of the corresponding monitoring and collection node includes:

[0010] recognizing the cable image contained in the image data;

[0011] Corresponding cable data information is generated according to the image recognition result, and the cable data information includes deformation data, obstacle data and relative position relationship data of the cable line.

[0012] Optionally, determining the cable failure rate of the monitored cable area in the corresponding monitoring and collection node according to the cable data information includes:

[0013] Determine the line type of the cable line, and when the line type is the first type, determine the cable failure rate of the monitoring cable area in the corresponding monitoring collection node according to the deformation data of the cable line;

[0014] When the line type is the second type, the cable failure rate of the monitored cable area in the corresponding monitoring collection node is determined according to the obstacle data and relative position relationship data of the cable line.

[0015] Optionally, determining the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the deformation data of the cable line includes:

[0016] The cable failure rate of the cable line is determined according to the deformation data of the cable line, the preset deformation threshold intervals and the cable failure rate corresponding to each interval.

[0017] Optionally, determining the cable failure rate of the monitoring cable area in the corresponding monitoring collection node according to the obstacle data and relative position relationship data of the cable line includes:

[0018] Determining an obstacle type of the cable line, and determining a first failure rate based on the obstacle type;

[0019] Determining a second failure rate of the cable line according to the relative position relationship data of the cable line;

[0020] The first failure rate and the second failure rate are superimposed to obtain a cable failure rate of the cable line.

[0021] Optionally, the fixed preset period corresponding to each monitoring and collection node is adjusted according to the cable failure rate, including:

[0022] When the cable failure rate is greater than a first threshold, the fixed preset period is shortened according to a first preset ratio; when the cable failure rate is less than a second threshold, the fixed preset period is extended according to a second preset ratio, and the second threshold is less than the first threshold.

[0023] Optionally, when it is determined that the collected image data meets the fault alarm condition, generating alarm information includes:

[0024] determining a fault type and a fault level according to the image data;

[0025] Generate alarm information according to the fault type and the fault level.

[0026] In a second aspect, an embodiment of the present invention further provides an intelligent cable monitoring device based on image data, the device comprising:

[0027] A data information generation module, used to obtain image data collected by each monitoring and collection node at fixed preset periods, and identify the image data to obtain cable data information of the corresponding monitoring and collection node;

[0028] A cycle adjustment module, used to determine the cable failure rate of the monitoring cable area in the corresponding monitoring and collection node according to the cable data information, and to adjust the fixed preset cycle corresponding to each monitoring and collection node according to the cable failure rate;

[0029] The alarm information generation module is used to collect image data for each monitoring collection node in the respective adjusted cycles, and generate alarm information when it is determined that the collected image data meets the fault alarm condition.

[0030] In a third aspect, an embodiment of the present invention further provides an intelligent cable monitoring device based on image data, the device comprising:

[0031] one or more processors;

[0032] a storage device for storing one or more programs,

[0033] When the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent cable monitoring method based on image data described in the embodiment of the present invention.

[0034] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer executable instructions, wherein the computer executable instructions, when executed by a computer processor, are used to execute the intelligent cable monitoring method based on image data described in an embodiment of the present invention.

[0035] In the embodiment of the present invention, the image data collected by each monitoring and collection node is obtained at fixed preset periods, and the image data is respectively identified to obtain the cable data information of the corresponding monitoring and collection node; the cable failure rate of the monitoring cable area in the corresponding monitoring and collection node is determined according to the cable data information, and the fixed preset period corresponding to each monitoring and collection node is adjusted according to the cable failure rate; image data is collected for each monitoring and collection node in the respective adjusted periods, and when it is determined that the collected image data meets the fault alarm condition, an alarm message is generated. This solution solves the problem of single cable monitoring method and low efficiency in the prior art, while ensuring the low power consumption operation of the monitoring equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1A flowchart of an intelligent cable monitoring method based on image data provided by an embodiment of the present invention;

[0037] Figure 2 A flowchart of another intelligent cable monitoring method based on image data provided by an embodiment of the present invention;

[0038] Figure 3 A structural block diagram of an intelligent cable monitoring device based on image data provided by an embodiment of the present invention;

[0039] Figure 4 A schematic structural diagram of an intelligent cable monitoring device based on image data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] 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.

[0041] Figure 1 A flowchart of an intelligent cable monitoring method based on image data provided by an embodiment of the present invention can be executed by a cable system master control platform integrated by a server, and specifically includes the following steps:

[0042] Step S101: acquiring image data collected by each monitoring and collecting node at every fixed preset period, and identifying the image data respectively to obtain cable data information of the corresponding monitoring and collecting node.

[0043] Among them, the fixed preset period is a pre-set time period that may be a default time period after initialization. A plurality of monitoring and acquisition nodes are arranged in the cable line to capture image data corresponding to the cable line. Among them, the monitoring and acquisition node may be a low-power camera device arranged on a cable joint or a cable line, such as a common low-power natural light camera or an infrared camera. The cable line includes cable lines of various forms such as tunnels, underground cables, and overhead cables. The cable data information of the corresponding monitoring and acquisition node is obtained by identifying the acquired image data. The cable data information can be used to determine the failure rate of the cable.

[0044] Specifically, the cable image contained in the image data may be identified; and corresponding cable data information is generated according to the image identification result, wherein the cable data information includes deformation data, obstacle data and relative position relationship data of the cable line.

[0045] Step S102: determining the cable failure rate of the monitoring cable area in the corresponding monitoring and collection node according to the cable data information, and adjusting the fixed preset period corresponding to each monitoring and collection node according to the cable failure rate.

[0046] After obtaining the cable data information, the cable failure rate of the monitoring cable area in the monitoring acquisition node is determined based on the cable data information. Specifically, it includes the following:

[0047] Step S1021, determining the line type of the cable line, when the line type is the first type, determining the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the deformation data of the cable line.

[0048] Step S1022: When the line type is the second type, determine the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the obstacle data and relative position relationship data of the cable line.

[0049] The line type of the cable line can be determined by the type field data recorded in the cable data information. The line type of the cable line can also be identified when the image data is identified. In one embodiment, the first type can be an underground cable and the second type can be an overhead cable.

[0050] When the line type is the first type, the cable failure rate of the monitored cable area in the corresponding monitoring and collection node is determined according to the deformation data of the cable line. Specifically, the cable failure rate of the cable line can be determined according to the deformation data of the cable line, the preset deformation threshold interval and the cable failure rate corresponding to each interval. Among them, the deformation data includes a specific deformation ratio. If it is squeezed to 4 / 5 of the original size, the deformation ratio is 20%. Correspondingly, each deformation ratio can fall into the corresponding preset deformation threshold interval, and each preset deformation threshold interval has a respective cable failure rate. Exemplarily, the cable failure rate corresponding to the preset deformation threshold interval [0, 20%] is 10%, and the cable failure rate corresponding to the preset deformation threshold interval [50%, 70%] is 80%.

[0051] When the line type is the second type, the cable failure rate of the monitored cable area in the corresponding monitoring and acquisition node is determined according to the obstacle data and relative position relationship data of the cable line. Specifically, it can be: determine the obstacle type of the cable line, determine the first failure rate based on the obstacle type; determine the second failure rate of the cable line according to the relative position relationship data of the cable line; superimpose the first failure rate and the second failure rate to obtain the cable failure rate of the cable line. Among them, the fault objects include fallen leaves, snow, etc., and different types of fault objects correspond to different first failure rates. Among them, the relative position of the cable line includes the distance between two or more cable lines, and different distances correspond to different second failure rates. The closer the distance between the two, the higher the second failure rate. Exemplarily, if the determined first failure rate is 35% and the second failure rate is 50, the failure rate of the cable line determined after the superposition of the two is 85%.

[0052] In one embodiment, after determining the cable failure rate, the fixed preset period corresponding to each monitoring and collection node is further adjusted according to the cable failure rate. Specifically, when the cable failure rate is greater than the first threshold, the fixed preset period is shortened according to the first preset ratio; when the cable failure rate is less than the second threshold, the fixed preset period is extended according to the second preset ratio, and the second threshold is less than the first threshold. Exemplarily, the fixed preset period can be 1 day, the first preset ratio can be 1 / 2, and the second preset ratio can be 2 times. Exemplarily, the first threshold can be 50%, and the second threshold can be 20%.

[0053] Step S103: collect image data for each monitoring collection node in the adjusted period, and generate alarm information when it is determined that the collected image data meets the fault alarm condition.

[0054] After determining the adjusted cycle for each collection point, image data is collected for each monitoring collection node in the respective adjusted cycle to ensure efficient operation. At the same time, when it is determined that the collected image data meets the fault alarm condition, an alarm message is generated. Specifically, it includes: determining the fault type and fault level according to the image data; generating alarm information according to the fault type and the fault level. Exemplarily, if it is identified as a deformation fault based on the image data, it corresponds to a fault type of the century type, and if it is an obstacle fault, it corresponds to a fault type of the obstacle type. And the corresponding fault level is given according to different deformation rates, obstacle types and quantities. Exemplarily, a deformation rate of 20% corresponds to a low fault level, a deformation rate of 50% corresponds to a medium fault level, and a deformation rate of more than 70% corresponds to a high fault level. The fault level corresponding to the obstacle being fallen leaves is low, and the higher the thickness of the obstacle being snow, the corresponding fault levels are medium and high, respectively.

[0055] From the above, it can be known that by acquiring the image data collected by each monitoring and collection node at every fixed preset period, the image data is respectively identified to obtain the cable data information of the corresponding monitoring and collection node; the cable failure rate of the monitoring cable area in the corresponding monitoring and collection node is determined according to the cable data information, and the fixed preset period corresponding to each monitoring and collection node is adjusted according to the cable failure rate; for each monitoring and collection node, image data is collected in each adjusted period, and when it is determined that the collected image data meets the fault alarm condition, an alarm message is generated. This solution solves the problem of single cable monitoring method and low efficiency in the prior art, while ensuring the low power consumption operation of the monitoring equipment.

[0056] Figure 2 A flowchart of another intelligent cable monitoring method based on image data provided by an embodiment of the present invention is as follows: Figure 2 As shown in the figure, a specific and complete example is given. Specifically, it includes:

[0057] Step S201: acquiring image data collected by each monitoring collection node at a fixed preset period, and identifying the cable image contained in the image data.

[0058] Step S202: Generate corresponding cable data information according to the image recognition result, wherein the cable data information includes deformation data, obstacle data and relative position relationship data of the cable line.

[0059] Step S203: When the line type is the first type, determine the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the deformation data of the cable line.

[0060] Step S204: determining the cable failure rate of the cable line according to the deformation data of the cable line, the preset deformation threshold intervals and the cable failure rate corresponding to each interval.

[0061] Step S205: When the line type is the second type, determine the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the obstacle data and relative position relationship data of the cable line.

[0062] Step S206: determine the obstacle type of the cable line, determine a first failure rate based on the obstacle type, and determine a second failure rate of the cable line according to the relative position relationship data of the cable line.

[0063] Step S207: Superimpose the first failure rate and the second failure rate to obtain a cable failure rate of the cable line.

[0064] Step S208: When the cable failure rate is greater than a first threshold, shorten the fixed preset period according to a first preset ratio; when the cable failure rate is less than a second threshold, extend the fixed preset period according to a second preset ratio, and the second threshold is less than the first threshold.

[0065] Step S209: collect image data for each monitoring collection node in its own adjusted period.

[0066] Step S210: determine the fault type and fault level according to the image data, and generate alarm information according to the fault type and fault level.

[0067] It can be seen from the above scheme that cable monitoring with high efficiency and reasonable power consumption is achieved, which solves the problem of single cable monitoring method and low efficiency in the prior art, and at the same time ensures low power consumption operation of the monitoring equipment.

[0068] Figure 3 This is a structural block diagram of an intelligent cable monitoring device based on image data provided by an embodiment of the present invention. The device is used to execute the intelligent cable monitoring method based on image data provided by the above embodiment, and has the corresponding functional modules and beneficial effects of the execution method. Figure 3 As shown, the device specifically includes: a node data information generation module 101, a cycle adjustment module 102 and an alarm information generation module 103, wherein:

[0069] The data information generating module 101 is used to obtain the image data collected by each monitoring and collecting node at every fixed preset period, and identify the image data to obtain the cable data information of the corresponding monitoring and collecting node;

[0070] A cycle adjustment module 102 is used to determine the cable failure rate of the monitoring cable area in the corresponding monitoring and collection node according to the cable data information, and adjust the fixed preset cycle corresponding to each monitoring and collection node according to the cable failure rate;

[0071] The alarm information generating module 103 is used to collect image data for each monitoring and collecting node in the respective adjusted cycles, and generate alarm information when it is determined that the collected image data meets the fault alarm condition.

[0072] It can be seen from the above scheme that the image data collected by each monitoring and acquisition node is obtained at fixed preset periods, and the image data is identified respectively to obtain the cable data information of the corresponding monitoring and acquisition node; the cable failure rate of the monitoring cable area in the corresponding monitoring and acquisition node is determined according to the cable data information, and the fixed preset period corresponding to each monitoring and acquisition node is adjusted according to the cable failure rate; image data is collected for each monitoring and acquisition node in the respective adjusted periods, and when it is determined that the collected image data meets the fault alarm conditions, an alarm message is generated. This scheme solves the problem of single cable monitoring method and low efficiency in the prior art, while ensuring the low power consumption operation of the monitoring equipment. Among them, the specific functions performed by each module are as follows:

[0073] In a possible embodiment, the identifying the image data respectively to obtain the cable data information of the corresponding monitoring collection node includes:

[0074] recognizing the cable image contained in the image data;

[0075] Corresponding cable data information is generated according to the image recognition result, and the cable data information includes deformation data, obstacle data and relative position relationship data of the cable line.

[0076] In a possible embodiment, determining the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the cable data information includes:

[0077] Determine the line type of the cable line, and when the line type is the first type, determine the cable failure rate of the monitoring cable area in the corresponding monitoring collection node according to the deformation data of the cable line;

[0078] When the line type is the second type, the cable failure rate of the monitored cable area in the corresponding monitoring collection node is determined according to the obstacle data and relative position relationship data of the cable line.

[0079] In a possible embodiment, determining the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the deformation data of the cable line includes:

[0080] The cable failure rate of the cable line is determined according to the deformation data of the cable line, the preset deformation threshold intervals and the cable failure rate corresponding to each interval.

[0081] In a possible embodiment, determining the cable failure rate of the monitoring cable area in the corresponding monitoring collection node according to the obstacle data and relative position relationship data of the cable line includes:

[0082] Determining an obstacle type of the cable line, and determining a first failure rate based on the obstacle type;

[0083] Determining a second failure rate of the cable line according to the relative position relationship data of the cable line;

[0084] The first failure rate and the second failure rate are superimposed to obtain a cable failure rate of the cable line.

[0085] In a possible embodiment, the fixed preset period corresponding to each monitoring and collection node is adjusted according to the cable failure rate, including:

[0086] When the cable failure rate is greater than a first threshold, the fixed preset period is shortened according to a first preset ratio; when the cable failure rate is less than a second threshold, the fixed preset period is extended according to a second preset ratio, and the second threshold is less than the first threshold.

[0087] In a possible embodiment, when determining that the acquired image data meets the fault alarm condition, generating alarm information includes:

[0088] determining a fault type and a fault level according to the image data;

[0089] Generate alarm information according to the fault type and the fault level.

[0090] Figure 4 A schematic diagram of the structure of an intelligent cable monitoring device based on image data provided by an embodiment of the present invention, such as Figure 4 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 4 A 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 4 The example of connection via a 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 / modules corresponding to the intelligent cable monitoring method based on image data 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 intelligent cable monitoring method based on image data. 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 display devices such as display screens.

[0091] An embodiment of the present invention further provides a storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute an intelligent cable monitoring method based on image data when executed by a computer processor, the method comprising:

[0092] Obtaining image data collected by each monitoring and collecting node at fixed preset periods, and identifying the image data respectively to obtain cable data information of the corresponding monitoring and collecting node;

[0093] Determine the cable failure rate of the monitoring cable area in the corresponding monitoring and collection node according to the cable data information, and adjust the fixed preset period corresponding to each monitoring and collection node according to the cable failure rate;

[0094] Image data is collected for each monitoring collection node in the respective adjusted cycles, and when it is determined that the collected image data meets the fault alarm condition, an alarm message is generated.

[0095] Optionally, the identifying the image data respectively to obtain the cable data information of the corresponding monitoring and collection node includes:

[0096] recognizing the cable image contained in the image data;

[0097] Corresponding cable data information is generated according to the image recognition result, and the cable data information includes deformation data, obstacle data and relative position relationship data of the cable line.

[0098] Optionally, determining the cable failure rate of the monitored cable area in the corresponding monitoring and collection node according to the cable data information includes:

[0099] Determine the line type of the cable line, and when the line type is the first type, determine the cable failure rate of the monitoring cable area in the corresponding monitoring collection node according to the deformation data of the cable line;

[0100] When the line type is the second type, the cable failure rate of the monitored cable area in the corresponding monitoring collection node is determined according to the obstacle data and relative position relationship data of the cable line.

[0101] Optionally, determining the cable failure rate of the monitored cable area in the corresponding monitoring collection node according to the deformation data of the cable line includes:

[0102] The cable failure rate of the cable line is determined according to the deformation data of the cable line, the preset deformation threshold intervals and the cable failure rate corresponding to each interval.

[0103] Optionally, determining the cable failure rate of the monitoring cable area in the corresponding monitoring collection node according to the obstacle data and relative position relationship data of the cable line includes:

[0104] Determining an obstacle type of the cable line, and determining a first failure rate based on the obstacle type;

[0105] Determining a second failure rate of the cable line according to the relative position relationship data of the cable line;

[0106] The first failure rate and the second failure rate are superimposed to obtain a cable failure rate of the cable line.

[0107] Optionally, the fixed preset period corresponding to each monitoring and collection node is adjusted according to the cable failure rate, including:

[0108] When the cable failure rate is greater than a first threshold, the fixed preset period is shortened according to a first preset ratio; when the cable failure rate is less than a second threshold, the fixed preset period is extended according to a second preset ratio, and the second threshold is less than the first threshold.

[0109] Optionally, when it is determined that the collected image data meets the fault alarm condition, generating alarm information includes:

[0110] determining a fault type and a fault level according to the image data;

[0111] Generate alarm information according to the fault type and the fault level.

[0112] It is worth noting that in the above-mentioned embodiment of the intelligent cable monitoring device based on image data, 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.

[0113] 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. An intelligent cable monitoring method based on image data, characterized in that: include: Obtain image data collected by each monitoring and collecting node at fixed preset intervals, and identify the image data to obtain cable data information of the corresponding monitoring and collecting node, wherein the cable data information includes deformation data, obstacle data and relative position relationship data of the cable line; Determine the cable failure rate of the monitored cable area in the corresponding monitoring and collection node according to the cable data information, including: determine the line type of the cable line, when the line type is the first type, determine the cable failure rate of the monitored cable area in the corresponding monitoring and collection node according to the deformation data of the cable line, when the line type is the second type, determine the cable failure rate of the monitored cable area in the corresponding monitoring and collection node according to the obstacle data and relative position relationship data of the cable line, and adjust the fixed preset period corresponding to each monitoring and collection node according to the cable failure rate to obtain the cable failure rate, the first type is an underground cable, and the second type is an overhead cable; the cable failure rate of the monitored cable area in the corresponding monitoring and collection node according to the obstacle data and relative position relationship data of the cable line includes: determine the obstacle type of the cable line, determine the first failure rate based on the obstacle type, determine the second failure rate of the cable line according to the relative position relationship data of the cable line, and superimpose the first failure rate and the second failure rate to obtain the cable failure rate of the cable line; Image data is collected for each monitoring collection node in the respective adjusted cycles, and when it is determined that the collected image data meets the fault alarm condition, an alarm message is generated.

2. The intelligent cable monitoring method based on image data according to claim 1 is characterized in that: The identifying the image data respectively to obtain the cable data information of the corresponding monitoring and collection node includes: recognizing the cable image contained in the image data; Generate corresponding cable data information based on the image recognition results.

3. The intelligent cable monitoring method based on image data according to claim 1 is characterized in that: The determining, according to the deformation data of the cable line, the cable failure rate of the monitoring cable area in the corresponding monitoring collection node comprises: The cable failure rate of the cable line is determined according to the deformation data of the cable line, the preset deformation threshold intervals and the cable failure rate corresponding to each interval.

4. The intelligent cable monitoring method based on image data according to claim 1 is characterized in that: The fixed preset period corresponding to each monitoring and collection node is adjusted according to the cable failure rate, including: When the cable failure rate is greater than a first threshold, the fixed preset period is shortened according to a first preset ratio; when the cable failure rate is less than a second threshold, the fixed preset period is extended according to a second preset ratio, and the second threshold is less than the first threshold.

5. The intelligent cable monitoring method based on image data according to any one of claims 1 to 4, characterized in that: When it is determined that the collected image data meets the fault alarm condition, generating alarm information includes: determining a fault type and a fault level according to the image data; Generate alarm information according to the fault type and the fault level.

6. An intelligent cable monitoring device based on image data, characterized in that: include: A data information generation module is used to obtain image data collected by each monitoring and collection node at fixed preset periods, and to identify the image data to obtain cable data information of the corresponding monitoring and collection node, wherein the cable data information includes deformation data, obstacle data and relative position relationship data of the cable line; A cycle adjustment module, used to determine the cable failure rate of the monitored cable area in the corresponding monitoring and acquisition node according to the cable data information, the cycle adjustment module is specifically used to determine the line type of the cable line, when the line type is the first type, the cable failure rate of the monitored cable area in the corresponding monitoring and acquisition node is determined according to the deformation data of the cable line, when the line type is the second type, the cable failure rate of the monitored cable area in the corresponding monitoring and acquisition node is determined according to the obstacle data and relative position relationship data of the cable line, and the fixed preset cycle corresponding to each monitoring and acquisition node is adjusted according to the cable failure rate to obtain the cable failure rate, the first type is an underground cable, and the second type is an overhead cable; the cycle adjustment module is specifically used to determine the obstacle type of the cable line, determine the first failure rate based on the obstacle type, determine the second failure rate of the cable line according to the relative position relationship data of the cable line, and superimpose the first failure rate and the second failure rate to obtain the cable failure rate of the cable line; The alarm information generation module is used to collect image data for each monitoring collection node in the respective adjusted cycles, and generate alarm information when it is determined that the collected image data meets the fault alarm condition.

7. An intelligent cable monitoring device based on image data, 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 intelligent cable monitoring method based on image data as described in any one of claims 1-5.

8. A storage medium storing computer executable instructions, wherein the computer executable instructions are used to execute the intelligent cable monitoring method based on image data according to any one of claims 1 to 5 when executed by a computer processor.

Images