CN119339324A - A computer vision-based construction safety status assessment system and method - Google Patents
A computer vision-based construction safety status assessment system and method Download PDFInfo
- Publication number
- CN119339324A CN119339324A CN202411382916.8A CN202411382916A CN119339324A CN 119339324 A CN119339324 A CN 119339324A CN 202411382916 A CN202411382916 A CN 202411382916A CN 119339324 A CN119339324 A CN 119339324A
- Authority
- CN
- China
- Prior art keywords
- construction
- coefficient
- warning threshold
- hazard warning
- risk
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000010276 construction Methods 0.000 title claims abstract description 604
- 238000000034 method Methods 0.000 title claims abstract description 29
- 230000007613 environmental effect Effects 0.000 claims abstract description 106
- 238000012937 correction Methods 0.000 claims abstract description 66
- 238000012545 processing Methods 0.000 claims abstract description 9
- 239000000463 material Substances 0.000 claims description 56
- 230000006399 behavior Effects 0.000 claims description 51
- 238000012544 monitoring process Methods 0.000 claims description 42
- 230000002159 abnormal effect Effects 0.000 claims description 23
- 238000004458 analytical method Methods 0.000 claims description 20
- 238000009435 building construction Methods 0.000 claims description 18
- 230000008859 change Effects 0.000 claims description 16
- 230000000694 effects Effects 0.000 abstract description 11
- 230000008569 process Effects 0.000 abstract description 6
- 238000005516 engineering process Methods 0.000 abstract description 2
- 238000011156 evaluation Methods 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 7
- 238000004590 computer program Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 7
- 238000013461 design Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 230000004927 fusion Effects 0.000 description 3
- 238000003860 storage Methods 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000010921 in-depth analysis Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000001681 protective effect Effects 0.000 description 2
- 238000012300 Sequence Analysis Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000004035 construction material Substances 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000003828 downregulation Effects 0.000 description 1
- 230000001815 facial effect Effects 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
本发明涉及计算机视觉技术领域，公开了一种基于计算机视觉的建筑施工安全状态评估系统与方法，该系统包括：采集模块；判断模块，被配置为根据历史施工偏离系数判断是否需要对施工危险预警阈值进行修正：当判定需要对施工危险预警阈值进行修正时，设定施工危险预警阈值对应的修正系数，并获得修正施工危险预警阈值；处理模块，被配置为根据环境因素影响系数对修正施工危险预警阈值进行补偿，获得补偿施工危险预警阈值；预警模块，根据比对结果判断施工区域的施工安全状态等级，并根据施工安全状态等级判断是否进行危险预警或危险告警。本发明能够更准确地评估施工过程中的潜在风险，并及时发出预警或告警信号，确保施工活动的顺利进行。
The present invention relates to the field of computer vision technology, and discloses a construction safety status assessment system and method based on computer vision, the system comprising: an acquisition module; a judgment module, configured to judge whether it is necessary to correct the construction hazard warning threshold according to the historical construction deviation coefficient: when it is determined that the construction hazard warning threshold needs to be corrected, the correction coefficient corresponding to the construction hazard warning threshold is set, and the corrected construction hazard warning threshold is obtained; a processing module, configured to compensate the corrected construction hazard warning threshold according to the environmental factor influence coefficient, and obtain the compensated construction hazard warning threshold; an early warning module, judging the construction safety status level of the construction area according to the comparison result, and judging whether to perform a danger warning or danger alarm according to the construction safety status level. The present invention can more accurately assess the potential risks in the construction process, and issue early warning or alarm signals in time to ensure the smooth progress of construction activities.
Description
Technical Field
The invention relates to the technical field of computer vision, in particular to a building construction safety state evaluation system and method based on computer vision.
Background
Computer vision, an important branch of the field of artificial intelligence, simulates the human visual system by analyzing and understanding features in high-dimensional data such as images, video, and the like. At present, the technology is widely applied to a plurality of fields such as remote sensing image analysis, facial recognition, gesture detection and the like, and has gained wide acceptance. According to the difference of feature extraction technologies, computer vision methods are mainly divided into two methods based on traditional manual feature extraction and based on deep learning. In the existing building construction safety state evaluation system based on computer vision, simple analysis is performed only by relying on video or image data, and the complexity and the variability of a construction environment cannot be fully considered.
Disclosure of Invention
In view of the above, the invention provides a system and a method for evaluating the safety state of building construction based on computer vision, which aim to solve the problems that the prior art only relies on video or image data for simple analysis and the complexity and the variability of the construction environment are not fully considered.
In one aspect, the present invention provides a computer vision-based construction safety state assessment system, comprising:
The system comprises an acquisition module, a history construction record library, a construction deviation coefficient calculation module and a construction deviation coefficient calculation module, wherein the acquisition module is configured to determine a monitoring area in a building construction area, acquire construction stage information of the monitoring area and determine a construction danger early warning threshold according to the construction stage information;
The judging module is configured to judge whether the construction hazard early warning threshold needs to be corrected according to the historical construction deviation coefficient, when the construction hazard early warning threshold needs to be corrected, setting a correction coefficient corresponding to the construction hazard early warning threshold and obtaining a corrected construction hazard early warning threshold;
the judging module is further configured to control the collecting module to collect the environmental data of the monitoring area, analyze the environmental data, judge whether the correction construction hazard early warning threshold needs to be compensated based on an analysis result, and calculate an environmental factor influence coefficient of the monitoring area when the correction construction hazard early warning threshold is judged to be compensated;
the processing module is configured to compensate the corrected construction danger early warning threshold according to the environmental factor influence coefficient to obtain a compensated construction danger early warning threshold;
The early warning module is configured to control the acquisition module to acquire construction behavior data and building structure change data of the construction area, calculate a construction danger value according to the construction behavior data and the building structure change data, compare the construction danger value with a compensation construction danger early warning threshold value, judge a construction safety state grade of the construction area according to a comparison result, and judge whether to perform danger early warning or danger warning according to the construction safety state grade.
Further, analyzing the history construction record, and calculating the history construction deviation coefficient based on the analysis result includes:
analyzing the historical construction records to obtain normal construction behaviors and construction danger associated abnormal construction behaviors;
Determining construction risk factors corresponding to each construction risk associated abnormal construction behavior, and constructing a construction risk factor sequence;
counting a first number of the normal construction behaviors and a second number of the construction risk associated abnormal construction behaviors, and calculating a historical construction deviation coefficient of the monitoring area according to the first number, the second number and a construction risk factor sequence;
wherein C represents the historical construction deviation coefficient Na represents the second number, nb represents the first number, n represents the number of construction risk factors, and Ri represents the ith construction risk factor in the construction risk factor sequence.
Further, when determining the construction risk factor corresponding to each construction risk associated abnormal construction behavior, the method includes:
Extracting actual construction time and actual material consumption corresponding to construction dangerous association abnormal construction behaviors, obtaining planned construction time and planned material consumption, calculating a first construction time difference value according to the actual construction time and the planned construction time, and calculating a first material consumption difference value according to the actual material consumption and the planned material consumption;
Analyzing all normal construction behaviors, determining the construction time and the material consumption corresponding to each normal construction behavior, and extracting the minimum construction time and the minimum material consumption;
Calculating a second construction time difference value according to the actual construction time and the minimum construction time, and calculating a second material consumption difference value according to the actual material consumption and the minimum material consumption;
calculating a construction risk factor corresponding to each construction risk associated abnormal construction behavior based on the first construction time difference value, the first material consumption difference value, the second construction time difference value and the second material consumption difference value, wherein the construction risk factor is obtained by the following formula:
Wherein R represents the construction risk factor, α1 and α2 represent the weight coefficient of the first construction time difference and the weight coefficient of the first material usage difference, respectively, and the sum of α1 and α2 is 1, β1 and β2 represent the weight coefficient of the second construction time difference and the weight coefficient of the second material usage difference, respectively, and the sum of β1 and β2 is 1, Δt1 represents the first construction time difference, tj represents the planned construction time, Δm1 represents the first material usage difference, mj represents the minimum material usage, Δt2 represents the second construction time difference, tm represents the minimum construction time, Δm2 represents the second material usage difference, and Mm represents the minimum material usage.
Further, determining whether the construction hazard early warning threshold needs to be corrected according to the historical construction deviation coefficient includes:
comparing the historical construction deviation coefficient with a construction deviation coefficient threshold value, and judging whether the construction danger early warning threshold value needs to be corrected according to the comparison result;
When the historical construction deviation coefficient is smaller than or equal to the construction deviation coefficient threshold value, judging that the construction danger early warning threshold value does not need to be corrected;
and when the historical construction deviation coefficient is larger than the construction deviation coefficient threshold value, judging that the construction danger early warning threshold value needs to be corrected.
Further, setting a correction coefficient corresponding to the construction hazard early warning threshold, and when obtaining the corrected construction hazard early warning threshold, the method comprises the following steps:
the correction coefficients comprise a first correction coefficient, a second correction coefficient and a third correction coefficient;
calculating a coefficient ratio of the historical construction deviation coefficient to the construction deviation coefficient threshold;
When the coefficient ratio is greater than 1 and less than or equal to 1.1, selecting the first correction coefficient as the correction coefficient of the construction hazard early warning threshold, and multiplying the first correction coefficient by the construction hazard early warning threshold to obtain the corrected construction hazard early warning threshold;
When the coefficient ratio is greater than 1.1 and less than or equal to 1.3, selecting the second correction coefficient as the correction coefficient of the construction hazard early warning threshold, and multiplying the second correction coefficient by the construction hazard early warning threshold to obtain the corrected construction hazard early warning threshold;
And when the coefficient ratio is greater than 1.3, selecting the third correction coefficient as the correction coefficient of the construction danger early warning threshold, and multiplying the third correction coefficient by the construction danger early warning threshold to obtain the corrected construction danger early warning threshold.
Further, when judging whether the correction construction hazard early warning threshold needs to be compensated based on the analysis result, the method comprises the following steps:
comparing the environment parameter value with the parameter standard value, and judging whether to compensate the corrected construction hazard early warning threshold according to the comparison result;
when the environmental parameter values are not larger than the corresponding parameter standard values, judging that the correction construction danger early warning threshold is not compensated;
And when all the environmental parameter values are larger than the corresponding parameter standard values, judging to compensate the corrected construction danger early warning threshold value.
Further, when it is determined to compensate the corrected construction hazard pre-warning threshold, calculating an environmental factor influence coefficient of the monitoring area includes:
Extracting all environment parameter values larger than the parameter standard value, and calculating the difference value of each parameter standard value and the environment parameter value;
comparing the difference value with a difference value threshold, acquiring all difference values smaller than or equal to the difference value threshold according to the comparison result, establishing a first difference value set, acquiring all difference values larger than the difference value threshold, establishing a second difference value set, and calculating a first average difference value of the first difference value set and a second average difference value of the second difference value set;
Calculating the environmental factor influence coefficient according to the first average difference value and the second average difference value, wherein the environmental factor influence coefficient is obtained by the following formula:
wherein Ef represents the environmental factor influence coefficient, η1 and η2 represent the weight coefficient of the first average difference value and the weight coefficient of the second average difference value, and the sum of η1 and η2 is 1, Δ1 represents the first average difference value, Δ2 represents the second average difference value, k represents the adjustment coefficient, and k is greater than 1.
Further, compensating the corrected construction danger early warning threshold according to the environmental factor influence coefficient, when obtaining the compensated construction danger early warning threshold, the method comprises the following steps:
comparing the environmental factor influence coefficient with a first environmental factor influence coefficient and a second environmental factor influence coefficient, and selecting different compensation coefficients according to the comparison result, wherein the compensation coefficients comprise a first compensation coefficient, a second compensation coefficient and a third compensation coefficient;
when the environmental factor influence coefficient is smaller than the first environmental factor influence coefficient, selecting the first compensation coefficient as a compensation coefficient corresponding to the corrected construction danger early warning threshold value, and multiplying the first compensation coefficient by the corrected construction danger early warning threshold value to obtain a corrected construction danger early warning threshold value;
When the environmental factor influence coefficient is larger than or equal to the first environmental factor influence coefficient and smaller than the second environmental factor influence coefficient, selecting the second compensation coefficient as a compensation coefficient corresponding to the corrected construction danger early warning threshold value, and multiplying the second compensation coefficient by the corrected construction danger early warning threshold value to obtain a corrected construction danger early warning threshold value;
When the environmental factor influence coefficient is greater than or equal to the second environmental factor influence coefficient, selecting the third compensation coefficient as a compensation coefficient corresponding to the corrected construction danger early warning threshold value, and multiplying the third compensation coefficient by the corrected construction danger early warning threshold value to obtain the corrected construction danger early warning threshold value.
Further, judging the construction safety state level of the construction area according to the comparison result, and judging whether to perform danger early warning or warning according to the construction safety state level, wherein the method comprises the following steps:
when the construction danger value is smaller than the compensation construction danger early warning threshold value, judging the light level of the construction safety state level of the construction area, and not carrying out danger early warning or danger warning;
when the construction danger value is equal to the compensation construction danger early warning threshold value, judging the middle level of the construction safety state level of the construction area, and carrying out danger early warning but not carrying out danger warning;
And when the construction danger value is larger than the compensation construction danger early warning threshold value, judging the heavy grade of the construction safety state grade of the construction area, and directly carrying out danger warning.
Compared with the prior art, the computer vision-based building construction safety state evaluation system has the advantages that the construction danger early warning threshold can be adjusted according to construction stage information, scientificity and pertinence of early warning standards are guaranteed, a powerful basis is provided for dynamic adjustment of the early warning threshold through in-depth analysis of historical construction records and calculated historical construction deviation coefficients, the problem of false report or missing report caused by improper setting of the fixed threshold is effectively avoided, the influence of environmental factors on construction safety is fully considered, environmental factor influence coefficients are calculated through collecting and analyzing environmental data of a monitoring area, and further compensation is conducted on the corrected construction danger early warning threshold, so that the early warning threshold is closer to an actual construction environment, and early warning accuracy and reliability are improved. By collecting construction behavior data and building structure change data of a construction area, comprehensive monitoring of a construction safety state is achieved, and fusion analysis of the multidimensional data enables a system to evaluate potential risks in a construction process more accurately and send early warning or warning signals timely, so that constructors can take measures timely, potential safety hazards are eliminated, and smooth construction activities are guaranteed.
In another aspect, the invention further provides a building construction safety state assessment method based on computer vision, which comprises the following steps:
S100, determining a monitoring area in a building construction area, acquiring construction stage information of the monitoring area, and determining a construction danger early warning threshold according to the construction stage information; extracting corresponding historical construction records from a historical construction record library based on the monitoring area and the construction danger early warning threshold value, analyzing the historical construction records, and calculating a historical construction deviation coefficient based on an analysis result;
s200, judging whether the construction hazard early warning threshold needs to be corrected according to the historical construction deviation coefficient, setting a correction coefficient corresponding to the construction hazard early warning threshold when the construction hazard early warning threshold needs to be corrected, and obtaining a corrected construction hazard early warning threshold;
S300, collecting environment data of the monitoring area, analyzing the environment data, judging whether the correction construction danger early warning threshold needs to be compensated based on an analysis result, and calculating an environment factor influence coefficient of the monitoring area when the correction construction danger early warning threshold is judged to be compensated;
s400, compensating the corrected construction danger early warning threshold according to the environmental factor influence coefficient to obtain a compensated construction danger early warning threshold;
S500, collecting construction behavior data and building structure change data of the construction area, calculating a construction danger value according to the construction behavior data and the building structure change data, comparing the construction danger value with a compensation construction danger early warning threshold value, judging a construction safety state grade of the construction area according to a comparison result, and judging whether to perform danger early warning or danger warning according to the construction safety state grade.
It can be appreciated that the system and the method for evaluating the safety state of the building construction based on computer vision have the same beneficial effects and are not described herein.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 is a block diagram of a system for evaluating the safety status of a building construction based on computer vision according to an embodiment of the present invention;
fig. 2 is a flowchart of a building construction safety state evaluation method based on computer vision according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below 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 embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
Referring to fig. 1, in some embodiments of the present application, a system for evaluating a safety state of a building construction based on computer vision is provided, including:
The system comprises a monitoring area, an acquisition module, a historical construction record library, a historical construction deviation coefficient calculation module, a construction deviation coefficient calculation module and a construction deviation coefficient calculation module, wherein the monitoring area is configured to be determined in a building construction area, construction stage information of the monitoring area is acquired, and a construction danger early warning threshold value is determined according to the construction stage information;
in some embodiments of the invention, the construction phase information includes a current construction phase (e.g., foundation construction, body structure construction, finishing phase, etc.).
In some embodiments of the invention, the construction hazard pre-warning threshold is determined from different construction stage information. For example, for a finishing stage, the construction hazard warning threshold may be set relatively low because more detail work and personnel flow are involved at this time, increasing the possibility of accident occurrence, while for a main structure construction stage, the construction hazard warning threshold may be correspondingly increased because the involved construction activities are more basic and critical, to ensure structural safety.
The judging module is configured to judge whether the construction hazard early warning threshold needs to be corrected according to the historical construction deviation coefficient, when the construction hazard early warning threshold needs to be corrected, setting a correction coefficient corresponding to the construction hazard early warning threshold, and obtaining the corrected construction hazard early warning threshold;
The judging module is further configured to control the collecting module to collect the environmental data of the monitoring area, analyze the environmental data, judge whether the correction construction danger early warning threshold needs to be compensated based on the analysis result, and calculate the environmental factor influence coefficient of the monitoring area when the correction construction danger early warning threshold is judged to be compensated;
the processing module is configured to compensate the corrected construction danger early warning threshold according to the environmental factor influence coefficient to obtain a compensated construction danger early warning threshold;
The early warning module is configured to control the acquisition module to acquire construction behavior data and building structure change data of a construction area, calculate a construction danger value according to the construction behavior data and the building structure change data, compare the construction danger value with a compensation construction danger early warning threshold value, judge a construction safety state grade of the construction area according to the comparison result, and judge whether to perform danger early warning or danger warning according to the construction safety state grade.
In the embodiment, the judging module is used for making an intelligent decision according to the historical construction deviation coefficient so as to optimize the accuracy of the construction danger early warning threshold value, the processing module is used for carrying out fine adjustment on the environmental factors so as to ensure the comprehensiveness and accuracy of construction safety assessment, and the early warning module is used for monitoring and responding to potential safety risks in real time and improving the early warning efficiency through multi-dimensional data fusion.
It can be understood that the construction safety state evaluation system based on computer vision can adjust the construction danger early warning threshold according to construction stage information, ensure scientificity and pertinence of early warning standards, provide powerful basis for dynamic adjustment of the early warning threshold by deeply analyzing historical construction records and calculating the obtained historical construction deviation coefficient, effectively avoid the problem of false report or missing report caused by improper setting of a fixed threshold, fully consider the influence of environmental factors on construction safety, calculate the environmental factor influence coefficient by collecting and analyzing environmental data of a monitoring area, and further compensate the corrected construction danger early warning threshold, so that the early warning threshold is closer to an actual construction environment, and the accuracy and reliability of early warning are improved. By collecting construction behavior data and building structure change data of a construction area, comprehensive monitoring of a construction safety state is achieved, and fusion analysis of the multidimensional data enables a system to evaluate potential risks in a construction process more accurately and send early warning or warning signals timely, so that constructors can take measures timely, potential safety hazards are eliminated, and smooth construction activities are guaranteed.
In some embodiments of the present application, analyzing the historical construction record, when calculating the historical construction deviation coefficient based on the analysis result, includes:
analyzing the historical construction record to obtain normal construction behaviors and construction danger associated abnormal construction behaviors;
Determining construction risk factors corresponding to each construction risk associated abnormal construction behavior, and constructing a construction risk factor sequence;
Counting a first number of normal construction behaviors and a second number of construction risk associated abnormal construction behaviors, and calculating a historical construction deviation coefficient of a monitoring area according to the first number, the second number and a construction risk factor sequence;
Wherein C represents the historical construction deviation coefficient Na represents the second number, nb represents the first number, n represents the number of construction risk factors, and Ri represents the i-th construction risk factor in the construction risk factor sequence.
In this embodiment, the historic construction record library is generated by systematically recording information of each construction stage, and the main contents of the historic construction record library include specific construction activities, participators, construction time, used materials, equipment and any abnormal or accident records occurring at each construction stage.
In this embodiment, the normal construction behavior refers to a conventional operation flow meeting the safety specification, the technical standard and the design requirement in the building construction process, and the construction risk-related abnormal construction behavior refers to a construction activity having obvious deviation or not meeting the safety specification, the technical standard and the design requirement compared with the normal construction behavior. These abnormal construction behaviors are often closely related to construction hazards and may directly lead to the occurrence of safety accidents.
In some embodiments of the present application, when determining a construction risk factor corresponding to each construction risk associated abnormal construction behavior, the method includes:
Extracting actual construction time and actual material consumption corresponding to construction dangerous association abnormal construction behaviors, obtaining planned construction time and planned material consumption, calculating a first construction time difference value according to the actual construction time and the planned construction time, and calculating a first material consumption difference value according to the actual material consumption and the planned material consumption;
Analyzing all normal construction behaviors, determining the construction time and the material consumption corresponding to each normal construction behavior, and extracting the minimum construction time and the minimum material consumption;
Calculating a second construction time difference value according to the actual construction time and the minimum construction time, and calculating a second material consumption difference value according to the actual material consumption and the minimum material consumption;
Calculating a construction risk factor corresponding to each construction risk associated abnormal construction behavior based on the first construction time difference value, the first material consumption difference value, the second construction time difference value and the second material consumption difference value, wherein the construction risk factor is obtained by the following formula:
Wherein R represents a construction risk factor, α1 and α2 represent a weight coefficient of a first construction time difference and a weight coefficient of a first material usage difference, respectively, and a sum of α1 and α2 is 1, β1 and β2 represent a weight coefficient of a second construction time difference and a weight coefficient of a second material usage difference, respectively, and a sum of β1 and β2 is 1, Δt1 represents a first construction time difference, tj represents a planned construction time, Δm1 represents a first material usage difference, mj represents a minimum material usage, Δt2 represents a second construction time difference, tm represents a minimum construction time, Δm2 represents a second material usage difference, and Mm represents a minimum material usage.
In the present embodiment, α1 and α2, β1 and β2 represent the importance of the difference values of different dimensions in evaluating the construction risk factor, respectively. The weight coefficients can be adjusted according to actual construction experience and expert opinion so as to ensure that the calculation of construction risk factors is scientific and reasonable. And finally, calculating the formula to obtain the construction risk factor corresponding to each construction risk associated abnormal construction behavior. The construction risk factors not only consider the deviation of construction time and material consumption, but also combine the comparison with the optimal construction state, so that the risk degree of the construction activity can be reflected more accurately. The method provides an important basis for subsequent construction safety evaluation, adjustment of early warning threshold values and decision-making of dangerous early warning or alarming.
In some embodiments of the present application, determining whether a construction hazard warning threshold needs to be corrected according to a historical construction deviation coefficient includes:
Comparing the historical construction deviation coefficient with a construction deviation coefficient threshold value, and judging whether the construction danger early warning threshold value needs to be corrected according to the comparison result;
when the historical construction deviation coefficient is smaller than or equal to the construction deviation coefficient threshold value, judging that the construction danger early warning threshold value does not need to be corrected;
when the historical construction deviation coefficient is larger than the construction deviation coefficient threshold value, the construction danger early warning threshold value is judged to be required to be corrected.
In the embodiment, the construction deviation coefficient threshold value is obtained according to the historical construction deviation coefficient, and is predicted and determined by combining time sequence analysis and a machine learning algorithm, wherein the value reflects the normal fluctuation range of the construction deviation coefficient and is an important reference basis for evaluating whether the current construction state is abnormal or not. The historical construction deviation coefficient is analyzed by using the time sequence model, and a machine learning algorithm is introduced to train and optimize the model, so that the prediction accuracy can be further improved, and the predicted value of the construction deviation coefficient is closer to the actual situation.
In some embodiments of the present application, setting a correction coefficient corresponding to a construction hazard early warning threshold, and obtaining the corrected construction hazard early warning threshold includes:
the correction coefficients comprise a first correction coefficient, a second correction coefficient and a third correction coefficient;
Calculating a coefficient ratio of the historical construction deviation coefficient to a construction deviation coefficient threshold;
When the coefficient ratio is greater than 1 and less than or equal to 1.1, selecting a first correction coefficient as a correction coefficient of the construction hazard early warning threshold, and multiplying the first correction coefficient by the construction hazard early warning threshold to obtain a corrected construction hazard early warning threshold;
When the coefficient ratio is greater than 1.1 and less than or equal to 1.3, selecting a second correction coefficient as the correction coefficient of the construction danger early warning threshold value, and multiplying the second correction coefficient by the construction danger early warning threshold value to obtain a corrected construction danger early warning threshold value;
when the coefficient ratio is greater than 1.3, selecting the third correction coefficient as the correction coefficient of the construction danger early warning threshold value, and multiplying the third correction coefficient by the construction danger early warning threshold value to obtain the corrected construction danger early warning threshold value.
In this embodiment, the first correction coefficient is preferably 0.95, the second correction coefficient is preferably 0.9, and the third correction coefficient is preferably 0.85. Such settings are based on in-depth analysis of actual construction deviations and statistical rules of historical data. By setting different correction coefficients, different degrees of the construction deviation coefficient exceeding the normal range can be more flexibly dealt with, and therefore accurate adjustment of the construction danger early warning threshold is achieved.
It will be appreciated that the setting of the correction factor is not constant, but can be dynamically adjusted according to the actual construction situation and expert opinion. By continuously optimizing the value of the correction coefficient, the construction danger early warning system can be ensured to be always kept in the optimal state, and powerful guarantee is provided for construction safety.
In some embodiments of the present application, when determining whether compensation for the corrected construction hazard warning threshold is required based on the analysis result, the method includes:
Comparing the environment parameter value with the parameter standard value, and judging whether to compensate the corrected construction hazard early warning threshold according to the comparison result;
When the parameter values in all environments are not larger than the corresponding parameter standard values, judging that the correction construction danger early warning threshold is not compensated;
And when all the environmental parameter values are larger than the corresponding parameter standard values, judging to compensate the corrected construction hazard early warning threshold.
In this embodiment, the environmental parameter values include temperature, humidity, wind speed, which have a non-negligible effect on the performance of the construction activity. The variation of these parameters may be directly related to the performance of the construction material, the operating efficiency of the equipment, and the working state of the constructor, thereby affecting the construction risk. Therefore, the environmental parameters are brought into the consideration range of the construction hazard early warning system, and the method is an important means for improving the comprehensiveness and the accuracy of the early warning system.
In some embodiments of the present application, when determining to compensate for the corrected construction hazard pre-warning threshold, calculating an environmental factor influence coefficient of the monitored area includes:
Extracting all environment parameter values larger than the parameter standard value, and calculating the difference value of each parameter standard value and the environment parameter value;
Comparing the difference value with a difference value threshold, acquiring all difference values smaller than or equal to the difference value threshold according to the comparison result, establishing a first difference value set, acquiring all difference values larger than the difference value threshold, establishing a second difference value set, and calculating a first average difference value of the first difference value set and a second average difference value of the second difference value set;
calculating an environmental factor influence coefficient according to the first average difference value and the second average difference value, wherein the environmental factor influence coefficient is obtained by the following formula:
wherein Ef represents an environmental factor influence coefficient, η1 and η2 represent a weight coefficient of a first average difference value and a weight coefficient of a second average difference value, and a sum of η1 and η2 is 1, Δ1 represents the first average difference value, Δ2 represents the second average difference value, k represents an adjustment coefficient, and k is greater than 1.
In the present embodiment, the setting of the weight coefficients η1 and η2 is based on the evaluation of the degree of influence on the different environmental parameters. In general, the environmental parameter value represented by the first average difference Δ1 exceeds the standard value, but the degree of deviation is relatively small, and may not directly affect or affect the construction little, so a low weight coefficient η1 is given. In contrast, the environmental parameter value represented by the second average difference value Δ2 significantly exceeds the standard value, and is likely to pose a great threat to construction safety, so that it is necessary to assign a high weight coefficient η2. Such a setting helps to more accurately reflect the extent of influence of environmental factors on the construction hazard warning threshold. The adjustment coefficient k is obtained through historical experience and serves to adjust the sensitivity of the environmental factor influence coefficient. When the environmental parameter value deviates from the standard value far, the influence coefficient of the environmental factor can be more remarkable by increasing the k value, so that the effect of the environmental factor is more prominent in construction danger early warning. On the contrary, when the environmental parameter value only slightly deviates from the standard value, the excessive reaction can be avoided by properly reducing the k value, and the stability and the accuracy of the early warning system are ensured.
In some embodiments of the present application, compensating the corrected construction hazard pre-warning threshold according to the environmental factor influence coefficient, when obtaining the compensated construction hazard pre-warning threshold, includes:
Comparing the environmental factor influence coefficient with the first environmental factor influence coefficient and the second environmental factor influence coefficient, and selecting different compensation coefficients according to the comparison result, wherein the compensation coefficients comprise a first compensation coefficient, a second compensation coefficient and a third compensation coefficient;
When the environmental factor influence coefficient is smaller than the first environmental factor influence coefficient, selecting the first compensation coefficient as a compensation coefficient corresponding to the corrected construction danger early warning threshold value, and multiplying the first compensation coefficient by the corrected construction danger early warning threshold value to obtain a corrected construction danger early warning threshold value;
When the environmental factor influence coefficient is larger than or equal to the first environmental factor influence coefficient and smaller than the second environmental factor influence coefficient, selecting the second compensation coefficient as a compensation coefficient corresponding to the corrected construction danger early warning threshold value, and multiplying the second compensation coefficient by the corrected construction danger early warning threshold value to obtain the corrected construction danger early warning threshold value;
When the environmental factor influence coefficient is greater than or equal to the second environmental factor influence coefficient, selecting a third compensation coefficient as a compensation coefficient corresponding to the corrected construction danger early warning threshold value, and multiplying the third compensation coefficient by the corrected construction danger early warning threshold value to obtain the corrected construction danger early warning threshold value.
In this embodiment, in order to further refine the construction hazard early warning system under the influence of environmental factors, we introduce a multi-level compensation mechanism. First, by setting the first and second environmental factor influence coefficients as reference points, the system is able to automatically select the corresponding compensation coefficients according to different environmental pressure levels. The design not only improves the flexibility of the early warning system, but also ensures that the accuracy and the effectiveness of early warning can be kept under different environmental conditions. And setting the value of the first compensation coefficient to be close to 1, wherein the adjustment range of the early warning threshold value for correcting the construction danger is not large under the condition of small influence of environmental factors. The system is mainly used for avoiding the overstress reaction when the environmental parameters deviate from the standard values slightly, so that the normal operation of construction is affected. When the environmental factor influence coefficient increases between the first environmental factor influence coefficient and the second environmental factor influence coefficient, the system selects the second compensation coefficient. The value of the coefficient is smaller than the first compensation coefficient, which means that the system can perform larger-amplitude down-regulation on the corrected construction risk early warning threshold value under the condition that the environmental pressure is increased so as to early warn the potential construction risk. And when the environmental factor influence coefficient exceeds the second environmental factor influence coefficient, the threat of the current environment to construction safety is very serious. At this point, the system will enable a third compensation coefficient whose value will be much lower than the former two to achieve maximum amplitude adjustment for correcting the construction hazard warning threshold. The design ensures that the system can quickly and accurately give out early warning under extreme environmental conditions, and provides enough time and space for constructors to take necessary protective measures.
In some embodiments of the present application, when determining a construction safety state level of a construction area according to a comparison result and determining whether to perform danger early warning or alarm according to the construction safety state level, the method includes:
when the construction danger value is smaller than the compensation construction danger early warning threshold value, judging the light level of the construction safety state level of the construction area, and not carrying out danger early warning or danger warning;
When the construction danger value is equal to the compensation construction danger early warning threshold value, judging the middle level of the construction safety state level of the construction area, and carrying out danger early warning but not carrying out danger warning;
When the construction danger value is larger than the compensation construction danger early warning threshold value, judging the heavy level of the construction safety state level of the construction area, and directly carrying out danger warning.
In the present embodiment, the construction behavior data includes construction operation type data, operator information data, and construction equipment status data, and the building structure change data includes building structure deformation amount, stress distribution data, and crack monitoring data. When calculating construction hazard values according to construction behavior data and building structure change data, adopting a formulaCalculation is performed, wherein P represents a construction hazard value, i=1, 2,..6, μi represents construction operation type data, operator information data, construction equipment state data, building structure deformation amount, stress distribution data, and weight coefficients corresponding to crack monitoring data, X1 (t) represents a risk score of the construction operation type at time t, X2 (t) represents a risk score of the operator information data at time t, X3 (t) represents a risk score of the construction equipment state at time t, X4 (t) represents a building structure deformation amount at time t, X5 (t) represents an instantaneous value of the stress distribution at time t, X6 (t) represents a risk score of the crack monitoring data at time t, γ and ε represent adjustment parameters, and obtained empirically.
In this embodiment, when the construction danger value is lower than the compensated construction danger early warning threshold, we determine that the construction safety state level of the construction area is "light level", the construction environment is relatively safe at this time, and the construction activity can be performed normally without performing danger early warning or warning. When the construction danger value is just equal to the compensation construction danger early warning threshold value, the construction safety state level rises to be a middle level, and at the moment, the system starts to send out a danger early warning signal to prompt constructors to pay attention to potential risks, but the degree of emergency warning is not reached yet. And finally, when the construction danger value exceeds the compensation construction danger early warning threshold value, judging the construction safety state grade as a heavy grade, immediately starting a danger warning process by the system, and sending an emergency warning to constructors in various modes such as sound, optical signals and the like to ensure that the constructors can quickly take necessary protective measures to avoid construction accidents.
Referring to fig. 2, in some embodiments of the present application, a method for evaluating a safety state of a building construction based on computer vision is provided, which includes the following steps:
S100, determining a monitoring area in a building construction area, acquiring construction stage information of the monitoring area, and determining a construction danger early warning threshold according to the construction stage information; extracting corresponding historical construction records from a historical construction record library based on the monitoring area and the construction danger early warning threshold value, analyzing the historical construction records, and calculating a historical construction deviation coefficient based on an analysis result;
s200, judging whether the construction hazard early warning threshold needs to be corrected according to the historical construction deviation coefficient, setting a correction coefficient corresponding to the construction hazard early warning threshold when the construction hazard early warning threshold needs to be corrected, and obtaining a corrected construction hazard early warning threshold;
S300, collecting environment data of the monitoring area, analyzing the environment data, judging whether the correction construction danger early warning threshold needs to be compensated based on an analysis result, and calculating an environment factor influence coefficient of the monitoring area when the correction construction danger early warning threshold is judged to be compensated;
s400, compensating the corrected construction danger early warning threshold according to the environmental factor influence coefficient to obtain a compensated construction danger early warning threshold;
S500, collecting construction behavior data and building structure change data of the construction area, calculating a construction danger value according to the construction behavior data and the building structure change data, comparing the construction danger value with a compensation construction danger early warning threshold value, judging a construction safety state grade of the construction area according to a comparison result, and judging whether to perform danger early warning or danger warning according to the construction safety state grade.
It will be appreciated by those skilled in the art that embodiments of the application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flowchart and/or block of the flowchart illustrations and/or block diagrams, and combinations of flowcharts and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may 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, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the specific embodiments of the present invention without departing from the spirit and scope of the present invention, and any modifications and equivalents are intended to be included in the scope of the claims of the present invention.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411382916.8A CN119339324A (en) | 2024-09-30 | 2024-09-30 | A computer vision-based construction safety status assessment system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411382916.8A CN119339324A (en) | 2024-09-30 | 2024-09-30 | A computer vision-based construction safety status assessment system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN119339324A true CN119339324A (en) | 2025-01-21 |
Family
ID=94272109
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411382916.8A Pending CN119339324A (en) | 2024-09-30 | 2024-09-30 | A computer vision-based construction safety status assessment system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119339324A (en) |
-
2024
- 2024-09-30 CN CN202411382916.8A patent/CN119339324A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Alaswad et al. | A review on condition-based maintenance optimization models for stochastically deteriorating system | |
| CN117995403B (en) | Wearable vital sign monitoring system for field operations | |
| JPS59229622A (en) | Diagnosing device of plant | |
| JP5179086B2 (en) | Industrial process monitoring method and monitoring system | |
| US11740592B2 (en) | Control method, control apparatus, mechanical equipment, and recording medium | |
| CN109690641B (en) | Method and system for pre-detecting signs of abnormality in nuclear power plant equipment including process for determining equipment importance and alarm validity | |
| JP2021179740A (en) | Monitoring device, monitoring method, program, and model training device | |
| CN116611712A (en) | Semantic inference-based power grid work ticket evaluation system | |
| CN113369979A (en) | Online monitoring numerical control lathe cooling system based on cloud computing | |
| CN118504794A (en) | Intelligent fault diagnosis system of electric spark forming machine | |
| CN115358155A (en) | Power big data abnormity early warning method, device, equipment and readable storage medium | |
| CN114862167A (en) | Production safety assessment management method and system for manufacturing production line | |
| US20210192384A1 (en) | Device and method for monitoring a system | |
| KR102711443B1 (en) | Device of detecting emergency for risk prevention for root industry workers | |
| CN115049260A (en) | Application method and system of cognitive intelligent continuous casting ladle quality pre-judgment model | |
| CN119339324A (en) | A computer vision-based construction safety status assessment system and method | |
| US11544580B2 (en) | Methods and systems for improving asset operation based on identification of significant changes in sensor combinations in related events | |
| US20220188570A1 (en) | Learning apparatus, learning method, computer program and recording medium | |
| WO2022085350A1 (en) | Method for building abnormality diagnosis model, abnormality diagnosis method, device for building abnormality diagnosis model, and abnormality diagnosis device | |
| CN118840852B (en) | A method and system for monitoring and early warning of enterprise production safety environment based on industrial Internet | |
| CN114386730B (en) | A combustion stability evaluation method and system | |
| CN119289568B (en) | Sensor control system of refrigerant recycling machine | |
| CN118569658B (en) | A hazardous chemicals storage safety risk management system based on digital twin technology | |
| CN119147048B (en) | An environmental monitoring method and system based on digital twin technology | |
| CN118429888B (en) | Cutter detection method and device and shield equipment control method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |