Cable Attachment Recognition Device Based on Infrared Imaging Technology and Heat Dissipation Model

Abstract

The present application discloses a cable attachment recognition device based on infrared imaging technology and a heat dissipation model, and the present application belongs to the field of Internet of Things technology. It includes: an infrared image collector for acquiring infrared images of the cable; a wind sensor for acquiring wind direction data and wind speed data in the environment; a temperature sensor for acquiring environmental temperature information; a processing unit for inputting the infrared images of the cable, the environmental temperature information, the wind direction data and the wind speed data into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and determining whether the attachment recognition condition is satisfied according to the output result; if satisfied, it is determined that there are attachments on the cable. According to this technical solution, it is possible to judge whether there is an attachment phenomenon on the cable under certain conditions based on the data collected by the sensors, so that targeted attachment observation arrangements can be made, improving the monitoring efficiency of cable attachments and ensuring the operation safety of the cable.

Description

Technical Field

[0001] This application belongs to the technical field of the Internet of Things, and particularly relates to a cable attachment recognition device based on infrared imaging technology and a heat dissipation model. Background Art

[0002] In the process of accelerating the construction of socialism with Chinese characteristics in China, the electricity demand in cities is increasing continuously. Moreover, cables are widely used as connection circuits and transmission tools in the power system. Therefore, cable faults have become a very critical aspect of power failures.

[0003] In daily life, there are attachments on the surface of cables, which affects the normal heat dissipation of cables and is also an important factor leading to cable faults. In the prior art, technicians usually judge whether there are attachments on the cable surface based on vision. However, this method requires a large amount of human resources, and the efficiency of monitoring cable attachments is low. Therefore, how to efficiently monitor cable attachments has become an urgent problem to be solved in this technical field. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a cable attachment recognition device based on infrared imaging technology and a heat dissipation model, which can solve the problem of low efficiency in monitoring cable attachments in the prior art, make a judgment on whether there are attachment phenomena on the cable under certain conditions through the data collected by the sensor, so as to arrange the observation of attachments targeted, improve the monitoring efficiency of cable attachments, and ensure the operation safety of the cable.

[0005] In a first aspect, the embodiments of this application provide a cable attachment recognition device based on infrared imaging technology and a heat dissipation model. The device includes:

[0006] An infrared image collector, which is used to obtain the infrared image of the cable; wherein, the infrared image collector is arranged at the cable support and faces the cable laying direction;

[0007] A wind sensor, which is used to obtain the wind direction data and wind speed data in the environment;

[0008] A temperature sensor, which is used to obtain the environmental temperature information;

[0009] A processing unit, which is connected to the infrared image collector, the wind sensor and the temperature sensor, and is used to input the cable infrared image, the environmental temperature information, the wind direction data and the wind speed data into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and determine whether the attachment recognition condition is satisfied according to the output result; if satisfied, it is determined that there are attachments on the cable.

[0010] Further, the attachment includes at least one of snow, frost, ice, dust, and leaves;

[0011] The heat dissipation model includes:

[0012] A first heat dissipation model corresponding to attached snow;

[0013] A second heat dissipation model corresponding to attached frost;

[0014] A third heat dissipation model corresponding to attached ice;

[0015] A fourth heat dissipation model corresponding to attached dust;

[0016] A fifth heat dissipation model corresponding to attached leaves.

[0017] Further, the processing unit is specifically configured to:

[0018] Input the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into the first heat dissipation model, the second heat dissipation model, the third heat dissipation model, the fourth heat dissipation model, and the fifth heat dissipation model respectively;

[0019] Determine whether the attachment recognition condition is satisfied, and the attachment type when the attachment recognition condition is satisfied, according to the output results and confidence levels of each heat dissipation model.

[0020] Further, the processing unit is specifically configured to:

[0021] If the confidence levels of each heat dissipation model are all less than the first set confidence threshold, it is determined that there is no attachment on the cable;

[0022] If the confidence levels of at least two heat dissipation models are both greater than the second set confidence threshold, determine the attachment type on the cable according to the confidence level ranking result of the at least two heat dissipation models.

[0023] Further, the device further includes:

[0024] An alarm unit, connected to the processing unit, for generating alarm information of a corresponding level according to the attachment degree of the attachment and a pre-set alarm level mapping table when it is determined that there is an attachment on the cable;

[0025] A communication unit, for sending the alarm information to the attachment alarm response device.

[0026] Further, the attachment degree includes the attachment thickness or attachment length of the attachment.

[0027] Second aspect, an embodiment of the present application provides a method for identifying cable attachments based on infrared imaging technology and a heat dissipation model, the method comprising:

[0028] Obtaining a cable infrared image through an infrared image collector; wherein, the infrared image collector is disposed at the cable support and faces the cable laying direction;

[0029] Obtaining wind direction data, wind speed data, and ambient temperature information in the environment;

[0030] Inputting the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain an output result of the heat dissipation model; and determining whether the attachment recognition condition is satisfied according to the output result; if satisfied, it is determined that there are attachments on the cable.

[0031] Further, it is characterized in that the attachments include at least one of snow, frost, ice, dust, and leaves;

[0032] The heat dissipation model includes:

[0033] A first heat dissipation model corresponding to snow attachment;

[0034] A second heat dissipation model corresponding to frost attachment;

[0035] A third heat dissipation model corresponding to ice attachment;

[0036] A fourth heat dissipation model corresponding to dust attachment;

[0037] A fifth heat dissipation model corresponding to leaf attachment.

[0038] Further, the inputting the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain an output result of the heat dissipation model; and determining whether the attachment recognition condition is satisfied according to the output result; if satisfied, it is determined that there are attachments on the cable, includes:

[0039] Inputting the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into the first heat dissipation model, the second heat dissipation model, the third heat dissipation model, the fourth heat dissipation model, and the fifth heat dissipation model respectively;

[0040] Determining whether the attachment recognition condition is satisfied according to the output results and confidence levels of each heat dissipation model, and the attachment type when the attachment recognition condition is satisfied.

[0041] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the cable attachment recognition method based on infrared imaging technology and a heat dissipation model as described in the second aspect are implemented.

[0042] In an embodiment of the present application, an infrared image collector is configured to obtain an infrared image of a cable; a wind sensor is configured to obtain wind direction data and wind speed data in the environment; a temperature sensor is configured to obtain environmental temperature information; a processing unit is configured to input the cable infrared image, the environmental temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain an output result of the heat dissipation model; and determine whether an attachment recognition condition is satisfied according to the output result; if so, it is determined that there is an attachment on the cable. According to this technical solution, it is possible to judge whether there is an attachment phenomenon on the cable under certain conditions based on the data collected by the sensors, so that the attachment observation arrangement can be carried out targeted, improving the monitoring efficiency of cable attachments and ensuring the operation safety of the cable. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a schematic structural diagram of a cable attachment recognition device based on infrared imaging technology and a heat dissipation model provided in Embodiment 1 of the present application;

[0044] Figure 2 is a schematic structural diagram of a cable attachment recognition device based on infrared imaging technology and a heat dissipation model provided in Embodiment 2 of the present application;

[0045] Figure 3 is a schematic flowchart of a cable attachment recognition method based on infrared imaging technology and a heat dissipation model provided in Embodiment 3 of the present application;

[0046] Figure 4 is a schematic structural diagram of an electronic device provided in Embodiment 4 of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following provides a more detailed description of specific embodiments of this application with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting this application. Additionally, it should be noted that for ease of description, only parts related to this application rather than all content are shown in the drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operations are completed, but it can also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0048] The following will clearly describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some but not all of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application belong to the scope of protection of this application.

[0049] The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. generally belong to the same category, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and / or" in the specification and claims means at least one of the connected objects. The character " / " generally indicates an "or" relationship between the associated objects before and after.

[0050] The following will, with reference to the accompanying drawings, provide a detailed description of the cable attachment recognition device based on infrared imaging technology and a heat dissipation model provided in the embodiments of this application through specific embodiments and their application scenarios.

[0051] Embodiment 1

[0052] Figure 1 is a schematic structural diagram of the cable attachment recognition device based on infrared imaging technology and a heat dissipation model provided in Embodiment 1 of this application. As Figure 1 shown, the device includes:

[0053] An infrared image collector 101, configured to acquire an infrared image of the cable; wherein, the infrared image collector is disposed at the cable support and faces the cable laying direction;

[0054] A wind sensor 102 for obtaining wind direction data and wind speed data in the environment;

[0055] A temperature sensor 103 for obtaining environmental temperature information;

[0056] A processing unit 104, connected to the infrared image collector, the wind sensor, and the temperature sensor, for inputting the cable infrared image, the environmental temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and determining whether the attachment recognition condition is satisfied according to the output result; if so, it is determined that there is an attachment on the cable.

[0057] In this embodiment, the infrared image collector 101 may be a device for obtaining the cable infrared image. Among them, the cable infrared image may be an image generated by the infrared image collector 101 according to the infrared radiation of the cable. The orientation of the infrared image collector 101 may be a direction parallel to the cable laying. Specifically, the method of obtaining the cable infrared image by the infrared image collector 101 may be that the infrared image collector 101 is used to receive incident light in a target wavelength range, generate a cable image signal in response to the incident light in the target wavelength range, and generate the cable infrared image according to the cable image signal.

[0058] In this embodiment, the infrared image collector 101 is arranged at the cable support, and the orientation is parallel to the cable laying direction. Exemplarily, the cable is laid in the north-south direction, the infrared image collector 101 is arranged at the cable support in the north, and the orientation is south.

[0059] In this embodiment, the wind direction data can be understood as data recording the direction angle of the wind blowing. The wind speed data can be understood as data of the moving distance of the wind per unit time. In the prior art, there are various types of wind sensors. For example, propeller type wind direction and wind speed sensors, where the wind speed is of the three-cup type and the wind direction is of the single-wing type, and ultrasonic wind direction and wind speed sensors. It can be understood that the type of the wind sensor 102 is not specifically limited in this embodiment.

[0060] In this embodiment, the ultrasonic wind direction and wind speed sensor is taken as an example for the wind sensor 102 for description. The ultrasonic sensor measures the wind speed and wind direction by using the ultrasonic time difference method. Specifically, the ultrasonic sensor uses the sent acoustic wave pulses to measure the time or frequency difference at the receiving end to calculate the wind speed and wind direction.

[0061] In this embodiment, the environmental temperature information can be understood as the information of the physical quantity recording the degree of cold and heat of the environment. In the prior art, there are various types of temperature sensors. For example, bimetallic strip temperature sensors, bimetallic rod and metal tube temperature sensors, and resistance temperature sensors. It can be understood that the type of the temperature sensor 103 is not specifically limited in this embodiment.

[0062] In this embodiment, the bimetallic strip temperature sensor is taken as an example for the temperature sensor 103 for description. Specifically, the bimetallic strip is composed of two metals with different expansion coefficients pasted together. As the temperature changes, material A shrinks more than the other metal, causing the metal strip to tilt. The curvature of the tilt can be converted into an input signal and then converted into an output digital signal to obtain temperature data.

[0063] In this embodiment, the heat dissipation model can be a model that obtains the heat dissipation amount through statistical analysis of the input data. The output result of the heat dissipation model is the heat dissipation amount result obtained through the analysis of the heat dissipation model. The attachment recognition condition can be understood as the standard for judging whether there is an attachment on the cable, which can be preset by technicians.

[0064] The way to pre - construct the heat dissipation model can be to pre - divide data intervals for the cable infrared image, the environmental temperature information, the wind direction data, and the wind speed data, and determine the corresponding heat dissipation amount results according to the intervals. Exemplarily, when the environmental temperature is greater than or equal to - 15 °C and less than 0 °C, the corresponding heat dissipation amount result is 12 °C per hour; when the environmental temperature is greater than or equal to 0 °C and less than 15 °C, the corresponding heat dissipation amount result is 8 °C per hour; when the environmental temperature is greater than or equal to 15 °C and less than 30 °C, the corresponding heat dissipation amount result is 5 °C per hour.

[0065] In this embodiment, the processing unit 104 inputs the pre-acquired cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data as input data into a pre-constructed heat dissipation model. The heat dissipation model, based on a pre-set data range, sums up the heat dissipation values corresponding to each data and takes the average to finally output a heat dissipation result. Optionally, the heat dissipation result can also be determined by pre-determining weight coefficients for each data volume and using a weighted average method. The processing unit 104 compares the heat dissipation result with pre-set attachment recognition conditions. If the heat dissipation result meets the attachment recognition conditions, it is determined that there is an attachment on the cable. Exemplarily, the attachment recognition condition is that if the heat dissipation result is less than or equal to 1 degree Celsius per hour, it is determined that there is an attachment on the cable. When the heat dissipation result is 0.5 degree Celsius per hour, it is determined that there is an attachment on the cable.

[0066] In this embodiment, the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data can be used as four variables respectively. By inputting different values for the four variables, different output results will be obtained for the entire heat dissipation model.

[0067] In this embodiment, optionally, the attachments include at least one of snow, frost, ice, dust, and leaves;

[0068] The heat dissipation model includes:

[0069] A first heat dissipation model corresponding to attached snow;

[0070] A second heat dissipation model corresponding to attached frost;

[0071] A third heat dissipation model corresponding to attached ice;

[0072] A fourth heat dissipation model corresponding to attached dust;

[0073] A fifth heat dissipation model corresponding to attached leaves.

[0074] Among them, the attachments including at least one of snow, frost, ice, dust, and leaves can be understood as the attachments including one or more of snow, frost, ice, dust, and leaves. It can be understood that different attachments may cause different cable faults. For example, if the attachment is dust or leaves, it will slow down the heat dissipation of the cable, resulting in a high-temperature fault of the cable. If the attachment is snow, frost, ice, etc., it may cause a water immersion fault of the cable due to melting.

[0075] Combined with the above example, if the constructed model is five different heat dissipation models, after inputting four variables, the five heat dissipation models will obtain five different output results. In this case, based on the output results of each heat dissipation model, it is possible to determine which model has higher accuracy, and thus the type of attachment can be determined.

[0076] In this embodiment, the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data are pre-divided into data intervals. The first heat dissipation model corresponding to the attached snow can be understood as a machine model that determines the heat dissipation result corresponding to the attachment being snow according to the interval; the second heat dissipation model corresponding to the attached frost can be understood as a machine model that determines the heat dissipation result corresponding to the attachment being frost according to the interval; the third heat dissipation model corresponding to the attached ice can be understood as a machine model that determines the heat dissipation result corresponding to the attachment being ice according to the interval; the fourth heat dissipation model corresponding to the attached dust can be understood as a machine model that determines the heat dissipation result corresponding to the attachment being dust according to the interval; the fifth heat dissipation model corresponding to the attached leaves can be understood as a machine model that determines the heat dissipation result corresponding to the attachment being leaves according to the interval. Exemplarily, when the ambient temperature is greater than or equal to 0 degrees Celsius and less than 15 degrees Celsius, the heat dissipation result corresponding to the first heat dissipation model is 11 degrees Celsius per hour, the heat dissipation result corresponding to the second heat dissipation model is 13 degrees Celsius per hour, the heat dissipation result corresponding to the third heat dissipation model is 15 degrees Celsius per hour, the heat dissipation result corresponding to the fourth heat dissipation model is 6 degrees Celsius per hour, and the heat dissipation result corresponding to the fifth heat dissipation model is 4 degrees Celsius per hour.

[0077] In the technical solution provided by this embodiment, the attachments include at least one of snow, frost, ice, dust, and leaves. By monitoring different types of attachments, a reasonable and comprehensive monitoring mechanism is provided, which can thus specifically avoid different types of cable faults. In addition, by pre-constructing heat dissipation models for different attachment types, it is possible to more accurately determine the heat dissipation results when the acquired sensing data corresponds to different attachments, providing data support for the update of subsequent heat dissipation models.

[0078] In this embodiment, optionally, the processing unit 104 is specifically configured to:

[0079] Input the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into the first heat dissipation model, the second heat dissipation model, the third heat dissipation model, the fourth heat dissipation model, and the fifth heat dissipation model respectively;

[0080] Determine whether the attachment recognition condition is satisfied according to the output results and confidence levels of each heat dissipation model, and the type of attachment when the attachment recognition condition is satisfied.

[0081] In this embodiment, the technician pre-obtains the actual heat dissipation data of the cable and sets it as the standard result. The confidence level can be understood as the matching degree between the output results of each heat dissipation model and the standard result.

[0082] In this embodiment, the processing unit 104 inputs the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into the first heat dissipation model, the second heat dissipation model, the third heat dissipation model, the fourth heat dissipation model, and the fifth heat dissipation model respectively to obtain the first heat dissipation result, the second heat dissipation result, the third heat dissipation result, the fourth heat dissipation result, and the fifth heat dissipation result. Then, the above heat dissipation results are matched with the standard result to determine the confidence level of each heat dissipation result. Exemplarily, if the standard result is 10 degrees Celsius per hour and the first heat dissipation result is 6 degrees Celsius per hour, then the confidence level of the first heat dissipation result is determined to be 60%; if the first heat dissipation result is 8 degrees Celsius per hour, then the confidence level of the first heat dissipation result is determined to be 80%. The processing unit 104 determines whether it meets the attachment recognition condition according to each heat dissipation result and the confidence level. If it meets the attachment recognition condition, the attachment type is further determined.

[0083] The technical solution provided in this embodiment determines whether it meets the attachment recognition condition and the attachment type when the attachment recognition condition is met according to the output results of each heat dissipation model and the confidence level. By determining whether there is an attachment through the confidence level and the corresponding attachment type when there is an attachment, the accuracy of the judgment result can be further improved.

[0084] In this embodiment, optionally, the processing unit is specifically configured to:

[0085] If the confidence levels of all heat dissipation models are less than the first set confidence threshold, it is determined that there is no attachment on the cable;

[0086] If the confidence levels of at least two heat dissipation models are greater than the second set confidence threshold, the attachment type on the cable is determined according to the confidence level ranking result of the at least two heat dissipation models.

[0087] Among them, the first set confidence threshold can be understood as the lowest confidence value indicating the existence of an attachment, and the second confidence threshold can be understood as the standard confidence value indicating the existence of an attachment. It can be understood that the second confidence threshold is greater than the first confidence threshold. If the confidence levels of at least two heat dissipation models are both greater than the second set confidence threshold, then determining the type of attachment on the cable according to the confidence level sorting result of the at least two heat dissipation models can be that if the confidence levels corresponding to two or more heat dissipation results are greater than the second set confidence threshold, then sort the heat dissipation results in descending order of confidence level, and determine the type of attachment corresponding to the heat dissipation result with the highest confidence level as the type of attachment on the cable.

[0088] In this embodiment, the confidence levels of the first heat dissipation result, the second heat dissipation result, the third heat dissipation result, the fourth heat dissipation result, and the fifth heat dissipation result are respectively compared with the first set confidence threshold. If the confidence level of each heat dissipation model is less than the first set confidence threshold, it is determined that there is no attachment on the cable. If the confidence level of a heat dissipation model is greater than the first set confidence threshold, then it can be determined whether there is an attachment on the cable.

[0089] In this embodiment, the confidence levels of the first heat dissipation result, the second heat dissipation result, the third heat dissipation result, the fourth heat dissipation result, and the fifth heat dissipation result are respectively compared with the second set confidence threshold. If the confidence levels corresponding to two or more heat dissipation results are greater than the second set confidence threshold, then sort the heat dissipation results in descending order of confidence level, and determine the type of attachment corresponding to the heat dissipation result with the highest confidence level as the type of attachment on the cable. Exemplarily, the second set confidence threshold is 80%, the confidence level corresponding to the first heat dissipation result is 60%, the confidence level corresponding to the second heat dissipation result is 50%, the confidence level corresponding to the third heat dissipation result is 40, the confidence level corresponding to the fourth heat dissipation result is 85%, and the confidence level corresponding to the fifth heat dissipation result is 90%. The confidence level results corresponding to the fourth heat dissipation model and the fifth heat dissipation model meet the second set confidence threshold, so it is determined that there is an attachment on the cable. Since the confidence level of the fifth heat dissipation model is higher than that of the fourth heat dissipation model, the type of attachment is determined to be a leaf.

[0090] For the technical solution provided in this embodiment, if the confidence levels of all heat dissipation models are less than the first set confidence threshold, it is determined that there are no attachments on the cable; if there are at least two heat dissipation models with confidence levels greater than the second set confidence threshold, the type of attachment on the cable is determined according to the sorting result of the confidence levels of the at least two heat dissipation models. By comparing the confidence level of the heat dissipation model with the set confidence threshold, the judgment result of whether there is an attachment can be made more accurate. In addition, determining the type of attachment corresponding to the heat dissipation model with a high confidence level as the type of cable attachment, on the one hand, the judgment result is more accurate. On the other hand, determining the type of attachment facilitates the maintenance personnel to make timely responses according to the type of attachment, improving the maintenance efficiency.

[0091] For the technical solution provided in this embodiment, the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data are input into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and it is determined whether the attachment recognition condition is satisfied according to the output result; if it is satisfied, it is determined that there are attachments on the cable. By making a judgment on whether there is an attachment phenomenon on the cable under certain conditions based on the data collected by the sensor, the observation arrangement of the attachment can be carried out targeted, improving the monitoring efficiency of the cable attachment and ensuring the operation safety of the cable.

[0092] Embodiment 2

[0093] Figure 2 It is a schematic structural diagram of a cable attachment recognition device based on infrared imaging technology and a heat dissipation model provided in Embodiment 2 of the present application. As Figure 2 shown, the device includes:

[0094] An alarm unit 205, connected to the processing unit, is configured to generate alarm information of a corresponding level according to the degree of attachment of the attachment and a pre-set alarm level mapping table when it is determined that there are attachments on the cable;

[0095] A communication unit 206 is configured to send the alarm information to an attachment alarm response device.

[0096] In this embodiment, the degree of attachment of the attachment can be understood as the degree to which the cable is covered by the attachment. The alarm level can be used to indicate the urgency of the alarm information, which can specifically include a first-level alarm level, a second-level alarm level, and a third-level alarm level. It can be understood that the level of the first-level alarm level is higher than that of the second-level alarm level, which is higher than that of the third-level alarm level. The higher the level of the alarm level, the more urgent the corresponding alarm information. The alarm level mapping table can be understood as a data table for specifying the correspondence between the degree of attachment of the attachment and the alarm level, which can be pre-stored in the database. The alarm information can be a prompt message containing information such as the degree of attachment of the attachment and the alarm level. The attachment alarm response device can be understood as a terminal device that responds to the presence of an attachment on the cable, which can specifically be the terminal device corresponding to the cable maintenance personnel.

[0097] Generating alarm information of a corresponding level according to the degree of attachment of the attachment and the pre-set alarm level mapping table may mean that the higher the degree of attachment of the attachment, the higher the corresponding alarm level in the alarm level mapping table.

[0098] In this embodiment, when it is determined that there is an attachment on the cable, the alarm unit 205 determines the alarm level corresponding to the degree of attachment of the attachment according to the degree of attachment of the attachment and the pre-set alarm level mapping table, and generates alarm information of a corresponding level based on the alarm level. The communication unit 206 sends the alarm information to the attachment alarm response device. It can be understood that the prompting methods corresponding to alarm information of different levels are also different. For example, the prompting method for the alarm information corresponding to the third-level alarm level can be a pop-up window, the prompting method for the alarm information corresponding to the second-level alarm level can be a short message, and the prompting method for the alarm information corresponding to the first-level alarm level can be an alarm prompt tone and a light.

[0099] In this embodiment, optionally, the degree of attachment includes the attachment thickness or the attachment length of the attachment.

[0100] In this embodiment, the adhesion degree of the attachment is determined according to the adhesion thickness or adhesion length of the attachment, and the alarm level is determined according to the attachment degree and the alarm level mapping table. Exemplarily, it is stipulated in the alarm level mapping table that if the coverage length of the attachment is less than or equal to 20 cm or the coverage thickness of the attachment is less than or equal to 1 cm, the corresponding alarm level is the third-level alarm level; if the coverage length of the attachment is greater than 20 cm and less than 50 cm or the coverage thickness of the attachment is greater than 1 cm and less than 2 cm, the corresponding alarm level is the second-level alarm level; if the coverage length of the attachment is greater than or equal to 50 cm or the coverage thickness of the attachment is greater than or equal to 2 cm, the corresponding alarm level is the first-level alarm level. The coverage length of the attachment is 15 cm and the coverage thickness is 0.5 cm. The alarm unit 205 determines, according to the pre-set alarm level mapping table, that the alarm level corresponding to the adhesion degree of the attachment is the third-level alarm level, and generates alarm information including the adhesion degree of the attachment and the alarm level based on the third-level alarm level.

[0101] In the technical solution provided in this embodiment, the adhesion thickness or adhesion length of the attachment determines the adhesion degree, which can further improve the accuracy of the adhesion degree judgment.

[0102] In the technical solution provided in this embodiment, corresponding-level alarm information is generated according to the adhesion degree of the attachment and the pre-set alarm level mapping table, and the alarm information is sent to the attachment alarm response device. By determining the alarm level and sending the alarm information including the alarm level information to the attachment alarm response device, the maintenance personnel can clarify the urgency of the alarm information, so as to quickly take corresponding maintenance measures for different attachment conditions of the attachment, further improving the attachment monitoring efficiency and ensuring the safety of the cable operation.

[0103] Embodiment III

[0104] Figure 3 It is a schematic flowchart of a method for identifying cable attachments based on infrared imaging technology and a heat dissipation model provided in Embodiment III of the present application. As Figure 3 shown, the specific steps are as follows:

[0105] S301. Obtain a cable infrared image through an infrared image collector; wherein, the infrared image collector is arranged at the cable support and faces the cable laying direction.

[0106] S302. Obtain the wind direction data, wind speed data and ambient temperature information in the environment.

[0107] S303. Input the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and determine whether the attachment recognition condition is satisfied according to the output result; if it is satisfied, it is determined that there are attachments on the cable.

[0108] For the technical solution provided in this embodiment, the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data are input into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and it is determined whether the attachment recognition condition is satisfied according to the output result; if it is satisfied, it is determined that there are attachments on the cable. By using the data collected by the sensor to judge whether there is an attachment phenomenon on the cable under certain conditions, the observation arrangement of the attachment can be targeted, the monitoring efficiency of the cable attachment is improved, and the operation safety of the cable is ensured.

[0109] Further, the attachments include at least one of snow, frost, ice, dust, and leaves.

[0110] The heat dissipation model includes:

[0111] The first heat dissipation model corresponding to the attached snow;

[0112] The second heat dissipation model corresponding to the attached frost;

[0113] The third heat dissipation model corresponding to the attached ice;

[0114] The fourth heat dissipation model corresponding to the attached dust;

[0115] The fifth heat dissipation model corresponding to the attached leaves.

[0116] For the technical solution provided in this embodiment, the attachments include at least one of snow, frost, ice, dust, and leaves. By monitoring different types of attachments, a reasonable and comprehensive monitoring mechanism is provided, so that different types of cable faults can be avoided targeted. In addition, by pre-constructing the heat dissipation models for different attachment types, the heat dissipation results corresponding to different attachments for the acquired sensing data can be determined more accurately.

[0117] Further, the step of inputting the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and determining whether the attachment recognition condition is satisfied according to the output result; if it is satisfied, it is determined that there are attachments on the cable includes:

[0118] Input the cable infrared image, the ambient temperature information, the wind direction data, and the wind speed data into a first heat dissipation model, a second heat dissipation model, a third heat dissipation model, a fourth heat dissipation model, and a fifth heat dissipation model, respectively.

[0119] Determine whether the attachment recognition condition is satisfied and the type of attachment when the attachment recognition condition is satisfied based on the output results and confidence levels of the respective heat dissipation models.

[0120] The technical solution provided in this embodiment determines whether the attachment recognition condition is satisfied and the type of attachment when the attachment recognition condition is satisfied based on the output results and confidence levels of the respective heat dissipation models. Determining whether there is an attachment through the confidence level and the corresponding type of attachment when there is an attachment can further improve the accuracy of the judgment result.

[0121] Embodiment 4

[0122] Figure 4 is a schematic structural diagram of an electronic device provided in Embodiment 4 of the present application. As Figure 4 shown, the present application embodiment also provides an electronic device 400, including a processor 401, a memory 402, a program or instruction stored on the memory 402 and executable on the processor 401. When the program or instruction is executed by the processor 401, it implements each process of the above-mentioned cable attachment recognition method embodiment based on infrared imaging technology and heat dissipation models, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0123] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0124] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover a non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the methods and devices in the embodiments of the present application are not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0125] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases, the former is a better implementation method.

[0126] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific implementation manners. The above specific implementation manners are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them fall within the protection scope of the present application.

[0127] The above is only the preferred embodiment of the present application and the technical principles applied. The present application is not limited to the specific embodiments described herein. Various obvious changes, re-adjustments and substitutions that can be made by those skilled in the art will not depart from the protection scope of the present application. Therefore, although the present application has been described in detail through the above embodiments, the present application is not limited to the above embodiments. Without departing from the concept of the present application, it can also include more other equivalent embodiments, and the scope of the present application is determined by the scope of the claims.

Claims

1. A cable attachment recognition device based on infrared imaging technology and a heat dissipation model, characterized in that The device includes: an infrared image collector for acquiring an infrared image of the cable; wherein, the infrared image collector is arranged at the cable support and faces the cable laying direction; a wind sensor for acquiring wind direction data and wind speed data in the environment; a temperature sensor for acquiring environmental temperature information; a processing unit connected to the infrared image collector, the wind sensor and the temperature sensor, for inputting the infrared image of the cable, the environmental temperature information, the wind direction data and the wind speed data into a pre-constructed heat dissipation model to obtain an output result of the heat dissipation model; and determining whether the attachment recognition condition is satisfied according to the output result; if satisfied, it is determined that there are attachments on the cable, and the attachments include at least one of snow, frost, ice, dust and leaves; the heat dissipation model includes a first heat dissipation model corresponding to attached snow, a second heat dissipation model corresponding to attached frost, a third heat dissipation model corresponding to attached ice, a fourth heat dissipation model corresponding to attached dust, and a fifth heat dissipation model corresponding to attached leaves. The processing unit is specifically configured to: input the infrared image of the cable, the environmental temperature information, the wind direction data and the wind speed data into the first heat dissipation model, the second heat dissipation model, the third heat dissipation model, the fourth heat dissipation model and the fifth heat dissipation model. If the confidence levels of each heat dissipation model are all less than the first set confidence threshold, it is determined that there are no attachments on the cable. If the confidence levels of at least two heat dissipation models are all greater than the second set confidence threshold, the type of attachment on the cable is determined according to the confidence level ranking result of the at least two heat dissipation models.

2. The cable attachment recognition device based on infrared imaging technology and heat dissipation model according to claim 1, characterized in that The device further includes: an alarm unit connected to the processing unit, for generating alarm information of a corresponding level according to the attachment degree of the attachment and a pre-set alarm level mapping table when it is determined that there are attachments on the cable; a communication unit for sending the alarm information to the attachment alarm response device.

3. The cable attachment recognition device based on infrared imaging technology and heat dissipation model according to claim 2, wherein The attachment degree includes the attachment thickness or attachment length of the attachment.

4. A method for identifying cable attachments based on infrared imaging technology and a heat dissipation model, characterized in that, The method includes: acquiring an infrared image of the cable through an infrared image collector; wherein, the infrared image collector is arranged at the cable support and faces the cable laying direction; acquiring wind direction data, wind speed data and environmental temperature information in the environment; Input the cable infrared image, the environmental temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and determine whether the attachment recognition condition is satisfied according to the output result; if satisfied, it is determined that there are attachments on the cable, and the attachments include at least one of snow, frost, ice, dust, and leaves; the heat dissipation model includes a first heat dissipation model corresponding to attached snow, a second heat dissipation model corresponding to attached frost, a third heat dissipation model corresponding to attached ice, a fourth heat dissipation model corresponding to attached dust, and a fifth heat dissipation model corresponding to attached leaves. The step of inputting the cable infrared image, the environmental temperature information, the wind direction data, and the wind speed data into a pre-constructed heat dissipation model to obtain the output result of the heat dissipation model; and determining whether the attachment recognition condition is satisfied according to the output result; if satisfied, it is determined that there are attachments on the cable includes: inputting the cable infrared image, the environmental temperature information, the wind direction data, and the wind speed data into the first heat dissipation model, the second heat dissipation model, the third heat dissipation model, the fourth heat dissipation model, and the fifth heat dissipation model respectively. If the confidence levels of all heat dissipation models are less than the first set confidence threshold, it is determined that there are no attachments on the cable. If the confidence levels of at least two heat dissipation models are greater than the second set confidence threshold, the type of attachment on the cable is determined according to the confidence level sorting result of the at least two heat dissipation models.

5. An electronic device, characterized in that, It includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, it implements the steps of the cable attachment recognition method based on infrared imaging technology and a heat dissipation model as described in claim 4.

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