Power transmission line icing galloping multi-source data linkage early warning system integrated with GB / T28181 video protocol

Abstract

The invention relates to the technical field of power transmission line galloping monitoring, in particular to a power transmission line icing galloping multi-source data linkage early warning system integrated with a GB / T28181 video protocol, which comprises a data acquisition module, a data preprocessing module, a multi-source data fusion analysis module, an early warning decision module and an early warning information issuing module, the data acquisition module acquires icing galloping video data through a video acquisition unit conforming to a GB / T28181 protocol, and synchronously acquires multi-source sensing data such as icing, acceleration and weather; after preprocessing, the fusion analysis module extracts video features through a deep learning model, performs cross check with the sensing data, and outputs a fusion analysis result; the early warning decision module generates graded early warning signals. The problems that a traditional early warning system is single in data, non-uniform in protocol and low in early warning precision are solved, visual and quantitative early warning of the icing galloping risk is achieved, and the operation and maintenance efficiency and safety of the power transmission line are improved.

Description

Technical Field

[0001] This invention relates to the technical field of transmission line galloping monitoring, and more particularly to a multi-source data linkage early warning system for transmission line icing galloping that integrates the GB / T28181 video protocol. Background Technology

[0002] Transmission lines are the core infrastructure of the power system, and their safe operation directly affects the stability of power supply. Icing and conductor galloping are the main forms of disasters affecting transmission lines in cold and windy regions. Icing can increase conductor load and reduce insulation performance, and in severe cases, cause tower collapse. Galloping can cause conductor fatigue and breakage, damage to fittings, and even line tripping, resulting in huge economic losses to the power system.

[0003] Current transmission line icing and galloping early warning technologies suffer from the following significant shortcomings: Limited data sources and accuracy: Existing systems often rely on single sensors (such as icing sensors or accelerometers) for data collection, making them susceptible to environmental interference (such as sensor condensation or electromagnetic interference) leading to data deviations. Furthermore, they fail to visually reflect details like icing patterns and galloping trajectories, posing a risk of false alarms and missed alarms. Disconnect between video surveillance and sensor data: While some systems incorporate video surveillance, the lack of a unified standard protocol for video transmission (e.g., different manufacturers using proprietary protocols) prevents the integration and analysis of video and sensor data. This limits their use to post-event retrospective analysis, preventing their application in real-time early warning decisions. Lack of multi-source data fusion and trend prediction: Current technologies largely rely on a simple "data collection - threshold comparison" early warning model, failing to incorporate meteorological data (such as temperature, humidity, and wind speed) to construct trend models of icing growth and galloping development. This makes it impossible to predict the direction of disaster evolution in advance, hindering maintenance personnel from developing timely response strategies. Low visualization of early warning information: Early warning signals are mostly pushed in the form of text and numerical values, lacking corresponding video evidence. Maintenance personnel cannot quickly locate the status of the fault site, resulting in delayed on-site response and increasing the risk of disaster expansion.

[0004] Furthermore, GB / T28181, as the unified communication protocol for security video surveillance systems in my country, has been widely used in transportation, security, and other fields. It possesses functions such as standardized device registration, real-time video stream transmission, and heartbeat keep-alive. However, it has not yet been integrated into the early warning scenario for icing and galloping on power transmission lines, thus failing to leverage the advantages of "unified protocol and data linkage." Therefore, there is an urgent need for a linkage early warning system that can integrate the GB / T28181 video protocol with multi-source data to address the pain points of existing technologies. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing transmission line icing and galloping early warning systems, such as "single data, incompatible protocols, delayed early warning, and poor visualization," and to provide a multi-source data linkage early warning system that integrates the GB / T28181 video protocol. This system enables a full-process early warning system that combines "video visualization monitoring + multi-source data quantitative analysis + trend prediction + rapid interaction," thereby improving the accuracy and efficiency of transmission line operation and maintenance.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A multi-source data linkage early warning system for transmission line icing and galloping, integrating the GB / T28181 video protocol, is provided, including: The data acquisition module includes a video acquisition unit and a multi-source sensing unit based on the GB / T28181 protocol. The video acquisition unit is deployed on the transmission line towers and key nodes along the line to complete device registration, real-time video stream transmission and device status detection in accordance with the GB / T28181 protocol, and to acquire video image data of the icing pattern of the transmission line and the conductor galloping trajectory. The data preprocessing module is used to perform dehazing and image stabilization preprocessing on video image data, noise filtering and timestamp synchronization on sensor data, and generate standardized data sequences. The multi-source data fusion analysis module is used to spatiotemporally correlate preprocessed video image data with sensor data. It extracts ice thickness estimation features and cyclone trajectory features from the video through a deep learning model, and cross-validates them with the measured ice thickness and cyclone parameters in the sensor data. Combined with meteorological data, it outputs the fusion analysis results. The early warning decision module is used to generate warning signals for excessive icing, excessive galloping amplitude, and composite disasters based on preset thresholds and fusion analysis results. The warning signals include warning level, fault location, and associated video clips. The early warning information release module is used to push early warning signals to the operation and maintenance terminal through the power dedicated communication network, and supports video access request response based on the GB / T28181 protocol to realize the visual retrospective of early warning site.

[0007] Preferably, the video acquisition unit includes: a high-definition PTZ camera equipped with a GB / T28181 protocol stack, supporting PTZ control and infrared night vision functions, used to acquire videos of icing and dancing under complex weather conditions.

[0008] Preferably, the multi-source sensing unit includes a micro-weather station for collecting precipitation, visibility and temperature change data along the transmission line. The data preprocessing module aligns the micro-weather data with the icing thickness data collected by the icing sensor on the time axis to generate an environment-icing association dataset.

[0009] Preferably, the fusion analysis results output by the deep learning model include the precise value of icing thickness, icing morphology and growth trend, icing distribution differences, core parameters of galloping, galloping stability assessment, and prediction of the impact of galloping on the line. The icing area of ​​the conductor is located from the video image, and the icing thickness is estimated by combining the binocular visual calibration parameters. The three-dimensional motion parameters of the conductor galloping are extracted from continuous video frames and verified for consistency with the vibration frequency collected by the accelerometer.

[0010] More preferably, the icing morphology and growth trend are determined by extracting the icing edge contour and transparency features from video images to determine the icing type, and combined with meteorological data to predict the icing growth rate in the future time period. The stability assessment of the agitation is based on historical agitation data and current weather conditions to determine whether the agitation is in a stable state, thus avoiding misjudgment of instantaneous disturbances.

[0011] Even better, by combining the line tower type and conductor tension parameters, we can analyze whether the current galloping parameters may lead to conductor fatigue or tower tilting, resulting in the risk of conductor strand breakage.

[0012] Preferably, the early warning decision module also includes a threshold dynamic adjustment submodule, which is used to automatically correct the icing thickness early warning threshold and the galloping amplitude safety threshold based on the transmission line voltage level, tower type and historical fault data.

[0013] Preferably, the early warning information release module sends SMS messages containing early warning level and location information to the mobile terminals of operation and maintenance personnel; pushes early warning messages conforming to the IEC61850 standard to the power dispatching platform; and responds to video-on-demand requests based on the GB / T28181 protocol by transmitting the video clips associated with the early warning back to the dispatching center in real time via the RTSP protocol.

[0014] Compared with the prior art, the beneficial effects of the present invention are: To improve the accuracy of early warnings and reduce false alarms and missed alarms, the system integrates video data, multi-source sensor data, and meteorological data. It uses a Kalman filter algorithm to cross-validate the ice thickness estimated from the video with the actual sensor values. At the same time, it combines meteorological conditions to correct the risk model. Compared with traditional single-sensor early warnings, the false alarm rate is reduced, ensuring the early warning signal is supported by both quantification and visualization.

[0015] By standardizing the protocol and breaking down data silos, the GB / T28181 video protocol is integrated into the early warning scenario of power transmission lines for the first time. This unifies the standards for device registration, video transmission, and status monitoring of video acquisition units, and solves the protocol compatibility problem of equipment from different manufacturers. At the same time, the protocol enables the spatiotemporal synchronization of video data and sensor data, avoiding the "disconnection between video and data" and providing a standardized data foundation for linkage analysis.

[0016] It has the ability to predict trends and avoid disaster risks in advance. The integrated analysis module is based on the icing morphology characteristics (such as rime and hoarfrost) and galloping trajectory parameters extracted from videos. Combined with meteorological data, it constructs an icing growth rate model (which can predict short-term icing changes) and a galloping stability assessment model. Compared with the traditional "threshold-triggered" early warning, it issues risk warnings in advance and allows maintenance personnel sufficient time to deal with the situation.

[0017] To optimize operation and maintenance efficiency and reduce handling costs, the early warning information release module supports the simultaneous push of "early warning signal + associated video clips". Operation and maintenance personnel can directly access the video of the fault site through the GB / T28181 protocol to quickly locate the location and severity of icing. At the same time, the system supports pushing IEC 61850 standard messages to the power dispatching platform to achieve seamless integration with the existing power operation and maintenance system, shortening the on-site handling response time and reducing the cost of manual inspection.

[0018] To ensure data reliability and adapt to complex scenarios, the system has a built-in data consistency verification mechanism that automatically issues a deviation warning when the deviation between video and sensor data exceeds a preset range, ensuring data validity. At the same time, the video acquisition unit supports infrared night vision and anti-shake and defogging functions, and can work stably under complex weather conditions such as low temperature and rain and snow, adapting to the field operation and maintenance environment of power transmission lines. Attached Figure Description

[0019] Figure 1 This is a flowchart of a multi-source data linkage early warning system for icing and dancing of transmission lines integrating the GB / T28181 video protocol, as described in a specific embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please refer to Figure 1 As shown, this application proposes a multi-source data linkage early warning system for transmission line icing and galloping that integrates the GB / T28181 video protocol, including: The data acquisition module includes a video acquisition unit and a multi-source sensing unit based on the GB / T28181 protocol. The video acquisition unit is deployed on the transmission line towers and key nodes along the line to complete device registration, real-time video stream transmission and device status detection in accordance with the GB / T28181 protocol, and to acquire video image data of the icing pattern of the transmission line and the conductor galloping trajectory. The data preprocessing module is used to perform dehazing and image stabilization preprocessing on video image data, noise filtering and timestamp synchronization on sensor data, and generate standardized data sequences. The multi-source data fusion analysis module is used to spatiotemporally correlate preprocessed video image data with sensor data. It extracts ice thickness estimation features and cyclone trajectory features from the video through a deep learning model, and cross-validates them with the measured ice thickness and cyclone parameters in the sensor data. Combined with meteorological data, it outputs the fusion analysis results. The early warning decision module is used to generate warning signals for excessive icing, excessive galloping amplitude, and composite disasters based on preset thresholds and fusion analysis results. The warning signals include warning level, fault location, and associated video clips. The early warning information release module is used to push early warning signals to the operation and maintenance terminal through the power dedicated communication network, and supports video access request response based on the GB / T28181 protocol to realize the visual retrospective of early warning site.

[0022] The system comprises a data acquisition module, a data preprocessing module, a multi-source data fusion and analysis module, an early warning decision-making module, and an early warning information dissemination module. Each module is connected via a dedicated power communication network (such as fiber optic Ethernet or a 5G private network) to ensure real-time data transmission and low latency. The system is deployed on transmission line towers and key nodes along the line, covering multiple monitoring points to form a distributed monitoring network.

[0023] The data acquisition module includes a video acquisition unit and a multi-source sensing unit, which are responsible for the acquisition and uploading of raw data.

[0024] Video Acquisition Unit: High-definition PTZ cameras equipped with the GB / T28181 protocol stack, such as 2-megapixel infrared PTZ cameras from Hikvision or Dahua Technology, are deployed on the tops of transmission line towers and in areas prone to icing along the line, such as windy areas and high-altitude regions. These PTZ cameras support pan-tilt control and infrared night vision functions, enabling them to acquire clear video under complex weather conditions such as nighttime, fog, or snow. The video acquisition unit registers with the upper-level platform via the GB / T28181 protocol, transmits H.264 encoded video streams in real time, and periodically sends device status information, such as online status and lens obstruction alarms. Video data is transmitted in RTSP stream format with a frame rate of 25fps and a resolution of 1920×1080, used to capture dynamic images of conductor icing patterns and galloping trajectories.

[0025] Multi-source sensing unit: Includes micro-weather station, icing sensor, and accelerometer. The micro-weather station is deployed near the tower to collect data such as precipitation, visibility, temperature, humidity, and wind speed; the icing sensor is directly mounted on the conductor to measure icing thickness; the accelerometer is mounted on both the conductor and the tower to collect vibration frequency and amplitude data. All sensor data is aggregated to the gateway via ZigBee or LoRa wireless protocol, and then transmitted to the preprocessing module via the power communication network.

[0026] The data preprocessing module runs on an edge computing gateway or cloud platform and is responsible for data cleaning and standardization.

[0027] For video image data, image processing algorithms are used for dehazing, based on dark channel prior algorithms and electronic image stabilization based on Kalman filtering, to reduce image blur caused by weather and vibration.

[0028] For sensor data, a Butterworth low-pass digital filter is used for noise filtering, and a unified timestamp is added to all data via the NTP protocol to ensure time synchronization between the video stream and the sensor data. After preprocessing, a standardized data sequence is generated in JSON or CSV format, containing timestamps, data values, and quality identifiers. For example, micrometeorological data and icing thickness data are aligned along the time axis to generate an environment-icing correlation dataset for subsequent analysis.

[0029] The multi-source data fusion and analysis module is deployed on cloud servers or high-performance edge devices, and uses deep learning models for feature extraction and cross-validation.

[0030] Deep learning models: Built on TensorFlow or PyTorch frameworks, including Convolutional Neural Networks (CNNs) for video image analysis and Long Short-Term Memory Networks (LSTMs) for time series prediction. Model training data comes from historical icing and dancing event datasets.

[0031] Icing analysis: The icing area of ​​the conductor is located from video images (using Mask R-CNN instance segmentation), and the icing thickness is estimated by combining binocular vision calibration parameters. For example, the thickness value is calculated by comparing the change in conductor diameter before and after icing. Simultaneously, icing edge contours and transparency features are extracted from the video images, and Canny edge detection and HSV color space analysis are used to determine the icing type, such as frost or rime. Finally, the icing growth rate is predicted over the next two hours using an ARIMA time series model combined with meteorological data.

[0032] Galloping Analysis: Three-dimensional motion parameters of the conductor galloping were extracted from continuous video frames and analyzed using optical flow and 3D reconstruction, including amplitude, frequency, and trajectory. These parameters were validated for consistency with vibration frequencies acquired by accelerometers, and data reliability was ensured through correlation coefficient analysis. Furthermore, based on historical galloping data and current meteorological conditions such as wind speed and temperature, a support vector machine (SVM) model was used to evaluate galloping stability, distinguishing between continuous galloping and transient disturbances.

[0033] Integrated Output: The model output includes precise values ​​for icing thickness, icing morphology and growth trends, differences in icing distribution, core galloping parameters including amplitude and frequency, galloping stability assessment (stable / unstable), and prediction of the impact of galloping on the line. For example, by combining the line tower type (such as ZMP1 type tower) and conductor tension parameters (from line design data), it analyzes whether the current galloping parameters may lead to conductor fatigue or tower tilting, and assesses the risk of conductor strand breakage.

[0034] When the wind speed is ≥8m / s and the swaying frequency is between 0.5 and 1Hz, it is judged as "unstable swaying" and there is a continuous risk.

[0035] By comparing the deviation between the video estimate and the sensor measurement in real time, a sensor calibration prompt is triggered when the ice thickness deviation is >2mm or the gyratory amplitude deviation is >0.2m. If a data source is interrupted (such as video transmission lag), the system automatically switches to a temporary analysis mode of "single source data + historical model" to ensure the confidence level of the output results.

[0036] The early warning information dissemination module pushes early warning information through multiple channels and supports visual backtracking. Through the dedicated power communication network, early warning signals are sent to maintenance personnel's mobile terminals in the form of SMS messages, such as: "Red Warning: Tower #A25 ice accumulation exceeds limit, thickness 18mm, location: E115.5°, N38.2°". Simultaneously, early warning messages conforming to the IEC61850 standard (using the MMS protocol) are pushed to the power dispatching platform, facilitating integration into existing SCADA systems.

[0037] It supports video-on-demand requests based on the GB / T28181 protocol. When the dispatch center initiates a request, the module transmits the video clips associated with the warning in real time via the RTSP protocol (e.g., video from 5 minutes before to 5 minutes after the warning), enabling on-site visual backtracking. The video stream can be displayed on a large screen to assist in operation and maintenance decision-making.

[0038] Taking a mountainous section of a 500kV transmission line as an example, after system deployment, during the winter icing period, the video acquisition unit captured images of ice-covered conductors, and the multi-source sensing unit monitored the temperature dropping to -5℃ and the wind speed at 8m / s. The data fusion analysis module estimated the ice thickness to be 12mm, the galloping amplitude to be 0.6m, and predicted the ice growth rate to be 2mm / h. After dynamically adjusting the threshold, the early warning decision module generated an orange alert and pushed it to the maintenance terminal through the publishing module. Maintenance personnel confirmed the on-site situation by reviewing the video and took timely de-icing measures, preventing the line from tripping.

[0039] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A multi-source data linkage early warning system for icing and galloping of transmission lines integrating the GB / T28181 video protocol, characterized in that, include: The data acquisition module includes a video acquisition unit and a multi-source sensing unit based on the GB / T28181 protocol. The video acquisition unit is deployed on the transmission line towers and key nodes along the line to complete device registration, real-time video stream transmission and device status detection in accordance with the GB / T28181 protocol, and to acquire video image data of the icing pattern of the transmission line and the conductor galloping trajectory. The data preprocessing module is used to perform dehazing and image stabilization preprocessing on video image data, noise filtering and timestamp synchronization on sensor data, and generate standardized data sequences. The multi-source data fusion analysis module is used to spatiotemporally correlate preprocessed video image data with sensor data. It extracts ice thickness estimation features and cyclone trajectory features from the video through a deep learning model, and cross-validates them with the measured ice thickness and cyclone parameters in the sensor data. Combined with meteorological data, it outputs the fusion analysis results. The early warning decision module is used to generate warning signals for excessive icing, excessive galloping amplitude, and composite disasters based on preset thresholds and fusion analysis results. The warning signals include warning level, fault location, and associated video clips. The early warning information release module is used to push early warning signals to the operation and maintenance terminal through the power dedicated communication network, and supports video access request response based on the GB / T28181 protocol to realize the visual retrospective of early warning site.

2. The transmission line icing and galloping multi-source data linkage early warning system integrating GB / T28181 video protocol as described in claim 1, characterized in that, The video acquisition unit includes a high-definition PTZ camera equipped with the GB / T28181 protocol stack, which supports PTZ control and infrared night vision functions, and is used to acquire videos of icing and dancing under complex weather conditions.

3. The transmission line icing and galloping multi-source data linkage early warning system integrating GB / T28181 video protocol as described in claim 1, characterized in that, The multi-source sensing unit includes a micro-weather station, which is used to collect precipitation, visibility and temperature change data along the transmission line. The data preprocessing module aligns the micro-weather data with the icing thickness data collected by the icing sensor on the time axis to generate an environment-icing association dataset.

4. The multi-source data linkage early warning system for icing and galloping of transmission lines integrating the GB / T28181 video protocol as described in claim 1, characterized in that, The fusion analysis results output by the deep learning model include precise values ​​of icing thickness, icing morphology and growth trend, differences in icing distribution, core parameters of galloping, galloping stability assessment, and prediction of the impact of galloping on the line. The icing area of ​​the conductor is located from video images, and the icing thickness is estimated by combining binocular visual calibration parameters. The three-dimensional motion parameters of conductor galloping are extracted from continuous video frames and their consistency is verified with the vibration frequency collected by the accelerometer.

5. A multi-source data linkage early warning system for transmission line icing and galloping integrating the GB / T28181 video protocol as described in claim 4, characterized in that, The icing morphology and growth trend are determined by extracting the icing edge contour and transparency features from video images to identify the icing type, and by combining meteorological data to predict the icing growth rate in the future time period. The stability assessment of the agitation is based on historical agitation data and current weather conditions to determine whether the agitation is in a stable state, thus avoiding misjudgment of instantaneous disturbances.

6. A multi-source data linkage early warning system for transmission line icing and galloping integrating the GB / T28181 video protocol as described in claim 4, characterized in that, By combining the line tower type and conductor tension parameters, we can analyze whether the current galloping parameters may lead to conductor fatigue or tower tilting, resulting in the risk of conductor strand breakage.

7. A multi-source data linkage early warning system for transmission line icing and galloping integrating the GB / T28181 video protocol as described in claim 1, characterized in that, The early warning decision module also includes a threshold dynamic adjustment submodule, which is used to automatically correct the icing thickness early warning threshold and the galloping amplitude safety threshold based on the transmission line voltage level, tower type and historical fault data.

8. A multi-source data linkage early warning system for transmission line icing and galloping integrating the GB / T28181 video protocol as described in claim 1, characterized in that, The early warning information release module sends SMS messages containing early warning level and location information to the mobile terminals of operation and maintenance personnel; pushes early warning messages conforming to the IEC61850 standard to the power dispatching platform; and responds to video-on-demand requests based on the GB / T28181 protocol, transmitting the video clips associated with the early warning back to the dispatching center in real time via the RTSP protocol.

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