A monitoring and alarm system for power lines

Abstract

The present invention discloses a monitoring and alarm system for power lines, and relates to the technical field of power system monitoring equipment. It includes a data acquisition module, a high-frequency arc monitoring module, a salt spray corrosion monitoring module, a risk identification module and an early warning monitoring module. Comprehensive monitoring is ensured by real-time acquisition of the operating status and environmental data of the power lines. The high-frequency oscillation signal characteristics in the power lines are captured, the abnormal trend of arc discharge is identified, and the arc fault risk is evaluated to accurately detect potential faults. The corrosion effects of the salt concentration and humidity in the air on the power lines are analyzed, and the environmental corrosion risk is evaluated. According to the arc fault risk and the corrosion risk, the power lines are classified into abnormal lines and normal lines, and the abnormal lines are monitored in real time, and the alarm information is sent to the power administrator to achieve rapid response and processing. The detection and management capabilities of potential risks of power lines are improved, and the safety and stability of power lines are effectively guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of power system monitoring equipment, in particular to a monitoring and alarm system for power lines. Background Art

[0002] With the progress of urbanization and technological development, the global demand for electricity is growing. The increased power load and complex power network make the maintenance and monitoring of power lines more important. Climate change and environmental pollution have increased the risk of corrosion in the environment where power lines are located. Salt spray in coastal areas has a significant corrosive effect on power equipment, and extreme weather conditions also increase the risk of failure in the power system. Failure of power lines will not only cause power outages, but may also cause more serious accidents. Therefore, timely monitoring and early warning can reduce the losses caused by failures and protect public safety and economic interests.

[0003] For example, the power line monitoring alarm device with publication number CN117593837A, in which the infrared sensor is connected to the voice alarm module, the light alarm module and the communication module respectively, for monitoring the surrounding state of the power line, generating and outputting the alarm signal, the voice alarm module and the light alarm module respectively output the voice alarm information and the light alarm information after receiving the alarm signal, the communication module is connected to the monitoring system, and sends the alarm signal to the monitoring system so that the staff can grasp the surrounding state of the power line through the monitoring system, and the power supply module is used for power supply. The above device realizes the safety monitoring of the surrounding of the power line, avoids personal injury and property loss caused by accidents of the power line, the combination of voice alarm and light alarm improves the warning effect, avoids potential dangers, and timely feedbacks the alarm and related information, which is convenient for management and response, and ensures the safety and stability of the power line.

[0004] For example, a power line monitoring and early warning system with publication number CN114937238A includes an image acquisition center and a power server. The image acquisition center is deployed on a video monitoring platform, and the image acquisition center and the power server perform wireless transmission. The image acquisition center includes a video import module, a video frame extraction module, and a preliminary detection module. The power server includes a fireworks recognition module, an engineering vehicle recognition module, a floating object recognition module, and a warning module. The system detects and identifies floating objects, engineering vehicles, fireworks, etc. around the power lines based on monitoring videos, solving the problems of insufficient manual inspections, weak inspection forces, and the inability to monitor and manage sudden safety hazards in a timely manner.

[0005] However, the above systems mainly rely on infrared sensors for monitoring, lacking adaptability to environmental changes such as salt spray and humidity, resulting in insufficient detection accuracy of arc faults. Focusing on video monitoring, the monitoring of salt spray concentration and humidity changes in the power line environment is insufficient, and the recognition and analysis capabilities of high-frequency arc signals are also limited. These systems fail to achieve multi-dimensional comprehensive analysis of high-frequency arc signals and environmental factors in power lines, limiting their application in power system fault warning and risk assessment. Therefore, improving the environmental adaptability, fault detection accuracy, and data analysis capabilities of power line monitoring systems is an urgent need for current technological development. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a monitoring and alarm system for a power line, which solves the problems of the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a monitoring and alarm system for power lines, comprising the following modules: a data acquisition module, a high-frequency arc monitoring module, a salt spray corrosion monitoring module, a risk identification module, and an early warning monitoring module; the data acquisition module is used to collect power line monitoring data in real time through sensors of the power lines; the high-frequency arc monitoring module is used to monitor high-frequency arc signals in the power lines, capture the characteristics of high-frequency oscillation signals in the power lines according to the power line monitoring data, identify the abnormal trend of arc discharge, and evaluate the arc fault risk of the current power lines; the salt spray corrosion monitoring module is used to monitor the salt spray corrosion of the surrounding environment of the power lines, analyze the influence of salt concentration and humidity in the air on the power lines according to the power line monitoring data, and evaluate the corrosion risk of the current power lines; the risk identification module is used to classify the current power lines into abnormal lines and normal lines according to the arc fault risk and corrosion risk of the current power lines; the early warning monitoring module is used to monitor abnormal lines and power line monitoring data, and mark the abnormal lines and send them to the power administrator.

[0008] Furthermore, the power line monitoring data includes power line high-frequency arc signal data and power line environmental data; the power line high-frequency arc signal data includes signal amplitude, signal frequency, pulse width, pulse interval, and signal phase; the power line environmental data includes surrounding air salt concentration and surrounding air humidity.

[0009] Furthermore, the specific process of capturing the high-frequency oscillation signal characteristics in the power line and identifying the abnormal trend of arc discharge is as follows: denoising and multi-dimensional feature extraction are performed on the high-frequency arc signal data of the power line; the multi-dimensional feature extraction of the high-frequency arc signal data of the power line includes frequency domain feature extraction, time domain feature extraction and time-frequency feature extraction; the frequency domain feature extraction includes analyzing the frequency components of the high-frequency signal of the power line through fast Fourier transform, and extracting the main frequency components and amplitudes; the time domain feature extraction includes extracting the pulse width, pulse interval and amplitude characteristics in the signal; the time-frequency feature extraction includes extracting the dynamic changes of the signal in the time and frequency dimensions through short-time Fourier transform, and capturing the transient change trend of the arc discharge signal; the extracted multi-dimensional features are matched with the arc discharge abnormal pattern library through the dynamic time warping algorithm to generate the multi-dimensional feature abnormal trend similarity, and identify the abnormal trend of arc discharge.

[0010] Furthermore, the specific process of evaluating the arc fault risk of the current power line is as follows: according to the similarity of abnormal trends of multi-dimensional features, weights are assigned to abnormal trends of different dimensional features to obtain the power line arc fault risk index.

[0011] Furthermore, based on the power line monitoring data, the specific process of analyzing the impact of salt concentration and humidity in the air on the power lines is as follows: based on the power line environmental data, compare the salt concentration of the surrounding air with the set salt concentration risk threshold; obtain the air salt concentration risk difference; compare the surrounding air humidity with the set air humidity risk threshold; obtain the air humidity risk difference; based on the air salt concentration risk difference and the air humidity risk difference, analyze the impact of salt concentration and humidity in the air on the corrosion rate of the power lines.

[0012] Furthermore, the specific process of evaluating the current corrosion risk of the power line is as follows: the air salt concentration risk difference and the air humidity risk difference are respectively comprehensively calculated with the set air salt concentration allowable deviation value and the air humidity allowable deviation value to obtain the power line corrosion risk index.

[0013] Furthermore, the classification process of classifying the current power line into abnormal line and normal line is as follows: according to the power line arc fault risk index and the power line corrosion risk index, they are compared with the set arc fault risk index threshold and the corrosion risk threshold respectively; when the power line arc fault risk index and the power line corrosion risk index are respectively less than the set arc fault risk index threshold and the corrosion risk threshold, the current power line is classified as a normal line, otherwise it is an abnormal line.

[0014] The present invention has the following beneficial effects:

[0015] (1) This power line monitoring and alarm system can comprehensively monitor the operating status and environmental factors of the power line through the integrated data acquisition module, high-frequency arc monitoring module and salt spray corrosion monitoring module, capture the high-frequency arc signal characteristics in real time, and analyze the salt spray corrosion situation, thereby improving the detection capability of potential risks of the power line. The high-frequency arc monitoring module can accurately identify the abnormal trend of arc discharge and evaluate the risk of arc fault by analyzing the high-frequency oscillation signal in the power line, ensuring timely detection and handling of arc problems that may cause system failures.

[0016] (2) In this power line monitoring and alarm system, the salt spray corrosion monitoring module evaluates the corrosion risk of the environment around the power line by monitoring the salt concentration and humidity, so that the system can adapt to different environmental conditions, especially in coastal areas where salt spray corrosion is more serious, and provide targeted protection measures. The risk identification module can classify power lines into abnormal lines and normal lines according to arc fault risks and corrosion risks, which helps to quickly locate lines that need special attention and improve the maintenance efficiency of the system. The early warning monitoring module monitors abnormal lines in real time and sends relevant information tags to power administrators to ensure that measures can be taken quickly when problems are found, reduce the impact of faults on the stability of the power system, and ensure the continuity and safety of power supply.

[0017] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a flow chart of a monitoring and alarm system for power lines. DETAILED DESCRIPTION

[0019] The embodiment of the present application solves the problem of real-time monitoring and fault warning of power lines in complex environments and high load conditions through a monitoring and alarm system for power lines. The system comprehensively utilizes high-frequency arc monitoring, salt spray corrosion detection and intelligent risk identification technology, and can accurately identify arc discharge anomalies and corrosion risks, and issue warnings in a timely manner, thereby effectively improving the operational safety and stability of power lines and reducing the impact of potential faults on the power system.

[0020] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0021] The power line monitoring data is collected in real time through the sensors on the power lines.

[0022] Monitor high-frequency arc signals in power lines, capture the high-frequency oscillation signal characteristics in power lines based on power line monitoring data, identify abnormal trends in arc discharge, and assess the arc fault risks of current power lines.

[0023] Monitor the salt spray corrosion in the environment around power lines, analyze the impact of salt concentration and humidity in the air on power lines based on power line monitoring data, and assess the current corrosion risk of power lines.

[0024] According to the arc fault risk and corrosion risk of the current power lines, the current power lines are classified into abnormal lines and normal lines.

[0025] Monitor abnormal lines and power line monitoring data, and mark abnormal lines and send them to power administrators.

[0026] See also Figure 1 The embodiment of the present invention provides a technical solution: a monitoring and alarm system for power lines, comprising the following modules: a data acquisition module, a high-frequency arc monitoring module, a salt spray corrosion monitoring module, a risk identification module, and an early warning monitoring module; the data acquisition module is used to collect power line monitoring data in real time through sensors of the power lines; the high-frequency arc monitoring module is used to monitor high-frequency arc signals in the power lines, capture the characteristics of high-frequency oscillation signals in the power lines according to the power line monitoring data, identify the abnormal trend of arc discharge, and evaluate the arc fault risk of the current power lines; the salt spray corrosion monitoring module is used to monitor the salt spray corrosion of the surrounding environment of the power lines, analyze the influence of salt concentration and humidity in the air on the power lines according to the power line monitoring data, and evaluate the corrosion risk of the current power lines; the risk identification module is used to classify the current power lines into abnormal lines and normal lines according to the arc fault risk and corrosion risk of the current power lines; the early warning monitoring module is used to monitor abnormal lines and power line monitoring data, and mark the abnormal lines and send them to the power administrator.

[0027] In this implementation, the data acquisition module is the basic part of the power line monitoring and alarm system, which is responsible for collecting various monitoring data in real time through sensors installed on the power lines. Sensors include current sensors, voltage sensors, temperature and humidity sensors, etc., which can obtain electrical parameters of power lines and surrounding environment information. These real-time data provide basic information support for subsequent arc monitoring and corrosion monitoring.

[0028] The high-frequency arc monitoring module is used to monitor high-frequency arc signals in power lines and analyze arc discharge anomalies.

[0029] Arc discharge is a kind of power fault, which usually manifests as a high-frequency oscillation signal. This module can detect and analyze the characteristics of these high-frequency signals and identify abnormal trends of arc discharge. Through these data, the system can evaluate the risk of arc faults in power lines and prevent potential power accidents. The salt spray corrosion monitoring module is used to monitor the influence of factors such as salt concentration and humidity in the environment around power lines on line corrosion.

[0030] The high salt content in the air will accelerate the corrosion of power equipment. This module monitors the salt concentration and humidity level in the air, combines the line monitoring data, and evaluates the corrosion effects of these environmental factors on the power line, thereby predicting the service life and maintenance needs of the power line. The risk identification module comprehensively analyzes the arc fault risk and corrosion risk of the power line, and classifies the power line into abnormal lines and normal lines. This module identifies the overall operating status of the power line by combining the data of the high-frequency arc monitoring module and the salt spray corrosion monitoring module. If the fault risk or corrosion risk of a line exceeds the preset standard, the line will be marked as an abnormal line, indicating that inspection and maintenance are required. The early warning monitoring module is used to monitor the operating status of abnormal lines and send early warning information to power managers. The main purpose of this module is to analyze the data of abnormal lines and send alarm information to relevant power managers in a timely manner so that necessary repair and maintenance measures can be taken to prevent potential faults from developing into actual accidents and ensure the continued safe operation of power lines.

[0031] Specifically, the power line monitoring data includes power line high-frequency arc signal data and power line environmental data; the power line high-frequency arc signal data includes signal amplitude, signal frequency, pulse width, pulse interval, and signal phase; the power line environmental data includes surrounding air salt concentration and surrounding air humidity.

[0032] In this embodiment, the power line monitoring and alarm system collects all data related to the power line status and the surrounding environment, including electrical signals and environmental parameters. These data are collected in real time by the system's sensors and are used to analyze the operating status of the power line and the impact of the external environment to ensure the safety and stability of the power system. The power line high-frequency arc signal data is various parameter data contained in the high-frequency signal generated by arc discharge in the power line. Arc discharge is a power fault phenomenon, and its signal characteristics include: Signal amplitude: represents the intensity of the arc discharge signal, that is, the maximum voltage or current value of the signal, reflecting the energy of the arc discharge. Signal frequency: refers to the oscillation frequency of the arc discharge signal, usually in the high-frequency range, which is an important feature for analyzing arc faults. Pulse width: refers to the duration of each pulse of the arc signal, which is used to evaluate the stability and intensity change of the arc discharge. Pulse interval: refers to the time interval between two consecutive arc pulses, reflecting the periodicity of the arc discharge. Signal phase: refers to the relative position of the signal in time, which is used to analyze the synchronization and phase difference of multiple signals, and help identify the source and location of the arc fault. Power line environmental data reflects the parameter data of the environment around the power line, especially the climate factors related to line corrosion and loss. This data is mainly used to evaluate the impact of environmental conditions on power line equipment to ensure timely detection of potential corrosion risks: Surrounding air salt concentration: The salt content in the air, especially in coastal areas, salt will accelerate the metal corrosion of power lines. Surrounding air humidity: The water vapor content in the air, high humidity will further enhance the corrosion effect of salt on metal materials. Therefore, by monitoring salt and humidity, the system can predict the corrosion rate and risk of power lines.

[0033] Specifically, the specific process of capturing the high-frequency oscillation signal characteristics in the power line and identifying the abnormal trend of arc discharge is as follows: denoising and multi-dimensional feature extraction of the high-frequency arc signal data of the power line; multi-dimensional feature extraction of the high-frequency arc signal data of the power line includes frequency domain feature extraction, time domain feature extraction and time-frequency feature extraction; frequency domain feature extraction includes analyzing the frequency components of the high-frequency signal of the power line through fast Fourier transform, and extracting the main frequency components and amplitudes; time domain feature extraction includes extracting the pulse width, pulse interval and amplitude characteristics in the signal; time-frequency feature extraction includes extracting the dynamic changes of the signal in the time and frequency dimensions through short-time Fourier transform, and capturing the transient change trend of the arc discharge signal; the extracted multi-dimensional features are matched with the arc discharge abnormal pattern library through the dynamic time warping algorithm to generate the multi-dimensional feature abnormal trend similarity, and identify the abnormal trend of arc discharge.

[0034] In this implementation, in the above-mentioned power line monitoring system, the calculation results of feature extraction are combined with the dynamic time warping algorithm (DTW) to identify the abnormal trend of arc discharge, and further calculate the similarity of frequency domain, time domain and time-frequency features. In order to avoid duplication of formula parameters and have clear correlation between each step, the following is an improved explanation and formula representation, feature extraction of high-frequency oscillation signal, main frequency component and the corresponding amplitude Represents the dominant frequency characteristics of the signal, the formula is: ;in, : Frequency domain signal, : Original time domain signal, The number of sampling points, f: frequency component, indicating the specific frequency being analyzed in the frequency domain, j: imaginary unit, used to process complex operations, : Rotation factor, which maps the time domain signal to the frequency component in the frequency domain. n represents the index of the sampling point in the time domain, that is, the specific sampling position or time point of the signal in the time domain. : Main frequency components, : Main frequency amplitude. Time domain feature extraction directly extracts pulse width from the signal , pulse interval and amplitude ,These features can reflect the temporal structure and intensity changes of the signal. The transient changes of the signal are analyzed in the time-frequency domain by short-time Fourier transform. This feature extraction can capture the instantaneous frequency and amplitude changes of the arc discharge signal. , and the time-frequency distribution of the signal can be observed. The formula is: ; : The original time domain signal represents the high-frequency arc signal data of the power line. Indicates the center position of the time window for signal analysis, represents the local frequency analyzed in the short-time Fourier transform, : Time window function is used to intercept the data of the signal in a specific time window to ensure that only a local time segment is analyzed. : Integral variable, a global variable representing time, used to traverse the entire signal. The kernel of the Fourier transform represents the extraction of frequency components. Signal at time and frequency The joint representation on the dimensions generates a time-frequency diagram to reveal the frequency components of the signal and their changes at different time points. The association of multi-dimensional features with the dynamic time warping algorithm (DTW), the extracted frequency domain, time domain and time-frequency features will be used to match the arc discharge abnormal pattern library. At this time, the dynamic time warping algorithm is used to calculate the extracted feature sequence Arc discharge feature sequence in the pattern library The similarity between them. The formula is: ;in, : Extracted feature sequence, including , , , . : Feature sequence in the pattern library, The distance between two feature points, the final output is the multi-dimensional feature anomaly trend similarity , m: the length of the alignment path, that is, the number of optimal matching path points between two sequences.

[0035] Specifically, the specific process of evaluating the arc fault risk of the current power line is as follows: according to the similarity of abnormal trends of multi-dimensional features, weights are assigned to abnormal trends of different dimensional features to obtain the power line arc fault risk index.

[0036] In this implementation, after completing the dynamic time warping algorithm calculation, the similarity between the multi-dimensional features and the pattern library is obtained. The similarity of each feature is calculated as follows: Frequency domain feature similarity : The similarity between frequency and amplitude can be calculated by and The difference is as follows: ;in, and is the frequency anomaly threshold and amplitude anomaly threshold in the pattern library, the similarity of time domain features, including pulse width, pulse interval, amplitude parameters, and the formula for the similarity of time domain features is as follows: ; Time domain characteristic value of the current signal; : Time domain reference features in the abnormal pattern library, The number of time domain feature dimensions. The time-frequency feature similarity formula is as follows: ;in, : The time-frequency domain characteristic value of the current signal. : Time-frequency domain features in the abnormal pattern library, The number of time-frequency feature dimensions. The formula for the power line arc fault risk index is as follows: ;in: :Power line arc fault risk index. Frequency domain feature similarity, Time domain feature similarity, Similarity of time-frequency features, The weight coefficients corresponding to the similarity of frequency domain, time domain and time-frequency features respectively.

[0037] Specifically, based on the power line monitoring data, the specific process of analyzing the impact of salt concentration and humidity in the air on the power lines is as follows: based on the power line environmental data, compare the surrounding air salt concentration with the set salt concentration risk threshold; obtain the air salt concentration risk difference; compare the surrounding air humidity with the set air humidity risk threshold; obtain the air humidity risk difference; based on the air salt concentration risk difference and the air humidity risk difference, analyze the impact of salt concentration and humidity in the air on the corrosion rate of power lines.

[0038] In this implementation scheme, the system extracts the salt concentration data in the surrounding air based on the monitored power line environment data. This data is compared with the preset salt concentration risk threshold. The salt concentration risk threshold is usually a reference value determined based on long-term corrosion research and the material characteristics of power equipment, representing the salt concentration level within the safe range. The comparison result generates a salt concentration risk difference, which indicates the degree of deviation of the actual salt concentration from the risk threshold. If the difference is large, it means that the salt concentration exceeds the safe range and the corrosion risk increases; otherwise, it means that the salt concentration is within a relatively safe range. The humidity data of the surrounding air is extracted and compared with the preset air humidity risk threshold. Air humidity has a great influence on the corrosion of power lines, especially in a high-salt environment, where the increase in humidity will accelerate the corrosion process. Salt concentration risk difference: represents the deviation of the salt content in the current air from the set safety threshold. The larger the difference, the higher the corrosion risk. Humidity risk difference: represents the difference between the current air humidity and the preset safety threshold. The higher the humidity, especially in a high-salt environment, the greater the possibility of accelerated corrosion. The humidity risk difference is used to quantify this degree of deviation. Corrosion rate impact: Based on the risk difference between salt concentration and humidity, the system can calculate the combined impact of these two factors on the corrosion rate of power lines. The corrosion rate usually increases with the increase of salt and humidity, so the system will combine these two data to derive a comprehensive corrosion risk assessment value to help predict potential corrosion failures of the line.

[0039] Specifically, the specific process of evaluating the current power line corrosion risk is as follows: the air salt concentration risk difference and the air humidity risk difference are respectively comprehensively calculated with the set air salt concentration allowable deviation value and the air humidity allowable deviation value to obtain the power line corrosion risk index.

[0040] In this implementation scheme, air salt concentration risk difference: the salt concentration risk difference is obtained by comparing the currently monitored air salt concentration with the set salt concentration risk threshold. This difference reflects the degree of influence of the current environmental salinity on the corrosion of power lines. Air humidity risk difference: the air humidity currently monitored is compared with the set humidity risk threshold to obtain the air humidity risk difference. This difference reflects the influence of humidity on the corrosion rate of the line. The air salt concentration risk difference and the air humidity risk difference are respectively combined with the set allowable deviation values ​​of salt concentration and humidity. The allowable deviation value is a pre-set tolerance range, which is used to indicate the corrosion risk that the power line can withstand under different conditions. The formula for the power line corrosion risk index is as follows, ; Among them, CRI: Corrosion Risk Index, represents the overall corrosion risk level of power lines. :Salt concentration risk difference (the difference between the current air salt concentration and the salt concentration threshold). : Allowable deviation value of salt concentration. : Air humidity risk difference (the difference between the current air humidity and the humidity threshold). The permissible deviation value of humidity. and : are the weights of salt concentration and humidity, respectively, reflecting the relative importance of the two to the corrosion risk. The higher the corrosion risk index, the greater the impact of environmental factors on line corrosion, and the higher the corrosion risk of power lines.

[0041] Specifically, the classification process of classifying the current power line into abnormal line and normal line is as follows: according to the power line arc fault risk index and the power line corrosion risk index, they are compared with the set arc fault risk index threshold and the corrosion risk threshold respectively; when the power line arc fault risk index and the power line corrosion risk index are respectively less than the set arc fault risk index threshold and the corrosion risk threshold, the current power line is classified as a normal line, otherwise it is an abnormal line.

[0042] In this implementation scheme, arc fault risk index comparison: based on the previously calculated arc fault risk index of the power line, compare it with the set arc fault risk index threshold. If the arc fault risk index is less than the threshold, it means that the arc discharge risk is low. Corrosion risk index comparison: compare the current power line corrosion risk index with the set corrosion risk threshold. If the corrosion risk index is less than the threshold, it means that the corrosion risk caused by environmental factors is low. Normal line: When the arc fault risk index and the corrosion risk index are both lower than their respective thresholds, the system judges the power line as a normal line, which means that the line is in good operating condition and the risk is within a controllable range. Abnormal line: If either the arc fault risk index or the corrosion risk index exceeds the corresponding threshold, the system will mark the line as an abnormal line, indicating that there is a potential safety hazard or failure risk.

[0043] In summary, this application has at least the following effects:

[0044] A monitoring and alarm system for power lines includes a data acquisition module, a high-frequency arc monitoring module, a salt spray corrosion monitoring module, a risk identification module, and an early warning monitoring module. Comprehensive monitoring is ensured by real-time collection of the operating status and environmental data of the power lines. The high-frequency oscillation signal characteristics in the power lines are captured to identify the abnormal trend of arc discharge, and the arc fault risk is evaluated to accurately detect potential faults. The corrosion effects of the salt concentration and humidity in the air on the power lines are analyzed to evaluate the environmental corrosion risk. According to the arc fault risk and corrosion risk, the power lines are classified into abnormal lines and normal lines, and the abnormal lines are monitored in real time, and the alarm information is sent to the power administrator to achieve rapid response and processing. The detection and management capabilities of potential risks of power lines are improved, and the safety and stability of power lines are effectively guaranteed.

[0045] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0046] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0047] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0048] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0049] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0050] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A monitoring and alarm system for power lines, characterized in that: It includes the following modules: data acquisition module, high-frequency arc monitoring module, salt spray corrosion monitoring module, risk identification module, and early warning monitoring module; The data acquisition module is used to collect power line monitoring data in real time through sensors of the power line; The high-frequency arc monitoring module is used to monitor the high-frequency arc signal in the power line, capture the high-frequency oscillation signal characteristics in the power line according to the power line monitoring data, identify the abnormal trend of arc discharge, and evaluate the arc fault risk of the current power line; The salt spray corrosion monitoring module is used to monitor the salt spray corrosion of the environment around the power line, analyze the influence of the salt concentration and humidity in the air on the power line according to the power line monitoring data, and evaluate the corrosion risk of the current power line; The risk identification module is used to classify the current power line into an abnormal line and a normal line according to the arc fault risk and corrosion risk of the current power line; The early warning monitoring module is used to monitor abnormal lines and power line monitoring data, and mark abnormal lines and send them to the power administrator; The specific process of capturing the high-frequency oscillation signal characteristics in the power line and identifying the abnormal trend of arc discharge is as follows: De-noising and multi-dimensional feature extraction of high-frequency arc signal data of power lines; The multi-dimensional feature extraction of high-frequency arc signal data of power lines includes frequency domain feature extraction, time domain feature extraction and time-frequency feature extraction; The frequency domain feature extraction includes analyzing the frequency components of the high-frequency signal of the power line by fast Fourier transform, and extracting the main frequency components and amplitudes; The time domain feature extraction includes extracting pulse width, pulse interval and amplitude features in the signal; The time-frequency feature extraction includes extracting the dynamic changes of the signal in the time and frequency dimensions through short-time Fourier transform to capture the transient change trend of the arc discharge signal; The extracted multi-dimensional features are matched with the arc discharge abnormal pattern library through the dynamic time warping algorithm to generate the multi-dimensional feature abnormal trend similarity and identify the arc discharge abnormal trend. The specific process of assessing the arc fault risk of current power lines is as follows: According to the similarity of abnormal trends of multi-dimensional features, weights are assigned to abnormal trends of different dimensional features to obtain the arc fault risk index of power lines; The power line monitoring data includes power line high-frequency arc signal data and power line environment data; The power line high-frequency arc signal data includes signal amplitude, signal frequency, pulse width, pulse interval, and signal phase; The power line environment data includes the surrounding air salt concentration and the surrounding air humidity; Based on the power line monitoring data, the specific process of analyzing the impact of salt concentration and humidity in the air on power lines is as follows: According to the power line environment data, the salt concentration of the surrounding air is compared with the set salt concentration risk threshold; and the air salt concentration risk difference is obtained; Compare the ambient air humidity with the set air humidity risk threshold; Obtain air humidity risk difference; According to the risk difference of air salt concentration and air humidity, the influence of air salt concentration and humidity on the corrosion rate of power lines is analyzed; The specific process of assessing the corrosion risk of current power lines is as follows: The air salt concentration risk difference and the air humidity risk difference are respectively comprehensively calculated with the set air salt concentration allowable deviation value and the air humidity allowable deviation value to obtain the power line corrosion risk index.

2. A monitoring and alarm system for power lines according to claim 1, characterized in that: The classification process of classifying the current power lines into abnormal lines and normal lines is as follows: According to the power line arc fault risk index and the power line corrosion risk index, the power line arc fault risk index and the corrosion risk threshold are compared with the set values ​​respectively; When the arc fault risk index and the corrosion risk index of the power line are respectively less than the set arc fault risk index threshold and the corrosion risk threshold, the current power line is classified as a normal line, otherwise it is an abnormal line.

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