Power transmission tower lightning monitoring and early warning system based on multi-source data

Abstract

The invention discloses a power transmission tower lightning monitoring and early warning system based on multi-source data, and relates to the technical field of lightning monitoring and early warning, and the system comprises an acquisition module which is used for responding to a lightning event, and collecting the instantaneous strain and temperature change of a power transmission tower; the stress resolving module is used for performing stress calculation on the instantaneous strain and the temperature change to obtain the stress change of the transmission tower; the weight calculation module is used for calculating the image difference degree between adjacent thunder and lightning events, performing irrelevant thunder and lightning effect removal on the image difference degree to obtain the purified image difference degree, and calculating the influence weight of the thunder and lightning events according to the purified image difference degree and the time decay factors of the thunder and lightning events; and the microscopic damage modeling module is used for constructing a microscopic damage model of the transmission tower based on a Paris rule. According to the invention, quantifiable comprehensive damage indexes can be rapidly output after lightning stroke occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of lightning monitoring and early warning, and in particular to a transmission tower lightning monitoring and early warning system based on multi-source data. Background Art

[0002] In high-voltage transmission networks, towers, the primary support structures for conductors, are constantly exposed to complex electromagnetic environments and extreme meteorological loads. The intense convective activity of thunderstorm clouds can generate high-current, broad-spectrum lightning strikes. Typhoon-associated rainfall, strong winds, and temperature swings can weaken coatings and induce material fatigue over long periods of time. To ensure power supply continuity across interregional power grids, operations and maintenance teams typically deploy strain gauges, temperature sensors, and high-definition cameras at key locations on towers to capture multi-dimensional information such as instantaneous strain histories, temperature steps, and crack propagation.

[0003] In the Chinese invention patent application publication number CN106019287A, a transmission line lightning monitoring and early warning method based on a small radar is disclosed. The radar detects cloud characteristics and electromagnetic field changes to predict lightning, and the early warning logic relies on meteorological thresholds.

[0004] However, combining the above practical application scenarios with the contents of the prior art:

[0005] Existing monitoring solutions typically process sensor load curves or crack images separately, lacking a unified framework to couple instantaneous stress increments, microscopic crack extensions, and meteorological intensity weights to a single damage metric. This makes it difficult to accurately quantify the accumulated weak damage from multiple lightning strikes. Furthermore, traditional assessment methods based on fixed weights or simple thresholds cannot dynamically reflect the actual hazard level after combining the intensity differences of lightning events with the time decay effect, leading to delayed warning signals or misjudgments. Therefore, there is an urgent need to develop a monitoring and early warning technology approach driven by lightning events that integrates instantaneous strain, temperature-coupled stress, real-time crack area, and comprehensive meteorological intensity according to standardized weights. This approach can quickly output a quantifiable comprehensive damage index after a lightning strike occurs, and trigger hierarchical operation and maintenance decisions accordingly. Summary of the Invention

[0006] The purpose of the present invention is to solve the shortcoming in the prior art that it is difficult to quickly output a quantifiable comprehensive damage index after a lightning strike occurs, and to propose a transmission tower lightning monitoring and early warning system based on multi-source data.

[0007] In order to solve the problems existing in the prior art, the present invention adopts the following technical solutions:

[0008] The transmission tower lightning monitoring and early warning system based on multi-source data includes:

[0009] A collection module for collecting instantaneous strain and temperature changes of transmission towers in response to lightning events;

[0010] The stress calculation module is used to calculate the stress of the transmission tower based on the instantaneous strain and temperature change;

[0011] A weight calculation module is used to calculate the image differences between adjacent lightning events, remove irrelevant lightning effects from the image differences, obtain purified image differences, and calculate the impact weight of the lightning event based on the purified image differences and the time attenuation factor of the lightning event;

[0012] Micro-damage modeling module, used to build a micro-damage model of transmission towers based on the Paris law;

[0013] A multi-factor damage assessment module is used to calculate the damage index of transmission towers based on the output of the microscopic damage model, impact weights, and stress changes, combined with the damage equivalence law;

[0014] The early warning decision module is used to generate early warning information of transmission towers based on damage indicators.

[0015] Preferably, collecting the instantaneous strain and temperature change of the transmission tower includes:

[0016] Fix the strain sensor and temperature sensor at the monitoring point of the transmission tower;

[0017] The strain sensor is used to collect instantaneous strain, and the temperature sensor is used to collect temperature changes.

[0018] Preferably, calculating the image difference between adjacent lightning events includes:

[0019] Get the transmission tower The first image data after the lightning event and the transmission tower in the Second image data after the lightning event;

[0020] Calculating a difference value of crack area, a difference value of crack length, and a difference value of crack density between the first image data and the second image data;

[0021] The image difference is calculated based on the difference values ​​of crack area, crack length and crack density.

[0022] Preferably, removing irrelevant lightning effects from the image difference to obtain a purified image difference includes:

[0023] The image differences of the previous N lightning events and their respective time attenuation coefficients are accumulated to obtain the cumulative sum of the differences of the previous N lightning events;

[0024] The image difference at the current moment is subtracted from the accumulated sum of the differences to obtain the purified image difference.

[0025] Preferably, the impact weight of the lightning event is calculated based on the difference of the purified image and the time attenuation factor of the lightning event, including:

[0026] Generate basic weights of lightning events based on meteorological data;

[0027] The basic weight is sequentially added to 1 and the difference of the purified image to obtain the impact increment of the lightning event;

[0028] The impact weight is obtained by calculating the ratio of the impact increment to the time attenuation coefficient of the lightning event.

[0029] Preferably, a microscopic damage model of a transmission tower is constructed based on the Paris law, including:

[0030] The number of lightning events is used as the input variable of Paris’ law;

[0031] The material constants of the transmission tower are used as fixed parameters of the Paris law;

[0032] The crack area of ​​the transmission tower is used as the output variable of the Paris law;

[0033] The micro damage model is determined based on input variables, fixed parameters and output variables.

[0034] Preferably, the damage index of the transmission tower is calculated based on the output of the microscopic damage model, the impact weight and the stress change, combined with the damage equivalence law, including:

[0035] Determine the macro stress effect of the damage equivalence law based on stress changes and the maximum stress of the transmission tower;

[0036] Determine the micro crack effect of the damage equivalence law based on the output of the micro damage model and the initial crack area of ​​the transmission tower;

[0037] Multiply the macro stress effect, micro crack effect and influence weight to get the The amount of damage caused to transmission towers by a single lightning event;

[0038] The damage amount of each lightning event is summed up to obtain the damage index of the transmission tower.

[0039] Preferably, generating early warning information of a transmission tower according to the damage index includes:

[0040] Setting the damage threshold of transmission towers based on expert rules, where the damage threshold includes normal threshold, warning threshold, and danger threshold;

[0041] Compare the damage threshold with the damage index to obtain a specific interval of the damage index within the damage threshold;

[0042] Generate different warning information according to specific intervals.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. In the present invention, through the complete processing flow from data acquisition to damage assessment, the originally scattered instantaneous strain, temperature change, crack image characteristics and meteorological intensity are mapped to the same damage indicator at one time. The acquisition module synchronously obtains strain, temperature and high-definition images under the triggering of lightning strikes; the stress solution module converts instantaneous strain and temperature changes into comparable stress increments; the weight calculation module uses the purified crack difference as a medium to link the image changes of each lightning strike with the meteorological basic weight; the micro-damage modeling module uses the Paris law to track crack accumulation at the material scale; finally, the multi-factor damage assessment module equivalently integrates the macro-stress effect, micro-crack effect and influence weight, and outputs the comprehensive damage index in real time, thereby breaking through the barriers between multi-source data and realizing the quantitative characterization of the weak cumulative damage of multiple lightning strikes.

[0045] 2. In order to break away from the limitations of fixed weights and static thresholds, the present invention uses a weight calculation module to generate basic weights based on meteorological quantities such as lightning current peak value and duration. This is then superimposed with the difference in cracks after purification to form an impact increment. Finally, a correction is made using an attenuation coefficient that decreases over time to obtain an impact weight that changes synchronously with the intensity and duration of the event. Subsequently, the multi-factor damage assessment module accumulates the contributions of each lightning strike according to the weights and compares the resulting comprehensive damage index with the grading threshold set by experts in real time. The early warning decision module then immediately outputs warning information. This amplifies warnings during strong lightning strikes while allowing the impact of older lightning strikes to decay naturally, avoiding false alarms and missed reports, and achieving a dynamic and accurate reflection of the actual hazard level. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0047] Figure 1 This is a functional module diagram of a transmission tower lightning monitoring and early warning system based on multi-source data provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0049] Example: This example provides a transmission tower lightning monitoring and early warning system based on multi-source data, see Figure 1 , specifically, including:

[0050] A collection module for collecting instantaneous strain and temperature changes of transmission towers in response to lightning events;

[0051] In an embodiment of the present invention, collecting instantaneous strain and temperature changes of a transmission tower includes:

[0052] Fix the strain sensor and temperature sensor at the monitoring point of the transmission tower;

[0053] The strain sensor is used to collect instantaneous strain, and the temperature sensor is used to collect temperature changes.

[0054] Specifically, the acquisition module, the functional unit responsible for acquiring basic data, detects lightning events through lightning sensors and other means, triggering the data collection process. The process involves first attaching strain sensors and temperature sensors to monitoring points on transmission towers. The strain sensors then collect instantaneous strain data, reflecting the stress and deformation of the towers, while the temperature sensors collect temperature change data, which affects the mechanical properties of the materials. This collected instantaneous strain and temperature change information provides the basis for subsequent stress calculations, damage assessments, and other processes, supporting the operation of the entire monitoring and early warning system.

[0055] The stress calculation module is used to calculate the stress of the transmission tower based on the instantaneous strain and temperature change;

[0056] Specifically, the stress solution module converts the instantaneous strain and temperature changes collected by sensors into stress changes, and depicts the mechanical response of the tower under lightning impact in real time. It not only unifies the original physical quantities into directly comparable stress scales, but also provides core input for subsequent micro-crack propagation modeling and multi-factor damage assessment. Therefore, it is a key bridge for the transition from field data to structural health indicators, improving the accuracy and timeliness of damage assessment.

[0057] In detail, the calculation formula of stress change is as follows:

[0058] Where, Indicates in After the lightning event, the stress changes of the transmission tower, represents a constant, Indicates in The instantaneous strain of a lightning event, Indicates in Temperature changes of lightning events, represents the sensitivity factor of stress to deformation, An indicator indicating the number of lightning events.

[0059] In detail, and Obtained through experimental calibration: First, in the laboratory, a sample with the same specifications as the tower material is subjected to multiple sets of combined impacts of known instantaneous strain and temperature increments, the corresponding stress changes are measured in real time, and then all the data are brought into the model , using the least squares method to and Do linear regression to get the slope and intercept , and will eventually Take as the stress sensitivity index of the material, Take it as the regression constant.

[0060] In detail, the calculation formula of stress change converts the deformation and temperature fluctuation of the tower into a stress value that reflects the risk of structural damage, through the constant Calibration and sensitivity Amplify and convert the combined effects of strain and temperature into intuitive stress changes; instantaneous strain refers to the deformation of the transmission tower material per unit length at the moment of lightning strike, reflecting the instantaneous deformation degree of the structure. It is a dimensionless ratio that reflects the deformation result; stress change is the change in the internal force per unit area of ​​the material at the moment of lightning strike, which is related to the material's destruction limit and is used to judge the damage risk. It is a pressure unit and reflects the mechanical response.

[0061] A weight calculation module is used to calculate the image differences between adjacent lightning events, remove irrelevant lightning effects from the image differences, obtain purified image differences, and calculate the impact weight of the lightning event based on the purified image differences and the time attenuation factor of the lightning event;

[0062] Generally speaking, in the lightning monitoring of transmission towers, image difference reflects the state changes of the towers after multiple lightning events. However, the original image difference will be affected by the weak cumulative influence of the previous lightning events. Removing irrelevant lightning effects from the image difference can eliminate environmental interference factors, separate the structural change information truly caused by the current lightning event, and more accurately quantify the true impact of each lightning event on the tower state. This makes the subsequent lightning event impact weight calculated based on the purified image difference more in line with the actual situation, ensuring that the data basis is more reliable and the evaluation results are more accurate when comprehensively evaluating the tower damage indicators, effectively improving the scientificity and practicality of the transmission tower lightning monitoring and early warning system.

[0063] In detail, the impact weight of the lightning event is calculated based on the difference of the purified image and the time attenuation factor of the lightning event. The basic weight generated by the meteorological data can be combined to reflect the actual damage degree of the current lightning event after eliminating the historical residual influence through the difference of the purified image. At the same time, the characteristic that the impact decreases over time is incorporated and reflected through the time attenuation factor. The impact degree of a single lightning event on the transmission tower in the dimension of actual damage time attenuation of meteorological intensity is dynamically quantified, providing a weight basis that fits the actual hazard level for subsequent multi-factor damage assessment, so that the assessment results can more accurately reflect the cumulative effect of multiple lightning strikes and avoid false alarms and omissions.

[0064] In an embodiment of the present invention, calculating the image difference between adjacent lightning events includes:

[0065] Get the transmission tower The first image data after the lightning event and the transmission tower in the Second image data after the lightning event;

[0066] In detail, in order to obtain the transmission tower The first image data after the lightning event and the The second image data after the first lightning event requires the deployment of image acquisition equipment at key monitoring locations on transmission towers in advance, and the setting of trigger mechanisms associated with lightning events for the equipment. After the lightning event ends, the corresponding image acquisition device is triggered to shoot the transmission tower and obtain an image covering the appearance of the tower structure and store it as the first image data; After the lightning event ends, the device is triggered again to perform the shooting operation, collect images of the same monitoring location, and obtain the second image data. In this way, the orderly acquisition of tower image data after different lightning events is achieved, providing basic material for the subsequent calculation of image difference.

[0067] Calculating a difference value of crack area, a difference value of crack length, and a difference value of crack density between the first image data and the second image data;

[0068] Specifically, the difference in crack area refers to extracting the area of ​​cracks on the transmission tower in the first and second images respectively, treating the cracks as irregular areas, calculating their proportion, converting them into actual areas, and then taking the absolute value of the difference between the two to reflect the increase or decrease in crack area after the two lightning events; the difference in crack length refers to obtaining the length of the longest extension direction of the crack in each image, calculating the absolute value of the difference, and reflecting the change in crack length; the difference in crack density refers to first calculating the number of cracks and length per unit area in each image, which are comprehensive indicators that represent the density of cracks, and then calculating the absolute value of the difference between the two to measure the change in crack distribution density. These difference values ​​quantify the changes in the crack status of the tower after the two lightning events from different dimensions.

[0069] The image difference is calculated based on the difference values ​​of the crack area, the crack length, and the crack density. The calculation formula of the image difference is as follows:

[0070] Where, Indicates the image difference, Indicates that the transmission tower is The crack area after the lightning event, Indicates that the transmission tower is The crack area after the lightning event, Indicates that the transmission tower is Crack length after the lightning event, Indicates that the transmission tower is Crack length after the lightning event, Indicates that the transmission tower is Crack density after a lightning event, Indicates that the transmission tower is Crack density after a lightning event, represents the difference in crack area, represents the difference in crack length, represents the difference in crack density, An indicator indicating the number of lightning events.

[0071] In detail, when calculating the image difference, the formula first takes the absolute value and calculates the Second and The absolute changes in the crack area, length, and density of the transmission tower after the lightning event are summed up and used as the numerator to reflect the absolute degree of change in the crack index; the crack area, length, and density corresponding to the two lightning events are then added up and summed up respectively, and used as the denominator for normalization to eliminate the influence of the index value. The final result is , which can comprehensively quantify the impact of adjacent lightning events on tower crack damage.

[0072] In an embodiment of the present invention, removing irrelevant lightning effects from the image difference to obtain a purified image difference includes:

[0073] The image differences of the previous N lightning events and their respective time attenuation coefficients are accumulated to obtain the cumulative sum of the differences of the previous N lightning events;

[0074] The image difference at the current moment is subtracted from the accumulated sum of the differences to obtain the purified image difference. The calculation formula for the purified image difference is as follows:

[0075] Where, Represents the difference of the image after purification, Indicates the image difference at the current moment, Indicates the image difference, Indicates the The time decay coefficient of a lightning event, represents the total number of lightning events, An indicator indicating the number of lightning events.

[0076] In detail, This means that the impact of each lightning event on the tower will gradually decay over time. For example, the crack expansion caused by the first lightning will contribute less to the current image difference three months later due to material relaxation and environmental adaptation. The residual effects of these historical lightning events are irrelevant lightning effects that need to be removed. The longer the time, The smaller it is, the more the impact is attenuated; It means that the residual effects of the previous N lightning events are accumulated to obtain the total interference of historical lightning at the current moment; due to the image difference at the current moment It consists of two parts: the real impact of the current lightning event and the residual impact of historical lightning events. Therefore, the purified image difference can be obtained by subtracting the total historical residual from the current image difference.

[0077] In detail, the time decay coefficient Usually takes the form of exponential decay First, statistically analyze the experimental data of actual crack or stress attenuation over time after multiple lightning strikes in the past, and use the least squares method to fit the optimal attenuation constant. , and then calculate the time difference between any historical lightning event and the current moment Substitute to get the corresponding , and in all Normalize again to ensure that the weights and values ​​meet the model requirements.

[0078] In an embodiment of the present invention, the impact weight of the lightning event is calculated based on the difference of the purified image and the time attenuation factor of the lightning event, including:

[0079] Generate basic weights of lightning events based on meteorological data;

[0080] Specifically, key meteorological quantities during each lightning occurrence, such as lightning current peak, echo top height or radar reflectivity, ground-to-ground flash density, and duration, are first normalized according to their respective historical extreme values. Weight coefficients relevant to physical meanings are then assigned, and linear superposition is performed to obtain the comprehensive intensity index S. Finally, S is remapped to the range of 0-1 as the basic weight. The closer the value is to 1, the stronger the lightning is at the meteorological level and the greater the potential damage to transmission towers.

[0081] The basic weight is sequentially added to 1 and the difference of the purified image to obtain the impact increment of the lightning event;

[0082] The impact weight is calculated by calculating the ratio of the impact increment to the time attenuation coefficient of the lightning event. The calculation formula of the impact weight is as follows:

[0083] Where, Indicates the The impact weight of the lightning event, represents the initial weight, Represents the difference of the image after purification, Indicates the Time decay coefficient of a lightning event.

[0084] Specifically, the basic weight is first generated by normalizing key quantities such as the peak lightning current in the meteorological data and then weighted superposition, reflecting the potential damage of the lightning's own meteorological intensity to the tower. The image difference after purification is then combined to remove irrelevant effects, and the image difference is added to the basic weight and 1 to obtain the impact increment, which is then integrated into the actual damage performance. Finally, it is divided by the time attenuation coefficient to consider the attenuation characteristics of the lightning impact over time. Through the calculation of (basic weight + damage-related increment) ÷ time attenuation, the impact of a single lightning event on the transmission tower is comprehensively quantified under the dimensions of meteorological intensity, actual damage, and time attenuation, thereby reasonably obtaining the impact weight.

[0085] Micro-damage modeling module, used to build a micro-damage model of transmission towers based on the Paris law;

[0086] Specifically, the Paris law excels at describing the subcritical crack expansion process under cyclic loads. When transmission towers are struck by lightning, cyclic stress changes can easily trigger crack initiation and expansion. This law can accurately characterize the quantitative relationship between stress and crack expansion. At the same time, it is based on fracture mechanics and adapts to the damage evolution law of tower metal materials. From the perspective of microscopic crack expansion and combined with the stress changes caused by lightning, it can quantitatively evaluate the cumulative damage of the tower, providing a reliable model support for subsequent damage index calculations and early warnings, which meets the needs of "microscopic damage quantitative analysis" in lightning damage monitoring of transmission towers.

[0087] In an embodiment of the present invention, a microscopic damage model of a transmission tower is constructed based on the Paris law, including:

[0088] The number of lightning events is used as the input variable of the Paris law, that is, the number of discrete lightning events is regarded as the number of loading cycles of the Paris equation;

[0089] The material constants of the transmission tower are used as fixed parameters of the Paris law;

[0090] The crack area of ​​the transmission tower is used as the output variable of the Paris law;

[0091] The micro damage model is determined based on the input variables, fixed parameters and output variables, where the micro damage model is as follows:

[0092] Where, The crack area increases with the The expansion rate of lightning events, The material crack growth base value representing the material constant, represents the stress intensity factor range, The stress sensitivity index of the material constant reflects the sensitivity of the material crack growth rate to the change of the stress intensity factor range. The bigger, A small change in the crack growth rate will cause a significant change. Indicates the After the lightning event, the crack area of ​​the transmission tower was An indicator indicating the number of lightning events.

[0093] In detail, the material crack extension base value It is an inherent property of the material, reflecting the inherent rate constant of crack growth when there is no obvious stress concentration or the stress intensity factor range is extremely small. It is determined by the material composition and microstructure, and reflects the material's natural ability to resist crack growth. The larger the material, the more brittle it is; stress sensitivity index Describes the sensitivity of the crack growth rate to changes in the stress intensity factor range, The larger the stress is, the more dramatic the change in crack growth rate will be. The two together quantify the impact of the inherent properties of the material on lightning damage, making the model fit the actual engineering.

[0094] A multi-factor damage assessment module is used to calculate the damage index of transmission towers based on the output of the microscopic damage model, impact weights, and stress changes, combined with the damage equivalence law;

[0095] In detail, by calculating the damage index of the transmission tower, it is possible to integrate the overall stress damage threat reflected by the comparison between the stress change at the macro level and the maximum stress of the tower, the crack extension contribution reflected by the output of the micro damage model and the initial crack area at the micro level, and the actual hazard differences of different lightning events represented by the impact weights and the time attenuation effect in multiple dimensions. Through multiplication and cumulative summation, the complex damage factors are converted into a single quantifiable indicator, which can comprehensively and accurately evaluate the cumulative damage degree of multiple lightning strikes to the transmission tower, provide a scientific quantitative basis for early warning decision-making, and realize dynamic and comprehensive judgment of the damage status of the tower.

[0096] In an embodiment of the present invention, based on the output of the microscopic damage model, the impact weight and the stress change, and in combination with the damage equivalence law, the damage index of the transmission tower is calculated, including:

[0097] The macro-stress effect of the damage equivalence law is determined based on stress changes and the maximum stress of the transmission tower. The macro-stress effect is an indicator that measures the degree of damage threat posed by actual stress to the tower based on the stress changes caused by lightning and compared with the maximum stress of the tower. It reflects the damage impact at the overall stress level.

[0098] The micro-crack effect of the damage equivalence law is determined based on the output of the micro-damage model and the initial crack area of ​​the transmission tower. The micro-crack effect focuses on the microscopic perspective of the material. Based on the output of the micro-damage model and the initial crack area of ​​the tower, it measures the contribution of micro-crack development to tower damage under lightning, reflecting the damage impact of cracks at the micro level.

[0099] Multiply the macro stress effect, micro crack effect and influence weight to get the The amount of damage caused to transmission towers by a single lightning event;

[0100] The damage amount of each lightning event is summed up to obtain the damage index of the transmission tower.

[0101] In detail, the damage equivalence law is as follows:

[0102] Where, It represents the damage index of N lightning events to the transmission tower. Indicates the The impact weight of the lightning event, Indicates in After the lightning event, the stress changes of the transmission tower, Indicates the maximum stress that the tower can withstand. Indicates the After the lightning event, the crack area of ​​the transmission tower was represents the initial crack area, represents the stress sensitivity factor, represents the crack sensitivity factor.

[0103] Specifically, lightning damage to towers is the result of the combined effects of macroscopic stress impact and microscopic crack expansion, with different lightning events having varying degrees of impact. By multiplying and accumulating the macroscopic stress effect, microscopic crack effect, and impact weights, the complex damage factors are transformed into a single, quantifiable indicator, following a multi-dimensional damage coupling logic: First, from both the macroscopic and microscopic levels, the macroscopic aspect measures the overall stress damage threat based on stress changes and the tower's maximum bearing stress. The microscopic aspect measures the microscopic crack damage contribution based on the microscopic damage model output and the initial crack area. The corresponding effect is determined in conjunction with the damage equivalence law, and then a weight reflecting the degree of lightning impact is incorporated. The single lightning damage amount is obtained through multiplication, and finally, the damage amounts from multiple lightning events are summed. Complex factors such as macroscopic stress impact, microscopic crack expansion, and differences in lightning impact are transformed into a single, quantifiable damage indicator, comprehensively reflecting the cumulative damage to towers caused by lightning.

[0104] In detail, the stress sensitivity factor and crack sensitivity factor All of them are obtained through material fatigue testing and field verification double calibration: first, multi-level cyclic loads are applied to the specimens made of the same material as the tower in the laboratory, and the stress amplitude-crack area-life curve is recorded. The initial value is obtained by using the least squares regression fitting model; then the simulation output is compared with the actual inspection damage data after lightning strikes in previous years, and fine-tuning is performed according to the principle of minimum error to determine the appropriate value for the target tower type. 、 .

[0105] The early warning decision module is used to generate early warning information of transmission towers based on damage indicators.

[0106] In an embodiment of the present invention, generating early warning information of a transmission tower according to damage indicators includes:

[0107] Setting the damage threshold of transmission towers based on expert rules, where the damage threshold includes normal threshold, warning threshold, and danger threshold;

[0108] In detail, when setting damage thresholds based on expert rules, experts in the power transmission field are first gathered. Combined with tower design standards, material properties, operating environment, etc., historical damage data and failure cases are referred to analyze the characteristics of different damage development stages. The indicator range for long-term stable operation and no obvious damage accumulation is determined as normal, the damage is developing but not endangering safety for the time being, and the threshold range for warning and danger is determined. After multiple rounds of discussion, verification and revision, a damage threshold system suitable for transmission towers is formed.

[0109] Compare the damage threshold with the damage index to obtain a specific interval of the damage index within the damage threshold;

[0110] Specifically, the calculated damage index is compared with the damage threshold to determine the specific preset range within which the damage index falls. This helps clarify the risk level of the tower damage. For example, if the normal threshold is set to [0, 20], the warning threshold is set to (20, 50], and the danger threshold is set to (50, +∞), if the calculated damage index is 35, the comparison shows that it falls within the range corresponding to the warning threshold, indicating that the tower damage has reached a warning level that requires attention.

[0111] Generate different warning information according to specific intervals.

[0112] Specifically, once the damage index is compared and determined to belong to a specific range, the system automatically matches and outputs the warning content corresponding to that range, visually prompting operators and maintenance personnel on the tower's risk status and response strategies. For example, the normal range [0, 20] is set to correspond to "Normal status, no action required," the warning range (20, 50) corresponds to "Attention: Damage index is high, inspection recommended within 7 days," and the dangerous range (50, +∞) corresponds to "Emergency: Damage exceeds the standard, immediate shutdown and maintenance." If a tower's damage index is 45, a warning message is generated: "Attention: Damage index 45, entering the warning range, inspection recommended within 7 days," achieving automated conversion from risk level to specific response instructions.

[0113] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A transmission tower lightning monitoring and early warning system based on multi-source data, characterized by: include: A collection module for collecting instantaneous strain and temperature changes of transmission towers in response to lightning events; The stress calculation module is used to calculate the stress of the transmission tower based on the instantaneous strain and temperature change; A weight calculation module is used to calculate the image differences between adjacent lightning events, remove irrelevant lightning effects from the image differences, obtain purified image differences, and calculate the impact weight of the lightning event based on the purified image differences and the time attenuation factor of the lightning event; Micro-damage modeling module, used to build a micro-damage model of transmission towers based on the Paris law; A multi-factor damage assessment module is used to calculate the damage index of transmission towers based on the output of the microscopic damage model, impact weights, and stress changes, combined with the damage equivalence law; The early warning decision module is used to generate early warning information of transmission towers based on damage indicators.

2. The transmission tower lightning monitoring and early warning system based on multi-source data according to claim 1 is characterized in that: Collect instantaneous strain and temperature changes of transmission towers, including: Fix the strain sensor and temperature sensor at the monitoring point of the transmission tower; The strain sensor is used to collect instantaneous strain, and the temperature sensor is used to collect temperature changes.

3. The transmission tower lightning monitoring and early warning system based on multi-source data according to claim 1 is characterized in that: Calculate the image difference between adjacent lightning events, including: Get the transmission tower The first image data after the lightning event and the transmission tower in the Second image data after the lightning event; Calculating a difference value of crack area, a difference value of crack length, and a difference value of crack density between the first image data and the second image data; The image difference is calculated based on the difference values ​​of crack area, crack length and crack density.

4. The transmission tower lightning monitoring and early warning system based on multi-source data according to claim 1 is characterized in that: The image difference is subjected to irrelevant lightning effects removal to obtain the purified image difference, including: The image differences of the previous N lightning events and their respective time attenuation coefficients are accumulated to obtain the cumulative sum of the differences of the previous N lightning events; The image difference at the current moment is subtracted from the accumulated sum of the differences to obtain the purified image difference.

5. The transmission tower lightning monitoring and early warning system based on multi-source data according to claim 1 is characterized in that: The impact weight of the lightning event is calculated based on the difference of the purified image and the time attenuation factor of the lightning event, including: Generate basic weights of lightning events based on meteorological data; The basic weight is sequentially added to 1 and the difference of the purified image to obtain the impact increment of the lightning event; The impact weight is obtained by calculating the ratio of the impact increment to the time attenuation coefficient of the lightning event.

6. The transmission tower lightning monitoring and early warning system based on multi-source data according to claim 1 is characterized in that: The microscopic damage model of transmission towers is constructed based on the Paris law, including: The number of lightning events is used as the input variable of Paris’ law; The material constants of the transmission tower are used as fixed parameters of the Paris law; The crack area of ​​the transmission tower is used as the output variable of the Paris law; The micro damage model is determined based on input variables, fixed parameters and output variables.

7. The transmission tower lightning monitoring and early warning system based on multi-source data according to claim 1 is characterized in that: Based on the output of the microscopic damage model, the impact weight and stress change, and in combination with the damage equivalence law, the damage index of the transmission tower is calculated, including: Determine the macro stress effect of the damage equivalence law based on stress changes and the maximum stress of the transmission tower; Determine the micro crack effect of the damage equivalence law based on the output of the micro damage model and the initial crack area of ​​the transmission tower; Multiply the macro stress effect, micro crack effect and influence weight to get the The amount of damage caused to transmission towers by a single lightning event; The damage amount of each lightning event is summed up to obtain the damage index of the transmission tower.

8. The transmission tower lightning monitoring and early warning system based on multi-source data according to claim 1 is characterized in that: Generate early warning information for transmission towers based on damage indicators, including: Setting the damage threshold of transmission towers based on expert rules, where the damage threshold includes normal threshold, warning threshold, and danger threshold; Compare the damage threshold with the damage index to obtain a specific interval of the damage index within the damage threshold; Generate different warning information according to specific intervals.

Images