Substation enclosing wall safety risk monitoring and early warning system and method

Abstract

The invention discloses a transformer substation enclosure safety risk monitoring and early warning system and method, and relates to the technical field of enclosure monitoring, and the method comprises the steps: obtaining the abnormal condition of each sub-region, analyzing the overall abnormal state of an enclosure through combining the abnormal conditions of all sub-regions, and dividing the enclosure into no risk, first-level risk and second-level risk based on an analysis result. And when the enclosing wall is divided into first-level risks, carrying out association processing on environmental factors and construction operation factors of the enclosing wall, generating an influence coefficient for the enclosing wall, combining an overall abnormal state of the first-level risk enclosing wall with the influence coefficient, predicting a future development trend of the enclosing wall state, and generating a corresponding management strategy for the enclosing wall according to a prediction result. The early warning system can comprehensively consider the environment and construction operation factors in the transformer substation and predict the development trend of the enclosing wall state when monitoring that the enclosing wall state changes slightly, so that management can be carried out in advance, and the safety and stability of the enclosing wall are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of fence monitoring, and particularly to a safety risk monitoring and early warning system and method for a substation fence. Background Art

[0002] An early warning system is a key technical means for ensuring the safe operation of a substation. As the core link in the power grid system, the substation shoulders the important tasks of power conversion and distribution. The fence is the first physical barrier of the substation, which plays a role in blocking external intrusion, preventing illegal entry, and protecting the equipment and personnel inside the station. However, the substation fence faces various security threats, such as external force damage, geological disaster attacks (such as floods, landslides, etc.), environmental changes (such as corrosion, aging), and the risk of human intrusion.

[0003] The existing technologies have the following deficiencies:

[0004] The existing early warning systems usually set sensing devices near the substation fence to monitor the status of the fence in real time (such as settlement, inclination, etc.). When the monitored fence status changes (that is, the settlement exceeds the settlement threshold or the inclination exceeds the inclination threshold), the early warning system issues an early warning signal. However, in actual applications, when the fence status changes slightly (that is, the settlement does not exceed the settlement threshold or the inclination does not exceed the inclination threshold, but the settlement is close to the settlement threshold or the inclination is close to the inclination threshold), the environment and construction operations in the substation may exacerbate the change range of the fence status in the short term. The early warning system does not comprehensively consider such problems, which may increase the security risk of the fence and cannot guarantee the safety and stability of the fence. Summary of the Invention

[0005] The purpose of the present invention is to provide a safety risk monitoring and early warning system and method for a substation fence, which can comprehensively consider the environmental and construction operation factors in the substation when the monitored fence status changes slightly, predict the development trend of the fence status, so as to facilitate early management and ensure the safety and stability of the fence.

[0006] To achieve the above purpose, the present invention provides the following technical solution: A safety risk monitoring and early warning method for a substation fence, the early warning method comprising the following steps:

[0007] The early warning system obtains the information of the monitored fence in the substation, divides the fence into multiple monitoring sub - regions, monitors the status data of each sub - region through sensing devices, obtains the abnormal conditions of each sub - region, and analyzes the overall abnormal status of the fence by combining the abnormal conditions of all sub - regions;

[0008] Based on the analysis results, the fence is divided into risk - free, first - level risk, and second - level risk, and the fences with second - level risk are included in the management area;

[0009] When the perimeter wall is classified as a first-level risk, the environmental factors and construction operation factors of the perimeter wall are correlated to generate an influence coefficient for the perimeter wall. The overall abnormal state of the first-level risk perimeter wall is combined with the influence coefficient to predict the future development trend of the perimeter wall state, and corresponding management strategies are generated for the perimeter wall based on the prediction results.

[0010] Preferably, after monitoring the status data of each sub-region through a sensing device, the abnormal conditions of each sub-region are obtained, including the following steps:

[0011] Monitor the status data of each sub-region through a sensing device, and the status data includes settlement value, inclination angle, and crack variation index;

[0012] Normalize the settlement value, inclination angle, and crack variation index so that the value ranges of the settlement value, inclination angle, and crack variation index are mapped to between [0, 1], obtain the normalized settlement value, normalized inclination angle, and normalized crack variation index, and sum the normalized settlement value, normalized inclination angle, and normalized crack variation index to obtain the abnormal factor of the sub-region.

[0013] Preferably, analyze the overall abnormal state of the perimeter wall by combining the abnormal conditions of all sub-regions, including the following steps:

[0014] Obtain the midpoint of the perimeter wall by dividing the perimeter wall length by 2, and calculate the midpoint of each sub-region. The expression is: In the formula, x i is the midpoint of the i-th sub-region, L is the perimeter wall length, and n is the number of sub-region divisions;

[0015] Calculate the distance from the midpoint of the i-th sub-region to the midpoint of the perimeter wall. The expression is: d i =|x i -C|. In the formula, d i is the distance from the midpoint of the i-th sub-region to the midpoint of the perimeter wall, x i is the midpoint of the i-th sub-region, and C is the midpoint of the perimeter wall;

[0016] After obtaining the distances from the midpoints of all sub-regions to the midpoint of the perimeter wall, sum the distances from the midpoints of all sub-regions to the midpoint of the perimeter wall to obtain the total distance. Obtain the influence value of the sub-region by dividing the distance from the midpoint of the sub-region to the midpoint of the perimeter wall by the total distance. Add 1 to the influence value of each sub-region to obtain the correction value, and use the reciprocal of the correction value as the weight of the sub-region;

[0017] Analyze the combination of all sub-regions of the perimeter wall to obtain the overall abnormal coefficient of the perimeter wall. The expression is: In the formula, wq z is the overall abnormal coefficient, g i is the weight of the i-th sub-region, yc iis the abnormal factor of the i-th sub-region.

[0018] Preferably, based on the analysis results, the enclosure is divided into risk-free, first-level risk, and second-level risk, including the following steps:

[0019] After obtaining the overall abnormal coefficient of the enclosure, compare the overall abnormal coefficient with a preset first coefficient threshold and a second coefficient threshold. The first coefficient threshold is used to determine whether there is a safety risk for the enclosure, and the second coefficient threshold is used to determine the severity of the enclosure risk;

[0020] If the overall abnormal coefficient is less than or equal to the first coefficient threshold, it is determined that there is no safety risk for the enclosure, and the enclosure is divided into risk-free;

[0021] If the overall abnormal coefficient is greater than the first coefficient threshold and less than or equal to the first coefficient threshold, it is determined that there is a minor risk for the enclosure, and the enclosure is divided into first-level risk;

[0022] If the overall abnormal coefficient is greater than the second coefficient threshold, it is determined that there is a serious risk for the enclosure, and the enclosure is divided into second-level risk.

[0023] Preferably, when the enclosure is divided into first-level risk, the environmental factors and construction operation factors of the enclosure are correlated to generate an influence coefficient for the enclosure, including the following steps:

[0024] When the enclosure is divided into first-level risk, obtain the environmental data near the enclosure. The environmental data includes ground vibration, wind speed, and rainfall. Obtain the construction operation data near the enclosure. The construction operation data includes the underground water level volatility caused by construction and the distance between the excavation foundation pit and the enclosure;

[0025] Substitute the ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavation foundation pit and the enclosure into the linear regression analysis model to calculate and obtain the influence coefficient. The expression is:

[0026] In the formula, YX s is the influence coefficient, {y1, y2, y3, y4, y5} are the ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavation foundation pit and the enclosure respectively, {w1, w2, w3, w4, w5} are the regression coefficients of the ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavation foundation pit and the enclosure respectively, and the regression coefficients are all greater than 0.

[0027] Preferably, combine the overall abnormal state of the first-level risk enclosure with the influence coefficient to predict the future development trend of the enclosure state, and generate corresponding management strategies for the enclosure according to the prediction results, including the following steps:

[0028] Obtain the influence coefficient and the overall anomaly coefficient of the first-level risk enclosure, comprehensively calculate the influence coefficient and the overall anomaly coefficient, and obtain the development status index of the first-level risk enclosure;

[0029] Compare the obtained development status index with a preset anomaly threshold. The anomaly threshold is used to predict the future development trend of the enclosure status. If the development status index is less than or equal to the anomaly threshold, it is predicted that the future of the enclosure status will develop towards abnormal improvement. If the development status index is greater than the anomaly threshold, it is predicted that the future of the enclosure status will develop towards abnormal deterioration.

[0030] Preferably, comprehensively calculate the influence coefficient and the overall anomaly coefficient to obtain the development status index of the first-level risk enclosure. The expression is:

[0031] fz s =α*wq z +β*YX s , where wq z is the overall anomaly coefficient, YX s is the influence coefficient, fz s is the development status index, α and β are the adjustment factors of the overall anomaly coefficient and the influence coefficient respectively, and both α and β are greater than 0.

[0032] The substation enclosure safety risk monitoring and early warning system includes an abnormal state analysis module, a classification module, and a prediction module;

[0033] Abnormal state analysis module: Obtain the information of the enclosures monitored in the substation, divide the enclosures into multiple monitoring sub-areas, monitor the status data of each sub-area through sensing devices, obtain the abnormal conditions of each sub-area, and analyze the overall abnormal state of the enclosures by combining the abnormal conditions of all sub-areas;

[0034] Classification module: Based on the analysis results, divide the enclosures into risk-free, first-level risk, and second-level risk, and classify the enclosures with second-level risk into the management area;

[0035] Prediction module: When the enclosure is classified as first-level risk, correlate the environmental factors and construction operation factors of the enclosure to generate an influence coefficient for the enclosure, combine the overall abnormal state of the first-level risk enclosure with the influence coefficient, predict the future development trend of the enclosure status, and generate corresponding management strategies for the enclosure according to the prediction results.

[0036] In the above technical solution, the technical effects and advantages provided by the present invention:

[0037] The present invention obtains the abnormal conditions of each sub-region, analyzes the overall abnormal state of the enclosure wall by combining the abnormal conditions of all sub-regions, divides the enclosure wall into risk-free, first-level risk, and second-level risk based on the analysis results. When the enclosure wall is divided into first-level risk, the environmental factors and construction operation factors of the enclosure wall are associated and processed to generate an influence coefficient for the enclosure wall. The overall abnormal state of the first-level risk enclosure wall is combined with the influence coefficient to predict the future development trend of the enclosure wall state, and corresponding management strategies are generated for the enclosure wall according to the prediction results. The early warning system can comprehensively consider the environment and construction operation factors in the substation when monitoring small changes in the enclosure wall state, predict the development trend of the enclosure wall state, so as to facilitate early management and ensure the safety and stability of the enclosure wall. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings.

[0039] Figure 1 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0041] Embodiment 1: Please refer to Figure 1 As shown, for the method for monitoring and early warning of the safety risk of the substation enclosure wall in this embodiment, the early warning method includes the following steps:

[0042] The early warning system obtains the information of the monitored enclosure wall in the substation, divides the enclosure wall into multiple monitoring sub-regions, monitors the state data of each sub-region through sensing devices, obtains the abnormal conditions of each sub-region, analyzes the overall abnormal state of the enclosure wall by combining the abnormal conditions of all sub-regions, divides the enclosure wall into risk-free, first-level risk, and second-level risk based on the analysis results, classifies the second-level risk enclosure wall into the management area. When the enclosure wall is divided into first-level risk, the environmental factors and construction operation factors of the enclosure wall are associated and processed to generate an influence coefficient for the enclosure wall. The overall abnormal state of the first-level risk enclosure wall is combined with the influence coefficient to predict the future development trend of the enclosure wall state, and corresponding management strategies are generated for the enclosure wall according to the prediction results.

[0043] In this application, by obtaining the abnormal conditions of each sub-region and combining the abnormal conditions of all sub-regions to analyze the overall abnormal state of the fence, the fence is divided into risk-free, first-level risk, and second-level risk based on the analysis results. When the fence is divided into the first-level risk, the environmental factors and construction operation factors of the fence are associated and processed to generate an influence coefficient for the fence. The overall abnormal state of the first-level risk fence is combined with the influence coefficient to predict the future development trend of the fence state, and corresponding management strategies are generated for the fence according to the prediction results. The early warning system can comprehensively consider the environment and construction operation factors in the substation when monitoring small changes in the fence state, predict the development trend of the fence state, so as to facilitate early management and ensure the safety and stability of the fence.

[0044] Embodiment 2: The early warning system obtains the information of the monitored fence in the substation and divides the fence into multiple monitoring sub-regions, including the following steps:

[0045] The system first obtains the basic information of the fence, including the total length, structural type, material, surrounding environment, etc. of the fence. This information provides a data basis for the division and monitoring of the fence, so as to optimize the division of sub-regions and the layout of sensors.

[0046] According to the total length of the fence and the required monitoring accuracy, calculate the number of sub-regions to be divided. Usually, an equal division strategy is adopted to divide the sub-regions, that is, the sub-regions are evenly divided according to the length of the fence, and the length of each sub-region is equal. When the fence length is large, more sub-regions are divided to ensure the comprehensiveness and meticulousness of monitoring.

[0047] Determine the starting point and ending point of each sub-region according to the equal division strategy to ensure that the boundaries of each region are clear. For example, if the total length of the fence is L meters and it is planned to be divided into n sub-regions, the length of each sub-region is L / n meters. Mark the start and end positions of each sub-region section by section for the subsequent installation of monitoring equipment and data management.

[0048] Number each of the divided sub-regions, for example, from No. 1 to No. n. The numbering facilitates subsequent data management, positioning of abnormal regions, and recording of early warning information. The system marks the range and number of each sub-region on a map or 3D model to make it clear at a glance.

[0049] According to the division results of the sub-regions, configure corresponding monitoring equipment (such as vibration sensors, displacement sensors, etc.) in each region. The sensors should be installed to cover the key parts of each sub-region to ensure the detection of state changes such as settlement, inclination, and vibration. For key regions or longer fence sections, the density of monitoring equipment can be appropriately increased to improve the sensitivity of monitoring.

[0050] After installing sensors in each sub-region, a data acquisition and transmission network is established. Connect the data acquisition system of each sub-region to the central control system to achieve real-time data transmission and unified management. The system can manage the data of each sub-region in partitions and summarize the monitoring data of each sub-region into the early warning system.

[0051] After monitoring the status data of each sub-region through the sensing device, obtain the abnormal conditions of each sub-region, including the following steps:

[0052] Monitor the status data of each sub-region through the sensing device, and the status data includes settlement value, tilt angle, and crack variation index;

[0053] The acquisition logic of the crack variation index is: obtain the number of cracks monitored in the sub-region through the camera device, and obtain the length of each crack. Calculate the average crack length and crack standard deviation based on the length of each crack, and obtain the crack variation index by dividing the average crack length by the crack standard deviation. The larger the crack variation index, the more serious the overall crack abnormal condition of the sub-region;

[0054] Normalize the settlement value, tilt angle, and crack variation index so that the value ranges of the settlement value, tilt angle, and crack variation index are mapped to between [0, 1], obtain the normalized settlement value, normalized tilt angle, and normalized crack variation index, and sum the normalized settlement value, normalized tilt angle, and normalized crack variation index to obtain the abnormal factor of the sub-region.

[0055] Analyze the overall abnormal state of the fence in combination with the abnormal conditions of all sub-regions, including the following steps:

[0056] Obtain the midpoint of the fence by dividing the fence length by 2, and calculate the midpoint of each sub-region. The expression is: In the formula, x i is the midpoint of the i-th sub-region, L is the fence length, and n is the number of sub-region divisions;

[0057] Calculate the distance from the midpoint of the i-th sub-region to the midpoint of the fence. The expression is: d i =|x i -C|. In the formula, d i is the distance from the midpoint of the i-th sub-region to the midpoint of the fence, x i is the midpoint of the i-th sub-region, and C is the midpoint of the fence;

[0058] After obtaining the distances from the midpoints of all sub-regions to the midpoint of the enclosure wall, sum up the distances from the midpoints of all sub-regions to the midpoint of the enclosure wall to obtain the total distance. Obtain the influence value of each sub-region by dividing the distance from the midpoint of the sub-region to the midpoint of the enclosure wall by the total distance. Add 1 to the influence value of each sub-region to obtain the correction value (if the center of the sub-region coincides with the center of the enclosure wall, it will cause the distance to be 0). Use the reciprocal of the correction value as the weight of the sub-region (add 1 to the influence value of each sub-region to obtain the correction value, so that when the distance is 0, the denominator is not 0);

[0059] The larger the abnormal factor value of the sub-region, the more serious the abnormality of the sub-region. Combine and analyze all sub-regions of the enclosure wall to obtain the overall abnormal coefficient of the enclosure wall. The expression is as follows: In the formula, wq z is the overall abnormal coefficient, g i is the weight of the i-th sub-region, yc i is the abnormal factor of the i-th sub-region. The larger the overall abnormal coefficient, the more serious the overall abnormal condition of the enclosure wall.

[0060] Based on the analysis results, divide the enclosure wall into risk-free, first-level risk, and second-level risk. Incorporate the enclosure walls with second-level risk into the management area, including the following steps:

[0061] After obtaining the overall abnormal coefficient of the enclosure wall, compare the overall abnormal coefficient with the preset first coefficient threshold and second coefficient threshold. The first coefficient threshold is used to determine whether there is a safety risk for the enclosure wall, and the second coefficient threshold is used to determine the severity of the enclosure wall risk;

[0062] If the overall abnormal coefficient is less than or equal to the first coefficient threshold, it is determined that there is no safety risk for the enclosure wall, and the enclosure wall is classified as risk-free;

[0063] If the overall abnormal coefficient is greater than the first coefficient threshold and less than or equal to the first coefficient threshold, it is determined that there is a minor risk for the enclosure wall, and the enclosure wall is classified as first-level risk;

[0064] If the overall abnormal coefficient is greater than the second coefficient threshold, it is determined that there is a serious risk for the enclosure wall, and the enclosure wall is classified as second-level risk.

[0065] When the enclosure wall is classified as first-level risk, perform an association process on the environmental factors and construction operation factors of the enclosure wall to generate an influence coefficient for the enclosure wall, including the following steps:

[0066] When the enclosure wall is classified as first-level risk, obtain the environmental data near the enclosure wall. The environmental data includes ground vibration, wind speed, and rainfall. Obtain the construction operation data near the enclosure wall. The construction operation data includes the underground water level volatility caused by construction and the distance between the excavated foundation pit and the enclosure wall;

[0067] Substitute the ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavated foundation pit and the enclosure wall into the linear regression analysis model to calculate and obtain the influence coefficient. The expression is as follows:

[0068] In the formula, YX s is the influence coefficient. {y1, y2, y3, y4, y5} are the ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavated foundation pit and the enclosure wall respectively. {w1, w2, w3, w4, W5} are the regression coefficients of the ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavated foundation pit and the enclosure wall respectively, and the regression coefficients are all greater than 0;

[0069] The logical factors that make up the influence coefficient in the use of the present invention: Taking the influence of environmental data and construction operation data on the safety of the enclosure wall as an example, one is the index, that is, the factor that causes the change in the safety of the enclosure wall; the second is the weight of these indexes, that is, the proportion occupied when each main influencing data is generated; the third is the operation equation, that is, through what kind of mathematical operation process to obtain the result, and the influence coefficient obtained by operating the indexes with their respective weights through the operation equation.

[0070] Perform data conversion and processing on the main influencing data obtained from the samples, and convert them into the data language recognized by computer software; secondly, use SPSS software to perform Logistic regression analysis on these evaluation factors, and screen out the factors and their weights that have important correlations with the results; thirdly, substitute the evaluation factors and weights into the Logistic regression equation for operation to obtain the results. Specifically:

[0071] First, ensure the integrity of the main influencing data, handle missing values and outliers, and convert the data into a format recognizable by SPSS software. Usually, the data is stored in formats such as csv, xlsx, etc., and then imported into SPSS. Open the SPSS software, import the processed data file, and convert variables as needed. For example, for continuous variables, perform standardization or normalization. Select the "Analyze" menu, then select the "Binary Logistic" option under "Regression". In the dialog box, add the dependent variable (result) and independent variables (main influencing data) to the corresponding boxes. SPSS will fit a Logistic regression model based on the selected variables. In the output results, you will see information such as the coefficients, standard errors, p-values of the model. Check the coefficients and p-values in the output results to determine which variables are significantly correlated with the result. Usually, a p-value less than 0.05 is considered significant. While fitting the model, use variable selection methods such as stepwise regression to help screen the most relevant factors. According to the coefficients of the Logistic regression model, the magnitude of the coefficient reflects the degree of influence of each factor on the result, and the sign of the coefficient indicates the direction of the influence. After obtaining the significant factors and their coefficients, obtain the Logistic regression equation, which is used to calculate the probability of each sample and then predict the result.

[0072] The larger the influence coefficient, the easier it is for the fence of the first-level risk to develop towards the fence of the second-level risk.

[0073] Combine the overall abnormal state of the first-level risk fence with the influence coefficient to predict the future development trend of the fence state, and generate corresponding management strategies for the fence based on the prediction results, including the following steps:

[0074] Obtain the influence coefficient and the overall abnormal coefficient of the first-level risk fence, comprehensively calculate the influence coefficient and the overall abnormal coefficient, and obtain the development status index of the first-level risk fence. The expression is:

[0075] fz s =α*wq z +β*YX s , where, wq z is the overall abnormal coefficient, YX s is the influence coefficient, fz s is the development status index, α and β are the adjustment factors of the overall abnormal coefficient and the influence coefficient respectively, and both α and β are greater than 0;

[0076] The larger the development status index, the more it indicates that the future state of the enclosure wall will develop towards an abnormal deterioration trend. Compare the obtained development status index with a preset abnormal threshold, which is used to predict the future development trend of the enclosure wall state. If the development status index is less than or equal to the abnormal threshold, it is predicted that the future state of the enclosure wall will develop towards abnormal improvement. If the development status index is greater than the abnormal threshold, it is predicted that the future state of the enclosure wall will develop towards abnormal deterioration;

[0077] Based on whether the future state of the enclosure wall develops towards abnormal improvement or deterioration, different management strategies can be adopted to effectively prevent potential risks and ensure the safety of the enclosure wall. The following are the management strategies for these two trends:

[0078] 1. Predict that the future state of the enclosure wall will develop towards abnormal improvement:

[0079] When the monitoring data and analysis indicate that the state of the enclosure wall is developing towards an improvement trend, the management strategy can focus on maintaining and consolidating this improvement effect and reducing potential interference and impact on the enclosure wall:

[0080] Regular monitoring: Continue to regularly collect the state data of the enclosure wall and maintain the monitoring frequency. Although the trend is positive, it is still necessary to closely observe to prevent short-term state fluctuations or the emergence of new risk factors.

[0081] Consolidate existing protection measures: On the basis of the stable state, ensure that the implemented protection measures are effective (such as strengthening the foundation, drainage management), and avoid creating new pressures on the enclosure wall.

[0082] Reduce high-intensity construction interference: Restrict high-intensity construction activities near the enclosure wall, especially equipment with high vibration intensity, to prevent the state from deteriorating again after improvement.

[0083] Set warning thresholds: For the monitored settlement and inclination data, relatively loose warning thresholds can be set to ensure that warnings are issued only when significant changes actually occur, in order to reduce false alarm interference.

[0084] Regular maintenance: Appropriately reduce the frequency of maintenance measures, such as conducting a comprehensive inspection of the enclosure wall quarterly or semi-annually, to ensure that the enclosure wall is in a safe state.

[0085] Long-term state assessment: Under the trend of the enclosure wall tending to improve, regular state assessment reports can be conducted to observe whether the enclosure wall can maintain a good state and decide whether to reduce the monitoring frequency or cut back on related resources.

[0086] 2. Predict that the future state of the enclosure wall will develop towards abnormal deterioration:

[0087] When the monitoring data and analysis indicate that the state of the enclosure wall may develop towards a deterioration trend, more proactive management strategies need to be adopted to slow down the deterioration rate and ensure the safety of the enclosure wall:

[0088] Encryption monitoring frequency: Increase the acquisition frequency of monitoring data to ensure timely acquisition of changes in the status of the enclosure wall, especially in areas with higher risks.

[0089] Adjust the warning threshold: Lower the warning threshold for monitoring the status of the enclosure wall (such as settlement and inclination) so that the system can issue a warning when there are slight signs of deterioration in the status of the enclosure wall, facilitating rapid response by management personnel.

[0090] Reinforcement and support measures: Implement reinforcement measures according to the current status and deterioration rate of the enclosure wall, such as deepening the foundation, increasing the support structure, improving the drainage system, etc., to enhance the stability of the enclosure wall.

[0091] Restrict construction activities: Restrict or suspend high-intensity construction activities near the enclosure wall, especially in areas where the deterioration trend of the enclosure wall is obvious, to prevent the impact of construction from exacerbating the change in the status of the enclosure wall.

[0092] Surrounding environment control: Strictly control the soil and groundwater conditions around the enclosure wall. For example, install temporary drainage equipment during heavy rain to prevent the foundation from being soaked by water and causing further settlement.

[0093] Real-time data analysis and prediction: Use historical data combined with real-time data, and adopt a data model to predict the future status of the enclosure wall, evaluate the development speed of the deterioration trend, and facilitate timely adoption of preventive measures.

[0094] Regular risk assessment and emergency plan: Increase the frequency of risk assessment of the enclosure wall status, regularly evaluate the safety status of the enclosure wall, update the emergency plan, and regularly drill emergency measures to quickly respond to possible emergencies.

[0095] Notification and communication mechanism: Ensure smooth communication among construction personnel, maintenance personnel, and management, promptly notify the deterioration trend and warning situation of the enclosure wall, and ensure cooperation and response among various departments.

[0096] Embodiment 3: The substation enclosure wall safety risk monitoring and warning system described in this embodiment includes an abnormal status analysis module, a classification module, and a prediction module;

[0097] Abnormal status analysis module: Obtain the information of the monitored enclosure wall in the substation, divide the enclosure wall into multiple monitoring sub-areas, monitor the status data of each sub-area through sensing devices, obtain the abnormal conditions of each sub-area, and analyze the overall abnormal status of the enclosure wall in combination with the abnormal conditions of all sub-areas. The overall abnormal status is sent to the classification module;

[0098] Classification module: Based on the analysis results, divide the enclosure wall into risk-free, first-level risk, and second-level risk, and include the enclosure walls with second-level risk in the management area. The classification results are sent to the prediction module;

[0099] Prediction module: When the fence is classified as a first-level risk, the environmental factors and construction operation factors of the fence are associated and processed to generate an influence coefficient for the fence. The overall abnormal state of the first-level risk fence is combined with the influence coefficient to predict the future development trend of the fence state, and corresponding management strategies are generated for the fence based on the prediction results.

[0100] The above formulas are all calculated by taking the numerical values after dimensionlessization. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0101] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Among them, A and B can be singular or plural. In addition, the character " / " in this article generally represents an "or" relationship between the front and back associated objects, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context before and after.

[0102] It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0103] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0104] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, and all should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for monitoring and warning of safety risks of a substation fence, characterized in that: The warning method includes the following steps: The warning system obtains the information of the monitored fence in the substation, divides the fence into multiple monitoring sub-areas, monitors the status data of each sub-area through sensing devices, obtains the abnormal conditions of each sub-area, and analyzes the overall abnormal state of the fence by combining the abnormal conditions of all sub-areas; Based on the analysis results, the fence is divided into risk-free, first-level risk, and second-level risk, and the fence with second-level risk is included in the management area; When the fence is divided into first-level risk, the environmental factors and construction operation factors of the fence are associated to generate an influence coefficient for the fence. The overall abnormal state of the first-level risk fence is combined with the influence coefficient to predict the future development trend of the fence state, and a corresponding management strategy is generated for the fence according to the prediction results.

2. The substation fence safety risk monitoring and early warning method according to claim 1, wherein: After monitoring the status data of each sub-area through sensing devices, the abnormal conditions of each sub-area are obtained, including the following steps: Monitor the status data of each sub-area through sensing devices, and the status data includes settlement value, tilt angle, and crack variation index; Normalize the settlement value, tilt angle, and crack variation index so that the value ranges of the settlement value, tilt angle, and crack variation index are mapped to between [0,1], obtain the normalized settlement value, normalized tilt angle, and normalized crack variation index, and sum the normalized settlement value, normalized tilt angle, and normalized crack variation index to obtain the abnormal factor of the sub-area.

3. The substation fence safety risk monitoring and early warning method according to claim 2, wherein: Analyze the overall abnormal state of the fence by combining the abnormal conditions of all sub-areas, including the following steps: Obtain the midpoint of the enclosure by dividing the length of the enclosure by 2, and calculate the midpoint of each sub-region. The expression is: In the formula, x i is the midpoint of the i-th sub-region, L is the length of the enclosure, and n is the number of sub-region divisions; Calculate the distance from the midpoint of the i-th sub-region to the midpoint of the enclosure wall, and the expression is: d i = |x i - C|, where d i is the distance from the midpoint of the i-th sub-region to the midpoint of the enclosure wall, x i is the midpoint of the i-th sub-region, and C is the midpoint of the enclosure wall; After obtaining the distances from the midpoints of all sub-areas to the midpoint of the fence, sum the distances from the midpoints of all sub-areas to the midpoint of the fence to obtain the total distance, obtain the influence value of the sub-area by dividing the distance from the midpoint of the sub-area to the midpoint of the fence by the total distance, add 1 to the influence value of each sub-area to obtain the correction value, and use the reciprocal of the correction value as the weight of the sub-area; Combining and analyzing all sub-regions of the enclosure to obtain the overall anomaly coefficient of the enclosure, the expression is: In the formula, wq z is the overall anomaly coefficient, g i is the weight of the i-th sub-region, yc i is the anomaly factor of the i-th sub-region.

4. The substation fence safety risk monitoring and early warning method according to claim 3, characterized in that: Based on the analysis results, the fence is divided into risk-free, first-level risk, and second-level risk, including the following steps: After obtaining the overall abnormal coefficient of the fence, compare the overall abnormal coefficient with a preset first coefficient threshold and a second coefficient threshold. The first coefficient threshold is used to judge whether there is a safety risk for the fence, and the second coefficient threshold is used to judge the severity of the fence risk; If the overall abnormal coefficient is less than or equal to the first coefficient threshold, it is judged that there is no safety risk for the fence, and the fence is divided into risk-free; If the overall abnormal coefficient is greater than the first coefficient threshold and less than or equal to the first coefficient threshold, it is judged that there is no minor risk for the fence, and the fence is divided into first-level risk; If the overall abnormal coefficient is greater than the second coefficient threshold, it is judged that there is a serious risk for the fence, and the fence is divided into second-level risk.

5. The substation fence safety risk monitoring and early warning method according to claim 4, wherein: When the fence is divided into first-level risk, the environmental factors and construction operation factors of the fence are associated to generate an influence coefficient for the fence, including the following steps: When the fence is divided into first-level risk, obtain the environmental data near the fence, and the environmental data includes ground vibration, wind speed, and rainfall. Obtain the construction operation data near the fence, and the construction operation data includes the underground water level volatility caused by construction and the distance between the excavated foundation pit and the fence; Substitute the ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavated foundation pit and the enclosure wall into the linear regression analysis model to calculate and obtain the influence coefficient. The expression is as follows: In the formula, YX s is the influence coefficient, {y1, y2, y3, y4, y5} are respectively ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavated foundation pit and the enclosure wall, {w1, w2, w3, w4, w5} are respectively the regression coefficients of ground vibration, wind speed, rainfall, underground water level volatility, and the distance between the excavated foundation pit and the enclosure wall, and the regression coefficients are all greater than 0.

6. The substation fence safety risk monitoring and early warning method according to claim 5, characterized in that: Combine the overall abnormal state of the first-level risk enclosure wall with the influence coefficient to predict the future development trend of the enclosure wall state, and generate corresponding management strategies for the enclosure wall based on the prediction results. The steps are as follows: Obtain the influence coefficient and the overall abnormal coefficient of the first-level risk enclosure wall, and comprehensively calculate the influence coefficient and the overall abnormal coefficient to obtain the development state index of the first-level risk enclosure wall; Compare the obtained development state index with the preset abnormal threshold. The abnormal threshold is used to predict the future development trend of the enclosure wall state. If the development state index is less than or equal to the abnormal threshold, it is predicted that the future development trend of the enclosure wall state will be towards abnormal improvement. If the development state index is greater than the abnormal threshold, it is predicted that the future development trend of the enclosure wall state will be towards abnormal deterioration.

7. The substation fence safety risk monitoring and early warning method according to claim 6, characterized in that: Comprehensively calculate the influence coefficient and the overall abnormal coefficient to obtain the development state index of the first-level risk enclosure wall. The expression is as follows: fz s = α * wq z + β * YX s , where wq z is the overall anomaly coefficient, YX s is the influence coefficient, fz s is the development status index, and α and β are the adjustment factors for the overall anomaly coefficient and the influence coefficient respectively, and both α and β are greater than 0.

8. A safety risk monitoring and early warning system for a substation fence, which is used to implement the early warning method described in any one of claims 1-7, characterized in that: It includes an abnormal state analysis module, a classification module, and a prediction module; Abnormal state analysis module: Obtain the information of the monitored enclosure wall in the substation, divide the enclosure wall into multiple monitoring sub-areas, monitor the state data of each sub-area through sensing devices, obtain the abnormal conditions of each sub-area, and analyze the overall abnormal state of the enclosure wall by combining the abnormal conditions of all sub-areas; Classification module: Based on the analysis results, divide the enclosure wall into risk-free, first-level risk, and second-level risk, and include the second-level risk enclosure wall in the management area; Prediction module: When the enclosure wall is classified as a first-level risk, correlate the environmental factors and construction operation factors of the enclosure wall to generate an influence coefficient for the enclosure wall. Combine the overall abnormal state of the first-level risk enclosure wall with the influence coefficient to predict the future development trend of the enclosure wall state, and generate corresponding management strategies for the enclosure wall based on the prediction results.

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