Intelligent cable layout control system

Abstract

The embodiment of the application discloses a kind of intelligent cable layout control systems, the system includes: historical information data acquisition module, is configured to before carrying out cable arrangement, obtains cable historical information data;Sensor information determination module is configured to determine the sensor type and corresponding sensor quantity and sensor position of cable line according to the fault data and sensor data in the historical information data;Sensor information sending module is configured to the sensor type and corresponding sensor quantity and sensor position of cable line are sent to binding equipment, to be used for carrying out cable laying.This scheme solves the problem of high cost of intelligent cable in the prior art, while ensuring the necessary functions, reduces the overall cable laying cost.

Description

Technical Field

[0001] This application relates to the field of cable technology, and in particular to an intelligent cable layout control system. Background Technology

[0002] With the increasing popularity of smart cables, embedding sensors in cable equipment for data collection and monitoring has become an important development direction for smart cables. Examples include temperature monitoring via embedded temperature sensors and tensile force monitoring via embedded tensile force sensors.

[0003] In related technologies, data monitoring via implanted sensors can prevent cable faults and, in the event of a fault, pinpoint its location immediately. However, as smart cables become more feature-rich, the cost of implanted sensors is also increasing. Therefore, how to ensure essential functions while reducing overall cable laying costs has become a pressing issue. Summary of the Invention

[0004] This invention provides an intelligent cable layout control system that solves the problem of high cost of intelligent cables in the prior art, reducing the overall cable laying cost while ensuring necessary functions.

[0005] In a first aspect, embodiments of the present invention provide an intelligent cable layout control system, comprising: a historical information data acquisition module, configured to acquire historical cable information data before cable laying; a sensor information determination module, configured to determine the sensor type, corresponding sensor quantity, and sensor location of the cable line based on fault data and sensor data in the historical information data; and a sensor information transmission module, configured to transmit the sensor type, corresponding sensor quantity, and sensor location of the cable line to a binding device for cable laying.

[0006] Furthermore, the sensor information determination module includes a first determination unit, which is configured to:

[0007] Obtain fault data and sensor data recorded in historical information data;

[0008] In the presence of fault data, the sensor type and the corresponding first sensor data at the time of the fault are determined based on the fault data, wherein the sensor data includes the first sensor data.

[0009] The number and location of sensors in the cable line are determined based on the data from the first sensor.

[0010] Furthermore, the sensor information determination module further includes a second determination unit, which is configured to:

[0011] Statistical information is obtained by analyzing the data from the first sensor.

[0012] The number and location of sensors in the cable line are determined based on the extreme points in the statistical information.

[0013] Furthermore, the sensor information determination module also includes a third determination unit, which is configured to:

[0014] Obtain fault data and sensor data recorded in historical information data;

[0015] In the absence of fault data, statistical analysis is performed on the sensor values ​​of each type in the sensor data to generate associated sensor statistical values.

[0016] If the statistical values ​​of the associated sensors satisfy the correlation relationship, the sensor type of the cable line is determined based on the statistical values ​​of the associated sensors.

[0017] The number and location of sensors in the cable line are determined based on the sensor values ​​corresponding to each category of sensors in the joint sensor statistics.

[0018] Secondly, embodiments of the present invention also provide an intelligent cable layout control method, comprising:

[0019] Before laying cables, obtain historical cable information data;

[0020] The types of sensors, the corresponding number of sensors, and the locations of sensors in the cable line are determined based on the fault data and sensor data in the historical information data.

[0021] The types, quantities, and locations of the sensors in the cable line are sent to the bonding device for cable laying.

[0022] Furthermore, determining the types, quantities, and locations of sensors in the cable line based on fault data and sensor data from the historical information data includes:

[0023] Obtain fault data and sensor data recorded in historical information data;

[0024] In the presence of fault data, the sensor type and the corresponding first sensor data at the time of the fault are determined based on the fault data, wherein the sensor data includes the first sensor data.

[0025] The number and location of sensors in the cable line are determined based on the data from the first sensor.

[0026] Furthermore, determining the number and location of sensors in the cable line based on the first sensor data includes:

[0027] Statistical information is obtained by analyzing the data from the first sensor.

[0028] The number and location of sensors in the cable line are determined based on the extreme points in the statistical information.

[0029] Furthermore, determining the types, quantities, and locations of sensors in the cable line based on fault data and sensor data from the historical information data includes:

[0030] Obtain fault data and sensor data recorded in historical information data;

[0031] In the absence of fault data, statistical analysis is performed on the sensor values ​​of each type in the sensor data to generate associated sensor statistical values.

[0032] If the statistical values ​​of the associated sensors satisfy the correlation relationship, the sensor type of the cable line is determined based on the statistical values ​​of the associated sensors.

[0033] The number and location of sensors in the cable line are determined based on the sensor values ​​corresponding to each category of sensors in the joint sensor statistics.

[0034] Thirdly, embodiments of the present invention also provide an intelligent cable layout control device, the device comprising:

[0035] One or more processors;

[0036] Storage device for storing one or more programs.

[0037] When the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent cable layout control method described in the embodiments of the present invention.

[0038] Fourthly, embodiments of the present invention also provide a storage medium for storing computer-executable instructions, which, when executed by a computer processor, are used to execute the intelligent cable layout control method described in the embodiments of the present invention.

[0039] In this embodiment of the invention, a historical information data acquisition module is configured to acquire historical cable information data before cable laying; a sensor information determination module is configured to determine the sensor types, corresponding sensor quantities, and sensor locations of the cable line based on fault data and sensor data in the historical information data; and a sensor information transmission module is configured to send the sensor types, corresponding sensor quantities, and sensor locations of the cable line to a binding device for cable laying. This solution solves the problem of high cost of smart cables in the prior art, reducing the overall cable laying cost while ensuring necessary functions. Attached Figure Description

[0040] Figure 1 The following is a block diagram of the module structure of the intelligent cable layout control system provided in Embodiment 1 of the present invention;

[0041] Figure 2 This is a block diagram of the module structure of the intelligent cable layout control system provided in Embodiment 2 of the present invention;

[0042] Figure 3 This is a flowchart of the intelligent cable layout control method provided in Embodiment 3 of the present invention;

[0043] Figure 4 This is a schematic diagram of the structure of the intelligent cable layout control device provided in Embodiment 4 of the present invention. Detailed Implementation

[0044] The embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and not intended to limit the scope of the invention. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the embodiments of the present invention, and not all structures.

[0045] Example 1

[0046] Figure 1 This is a block diagram of the module structure of the intelligent cable layout control system provided in Embodiment 1 of the present invention, as shown below. Figure 1 As shown in the diagram, the module structure specifically includes:

[0047] The historical information data acquisition module 101 is configured to acquire historical cable information data before cable laying.

[0048] The sensor information determination module 102 is configured to determine the type of sensor, the corresponding number of sensors, and the sensor location of the cable line based on the fault data and sensor data in the historical information data.

[0049] The sensor information sending module 103 is configured to send the types of sensors, the corresponding number of sensors, and the sensor locations of the cable lines to the binding device for cable laying.

[0050] The application scenario of this application embodiment is to determine the type, quantity, and location of sensors during the current cable laying by analyzing historical cable fault data and sensor data. Specifically, based on the fault data and sensor data in the historical information data, the type, quantity, and location of sensors in the cable line are determined and sent to the bonding device for cable laying.

[0051] Based on the above application scenarios, it is understood that the execution subject of the embodiments of this application can be an intelligent electronic device with an integrated intelligent cable layout control system, such as a laptop, tablet computer or mobile phone, etc., and no specific limitation is made here.

[0052] In this embodiment, the cable arrangement can be understood as cable laying. It is understood that embedding sensors in the cable equipment for data collection and monitoring is also part of the cable arrangement. The cable historical information data can be understood as information data of the cables monitored in the past, which can be manually entered and recorded by technicians or automatically generated by the system based on monitoring data. The cable historical information data can be stored in a database in the form of a database table or document. The cable historical information data can be obtained by querying the database.

[0053] In this embodiment, before laying the cable, the historical information data acquisition module 101 obtains historically monitored cable information data by querying the database.

[0054] In this embodiment, the fault data can be understood as parameter data corresponding to historical cable faults. Specifically, the fault data includes fault parameter data types. The fault types can include high-temperature faults, water immersion faults, and dense smoke faults, etc. The sensor data can be understood as parameter data acquired by sensors when historical cable faults occurred. The sensor type can be understood as the type of sensor corresponding to the collection of different cable parameter data, such as temperature sensors, water immersion sensors, and smoke sensors. The number of sensors can be understood as the number of sensors required when laying the cable. The sensor location can be understood as the location where the sensors are implanted during cable laying.

[0055] In this embodiment, the sensor information determination module 102 determines the type, number, and location of sensors required for the current cable laying based on the fault parameter type in historical information data and the parameter data obtained by the sensors.

[0056] In this embodiment, the binding device can be the equipment terminal of a technician. The sensor information sending module 103 sends information such as the required sensor type, number of sensors, and sensor installation location to the binding device, so that the technician can perform the current cable laying based on the sensor information data.

[0057] The technical solution provided in this embodiment includes a historical information data acquisition module configured to acquire historical cable information data before cable laying; a sensor information determination module configured to determine the type, quantity, and location of sensors in the cable line based on fault data and sensor data in the historical information data; and a sensor information transmission module configured to send the sensor type, quantity, and location of the cable line to the binding device for cable laying. This solution solves the problem of high cost of smart cables in the prior art, reducing the overall cable laying cost while ensuring necessary functions.

[0058] Example 2

[0059] Figure 2 This is a block diagram of the module structure of the intelligent cable layout control system provided in Embodiment 2 of the present invention, as shown below. Figure 2 As shown in the diagram, the module structure specifically includes:

[0060] The first determining unit 2021 is configured in:

[0061] Obtain fault data and sensor data recorded in historical information data;

[0062] In the presence of fault data, the sensor type and the corresponding first sensor data at the time of the fault are determined based on the fault data, wherein the sensor data includes the first sensor data.

[0063] The number and location of sensors in the cable line are determined based on the data from the first sensor.

[0064] In this embodiment, the first sensor data can be the parameter data monitored by the sensor within one hour before and after the time point of the historical cable fault, or it can be all the data monitored on the day the fault occurred. The specific settings can be configured by technicians according to the actual situation.

[0065] In this embodiment, determining the sensor type based on the fault data can be done by determining the sensor type based on the fault parameter data type. For example, when the fault parameter data type is a high-temperature fault, the sensor type is determined to be a temperature sensor; for example, when the fault parameter data type is a water immersion fault, the sensor type is determined to be a water immersion sensor; for example, when the fault parameter data type is a dense smoke fault, the sensor type is determined to be a smoke sensor. Determining the corresponding first sensor data at the time of the fault based on the fault data can be done by reading parameter data monitored by sensors embedded in the cable equipment within a one-hour period before and after the fault time point from the fault data.

[0066] In this embodiment, the first determining unit 2021 queries historical information data recorded in a database for fault data and sensor data. If fault data is found, the sensor type is determined based on the fault parameter data type in the fault data, and parameter data monitored by the sensors within one hour before and after the fault time point is read as first sensor data. Based on the first sensor data, the number of sensors required for the cable line to be laid and the sensor placement locations are determined. Specifically, the number of sensors can be determined based on the duration of historical faults, and the sensor locations can be determined based on historical fault locations. The fault data and the first sensor data can be pre-associated and stored. It is understood that the sensor data includes the first sensor data.

[0067] In this embodiment, optionally, the sensor information determining module further includes a second determining unit, the second determining unit 2022 being configured in:

[0068] Statistical information is obtained by analyzing the data from the first sensor.

[0069] The number and location of sensors in the cable line are determined based on the extreme points in the statistical information.

[0070] In this embodiment, the statistical information can be based on sensor values ​​obtained from sensors implanted at different locations in the cable equipment. Specifically, it can be a sensor data curve plotted based on the sensor values ​​corresponding to sensors with different numbers. The extreme points can be understood as peak points in the curve plot. It is understood that the curve plot can have multiple peak points.

[0071] In this embodiment, the method of obtaining statistical information by statistically analyzing the first sensor data can be to plot sensor data curves based on sensor data acquired from sensors with different numbers. Determining the number and location of sensors in the cable line based on the extreme points in the statistical information can be achieved by identifying the locations corresponding to the peaks in the curve that meet certain conditions as the locations of the sensors to be implanted. The number of sensors to be implanted is determined based on the peak slope corresponding to the peaks that meet the conditions.

[0072] In this embodiment, the second determining unit 2022 statistically analyzes the first sensor data acquired by sensors with different numbers to obtain a sensor data curve. It determines the data values ​​corresponding to the peak points in the curve and compares the data values ​​of each peak point with a pre-set preset threshold. Based on the peak slope corresponding to the peak points whose data values ​​are greater than the preset threshold, it determines the number of sensors to be implanted and sets the location of the peak point as the sensor location. The preset threshold is the minimum critical value for a cable fault. For example, if the sensor data is temperature data and the minimum temperature for a high-temperature fault is 40°C, then 40°C is set as the preset threshold. The number of sensors to be implanted is determined based on the peak slope corresponding to the peak points whose data values ​​are greater than or equal to 40°C, and the location of the peak point is set as the sensor location. Specifically, a larger peak slope corresponds to fewer sensors, and a smaller peak slope corresponds to more sensors.

[0073] In this embodiment, optionally, the sensor information determining module further includes a third determining unit, the third determining unit 2023 being configured in:

[0074] Obtain fault data and sensor data recorded in historical information data;

[0075] In the absence of fault data, statistical analysis is performed on the sensor values ​​of each type in the sensor data to generate associated sensor statistical values.

[0076] If the statistical values ​​of the associated sensors satisfy the correlation relationship, the sensor type of the cable line is determined based on the statistical values ​​of the associated sensors.

[0077] The number and location of sensors in the cable line are determined based on the sensor values ​​corresponding to each category of sensors in the joint sensor statistics.

[0078] In this embodiment, the associated sensor statistics can be understood as pairwise correlation statistics performed on sensor data corresponding to different types of sensors. For example, the sensor data includes temperature data, smoke data, and water immersion data. Correlation statistics are performed on temperature data and smoke data, temperature data and water immersion data, and smoke data and water immersion data, respectively. Specifically, the correlation statistics can be performed by obtaining sensor curves corresponding to two sensor data points based on sensor data at different time points, or by storing data values ​​of different types of sensor data separately. The correlation of the associated sensor statistics can be understood as the associated sensor statistics satisfying a preset correlation relationship.

[0079] In this embodiment, the third determining unit 2023 queries the database for fault data and sensor data recorded in historical information data. If no fault data exists, the third determining unit 2023 performs pairwise correlation statistics on the sensor data based on the sensor data type to generate correlated sensor statistical values. If the correlated data statistical values ​​satisfy a preset correlation relationship, the sensor type of the cable line to be laid is determined based on the data type in the correlated sensor statistical values. Furthermore, the number of sensors and sensor locations in the cable line are determined based on the sensor values ​​corresponding to each category of sensors in the correlated sensor statistical values. Specifically, the number of sensors to be implanted can be determined based on the magnitude of the sensor values, and the sensor locations can be determined based on the location points corresponding to the specific sensor values.

[0080] In this embodiment, optionally, the generation of sensor statistical values ​​from temperature data and smoke concentration data is described as an example. Sensor curves corresponding to the temperature and smoke sensor data at different time points are obtained. When the similarity between the two sensor curves is greater than a similarity threshold or the slope difference between the two sensor curves is less than a slope difference threshold, it is determined that the temperature data and smoke concentration data satisfy a correlation relationship. Accordingly, the temperature sensor and smoke sensor are set as the types of sensors to be implanted. The maximum values ​​of the temperature data and smoke concentration data are determined respectively. If the maximum value exceeds a preset threshold, the number of sensors is determined to be 10; if the maximum value does not exceed the preset threshold, the number of sensors is determined to be 5. Simultaneously, the location points corresponding to the maximum temperature value and the maximum smoke concentration value are used as the implantation locations of the temperature sensor and the smoke sensor, respectively.

[0081] In this embodiment, optionally, the generation of sensor statistical values ​​from temperature data and smoke concentration data is described as an example. Two sensor data values ​​are obtained based on temperature and smoke sensor data at different time points. It is determined whether the two data values ​​satisfy the same growth trend. If the temperature data values ​​and smoke concentration data values ​​at all time points satisfy the same growth trend, then it is determined that the temperature data and smoke concentration data satisfy a correlation relationship. For example, at 9:00, the temperature data value is 30°C and the smoke concentration data value is 28ppm; at 9:05, the temperature data value is 32°C and the smoke concentration data value is 30ppm; and at 9:10, the temperature data value is 34°C and the smoke concentration data value is 32ppm. It is determined that the temperature data and smoke concentration data satisfy a correlation relationship. Accordingly, the temperature sensor and smoke sensor are set as the types of sensors to be implanted. The maximum values ​​of the temperature data and smoke concentration data are determined respectively. If the maximum value exceeds a preset threshold, the number of sensors is determined to be 10; if the maximum value does not exceed the preset threshold, the number of sensors is determined to be 5. Meanwhile, the locations corresponding to the maximum temperature and the maximum smoke concentration are used as the implantation locations for the temperature sensor and the smoke sensor, respectively.

[0082] The technical solution provided in this embodiment, when fault data exists, determines the sensor type and the corresponding first sensor data at the time of the fault based on the fault data, wherein the sensor data includes the first sensor data; and determines the number and location of sensors in the cable line based on the first sensor data. When no fault data exists, statistical analysis is performed on the sensor values ​​of each type in the sensor data to generate associated sensor statistical values; if the associated sensor statistical values ​​satisfy the correlation relationship, the sensor type of the cable line is determined based on the associated sensor statistical values; and the number and location of sensors in the cable line are determined based on the sensor values ​​corresponding to each category of sensors in the associated sensor statistical values. This method of flexibly setting sensor information based on different historical data makes the type, number, and location of sensors embedded during cable laying more reasonable.

[0083] Figure 3 The flowchart of the intelligent cable layout control method provided in Embodiment 3 of the present invention is as follows: Figure 3 As shown, the specific steps of this method include:

[0084] Before laying cables, obtain historical cable information data;

[0085] The types of sensors, the corresponding number of sensors, and the locations of sensors in the cable line are determined based on the fault data and sensor data in the historical information data.

[0086] The types, quantities, and locations of the sensors in the cable line are sent to the bonding device for cable laying.

[0087] In this embodiment, optionally, determining the type of sensor, the corresponding number of sensors, and the sensor location of the cable line based on the fault data and sensor data in the historical information data includes:

[0088] Obtain fault data and sensor data recorded in historical information data;

[0089] In the presence of fault data, the sensor type and the corresponding first sensor data at the time of the fault are determined based on the fault data, wherein the sensor data includes the first sensor data.

[0090] The number and location of sensors in the cable line are determined based on the data from the first sensor.

[0091] In this embodiment, optionally, determining the number and location of sensors in the cable line based on the first sensor data includes:

[0092] Statistical information is obtained by analyzing the data from the first sensor.

[0093] The number and location of sensors in the cable line are determined based on the extreme points in the statistical information.

[0094] In this embodiment, optionally, determining the type of sensor, the corresponding number of sensors, and the sensor location of the cable line based on the fault data and sensor data in the historical information data includes:

[0095] Obtain fault data and sensor data recorded in historical information data;

[0096] In the absence of fault data, statistical analysis is performed on the sensor values ​​of each type in the sensor data to generate associated sensor statistical values.

[0097] If the statistical values ​​of the associated sensors satisfy the correlation relationship, the sensor type of the cable line is determined based on the statistical values ​​of the associated sensors.

[0098] The number and location of sensors in the cable line are determined based on the sensor values ​​corresponding to each category of sensors in the joint sensor statistics.

[0099] The technical solution provided in this embodiment acquires historical cable information data before cable laying; determines the types, quantities, and locations of sensors for the cable line based on fault data and sensor data in the historical information data; and sends the sensor types, quantities, and locations of the cable line to the binding device for cable laying. This solution solves the problem of high cost of smart cables in the prior art, reducing the overall cable laying cost while ensuring necessary functions.

[0100] Figure 4 This is a schematic diagram of the intelligent cable layout control device provided in Embodiment 4 of the present invention, as shown below. Figure 4 As shown, the device includes a processor 401, a memory 402, an input device 403, and an output device 404; the number of processors 401 in the device can be one or more. Figure 4 Taking a processor 401 as an example; the processor 401, memory 402, input device 403, and output device 404 in the device can be connected via a bus or other means. Figure 4 Taking a bus connection as an example, the memory 402, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the intelligent cable layout control method in this embodiment of the invention. The processor 401 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 402, thereby realizing the aforementioned intelligent cable layout control method. The input device 403 can be used to receive input digital or character information and generate key signal inputs related to user settings and function control of the device. The output device 404 may include a display screen or other display device.

[0101] This invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform an intelligent cable layout control method. The method includes: acquiring historical cable information data before cable laying; determining the types, quantities, and locations of sensors in the cable line based on fault data and sensor data in the historical information data; and sending the types, quantities, and locations of the sensors in the cable line to a bonding device for cable laying.

[0102] It is worth noting that in the embodiments of the above-mentioned intelligent cable layout control system device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of the present invention.

[0103] Note that the above are merely preferred embodiments and the technical principles applied in this invention. Those skilled in the art will understand that the embodiments of this invention are not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the protection scope of this invention. Therefore, although the embodiments of this invention have been described in detail above, the embodiments of this invention are not limited to the above embodiments. More other equivalent embodiments may be included without departing from the concept of the embodiments of this invention, and the scope of the embodiments of this invention is determined by the scope of the appended claims.

Claims

1. An intelligent cable layout control system, characterized in that, include: The historical information data acquisition module is configured to acquire historical cable information data before cable laying; The sensor information determination module is configured to determine the type of sensor, the corresponding number of sensors, and the sensor location of the cable line based on the fault data and sensor data in the historical information data. The sensor information determination module includes a first determination unit, which is configured to: acquire fault data and sensor data recorded in historical information data; in the presence of fault data, determine the type of sensor and the corresponding first sensor data at the time of the fault based on the fault data; the sensor data includes the first sensor data; determine the number of sensors and the location of sensors in the cable line based on the first sensor data; the first sensor data is the parameter data monitored by the sensors within one hour before and after the time point of the historical cable fault. The sensor information determination module further includes a second determination unit, which is configured to: perform statistics on the first sensor data to obtain statistical information, and determine the number of sensors and sensor locations in the cable line based on the extreme points in the statistical information. The statistical information is a sensor data curve plotted based on the sensor values ​​corresponding to sensors with different numbers, and the extreme points of the sensor data curve plot are peak points. The second determining unit is further configured to: determine the data value corresponding to the peak point in the sensor data curve, compare the data value of each peak point with a preset threshold, determine the number of sensors in the cable line based on the peak slope corresponding to the peak point whose data value is greater than the preset threshold, and determine the position corresponding to the peak point as the sensor position; wherein, the larger the peak slope, the fewer the corresponding number of sensors are set, and the smaller the peak slope, the more the corresponding number of sensors are set, and the preset threshold is the minimum critical value to satisfy the cable fault; The sensor information determination module further includes a third determination unit, which is configured to: acquire fault data and sensor data recorded in historical information data; when there is no fault data, perform statistical analysis on the sensor values ​​of each type in the sensor data to generate associated sensor statistical values; when the associated sensor statistical values ​​satisfy the association relationship, determine the sensor type of the cable line based on the associated sensor statistical values; and determine the number of sensors and sensor locations of the cable line according to the sensor values ​​corresponding to each category of sensors in the associated sensor statistical values. The correlation relationship of the associated sensor statistical values ​​includes: the similarity of the sensor curves corresponding to different types of sensors is greater than the similarity threshold, or the slope difference of the sensor curves corresponding to different types of sensors is less than the slope difference threshold, or the data values ​​of different types of sensors at all time points satisfy the same growth trend. The sensor information transmission module is configured to send the types of sensors, the corresponding number of sensors, and the sensor locations of the cable lines to the binding device for cable laying.

2. An intelligent cable layout control method, characterized in that, include: Before laying cables, obtain historical cable information data; The cable line sensor types, corresponding sensor quantities, and sensor locations are determined based on the fault data and sensor data in the historical information data. This includes: acquiring fault data and sensor data recorded in the historical information data; determining the sensor types and corresponding first sensor data at the time of the fault based on the fault data when fault data exists; the sensor data including the first sensor data; statistically analyzing the first sensor data to obtain statistical information; and determining the number of sensors and sensor locations in the cable line based on the extreme points in the statistical information. In the absence of fault data, statistical analysis is performed on the sensor values ​​of each type in the sensor data to generate associated sensor statistical values. If the associated sensor statistical values ​​satisfy the correlation relationship, the sensor types of the cable line are determined based on these values. The number and location of sensors in the cable line are determined according to the sensor values ​​corresponding to each category of sensors in the associated sensor statistical values. The associated sensor statistical values ​​satisfying the correlation relationship include: the similarity of sensor curves corresponding to different types of sensors is greater than a similarity threshold; or the slope difference of sensor curves corresponding to different types of sensors is less than a slope difference threshold; or the data values ​​of different types of sensors at all time points show the same growth trend. The first sensor data consists of parameter data monitored by the sensors within one hour before and after the occurrence of a historical cable fault. The statistical information is a sensor data curve plotted based on the sensor values ​​corresponding to different sensor numbers, with the extreme points of the sensor data curve being peak points. The data values ​​corresponding to the peak points in the sensor data curve are determined, and the data values ​​of each peak point are compared with a preset threshold. The number of sensors for the cable line is determined based on the peak slope corresponding to the peak point whose data value is greater than the preset threshold, and the location corresponding to the peak point is determined as the sensor location. The larger the peak slope, the fewer sensors are set, and the smaller the peak slope, the more sensors are set. The preset threshold is the minimum critical value to satisfy cable fault. The types, quantities, and locations of the sensors in the cable line are sent to the bonding device for cable laying.

3. An intelligent cable layout control device, the device comprising: One or more processors; A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to implement the intelligent cable layout control method as described in claim 2.

4. A storage medium storing computer-executable instructions, which, when executed by a computer processor, are used to perform the intelligent cable layout control method as described in claim 2.

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