Super high-rise building construction management method and system based on multi-source data

Abstract

The invention belongs to the technical field of construction management, and discloses a super high-rise building construction management method and system based on multi-source data. Comprising the steps that wind condition data of different construction floors in the super high-rise building are collected in real time, and a vertical wind condition zone is formed; performing time domain evolution prediction on the vertical wind regime, and performing multi-source fusion in combination with the obtained weather forecast data to generate a multi-source predicted wind regime; comprehensively analyzing the multi-source predicted wind regime, quantitatively representing wind-induced static effects and wind-induced dynamic effects of different construction floors, calculating environmental comfort and construction safety risks of the different construction floors, and automatically identifying a safety construction time window; construction plans of different construction floors are obtained, and differential recommendation of aerial work tasks is carried out on the safety construction time windows; according to the invention, optimal configuration of construction resources and fine management of the construction process can be realized, and the safety, efficiency and economical efficiency of super high-rise building construction are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of construction management, more particularly, the present application relates to a kind of super high-rise building construction management method and system based on multi-source data. BACKGROUND

[0002] With the acceleration of urbanization and the increasing shortage of land resources, super high-rise buildings, as an important way to expand urban space, are showing a rapid growth trend worldwide. Due to their height characteristics, super high-rise buildings face complex wind environment challenges that ordinary buildings do not have. Related research shows that wind environment is one of the key factors affecting construction safety, progress and quality during the construction process of super high-rise buildings. Currently, wind environment management in super high-rise building construction mainly relies on ground weather station data and experience-based decision-making. However, due to the complexity of urban wind environment and the unique "chimney effect" of super high-rise buildings, there is a significant difference between ground wind conditions and high-altitude wind conditions. Traditional single-point wind condition monitoring methods cannot accurately reflect the wind field characteristics at different heights of super high-rise buildings, resulting in a lack of scientific basis for construction decisions.

[0003] The existing super high-rise building risk management technology mainly has the following shortcomings: one-sidedness of wind condition data collection and prediction: wind condition monitoring systems generally use discrete point layout, making it difficult to form a complete vertical wind condition zone concept. At the same time, the prediction method relies too much on macro meteorological data and lacks detailed consideration of the building microenvironment. Single evaluation of wind-induced effects: existing evaluation methods often consider wind-induced static effects and wind-induced dynamic effects separately, lack comprehensive analysis methods, and cannot fully represent the comprehensive risk under complex wind environment. Experience dependence of construction decisions: construction window identification and high-altitude operation arrangement mainly rely on experience-based judgment, lack of data-driven intelligent decision support, and the scientificity and accuracy of decisions are insufficient.

[0004] In view of this, the present application proposes a super high-rise building construction management method and system based on multi-source data to solve the above problems. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art and achieve the above-mentioned purposes, the present application provides the following technical solution: a super high-rise building construction management method based on multi-source data, comprising: real-time collection of wind condition data at different construction floors of the super high-rise building, and integration of the wind condition data at different construction floors to form a vertical wind condition zone; time-domain evolution prediction of the vertical wind condition zone, and multi-source fusion with the obtained meteorological forecast data to generate a multi-source predicted wind condition zone; comprehensive analysis of the multi-source predicted wind condition zone to quantitatively represent the wind-induced static effects and wind-induced dynamic effects of different construction floors of the super high-rise building under the action of the multi-source wind condition zone. Based on wind-induced static and wind-induced dynamic effects, the environmental comfort and construction safety risks of different construction floors are calculated, and the safe construction time windows of different construction floors are automatically identified according to the environmental comfort and construction safety risks. Obtain construction plans for different floors and make differentiated recommendations for high-altitude work tasks for each safe construction time window based on the construction plans.

[0006] Furthermore, the wind data includes wind speed, wind direction angle, and wind pressure; The content that integrates wind condition data from different construction floors includes: Based on the wind condition data of each construction floor, the wind condition characteristics of each construction floor are obtained. The wind condition characteristics include average wind speed, standard deviation of wind speed, maximum wind speed, prevailing wind direction, average wind pressure, and peak wind pressure. Peak wind pressure includes positive peak wind pressure and negative peak wind pressure. Different construction floors are assigned incrementally increasing numerical labels and marked as floor labels. Each group of wind condition characteristics is sorted from smallest to largest according to the floor label of the corresponding construction floor to form a vertical wind condition zone. The content of time-domain evolution prediction of vertical wind zones includes: Get Historical wind zones and vertical wind zones are collectively referred to as analysis wind zones. The dominant wind direction in each analysis wind zone is sequentially removed to obtain continuous features. The continuous features corresponding to the same construction floor are integrated to form the analysis features for each construction floor. Each set of analysis features is then input into a pre-trained wind prediction model to predict... Continuous characteristics of a series of future moments; collect Based on historical wind direction data and combined with wind angle data, predictions are made. The prevailing wind direction at different construction floors in a continuous future timeframe; By integrating the prevailing wind direction and continuous characteristics at future times, we obtain the future wind zone.

[0007] Furthermore, the content generated for multi-source predicted wind zones includes: Beforehand, wind field simulations were performed on super high-rise buildings under different meteorological forecast data conditions. Wind condition data were collected sequentially from different construction floors within the super high-rise buildings to form corresponding vertical wind condition zones, which were then marked as calibration wind condition zones. For each simulation process, the corresponding vertical wind condition zone was extracted and marked as the simulated wind condition zone. For each simulation process, a mapping relationship between the corresponding meteorological forecast data and the simulated wind condition zone was established to form a wind condition mapping model. Based on the simulated wind condition zone and calibration wind condition zone corresponding to each simulation scenario, a wind condition calibration function was established. Get Meteorological forecast data corresponding to consecutive future moments are input into the wind condition mapping model to obtain the corresponding simulated wind condition zones. These simulated wind condition zones are then corrected using a wind condition calibration function to obtain the meteorological wind condition zones. Corresponding weight coefficients are set for the meteorological wind condition zones and the future wind condition zones. Based on the weight set, the meteorological wind condition zones and the future wind condition zones at the same future moment are weighted and summed to generate multi-source predicted wind condition zones.

[0008] Furthermore, on The multi-source predicted wind conditions at consecutive future moments are analyzed in sequence to quantitatively characterize the wind-induced static and wind-induced dynamic effects of different construction floors at different future moments. The quantitative characterization of wind-induced static effects on different construction floors includes: A preset windward area set is used, which includes the windward area of ​​the super high-rise building at different construction floors and under different prevailing wind directions. Based on the prevailing wind direction corresponding to each construction floor, the windward area corresponding to each construction floor is obtained from the windward area set. Based on the average wind pressure and windward area corresponding to each construction floor, the static thrust of each construction floor is calculated. Based on the positive and negative peak wind pressures corresponding to each construction floor, determine the extreme wind pressure of each construction floor; based on the extreme and average wind pressures corresponding to each construction floor, calculate the wind pressure fluctuation of each construction floor; based on the wind pressure fluctuations, average wind pressures, and preset gust coefficients corresponding to each construction floor, calculate the static pressure of each construction floor. The static effect index of each construction floor is calculated based on the static thrust, static pressure and windward area of ​​each construction floor.

[0009] Furthermore, the quantitative characterization of wind-induced dynamic effects on different construction floors includes: A preset windward width set is provided, which includes the windward width of the super high-rise building at different construction floors and under different prevailing wind directions. Based on the prevailing wind direction corresponding to each construction floor, the windward width corresponding to each construction floor is obtained from the windward width set. Based on the maximum wind speed, windward width, and preset Strauhall number corresponding to each construction floor, the vortex shedding frequency of each construction floor is calculated. Based on the maximum wind speed, average wind speed and vortex shedding frequency of each construction floor, calculate the vortex-induced vibration intensity index of each construction floor. Calculate the turbulence intensity of each construction floor based on the standard deviation and average wind speed of each construction floor; calculate the gust response factor of each construction floor based on the turbulence intensity of each construction floor; calculate the wind pressure ratio of each construction floor based on the extreme wind pressure and average wind pressure of each construction floor. Based on the gust response factor, turbulence intensity, and wind pressure ratio of each construction floor, the gust vibration intensity index of each construction floor is calculated.

[0010] Furthermore, the calculation of environmental comfort and construction safety risks for different construction floors includes: Based on the vortex-induced vibration intensity index and gust vibration intensity index of each construction floor, calculate the dynamic effect index of each construction floor; based on the dynamic effect index of each construction floor, calculate the vibration comfort of each construction floor; based on the static effect index of each construction floor, calculate the wind pressure comfort of each construction floor; based on the vortex-induced vibration standard index and gust vibration intensity index of each construction floor, calculate the operational stability of each construction floor. The environmental comfort of each construction floor is obtained by weighted summation of vibration comfort, wind pressure comfort, and operational stability. Based on the static effect index of each construction floor, calculate the structural safety index of each construction floor; based on the static and dynamic effect indexes of each construction floor, calculate the personnel safety risk of each construction floor; based on the static effect index and gust vibration intensity index of each construction floor, calculate the comprehensive effect index of each construction floor; compare the comprehensive effect index corresponding to the same construction floor with the vortex-induced vibration standard index, and determine the equipment safety risk corresponding to each construction floor based on the comparison results. The construction safety risk of each construction floor is calculated by weighted summation of the structural safety risk, personnel safety risk, and equipment safety risk.

[0011] Furthermore, the content of the safe construction time window for automatically identifying construction floors includes: The system presets comfort and risk thresholds, compares the environmental comfort and construction safety risks of the current floor at different future times with the comfort and risk thresholds respectively; the current floor is the construction floor that is automatically identified during the safe construction time window. If the environmental comfort level at the same future moment is greater than the comfort threshold and the construction safety risk is less than the risk threshold, then the corresponding future moment will be selected as the candidate moment. Get the current floor A collaborative floor is identified, and a collaborative assessment set corresponding to the current floor is constructed. Based on the construction floors in the collaborative assessment set, the comprehensive comfort and comprehensive safety risks of the current floor at different candidate times are calculated, and then compared with the comfort threshold and risk threshold respectively. If the overall comfort level at the same candidate time point is greater than the comfort threshold and the overall safety risk is less than the risk threshold, then the corresponding candidate time point will be used as the construction time point. Connectivity analysis is performed on the construction time corresponding to the current floor to obtain the candidate construction time window corresponding to the current floor; the number of construction times in each candidate construction time window is counted to obtain the construction duration of each candidate construction time window; each construction duration is compared with a preset duration threshold, and the candidate construction time window whose construction duration is greater than the duration threshold is marked as a safe construction time window.

[0012] Furthermore, the differentiated recommendations for high-altitude work tasks within each safe construction time window include: Different numerical labels are assigned to different high-altitude work tasks and marked as task labels. Based on the construction plans for different construction floors, task sets are obtained for each construction floor, including the task labels for all unfinished high-altitude work tasks for that floor. Window characteristic data for each safe construction time window is constructed, and each set of window characteristic data is integrated with the task set for the corresponding construction floor to obtain task characteristic data for each safe construction time window. Each set of task characteristic data is input into a trained task recommendation model to obtain a task recommendation set corresponding to each safe construction time window. The task recommendation set includes... The task vectors are grouped, and each group of task vectors includes a task label and a task priority; Based on the task recommendation set for each safe construction time window, the optimal work task corresponding to each safe construction time window is obtained; the optimal work task corresponding to each safe construction time window is analyzed to determine whether there is a resource competition problem; if there is a resource competition problem, the task adjustment strategy is executed, and the problem is repeatedly checked for resource competition problems; until there is no resource competition problem, differentiated recommendations for high-altitude work tasks are made for each safe construction time window based on the optimal work task corresponding to each safe construction time window.

[0013] Furthermore, the task adjustment strategy includes: By comparing and analyzing the safe construction time windows of each construction floor, multiple sets of intersecting windows are obtained. The sets of intersecting windows include multiple safe construction time windows that have time overlap. For each set of intersection windows, compare the best work tasks for each safe construction time window to determine if there are any identical best work tasks. If there are identical best work tasks, mark the corresponding best work tasks as competing work tasks and count the number of competing tasks for each type of competing work task in each set of intersection windows. Obtain the number of construction resources for each type of competing work task and compare it with the corresponding number of competing tasks. If the number of construction resources is less than the number of competing tasks, mark the corresponding competing work task as an adjustment work task. All safe construction time windows corresponding to the adjusted work tasks are marked as candidate adjustment windows. Each candidate adjustment window is then sorted from highest to lowest priority according to its corresponding task priority, generating a window sequence. The windows ranked later in the sequence are then... The candidate adjustment windows are marked as adjustment windows; the best job corresponding to each adjustment window is adjusted according to the second-best job corresponding to each adjustment window.

[0014] A construction management system for super high-rise buildings based on multi-source data, implementing the aforementioned construction management method for super high-rise buildings based on multi-source data, includes: The wind condition sensing module is used to collect wind condition data of different construction floors in a super high-rise building in real time, and integrate the wind condition data of different construction floors to form a vertical wind condition zone. The wind condition prediction module is used to predict the temporal evolution of vertical wind condition zones and to perform multi-source fusion with the acquired meteorological forecast data to generate multi-source predicted wind condition zones. The effect characterization module is used to comprehensively analyze the multi-source predicted wind conditions and quantitatively characterize the wind-induced static and wind-induced dynamic effects of different construction floors of super high-rise buildings under the action of multi-source wind conditions. The window recognition module is used to calculate the environmental comfort and construction safety risks of different construction floors based on wind-induced static and wind-induced dynamic effects, and automatically identify the safe construction time window for different construction floors according to the environmental comfort and construction safety risks. The task recommendation module is used to obtain the construction plans for different construction floors and make differentiated recommendations for high-altitude operation tasks for each safe construction time window based on the construction plans.

[0015] The technical effects and advantages of the construction management method and system for super high-rise buildings based on multi-source data of this invention are as follows: By collecting real-time three-dimensional wind data from different construction floors and combining it with meteorological forecast data for time-domain prediction and multi-source fusion, a predicted wind band comprehensively reflecting the characteristics of the high-altitude wind environment is generated. This enables high-precision characterization of the wind-induced characteristics of super high-rise building construction sites, improving the accuracy and reliability of wind environment perception. A comprehensive analysis method is employed to quantitatively characterize the static and dynamic effects of super high-rise buildings under complex wind conditions, comprehensively reflecting the impact of wind-induced loads on super high-rise buildings and construction safety, providing a scientific quantitative basis for construction decisions. Based on adaptive analysis of environmental comfort and construction safety risks, it can intelligently identify suitable construction floors for different buildings. The system identifies safe operating time windows for each floor and provides differentiated recommendations for high-altitude operations based on the construction plan, enabling rational allocation of resources to maximize construction safety and operational efficiency. It achieves intelligent management across the entire process, from wind environment perception and load effect assessment to safety decision support, effectively addressing issues in traditional construction management such as insufficient consideration of wind environment impacts, inaccurate construction safety risk assessments, and a lack of scientific basis for work arrangements. This optimizes the allocation of construction resources and refines the management of the construction process, improving the safety, efficiency, and economy of super high-rise building construction, and providing comprehensive intelligent decision support for super high-rise building construction. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a super high-rise building construction management system based on multi-source data according to Embodiment 1 of the present invention; Figure 2 This is a flowchart of a construction management method for super high-rise buildings based on multi-source data, which is an embodiment 2 of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1 Please see Figure 1 As shown in the figure, the super high-rise building construction management system based on multi-source data described in this embodiment includes a wind condition sensing module, a wind condition prediction module, an effect characterization module, a window recognition module, and a job recommendation module; each module is connected through wired and / or wireless means to realize data transmission between modules.

[0019] The wind condition sensing module is used to collect wind condition data of different construction floors in a super high-rise building in real time, and integrate the wind condition data of different construction floors to form a vertical wind condition zone.

[0020] Wind data includes, but is not limited to, wind speed, wind direction angle, and wind pressure; where wind speed refers to the speed at which air flows per unit time, and wind direction angle refers to the angle used (…). ~ () indicates the direction of wind origin, and wind pressure refers to the wind load borne by different construction floors; wind condition data is acquired through multiple ultrasonic anemometers and wind pressure sensors distributed in different construction floors; construction floors refer to the floors in a super high-rise building that are under construction. The content that integrates wind condition data from different construction floors includes: The mean and standard deviation of the wind speed corresponding to each construction floor are calculated to obtain the average wind speed and standard deviation of the wind speed for each construction floor. Based on the wind speed corresponding to each construction floor, the maximum wind speed of each construction floor is obtained. The method for obtaining the maximum wind speed is to compare the wind speeds of the same construction floor and take the wind speed with the largest value as the maximum wind speed of the corresponding construction floor. Divide the continuously changing wind direction angle evenly into One wind direction range, It is an integer greater than 1; where each wind direction interval corresponds to a wind direction type, such as north wind, east wind, northeast wind, etc. For example, the continuously changing wind direction angle is evenly divided into 8 wind direction intervals, i.e. The wind direction ranges are as follows: North wind corresponds to ~ Northeast winds correspond ~ Dongfeng corresponds ~ Southeast winds correspond ~ South wind corresponds ~ Southwest winds correspond ~ West winds correspond ~ Northwest winds correspond ~ ; Based on the wind direction angle corresponding to each construction floor, the frequency of occurrence of each wind direction interval corresponding to each construction floor is counted (i.e., the number of all wind direction angles corresponding to each construction floor entering each wind direction interval is counted); the frequency of occurrence corresponding to the same construction floor is compared, and the wind direction type corresponding to the wind direction interval with the highest frequency of occurrence is taken as the dominant wind direction of the corresponding construction floor. For example, the wind direction angles corresponding to construction floor A are as follows: , , , ,because, and fall into ~ middle, fall into ~ middle, fall into ~ Therefore, the frequency of occurrence of the north wind direction interval is 2, the frequency of occurrence of the northeast wind direction interval and the east wind direction interval is 1, and the frequency of occurrence of the other wind direction intervals is 0. The average wind pressure for each construction floor is calculated. The wind pressure for each floor is then labeled as either positive or negative. Positive wind pressure is defined as a wind pressure with a positive exponent, and negative wind pressure as a wind pressure with a negative exponent. The positive wind pressures for the same construction floor are compared, and the highest positive wind pressure is taken as the peak positive wind pressure for that floor. Similarly, the negative wind pressures for the same construction floor are compared, and the lowest negative wind pressure is taken as the peak negative wind pressure. Both the peak and negative wind pressures are collectively referred to as peak wind pressure. The average wind speed, standard deviation of wind speed, maximum wind speed, prevailing wind direction, average wind pressure, and peak wind pressure corresponding to the same construction floor are integrated to obtain the wind condition characteristics of each construction floor. Different construction floors are assigned incrementally increasing numerical labels, which are marked as floor labels. Among them, the higher the construction floor, the larger the corresponding floor label. Each group of wind condition characteristics is sorted from small to large according to the floor label of the corresponding construction floor to form a vertical wind condition band, which is used to reveal the overall distribution law of wind speed, wind pressure, and wind direction with height in super high-rise buildings, and provide a global basis for subsequent wind-induced effect analysis and construction safety planning.

[0021] The wind condition prediction module is used to predict the temporal evolution of vertical wind condition zones and to perform multi-source fusion with the acquired meteorological forecast data to generate multi-source predicted wind condition zones.

[0022] The content of time-domain evolution prediction of vertical wind zones includes: Get A historical wind zone is a vertical wind zone formed at a historical moment. It is an integer greater than 1; where, The historical wind patterns correspond to consecutive moments, and The latest time corresponding to each historical wind condition band is the time before the real-time time (i.e., the time when wind condition data is collected in real time); Historical wind patterns and vertical wind patterns are collectively referred to as analysis wind patterns. The prevailing wind direction is sequentially removed from each analysis wind pattern to obtain continuous features (i.e., wind pattern features without the prevailing wind direction). The continuous features corresponding to the same construction floor are integrated to form the analysis features for each construction floor. Each set of analysis features is then input into a trained wind prediction model to predict... Continuous characteristics of consecutive future moments It is an integer greater than 1; collect A set of historical wind direction data, including wind direction angles collected at different construction floors at historical times; among them, The historical wind direction data corresponds to consecutive time periods, and The latest time corresponding to a set of historical wind direction data is the time before the real-time time (i.e. the time when wind condition data is collected in real time); The wind direction angles in the wind condition data are integrated into real-time wind direction data, and historical and real-time wind direction data are collectively referred to as analytical wind direction data. The wind direction angles in the analytical wind direction data are then converted into corresponding wind direction vectors, the form of which is... , The wind direction angle is determined by combining the wind direction vectors corresponding to the same construction floor and time from the analyzed wind direction data to form a comprehensive vector. Then, the comprehensive vectors corresponding to the same construction floor from the analyzed wind direction data are combined to form wind direction features. Each set of wind direction features is input into the trained wind direction prediction model to predict the wind direction angle. The composite vector of consecutive future moments, and the determination The prevailing wind direction at different construction floors in consecutive future moments; the wind direction vector in each predicted composite vector is sequentially converted into the corresponding wind direction angle, according to... Determine the wind direction angle corresponding to different construction floors at consecutive future moments. The prevailing wind direction at different construction floors in a continuous future timeframe; By integrating the prevailing wind direction and continuous characteristics at future moments, we obtain the future wind zone; that is, by sequentially acquiring... The system generates future wind zones at consecutive future moments, enabling the prediction of the temporal evolution of vertical wind zones.

[0023] Both the wind condition prediction model and the wind direction prediction model are RNN neural network models, meaning their training processes are identical, differing only in the input and output data. This embodiment uses the wind condition prediction model as an example to illustrate the training process, specifically as follows: Pre-continuous collection Group the continuous features of the same construction floor and construct a training set. Based on the training set, train a wind condition prediction model that predicts continuous features in future moments; The sliding step size is preset based on the practical experience of those skilled in the art. and the length of the sliding window In this embodiment, the preferred embodiment is... =1; The continuous features within the training set are transformed into multiple training samples using a sliding window method, with each training sample containing continuous features. Grouped continuous features; each training sample is used as input to the wind condition prediction model to predict the sliding step size. The subsequent continuous features are used as output, and the subsequent features of each training sample are used as output. Using continuous features as prediction targets, the model accuracy is evaluated using the mean absolute percentage error (MAPE) on the prediction results. When the calculated MAPE is less than the preset error threshold, the wind condition prediction model training is completed, generating a wind condition prediction model that predicts the continuous features at the next moment based on multiple sets of continuous features. The error threshold is preset by those skilled in the art according to the prediction accuracy requirements of the wind condition prediction model.

[0024] For example, training set It contains 10 consecutive features. Define a sliding window with a length of 3 and a step size of 1. Use the sliding window to construct 7 training samples. Each training sample contains 3 consecutive features. The next consecutive feature after the first 3 consecutive features is used as the prediction target; that is, the training samples... Training samples The corresponding prediction target is Training samples Training samples The corresponding prediction target is Similarly, this is used to train wind condition prediction models.

[0025] The content of generating multi-source predicted wind conditions includes: CFD simulations of the wind field around the super high-rise building were performed under different meteorological forecast data conditions. Wind condition data of different construction floors within the super high-rise building were collected sequentially to form corresponding vertical wind condition zones, which were then marked as calibration wind condition zones. The meteorological forecast data, including wind speed and wind direction type, was obtained through API interfaces provided by third-party meteorological service providers (such as Moji Weather and Hefeng Weather). It should be noted that CFD simulation of the wind field around the building based on meteorological forecast data is an existing technology, and the specific process will not be elaborated on here. For each simulation process, the corresponding vertical wind bands are extracted sequentially and marked as simulated wind bands. For each simulation process, a mapping relationship between the corresponding meteorological forecast data and the simulated wind bands is established to form a wind condition mapping model. Based on the simulated wind bands and calibration wind bands corresponding to each simulation process, a wind condition calibration function is established to correct the simulated wind bands output by the CFD simulation. The wind condition calibration function is obtained by those skilled in the art by fitting the deviation between the simulated wind bands and the calibration wind bands, and can take the form of linear functions, hierarchical correction functions, etc. Get Meteorological forecast data corresponding to consecutive future moments are input into the wind condition mapping model to obtain the corresponding simulated wind condition zones. These simulated wind condition zones are then corrected using a wind condition calibration function to obtain the meteorological wind condition zones. Weight coefficients are set for the meteorological wind condition zones and the future wind condition zones, with the sum of all weight coefficients being 1. These weight coefficients are preset by those skilled in the art based on the actual situation. Based on the weight set, the meteorological wind condition zones and the future wind condition zones at the same future moment are weighted and summed to generate multi-source predicted wind condition zones.

[0026] It should be noted that the wind condition calibration function only applies to the average wind speed, standard deviation of wind speed, maximum wind speed, average wind pressure, and peak wind pressure in the simulated wind condition zone; while for the prevailing wind direction, the prevailing wind direction in the calibration wind condition zone is directly replaced with the prevailing wind direction in the simulated wind condition zone. It should be understood that, since the future wind condition zone can make full use of the temporal evolution information of the vertical wind condition zone and more accurately reflect the high dependence characteristics of the local wind field of each construction floor, when the prevailing wind direction in the meteorological wind condition zone is different from that in the future wind condition zone, the prevailing wind direction in the future wind condition zone will be used as the prevailing wind direction in the multi-source predicted wind condition zone.

[0027] The effect characterization module is used to comprehensively analyze multi-source predicted wind conditions and quantitatively characterize the wind-induced static and wind-induced dynamic effects of different construction floors under the influence of multi-source wind conditions on super high-rise buildings.

[0028] right The multi-source predicted wind conditions at consecutive future moments are analyzed in sequence to quantitatively characterize the wind-induced static and wind-induced dynamic effects of different construction floors at different future moments. It should be noted that since the quantitative characterization of the wind-induced static and wind-induced dynamic effects of different construction floors is consistent at different future times, this embodiment only takes one future time as an example to explain in detail the quantitative characterization of the wind-induced static and wind-induced dynamic effects of different construction floors.

[0029] The quantitative characterization of wind-induced static effects on different construction floors includes: A preset windward area set is provided, which includes the windward area of ​​the super high-rise building at different construction floors and under different prevailing wind directions. The windward area is the area of ​​the windward side of the construction floor, which is obtained by those skilled in the art through on-site measurement. According to the prevailing wind direction corresponding to each construction floor, the windward area corresponding to each construction floor is obtained from the windward area set. The static thrust corresponding to each construction floor is obtained by calculating the product of the average wind pressure corresponding to each construction floor and the windward area. Based on the positive and negative peak wind pressures corresponding to each construction floor, the extreme wind pressures of each construction floor are determined. The method for determining the extreme wind pressures is as follows: take the absolute value of the negative peak wind pressure corresponding to the construction floor to obtain the extreme peak wind pressure; compare the positive peak wind pressure corresponding to the construction floor with the extreme peak wind pressure, and take the larger of the two as the extreme wind pressure; calculate the difference between the extreme wind pressure and the average wind pressure corresponding to each construction floor to obtain the wind pressure fluctuation corresponding to each construction floor; calculate the product of the wind pressure fluctuation corresponding to each construction floor and the preset gust coefficient, and add it to the corresponding average wind pressure to obtain the static pressure corresponding to each construction floor; wherein, the gust coefficient is preset by those skilled in the art according to the actual situation, and in this embodiment, the preferred gust coefficient is 0.85; Based on the static thrust, static pressure, and windward area of ​​each construction floor, the static effect index for each construction floor is calculated to quantitatively characterize the wind-induced static effect of different construction floors; the expression for the static effect index is: ; In the formula, As a static effect index, For static thrust, For static pressure, For windward area, air density (values ​​are given) ), The acceleration due to gravity (with values ​​of...) ), The height of the construction floor above the ground; wherein, the height of the construction floor above the ground is obtained by a person skilled in the art through on-site measurement.

[0030] The quantitative characterization of wind-induced dynamic effects at different construction floors includes: A preset set of windward widths is provided, which includes the windward widths of the super high-rise building at different construction floors and under different prevailing wind directions. The windward width is the width of the windward surface of each construction floor, obtained by those skilled in the art through on-site measurement. Based on the prevailing wind direction corresponding to each construction floor, the windward width corresponding to each construction floor is obtained from the set of windward widths. The ratio of the maximum wind speed to the windward width corresponding to each construction floor is calculated sequentially, and then multiplied by a preset Strouhal number to obtain the vortex shedding frequency corresponding to each construction floor. The Strouhal number is preset by those skilled in the art based on the shape of the windward surface corresponding to the construction floor; in this embodiment, the preferred range for the Strouhal number is [insert range here]. ; Based on the maximum wind speed, average wind speed, and vortex shedding frequency of each construction floor, the vortex-induced vibration intensity index for each construction floor is calculated. This index is used to quantitatively characterize the vibration intensity caused by vortex shedding under wind conditions on different construction floors. The expression for the vortex-induced vibration intensity index is: ; In the formula, This is an index of vortex-induced vibration intensity. At maximum wind speed, The average wind speed, The frequency of vortex shedding. The natural frequency of the super high-rise building (i.e., the characteristic frequency of the super high-rise building when it undergoes free vibration without external force); wherein, the natural frequency of the super high-rise building is determined by those skilled in the art through on-site measurement.

[0031] The ratio of the standard deviation of wind speed to the average wind speed for each construction floor is calculated sequentially to obtain the turbulence intensity for each construction floor. Based on the turbulence intensity of each construction floor, the gust response factor for each construction floor is calculated; the expression for the gust response factor is: ; In the formula, For gust response factor, Roughness factor The turbulence intensity is defined as follows: The roughness factor is an empirical coefficient reflecting the influence of the roughness of the underlying surface (such as urban areas, rural areas, open farmland, etc.) on the wind speed turbulence characteristics of the supertall building. Since supertall buildings are typically located in urban core areas or city centers, this embodiment... ; The extreme wind pressure to average wind pressure ratio of each construction floor is calculated sequentially to obtain the wind pressure ratio of each construction floor. The gust response factor, turbulence intensity and wind pressure ratio of each construction floor are multiplied sequentially to obtain the gust vibration intensity index of each construction floor, which is used to quantitatively characterize the vibration intensity and wind load fluctuation effect of different construction floors under gust action.

[0032] It should be noted that the average wind speed, wind speed standard deviation, maximum wind speed, prevailing wind direction, average wind pressure, and peak wind pressure used in the above quantitative characterization of wind-induced static and dynamic effects on different construction floors are all derived from multi-source predicted wind conditions.

[0033] It should be understood that static thrust refers to the resultant horizontal force generated by wind on a super high-rise building. Taking into account the average wind pressure and the windward area, it is a basic parameter for assessing the overall lateral stability of the building. Static pressure takes into account the average wind pressure and wind pressure fluctuations. By adding the gust coefficient correction, it can more accurately characterize the actual pressure effect of wind on the surface of a super high-rise building. Vortex shedding frequency refers to the frequency at which vortices alternately form and shed on both sides of a supertall building as airflow passes around it. It is determined by the maximum wind speed and the windward width and shape of the windward side, and is the fundamental cause of vortex-induced vibration. Turbulence intensity is a parameter that characterizes the degree of turbulence in a wind field and directly affects the pulsating characteristics of wind loads and the dynamic response of a supertall building. Gust response factor comprehensively considers turbulence intensity, roughness factor, and structural characteristics, and is used to characterize the degree of amplification of the dynamic response of a supertall building under gusts relative to the average wind load.

[0034] The window recognition module is used to calculate the environmental comfort and construction safety risks of different construction floors based on wind-induced static and wind-induced dynamic effects, and automatically identify the safe construction time window for different construction floors according to the environmental comfort and construction safety risks.

[0035] based on The wind-induced static and dynamic effects at consecutive future moments are used to calculate the environmental comfort and construction safety risks of different construction floors at different future moments. It should be noted that since the calculation of environmental comfort and construction safety risks for different construction floors is the same at different future times, this embodiment only takes one future time as an example to explain in detail the calculation of environmental comfort and construction safety risks for different construction floors.

[0036] The calculation of environmental comfort and construction safety risks for different construction floors includes: The vortex-induced vibration intensity index and gust vibration intensity index corresponding to each construction floor are normalized to obtain the standard vortex-induced vibration index and gust vibration index corresponding to each construction floor. The normalization method is, for example, minimum-maximum normalization, exponential normalization, etc. The standard vortex-induced vibration index and the standard gust vibration index are respectively set with corresponding weighting coefficients, and the sum of all weighting coefficients is 1. These weighting coefficients are preset by those skilled in the art according to the actual situation. Based on the weighting coefficients, the standard vortex-induced vibration index and the standard gust vibration index corresponding to each construction floor are weighted and summed to obtain the dynamic effect index corresponding to each construction floor. A vibration comfort threshold is preset to control the sensitivity of vibration comfort to dynamic effect. In this embodiment, the vibration comfort threshold is preferably 0.15. The ratio of the dynamic effect index corresponding to each construction floor to the vibration comfort threshold is calculated, and the negative number is taken. Then, it is processed by the natural exponential function (i.e., the exponential function with the natural constant as the base) to obtain the vibration comfort level corresponding to each construction floor, which reflects the degree of influence of the vibration of the construction floor on human comfort. A preset wind pressure comfort threshold is used to control the sensitivity of wind pressure comfort to static effects. In this embodiment, the preferred wind pressure comfort threshold is 0.3. The ratio of the static effect index corresponding to each construction floor to the wind pressure comfort threshold is calculated to obtain the relative wind pressure intensity ratio corresponding to each construction floor. The relative wind pressure intensity ratio corresponding to each construction floor is squared sequentially, then one is added, and the reciprocal is taken to obtain the wind pressure comfort corresponding to each construction floor, which is used to reflect the degree of direct impact of wind pressure on personnel activities. Calculate the difference between the standard index of vortex-induced vibration corresponding to each construction floor and obtain the vortex-induced vibration stability factor corresponding to each construction floor; calculate the difference between the standard index of gust vibration corresponding to each construction floor and half of the standard index of gust vibration corresponding to each construction floor and obtain the gust vibration stability factor corresponding to each construction floor; calculate the product of the vortex-induced vibration stability factor and the gust vibration stability factor corresponding to each construction floor and obtain the operational stability corresponding to each construction floor, which is used to reflect the stability when performing delicate operations (such as welding, bolt installation, etc.). Weighting factors are set for vibration comfort, wind pressure comfort, and operational stability, with the sum of all weighting factors being 1. These factors are preset by those skilled in the art based on actual conditions. Based on the weighting factors, the vibration comfort, wind pressure comfort, and operational stability of each construction floor are weighted and summed to obtain the environmental comfort of each construction floor.

[0037] Calculate twice the static effect index corresponding to each construction floor, take the opposite number, and then process it through the natural exponential function to obtain the structural safety index corresponding to each construction floor; calculate the difference between the index and the structural safety index corresponding to each construction floor to obtain the structural safety risk corresponding to each construction floor, which is used to reflect the risk of wind load causing damage to the structure of each construction floor itself. Calculate the sum of half and one of the static effect index corresponding to each construction floor, multiply it by the corresponding dynamic effect index, and then normalize it to obtain the personnel safety risk corresponding to each construction floor, which is used to reflect the comprehensive safety risk of personnel performing high-altitude operations on each construction floor. The static effect indices for each construction floor are normalized to obtain the static standard indices for each floor. The sum of half the static standard indices and half the corresponding gust vibration standard indices for each floor is calculated to obtain the comprehensive effect indices for each floor. The comprehensive effect indices for the same floor are compared with the vortex-induced vibration standard indices. Based on the comparison results, the equipment safety risks for each floor are determined to reflect the operational safety risks of construction equipment (such as tower cranes and construction elevators). The method for determining the equipment safety risks for each floor based on the comparison results is as follows: if the comprehensive effect index is greater than or equal to the vortex-induced vibration standard index, then the comprehensive effect index is considered the equipment safety risk; if the comprehensive effect index is less than the vortex-induced vibration standard index, then the vortex-induced vibration standard index is considered the equipment safety risk. Weighting factors are set for structural safety risks, personnel safety risks, and equipment safety risks respectively, and the sum of all weighting factors is 1. These factors are preset by those skilled in the art based on the actual situation. Based on the weighting factors, the structural safety risks, personnel safety risks, and equipment safety risks corresponding to each construction floor are weighted and summed to obtain the construction safety risks corresponding to each construction floor.

[0038] The content of the safe construction time window for automatically identifying construction floors includes: The system presets comfort and risk thresholds, comparing the environmental comfort and construction safety risks of the current floor at different future times with the comfort and risk thresholds respectively. The current floor is the construction floor automatically identified during the safe construction time window. Both the comfort and risk thresholds are preset by those skilled in the art based on actual conditions. If the environmental comfort level at the same future moment is greater than the comfort threshold and the construction safety risk is less than the risk threshold, then the corresponding future moment will be selected as the candidate moment. If the environmental comfort level at the same future moment is less than or equal to the comfort threshold, or the construction safety risk is greater than or equal to the risk threshold, then the corresponding future moment will not be considered as a candidate moment. Get the current floor One collaborative floor, It is an integer greater than 1; where the cooperating floor is the construction floor adjacent to the current floor; according to the current floor's corresponding... For each collaborative floor, a collaborative evaluation set corresponding to the current floor is constructed. The collaborative evaluation set includes the current floor and its corresponding floor. The collaborative assessment set includes several floors; based on the environmental comfort and construction safety risks of each construction floor at different candidate times, the comprehensive comfort and comprehensive safety risks of the current floor at different candidate times are calculated; the comprehensive comfort and comprehensive safety risks of the current floor at different candidate times are then compared with the comfort threshold and the risk threshold, respectively. If the overall comfort level at the same candidate time point is greater than the comfort threshold and the overall safety risk is less than the risk threshold, then the corresponding candidate time point will be used as the construction time point. If the environmental comfort level at the same candidate time is less than or equal to the comfort threshold, or the comprehensive safety risk is greater than or equal to the risk threshold, then the corresponding candidate time will not be used as the construction time. A connectivity analysis is performed on the construction time corresponding to the current floor (i.e., consecutive construction time moments are merged) to obtain candidate construction time windows for the current floor; the number of construction time moments within each candidate construction time window is counted to obtain the construction duration of each candidate construction time window; the construction duration of each candidate construction time window is compared with a preset duration threshold, which is preset by those skilled in the art based on actual conditions; candidate construction time windows with a construction duration greater than the duration threshold are marked as safe construction time windows, while candidate construction time windows with a construction duration less than or equal to the duration threshold are not marked.

[0039] The calculation process for overall comfort is as follows: compare the environmental comfort levels corresponding to each construction floor in the collaborative evaluation set, and take the environmental comfort level with the lowest value as the overall comfort level; The calculation process for comprehensive safety risk is as follows: the average safety risk is calculated by averaging the construction safety risk of each construction floor in the collaborative assessment set; the product of the average safety risk and the preset contribution coefficient is calculated, and then the maximum safety risk is added to obtain the comprehensive safety risk; wherein, the maximum safety risk is the construction safety risk with the largest value among all construction safety risk levels corresponding to the collaborative assessment set; the contribution coefficient is preset by those skilled in the art according to the actual situation, and in this embodiment, the preferred contribution coefficient is 0.1.

[0040] It should be understood that the two-stage judgment mechanism for determining the construction time reflects a progressive evaluation strategy from the local to the overall. The first judgment is based on the current floor's own conditions for preliminary screening, quickly eliminating obviously unsuitable times for construction and reducing the amount of calculation. The second judgment considers the synergistic effects of adjacent floors, comprehensively evaluating the coupling effect of multiple floors to avoid safety hazards caused by neglecting the interaction between floors. This approach ensures both computational efficiency and the comprehensiveness and safety of construction decisions, making it suitable for complex scenarios of multi-floor parallel construction in super high-rise buildings and effectively identifying truly safe and reliable safe construction time windows.

[0041] The task recommendation module is used to obtain the construction plans for different construction floors and make differentiated recommendations for high-altitude operation tasks for each safe construction time window based on the construction plans.

[0042] The construction plan refers to the list of unfinished high-altitude work tasks for the current construction floor, which is obtained through the super high-rise building construction management system. The list of high-altitude work tasks includes all unfinished high-altitude work tasks, such as steel structure hoisting, high-altitude concrete pouring, and formwork installation. The differentiated recommendations for high-altitude work tasks for each safe construction time window include: Different numerical labels are set for different high-altitude work tasks and marked as task labels; the wind-induced static effect, vortex-induced vibration intensity index, gust vibration intensity index, comprehensive comfort, comprehensive safety risk and construction time corresponding to each safe construction time window are used as window characteristic data for the corresponding safe construction time window; according to the construction plan of different construction floors, the task set of each construction floor is obtained, and the task set includes the task labels of all unfinished high-altitude work tasks on the corresponding construction floor. Each set of window characteristic data is integrated with the corresponding task set for the construction floor to obtain task characteristic data for each safe construction time window. Each set of task characteristic data is then input into a trained task recommendation model to obtain a task recommendation set corresponding to each safe construction time window. The task recommendation set includes... Group task vectors, This refers to the number of task tags in the task characteristic data corresponding to the safe construction window; each task vector includes task tags and task priorities. The task recommendation model is a deep neural network model, which includes an input layer, hidden layers, and an output layer. Each hidden layer contains multiple neurons, and each neuron is connected to the neurons in the next layer. The connections contain weights that determine the importance and influence of the data in the neural network. An activation function is applied to each neuron between the hidden layer and the output layer. The activation function introduces non-linearity, allowing the network to learn more complex patterns and features. It should be noted that the training samples used to train the task recommendation model were collected in advance by those skilled in the art. Group different task characteristic data, The integer is greater than 1; based on practical experience, the window characteristic data in each group of task characteristic data is analyzed, and according to the analysis results, the corresponding task priority is set for each task label in each group of task characteristic data in sequence, thereby obtaining... The task recommendation set corresponding to the group task characteristic data; based on We use different task characteristic data and corresponding task recommendation sets to construct training samples for training a task recommendation model.

[0043] Based on the task recommendation set for each safe construction time window, the optimal work task corresponding to each safe construction time window is obtained. The optimal work task is the high-altitude work task corresponding to the task tag with the highest task priority in the task recommendation set. The optimal work tasks corresponding to each safe construction time window are analyzed to determine whether there is a resource competition problem. If there is a resource competition problem, a task adjustment strategy is implemented, and the problem is repeatedly checked until there is no resource competition problem. Based on the optimal work task corresponding to each safe construction time window, differentiated recommendations for high-altitude work tasks are made for each safe construction time window.

[0044] The task adjustment strategy includes: The safe construction time windows of each construction floor are compared and analyzed to obtain multiple sets of intersecting windows. The sets of intersecting windows include multiple safe construction time windows that have time overlap. For example, safe construction time window 1 is 08:00-12:00 and safe construction time window 2 is 10:00-14:00. Since the two windows have an overlap in the period from 10:00 to 12:00, safe construction time window 1 and safe construction time window 2 are taken as a set of intersecting windows. For each set of intersection windows, the best work tasks for each safe construction time window are compared to determine if there are identical best work tasks. If identical best work tasks exist, they are marked as competing work tasks, and the number of competing tasks for each type of competing work task within each set of intersection windows is counted. The number of competing tasks corresponds to the number of safe construction time windows for each competing work task. The number of construction resources for each type of competing work task is obtained and compared with the corresponding number of competing tasks. The number of construction resources refers to the number of resources used to complete high-altitude work tasks, such as the number of available tower cranes and concrete pump trucks, which are obtained through the super high-rise building construction management system. If the number of construction resources is less than the number of competing tasks, the corresponding competing work task is marked as an adjustment work task. If the number of construction resources is greater than the number of competing tasks, the competing work task is not marked. All safe construction time windows corresponding to the adjusted work tasks are marked as candidate adjustment windows, and all candidate adjustment windows belong to the same set of intersection windows. Each candidate adjustment window is sorted from highest to lowest according to its corresponding task priority (i.e., the task priority corresponding to the adjusted work task), generating a window sequence. The windows ranked later in the window sequence are then sorted... The candidate adjustment window for a given bit is marked as the adjustment window. ;in, Indicates the number of competitors. This indicates the quantity of construction resources. Based on the suboptimal task corresponding to each adjustment window, the optimal task corresponding to each adjustment window is adjusted. The suboptimal task is a high-altitude operation task in the task recommendation set whose task priority is adjacent to the task priority of the current optimal task in the corresponding adjustment window, and the task priority of the suboptimal task is lower than the task priority of the corresponding optimal task in the corresponding adjustment window.

[0045] It should be understood that the purpose of formulating task adjustment strategies is to resolve the resource competition problem between overlapping safe construction time windows during the construction of super high-rise buildings, ensure that limited construction resources can be rationally allocated, and thus maximize construction efficiency while ensuring construction safety.

[0046] This embodiment collects real-time three-dimensional wind data from different construction floors and combines it with meteorological forecast data for time-domain prediction and multi-source fusion to generate a predicted wind band that comprehensively reflects the characteristics of the high-altitude wind environment. This allows for a high-precision characterization of the wind-induced characteristics of the super high-rise building construction site, improving the accuracy and reliability of wind environment perception. A comprehensive analysis method is used to quantitatively characterize the static and dynamic effects of super high-rise buildings under complex wind conditions, comprehensively reflecting the impact of wind-induced loads on super high-rise buildings and construction safety, providing a scientific quantitative basis for construction decisions. Based on adaptive analysis of environmental comfort and construction safety risks, it can intelligently identify suitable construction methods for different levels of construction. The system identifies safe working time windows for each floor and provides differentiated recommendations for high-altitude work tasks based on the construction plan, enabling rational allocation of resources to maximize construction safety and operational efficiency. It achieves intelligent management across the entire process, from wind environment perception and load effect assessment to safety decision support, effectively addressing issues in traditional construction management such as insufficient consideration of wind environment impacts, inaccurate construction safety risk assessments, and a lack of scientific basis for work arrangements. This optimizes the allocation of construction resources and refines the management of the construction process, improving the safety, efficiency, and economy of super high-rise building construction, and providing comprehensive intelligent decision support for super high-rise building construction.

[0047] Example 2 Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A method for construction management of super high-rise buildings based on multi-source data is provided, the method including: Real-time wind condition data of different construction floors in super high-rise buildings is collected and integrated to form a vertical wind condition zone. The temporal evolution of vertical wind zones is predicted, and multi-source fusion is performed in combination with the acquired meteorological forecast data to generate multi-source predicted wind zones. A comprehensive analysis of multi-source predicted wind conditions was conducted to quantitatively characterize the wind-induced static and wind-induced dynamic effects on different construction floors of super high-rise buildings under the influence of multi-source wind conditions. Based on wind-induced static and wind-induced dynamic effects, the environmental comfort and construction safety risks of different construction floors are calculated, and the safe construction time windows of different construction floors are automatically identified according to the environmental comfort and construction safety risks. Obtain construction plans for different floors and make differentiated recommendations for high-altitude work tasks for each safe construction time window based on the construction plans.

[0048] Example 3 This application also provides an electronic device. The electronic device may include one or more processors and one or more memories. The memories store computer-readable code, which, when executed by the one or more processors, can perform the multi-source data-based construction management method for super high-rise buildings as described above.

[0049] The method or system according to the embodiments of this application can also be implemented using the architecture of the electronic device shown in this application. The electronic device may include a bus, one or more CPUs, ROM, RAM, a communication port connected to a network, input / output, a hard disk, etc. The storage device in the electronic device, such as a ROM or hard disk, may store the construction management method for super high-rise buildings based on multi-source data provided in this application. Furthermore, the electronic device may also include a user interface. Of course, the architecture shown in this application is merely exemplary; when implementing different devices, one or more components of the electronic device shown in this application may be omitted according to actual needs.

[0050] Example 4 One embodiment of this application discloses a computer-readable storage medium. The computer-readable storage medium stores computer-readable instructions. When the computer-readable instructions are executed by a processor, a construction management method for super high-rise buildings based on multi-source data, as described in the above-described embodiments of this application, can be performed. The storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0051] Furthermore, according to embodiments of this application, the processes described in the above-referenced flowcharts can be implemented as computer software programs. For example, this application provides a non-transitory machine-readable storage medium storing machine-readable instructions that can be executed by a processor to perform instructions corresponding to the method steps provided in this application, such as a method for construction management of super high-rise buildings based on multi-source data. When this computer program is executed by a central processing unit (CPU), it performs the functions defined in the method of this application.

[0052] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0053] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0054] In the description of this invention, it should be understood that the terms "first," "second," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0055] In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0056] In the description of this invention, "several" means one or more, and "a large number" means two or more.

[0057] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0058] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0059] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A construction management method for super high-rise buildings based on multi-source data, characterized in that, include: Real-time wind condition data of different construction floors in super high-rise buildings is collected and integrated to form a vertical wind condition zone. The temporal evolution of vertical wind zones is predicted, and multi-source fusion is performed in combination with the acquired meteorological forecast data to generate multi-source predicted wind zones. A comprehensive analysis of multi-source predicted wind conditions was conducted to quantitatively characterize the wind-induced static and wind-induced dynamic effects on different construction floors of super high-rise buildings under the influence of multi-source wind conditions. Based on wind-induced static and wind-induced dynamic effects, the environmental comfort and construction safety risks of different construction floors are calculated, and the safe construction time windows of different construction floors are automatically identified according to the environmental comfort and construction safety risks. Obtain construction plans for different floors and make differentiated recommendations for high-altitude work tasks for each safe construction time window based on the construction plans.

2. The construction management method for super high-rise buildings based on multi-source data according to claim 1, characterized in that, Wind data includes wind speed, wind direction angle, and wind pressure; The content that integrates wind condition data from different construction floors includes: Based on the wind condition data of each construction floor, the wind condition characteristics of each construction floor are obtained. The wind condition characteristics include average wind speed, standard deviation of wind speed, maximum wind speed, prevailing wind direction, average wind pressure, and peak wind pressure. Peak wind pressure includes positive peak wind pressure and negative peak wind pressure. Different construction floors are assigned incrementally increasing numerical labels and marked as floor labels. Each group of wind condition characteristics is sorted from smallest to largest according to the floor label of the corresponding construction floor to form a vertical wind condition zone. The content of time-domain evolution prediction of vertical wind zones includes: Get Historical wind zones and vertical wind zones are collectively referred to as analysis wind zones. The dominant wind direction in each analysis wind zone is sequentially removed to obtain continuous features. The continuous features corresponding to the same construction floor are integrated to form the analysis features for each construction floor. Each set of analysis features is then input into a pre-trained wind prediction model to predict... Continuous characteristics of a series of future moments; collect Based on historical wind direction data and combined with wind angle data, predictions are made. The prevailing wind direction at different construction floors in a continuous future timeframe; By integrating the prevailing wind direction and continuous characteristics at future times, we obtain the future wind zone.

3. The construction management method for super high-rise buildings based on multi-source data according to claim 2, characterized in that, The content of generating multi-source predicted wind conditions includes: Beforehand, wind field simulations were performed on super high-rise buildings under different meteorological forecast data conditions. Wind condition data were collected sequentially from different construction floors within the super high-rise buildings to form corresponding vertical wind condition zones, which were then marked as calibration wind condition zones. For each simulation process, the corresponding vertical wind condition zone was extracted and marked as the simulated wind condition zone. For each simulation process, a mapping relationship between the corresponding meteorological forecast data and the simulated wind condition zone was established to form a wind condition mapping model. Based on the simulated wind condition zone and calibration wind condition zone corresponding to each simulation scenario, a wind condition calibration function was established. Get Meteorological forecast data corresponding to consecutive future moments are input into the wind condition mapping model to obtain the corresponding simulated wind condition zones. These simulated wind condition zones are then corrected using a wind condition calibration function to obtain the meteorological wind condition zones. Corresponding weight coefficients are set for the meteorological wind condition zones and the future wind condition zones. Based on the weight set, the meteorological wind condition zones and the future wind condition zones at the same future moment are weighted and summed to generate multi-source predicted wind condition zones.

4. The construction management method for super high-rise buildings based on multi-source data according to claim 3, characterized in that, right The multi-source predicted wind conditions at consecutive future moments are analyzed in sequence to quantitatively characterize the wind-induced static and wind-induced dynamic effects of different construction floors at different future moments. The quantitative characterization of wind-induced static effects on different construction floors includes: The preset windward area set includes the windward area of ​​the super high-rise building at different construction floors and under different prevailing wind directions; Based on the prevailing wind direction corresponding to each construction floor, the windward area corresponding to each construction floor is obtained from the windward area concentration; based on the average wind pressure and windward area corresponding to each construction floor, the static thrust of each construction floor is calculated. Based on the positive and negative peak wind pressures corresponding to each construction floor, determine the extreme wind pressure of each construction floor; based on the extreme and average wind pressures corresponding to each construction floor, calculate the wind pressure fluctuation of each construction floor; based on the wind pressure fluctuations, average wind pressures, and preset gust coefficients corresponding to each construction floor, calculate the static pressure of each construction floor. The static effect index of each construction floor is calculated based on the static thrust, static pressure and windward area of ​​each construction floor.

5. The construction management method for super high-rise buildings based on multi-source data according to claim 4, characterized in that, The quantitative characterization of wind-induced dynamic effects at different construction floors includes: A preset windward width set is provided, which includes the windward width of the super high-rise building at different construction floors and under different prevailing wind directions. Based on the prevailing wind direction corresponding to each construction floor, the windward width corresponding to each construction floor is obtained from the windward width set. Based on the maximum wind speed, windward width, and preset Strauhall number corresponding to each construction floor, the vortex shedding frequency of each construction floor is calculated. Based on the maximum wind speed, average wind speed and vortex shedding frequency of each construction floor, calculate the vortex-induced vibration intensity index of each construction floor. Calculate the turbulence intensity of each construction floor based on the standard deviation and average wind speed of each construction floor; calculate the gust response factor of each construction floor based on the turbulence intensity of each construction floor; calculate the wind pressure ratio of each construction floor based on the extreme wind pressure and average wind pressure of each construction floor. Based on the gust response factor, turbulence intensity, and wind pressure ratio of each construction floor, the gust vibration intensity index of each construction floor is calculated.

6. The construction management method for super high-rise buildings based on multi-source data according to claim 5, characterized in that, The calculation of environmental comfort and construction safety risks for different construction floors includes: Based on the vortex-induced vibration intensity index and gust vibration intensity index of each construction floor, calculate the dynamic effect index of each construction floor; based on the dynamic effect index of each construction floor, calculate the vibration comfort of each construction floor; based on the static effect index of each construction floor, calculate the wind pressure comfort of each construction floor; based on the vortex-induced vibration standard index and gust vibration intensity index of each construction floor, calculate the operational stability of each construction floor. The environmental comfort of each construction floor is obtained by weighted summation of vibration comfort, wind pressure comfort, and operational stability. Based on the static effect index of each construction floor, calculate the structural safety index of each construction floor; based on the static and dynamic effect indexes of each construction floor, calculate the personnel safety risk of each construction floor; based on the static effect index and gust vibration intensity index of each construction floor, calculate the comprehensive effect index of each construction floor; compare the comprehensive effect index corresponding to the same construction floor with the vortex-induced vibration standard index, and determine the equipment safety risk corresponding to each construction floor based on the comparison results. The construction safety risk of each construction floor is calculated by weighted summation of the structural safety risk, personnel safety risk, and equipment safety risk.

7. The construction management method for super high-rise buildings based on multi-source data according to claim 6, characterized in that, The content of the safe construction time window for automatically identifying construction floors includes: The system presets comfort and risk thresholds, compares the environmental comfort and construction safety risks of the current floor at different future times with the comfort and risk thresholds respectively; the current floor is the construction floor that is automatically identified during the safe construction time window. If the environmental comfort level at the same future moment is greater than the comfort threshold and the construction safety risk is less than the risk threshold, then the corresponding future moment will be selected as the candidate moment. Get the current floor A collaborative floor is identified, and a collaborative assessment set corresponding to the current floor is constructed. Based on the construction floors in the collaborative assessment set, the comprehensive comfort and comprehensive safety risks of the current floor at different candidate times are calculated, and then compared with the comfort threshold and risk threshold respectively. If the overall comfort level at the same candidate time point is greater than the comfort threshold and the overall safety risk is less than the risk threshold, then the corresponding candidate time point will be used as the construction time point. Connectivity analysis is performed on the construction time corresponding to the current floor to obtain the candidate construction time window corresponding to the current floor; the number of construction times in each candidate construction time window is counted to obtain the construction duration of each candidate construction time window; each construction duration is compared with a preset duration threshold, and the candidate construction time window whose construction duration is greater than the duration threshold is marked as a safe construction time window.

8. The construction management method for super high-rise buildings based on multi-source data according to claim 7, characterized in that, The differentiated recommendations for high-altitude work tasks for each safe construction time window include: Different numerical labels are assigned to different high-altitude work tasks and marked as task labels. Based on the construction plans for different construction floors, task sets are obtained for each construction floor, including the task labels for all unfinished high-altitude work tasks for that floor. Window characteristic data for each safe construction time window is constructed, and each set of window characteristic data is integrated with the task set for the corresponding construction floor to obtain task characteristic data for each safe construction time window. Each set of task characteristic data is input into a trained task recommendation model to obtain a task recommendation set corresponding to each safe construction time window. The task recommendation set includes... The task vectors are grouped, and each group of task vectors includes a task label and a task priority; Based on the task recommendation set for each safe construction time window, the optimal work task corresponding to each safe construction time window is obtained; the optimal work task corresponding to each safe construction time window is analyzed to determine whether there is a resource competition problem; if there is a resource competition problem, the task adjustment strategy is executed, and the problem is repeatedly checked for resource competition problems; until there is no resource competition problem, differentiated recommendations for high-altitude work tasks are made for each safe construction time window based on the optimal work task corresponding to each safe construction time window.

9. A construction management method for super high-rise buildings based on multi-source data according to claim 8, characterized in that, The task adjustment strategy includes: By comparing and analyzing the safe construction time windows of each construction floor, multiple sets of intersecting windows are obtained. The sets of intersecting windows include multiple safe construction time windows that have time overlap. For each set of intersection windows, compare the best work tasks for each safe construction time window to determine if there are any identical best work tasks. If there are identical best work tasks, mark the corresponding best work tasks as competing work tasks and count the number of competing tasks for each type of competing work task in each set of intersection windows. Obtain the number of construction resources for each type of competing work task and compare it with the corresponding number of competing tasks. If the number of construction resources is less than the number of competing tasks, mark the corresponding competing work task as an adjustment work task. All safe construction time windows corresponding to the adjusted work tasks are marked as candidate adjustment windows. Each candidate adjustment window is then sorted from highest to lowest priority according to its corresponding task priority, generating a window sequence. The windows ranked later in the sequence are then... The candidate adjustment windows are marked as adjustment windows; the best job corresponding to each adjustment window is adjusted according to the second-best job corresponding to each adjustment window.

10. A construction management system for super high-rise buildings based on multi-source data, implementing the construction management method for super high-rise buildings based on multi-source data as described in any one of claims 1-9, characterized in that, include: The wind condition sensing module is used to collect wind condition data of different construction floors in a super high-rise building in real time, and integrate the wind condition data of different construction floors to form a vertical wind condition zone. The wind condition prediction module is used to predict the temporal evolution of vertical wind condition zones and to perform multi-source fusion with the acquired meteorological forecast data to generate multi-source predicted wind condition zones. The effect characterization module is used to comprehensively analyze the multi-source predicted wind conditions and quantitatively characterize the wind-induced static and wind-induced dynamic effects of different construction floors of super high-rise buildings under the action of multi-source wind conditions. The window recognition module is used to calculate the environmental comfort and construction safety risks of different construction floors based on wind-induced static and wind-induced dynamic effects, and automatically identify the safe construction time window for different construction floors according to the environmental comfort and construction safety risks. The task recommendation module is used to obtain the construction plans for different construction floors and make differentiated recommendations for high-altitude operation tasks for each safe construction time window based on the construction plans.

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