Large cantilever structure construction safety risk assessment system

Abstract

The invention relates to the technical field of large cantilever structure construction, in particular to a large cantilever structure construction safety risk assessment system which comprises an environment change factor assessment module, a structure health diagnosis module, a comprehensive risk assessment module and an intelligent safety control module. The environment change factor evaluation module collects environment data of a construction site in real time through an environment sensor and evaluates the influence of environment factor changes on construction safety of the large cantilever structure in real time. The structural health diagnosis module analyzes stress, deformation and dynamic response states of the structural health diagnosis module and predicts potential structural damage; the comprehensive risk assessment module performs global security risk assessment; the intelligent safety control module automatically controls safety guarantee measures of a construction site. According to the invention, the data accuracy and the health monitoring accuracy in the construction process are ensured, and comprehensive safety state information is provided for a construction party.

Description

Technical Field

[0001] The invention relates to the technical field of large cantilever structure construction, and in particular to a large cantilever structure construction safety risk assessment system. Background Art

[0002] With the continuous expansion of the scale of construction projects, cantilever structures are used more and more widely in construction. Large cantilever structures face higher safety risks during construction due to their complex force and diverse structural forms. During the construction process, cantilever structures not only bear their own weight and construction loads, but are also affected by changes in environmental factors (such as wind speed, temperature, humidity, etc.), resulting in constant changes in the stress, deformation and vibration characteristics of the structure. If there is a lack of effective monitoring and evaluation of the structural health status and environmental changes during construction, it is easy to cause safety accidents, posing serious hidden dangers to project quality and construction personnel.

[0003] Existing construction monitoring and risk assessment technologies for large cantilever structures usually rely on a single environmental or structural monitoring method, and lack the ability to comprehensively assess environmental changes and structural health status. Traditional methods mainly rely on manual monitoring of environmental factors or collecting structural data through a single sensor, with low assessment accuracy and difficulty adapting to complex construction environments. At the same time, existing systems mostly use static risk level judgments in risk assessment, failing to fully consider the dynamic changes and interactions between environmental factors and structural health status, and are unable to effectively assess safety risks in the construction process in real time. More importantly, traditional construction safety monitoring systems lack intelligent control mechanisms and are unable to automatically take corresponding emergency control measures when risk levels rise, resulting in insufficient timeliness and effectiveness of safety assurance.

[0004] In response to the above problems, the present invention provides a large cantilever structure construction safety risk assessment system, which not only fills the gap in the prior art in the comprehensive monitoring of the environment and structure, but also improves the intelligence level of construction safety risk management. Summary of the invention

[0005] The invention provides a large cantilever structure construction safety risk assessment system.

[0006] The large cantilever structure construction safety risk assessment system includes an environmental change factor assessment module, a structural health diagnosis module, a comprehensive risk assessment module, and an intelligent safety control module, among which; The environmental change factor assessment module collects environmental data of the construction site in real time through environmental sensors, including wind speed, airflow, temperature, and humidity, and assesses the impact of environmental factor changes on the safety of large cantilever structure construction in real time; The structural health diagnosis module collects structural response data of large cantilever structures, including strain, displacement and vibration data, by integrating multi-modal sensors, analyzes its stress, deformation and dynamic response state, and predicts potential structural damage, including: Structural response data acquisition and processing: The structural response data of the large cantilever structure is collected through multimodal sensors, and the collected structural response data is preprocessed, including denoising and smoothing; Structural health analysis: Analyze the stress, deformation and dynamic response status of the structure based on the pre-processed structural response data; Health prediction: Based on the results of structural health analysis, potential structural damage is predicted through a convolutional neural network (CNN) model; The comprehensive risk assessment module performs a global safety risk assessment based on the assessment results of the potential impact of environmental factor changes on the construction safety of large cantilever structures and the prediction results of potential structural damage; The intelligent safety control module automatically controls the safety measures of the construction site according to the results of the global safety risk assessment, including dispatching construction personnel, controlling the operation of mechanical equipment, early warning of risk areas and suspension of operations.

[0007] Optionally, the environmental change factor assessment module includes: Environmental data collection: Environmental sensors installed at the construction site collect environmental data in real time, including wind speed, airflow, temperature, and humidity, and perform preliminary processing on the collected environmental data, including standardization and missing value processing; Environmental change analysis: Based on the preliminary processed environmental data, analyze the changing trends and fluctuations of environmental factors; Environmental risk assessment: Combined with the results of environmental change analysis, evaluate the impact of environmental changes on the construction safety of large cantilever structures.

[0008] Optionally, the environmental data collection includes: Wind speed collection: collect wind speed data at the construction site in real time by installing wind speed sensors; Airflow collection: collect airflow data at the construction site in real time by installing airflow sensors; Temperature collection: Install temperature sensors to collect temperature data at the construction site in real time; Humidity collection: collect humidity data at the construction site in real time by installing humidity sensors; Preliminary data processing: Preliminary processing of the collected environmental data, including: Standardization: Z-Score standardization is used to standardize environmental data; Missing value processing: Linear interpolation is used to fill missing values ​​through the linear relationship between previous and subsequent data points.

[0009] Optionally, the environmental change analysis includes: Trend analysis: Use the exponentially weighted moving average (EWMA) algorithm to perform trend analysis on environmental data to smooth fluctuations and identify changing trends; Volatility Analysis: The volatility of environmental data is analyzed using the Autoregressive Conditional Heteroskedasticity (ARCH) model to capture the non-constant nature of volatility.

[0010] Optionally, the environmental risk assessment includes: Risk score calculation: combining the results of trend analysis and fluctuation analysis, and calculating a comprehensive environmental risk score through a weighted algorithm ; Risk classification: Score environmental risks The upper limit of the preset environmental risk threshold and environmental risk threshold For comparison, When When , it indicates a high environmental risk.

[0011] Optionally, the structural response data acquisition and processing includes: Structural response data acquisition: collecting strain, displacement and vibration data of the large cantilever structure through a multimodal sensor, specifically including: Strain data collection: Install strain gauges at the stress-bearing parts of the structure to collect real-time strain changes of the structure under load; Displacement data collection: Install displacement sensors at the cantilever ends and support points of the structure to monitor the displacement and deformation of the structure in real time; Vibration data collection: Install acceleration sensors at the vibration locations of the structure to collect vibration response data of the structure under the influence of the external environment or internal operations; De-noising: Kalman filtering algorithm is used to denoise the collected structural response data; Smoothing: The moving average method is used to smooth the denoised structural response data.

[0012] Optionally, the structural health analysis includes: Stress analysis: Calculate the stress distribution of the structure using strain data; Deformation analysis: Based on displacement data, calculate the overall deformation of the structure under external forces; Dynamic response analysis: Analyze the vibration data using spectrum analysis algorithms to identify the vibration amplitude of the structure.

[0013] Optionally, the convolutional neural network (CNN) model includes: Multi-dimensional health status matrix construction: Based on the results of structural health analysis, including stress distribution, overall deformation, vibration amplitude, the health status matrix is ​​constructed by time step arrangement ; Feature weight learning: By adaptively learning the weight of each health feature, the contribution of each feature to injury prediction is automatically adjusted; Temporal convolution: Apply one-dimensional convolution to the weighted health features. The convolution operation extracts dynamic features on the time series, that is, for each time step Convolution of the feature vector; Result output: Input the result of temporal convolution into the fully connected layer and output the prediction result through the Softmax activation function ; Injury classification: will predict the outcome The preset damage threshold and the lower damage threshold For comparison, When When , indicates severe injury.

[0014] Optionally, the comprehensive risk assessment module includes: Low risk: When the environmental risk is low and the structural damage risk is slight, the overall risk is low; Medium risk: When the environmental risk is low environmental risk and the structural damage risk is moderate damage, the comprehensive risk is medium risk; when the environmental risk is medium environmental risk and the structural damage risk is slight damage, the comprehensive risk is medium risk; Medium-high risk: When the environmental risk is low environmental risk and the structural damage risk is severe damage, the comprehensive risk is medium-high risk; when the environmental risk is medium environmental risk and the structural damage risk is moderate damage, the comprehensive risk is medium-high risk; when the environmental risk is high environmental risk and the structural damage risk is slight damage, the comprehensive risk is medium-high risk; High risk: When the environmental risk is medium environmental risk and the structural damage risk is severe damage, the comprehensive risk is high risk; when the environmental risk is high environmental risk and the structural damage risk is medium damage, the comprehensive risk is high risk; Extremely high risk: When the environmental risk is high and the structural damage risk is severe, the combined risk is extremely high.

[0015] Optionally, the intelligent safety control module includes: Low risk - regular monitoring: When the overall risk is low, regular monitoring is maintained and safety parameters of the construction site are regularly inspected and monitored; Medium risk - personnel dispatch and area inspection: When the overall risk is medium, the personnel will be automatically dispatched to the post, and the inspection of the site will be strengthened, and the inspection frequency of the risk area will be increased; Medium-high risk - equipment control and early warning: When the comprehensive risk is medium-high, reduce the operating speed or frequency of mechanical equipment and restrict irrelevant personnel from entering the risk area; High risk - partial operation suspension and area closure: When the comprehensive risk is high, some operations will be automatically suspended, and at the same time, the high-risk area will be closed to prevent people from entering, and the management staff will be notified to conduct inspections; Extremely high risk - full suspension and emergency response: When the comprehensive risk is extremely high, all operations will be stopped immediately, and emergency response measures will be initiated to evacuate all personnel from the construction site, fully close the high-risk area, and notify the emergency rescue team to handle the situation.

[0016] Beneficial effects of the present invention: The present invention realizes real-time monitoring and evaluation of changes in environmental factors on the construction site and the health status of large cantilever structures through the environmental change factor evaluation module and the structural health diagnosis module. The environmental change factor evaluation module collects and processes environmental data through a variety of sensors, analyzes the changing trends and volatility of environmental factors, and evaluates the potential impact of environmental changes on construction safety. The structural health diagnosis module collects structural response data such as strain, displacement, and vibration through multimodal sensors, and uses a convolutional neural network model to analyze the structural health status and predict potential structural damage, thereby ensuring the data accuracy and accuracy of health monitoring during the construction process, and providing comprehensive safety status information for the construction party.

[0017] The present invention adopts a classified and combined risk assessment method through a comprehensive risk assessment module, and evaluates different levels of environmental risk and structural damage risk into a comprehensive risk level. By introducing a risk combination matrix, the interactive impact of environmental factors and structural status can be intuitively identified, which significantly improves the accuracy and sensitivity of risk assessment. The classified and combined assessment method can not only accurately divide the comprehensive risk level, but also trigger corresponding early warning and control measures according to different risk levels, thereby ensuring the safety of the construction process and the timeliness of the system response.

[0018] The present invention, through a multi-level response mechanism, automatically adjusts the safety measures of the construction site according to the results of real-time comprehensive risk assessment, maintains routine monitoring under low-risk conditions, automatically dispatches personnel, adjusts equipment operation, and closes high-risk areas under medium- and high-risk conditions and above, and initiates a comprehensive emergency response when the risk is extremely high, so as to ensure the safety of personnel and equipment at the construction site. The hierarchical control method not only improves construction safety and management efficiency, but also can flexibly respond to changes on site under different risk levels, take preventive and emergency measures in time, effectively reduce the possibility of safety accidents, and provide all-round intelligent safety protection for the construction site. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A schematic diagram of system function modules according to an embodiment of the present invention; Figure 2 Schematic diagram of a structural health diagnosis module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0022] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0023] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0024] like Figure 1-Figure 2 As shown, the large cantilever structure construction safety risk assessment system includes an environmental change factor assessment module, a structural health diagnosis module, a comprehensive risk assessment module and an intelligent safety control module, wherein; The environmental change factor assessment module collects environmental data of the construction site in real time through environmental sensors, including wind speed, airflow, temperature, and humidity, and assesses the impact of environmental factor changes on the safety of large cantilever structure construction in real time; The structural health diagnosis module collects structural response data of large cantilever structures, including strain, displacement and vibration data, by integrating multi-modal sensors, analyzes its stress, deformation and dynamic response state, and predicts potential structural damage, including: Structural response data acquisition and processing: The structural response data of the large cantilever structure is collected through multimodal sensors, and the collected structural response data is preprocessed, including denoising and smoothing; Structural health analysis: Analyze the stress, deformation and dynamic response status of the structure based on the pre-processed structural response data; Health prediction: Based on the results of structural health analysis, potential structural damage is predicted through a convolutional neural network (CNN) model; The comprehensive risk assessment module conducts a global safety risk assessment based on the assessment results of the potential impact of environmental factors changes on the construction safety of large cantilever structures and the prediction results of potential structural damage; The intelligent safety control module automatically controls the safety measures at the construction site based on the results of the global safety risk assessment, including dispatching construction personnel, controlling the operation of mechanical equipment, early warning of risk areas, and suspending operations, to ensure that the safety risks during the construction process are within controllable range; Through the above content, it is possible to monitor and evaluate the changes in environmental factors and the health status of the structure during the construction process in real time, accurately predict potential structural damage or risks, and automatically adjust safety measures through intelligent decision-making mechanisms. This not only effectively improves the safety of the construction site and reduces potential risks, but also provides efficient and accurate safety assurance measures to ensure that various safety factors during the construction process are fully monitored and managed, reducing the possibility of accidents.

[0025] The environmental change factor assessment module includes: Environmental data collection: Environmental sensors installed at the construction site collect environmental data in real time, including wind speed, airflow, temperature, and humidity, and perform preliminary processing on the collected environmental data, including standardization and missing value processing; Environmental change analysis: Based on the preliminary processed environmental data, analyze the changing trends and fluctuations of environmental factors; Environmental risk assessment: Combined with the results of environmental change analysis, assess the impact of environmental changes on the construction safety of large cantilever structures; Through the above content, it is possible to comprehensively monitor the potential impact of environmental changes on the construction safety of large cantilever structures. Through accurate data collection, trend analysis and risk assessment, abnormal environmental changes can be identified in a timely manner, providing a scientific basis for the construction party, helping decision makers to predict and respond to potential safety risks in advance, ensuring that safety measures in the construction process are optimized, reducing the incidence of accidents caused by environmental factors, and improving the safety of the construction site and construction efficiency.

[0026] Environmental data collection includes: Wind speed collection: collect wind speed data at the construction site in real time by installing wind speed sensors; Airflow collection: collect airflow data at the construction site in real time by installing airflow sensors; Temperature collection: Install temperature sensors to collect temperature data at the construction site in real time; Humidity collection: collect humidity data at the construction site in real time by installing humidity sensors; Preliminary data processing: Preliminary processing of the collected environmental data, including: Standardization: Z-Score standardization is used to standardize environmental data, expressed as: ; in, is the standardized value, is the original data value, is the mean (average) of the data, is the standard deviation of the data; Missing value processing: Linear interpolation is used to fill missing values ​​through the linear relationship between the previous and next data points, expressed as: ; in, and are the known data point values ​​before and after the missing value, and are the timestamps of the previous and next data points, is the timestamp of the missing data point, is the missing value obtained after interpolation, that is, the missing data point that needs to be filled; Through the above content, high-precision monitoring of construction site environmental data is achieved. Standardization processing enables data of different dimensions to be analyzed at a unified scale, avoiding deviations caused by different data scales. Missing value processing fills data gaps through linear interpolation to ensure data continuity and integrity. This not only ensures the accuracy and consistency of environmental data, but also improves the system's sensitivity to environmental changes and the accuracy of analysis.

[0027] Environmental change analysis includes: Trend analysis: The exponentially weighted moving average (EWMA) algorithm is used to perform trend analysis on environmental data to smooth fluctuations and identify changing trends, expressed as: ; in, For at the moment The weighted average of is the current environment data value, is the smoothing coefficient (usually between 0 and between); Volatility analysis: The volatility of environmental data is analyzed using the autoregressive conditional heteroskedasticity (ARCH) model to capture the non-constant nature of volatility, expressed as: ; in, is the volatility variance at the current moment, is a constant term, are the parameters of the ARCHH model, For the front The environmental data value at the moment, is the order of the lag term; Through the above content, the EWMA algorithm can smooth short-term fluctuations, quickly identify long-term change trends in environmental data, and improve the system's sensitivity to environmental changes. The ARCH model can accurately capture the volatility of data, allowing construction managers to timely predict the potential risks brought about by non-constant fluctuations in the environment. This not only improves the accuracy of environmental risk prediction, but also provides a scientific and intelligent decision-making basis for the safety management of large cantilever structure construction.

[0028] Environmental risk assessment includes: Risk score calculation: Combine the results of trend analysis and fluctuation analysis to calculate a comprehensive environmental risk score through a weighted algorithm , expressed as: ; in, It is the environmental risk score, indicating the comprehensive environmental risk level. It is the environmental trend score, which reflects the changing trend of current environmental data. is the volatility score, which reflects the volatility of environmental data. , is the weight coefficient, which is used to adjust the impact of trend and volatility scores on environmental risks; Risk classification: Score environmental risks The upper limit of the preset environmental risk threshold and environmental risk threshold For comparison, When When When , it indicates high environmental risk; Upper limit of environmental risk threshold and environmental risk threshold The settings are based on historical environmental data and construction safety requirements, including: Collect historical environmental data and safety accident records: Collect historical environmental data (including wind speed, airflow, temperature, humidity, etc.) and corresponding safety accident records (such as accidents caused by changes in environmental conditions) at the construction site, and calculate environmental trends and volatility scores and ; Calculate the mean and standard deviation of the historical environmental risk score: Use the weighted risk score formula to calculate the historical environmental risk score The mean and standard deviation of are expressed as: ; ; in, is the environmental risk score at each historical moment, is the total amount of historical data, is the mean, is the standard deviation; Risk threshold setting: Based on the mean and standard deviation of historical environmental risk scores, set the upper limit of the environmental risk threshold and environmental risk threshold , expressed as: ; ; in, is a coefficient less than 1, with a value of 0.5 or 0.75. is a coefficient greater than 1, and its value is 1.5 or 2; Through the above content, the impact of environmental changes on construction safety can be evaluated in real time, and corresponding early warning and control measures can be triggered when the risk score exceeds the threshold. Through dynamic adjustment based on historical data, it can not only adapt to changes in different environmental conditions, but also improve the accuracy and sensitivity of risk identification, providing a more reliable and effective safety guarantee for the construction of large cantilever structures.

[0029] Structural response data acquisition and processing include: Structural response data acquisition: Multimodal sensors are used to collect strain, displacement and vibration data of large cantilever structures, including: Strain data collection: Install strain gauges at the stress-bearing parts of the structure to collect real-time strain changes of the structure under load; Displacement data collection: Install displacement sensors at the cantilever ends and support points of the structure to monitor the displacement and deformation of the structure in real time; Vibration data collection: Install acceleration sensors at the vibration locations of the structure to collect vibration response data of the structure under the influence of the external environment or internal operations; De-noising: The Kalman filter algorithm is used to denoise the collected structural response data, which is expressed as: ; in, For the moment The posterior estimated state of is the prior estimated state, is the Kalman gain, used to adjust the estimated value, is the collected measurement value, is the measurement matrix; Smoothing: The moving average method is used to smooth the denoised structural response data to eliminate short-term fluctuations and enhance the stability of the data, which is expressed as: ; in, For the moment The moving average of For at the moment The collected denoised structural response data, is the length of the smoothing window; Through the above content, the impact of environmental noise and measurement errors can be effectively reduced, making the collected structural response data more reliable. This not only improves the accuracy of structural monitoring, but also makes safety management during the construction process more scientific and operational, which helps to achieve more accurate structural health monitoring and risk warning.

[0030] Structural health analysis includes: Stress analysis: Use strain data to calculate the stress distribution of the structure, expressed as: ; in, is stress, is the elastic modulus of the material, is the strain data after preprocessing; Deformation analysis: Based on the displacement data, the overall deformation of the structure under the action of external forces is calculated and expressed as: ; in, is the total deformation of the structure, and are the maximum and minimum displacement values ​​at specific locations on the structure, respectively; Dynamic response analysis: The vibration data is analyzed using a spectrum analysis algorithm to identify the vibration amplitude of the structure, expressed as: ; in, For frequency The amplitude of the following For the moment Vibration data, is the total number of sampled data; Through the above content, the health status of large cantilever structures during the construction process can be comprehensively evaluated. The force distribution can be analyzed through the stress-strain relationship to ensure the safety of the structure under load. The deformation analysis reveals the overall deformation degree of the structure and helps to identify potential over-limit risks. The spectrum analysis identifies the resonant frequency and vibration amplitude, and promptly discovers abnormal vibrations that may affect the stability of the structure. It helps the construction party to fully grasp the real-time status of the structure, identify and prevent potential safety hazards in advance, and greatly improve the reliability and safety of large cantilever structure construction.

[0031] The Convolutional Neural Network (CNN) model consists of: Multi-dimensional health status matrix construction: Based on the results of structural health analysis, including stress distribution, overall deformation, vibration amplitude, the health status matrix is ​​constructed by time step arrangement , expressed as: ; ; ; in, For the moment The force characteristics (stress), For the moment The deformation characteristics (total deformation), For the moment Dynamic response characteristics (vibration amplitude); ; in, is the number of time steps; Feature weight learning: By adaptively learning the weight of each health feature, the contribution of each feature to damage prediction is automatically adjusted, which is expressed as: ; ; ; in, , , are the weighted stress characteristics, deformation characteristics, and dynamic response characteristics, respectively. , , are the weights of stress characteristics, deformation characteristics, and dynamic response characteristics respectively; Temporal convolution: Apply one-dimensional convolution to the weighted health features. The convolution operation extracts dynamic features on the time series, that is, for each time step Convolution is performed on the feature vector of, expressed as: ; in, is the time series feature after convolution, is the weight of the temporal convolution kernel, is the size of the convolution kernel, that is, the receptive field in the time dimension, is the weighted health feature matrix In the time step and The value of the feature position; Result output: Input the result of temporal convolution into the fully connected layer and output the prediction result through the Softmax activation function , expressed as: ; in, Score the damage of the structure. is the weight of the fully connected layer, is the bias of the fully connected layer; Injury classification: will predict the outcome The preset damage threshold and the lower damage threshold For comparison, When When , it indicates severe injury; Damage threshold upper limit and the lower damage threshold The mean and standard deviation of health characteristics are calculated based on the health characteristics, including stress , deformation and vibration amplitude , calculate the mean stress and standard deviation , deformation mean and standard deviation , vibration mean and standard deviation ; Threshold calculation: Based on the statistical data of health characteristics, define the upper limit of the injury threshold of the injury score and the lower damage threshold , expressed as: ; ; in, , , is the weight coefficient of the lower limit of the damage score, , , is the weight coefficient of the upper limit of the damage score, , , , , , is the control coefficient; Through the above content, the real-time health characteristics of the structure can be captured comprehensively and flexibly, and key damage characteristics can be adaptively focused. In addition, the time series convolution module effectively extracts the dynamic change pattern of the structural health characteristics, enhancing the sensitivity and accuracy of the model in damage prediction. Through the reasonable setting of the upper and lower thresholds, the model can associate the damage score with the specific health characteristics and make accurate classification judgments, so that the model can more accurately predict and classify the damage status, providing highly reliable and adaptable technical support for structural health monitoring.

[0032] The comprehensive risk assessment module includes: Low risk: When the environmental risk is low and the structural damage risk is slight, the overall risk is low; Medium risk: When the environmental risk is low environmental risk and the structural damage risk is moderate damage, the comprehensive risk is medium risk; when the environmental risk is medium environmental risk and the structural damage risk is slight damage, the comprehensive risk is medium risk; Medium-high risk: When the environmental risk is low environmental risk and the structural damage risk is severe damage, the comprehensive risk is medium-high risk; when the environmental risk is medium environmental risk and the structural damage risk is moderate damage, the comprehensive risk is medium-high risk; when the environmental risk is high environmental risk and the structural damage risk is slight damage, the comprehensive risk is medium-high risk; High risk: When the environmental risk is medium environmental risk and the structural damage risk is severe damage, the comprehensive risk is high risk; when the environmental risk is high environmental risk and the structural damage risk is medium damage, the comprehensive risk is high risk; Very high risk: When the environmental risk is high and the structural damage risk is severe, the combined risk is very high;

[0033] Through the above content, the interactive impact of environmental factors and structural status can be intuitively identified, so as to accurately divide the comprehensive risk level. The classification and combination evaluation method improves the accuracy of risk judgment, allowing the system to automatically trigger appropriate early warning and control measures according to different risk levels, ensuring the safety of the construction process and the timeliness of response.

[0034] The intelligent safety control module includes: Low risk - regular monitoring: When the overall risk is low, regular monitoring is maintained, and safety parameters of the construction site are regularly inspected and monitored to ensure that construction activities are carried out within a safe range; Medium risk - personnel dispatch and area inspection: When the comprehensive risk is medium, the personnel will be automatically dispatched to the post, and the inspection of the site will be strengthened, and the inspection frequency of the risk area will be increased to ensure the early detection of potential hazards and ensure construction safety; Medium-high risk - equipment control and early warning: When the comprehensive risk is medium-high, reduce the operating speed or frequency of mechanical equipment to reduce the impact on the structure, issue early warnings for risk areas, and restrict unrelated personnel from entering risk areas to ensure the safety of construction personnel; High risk - partial operation suspension and area closure: When the comprehensive risk is high, some operations will be automatically suspended to reduce the load impact of construction on the structure. At the same time, high-risk areas will be closed to prevent people from entering, and management personnel will be notified to conduct inspections; Extremely high risk - full suspension and emergency response: When the comprehensive risk is extremely high, all operations will be stopped immediately, and emergency response measures will be initiated to evacuate all personnel from the construction site, fully close the high-risk area, and notify the emergency rescue team to handle it, so as to protect the safety of the site to the greatest extent; Through the above content, we can take multi-level control measures from routine monitoring to comprehensive emergency response according to the real-time risk assessment results, flexibly respond to on-site changes, improve construction safety and management efficiency, not only maintain normal operations when the risk is low, but also quickly take corresponding preventive and emergency measures when the risk is high, effectively reduce the probability of safety accidents, and provide all-round safety protection for the construction site.

[0035] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0036] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. Large cantilever structure construction safety risk assessment system, characterized by: It includes environmental change factor assessment module, structural health diagnosis module, comprehensive risk assessment module and intelligent safety control module, among which; The environmental change factor assessment module collects environmental data of the construction site in real time through environmental sensors, including wind speed, airflow, temperature, and humidity, and assesses the impact of environmental factor changes on the safety of large cantilever structure construction in real time; The structural health diagnosis module collects structural response data of large cantilever structures, including strain, displacement and vibration data, by integrating multi-modal sensors, analyzes its stress, deformation and dynamic response state, and predicts potential structural damage, including: Structural response data acquisition and processing: The structural response data of the large cantilever structure is collected through multimodal sensors, and the collected structural response data is preprocessed, including denoising and smoothing; Structural health analysis: Analyze the stress, deformation and dynamic response status of the structure based on the pre-processed structural response data; Health status prediction: Based on the results of structural health analysis, potential structural damage is predicted through a convolutional neural network model; The comprehensive risk assessment module performs a global safety risk assessment based on the assessment results of the potential impact of environmental factor changes on the construction safety of large cantilever structures and the prediction results of potential structural damage; The intelligent safety control module automatically controls the safety measures of the construction site according to the results of the global safety risk assessment, including dispatching construction personnel, controlling the operation of mechanical equipment, early warning of risk areas and suspension of operations.

2. The large cantilever structure construction safety risk assessment system according to claim 1 is characterized in that: The environmental change factor assessment module includes: Environmental data collection: Environmental sensors installed at the construction site collect environmental data in real time, including wind speed, airflow, temperature, and humidity, and perform preliminary processing on the collected environmental data, including standardization and missing value processing; Environmental change analysis: Based on the preliminary processed environmental data, analyze the changing trends and fluctuations of environmental factors; Environmental risk assessment: Combined with the results of environmental change analysis, evaluate the impact of environmental changes on the construction safety of large cantilever structures.

3. The large cantilever structure construction safety risk assessment system according to claim 2 is characterized in that: The environmental data collection includes: Wind speed collection: collect wind speed data at the construction site in real time by installing wind speed sensors; Airflow collection: collect airflow data at the construction site in real time by installing airflow sensors; Temperature collection: Install temperature sensors to collect temperature data at the construction site in real time; Humidity collection: collect humidity data at the construction site in real time by installing humidity sensors; Preliminary data processing: Preliminary processing of the collected environmental data, including: Standardization: Z-Score standardization is used to standardize environmental data; Missing value processing: Linear interpolation is used to fill missing values ​​through the linear relationship between previous and subsequent data points.

4. The large cantilever structure construction safety risk assessment system according to claim 3 is characterized in that: The environmental change analysis includes: Trend analysis: Use the exponentially weighted moving average algorithm to perform trend analysis on environmental data to smooth fluctuations and identify changing trends; Volatility Analysis: The volatility of environmental data is analyzed using an autoregressive conditional heteroskedasticity model to capture the non-constant nature of volatility.

5. The large cantilever structure construction safety risk assessment system according to claim 4 is characterized in that: The environmental risk assessment includes: Risk score calculation: Combine the results of trend analysis and fluctuation analysis to calculate a comprehensive environmental risk score through a weighted algorithm ; Risk classification: Score environmental risks The upper limit of the preset environmental risk threshold and environmental risk threshold For comparison, When When , it indicates a high environmental risk.

6. The large cantilever structure construction safety risk assessment system according to claim 5 is characterized in that: The structural response data acquisition and processing includes: Structural response data acquisition: Multimodal sensors are used to collect strain, displacement and vibration data of large cantilever structures, including: Strain data collection: Install strain gauges at the stress-bearing parts of the structure to collect real-time strain changes of the structure under load; Displacement data collection: Install displacement sensors at the cantilever ends and support points of the structure to monitor the displacement and deformation of the structure in real time; Vibration data collection: Install acceleration sensors at the vibration locations of the structure to collect vibration response data of the structure under the influence of the external environment or internal operations; De-noising: Kalman filtering algorithm is used to denoise the collected structural response data; Smoothing: The moving average method is used to smooth the denoised structural response data.

7. The large cantilever structure construction safety risk assessment system according to claim 6 is characterized in that: The structural health analysis includes: Stress analysis: Calculate the stress distribution of the structure using strain data; Deformation analysis: Based on displacement data, calculate the overall deformation of the structure under external forces; Dynamic response analysis: Analyze the vibration data using spectrum analysis algorithms to identify the vibration amplitude of the structure.

8. The large cantilever structure construction safety risk assessment system according to claim 7 is characterized in that: The convolutional neural network model includes: Multi-dimensional health status matrix construction: Based on the results of structural health analysis, including stress distribution, overall deformation, vibration amplitude, the health status matrix is ​​constructed by time step arrangement ; Feature weight learning: By adaptively learning the weight of each health feature, the contribution of each feature to injury prediction is automatically adjusted; Temporal convolution: Apply one-dimensional convolution to the weighted health features. The convolution operation extracts dynamic features on the time series, that is, for each time step Convolution of the feature vector; Result output: Input the result of temporal convolution into the fully connected layer and output the prediction result through the Softmax activation function ; Injury classification: will predict the outcome The preset damage threshold and the lower damage threshold For comparison, When When , indicates severe injury.

9. The large cantilever structure construction safety risk assessment system according to claim 8 is characterized in that: The comprehensive risk assessment module includes: Low risk: When the environmental risk is low and the structural damage risk is slight, the overall risk is low; Medium risk: When the environmental risk is low environmental risk and the structural damage risk is moderate damage, the comprehensive risk is medium risk; when the environmental risk is medium environmental risk and the structural damage risk is slight damage, the comprehensive risk is medium risk; Medium-high risk: When the environmental risk is low environmental risk and the structural damage risk is severe damage, the comprehensive risk is medium-high risk; when the environmental risk is medium environmental risk and the structural damage risk is moderate damage, the comprehensive risk is medium-high risk; when the environmental risk is high environmental risk and the structural damage risk is slight damage, the comprehensive risk is medium-high risk; High risk: When the environmental risk is medium environmental risk and the structural damage risk is severe damage, the comprehensive risk is high risk; when the environmental risk is high environmental risk and the structural damage risk is medium damage, the comprehensive risk is high risk; Extremely high risk: When the environmental risk is high and the structural damage risk is severe, the combined risk is extremely high.

10. The large cantilever structure construction safety risk assessment system according to claim 9 is characterized in that: The intelligent safety control module comprises: Low risk - regular monitoring: When the overall risk is low, regular monitoring is maintained and safety parameters of the construction site are regularly inspected and monitored; Medium risk - personnel dispatch and area inspection: When the overall risk is medium, the personnel will be automatically dispatched to the post, and the inspection of the site will be strengthened, and the inspection frequency of the risk area will be increased; Medium-high risk - equipment control and early warning: When the comprehensive risk is medium-high, reduce the operating speed or frequency of mechanical equipment and restrict irrelevant personnel from entering the risk area; High risk - partial operation suspension and area closure: When the comprehensive risk is high, some operations will be automatically suspended, and at the same time, the high-risk area will be closed to prevent people from entering, and the management staff will be notified to conduct inspections; Extremely high risk - full suspension and emergency response: When the comprehensive risk is extremely high, all operations will be stopped immediately, and emergency response measures will be initiated to evacuate all personnel from the construction site, fully close the high-risk area, and notify the emergency rescue team to handle the situation.

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