An image recognition-based main tower construction safety intelligent management and control system

Abstract

The application relates to the technical field of construction safety management, in particular to a main tower construction safety intelligent management and control system based on image recognition, which comprises a plurality of management and control terminals, each of which is provided with an elevation positioning chip and an interaction device; a demand setting module, which is used to determine the expected distance of each management and control terminal in each detection period in the moving process based on the construction range; a positioning module, which is used to determine the actual position of the management and control terminal; a model construction module, which is used to generate a digital twin model; an association module, which is used to associate each management and control terminal with the construction personnel model; a mapping construction module, which is used to construct the mapping relationship between the management and control terminal and the construction personnel model; and an analysis module, which is used to analyze whether the movement of the management and control terminal is qualified based on the comparison result of the actual distance and the expected distance. The application improves the accuracy of the analysis of the moving track of the management and control terminal and further improves the precision of the main tower construction safety management and control.

Description

Technical Field

[0001] This invention relates to the field of construction safety management technology, and in particular to an intelligent control system for main tower construction safety based on image recognition. Background Technology

[0002] Traditional main tower construction safety management relies primarily on manual inspections and on-site supervision. This approach has several drawbacks. For instance, manual inspections have limited frequency and coverage, making it difficult to monitor the dynamic status of construction personnel and equipment in a real-time and comprehensive manner. On-site supervision is also susceptible to human factors, such as fatigue and negligence, leading to the failure to promptly identify and address safety hazards. Furthermore, the complex and variable environment of construction sites, including weather changes, material storage, and equipment operation, increases the difficulty of safety management. Although some construction safety management systems currently employ positioning technology, the positioning accuracy is often insufficient and easily affected by environmental factors such as building obstructions and electromagnetic interference, resulting in inaccurate positioning results that fail to meet the high-precision requirements of construction safety management.

[0003] For example, Chinese Patent Publication No. CN117474321B discloses a method and system for intelligent risk identification at construction sites based on BIM models, including the following steps: A: collecting modeling information; B: constructing a BIM model; C: creating a safety rule set using BIM software; D: setting up Bluetooth beacons, fixed image acquisition devices, mobile image acquisition devices, and GPS positioning devices; based on the safety rule set, GPS positioning technology, Bluetooth beacon positioning technology, and image recognition technology, if the location of construction personnel and / or the image shows a situation that does not comply with fall prevention safety rules or passage safety rules, the processing module notifies the designated supervisor through an alarm device. This invention can effectively perform real-time intelligent identification and early warning of various risks at construction sites, thereby eliminating safety hazards during construction, improving the timeliness and accuracy of risk identification at construction sites, and ensuring safe construction.

[0004] However, existing technologies still have the following problems:

[0005] The analysis of the movement trajectory of the control terminal is not accurate enough, and there is a lack of automated analysis and classification capabilities for abnormal data that exceeds the threshold. Summary of the Invention

[0006] To address this, the present invention provides an intelligent control system for main tower construction safety based on image recognition, which overcomes the problems in the prior art where the analysis of the movement trajectory of the control terminal is not accurate enough and there is a lack of automated analysis and classification capabilities for abnormal data that exceeds the threshold.

[0007] To achieve the above objectives, the present invention provides an intelligent control system for main tower construction safety based on image recognition, comprising:

[0008] Several control terminals are equipped with elevation positioning chips and interactive devices;

[0009] The demand setting module, which is connected to the control terminal, is used to determine the expected distance of each control terminal during each detection cycle during the movement based on the construction scope.

[0010] The positioning module, which is connected to the control terminal, includes several deployment elevation positioning chips set at corresponding positions to determine the actual position of the control terminal;

[0011] The model building module is used to generate digital twin models, which include: a main tower model and a construction personnel model;

[0012] The association module is connected to both the control terminal and the model building module to perform association processing between each control terminal and the construction personnel model.

[0013] A mapping construction module, which is connected to the association module, is used to construct a mapping relationship between the control terminal and the construction personnel model, so as to display and mark the movement trajectory of each control terminal in the digital twin model;

[0014] The comparison module is connected to the demand setting module and the positioning module respectively, and is used to determine the actual distance between a single control terminal and the construction area in a single detection cycle during the construction process, and compare the actual distance with the corresponding expected distance;

[0015] The analysis module is connected to the control terminal, the demand setting module, the positioning module, the model building module, the association module, the mapping building module, and the comparison module, respectively. It is used to analyze whether the movement of the control terminal is qualified based on the comparison result of the actual distance and the expected distance. If the movement of the control terminal is initially determined to be unqualified, a second determination is made on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal, or the reasons for the unqualified movement of the control terminal are analyzed.

[0016] Furthermore, the analysis module is used to analyze whether the movement of the control terminal is qualified based on the comparison result of the actual distance and the expected distance, including:

[0017] Calculate the absolute value of the difference between the actual distance and the expected distance to obtain the distance deviation.

[0018] If the distance deviation is less than or equal to the first preset distance deviation, the analysis module determines that the movement of the control terminal is qualified.

[0019] If the distance deviation is greater than the first preset distance deviation and less than or equal to the second preset distance deviation, the analysis module initially determines that the movement of the control terminal is unqualified, and makes a second determination on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal.

[0020] If the distance deviation is greater than the second preset distance deviation, the analysis module determines that the movement of the control terminal is unqualified, and analyzes the reason for the unqualified movement of the control terminal based on the distance deviation.

[0021] Furthermore, the analysis module is used to perform a secondary determination on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal, including:

[0022] If the cumulative movement distance is greater than or equal to the preset cumulative movement distance, the movement of the control terminal is determined to be unqualified, and the reason for the unqualified movement of the control terminal is analyzed based on the distance deviation.

[0023] If the cumulative movement distance is less than the preset cumulative movement distance, the first preset distance deviation is determined to be unqualified, and the first preset distance deviation is corrected based on the cumulative total movement time after the control terminal receives the construction instruction.

[0024] Furthermore, the analysis module is used to correct the first preset distance deviation based on the cumulative total travel time after the control terminal receives the construction instructions, wherein the increase in the first preset distance deviation is negatively correlated with the cumulative total travel time.

[0025] Furthermore, the analysis module is used to analyze the reasons for the non-compliance of the control terminal's movement based on distance deviation, including:

[0026] Calculate the ratio of the second preset distance deviation to the distance deviation itself to obtain the distance deviation ratio.

[0027] If the distance deviation ratio is less than or equal to the first preset distance deviation ratio, then the vertical distance between the position of the control terminal and the position of the construction area at the current time node is determined, and the reason for the unqualified movement of the control terminal is analyzed based on the vertical distance.

[0028] If the distance deviation ratio is greater than the first preset distance deviation ratio and less than or equal to the second preset distance deviation ratio, then it is determined that the distance deviation in the historical record is obtained, and the reason for the failure of the movement of the control terminal is determined a second time based on the time domain dispersion of the distance deviation.

[0029] If the distance deviation ratio is greater than the second preset distance deviation ratio, it is determined to obtain the historical data reception record of the control terminal, and to determine whether a task change has occurred based on the historical data reception record.

[0030] Furthermore, the analysis module is used to analyze the reasons for the non-compliance of the control terminal's movement based on vertical distance, including:

[0031] Calculate the height difference between the location of the control terminal and the location of the construction area at the current time point to obtain the vertical distance.

[0032] If the vertical distance is less than or equal to the preset vertical distance, the reason for the failure of the movement of the control terminal is determined to be a control terminal malfunction, and an alarm signal is issued.

[0033] If the vertical distance is greater than the preset vertical distance, then it is determined that the second preset distance deviation should be corrected based on the vertical distance.

[0034] Furthermore, the analysis module is used to correct the second preset distance deviation based on the vertical distance, wherein the increase in the second preset distance deviation is positively correlated with the vertical distance.

[0035] Furthermore, the analysis module is used to perform a secondary determination of the reasons for the non-compliance of the control terminal's movement based on the time-domain dispersion of the distance deviation, including:

[0036] Obtain historical data on distance deviation.

[0037] Calculate the variance of the distance deviation to obtain the time-domain dispersion.

[0038] If the time-domain dispersion is less than or equal to the preset time-domain dispersion, the reason for the failure of the control terminal's movement is determined to be unreasonable path planning, and a replanning signal is issued.

[0039] If the time-domain dispersion is greater than the preset time-domain dispersion, the reason for the failure of the control terminal's movement is determined to be inaccurate positioning, and an elevation positioning chip is deployed to supplement it.

[0040] Furthermore, the analysis module is used to adjust the number of deployed elevation positioning chips based on the time-domain dispersion, wherein the increase in the number of deployed elevation positioning chips is positively correlated with the time-domain dispersion.

[0041] Furthermore, the analysis module is used to determine whether a task change has occurred based on historical data reception records, including:

[0042] If an updated receiving record exists, it is determined that the construction task of the control terminal has changed, and the construction area and expected distance are re-determined based on the received information.

[0043] If no updated receiving record is found, the reason for the unqualified movement of the control terminal is determined to be a control terminal malfunction, and an alarm signal is issued.

[0044] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention divides the movement status of the control terminal into three levels: qualified, initially unqualified (requiring secondary judgment), and seriously unqualified by setting a first preset distance deviation (qualified threshold) and a second preset distance deviation (severe unqualified threshold). For the case in the "initially unqualified" range (first preset deviation < deviation ≤ second preset deviation), the cumulative movement distance is introduced as a supplementary judgment dimension. If the cumulative movement distance is small (such as short-distance movement), the deviation may be caused by instantaneous interference (such as signal fluctuation), and secondary judgment can avoid misjudgment. If the cumulative movement distance is large (such as long-distance movement), the persistent deviation is more likely to reflect the real anomaly and needs to trigger an early warning. When the deviation exceeds the second preset threshold, the system directly judges it as unqualified and analyzes the cause based on the distance deviation. Through cause analysis, subsequent strategy adjustments can be further driven.

[0045] Furthermore, this invention determines whether the deviation is a single interference or a continuous anomaly by comparing the cumulative movement distance with a preset threshold. In scenarios where signals are easily interfered with (such as urban canyons, mining areas, and indoor construction), traditional single deviation judgment is prone to frequent false alarms, while the cumulative movement distance reflects the overall trend and reduces the impact of environmental interference. The longer the cumulative movement time, the greater the equipment positioning error may be due to factors such as signal cumulative attenuation and equipment heat drift. However, in practical applications, long-term movement (such as all-day construction) is often accompanied by more relaxed fault tolerance requirements. By establishing a negative correlation correction relationship through a machine learning model, the accuracy and practicality are balanced.

[0046] Furthermore, this invention calculates the distance deviation ratio. When the distance deviation ratio is less than or equal to the first preset distance deviation ratio, it directly analyzes the vertical distance between the control terminal and the construction area. This analysis method can accurately locate movement non-compliance issues caused by non-compliance with vertical distance requirements, avoiding blindly investigating other factors and improving the efficiency of problem diagnosis. When the distance deviation ratio is between the first and second preset values, by analyzing the temporal dispersion of the distance deviation in historical records, it can further determine whether there are other dynamic factors (such as changes in the construction environment, equipment failure, etc.) causing movement non-compliance. This secondary judgment method can analyze the problem more comprehensively and avoid misjudgment. The preset values ​​are determined based on data: the first and second preset distance deviation ratios are obtained through statistical analysis of data from a large number of actual construction scenarios. This data-based method ensures the scientificity and rationality of the preset values ​​and avoids errors caused by subjective settings. Through statistical analysis of actual data, it can more accurately reflect the actual situation in the construction scenario, thereby improving the reliability of the entire analysis system.

[0047] Furthermore, by calculating the vertical distance between the control terminal and the construction area, this invention can quickly determine whether a movement failure is caused by a terminal malfunction. When the vertical distance is less than or equal to a preset value, it is directly determined to be a terminal malfunction and an alarm is issued, facilitating timely repair or replacement of the equipment. When the vertical distance is greater than the preset value, a second preset distance deviation is corrected based on the vertical distance. This dynamic adjustment mechanism can more accurately reflect changes in the actual construction environment and avoid misjudgments caused by fixed deviation values. By calculating the variance (time-domain dispersion) of the distance deviation, the cause of the movement failure can be further analyzed. When the variance is less than the preset value, it is determined to be due to unreasonable path planning; when the variance is greater than the preset value, it is determined to be due to unreasonable path planning. When the value is not specified, it is determined that the positioning is inaccurate. This secondary judgment mechanism can analyze the problem more comprehensively and avoid misjudgment due to a single factor. Based on the time domain dispersion, the number of elevation positioning chips deployed can be dynamically adjusted according to changes in the actual construction environment, ensuring the accuracy and reliability of positioning. By establishing a positive correlation model between the vertical distance and the actual distance deviation, the second preset distance deviation can be dynamically corrected. The deviation value can be flexibly adjusted according to changes in the actual construction environment. By establishing a positive correlation model between the time domain dispersion and the number of elevation positioning chips deployed, the number of chips deployed can be dynamically adjusted according to actual positioning needs.

[0048] Furthermore, by checking for updated reception records, this invention can promptly detect changes in the construction tasks of the control terminal. This method ensures rapid response to task changes during construction, avoiding construction chaos or errors caused by untimely handling of task changes. When a task change is detected, the construction area and expected distance are redefined based on the new received information. This dynamic adjustment mechanism ensures that construction parameters remain consistent with the current task, improving the accuracy and efficiency of construction. By clearly distinguishing between task changes and equipment malfunctions, it avoids misjudgments caused by task changes. In the absence of task changes, if the movement of the control terminal is unqualified, it can be clearly determined as an equipment malfunction, and an alarm signal can be issued for timely repair or replacement of the equipment. Attached Figure Description

[0049] Figure 1 This is a structural block diagram of the intelligent control system for main tower construction safety based on image recognition, as described in this invention.

[0050] Figure 2 A flowchart for determining whether the movement of the control terminal is qualified;

[0051] Figure 3 This is a flowchart illustrating the reasons for motion non-compliance in the control terminal based on distance deviation analysis according to the present invention.

[0052] Figure 4This is a flowchart illustrating the secondary determination of the reasons for the non-compliance of the movement of the control terminal based on the time-domain discreteness of the distance deviation, as per the present invention. Detailed Implementation

[0053] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0054] It should be noted that the data in this embodiment are all derived from a comprehensive analysis and evaluation of historical data from the six months prior to this determination and the corresponding historical determination results by the system described in this invention. Those skilled in the art will understand that the system described in this invention can determine the above-mentioned parameters for a single item by selecting the value with the highest proportion based on the data distribution as the preset standard parameter, using weighted summation to obtain the value as the preset standard parameter, substituting each historical data point into a specific formula and using the value obtained by that formula as the preset standard parameter, or other selection methods, as long as the system described in this invention can clearly define different specific situations in the single-item determination process through the obtained values.

[0055] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0056] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0057] Please see Figure 1 As shown, it is a structural block diagram of the intelligent control system for main tower construction safety based on image recognition of the present invention.

[0058] The image recognition-based intelligent management and control system for main tower construction safety provided in this embodiment includes:

[0059] Several control terminals are equipped with elevation positioning chips and interactive devices;

[0060] The demand setting module, which is connected to the control terminal, is used to determine the expected distance of each control terminal during each detection cycle during the movement based on the construction scope.

[0061] The positioning module, which is connected to the control terminal, includes several deployment elevation positioning chips set at corresponding positions to determine the actual position of the control terminal;

[0062] The model building module is used to generate digital twin models, which include: a main tower model and a construction personnel model;

[0063] The association module is connected to both the control terminal and the model building module to perform association processing between each control terminal and the construction personnel model.

[0064] A mapping construction module, which is connected to the association module, is used to construct a mapping relationship between the control terminal and the construction personnel model, so as to display and mark the movement trajectory of each control terminal in the digital twin model;

[0065] The comparison module is connected to the demand setting module and the positioning module respectively, and is used to determine the actual distance between a single control terminal and the construction area in a single detection cycle during the construction process, and compare the actual distance with the corresponding expected distance;

[0066] The analysis module is connected to the control terminal, the demand setting module, the positioning module, the model building module, the association module, the mapping building module, and the comparison module, respectively. It is used to analyze whether the movement of the control terminal is qualified based on the comparison result of the actual distance and the expected distance. If the movement of the control terminal is initially determined to be unqualified, a second determination is made on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal, or the reasons for the unqualified movement of the control terminal are analyzed.

[0067] Please see Figure 2 As shown, it is a flowchart for determining whether the movement of the analysis and control terminal is qualified.

[0068] Specifically, the analysis module is used to analyze whether the movement of the control terminal is qualified based on the comparison result of the actual distance and the expected distance, including:

[0069] Calculate the absolute value of the difference between the actual distance and the expected distance to obtain the distance deviation.

[0070] If the distance deviation is less than or equal to the first preset distance deviation, the analysis module determines that the movement of the control terminal is qualified.

[0071] If the distance deviation is greater than the first preset distance deviation and less than or equal to the second preset distance deviation, the analysis module initially determines that the movement of the control terminal is unqualified, and makes a second determination on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal.

[0072] If the distance deviation is greater than the second preset distance deviation, the analysis module determines that the movement of the control terminal is unqualified, and analyzes the reason for the unqualified movement of the control terminal based on the distance deviation.

[0073] In this embodiment of the invention, the first preset distance deviation is the average value of the actual distance deviations when several identical control terminals actually move and pass the test, and the second preset distance deviation is the minimum value of the actual distance deviations when several identical control terminals actually move and fail the test. However, the above values ​​are not limited to these values, and those skilled in the art can adjust the values ​​according to actual needs.

[0074] This invention categorizes the movement status of a control terminal into three levels: qualified, initially unqualified (requiring secondary judgment), and seriously unqualified, by setting a first preset distance deviation (qualified threshold) and a second preset distance deviation (severe unqualified threshold). For cases in the "initially unqualified" range (first preset deviation < deviation ≤ second preset deviation), cumulative movement distance is introduced as a supplementary judgment dimension. If the cumulative movement distance is small (e.g., short-distance movement), the deviation may be caused by instantaneous interference (e.g., signal fluctuations), and secondary judgment can avoid misjudgment. If the cumulative movement distance is large (e.g., long-distance movement), the persistent deviation is more likely to reflect a real anomaly, requiring an early warning. When the deviation exceeds the second preset threshold, the system directly determines unqualified and analyzes the cause based on the distance deviation. Through cause analysis, subsequent strategy adjustments can be further driven.

[0075] Specifically, the analysis module is used to perform a secondary determination on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal, including:

[0076] If the cumulative movement distance is greater than or equal to the preset cumulative movement distance, the movement of the control terminal is determined to be unqualified, and the reason for the unqualified movement of the control terminal is analyzed based on the distance deviation.

[0077] If the cumulative movement distance is less than the preset cumulative movement distance, the first preset distance deviation is determined to be unqualified, and the first preset distance deviation is corrected based on the cumulative total movement time after the control terminal receives the construction instruction.

[0078] It is understandable that elevation positioning chips have measurement errors. A single measurement may cause the deviation to exceed the preset threshold due to signal interference and multipath effect. For example, the signal may be briefly blocked when a tower crane passes by, causing the positioning to jump. The cumulative movement distance reflects the overall trend over a period of time. If only a single deviation exceeds the preset threshold but the cumulative value does not exceed the standard, it indicates that it is an occasional error rather than a real violation.

[0079] In this embodiment of the invention, the preset cumulative movement distance is the average of the cumulative movement distances of several control terminals when their movement is qualified under the same movement trajectory. The correction of the first preset distance deviation based on the cumulative total movement time after the control terminal receives the construction instruction can be determined by the following method: using a machine learning model (such as regression analysis), the relationship between the cumulative total movement time and the actual distance deviation in historical data is analyzed to establish a threshold correction model. Input features (cumulative total movement time, construction area, equipment type) and output target: the dynamically adjusted first preset distance deviation. The analysis module is used to correct the first preset distance deviation based on the cumulative total movement time after the control terminal receives the construction instruction. The increase in the first preset distance deviation is negatively correlated with the cumulative total movement time.

[0080] This invention determines whether a deviation is a single interference or a continuous anomaly by comparing the cumulative movement distance with a preset threshold. In scenarios where signals are easily interfered with (such as urban canyons, mining areas, and indoor construction), traditional single deviation judgment is prone to frequent false alarms, while the cumulative movement distance reflects the overall trend and reduces the impact of environmental interference. The longer the total cumulative movement time, the greater the equipment positioning error may be due to factors such as signal attenuation and equipment heat drift. However, in practical applications, long-term movement (such as all-day construction) is often accompanied by more lenient fault tolerance requirements. By establishing a negative correlation correction relationship through a machine learning model, a balance between accuracy and practicality can be achieved.

[0081] Please see Figure 3 As shown, it is a flowchart of the reasons for the non-compliance of the control terminal based on distance deviation analysis.

[0082] Specifically, the analysis module is used to analyze the reasons for the non-compliance of the control terminal based on distance deviation, including:

[0083] Calculate the ratio of the second preset distance deviation to the distance deviation itself to obtain the distance deviation ratio.

[0084] If the distance deviation ratio is less than or equal to the first preset distance deviation ratio, then the vertical distance between the position of the control terminal and the position of the construction area at the current time node is determined, and the reason for the unqualified movement of the control terminal is analyzed based on the vertical distance.

[0085] If the distance deviation ratio is greater than the first preset distance deviation ratio and less than or equal to the second preset distance deviation ratio, then it is determined that the distance deviation in the historical record is obtained, and the reason for the failure of the movement of the control terminal is determined a second time based on the time domain dispersion of the distance deviation.

[0086] If the distance deviation ratio is greater than the second preset distance deviation ratio, it is determined to obtain the historical data reception record of the control terminal, and to determine whether a task change has occurred based on the historical data reception record.

[0087] In this embodiment of the invention, the first preset distance deviation ratio can be determined by the following method: collecting a large amount of movement data of the control terminal in the actual construction scenario, including the actual distance, expected distance, and corresponding construction area location for each movement; filtering this data to identify those cases where movement is unqualified due to vertical distance issues, i.e., the vertical distance between the control terminal and the construction area location during movement does not meet the requirements, thus causing the actual distance deviation to exceed the normal range; calculating the distance deviation ratio: for the filtered unqualified data, calculating the ratio of the second preset distance deviation to the actual distance deviation for each data point; statistically analyzing the distance deviation ratios corresponding to all data points where movement is unqualified due to vertical distance issues; calculating the average of these ratios to obtain the first preset distance deviation ratio; the method for determining the second preset distance deviation ratio is the same as the method for determining the first preset distance deviation ratio.

[0088] This invention calculates the distance deviation ratio. When the distance deviation ratio is less than or equal to a first preset distance deviation ratio, it directly analyzes the vertical distance between the control terminal and the construction area. This analysis method can accurately locate movement non-compliance issues caused by non-compliance with vertical distance requirements, avoiding blindly investigating other factors and improving the efficiency of problem diagnosis. When the distance deviation ratio is between the first and second preset values, by analyzing the temporal dispersion of the distance deviation in historical records, it can further determine whether there are other dynamic factors (such as changes in the construction environment, equipment failure, etc.) causing movement non-compliance. This secondary judgment method can analyze the problem more comprehensively and avoid misjudgment. The preset values ​​are determined based on data: the first and second preset distance deviation ratios are obtained through statistical analysis of data from a large number of actual construction scenarios. This data-based method ensures the scientificity and rationality of the preset values ​​and avoids errors caused by subjective settings. Through statistical analysis of actual data, it can more accurately reflect the actual situation in the construction scenario, thereby improving the reliability of the entire analysis system.

[0089] Specifically, the analysis module is used to analyze the reasons for the non-compliance of the control terminal's movement based on vertical distance, including:

[0090] Calculate the height difference between the location of the control terminal and the location of the construction area at the current time point to obtain the vertical distance.

[0091] If the vertical distance is less than or equal to the preset vertical distance, the reason for the failure of the movement of the control terminal is determined to be a control terminal malfunction, and an alarm signal is issued.

[0092] If the vertical distance is greater than the preset vertical distance, then it is determined that the second preset distance deviation should be corrected based on the vertical distance.

[0093] The preset vertical distance in this embodiment of the invention can be determined by the following method: Collecting a large amount of movement data from control terminals: This data should include the actual location, expected location, and specific location of the construction area (including height information) for each movement. Ensure the data covers various construction scenarios and different types of control terminals to improve the universality and accuracy of the preset vertical distance; Screening out cases where movement is unqualified due to vertical distance issues: From the collected data, identify cases where the vertical distance between the actual location of the control terminal and the location of the construction area does not meet the requirements, resulting in unqualified movement. These cases should be clearly marked as "unqualified due to vertical distance issues"; Calculating the vertical distance of each unqualified case: For each selected unqualified case, calculate the height difference between the location of the control terminal at the current time node and the location of the construction area, i.e., the vertical distance. Statistically calculate the vertical distance of all unqualified cases and obtain the preset vertical distance by averaging the values.

[0094] In this embodiment of the invention, the increase in the second preset distance deviation is positively correlated with the vertical distance. The correction of the second preset distance deviation based on the vertical distance includes collecting a large amount of movement data from the control terminal, including the actual location, expected location, and specific location of the construction area (including height information) for each movement. For each data point, the height difference (vertical distance) between the location of the control terminal at the current time node and the location of the construction area, and the absolute value of the difference between the actual distance and the expected distance (actual distance deviation) are calculated. Through data analysis, a positive correlation model between the vertical distance and the actual distance deviation is established. Based on the positive correlation model, the correction coefficient and constant term are determined. These parameters can be obtained by regression analysis of historical data. Based on the vertical distance, the corrected second preset distance deviation (the sum of the product of the original second preset distance deviation and the vertical distance correction coefficient) is calculated.

[0095] Please see Figure 4 As shown, it is a flowchart for secondary determination of the reasons for the non-compliance of the movement of the control terminal based on the time-domain dispersion of the distance deviation.

[0096] Specifically, the analysis module is used to perform a secondary determination of the reasons for the non-compliance of the control terminal's movement based on the time-domain dispersion of the distance deviation, including:

[0097] Obtain historical data on distance deviation.

[0098] Calculate the variance of the distance deviation to obtain the time-domain dispersion.

[0099] If the time-domain dispersion is less than or equal to the preset time-domain dispersion, the reason for the failure of the control terminal's movement is determined to be unreasonable path planning, and a replanning signal is issued.

[0100] If the time-domain dispersion is greater than the preset time-domain dispersion, the reason for the failure of the control terminal's movement is determined to be inaccurate positioning, and an elevation positioning chip is deployed to supplement it.

[0101] The preset time-domain dispersion in this embodiment of the invention can be determined by the following method: collecting a large amount of movement data from control terminals. This data should include the actual location, expected location, and specific location of the construction area (including height information) for each movement. Cases where movement is unqualified due to time-domain dispersion issues are then identified. From the collected data, cases where the actual distance deviation of the control terminals changes frequently over time, resulting in unqualified movement, are clearly marked as "unqualified due to time-domain dispersion issues." For each unqualified case, historical data of its distance deviation is obtained, the variance of the distance deviation is calculated, and the time-domain dispersion is obtained. The time-domain dispersion of all cases where movement is unqualified due to time-domain dispersion issues is statistically analyzed, and the average value is taken as the preset time-domain dispersion.

[0102] Specifically, the analysis module is used to adjust the number of deployed elevation positioning chips based on the time-domain dispersion, wherein the increase in the number of deployed elevation positioning chips is positively correlated with the time-domain dispersion.

[0103] In this embodiment of the invention, adjusting the number of deployed elevation positioning chips based on the time-domain dispersion involves collecting a large amount of movement data from control terminals, including the actual location, expected location, and specific location (including height information) of each movement. This ensures data coverage of various construction scenarios and different types of control terminals. For each data point, historical data on its distance deviation is obtained, the variance of the distance deviation is calculated, and the time-domain dispersion is obtained. Through data analysis, a positive correlation model between the time-domain dispersion and the number of deployed elevation positioning chips is established. Based on the positive correlation model, adjustment coefficients and constant terms are determined. The adjusted number of deployed elevation positioning chips is then calculated based on the time-domain dispersion (the sum of the original number of deployed elevation positioning chips, the time-domain dispersion, and the positive correlation coefficient).

[0104] This invention, by calculating the vertical distance between the control terminal and the construction area, can quickly determine whether a movement failure is caused by a terminal malfunction. When the vertical distance is less than or equal to a preset value, it is directly identified as a terminal malfunction and an alarm is issued, facilitating timely repair or replacement of the equipment. When the vertical distance is greater than the preset value, a second preset distance deviation is corrected based on the vertical distance. This dynamic adjustment mechanism can more accurately reflect changes in the actual construction environment and avoid misjudgments caused by fixed deviation values. By calculating the variance (time-domain dispersion) of the distance deviation, the cause of the movement failure can be further analyzed. When the variance is less than the preset value, it is determined that the path planning is unreasonable; when the variance is greater than the preset value, it is determined that the movement failure is caused by a terminal malfunction. If the positioning is deemed inaccurate, this secondary judgment mechanism can analyze the problem more comprehensively and avoid misjudgment based on a single factor. The deployment number of elevation positioning chips is dynamically adjusted based on the time-domain dispersion, allowing for flexible adjustment of the positioning system's accuracy according to changes in the actual construction environment, ensuring positioning accuracy and reliability. By establishing a positive correlation model between the vertical distance and the actual distance deviation, a second preset distance deviation is dynamically corrected, allowing for flexible adjustment of the deviation value according to changes in the actual construction environment. Furthermore, by establishing a positive correlation model between the time-domain dispersion and the deployment number of elevation positioning chips, the deployment number is dynamically adjusted, allowing for flexible adjustment of the chip quantity according to actual positioning needs.

[0105] Specifically, the analysis module is used to determine whether a task change has occurred based on historical data reception records, including:

[0106] If an updated receiving record exists, it is determined that the construction task of the control terminal has changed, and the construction area and expected distance are re-determined based on the received information.

[0107] If no updated receiving record is found, the reason for the unqualified movement of the control terminal is determined to be a control terminal malfunction, and an alarm signal is issued.

[0108] This invention can promptly detect changes in the construction tasks of the control terminal by checking for updated reception records. This method ensures rapid response to task changes during construction, avoiding construction chaos or errors caused by untimely handling of task changes. When a task change is detected, the construction area and expected distance are redefined based on the new received information. This dynamic adjustment mechanism ensures that construction parameters remain consistent with the current task, improving the accuracy and efficiency of construction. By clearly distinguishing between task changes and equipment malfunctions, it avoids misjudgments caused by task changes. Even without a task change, if the movement of the control terminal is unqualified, it can be clearly identified as an equipment malfunction, and an alarm signal can be issued for timely repair or replacement of the equipment.

[0109] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0110] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A main tower construction safety intelligent control system based on image recognition, characterized in that, include: Several control terminals are equipped with elevation positioning chips and interactive devices; The demand setting module, which is connected to the control terminal, is used to determine the expected distance of each control terminal during each detection cycle during the movement based on the construction scope. The positioning module, which is connected to the control terminal, includes several deployment elevation positioning chips set at corresponding positions to determine the actual position of the control terminal; The model building module is used to generate digital twin models, which include: a main tower model and a construction personnel model; The association module is connected to both the control terminal and the model building module to perform association processing between each control terminal and the construction personnel model. A mapping construction module, which is connected to the association module, is used to construct a mapping relationship between the control terminal and the construction personnel model, so as to display and mark the movement trajectory of each control terminal in the digital twin model; The comparison module is connected to the demand setting module and the positioning module respectively, and is used to determine the actual distance between a single control terminal and the construction area in a single detection cycle during the construction process, and compare the actual distance with the corresponding expected distance; The analysis module is connected to the control terminal, the demand setting module, the positioning module, the model building module, the association module, the mapping building module, and the comparison module, respectively. It is used to analyze whether the movement of the control terminal is qualified based on the comparison result of the actual distance and the expected distance. When the movement of the control terminal is initially determined to be unqualified, a second determination is made on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal, or the reasons for the unqualified movement of the control terminal are analyzed. The analysis module is used to analyze whether the movement of the control terminal is qualified based on the comparison result of the actual distance and the expected distance, including: Calculate the absolute value of the difference between the actual distance and the expected distance to obtain the distance deviation. If the distance deviation is less than or equal to the first preset distance deviation, the analysis module determines that the movement of the control terminal is qualified. If the distance deviation is greater than the first preset distance deviation and less than or equal to the second preset distance deviation, the analysis module initially determines that the movement of the control terminal is unqualified, and makes a second determination on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal. If the distance deviation is greater than the second preset distance deviation, the analysis module determines that the movement of the control terminal is unqualified, and analyzes the reason for the unqualified movement of the control terminal based on the distance deviation. The analysis module is used to perform a secondary judgment on whether the movement of the control terminal is qualified based on the cumulative movement distance of the control terminal, including: If the cumulative movement distance is greater than or equal to the preset cumulative movement distance, the movement of the control terminal is determined to be unqualified, and the reason for the unqualified movement of the control terminal is analyzed based on the distance deviation. If the cumulative movement distance is less than the preset cumulative movement distance, the first preset distance deviation is determined to be unqualified, and the first preset distance deviation is corrected based on the cumulative total movement time after the control terminal receives the construction instruction.

2. The intelligent control system for main tower construction safety based on image recognition according to claim 1, characterized in that, The analysis module is used to correct the first preset distance deviation based on the cumulative total travel time after the control terminal receives the construction instructions, wherein the increase in the first preset distance deviation is negatively correlated with the cumulative total travel time.

3. The intelligent control system for main tower construction safety based on image recognition according to claim 1, characterized in that, The analysis module is used to analyze the reasons for the movement failure of the control terminal based on distance deviation, including: Calculate the ratio of the second preset distance deviation to the distance deviation itself to obtain the distance deviation ratio. If the distance deviation ratio is less than or equal to the first preset distance deviation ratio, then the vertical distance between the position of the control terminal and the position of the construction area at the current time node is determined, and the reason for the unqualified movement of the control terminal is analyzed based on the vertical distance. If the distance deviation ratio is greater than the first preset distance deviation ratio and less than or equal to the second preset distance deviation ratio, then it is determined that the distance deviation in the historical record is obtained, and a second determination is made on the reason for the failure of the movement of the control terminal based on the time domain dispersion of the distance deviation. If the distance deviation ratio is greater than the second preset distance deviation ratio, it is determined that the historical data reception record of the control terminal is obtained, and a task change is determined based on the historical data reception record.

4. The intelligent control system for main tower construction safety based on image recognition according to claim 3, characterized in that, The analysis module is used to analyze the reasons for non-compliance of the control terminal's movement based on vertical distance, including: Calculate the height difference between the location of the control terminal and the location of the construction area at the current time point to obtain the vertical distance. If the vertical distance is less than or equal to the preset vertical distance, the reason for the failure of the movement of the control terminal is determined to be a control terminal malfunction, and an alarm signal is issued. If the vertical distance is greater than the preset vertical distance, then it is determined that the second preset distance deviation should be corrected based on the vertical distance.

5. The intelligent control system for main tower construction safety based on image recognition according to claim 4, characterized in that, The analysis module is used to correct the second preset distance deviation based on the vertical distance, wherein the increase in the second preset distance deviation is positively correlated with the vertical distance.

6. The intelligent control system for main tower construction safety based on image recognition according to claim 3, characterized in that, The analysis module is used to perform a secondary determination of the reasons for the non-compliance of the control terminal's movement based on the time-domain dispersion of the distance deviation, including: Obtain historical data on distance deviation. Calculate the variance of the distance deviation to obtain the time-domain dispersion. If the time-domain dispersion is less than or equal to the preset time-domain dispersion, the reason for the failure of the control terminal's movement is determined to be unreasonable path planning, and a replanning signal is issued. If the time-domain dispersion is greater than the preset time-domain dispersion, the reason for the failure of the control terminal's movement is determined to be inaccurate positioning, and an elevation positioning chip is deployed to supplement it.

7. The intelligent control system for main tower construction safety based on image recognition according to claim 6, characterized in that, The analysis module is used to adjust the number of deployed elevation positioning chips based on the time-domain dispersion, wherein the increase in the number of deployed elevation positioning chips is positively correlated with the time-domain dispersion.

8. The intelligent control system for main tower construction safety based on image recognition according to claim 7, characterized in that, The analysis module is used to determine whether a task change has occurred based on historical data reception records, including: If an updated receiving record exists, it is determined that the construction task of the control terminal has changed, and the construction area and expected distance are re-determined based on the received information. If no updated receiving record is found, the reason for the unqualified movement of the control terminal is determined to be a control terminal malfunction, and an alarm signal is issued.

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