A system and method for detecting icing sections of cable lines

Abstract

This application discloses a system, method, apparatus, and storage medium for detecting icing sections of cable lines. The technical solution provided in this application detects the vibration data curves of corresponding vibration sensors based on set icing detection indicators when the vibration data curves of vibration data do not match the environmental wind data curves. This determines the icing detection results at the corresponding locations of each vibration sensor, identifies icing nodes based on the icing detection results, and generates icing sections based on consecutive icing nodes. The icing center of the icing section is determined by analyzing the vibration data curves of each vibration sensor within the icing section, and the icing section and icing center are reported to the system backend. Using the above technical means, the icing situation of the line can be understood in a timely manner, allowing for timely de-icing treatment, ensuring the operational stability and reliability of the line, preventing line breaks due to icing, and improving the safety of power transmission.

Description

Technical Field

[0001] This application relates to the field of cable monitoring technology, and in particular to a system, method, apparatus and storage medium for detecting icy sections of cable lines. Background Technology

[0002] Currently, during icy and snowy weather, cable lines frequently suffer from ice and snow accretion, leading to hazards such as broken strands, broken wires, tower collapse, conductor-to-ground flashover, short-circuit tripping, and ice galloping, causing significant losses to society and production. Therefore, monitoring transmission line accretion and promptly reporting abnormalities in cases of severe accretion can effectively prevent disasters.

[0003] However, traditional methods for monitoring icing and snow cover on railway lines mostly rely on manual inspections, which are cumbersome and inconvenient, and manual inspections are inefficient and cannot locate icy sections in a timely manner. Summary of the Invention

[0004] This application provides a system, method, device, and storage medium for detecting icing sections of cable lines. By analyzing wind and vibration data curves of the line, the system determines icing sections and icing centers, and then reports the icing sections and icing centers to the system backend. This allows the system to understand the icing situation of the line in a timely manner, perform de-icing treatment promptly, ensure the operational stability and reliability of the line, avoid line breaks due to icing, and improve the safety of power transmission.

[0005] In a first aspect, embodiments of this application provide a cable line icing section detection system, including a processor, a wind detection module, and multiple vibration sensors;

[0006] The wind detection module is used to periodically detect the environmental wind force data of the current cable line; multiple vibration sensors are arranged at intervals along the current cable line to collect vibration data at each corresponding position on the current cable line.

[0007] The processor is connected to the wind detection module and the vibration sensor. In icy and snowy weather, it periodically acquires the environmental wind data collected by the wind detection module, determines the target number of environmental wind data collected at different time points within a set time period that reaches a set wind threshold, and, if the target number is reached, acquires the vibration data collected continuously by each vibration sensor within the set time period. It then determines whether the vibration data curve matches the environmental wind data curve. If the vibration data curve does not match the environmental wind data curve, it detects the vibration data curve of the corresponding vibration sensor based on a set icing detection index, determines the icing detection result at each vibration sensor location, identifies icing nodes based on the icing detection results, and generates icy road sections based on consecutive icing nodes. Finally, it analyzes the vibration data curves of each vibration sensor within the icy road section to determine the icing center, and reports the icy road section and the icing center to the system backend.

[0008] Furthermore, when determining whether the data curve of the vibration data matches the data curve of the environmental wind data, the processor is specifically used to determine the vibration data fluctuation range corresponding to each wind force value based on the data curve of the environmental wind data, to fit and construct a wind force vibration correlation curve based on the vibration data fluctuation range, and to determine whether the data curve of the vibration data matches the data curve of the environmental wind data based on the curve similarity between the data curve of the vibration data and the wind force vibration correlation curve.

[0009] Furthermore, when determining the icing center of the icy road section based on the vibration data curves of each vibration sensor in the icy road section, the processor is specifically used to compare the vibration data curves of each vibration sensor in the icy road section with the set vibration curve of the icing center, and select the position corresponding to the vibration data curve with the highest similarity as the icing center of the icy road section.

[0010] Furthermore, the processor is also used to query the vibration data curve of the vibration sensor corresponding to the icing center, obtain the peak value of the curve, determine the icing thickness of the icing center based on the peak value of the curve, and report the icing thickness to the system backend.

[0011] In a second aspect, embodiments of this application provide a method for detecting icing sections of cable lines, applied to a processor of the cable line icing section detection system as described in the first aspect, comprising:

[0012] In snowy weather, the environmental wind force data collected by the wind force detection module is acquired at regular intervals to determine the target number of environmental wind force data collected at different time points within a set time period that reach the set wind force threshold.

[0013] When the target quantity reaches the set quantity index, obtain the vibration data collected continuously by each vibration sensor within a set time period in the past, and determine whether the data curve of the vibration data matches the data curve of the environmental wind force data.

[0014] If the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, the vibration data curve of the corresponding vibration sensor is detected based on the set icing detection index to determine the icing detection result at the corresponding position of each vibration sensor. Based on the icing detection result, icing nodes are determined, and icing road sections are generated based on the continuous icing nodes. The icing center of the icing road section is determined by analyzing the vibration data curves of each vibration sensor in the icing road section, and the icing road section and the icing center are reported to the system backend.

[0015] Further, determining whether the data curve of the vibration data matches the data curve of the environmental wind data includes:

[0016] The vibration data fluctuation range corresponding to each wind force value is determined based on the data curve of the environmental wind force data. A wind force vibration correlation curve is constructed based on the vibration data fluctuation range. The similarity between the vibration data curve and the wind force vibration correlation curve is used to determine whether the vibration data curve matches the environmental wind force data curve.

[0017] Further, determining the icing center of the icy road section based on the vibration data curves of each vibration sensor in the icy road section includes:

[0018] The vibration data curves of each vibration sensor in the icy road section are compared with the set vibration curve of the icing center, and the position corresponding to the vibration data curve with the highest similarity is selected as the icing center of the icy road section.

[0019] Furthermore, it also includes:

[0020] Query the vibration data curve of the vibration sensor corresponding to the icing center, obtain the peak value of the curve, determine the icing thickness of the icing center based on the peak value of the curve, and report the icing thickness to the system backend.

[0021] In a third aspect, embodiments of this application provide a cable line icing section detection device, applied to a processor of the cable line icing section detection system as described in the first aspect, comprising:

[0022] The detection module is used to periodically acquire environmental wind data collected by the wind detection module in icy and snowy weather conditions, and determine the target number of environmental wind data collected at different time points within a set time period that reach the set wind threshold.

[0023] The matching module is used to acquire vibration data collected continuously by each vibration sensor within a set time period in the past when the target number reaches a set number indicator, and to determine whether the data curve of the vibration data matches the data curve of the environmental wind data.

[0024] The analysis module is used to detect the vibration data curve of the corresponding vibration sensor based on the set icing detection index when the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, determine the icing detection result at the corresponding position of each vibration sensor, determine the icing node based on the icing detection result, and generate icing road segments based on the continuous icing nodes; determine the icing center of the icing road segment based on the analysis of the vibration data curve of each vibration sensor in the icing road segment, and report the icing road segment and the icing center to the system backend.

[0025] In a fourth aspect, embodiments of this application provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the cable line icing section detection method as described in the second aspect.

[0026] This application embodiment acquires environmental wind data collected by a wind detection module at regular intervals during icy and snowy weather conditions, determines the target number of environmental wind data collected at different time points within a set time period that reaches a set wind threshold; when the target number reaches the set number indicator, it acquires vibration data collected continuously by each vibration sensor within the set time period, and determines whether the data curve of the vibration data matches the data curve of the environmental wind data; when the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, it detects the vibration data curve of the corresponding vibration sensor based on a set icing detection index, determines the icing detection result at the corresponding location of each vibration sensor, determines icing nodes based on the icing detection results, and generates icy road sections based on continuous icing nodes; it analyzes the vibration data curves of each vibration sensor in the icy road section to determine the icing center of the icy road section, and reports the icy road section and icing center to the system backend. By employing the aforementioned technical means, the icing sections and icing centers are determined through analysis of line wind and vibration data curves. These icing sections and centers are then reported to the system backend, enabling the system to promptly understand the icing situation of the lines, carry out timely de-icing treatment, ensure the operational stability and reliability of the lines, avoid line breaks due to icing, and improve the safety of power transmission. Attached Figure Description

[0027] Figure 1 This is a flowchart of a method for detecting icy sections of cable lines provided in Embodiment 1 of this application;

[0028] Figure 2 This is a schematic diagram of the structure of a cable line icing section detection system provided in Embodiment 1 of this application;

[0029] Figure 3 This is a schematic diagram of the structure of a cable line icing section detection device provided in Embodiment 2 of this application;

[0030] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of this application. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below 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 it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing 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 operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0032] Example 1:

[0033] Figure 1 A flowchart of a cable line icing section detection method provided in Embodiment 1 of this application is given. The cable line icing section detection method provided in this embodiment can be executed by a cable line icing section detection system. The cable line icing section detection system can be implemented by software and / or hardware. The cable line icing section detection system can be composed of two or more physical entities.

[0034] The following description uses the cable line icing section detection system as an example to illustrate the cable line icing section detection method. (Refer to...) Figure 1 The specific methods for detecting icy sections of the cable line include:

[0035] S110. In snowy weather, the environmental wind force data collected by the wind force detection module is acquired periodically to determine the target number of environmental wind force data collected at different time nodes within a set time period that reaches the set wind force threshold.

[0036] S120. When the target quantity reaches the set quantity index, obtain the vibration data collected continuously by each vibration sensor in the past set time period, and determine whether the data curve of the vibration data matches the data curve of the environmental wind data.

[0037] S130. If the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, the vibration data curve of the corresponding vibration sensor is detected based on the set icing detection index, the icing detection result at the corresponding position of each vibration sensor is determined, the icing node is determined based on the icing detection result, and an icing road segment is generated based on the continuous icing nodes; the icing center of the icing road segment is determined by analyzing the vibration data curve of each vibration sensor in the icing road segment, and the icing road segment and the icing center are reported to the system backend.

[0038] The cable line icing detection method of this application aims to trigger the detection of icing conditions by monitoring the vibration data of the cable line and utilizing the matching of vibration data curves with environmental wind data. Similarly, by detecting vibration data at various locations along the line, the method analyzes the vibration data curves to determine whether icing has occurred at each location, and locates the icing sections based on the icing detection results. Precise location of icing sections facilitates timely line maintenance by line operation and maintenance personnel, improving the safety and reliability of line operation.

[0039] Specifically, refer to Figure 2 This application provides a cable line icing section detection system, including a processor 12, a wind detection module 14, and multiple vibration sensors 13. The wind detection module 14 is used to periodically detect the environmental wind force data of the current cable line 11. The multiple vibration sensors 13 are spaced along the current cable line 11 to collect vibration data at corresponding locations on the current cable line 11. The processor 12 is signal-connected to the wind detection module 14 and the vibration sensors 13, and is used to periodically acquire the environmental wind force data collected by the wind detection module in icy and snowy weather, determine the target number of environmental wind force data collected at different time points within a set time period that reaches a set wind force threshold, and then... Once the set quantity target is met, the vibration data collected continuously from each vibration sensor within a set time period is acquired. It is then determined whether the vibration data curve matches the environmental wind data curve. If the vibration data curve does not match the environmental wind data curve, the vibration data curve of the corresponding vibration sensor is detected based on the set icing detection index. The icing detection results at the corresponding locations of each vibration sensor are determined. Based on the icing detection results, icing nodes are identified, and icing road sections are generated based on consecutive icing nodes. The icing center of the icing road section is determined by analyzing the vibration data curves of each vibration sensor in the icing road section. The icing road section and icing center are then reported to the system backend.

[0040] The processor can be set at any location on the current cable line. It can obtain relevant environmental wind and vibration data by communicating wirelessly with the wind detection module and vibration sensor on the line, so as to perform line icing analysis based on the environmental wind and vibration data.

[0041] The processor collects ambient temperature data via a temperature sensor. When the ambient temperature is below a set threshold (e.g., 0 degrees Celsius), it determines that the weather is icy or snowy and triggers cable icing detection. The processor can also obtain real-time weather data via a network and trigger cable icing detection when icy or snowy weather is confirmed.

[0042] Furthermore, in icy and snowy weather conditions, environmental wind data is collected at regular intervals to determine the target number of environmental wind data points collected at different time points within a set time period that reach a set wind threshold. Because cable lines will sway due to the wind force when the environmental wind reaches a certain value, the detected vibration data of the cable line differs depending on whether the line is iced or not. Based on this principle, this application embodiment utilizes the vibration of cable lines under wind action to perform line icing analysis, in order to accurately determine the icy sections of the line.

[0043] Among them, for the environmental wind data collected at different time points, a wind threshold is set by comparing them. If the target number of environmental wind data that reaches the set wind threshold in the past set time period is reached, it means that the environmental wind in the past set time period is suitable for line icing analysis. The vibration data generated by the environmental wind causing the cable line to sway can be used to detect the icing of the cable line.

[0044] Furthermore, once the target quantity is reached, vibration data collected by each vibration sensor at different time points during a predetermined period is acquired, and vibration data curves for each sensor are constructed based on this data. Then, by determining whether the vibration data curves match the aforementioned environmental wind data curves, it is decided whether to perform line icing detection.

[0045] Specifically, the vibration data fluctuation range corresponding to each wind force value is determined based on the data curve of the environmental wind force data. A wind force vibration correlation curve is constructed based on the vibration data fluctuation range. The similarity between the vibration data curve and the wind force vibration correlation curve is used to determine whether the vibration data curve matches the environmental wind force data curve.

[0046] Prior to this, the fluctuation range of vibration data of the cable line under different wind conditions was measured through actual testing to establish a mapping relationship between wind data and vibration data fluctuation range. Then, based on the data curve of the environmental wind data, the vibration data fluctuation range corresponding to each wind data point on the curve was found. This allows for the distribution information of vibration data fluctuation range under the influence of environmental wind data at different time points when the line is not iced. By fitting the vibration data fluctuation range at different time points, the vibration data curve under the condition of the line not icing can be obtained, defined as the wind-vibration correlation curve. This curve represents the distribution of vibration data affected by wind when the line is not iced. It can be understood that by comparing the data curve of the actual detected vibration data with this wind-vibration correlation curve, if the similarity between the two curves is lower than the set similarity threshold, it indicates that the current vibration data distribution of the line does not conform to the vibration data distribution pattern of the line under the condition of not icing, indicating that the line may be icing at this time, and the actual vibration data curve does not match the environmental wind data curve. In this case, the icing detection logic of the line can be triggered to detect icing.

[0047] Furthermore, based on the set icing detection index, the vibration data curve of the corresponding vibration sensor is detected to determine the icing detection result at the corresponding position of each vibration sensor, and the icing detection result is used to determine whether icing has occurred at the corresponding position of each vibration sensor.

[0048] Understandably, under icing conditions, line vibration data will remain within a stable range. Therefore, an icing detection index can be established based on the vibration data during icing, indicating the range of vibration fluctuations under icing conditions. Based on the matching results of environmental wind data and line vibration data, the vibration data corresponding to each mismatched vibration sensor is compared to the icing detection index. If the number of vibration data falling within the icing detection index reaches a set percentage of the total, then icing is considered to have occurred at the corresponding sensor location.

[0049] It should be noted that directly judging whether a line is icy based on the comparison between vibration data and icing detection indicators may be affected by short-term bird interference, which can cause changes in vibration data and introduce some error into the detection results. However, by matching environmental wind data with line vibration data, in cases where the two do not match, the corresponding sensor location is highly likely to have icing. In such cases, judging whether the line is icy based on the comparison between vibration data and icing detection indicators is significantly more accurate.

[0050] The system determines whether the line is iced by comparing vibration data with icing detection indicators, identifying the icing detection results at the corresponding locations of each vibration sensor (i.e., iced or uniced). Based on these icing detection results, icing locations are identified as icing nodes. Furthermore, continuous icing occurrences on the current line segment (i.e., consecutive icing nodes) are connected to generate an icing section, which is then reported to the system backend. This instructs maintenance personnel to promptly proceed to the icing section to perform de-icing and ice removal operations, ensuring the safe and stable operation of the line.

[0051] Furthermore, the processor compares the vibration data curves of each vibration sensor on the icy road section with the pre-defined vibration curve for the icing center, selecting the location corresponding to the vibration data curve with the highest similarity as the icing center of the icy road section. Prior to this, vibration data from the icing center is collected through pre-field testing to construct the icing center vibration curve. A large number of icing center vibration curves are constructed by collecting vibration data from the icing center under icing conditions. Subsequently, the processor iterates through the pre-constructed icing center vibration curves based on the vibration data curves of each vibration sensor on the icy road section. The location corresponding to the vibration data curve with the highest similarity to the icing center vibration curve is selected as the icing center of the icy road section, thus accurately locating the icing center. Similarly, this icing center is reported to the system backend so that maintenance personnel can identify the location of severe icing and take appropriate countermeasures in advance.

[0052] Optionally, in one embodiment, the processor is further configured to query the vibration data curve of the vibration sensor corresponding to the icing center, obtain the peak value of the curve, determine the icing thickness of the icing center based on the peak value, and report the icing thickness to the system backend. It is understood that the amplitude of the vibration data at the icing center varies depending on the icing thickness. Therefore, when collecting a large number of vibration curves at icing centers, the actual thickness of the icing center and the corresponding peak value can also be detected to construct a corresponding icing thickness-peak value relationship. Subsequently, by comparing the peak value of the vibration data curve with this icing thickness-peak value relationship, the corresponding icing thickness can be determined. The icing thickness is then reported to the system backend so that maintenance personnel can ascertain the severity of icing and take appropriate countermeasures in advance.

[0053] Optionally, in one embodiment, monitoring cameras can be installed along different sections of the line. These cameras capture images at corresponding monitoring locations (such as the beginning of the line or other locations) and report them to the processor. Based on the captured images, the processor uses a pre-built anomaly detection model to identify whether the images show signs of line icing. Prior to this, images showing icing anomalies are collected as training images and input into the neural network-based anomaly detection model for training. This enables the model to detect and identify icing anomalies, allowing it to subsequently identify line icing from the input monitoring images. Anomaly detection models can also be image classification models. Image classification models can be convolutional neural networks (CNNs). An initial CNN is trained to enable it to extract features from training samples effectively and possess a certain image classification capability. The basic structure of a CNN can include convolutional layers, pooling layers, and fully connected layers. Convolutional and pooling layers are distributed alternately. Convolutional layers can extract features from training samples through convolution calculations. Pooling layers can downsample the training samples input to the CNN, i.e., reduce the size of the training samples while retaining important information. Fully connected layers classify images based on the image features determined by the convolutional layers. Specifically, during the testing phase, a large number of images of lines showing icing and other normal conditions are collected as training samples to train the image classification model. During training, an image set of different states of the fixed line location is first acquired. This image set is then preprocessed and divided into a training sample set and a validation sample set. Preprocessing may include cropping to a uniform size and removing blurry images. The training sample set is then further divided into positive and negative samples. Positive samples represent images of fixed lines covered in ice or fire, while negative samples represent images of fixed lines in a normal state. The setting of positive and negative samples can be adaptively selected based on the model's ability to classify different states, corresponding to the state of the fixed line location. In this way, the detection of monitoring images can be equated to a binary classification problem: either the line is icy, or the line is in a normal state. Therefore, the ground truth value of each positive sample can be marked as 1, and the ground truth value of each negative sample can be marked as 0. The anomaly detection model is trained using multiple marked positive samples and multiple marked negative samples. After each training iteration, the trained anomaly detection model can be iteratively optimized using a validation sample set and a loss function. Training is stopped when the anomaly detection model reaches a preset accuracy or the preset number of training rounds is reached, and the anomaly detection model after training is stopped is taken as the final anomaly detection model. Then, by inputting monitoring images into the anomaly detection model, it is possible to identify whether line icing has occurred.When icing occurs, the degree of icing can be further identified based on the image features of the monitoring images. During the training of the anomaly detection model, the icing images are labeled with corresponding degrees of icing (e.g., partial coverage, full coverage, or corresponding ice thickness, etc.) to train the anomaly detection model, enabling it to identify the degree of icing in the monitoring images. This allows for accurate and timely preventative measures to be taken when an icing anomaly is confirmed.

[0054] The above describes a process where, under icy and snowy weather conditions, environmental wind data collected by a wind detection module is acquired periodically to determine the target number of environmental wind data collected at different time points within a set time period that reaches a set wind threshold. If the target number is reached, vibration data collected continuously from various vibration sensors within the set time period is acquired, and it is determined whether the vibration data curve matches the environmental wind data curve. If the vibration data curve does not match the environmental wind data curve, the vibration data curve of the corresponding vibration sensor is detected based on a set icing detection index to determine the icing detection result at each vibration sensor location. Based on the icing detection result, icing nodes are determined, and icy road sections are generated based on consecutive icing nodes. The icing center of the icy road section is determined by analyzing the vibration data curves of each vibration sensor within the icy road section, and the icy road section and icing center are reported to the system backend. By employing the aforementioned technical means, the icing sections and icing centers are determined through analysis of line wind and vibration data curves. These icing sections and centers are then reported to the system backend, enabling the system to promptly understand the icing situation of the lines, carry out timely de-icing treatment, ensure the operational stability and reliability of the lines, avoid line breaks due to icing, and improve the safety of power transmission.

[0055] Example 2:

[0056] Based on the above embodiments, Figure 3 This is a schematic diagram of a cable line icing section detection device provided in Embodiment 2 of this application. (Reference) Figure 3 The cable line icing section detection device provided in this embodiment specifically includes:

[0057] The detection module 21 is used to periodically acquire environmental wind data collected by the wind detection module in snowy weather conditions, and determine the target number of environmental wind data collected at different time points within a set time period that reach the set wind threshold.

[0058] Matching module 22 is used to acquire vibration data collected continuously by each vibration sensor within a set time period in the past when the target number reaches a set number index, and to determine whether the data curve of the vibration data matches the data curve of the environmental wind force data.

[0059] Analysis module 23 is used to detect the vibration data curve of the corresponding vibration sensor based on the set icing detection index when the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, determine the icing detection result at the corresponding position of each vibration sensor, determine the icing node based on the icing detection result, and generate an icing road segment based on the continuous icing nodes; determine the icing center of the icing road segment by analyzing the vibration data curve of each vibration sensor of the icing road segment, and report the icing road segment and the icing center to the system backend.

[0060] Further, determining whether the data curve of the vibration data matches the data curve of the environmental wind data includes:

[0061] The vibration data fluctuation range corresponding to each wind force value is determined based on the data curve of the environmental wind force data. A wind force vibration correlation curve is constructed based on the vibration data fluctuation range. The similarity between the vibration data curve and the wind force vibration correlation curve is used to determine whether the vibration data curve matches the environmental wind force data curve.

[0062] Further, determining the icing center of the icy road section based on the vibration data curves of each vibration sensor in the icy road section includes:

[0063] The vibration data curves of each vibration sensor in the icy road section are compared with the set vibration curve of the icing center, and the position corresponding to the vibration data curve with the highest similarity is selected as the icing center of the icy road section.

[0064] Furthermore, it also includes:

[0065] Query the vibration data curve of the vibration sensor corresponding to the icing center, obtain the peak value of the curve, determine the icing thickness of the icing center based on the peak value of the curve, and report the icing thickness to the system backend.

[0066] The above describes a process where, under icy and snowy weather conditions, environmental wind data collected by a wind detection module is acquired periodically to determine the target number of environmental wind data collected at different time points within a set time period that reaches a set wind threshold. If the target number is reached, vibration data collected continuously from various vibration sensors within the set time period is acquired, and it is determined whether the vibration data curve matches the environmental wind data curve. If the vibration data curve does not match the environmental wind data curve, the vibration data curve of the corresponding vibration sensor is detected based on a set icing detection index to determine the icing detection result at each vibration sensor location. Based on the icing detection result, icing nodes are determined, and icy road sections are generated based on consecutive icing nodes. The icing center of the icy road section is determined by analyzing the vibration data curves of each vibration sensor within the icy road section, and the icy road section and icing center are reported to the system backend. By employing the aforementioned technical means, the icing sections and icing centers are determined through analysis of line wind and vibration data curves. These icing sections and centers are then reported to the system backend, enabling the system to promptly understand the icing situation of the lines, carry out timely de-icing treatment, ensure the operational stability and reliability of the lines, avoid line breaks due to icing, and improve the safety of power transmission.

[0067] The cable line icing section detection device provided in Embodiment 2 of this application can be used to perform the cable line icing section detection method provided in Embodiment 1 above, and has the corresponding functions and beneficial effects.

[0068] Example 3:

[0069] This application provides an electronic device in embodiment three, referring to... Figure 4 The electronic device includes a processor 31, a memory 32, a communication module 33, an input device 34, and an output device 35. The electronic device may have one or more processors and one or more memories. The processor, memory, communication module, input device, and output device of the electronic device can be connected via a bus or other means.

[0070] Memory, 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 cable line icing section detection method described in any embodiment of this application (e.g., the detection module, matching module, and analysis module in the cable line icing section detection device). Memory may primarily include a program storage area and a data storage area, wherein the program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device, etc. Furthermore, memory may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0071] The communication module is used for data transmission.

[0072] The processor executes various functional applications and data processing of the device by running software programs, instructions, and modules stored in memory, thereby realizing the above-mentioned method for detecting icy sections of cable lines.

[0073] Input devices can be used to receive input numerical or character information, and to generate key signal inputs related to user settings and function control of the device. Output devices may include display devices such as displays.

[0074] The electronic equipment provided above can be used to perform the cable line icing section detection method provided in Embodiment 1 above, and has the corresponding functions and beneficial effects.

[0075] Example 4:

[0076] This application embodiment also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to perform a method for detecting icy sections of cable lines. This method includes: in icy and snowy weather conditions, periodically acquiring environmental wind data collected by a wind detection module, determining a target number of environmental wind data collected at different time points within a previously set time period that reaches a set wind threshold; and, when the target number reaches a set quantity indicator, acquiring vibration data continuously and periodically collected by various vibration sensors within the previously set time period, and determining the vibration data... The system checks whether the data curve matches the data curve of the environmental wind data. If the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, it detects the vibration data curve of the corresponding vibration sensor based on the set icing detection index, determines the icing detection result at the corresponding position of each vibration sensor, determines the icing node based on the icing detection result, and generates an icy road segment based on the continuous icing nodes. The system analyzes the vibration data curve of each vibration sensor in the icy road segment to determine the icing center of the icy road segment, and reports the icy road segment and the icing center to the system backend.

[0077] Storage medium – any type of memory device or storage device. The term “storage medium” is intended to include: mounting media, such as CD-ROM, floppy disk, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. Storage medium may also include other types of memory or combinations thereof. Furthermore, storage medium may reside in a first computer system in which the program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term “storage medium” can include two or more storage media residing in different locations (e.g., in different computer systems connected via a network). Storage medium may store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0078] Of course, the computer-executable instructions provided in the embodiments of this application are not limited to the cable line icing section detection method described above, but can also perform related operations in the cable line icing section detection method provided in any embodiment of this application.

[0079] The cable icing section detection device, storage medium, and electronic equipment provided in the above embodiments can execute the cable icing section detection method provided in any embodiment of this application. For technical details not described in detail in the above embodiments, please refer to the cable icing section detection method provided in any embodiment of this application.

[0080] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of this application, the scope of which is determined by the scope of the claims.

Claims

1. A cable line icing section detection system, characterized in that, Includes a processor, a wind detection module, and multiple vibration sensors; The wind detection module is used to periodically detect the environmental wind force data of the current cable line; multiple vibration sensors are arranged at intervals along the current cable line to collect vibration data at each corresponding position on the current cable line. The processor is connected to the wind detection module and the vibration sensor. In icy and snowy weather, it periodically acquires the environmental wind data collected by the wind detection module, determines the target number of environmental wind data collected at different time points within a set time period that reaches a set wind threshold, and when the target number reaches the set threshold, acquires the vibration data collected continuously by each vibration sensor within the set time period, determines whether the data curve of the vibration data matches the data curve of the environmental wind data, and if the vibration data curve does not match the wind data curve of the environmental wind data, detects the vibration data curve of the corresponding vibration sensor based on a set icing detection index, determines the icing detection result at the corresponding location of each vibration sensor, determines icing nodes based on the icing detection results, and generates icy road sections based on consecutive icing nodes. Based on the vibration data curves of each vibration sensor in the icy road section, the icing center of the icy road section is determined, and the icy road section and the icing center are reported to the system backend. The icing center is the location with severe icing. When determining the icing center of the icy road section based on the vibration data curves of each vibration sensor in the icy road section, the processor is specifically used to compare the vibration data curves of each vibration sensor in the icy road section with the set vibration curve of the icing center, and select the position corresponding to the vibration data curve with the highest similarity as the icing center of the icy road section. The vibration curve of the icing center is constructed by pre-testing the vibration data of the icing center in the field.

2. The cable line icing section detection system according to claim 1, characterized in that, When determining whether the data curve of the vibration data matches the data curve of the environmental wind data, the processor is specifically used to determine the vibration data fluctuation range corresponding to each wind force value based on the data curve of the environmental wind data, to fit and construct a wind force vibration correlation curve based on the vibration data fluctuation range, and to determine whether the data curve of the vibration data matches the data curve of the environmental wind data based on the curve similarity between the data curve of the vibration data and the wind force vibration correlation curve.

3. The cable line icing section detection system according to claim 1, characterized in that, The processor is also used to query the vibration data curve of the vibration sensor corresponding to the icing center, obtain the peak value of the curve, compare the peak value of the curve with the pre-built relationship between the icing thickness and the peak value of the curve to determine the icing thickness of the icing center, and report the icing thickness to the system backend.

4. A method for detecting icing sections of cable lines, applied to the processor of the cable line icing section detection system as described in claim 1, characterized in that, include: In snowy weather, the environmental wind force data collected by the wind force detection module is acquired at regular intervals to determine the target number of environmental wind force data collected at different time points within a set time period that reach the set wind force threshold. When the target quantity reaches the set quantity index, obtain the vibration data collected continuously by each vibration sensor within a set time period in the past, and determine whether the data curve of the vibration data matches the data curve of the environmental wind force data. If the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, the vibration data curve of the corresponding vibration sensor is detected based on the set icing detection index, the icing detection result at the corresponding position of each vibration sensor is determined, the icing node is determined based on the icing detection result, and the icing road section is generated based on the continuous icing nodes. The icing center of the icy road section is determined by analyzing the vibration data curves of each vibration sensor in the icy road section, and the icy road section and the icing center are reported to the system backend. The ice-covered center refers to the location with severe ice accumulation. The step of determining the icing center of the icy road section based on the vibration data curves of each vibration sensor in the icy road section includes: comparing the vibration data curves of each vibration sensor in the icy road section with a set vibration curve of the icing center, and selecting the position corresponding to the vibration data curve with the highest similarity as the icing center of the icy road section, wherein the vibration curve of the icing center is constructed by pre-testing the vibration data of the icing center in the field.

5. The method for detecting icy sections of cable lines according to claim 4, characterized in that, The step of determining whether the data curve of the vibration data matches the data curve of the environmental wind data includes: The vibration data fluctuation range corresponding to each wind force value is determined based on the data curve of the environmental wind force data. A wind force vibration correlation curve is constructed based on the vibration data fluctuation range. The similarity between the vibration data curve and the wind force vibration correlation curve is used to determine whether the vibration data curve matches the environmental wind force data curve.

6. The method for detecting icy sections of cable lines according to claim 4, characterized in that, Also includes: The vibration data curve of the vibration sensor corresponding to the icing center is queried, the peak value of the curve is obtained, the peak value of the curve is compared with the pre-built relationship between the icing thickness and the peak value of the curve to determine the icing thickness of the icing center, and the icing thickness is reported to the system backend.

7. A cable line icing section detection device, applied to the processor of the cable line icing section detection system as described in claim 1, characterized in that, include: The detection module is used to periodically acquire environmental wind data collected by the wind detection module in icy and snowy weather conditions, and determine the target number of environmental wind data collected at different time points within a set time period that reach the set wind threshold. The matching module is used to acquire vibration data collected continuously by each vibration sensor within a set time period in the past when the target number reaches a set number indicator, and to determine whether the data curve of the vibration data matches the data curve of the environmental wind data. The analysis module is used to detect the vibration data curve of the corresponding vibration sensor based on the set icing detection index when the vibration data curve of the vibration data does not match the wind data curve of the environmental wind data, determine the icing detection result at the corresponding position of each vibration sensor, determine the icing node based on the icing detection result, and generate icing road sections based on the continuous icing nodes. The icing center of the icy road section is determined by analyzing the vibration data curves of each vibration sensor in the icy road section. The icy road section and the icing center are then reported to the system backend. The icing center is the location with severe icing. The analysis module is specifically used to: compare the vibration data curves of each vibration sensor in the icy road section with the set vibration curve of the icing center, and select the location corresponding to the vibration data curve with the highest similarity as the icing center of the icy road section. The vibration curve of the icing center is constructed by pre-testing the vibration data of the icing center in the field.

8. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the cable line icing section detection method as described in any one of claims 4-6.

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