A smart safety monitoring and early warning system for electric hanging baskets used in building construction

Abstract

The application relates to the technical field of safety monitoring and early warning, and discloses a kind of wisdom safety monitoring and early warning systems for electric hanging basket for building construction, the system includes: early warning value setting module is configured to determine the initial monitoring early warning value of the monitored hanging basket according to load distribution data;Environment judgment and optimization module is configured to determine the optimization coefficient of initial monitoring early warning value according to use environment deviation value, and obtain optimized monitoring early warning value;Operation judgment and compensation module is configured to determine the compensation coefficient of optimized monitoring early warning value based on real-time operation parameters and rope monitoring data, and obtain compensated monitoring early warning value;Early warning module is configured to determine the early warning level of the monitored hanging basket according to compensated monitoring early warning value.The application can monitor the safety state of electric hanging basket in actual operation process in real time and accurately, and timely issue early warning according to monitoring result, effectively prevent the safety hazard of electric hanging basket.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of safety monitoring and early warning, in particular to an electric hanging basket intelligent safety monitoring and early warning system for building construction. BACKGROUND

[0002] As a kind of equipment frequently used in aerial work, electric hanging basket is particularly widely used in the construction industry, especially in the construction of building exterior wall, daily maintenance and cleaning operation. However, the traditional electric hanging basket often accompanies many security risks that cannot be ignored in the actual operation process. For example, the occurrence of overload phenomenon will cause the hanging basket structure to bear excessive pressure, thereby affecting its stability; If the hanging basket is inclined during use, it will not only affect the work efficiency, but also may cause falling accident; In addition, the rope, as an important part of the hanging basket, once broken, the consequences are unpredictable. Once these potential safety problems break out in actual operation, they will pose a serious threat to the personal safety of the workers, and even cause major accidents and irreparable losses.

[0003] Therefore, it is necessary to design an electric hanging basket intelligent safety monitoring and early warning system for building construction to solve the problems existing in the prior art. SUMMARY

[0004] In view of this, the present application provides an electric hanging basket intelligent safety monitoring and early warning system for building construction, which aims to effectively prevent and solve the security risks of electric hanging basket in the actual operation process.

[0005] The present application provides an electric hanging basket intelligent safety monitoring and early warning system for building construction, which comprises:

[0006] The early warning value setting module is configured to determine the hanging basket to be monitored, collect the load distribution data of the hanging basket to be monitored, and determine the initial monitoring early warning value of the hanging basket to be monitored according to the load distribution data; wherein the initial monitoring early warning value includes initial hanging basket inclination angle and initial hanging basket swing amplitude;

[0007] The environmental judgment and optimization module is configured to collect the use environment data of the hanging basket to be monitored, analyze the use environment data, and determine whether to optimize the initial monitoring early warning value according to the analysis result; if yes, determine the use environment deviation value of the hanging basket to be monitored according to the use environment data, determine the optimization coefficient of the initial monitoring early warning value according to the use environment deviation value, and obtain the optimized monitoring early warning value;

[0008] The operation judgment and compensation module is configured to collect the real-time operating parameters of the suspended platform to be monitored, and determine whether to compensate the optimized monitoring warning value based on the real-time operating parameters; if so, it collects the rope monitoring data of the suspended platform to be monitored, determines the compensation coefficient of the optimized monitoring warning value based on the real-time operating parameters and the rope monitoring data, and obtains the compensated monitoring warning value.

[0009] The early warning module is configured to determine the early warning level of the suspended platform to be monitored based on the compensation monitoring early warning value.

[0010] Furthermore, when the warning value setting module determines the initial monitoring warning value of the suspended platform to be monitored based on the load distribution data, it includes:

[0011] The load distribution data is analyzed to obtain the number of personnel, personnel weight, personnel location, material weight, and material location;

[0012] Determine the center position of the suspended platform to be monitored;

[0013] The overall center of gravity offset of the monitored suspended platform is calculated based on the center location, number of personnel, personnel weight, personnel position, material weight, and material position.

[0014] The overall center of gravity offset is compared with historical data, and the initial monitoring and early warning value is determined based on the comparison results.

[0015] Furthermore, when determining the initial monitoring and early warning value based on the comparison results, the following steps are included:

[0016] When there is a historical overall center of gravity offset in the historical data that is the same as the overall center of gravity offset, the historical monitoring and early warning value corresponding to the historical overall center of gravity offset is used as the initial monitoring and early warning value.

[0017] When there is no historical overall center of gravity offset in the historical data that is the same as the overall center of gravity offset, the average value of all the historical overall center of gravity offsets in the historical data is calculated and recorded as the historical average center of gravity offset. The initial monitoring and warning value is determined based on the historical average center of gravity offset.

[0018] Furthermore, when determining the initial monitoring and early warning value based on the historical average centroid offset, the following steps are included:

[0019] Calculate the absolute value of the difference between the overall center of gravity offset and the historical average center of gravity offset, and record it as the absolute center of gravity offset difference;

[0020] The absolute center of gravity offset difference is compared with the first absolute center of gravity offset difference and the second absolute center of gravity offset difference, and the initial monitoring and warning value is determined based on the comparison result; wherein, the first absolute center of gravity offset difference is less than the second absolute center of gravity offset difference;

[0021] When the absolute center of gravity offset difference is less than or equal to the first absolute center of gravity offset difference, the initial monitoring warning value is determined to be the first monitoring warning value;

[0022] When the absolute center of gravity offset difference is greater than the first absolute center of gravity offset difference and less than or equal to the second absolute center of gravity offset difference, the initial monitoring warning value is determined to be the second monitoring warning value.

[0023] When the absolute center of gravity offset difference is greater than the second absolute center of gravity offset difference, the initial monitoring warning value is determined to be the third monitoring warning value.

[0024] Furthermore, when the environment judgment and optimization module parses the usage environment data and determines whether to optimize the initial monitoring and early warning value based on the parsing results, it includes:

[0025] The environmental data is analyzed to obtain the wind speed characteristic value, temperature characteristic value, humidity characteristic value and terrain characteristic value of the suspended basket to be monitored;

[0026] Obtain the standard wind speed value corresponding to the wind speed characteristic value, and calculate the difference between the wind speed characteristic value and the standard wind speed value, which is denoted as the wind speed difference.

[0027] The wind speed difference is compared with the wind speed difference threshold. If the wind speed difference is greater than or equal to the wind speed difference threshold, it is determined that the initial monitoring and warning value should be optimized.

[0028] Otherwise, it is determined that the initial monitoring and early warning value will not be optimized.

[0029] Furthermore, when the environmental judgment and optimization module determines the environmental deviation value of the suspended platform to be monitored based on the environmental data, it includes:

[0030] Obtain the standard values ​​of temperature, humidity, and terrain corresponding to the temperature characteristic value, humidity characteristic value, and terrain characteristic value, respectively;

[0031] The temperature difference, humidity difference, and terrain difference are obtained. After normalizing the wind speed difference, temperature difference, humidity difference, and terrain difference, the environmental deviation value of the suspended platform to be monitored is determined.

[0032] The environmental deviation value is obtained by the following formula:

[0033] Ed=α1·ΔV'+α2·ΔT'+α3·ΔH'+α4·ΔG';

[0034] Where Ed represents the environmental deviation value; ΔV′ represents the normalized wind speed difference; ΔT′ represents the normalized temperature difference; ΔH′ represents the normalized humidity difference; ΔG′ represents the normalized terrain difference; α1, α2, α3 and α4 represent weighting coefficients, and α1+α2+α3+α4=1.

[0035] Further, when the environmental judgment and optimization module determines the optimization coefficient of the initial monitoring and early warning value based on the deviation value of the usage environment, and obtains the optimized monitoring and early warning value, it includes:

[0036] The deviation value of the usage environment is compared with the first deviation value of the usage environment and the second deviation value of the usage environment, and the optimization coefficient is determined based on the comparison result; wherein, the first deviation value of the usage environment is less than the second deviation value of the usage environment.

[0037] When the deviation value of the usage environment is less than or equal to the first deviation value of the usage environment, the optimization coefficient is determined to be the first optimization coefficient;

[0038] When the deviation value of the usage environment is greater than the first deviation value of the usage environment and less than or equal to the second deviation value of the usage environment, the optimization coefficient is determined to be the second optimization coefficient;

[0039] When the deviation value of the usage environment is greater than the deviation value of the second usage environment, the optimization coefficient is determined to be the third optimization coefficient;

[0040] The initial monitoring and early warning value is optimized based on the optimization coefficient to obtain the optimized monitoring and early warning value.

[0041] Furthermore, when the operation judgment and compensation module determines whether to compensate the optimized monitoring and early warning value based on the real-time operation parameters, it includes:

[0042] Feature extraction is performed on the real-time operating parameters to obtain the maximum real-time operating speed;

[0043] The maximum real-time operating speed is compared with the maximum real-time operating speed threshold. If the maximum real-time operating speed is greater than the maximum real-time operating speed threshold, it is determined that the optimized monitoring and early warning value should be compensated.

[0044] Otherwise, it is determined that no compensation will be made for the optimized monitoring and early warning value.

[0045] Furthermore, when the operation judgment and compensation module determines the compensation coefficient of the optimized monitoring early warning value based on the real-time operation parameters and rope monitoring data, and obtains the compensated monitoring early warning value, it includes:

[0046] The rope monitoring data is analyzed to obtain the maximum rope tension value;

[0047] A compensation vector set is constructed based on the maximum real-time operating speed and the maximum rope tension value;

[0048] The compensation vector group is compared with the historical compensation group, and the optimization coefficient is determined based on the comparison result;

[0049] When there is a historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the historical compensation coefficient corresponding to the historical compensation vector group is used as the compensation coefficient.

[0050] When there is no historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the overlap between the compensation vector group and each historical compensation vector group is calculated, the maximum overlap is extracted, and the compensation coefficient is determined based on the maximum overlap.

[0051] The maximum overlap is compared with the mapping compensation coefficient table, and the compensation coefficient is determined based on the comparison result.

[0052] The optimized monitoring and early warning value is compensated according to the compensation coefficient to obtain the compensated monitoring and early warning value.

[0053] Furthermore, when the early warning module determines the early warning level of the suspended platform to be monitored based on the compensated monitoring early warning value, it includes:

[0054] The warning levels include low, medium, and high.

[0055] The compensation monitoring early warning value is compared with the first compensation monitoring early warning value and the second compensation monitoring early warning value, and the early warning level of the suspended platform to be monitored is determined according to the comparison result; wherein, the first compensation monitoring early warning value is less than the second compensation monitoring early warning value;

[0056] When the compensation monitoring early warning value is less than or equal to the first compensation monitoring early warning value, the early warning level of the suspended platform to be monitored is determined to be low.

[0057] When the compensation monitoring warning value is greater than the first compensation monitoring warning value and less than or equal to the second compensation monitoring warning value, the warning level of the suspended platform to be monitored is determined to be medium.

[0058] When the compensation monitoring early warning value is greater than the second compensation monitoring early warning value, the early warning level of the suspended platform to be monitored is determined to be high.

[0059] Compared with existing technologies, the beneficial effects of this invention are as follows: The intelligent safety monitoring and early warning system for electric suspended scaffolds used in construction provided by this invention can monitor the safety status of electric suspended scaffolds in real time and accurately during actual operation, and issue timely early warnings based on the monitoring results, effectively preventing potential safety hazards. Specifically, through the early warning value setting module, the system can determine the initial monitoring and early warning value based on the load distribution data of the scaffold, providing a benchmark for subsequent monitoring and early warning. The environmental judgment and optimization module further considers the impact of the scaffold's operating environment on its safety status, improving the accuracy and reliability of the early warning through the analysis and optimization of the operating environment data. The operation judgment and compensation module can compensate the optimized monitoring and early warning value based on the real-time operating parameters of the scaffold and rope monitoring data, further improving the accuracy of the early warning. Finally, the early warning module determines the early warning level of the scaffold based on the compensated monitoring and early warning value, providing operators with clear and intuitive early warning information, helping them to take timely measures to ensure construction safety. Attached Figure Description

[0060] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0061] Figure 1 This is a structural block diagram of an intelligent safety monitoring and early warning system for electric suspended platforms used in building construction, provided in an embodiment of the present invention. Detailed Implementation

[0062] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0063] See Figure 1 As shown in some embodiments of this application, this embodiment provides a smart safety monitoring and early warning system for electric suspended scaffolds used in building construction, including:

[0064] The warning value setting module is configured to identify the suspended platform to be monitored, collect the load distribution data of the suspended platform to be monitored, and determine the initial monitoring warning value of the suspended platform to be monitored based on the load distribution data; wherein, the initial monitoring warning value includes the initial tilt angle of the suspended platform and the initial sway amplitude of the suspended platform;

[0065] The environmental judgment and optimization module is configured to collect the usage environment data of the suspended platform to be monitored, and parse the usage environment data. Based on the parsing results, it determines whether to optimize the initial monitoring warning value. If so, it determines the usage environment deviation value of the suspended platform to be monitored based on the usage environment data, determines the optimization coefficient of the initial monitoring warning value based on the usage environment deviation value, and obtains the optimized monitoring warning value.

[0066] The operation judgment and compensation module is configured to collect the real-time operating parameters of the suspended platform to be monitored, and determine whether to compensate the optimized monitoring warning value based on the real-time operating parameters; if so, it collects the rope monitoring data of the suspended platform to be monitored, determines the compensation coefficient of the optimized monitoring warning value based on the real-time operating parameters and the rope monitoring data, and obtains the compensated monitoring warning value.

[0067] The early warning module is configured to determine the early warning level of the suspended platform to be monitored based on the compensation monitoring early warning value.

[0068] It is understood that the intelligent safety monitoring and early warning system for electric suspended scaffolds used in construction provided in this embodiment can monitor the safety status of the electric suspended scaffold in real time and accurately during actual operation, and issue timely warnings based on the monitoring results, effectively preventing potential safety hazards. Specifically, through the early warning value setting module, the system can determine the initial monitoring and early warning value based on the load distribution data of the scaffold, providing a benchmark for subsequent monitoring and early warning. The environmental judgment and optimization module further considers the impact of the scaffold's operating environment on its safety status, improving the accuracy and reliability of the early warning through the analysis and optimization of the operating environment data. The operation judgment and compensation module can compensate the optimized monitoring and early warning value based on the real-time operating parameters of the scaffold and rope monitoring data, further improving the accuracy of the early warning. Finally, the early warning module determines the early warning level of the scaffold based on the compensated monitoring and early warning value, providing operators with clear and intuitive early warning information, helping them to take timely measures to ensure construction safety.

[0069] Specifically, when the warning value setting module determines the initial monitoring warning value for the suspended platform to be monitored based on the load distribution data, it includes:

[0070] The load distribution data is analyzed to obtain the number of personnel, personnel weight, personnel location, material weight, and material location;

[0071] Determine the center position of the suspended platform to be monitored;

[0072] The overall center of gravity offset of the monitored suspended platform is calculated based on the center location, number of personnel, personnel weight, personnel position, material weight, and material position.

[0073] The overall center of gravity offset is compared with historical data, and the initial monitoring and early warning value is determined based on the comparison results.

[0074] In this embodiment, it is assumed that the suspended platform of the suspended platform to be monitored is established in a two-dimensional coordinate system (XY) on a horizontal plane; the center point of the suspended platform is set as the origin (0,0); there are several loads (including personnel and materials), and the mass of each load is mi (including the weight of personnel and the weight of materials); the position coordinates are (Xi,Yi);

[0075] Calculate the overall centroid coordinates (Xc, Yc):

[0076]

[0077] Calculate the overall center of gravity offset Dc:

[0078]

[0079] Where n represents the total number of personnel and materials, i = 1, 2, ..., n.

[0080] Understandably, the overall center of gravity offset calculated using the above formula can intuitively reflect the changes in the center of gravity of the suspended platform under monitoring due to the distribution of personnel and materials. Comparing this overall center of gravity offset with historical data is a crucial step. Historical data contains information on the safety status of the suspended platform and the corresponding center of gravity offset under different load distributions. If the comparison results show that the current overall center of gravity offset is close to or exceeds the center of gravity offset when dangerous situations occurred in the historical data, then the initial monitoring warning value needs to be appropriately increased to ensure timely warnings of potential dangers.

[0081] Specifically, determining the initial monitoring and early warning value based on the comparison results includes:

[0082] When there is a historical overall center of gravity offset in the historical data that is the same as the overall center of gravity offset, the historical monitoring and early warning value corresponding to the historical overall center of gravity offset is used as the initial monitoring and early warning value.

[0083] When there is no historical overall center of gravity offset in the historical data that is the same as the overall center of gravity offset, the average value of all the historical overall center of gravity offsets in the historical data is calculated and recorded as the historical average center of gravity offset. The initial monitoring and warning value is determined based on the historical average center of gravity offset.

[0084] Understandably, when a historical overall center of gravity offset exists in the historical data, directly using the corresponding historical monitoring and warning value can quickly and accurately determine the initial monitoring and warning value. This is because it means that the current load distribution has been recorded in the past, and the corresponding safety status and warning value have been verified in practice. However, when no identical historical overall center of gravity offset exists, calculating the historical average center of gravity offset and determining the initial monitoring and warning value based on this is a reasonable approximation method. The historical average center of gravity offset integrates center of gravity offsets under various historical load distributions, and the initial monitoring and warning value determined based on this can reflect the safety status of the suspended platform under normal conditions to a certain extent.

[0085] Specifically, determining the initial monitoring and early warning value based on the historical average centroid offset includes:

[0086] Calculate the absolute value of the difference between the overall center of gravity offset and the historical average center of gravity offset, and record it as the absolute center of gravity offset difference;

[0087] The absolute center of gravity offset difference is compared with the first absolute center of gravity offset difference and the second absolute center of gravity offset difference, and the initial monitoring and warning value is determined based on the comparison result; wherein, the first absolute center of gravity offset difference is less than the second absolute center of gravity offset difference;

[0088] When the absolute center of gravity offset difference is less than or equal to the first absolute center of gravity offset difference, the initial monitoring warning value is determined to be the first monitoring warning value;

[0089] When the absolute center of gravity offset difference is greater than the first absolute center of gravity offset difference and less than or equal to the second absolute center of gravity offset difference, the initial monitoring warning value is determined to be the second monitoring warning value.

[0090] When the absolute center of gravity offset difference is greater than the second absolute center of gravity offset difference, the initial monitoring warning value is determined to be the third monitoring warning value.

[0091] Understandably, by comparing the absolute center of gravity offset difference with the first and second absolute center of gravity offset differences, the initial monitoring and warning value can be determined more precisely based on the degree of difference between the overall center of gravity offset and the historical average center of gravity offset. The first monitoring and warning value corresponds to a situation where the difference between the overall center of gravity offset and the historical average center of gravity offset is small, indicating that the current load distribution of the suspended platform is relatively close to the normal state, and the risk factor is relatively low. The second monitoring and warning value corresponds to a situation where the absolute center of gravity offset difference is in the middle range, at which point the load distribution of the suspended platform deviates to some extent from the normal situation, but has not yet reached a very dangerous level. The third monitoring and warning value is determined when the absolute center of gravity offset difference is large, meaning that the current center of gravity offset of the suspended platform is relatively serious, and there may be a high safety risk.

[0092] In this embodiment, the first monitoring and warning value is preferably that the initial tilt angle of the suspended basket does not exceed 5 degrees and the initial sway amplitude of the suspended basket does not exceed 10 centimeters; the second monitoring and warning value is preferably that the initial tilt angle of the suspended basket does not exceed 10 degrees and the initial sway amplitude of the suspended basket does not exceed 15 centimeters; the third monitoring and warning value is preferably that the initial tilt angle of the suspended basket does not exceed 15 degrees and the initial sway amplitude of the suspended basket does not exceed 20 centimeters.

[0093] Specifically, when the environment judgment and optimization module parses the usage environment data and determines whether to optimize the initial monitoring and early warning value based on the parsing results, it includes:

[0094] The environmental data is analyzed to obtain the wind speed characteristic value, temperature characteristic value, humidity characteristic value and terrain characteristic value of the suspended basket to be monitored;

[0095] Obtain the standard wind speed value corresponding to the wind speed characteristic value, and calculate the difference between the wind speed characteristic value and the standard wind speed value, which is denoted as the wind speed difference.

[0096] The wind speed difference is compared with the wind speed difference threshold. If the wind speed difference is greater than or equal to the wind speed difference threshold, it is determined that the initial monitoring and warning value should be optimized.

[0097] Otherwise, it is determined that the initial monitoring and early warning value will not be optimized.

[0098] In this embodiment, the wind speed characteristic value, temperature characteristic value, humidity characteristic value and terrain characteristic value are preferably the maximum wind speed, average temperature, average humidity and ground slope, respectively.

[0099] Understandably, the environmental assessment and optimization module, through comprehensive analysis of environmental data, can accurately determine the impact of environmental factors on the safety of the electric suspended platform during actual operation. For example, in high wind conditions, the platform may experience significant wind resistance, increasing the risk of tilting and swaying. Therefore, when the environmental assessment and optimization module detects that the difference between the wind speed characteristic value and the wind speed standard value exceeds a preset wind speed difference threshold, it determines that the wind speed conditions have a significant impact on the platform's safety. In this case, the initial monitoring and warning values ​​need to be optimized to improve the accuracy and timeliness of the warnings.

[0100] Specifically, when the environmental judgment and optimization module determines the environmental deviation value of the suspended platform to be monitored based on the environmental data, it includes:

[0101] Obtain the standard values ​​of temperature, humidity, and terrain corresponding to the temperature characteristic value, humidity characteristic value, and terrain characteristic value, respectively;

[0102] The temperature difference, humidity difference, and terrain difference are obtained. After normalizing the wind speed difference, temperature difference, humidity difference, and terrain difference, the environmental deviation value of the suspended platform to be monitored is determined.

[0103] The environmental deviation value is obtained by the following formula:

[0104] Ed=α1·ΔV'+α2·ΔT'+α3·ΔH'+α4·ΔG'

[0105] Where Ed represents the environmental deviation value; ΔV′ represents the normalized wind speed difference; ΔT′ represents the normalized temperature difference; ΔH′ represents the normalized humidity difference; ΔG′ represents the normalized terrain difference; α1, α2, α3 and α4 represent weighting coefficients, and α1+α2+α3+α4=1.

[0106] In this embodiment, the temperature difference is the difference between the temperature characteristic value and the temperature standard value, the humidity difference is the difference between the humidity characteristic value and the humidity standard value, and the terrain difference is the difference between the terrain characteristic value and the terrain standard value.

[0107] Understandably, the environmental assessment and optimization module comprehensively considers the impact of multiple environmental factors, such as wind speed, temperature, humidity, and terrain, on the safety status of the electric suspended platform when determining the environmental deviation value. By normalizing the differences between these environmental factors and their corresponding standard values, and then weighting them using coefficients, the environmental deviation value is derived. This calculation process not only improves the quantitative assessment capability of the impact of environmental factors but also ensures that the early warning system maintains high accuracy and stability under different environmental conditions.

[0108] Specifically, when the environmental judgment and optimization module determines the optimization coefficient of the initial monitoring and early warning value based on the deviation value of the usage environment, and obtains the optimized monitoring and early warning value, it includes:

[0109] The deviation value of the usage environment is compared with the first deviation value of the usage environment and the second deviation value of the usage environment, and the optimization coefficient is determined based on the comparison result; wherein, the first deviation value of the usage environment is less than the second deviation value of the usage environment.

[0110] When the deviation value of the usage environment is less than or equal to the first deviation value of the usage environment, the optimization coefficient is determined to be the first optimization coefficient;

[0111] When the deviation value of the usage environment is greater than the first deviation value of the usage environment and less than or equal to the second deviation value of the usage environment, the optimization coefficient is determined to be the second optimization coefficient;

[0112] When the deviation value of the usage environment is greater than the deviation value of the second usage environment, the optimization coefficient is determined to be the third optimization coefficient;

[0113] The initial monitoring and early warning value is optimized based on the optimization coefficient to obtain the optimized monitoring and early warning value.

[0114] In this embodiment, the optimization coefficients are represented as (angle optimization coefficient, amplitude optimization coefficient).

[0115] In this embodiment, the first optimization coefficient is preferably (0.8, 0.85), the second optimization coefficient is preferably (0.85, 0.9), and the third optimization coefficient is preferably (0.9, 0.95).

[0116] Understandably, by setting optimization coefficients corresponding to different deviations from the operating environment, the system can appropriately adjust the initial monitoring and warning values ​​according to different environmental conditions, thereby improving the targeting and adaptability of the warnings. When the deviation from the operating environment is small, i.e., the environmental conditions are close to the standard value, the system selects a lower optimization coefficient to reduce oversensitivity to environmental factors. Conversely, when the deviation from the operating environment is large, i.e., the environmental conditions differ significantly from the standard value, the system selects a higher optimization coefficient to strengthen the warning effect and ensure that operators are fully aware of potential safety risks.

[0117] Specifically, when the operation judgment and compensation module determines whether to compensate the optimized monitoring and early warning value based on the real-time operation parameters, it includes:

[0118] Feature extraction is performed on the real-time operating parameters to obtain the maximum real-time operating speed;

[0119] The maximum real-time operating speed is compared with the maximum real-time operating speed threshold. If the maximum real-time operating speed is greater than the maximum real-time operating speed threshold, it is determined that the optimized monitoring and early warning value should be compensated.

[0120] Otherwise, it is determined that no compensation will be made for the optimized monitoring and early warning value.

[0121] Understandably, the operation judgment and compensation module, through monitoring and analyzing real-time operating parameters, can promptly detect potential anomalies during the operation of the electric suspended platform. For example, excessively high operating speeds may increase the platform's tilt and sway, thereby increasing safety hazards. Therefore, when the operation judgment and compensation module detects that the maximum real-time operating speed exceeds the preset maximum real-time operating speed threshold, it determines that the platform's operating status may significantly impact safety. In this case, compensation is needed to optimize the monitoring and warning values ​​to improve the accuracy and timeliness of the warnings.

[0122] Specifically, when the operation judgment and compensation module determines the compensation coefficient of the optimized monitoring early warning value based on the real-time operation parameters and rope monitoring data, and obtains the compensated monitoring early warning value, it includes:

[0123] The rope monitoring data is analyzed to obtain the maximum rope tension value;

[0124] A compensation vector set is constructed based on the maximum real-time operating speed and the maximum rope tension value;

[0125] The compensation vector group is compared with the historical compensation group, and the optimization coefficient is determined based on the comparison result;

[0126] When there is a historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the historical compensation coefficient corresponding to the historical compensation vector group is used as the compensation coefficient.

[0127] When there is no historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the overlap between the compensation vector group and each historical compensation vector group is calculated, the maximum overlap is extracted, and the compensation coefficient is determined based on the maximum overlap.

[0128] The maximum overlap is compared with the mapping compensation coefficient table, and the compensation coefficient is determined based on the comparison result.

[0129] The optimized monitoring and early warning value is compensated according to the compensation coefficient to obtain the compensated monitoring and early warning value.

[0130] Understandably, when a historical compensation group contains a vector group that is identical to the current compensation vector group, the Euclidean distance is 0 and the overlap is 100%. In this case, the corresponding historical compensation coefficient is directly used as the current compensation coefficient. However, when no identical vector group exists in the historical compensation group, the Euclidean distance between the current compensation vector group and each historical compensation vector group is calculated. The historical compensation vector group with the smallest Euclidean distance is extracted, and its corresponding compensation coefficient is used as a basis, combined with the maximum overlap, to fine-tune the compensation coefficient to obtain a more accurate compensation value.

[0131] Understandably, the mapping compensation coefficient table is a pre-defined table that records the compensation coefficients corresponding to different overlap ranges. Once the judgment and compensation module determines the maximum overlap, the corresponding compensation coefficient can be quickly and accurately obtained by looking up the mapping compensation coefficient table. This design not only improves the efficiency of determining the compensation coefficients but also ensures the accuracy and rationality of the compensation values.

[0132] In this embodiment, when the overlap is 86%, the corresponding compensation coefficient is (0.85, 0.85); when the overlap is 92%, the corresponding compensation coefficient is (0.9, 0.9); and when the overlap is 98%, the corresponding compensation coefficient is (0.95, 0.95).

[0133] Specifically, when the early warning module determines the early warning level of the suspended platform to be monitored based on the compensated monitoring early warning value, it includes:

[0134] The warning levels include low, medium, and high.

[0135] The compensation monitoring early warning value is compared with the first compensation monitoring early warning value and the second compensation monitoring early warning value, and the early warning level of the suspended platform to be monitored is determined according to the comparison result; wherein, the first compensation monitoring early warning value is less than the second compensation monitoring early warning value;

[0136] When the compensation monitoring early warning value is less than or equal to the first compensation monitoring early warning value, the early warning level of the suspended platform to be monitored is determined to be low.

[0137] When the compensation monitoring warning value is greater than the first compensation monitoring warning value and less than or equal to the second compensation monitoring warning value, the warning level of the suspended platform to be monitored is determined to be medium.

[0138] When the compensation monitoring early warning value is greater than the second compensation monitoring early warning value, the early warning level of the suspended platform to be monitored is determined to be high.

[0139] Understandably, by setting different warning levels corresponding to different compensation monitoring warning values, the system can classify the safety status of the electric suspended platform into different levels, providing operators with more intuitive and easily understandable warning information. When the compensation monitoring warning value is low, meaning the safety status of the suspended platform is relatively good, the system issues a low-level warning, prompting operators to pay attention to the operating status of the suspended platform. Conversely, when the compensation monitoring warning value is high, meaning there may be significant safety hazards in the suspended platform, the system issues a high-level warning, alerting operators to take immediate measures to ensure construction safety. This design not only improves the readability and operability of the warning information but also effectively enhances the safety assurance capabilities of the electric suspended platform during construction.

[0140] It should also be noted that when issuing warnings, either the compensation basket tilt angle or the compensation basket sway amplitude is selected as the warning indicator, and the higher of the two warning levels is taken as the final warning level. For example, if the warning level for the compensation basket tilt angle is medium and the warning level for the compensation basket sway amplitude is high, the system will ultimately issue a warning based on the high warning level.

[0141] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0143] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxesFigure 1 The function specified in one or more boxes.

[0144] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A smart safety monitoring and early warning system for electric suspended scaffolds used in building construction, characterized in that, include The warning value setting module is configured to identify the suspended platform to be monitored, collect the load distribution data of the suspended platform to be monitored, and determine the initial monitoring warning value of the suspended platform to be monitored based on the load distribution data; wherein, the initial monitoring warning value includes the initial tilt angle of the suspended platform and the initial sway amplitude of the suspended platform; The environmental judgment and optimization module is configured to collect the usage environment data of the suspended platform to be monitored, and parse the usage environment data. Based on the parsing results, it determines whether to optimize the initial monitoring warning value. If so, it determines the usage environment deviation value of the suspended platform to be monitored based on the usage environment data, determines the optimization coefficient of the initial monitoring warning value based on the usage environment deviation value, and obtains the optimized monitoring warning value. The operation judgment and compensation module is configured to collect the real-time operating parameters of the suspended platform to be monitored, and determine whether to compensate the optimized monitoring warning value based on the real-time operating parameters; if so, it collects the rope monitoring data of the suspended platform to be monitored, determines the compensation coefficient of the optimized monitoring warning value based on the real-time operating parameters and the rope monitoring data, and obtains the compensated monitoring warning value. The early warning module is configured to determine the early warning level of the suspended platform to be monitored based on the compensation monitoring early warning value; When the warning value setting module determines the initial monitoring warning value of the suspended platform to be monitored based on the load distribution data, it includes: The load distribution data is analyzed to obtain the number of personnel, personnel weight, personnel location, material weight, and material location; Determine the center position of the suspended platform to be monitored; The overall center of gravity offset of the monitored suspended platform is calculated based on the center location, number of personnel, personnel weight, personnel position, material weight, and material position. The overall center of gravity offset is compared with historical data, and the initial monitoring and early warning value is determined based on the comparison results; When determining the initial monitoring and early warning value based on the comparison results, the following are included: When there is a historical overall center of gravity offset in the historical data that is the same as the overall center of gravity offset, the historical monitoring and early warning value corresponding to the historical overall center of gravity offset is used as the initial monitoring and early warning value. When there is no historical overall center of gravity offset in the historical data that is the same as the overall center of gravity offset, calculate the average value of all the historical overall center of gravity offsets in the historical data and record it as the historical average center of gravity offset. Determine the initial monitoring and warning value based on the historical average center of gravity offset. When determining the initial monitoring and early warning value based on the historical average centroid offset, the following are included: Calculate the absolute value of the difference between the overall center of gravity offset and the historical average center of gravity offset, and record it as the absolute center of gravity offset difference; The absolute center of gravity offset difference is compared with the first absolute center of gravity offset difference and the second absolute center of gravity offset difference, and the initial monitoring and warning value is determined based on the comparison result; wherein, the first absolute center of gravity offset difference is less than the second absolute center of gravity offset difference; When the absolute center of gravity offset difference is less than or equal to the first absolute center of gravity offset difference, the initial monitoring warning value is determined to be the first monitoring warning value; When the absolute center of gravity offset difference is greater than the first absolute center of gravity offset difference and less than or equal to the second absolute center of gravity offset difference, the initial monitoring warning value is determined to be the second monitoring warning value. When the absolute center of gravity offset difference is greater than the second absolute center of gravity offset difference, the initial monitoring warning value is determined to be the third monitoring warning value.

2. The intelligent safety monitoring and early warning system for electric suspended scaffolding used in building construction according to claim 1, characterized in that, When the environment judgment and optimization module parses the usage environment data and determines whether to optimize the initial monitoring and early warning value based on the parsing results, it includes: The environmental data is analyzed to obtain the wind speed characteristic value, temperature characteristic value, humidity characteristic value and terrain characteristic value of the suspended basket to be monitored; Obtain the standard wind speed value corresponding to the wind speed characteristic value, and calculate the difference between the wind speed characteristic value and the standard wind speed value, which is denoted as the wind speed difference. The wind speed difference is compared with the wind speed difference threshold. If the wind speed difference is greater than or equal to the wind speed difference threshold, it is determined that the initial monitoring and warning value should be optimized. Otherwise, it is determined that the initial monitoring and early warning value will not be optimized.

3. The intelligent safety monitoring and early warning system for electric suspended scaffolding used in building construction according to claim 2, characterized in that, When the environmental judgment and optimization module determines the environmental deviation value of the suspended platform to be monitored based on the environmental data, it includes: Obtain the standard values ​​of temperature, humidity, and terrain corresponding to the temperature characteristic value, humidity characteristic value, and terrain characteristic value, respectively; The temperature difference, humidity difference, and terrain difference are obtained. After normalizing the wind speed difference, temperature difference, humidity difference, and terrain difference, the environmental deviation value of the suspended platform to be monitored is determined. The environmental deviation value is obtained by the following formula: Ed=α1·ΔV'+α2·ΔT'+α3·ΔH'+α4·ΔG'; Where Ed represents the environmental deviation value; ΔV′ represents the normalized wind speed difference; ΔT′ represents the normalized temperature difference; ΔH′ represents the normalized humidity difference; ΔG′ represents the normalized terrain difference; α1, α2, α3 and α4 represent weighting coefficients, and α1+α2+α3+α4=1.

4. The intelligent safety monitoring and early warning system for electric suspended scaffolding used in building construction according to claim 3, characterized in that, The environmental judgment and optimization module determines the optimization coefficient of the initial monitoring and early warning value based on the deviation value of the usage environment, and when obtaining the optimized monitoring and early warning value, it includes: The deviation value of the usage environment is compared with the first deviation value of the usage environment and the second deviation value of the usage environment, and the optimization coefficient is determined based on the comparison result; wherein, the first deviation value of the usage environment is less than the second deviation value of the usage environment. When the deviation value of the usage environment is less than or equal to the first deviation value of the usage environment, the optimization coefficient is determined to be the first optimization coefficient; When the deviation value of the usage environment is greater than the first deviation value of the usage environment and less than or equal to the second deviation value of the usage environment, the optimization coefficient is determined to be the second optimization coefficient; When the deviation value of the usage environment is greater than the deviation value of the second usage environment, the optimization coefficient is determined to be the third optimization coefficient; The initial monitoring and early warning value is optimized based on the optimization coefficient to obtain the optimized monitoring and early warning value.

5. The intelligent safety monitoring and early warning system for electric suspended scaffolding used in building construction according to claim 4, characterized in that, When the operation judgment and compensation module determines whether to compensate the optimized monitoring and early warning value based on the real-time operation parameters, it includes: Feature extraction is performed on the real-time operating parameters to obtain the maximum real-time operating speed; The maximum real-time operating speed is compared with the maximum real-time operating speed threshold. If the maximum real-time operating speed is greater than the maximum real-time operating speed threshold, it is determined that the optimized monitoring and early warning value should be compensated. Otherwise, it is determined that no compensation will be made for the optimized monitoring and early warning value.

6. The intelligent safety monitoring and early warning system for electric suspended scaffolding used in building construction according to claim 5, characterized in that, The operation judgment and compensation module determines the compensation coefficient of the optimized monitoring early warning value based on the real-time operation parameters and rope monitoring data, and when obtaining the compensated monitoring early warning value, it includes: The rope monitoring data is analyzed to obtain the maximum rope tension value; A compensation vector set is constructed based on the maximum real-time operating speed and the maximum rope tension value; The compensation vector group is compared with the historical compensation group, and the optimization coefficient is determined based on the comparison result; When there is a historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the historical compensation coefficient corresponding to the historical compensation vector group is used as the compensation coefficient. When there is no historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the overlap between the compensation vector group and each historical compensation vector group is calculated, the maximum overlap is extracted, and the compensation coefficient is determined based on the maximum overlap. The maximum overlap is compared with the mapping compensation coefficient table, and the compensation coefficient is determined based on the comparison result. The optimized monitoring and early warning value is compensated according to the compensation coefficient to obtain the compensated monitoring and early warning value.

7. The intelligent safety monitoring and early warning system for electric suspended scaffolding used in building construction according to claim 6, characterized in that, When the early warning module determines the early warning level of the suspended platform to be monitored based on the compensated monitoring early warning value, it includes: The warning levels include low, medium, and high. The compensation monitoring early warning value is compared with the first compensation monitoring early warning value and the second compensation monitoring early warning value, and the early warning level of the suspended platform to be monitored is determined according to the comparison result; wherein, the first compensation monitoring early warning value is less than the second compensation monitoring early warning value; When the compensation monitoring early warning value is less than or equal to the first compensation monitoring early warning value, the early warning level of the suspended platform to be monitored is determined to be low. When the compensation monitoring warning value is greater than the first compensation monitoring warning value and less than or equal to the second compensation monitoring warning value, the warning level of the suspended platform to be monitored is determined to be medium. When the compensation monitoring early warning value is greater than the second compensation monitoring early warning value, the early warning level of the suspended platform to be monitored is determined to be high.

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