A safety monitoring system for tall formwork construction

Abstract

The invention discloses a high-rise template construction safety monitoring system, which specifically relates to the technical field of building construction monitoring, and comprises a template data acquisition module, a dynamic load analysis module, an interpolation module, a time window analysis module, an adjacent area comprehensive analysis module and an early warning module; the template data acquisition module collects stress data of a foundation area in real time through a sensor network, the dynamic load analysis module dynamically adjusts the stress area division according to the stress data, the interpolation module performs smoothing on the adjusted data, the time window analysis module calculates regional stress fluctuations, the adjacent area comprehensive analysis module evaluates the stress influence of adjacent areas, the early warning module generates risk levels through fuzzy logic, and also comprises a construction report generation module for recording and generating safety reports; the invention can better control and accurately locate local dangerous areas, avoid large-scale blind inspections, and thus improve the safety management efficiency of construction sites.

Description

Technical Field

[0001] The present invention relates to the technical field of building construction monitoring, and more specifically, to a high-rise template construction safety monitoring system. Background Art

[0002] With the development of modern construction technology, the application of tall formwork has become more and more widespread in construction. This formwork support system is widely used in the construction of high-rise buildings, bridges, large industrial plants, etc., and can provide stable support to ensure the smooth pouring of concrete. However, the force of tall formwork is complex and changeable, and it is easily affected by multiple factors such as the external environment and construction load, which leads to challenges in its stability and safety. Traditional formwork monitoring methods mostly rely on manual inspection or simple monitoring equipment, which cannot effectively monitor the real-time changing force conditions during construction, and are prone to ignore local force anomalies or potential safety hazards. In addition, with the continuous increase in building height and construction scale, the demand for dynamic monitoring and real-time early warning of formwork force is becoming more and more urgent. Therefore, the development of an intelligent monitoring system that can monitor the force conditions of tall formwork construction in real time and dynamically and provide safety warnings has become an important demand in the current technical field. Summary of the invention

[0003] To achieve the above object, the present invention provides the following technical solutions:

[0004] A high-rise formwork construction safety monitoring system, including a formwork data acquisition module, a dynamic load analysis module, an interpolation module, a time window analysis module, an adjacent area comprehensive analysis module, and an early warning module;

[0005] The template data acquisition module collects data in real time through the sensor network, collecting the stress data of different foundation areas pre-divided by each tall template at the construction site;

[0006] The dynamic load analysis module analyzes the stress data of each foundation area in real time, dynamically adjusts the division of the stress area, and obtains the adjusted optimized areas;

[0007] The interpolation module performs interpolation processing based on the stress data of the optimized area to ensure smooth transition of the data and transmit the transition results to the time window analysis module to avoid misjudgment due to sudden changes;

[0008] The time window analysis module uses a sliding time window to average the stress data in the optimization area and generates its own fluctuation coefficient;

[0009] The adjacent area comprehensive analysis module is used to conduct a comprehensive analysis of the loads of adjacent optimization areas, consider the interaction between different areas, and generate the adjacent area influence coefficient;

[0010] Based on fuzzy logic, the early warning module performs fuzzy processing on the fluctuation coefficient of each optimized area and the influence coefficient of adjacent areas to generate the risk level of the optimized area.

[0011] In a preferred embodiment, a tall formwork construction safety monitoring system also includes a construction report generation module, which is used to record the operation status of the formwork data acquisition module, dynamic load analysis module, interpolation module, time window analysis module, adjacent area comprehensive analysis module and early warning module to generate a construction safety report.

[0012] In a preferred embodiment, the force condition data includes load, stress, displacement and vibration data.

[0013] In a preferred embodiment, the dynamic load analysis module dynamically adjusts the division of the stress area by analyzing the stress condition data of each foundation area in real time, and the adjusted optimization areas are:

[0014] The stress conditions of the foundation area are re-divided by the K-means clustering algorithm. The K-means clustering algorithm classifies the foundation areas with similar stress conditions into one category according to the similarity of the stress conditions of the foundation areas, thereby dynamically adjusting the division of the stress areas. The objective function is:

[0015] ; is the objective function, is the total number of base regions, is the number of stress-bearing areas, that is, the total number of optimization areas to be divided in the end. is the force data point of the ith foundation area, is the center point of the jth optimization area, Represents the calculation base area data point and the optimized regional center The Euclidean distance between

[0016] The ultimate goal is to minimize the objective function , and obtain the adjusted optimization areas.

[0017] In a preferred embodiment, when minimizing the objective function During the process, the stress and displacement of adjacent areas are checked for continuity to ensure that the adjusted area division will not produce mutations or discontinuities. Specifically:

[0018] Continuity formula check formula 1: Stress for each base area and adjacent areas Perform a continuity check, ;

[0019] Continuity formula check formula 2: displacement of each base area and adjacent areas Perform a continuity check, ; R is the set of all adjacent areas adjacent to the base area. The average stress value of all adjacent areas in the set needs to satisfy the continuity formula check formula 1, and the average displacement value needs to satisfy the continuity formula check formula 2;

[0020] , All are preset error values;

[0021] If the optimization area division result does not meet the continuity check conditions, the optimization area needs to be re-divided.

[0022] In a preferred embodiment, the interpolation module performs interpolation processing based on the force condition data of the optimization area, which means:

[0023] At the moment when the base area is merged or split, the force data of the optimized area is interpolated. The interpolation formula is:

[0024] ; It represents the force data set of the optimized area obtained at the moment when the base area is merged or split. It represents the force data set of a basic area closest to the center point of the optimization area before the dynamic adjustment. It represents the set of average force data of all adjacent basic areas at the moment before the dynamic adjustment of the basic area closest to the center point of the optimization area. is the preset adjustment factor.

[0025] In a preferred embodiment, the time window analysis module performs an average analysis on the stress condition data of the optimization area through a sliding time window, and generates its own fluctuation coefficient, which refers to:

[0026] Use HDi to mark the load, stress, displacement, and vibration amplitude. i represents the type of data. Use the sliding time window analysis method to obtain the average load, average stress, average displacement, and average vibration amplitude within the time window, and then perform the following calculations:

[0027] ; Indicates the preset scale factor, Indicates the total number of times data is collected within the time window. Represents the coefficient of self-volatility.

[0028] In a preferred embodiment, the adjacent region comprehensive analysis module is used to perform a comprehensive analysis on the loads of adjacent optimization regions, taking into account the interaction between different regions, and generating the adjacent region influence coefficient means:

[0029] Obtain the load data Lj from each adjacent area, and calculate the distance weight based on the distance between the adjacent area j and the current area. : ; is the attenuation coefficient, The value is greater than 1. Indicates the distance between the adjacent area and the current optimized area;

[0030] Calculate the load weight based on the load size of the adjacent area , load weight The load data Lj of the adjacent area j is obtained by the sum of the load data of all adjacent areas;

[0031] The calculation formula of the adjacent area influence coefficient is:

[0032] ; k represents the total number of adjacent regions, Represents the adjacent area influence coefficient.

[0033] In a preferred embodiment, the early warning module performs fuzzy processing on the own fluctuation coefficient of each optimized area and the influence coefficient of the adjacent area based on fuzzy logic, and generates the risk level of the optimized area, which refers to:

[0034] The optimization area's own fluctuation coefficient and the adjacent area's influence coefficient are taken as input variables, and the risk level of the optimization area is taken as the output variable. The input variables are fuzzified and their values ​​are converted into fuzzy sets. The output variables are fuzzified and their values ​​are converted into fuzzy sets. Fuzzy rules are formulated to describe the construction safety under different data type combinations. The fuzzified input variables are inferred through fuzzy rules to obtain the risk level of the optimization area.

[0035] Technical effects and advantages of the present invention:

[0036] The present invention can obtain the stress conditions of tall templates in the construction process in real time through the template data acquisition module, covering four data indicators: load, stress, displacement and vibration, to ensure dynamic monitoring of the construction site. This real-time data acquisition can timely reflect the stress changes during the construction process, which helps to prevent structural instability or accidents caused by abnormal stress.

[0037] Through the dynamic load analysis module, the present invention can intelligently and dynamically adjust the division of stress areas according to the stress conditions of each foundation area, optimize the area division, and improve the accuracy of monitoring. This function ensures that even if the stress distribution changes during the construction process, the system can respond quickly, adjust the monitoring area in time, and ensure the reliability of the data.

[0038] An important purpose of the present invention is to better control and accurately locate local dangerous areas. Through real-time analysis and regional adjustment of force data, the present invention can accurately identify local high-risk areas, avoid large-scale blind inspections, and thus improve the safety management efficiency of the construction site.

[0039] The interpolation module can avoid system misjudgment caused by instantaneous data mutations by smoothly processing the stress conditions, ensuring the continuity and consistency of data. This processing method reduces false alarms caused by data mutations during the monitoring process and improves the judgment accuracy of the system.

[0040] The time window analysis module uses a sliding time window to average the force data of each optimized area and generate its own fluctuation coefficient, which can effectively capture the force trend in the area and avoid misjudgment caused by short-term fluctuations. Combined with the interactive impact analysis of the adjacent area comprehensive analysis module, the system can more comprehensively evaluate the construction safety situation.

[0041] Through fuzzy logic processing, the present invention can use the self-fluctuation coefficient of the optimized area and the influence coefficient of the adjacent area as input variables, perform fuzzy processing and generate risk levels. This intelligent early warning mechanism can integrate multiple data, dynamically adjust the risk assessment level, help construction personnel to promptly discover potential safety hazards, and take corresponding preventive measures. The system also has a construction report generation function, which can record the operation of each module, generate a detailed construction safety report, provide construction safety assessment and traceability basis, and help project managers to promptly understand the construction progress and risk situation, thereby improving management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0043] Figure 1 The schematic diagram of a high-rise template construction safety monitoring system in the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] refer to Figure 1 The following examples are obtained:

[0046] Embodiment 1: A high-rise formwork construction safety monitoring system comprises a formwork data acquisition module, a dynamic load analysis module, an interpolation module, a time window analysis module, an adjacent area comprehensive analysis module, and an early warning module; the formwork data acquisition module, the dynamic load analysis module, the interpolation module, the time window analysis module, the adjacent area comprehensive analysis module, and the early warning module are communicatively connected with each other.

[0047] The template data acquisition module monitors the stress of the tall templates at the construction site in real time, and collects data through the sensor network to ensure the timeliness and accuracy of the data. The pre-divided foundation area makes the monitoring of the stress situation more refined, which helps to discover potential risks and ensure construction safety.

[0048] The dynamic load analysis module dynamically adjusts the division of the stress area by analyzing the real-time stress data. This module ensures that the system can adapt to changes in the construction process, identify which areas need more attention, and optimize the stress area at the best time to prevent uneven stress from causing safety problems.

[0049] When the stress conditions in the base area are adjusted, the interpolation module ensures smooth data transition to avoid system misjudgment due to sudden changes in values. Through interpolation processing, data continuity is maintained, ensuring the monitoring system's correct identification of emergencies and reducing false alarms or missed alarms.

[0050] The time window analysis module uses a sliding time window to perform an average analysis of the stress conditions, which can effectively reduce the errors caused by fluctuations in a short period of time and generate a more stable self-fluctuation coefficient. This analysis method can reflect long-term change trends and avoid misjudgments due to short-term data fluctuations, thereby improving the accuracy of construction safety monitoring.

[0051] The adjacent area comprehensive analysis module takes into account the mutual influence between adjacent areas, comprehensively analyzes the load conditions of adjacent areas, and calculates the influence coefficient of adjacent areas. The significance of this module is that the construction area is not isolated, and the stress changes in adjacent areas may affect the stress state of the current area. Comprehensively considering this mutual influence can more comprehensively monitor construction safety.

[0052] Based on fuzzy logic, the early warning module conducts a comprehensive analysis of the optimization area's own fluctuation coefficient and the influence coefficient of adjacent areas to generate a risk level. By fuzzifying the input data, the early warning module can handle complex and ambiguous situations, thereby accurately assessing the safety risks of each area and issuing alarms, providing construction personnel with timely safety tips and preventing major accidents.

[0053] The load data include load, stress, displacement and vibration data.

[0054] Load is the external force that the formwork structure bears during the construction process, such as the weight of building materials, equipment, and construction personnel. During the construction process, the load may change at any time, especially when constructing on the formwork support, the accumulation of materials such as concrete and steel bars will gradually increase the load. Therefore, real-time monitoring of the load is crucial to prevent overloading accidents.

[0055] Stress refers to the force (such as tensile stress, compressive stress, shear stress, etc.) generated inside the material under the action of external loads. It directly reflects the internal state of the formwork material or supporting structure during the stress process. Stress monitoring can help evaluate whether the structure has approached the material's bearing limit and discover potential failure points in time. Excessive stress may cause cracks, damage or local buckling of the formwork material, thereby affecting the safety of the overall structure.

[0056] Displacement refers to the deformation or displacement of the formwork or supporting structure under the action of force, which reflects the degree of deformation of the structure. Including changes in different directions such as horizontal displacement and vertical displacement, the displacement in the present invention can be obtained by constructing a rectangular coordinate system, and the distance between the initial position and the current position of the coordinates to obtain the numerical quantification of the displacement data. Displacement is an early sign of structural instability or instability. By monitoring the displacement, it can be determined whether the formwork has undergone abnormal displacement or settlement after bearing the load. If the displacement exceeds the range allowed by the design, it means that the formwork or support system may be at risk of failure.

[0057] Vibration is a dynamic response that may occur when a formwork structure is subjected to force. During construction, vibration may be caused by mechanical equipment, ground vibration, wind load and other factors. In the construction of tall formwork, vibration data can help identify the dynamic stability of the structure. Excessive vibration may cause hidden dangers such as loosening of the formwork and loosening of bolts, which in turn affects the overall stability of the formwork system. In addition, vibration may gradually accumulate in the continuous changes in construction loads, leading to structural fatigue or local failure. Therefore, monitoring vibration can help detect these potential problems in a timely manner.

[0058] The dynamic load analysis module analyzes the stress data of each foundation area in real time and dynamically adjusts the division of the stress area. The adjusted optimized areas are:

[0059] The stress conditions of the foundation area are re-divided by the K-means clustering algorithm. The K-means clustering algorithm classifies the foundation areas with similar stress conditions into one category according to the similarity of the stress conditions of the foundation areas, thereby dynamically adjusting the division of the stress areas. The objective function is:

[0060] ; is the objective function, is the total number of base regions, is the number of stress-bearing areas, that is, the total number of optimization areas to be divided in the end. is the force data point of the ith foundation area, is the center point of the jth optimization area, Represents the calculation base area data point and the optimized regional center Euclidean distance between the force data points In fact, it contains multiple data sets of the base area, namely, load, stress, displacement and vibration. Each stress area, i.e., the adjusted optimization area, may contain data points of multiple base areas. is the average value of all data points in the force area. The ultimate goal is to minimize the objective function , and the adjusted optimization areas are obtained. The areas that have not been changed are not considered as optimization areas, but may be considered as adjacent areas of the target optimization area in the future.

[0061] K-means clustering algorithm is a commonly used unsupervised learning algorithm for grouping data based on similarity between them. During the construction process, the stress data of the foundation area is taken as input, and the algorithm classifies them into multiple optimization areas according to the similarity of these data. Process description: First, the stress data of the foundation area at the construction site is collected. The stress conditions of each foundation area, including parameters such as load, stress, displacement, etc., are input into the algorithm. Next, the algorithm will preset a goal to divide all foundation areas into several different groups (i.e., optimization areas). The number of these groups is set in advance, called the "number of optimization areas". Then the algorithm will randomly select several foundation areas as the initial "center points", which represent the core of each optimization area. After that, the algorithm will calculate the similarity between each foundation area and each center point (similarity can be measured by calculating the difference in stress conditions). The foundation area will be assigned to the optimization area that is most similar to it. After the assignment is completed, the algorithm will recalculate the center point of each optimization area to make it more accurately represent the stress conditions of the area. This process will be repeated many times until each foundation area is accurately classified into the most appropriate optimization area and the center point no longer changes significantly.

[0062] In the construction of tall formwork, each foundation area may be subjected to different loads and stresses. Therefore, dynamic adjustments need to be made based on the actual stress conditions to ensure that each area can withstand a reasonable load. Dividing the foundation area into optimized areas helps to conduct a more detailed analysis of the force distribution to avoid the stress conditions in a certain area being ignored. During the construction process, the stress conditions will change with time and operation. The division of optimized areas can be dynamically adjusted based on the new stress data to ensure the safety of the entire construction process. By optimizing the division of areas, overload and abnormal stress in local areas can be discovered in a timely manner to prevent structural instability or accidents.

[0063] When using the dynamic load analysis module, follow the following preset strategies: you can set the load difference threshold, stress difference threshold, load safety threshold, and stress safety threshold. According to the changes in the force data of the foundation area, it is determined in real time whether the area division needs to be adjusted. The adjustment includes the following three situations:

[0064] Region merging: A difference threshold can be set for comparison. When the load and stress differences between adjacent foundation regions i and j are small, that is, both are smaller than the corresponding difference threshold and are within the safety threshold range, they can be merged into a new region.

[0065] Area segmentation: When the load or stress of a foundation area i exceeds the safety threshold, the area is divided into two or more new sub-areas in order to find the most dangerous sub-area for precise positioning.

[0066] The region does not change: When the region is dynamically divided and transformed, only the newly divided region and its adjacent regions are analyzed locally without recalculating the entire structure. The region that does not change can be ignored, which can also reduce the computational burden.

[0067] In minimizing the objective function During the process, the stress and displacement of adjacent areas are checked for continuity to ensure that the adjusted area division will not produce mutations or discontinuities. Specifically:

[0068] Continuity formula check formula 1: Stress for each base area and adjacent areas Perform a continuity check, ;

[0069] Continuity formula check formula 2: displacement of each base area and adjacent areas Perform a continuity check, ; R is the set of all adjacent areas adjacent to the base area. The average stress value of all adjacent areas in the set needs to satisfy the continuity formula check formula 1, and the average displacement value needs to satisfy the continuity formula check formula 2;

[0070] , All are preset error values;

[0071] If the optimization area division result does not meet the continuity check conditions, the optimization area needs to be re-divided.

[0072] Continuity check can ensure that the stress conditions of each area remain smooth and controllable in the adjusted optimization area, preventing local failure caused by mutation. When re-dividing the area, if there is no continuity check, the stress changes between the areas may be too drastic. The continuity check can monitor the stress conditions of adjacent areas to ensure that the transition between them is smooth and there is no obvious unevenness. Continuity check can help filter out unreasonable division results and ensure that the division of the optimization area is based on the actual stress conditions. This can avoid wrong adjustments or illogical area divisions, thereby improving the credibility and accuracy of the data. When performing K-means clustering, the algorithm may give some preliminary division results, which sometimes lead to excessive force differences between some areas. Continuity check ensures that any unreasonable divisions will be re-checked during the adjustment process of each optimization area, and then reasonable re-division will be performed to optimize the planning of the entire area. By performing continuity checks on the stress conditions, the system can readjust the area division in time in the case of discontinuity or irrationality.

[0073] The interpolation module performs interpolation processing based on the force data of the optimized area, which means:

[0074] At the moment when the base area is merged or split, the force data of the optimized area is interpolated. The interpolation formula is:

[0075] ; It represents the force data set of the optimized area obtained at the moment when the base area is merged or split. It represents the force data set of a basic area closest to the center point of the optimization area before the dynamic adjustment. It represents the set of average force data of all adjacent basic areas at the moment before the dynamic adjustment of the basic area closest to the center point of the optimization area. is the preset adjustment factor.

[0076] When foundation areas are merged or split, the stress conditions change. If interpolation is not performed, the system may think that this is an emergency or anomaly, which may lead to misjudgment. Interpolation can smooth the data when merging or splitting to avoid misjudgment and ensure that the system accurately analyzes the stress changes in the construction area. Interpolation can ensure that when the foundation area is divided into optimized areas, the stress data will not suddenly jump. Smoothing makes the data in the time series coherent and reduces discontinuities, which is crucial for long-term monitoring of construction safety.

[0077] In the interpolation processing formula, the force data not only depends on the current optimized area data, but also combines the previous historical data of the adjacent foundation area. This means that when interpolating, the system takes into account both the past force conditions of the area and the force changes in the surrounding areas. This method can more comprehensively reflect the force state of the current area and help improve the accuracy of the data. During the construction process, the force conditions in the foundation area continue to change with the progress of construction, and interpolation processing provides a flexible dynamic adjustment mechanism. Through the adjustment coefficient in the formula, the degree of influence of the interpolation can be set according to the construction requirements to ensure that the data processing results can reflect the actual situation, thereby improving the accuracy of monitoring.

[0078] The time window analysis module uses a sliding time window to average the stress data in the optimization area and generates its own fluctuation coefficient, which refers to:

[0079] Use HDi to mark the load, stress, displacement, and vibration amplitude. i represents the type of data. Use the sliding time window analysis method to obtain the average load, average stress, average displacement, and average vibration amplitude within the time window, and then perform the following calculations:

[0080] ; Indicates the preset scale factor, Indicates the total number of times data is collected within the time window. Represents the coefficient of self-volatility.

[0081] HDi marks different types of data, including load, stress, displacement and vibration amplitude. With these data, the stress condition of the area can be comprehensively measured. i represents the type of data (for example, the first type is load, the second type is stress, etc.). The sliding time window method is used to analyze the data in the optimization area. The sliding time window is a commonly used data analysis method that allows capturing data change trends over a continuous time period instead of focusing on the situation at a certain moment, which can better reflect the changes in the time dimension.

[0082] The logarithmic function can compress the magnitude of data differences, so that areas with large fluctuations can be significantly amplified, while areas with small fluctuations will not be overly exaggerated. In this way, the changing trend of the force data can be captured more sensitively. Adding 1 is to avoid negative values ​​of the logarithmic function.

[0083] The difference between each data point in the time window and the average value of the data of this type is calculated. The square will have a greater amplification effect on large differences and a smaller effect on small differences. In some cases, this will lead to oversensitivity to areas with large fluctuations, while the response to areas with small fluctuations is not obvious. By using the power of one half (i.e., the square root), the amplification effect on large differences can be reduced, so that a reasonable balance is maintained for larger fluctuations while retaining sufficient sensitivity to small fluctuations. In actual construction, the fluctuation of stress conditions often does not have extreme and huge changes, but relatively gentle and gradual changes. Using the square root of the difference can more accurately capture the actual stress fluctuations without exaggerating certain short-term and drastic changes.

[0084] Each data type (load, stress, displacement, vibration amplitude) is assigned a weighting factor based on its importance. This weighting factor is set according to a preset ratio in order to adjust the influence of different data in the calculation of the fluctuation coefficient. For example, load may be more important than vibration amplitude, so the weighting of load will be relatively large.

[0085] The larger the value of the self-fluctuation coefficient, the greater the data fluctuation of the optimized area in the current time window, indicating that the stress situation in the area is unstable. This may be due to changes in the stress during the construction process, or problems with some supporting structures in the area. The greater the fluctuation, the higher the risk in the construction process.

[0086] The adjacent area comprehensive analysis module is used to conduct a comprehensive analysis of the loads of adjacent optimization areas, taking into account the interaction between different areas. The adjacent area influence coefficient is generated to refer to:

[0087] Obtain the load data Lj from each adjacent area, and calculate the distance weight based on the distance between the adjacent area j and the current area. : ; is the attenuation coefficient, The value is greater than 1. Represents the distance between the adjacent region and the current optimization region. The distance weight indicates that the influence of the adjacent region j on the current optimization region decreases as the distance increases. The farther the adjacent region is, the weaker the force is, and the closer it is, the greater the influence is.

[0088] Calculate the load weight based on the load size of the adjacent area , load weight The load data Lj of the adjacent area j is obtained by adding the load data of all adjacent areas; the load weight is calculated according to the size of the load data of the adjacent area, which reflects the influence of the load of the adjacent area on the current optimization area. The larger the load proportion, the more significant the influence on the current area, and the better it can capture the force interaction between the areas;

[0089] The calculation formula of the adjacent area influence coefficient is:

[0090] ; k represents the total number of adjacent regions, Represents the adjacent area influence coefficient. The calculation combines all the influences of adjacent areas on the current area. This is obtained by weighted summation of the distance weight, load weight and load data of each adjacent area, which can reflect the overall effect of multiple adjacent areas on the current area. The larger the adjacent area influence coefficient value, the greater the comprehensive influence of the adjacent area on the current area. This may mean that the load of the adjacent area is large or the distance is close, and the force influence on the current area is significantly increased, and there may be a higher force risk.

[0091] The early warning module is based on fuzzy logic, and performs fuzzy processing on the fluctuation coefficient of each optimized area and the influence coefficient of adjacent areas. The risk level of the generated optimized area is:

[0092] The optimization area's own fluctuation coefficient and the adjacent area's influence coefficient are taken as input variables, and the risk level of the optimization area is taken as the output variable. The input variables are fuzzified and their values ​​are converted into fuzzy sets. The output variables are fuzzified and their values ​​are converted into fuzzy sets. Fuzzy rules are formulated to describe the construction safety under different data type combinations. The fuzzified input variables are inferred through fuzzy rules to obtain the risk level of the optimization area.

[0093] The self-fluctuation coefficient and the adjacent area influence coefficient are fuzzified. Fuzzification refers to converting these numerical data into fuzzy sets, which are defined as several fuzzy levels (such as "low", "medium", and "high"). For example, the self-fluctuation coefficient can be fuzzified into "small fluctuation", "medium fluctuation" and "large fluctuation", and the adjacent area influence coefficient can also be similarly fuzzified into "small impact", "medium impact" and "large impact". According to different combinations of input variables, the system formulates a series of fuzzy rules. These rules are used to describe the construction safety under different combinations. For example: If the self-fluctuation coefficient is "large fluctuation" and the adjacent area influence coefficient is "large impact", then the risk level of the optimized area may be "high risk". If the self-fluctuation coefficient is "small fluctuation" and the adjacent area influence coefficient is "small impact", then the risk level may be "low risk". The system can formulate a series of logical rules based on different fluctuations and impact levels, combined with actual construction conditions, to cover all possible input situations.

[0094] After the input variables are fuzzified, the system performs reasoning based on fuzzy rules. Reasoning means that the system combines the fuzzified input variables through rules to obtain a corresponding fuzzified output, that is, the risk level of the optimized area. The output variable (risk level) obtained by reasoning is also a fuzzy set, for example, it can be divided into "low risk", "medium risk" and "high risk". This output can be adjusted according to the actual situation of the construction site to help construction managers evaluate and identify possible safety risks. Finally, the system converts the results of fuzzy reasoning into specific risk levels. The higher the risk level, the greater the safety hazard in the optimized area, which requires higher attention and protective measures.

[0095] Embodiment 2: A high-rise formwork construction safety monitoring system also includes a construction report generation module, which is used to record the operation status of the formwork data acquisition module, dynamic load analysis module, interpolation module, time window analysis module, adjacent area comprehensive analysis module and early warning module to generate a construction safety report.

[0096] The construction report generation module can record the operation status of each module (template data acquisition module, dynamic load analysis module, interpolation module, time window analysis module, adjacent area comprehensive analysis module and early warning module) to ensure that all data of the construction process are systematically saved. This will help to review and trace any problems that occurred during the construction process, and facilitate the analysis of the cause of the accident or the optimization of the construction process.

[0097] Through the generated construction safety reports, project managers can have a detailed understanding of the stress conditions, fluctuations and safety hazards in each area. These reports can serve as a basis for future construction optimization, helping decision makers evaluate indicators such as safety and efficiency, and formulate more reasonable construction strategies.

[0098] The construction safety report can also serve as an important document for the compliance of the construction process to meet the requirements of regulatory agencies. If a safety incident or problem occurs, the report can provide evidence for project compliance and operating standards, proving that the monitoring measures and safety management processes during the construction process are in place.

[0099] In actual use, real-time records and regular reports can also be used to help construction managers quickly identify potential problems and make adjustments. The report generation module records changes in monitoring data to provide construction personnel with early warning signals and reduce the occurrence of unexpected accidents.

[0100] For example: Suppose that the stress condition in the foundation area of ​​a tall formwork construction site has changed. The stress condition is processed by the dynamic load analysis module, and the stress area division is adjusted. The interpolation module smoothes the adjusted data to ensure that the change will not be misjudged as a sudden risk. The time window analysis module records the average stress condition of this area over a period of time and generates the fluctuation coefficient of the area. The adjacent area comprehensive analysis module also finds that the adjacent area has a high load and generates a large adjacent area influence coefficient. The early warning module generates a higher risk level based on its own fluctuation coefficient and the adjacent area influence coefficient, and triggers an early warning signal, records all this information and generates a construction safety report.

[0101] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

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

[0103] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0104] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0105] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A high-rise formwork construction safety monitoring system, characterized in that: It includes template data acquisition module, dynamic load analysis module, interpolation module, time window analysis module, adjacent area comprehensive analysis module, and early warning module; The template data acquisition module collects data in real time through the sensor network, collecting the stress data of different foundation areas pre-divided by each tall template at the construction site; The dynamic load analysis module analyzes the stress data of each foundation area in real time, dynamically adjusts the division of the stress area, and obtains the adjusted optimized areas; The interpolation module performs interpolation processing based on the stress data of the optimized area to ensure smooth transition of the data and transmit the transition results to the time window analysis module to avoid misjudgment due to sudden changes; The time window analysis module uses a sliding time window to average the stress data in the optimization area and generates its own fluctuation coefficient; The adjacent area comprehensive analysis module is used to conduct a comprehensive analysis of the loads of adjacent optimization areas, consider the interaction between different areas, and generate the adjacent area influence coefficient; Based on fuzzy logic, the early warning module performs fuzzy processing on the fluctuation coefficient of each optimized area and the influence coefficient of adjacent areas to generate the risk level of the optimized area; The time window analysis module uses a sliding time window to average the stress data in the optimization area and generates its own fluctuation coefficient, which refers to: Use HDp to mark the load, stress, displacement, and vibration amplitude. p represents the type of data. Use the sliding time window analysis method to obtain the average load, average stress, average displacement, and average vibration amplitude within the time window, and then perform the following calculations: ; Indicates the preset scale factor, Indicates the total number of times data is collected within the time window. represents the coefficient of self-volatility; The adjacent area comprehensive analysis module is used to conduct a comprehensive analysis of the loads of adjacent optimization areas, taking into account the interaction between different areas. The adjacent area influence coefficient is generated to refer to: Obtain the load data Lm from each adjacent area, and calculate the distance weight based on the distance between the adjacent area m and the current area. ; is the attenuation coefficient, The value is greater than 1. Indicates the distance between the adjacent area and the current optimized area; Calculate the load weight based on the load size of the adjacent area , load weight The load data Lm of the adjacent area m is obtained by the sum of the load data of all adjacent areas; The calculation formula of the adjacent area influence coefficient is: ; M represents the total number of adjacent regions, Represents the adjacent area influence coefficient.

2. A tall formwork construction safety monitoring system according to claim 1, characterized in that: It also includes a construction report generation module, which is used to record the operation status of the template data acquisition module, dynamic load analysis module, interpolation module, time window analysis module, adjacent area comprehensive analysis module and early warning module, and generate a construction safety report.

3. A high-rise formwork construction safety monitoring system according to claim 2, characterized in that: The load data include load, stress, displacement and vibration data.

4. A high-rise formwork construction safety monitoring system according to claim 3, characterized in that: The dynamic load analysis module analyzes the stress data of each foundation area in real time and dynamically adjusts the division of the stress area. The adjusted optimized areas are: The stress conditions of the foundation area are re-divided by the K-means clustering algorithm. The K-means clustering algorithm classifies the foundation areas with similar stress conditions into one category according to the similarity of the stress conditions of the foundation areas, thereby dynamically adjusting the division of the stress areas. The objective function is: ; is the objective function, is the total number of base regions, is the number of stress-bearing areas, that is, the total number of optimization areas to be divided in the end. is the force data point of the ith foundation area, is the center point of the jth optimization area, Represents the calculation base area data point and the optimized regional center The Euclidean distance between The ultimate goal is to minimize the objective function , and obtain the adjusted optimization areas.

5. A high-rise formwork construction safety monitoring system according to claim 4, characterized in that: In minimizing the objective function During the process, the stress and displacement of adjacent areas are checked for continuity to ensure that the adjusted area division will not produce mutations or discontinuities. Specifically: Continuity formula check formula 1: Stress for each base area and adjacent areas Perform a continuity check, ; Continuity formula check formula 2: displacement of each base area and adjacent areas Perform a continuity check, ; R is the set of all adjacent areas adjacent to the base area. The average stress value of all adjacent areas in the set needs to satisfy the continuity formula check formula 1, and the average displacement value needs to satisfy the continuity formula check formula 2; , All are preset error values; If the optimization area division result does not meet the continuity check conditions, the optimization area needs to be re-divided.

6. A high-rise formwork construction safety monitoring system according to claim 5, characterized in that: The interpolation module performs interpolation processing based on the force data of the optimized area, which means: At the moment when the base area is merged or split, the force data of the optimized area is interpolated. The interpolation formula is: ; It represents the force data set of the optimized area obtained at the moment when the base area is merged or split. It represents the force data set of a basic area closest to the center point of the optimization area before the dynamic adjustment. It represents the set of average force data of all adjacent basic areas at the moment before the dynamic adjustment of the basic area closest to the center point of the optimization area. is the preset adjustment factor.

7. A high-rise formwork construction safety monitoring system according to claim 6, characterized in that: The early warning module is based on fuzzy logic, and performs fuzzy processing on the fluctuation coefficient of each optimized area and the influence coefficient of adjacent areas. The risk level of the generated optimized area is: The optimization area's own fluctuation coefficient and the adjacent area's influence coefficient are taken as input variables, and the risk level of the optimization area is taken as the output variable. The input variables are fuzzified and their values ​​are converted into fuzzy sets. The output variables are fuzzified and their values ​​are converted into fuzzy sets. Fuzzy rules are formulated to describe the construction safety under different data type combinations. The fuzzified input variables are inferred through fuzzy rules to obtain the risk level of the optimization area.

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