Construction site risk operation data management method and system

Abstract

The invention discloses a construction site risk operation data management method and system, and relates to the technical field of data management. According to the construction site risk operation data management method and system, historical normal operation data stored in a database are obtained, the historical normal operation data are analyzed, and normal operation historical data parameter factors are obtained; and obtaining current construction site risk data. Through an intelligent data analysis and risk level classification mechanism, automatic assessment of the job event is realized, and the accuracy and real-time performance of risk assessment are improved; meanwhile, based on archiving and classification of high-risk event contents, more systematic data support can be provided for subsequent safety prevention and control, and the problem that a traditional construction data management method generally only depends on a single factor to perform classification and archiving, and consequently, when risk events of different types and different degrees are in the face, the construction data management efficiency is greatly improved is solved. And flexible classification is carried out according to specific event characteristics.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a method and system for managing data on risky operations at a construction site. Background Art

[0002] With the rapid development of the infrastructure industry, risk management at construction sites has become a key link in ensuring worker safety, improving project quality, and controlling costs. The management of risk operation data at construction sites is particularly important. As the scale and complexity of construction projects continue to increase, how to effectively collect, record, analyze, evaluate, and manage risk operation data at construction sites has become the key to improving the level of construction safety management.

[0003] Traditional construction data management methods usually rely on only a single factor for classification and archiving, which leads to the problem of inflexible classification based on specific event characteristics when facing risk events of different types and degrees. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a construction site risk operation data management method and system, which solves the problem that the traditional construction data management method usually only relies on a single factor for classification and archiving, resulting in the problem of not being able to flexibly classify according to specific event characteristics when facing risk events of different types and degrees.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a construction site risk operation data management method and system, comprising the following steps: obtaining historical normal operation data stored in a database, analyzing the historical normal operation data, and obtaining normal operation historical data parameter factors; obtaining current construction site risk data, and classifying the risk level of operation events corresponding to the current construction site risk data based on the current construction site risk data combined with the normal operation historical data parameter factors, wherein the current construction site risk data includes construction site environment data and construction site machinery and equipment data; if the risk level is judged to be low, the operation event corresponding to the current construction site risk data is recorded as a low-risk event; if the risk level is judged to be high, the operation event corresponding to the current construction site risk data is recorded as a high-risk event; based on the high-risk event, high-risk event content data is obtained, and the high-risk event content data is classified and archived.

[0006] Furthermore, the historical normal operation data includes historical construction site normal environment data and historical construction site normal mechanical equipment data; obtaining the normal operation historical data parameter factor includes the following steps: obtaining an environmental indicator weight data set and a mechanical equipment weight data set from a database; obtaining the normal operation historical data parameter coefficient corresponding to each historical normal operation data based on the environmental indicator weight data set, the mechanical equipment weight data set, the historical construction site normal environment data and the historical construction site normal mechanical equipment data; summing up each normal operation historical data parameter coefficient and then averaging it to obtain the normal operation historical data parameter factor.

[0007] Furthermore, the calculation formula of the parameter coefficient of the normal operation historical data is: ; In the formula, is the parameter coefficient of the normal operation historical data corresponding to the i-th historical normal operation data, is the ath environmental data indicator of the normal environmental data of the historical construction site in the ith historical normal operation data, a is the number of the environmental data indicator, a=1, 2, ..., A, A is the total number of environmental data indicators, for The weight factor of is the bth mechanical equipment data index of the normal mechanical equipment data of the historical construction site in the i-th historical normal operation data, b is the number of the mechanical equipment data index, b=1, 2, ..., B, B is the total number of mechanical equipment data indexes, for The weight factor of .

[0008] Furthermore, based on the current construction site risk data combined with the normal operation history data parameter factors, the risk level of the operation events corresponding to the current construction site risk data is classified. The specific analysis process is as follows: the environmental indicator weight data set and the mechanical equipment weight data set are obtained from the database; The environmental index weight data set is processed comprehensively with the construction site environmental data to obtain the environmental assessment value; The mechanical equipment weight data set is processed comprehensively with the mechanical equipment data of the construction site to obtain the mechanical equipment evaluation value; Combine the environmental assessment value with the mechanical equipment assessment value to obtain the risk assessment factor corresponding to the current construction site risk data; compare the risk assessment factor with the reference factor of normal operation historical data to determine whether the risk assessment factor is greater than the reference factor of normal operation historical data; if the risk assessment factor is greater than the reference factor of normal operation historical data, the risk level is judged to be high, and the operation event corresponding to the current construction site risk data is recorded as a high-risk event; if the risk assessment factor is not greater than the reference factor of normal operation historical data, the risk level is judged to be low, and the operation event corresponding to the current construction site risk data is recorded as a low-risk event.

[0009] Furthermore, high-risk event content information data is obtained based on high-risk events, and the high-risk event content information data is classified and archived, including the following steps: comparing the high-risk event content information data with the high-risk event content information matching data corresponding to each risk type stored in a database to obtain a high-risk event comparison value, the high-risk event content information data includes high-risk environmental indicator data and high-risk mechanical equipment indicator data, and the high-risk event content information matching data corresponding to each risk type includes high-risk environmental indicator matching values ​​and high-risk mechanical equipment indicator matching values; determining the high-risk event content information matching data corresponding to the minimum high-risk event comparison value, and obtaining the risk type corresponding to the high-risk event content information matching data from the database based on the high-risk event content information matching data.

[0010] Furthermore, obtaining a high-risk event comparison value includes the following steps: obtaining the allowable deviation for high-risk environmental indicator matching; comparing the allowable deviation for high-risk environmental indicator matching, the high-risk environmental indicator data with the high-risk environmental indicator matching data corresponding to each risk type, to obtain a high-risk environmental indicator matching value; obtaining the allowable deviation for high-risk mechanical equipment indicator matching; comparing the allowable deviation for high-risk mechanical equipment indicator matching, the high-risk mechanical equipment indicator data with the high-risk mechanical equipment indicator matching data corresponding to each risk type, to obtain a high-risk mechanical equipment indicator matching value; combining the high-risk environmental indicator matching value and the high-risk mechanical equipment indicator matching value to obtain a high-risk event comparison value.

[0011] Furthermore, the calculation formula of the high-risk event comparison value is: ; In the formula, is the high-risk event comparison value, C is the high-risk environment indicator matching value, is the weight factor of C, F is the matching value of high-risk mechanical equipment indicators, is the weight factor of F.

[0012] Furthermore, the allowable deviation of high-risk environmental indicator matching is obtained, and the specific analysis process is as follows: obtaining high-risk environmental event occurrence data, the high-risk environmental event occurrence data including the number of high-risk environmental event occurrences, the frequency of high-risk environmental event occurrences and the minimum time interval between two adjacent high-risk environmental events; obtaining a matching set of high-risk environmental event occurrence data stored in a database, the high-risk environmental event occurrence data matching set including a plurality of high-risk environmental event occurrence data matching values, the high-risk environmental event occurrence data matching values ​​including a high-risk environmental event occurrence number matching value, a high-risk environmental event occurrence frequency matching value and a minimum time interval matching value between two adjacent high-risk environmental events; comparing the high-risk environmental event occurrence data with each high-risk environmental event occurrence data matching value stored in the database one by one to determine each environmental event occurrence comparison value; determining the high-risk environmental event occurrence data matching value corresponding to the minimum environmental event occurrence comparison value, and obtaining the high-risk environmental indicator matching allowable deviation corresponding to the high-risk environmental event occurrence data matching value from the database based on the high-risk environmental event occurrence data matching value.

[0013] Furthermore, the allowable deviation of high-risk mechanical equipment indicator matching is obtained, and the specific analysis process is as follows: obtaining high-risk mechanical equipment event occurrence data, the high-risk mechanical equipment event occurrence data includes the number of high-risk mechanical equipment event occurrences, the high-risk mechanical equipment event occurrence frequency and the average number of mechanical equipment damages; obtaining a high-risk mechanical equipment event occurrence data matching set stored in a database, the high-risk mechanical equipment event occurrence data matching set includes multiple high-risk mechanical equipment event occurrence data matching values, the high-risk mechanical equipment event occurrence data matching values ​​include the high-risk mechanical equipment event occurrence number matching value, the high-risk mechanical equipment event occurrence frequency matching value, and the average number of mechanical equipment damages matching value; comparing the high-risk mechanical equipment event occurrence data with each high-risk mechanical equipment event occurrence data matching value stored in the database one by one to determine each mechanical equipment event occurrence comparison value; determining the high-risk mechanical equipment event occurrence data matching value corresponding to the minimum mechanical equipment event occurrence comparison value, and obtaining the high-risk mechanical equipment indicator matching allowable deviation corresponding to the high-risk mechanical equipment event occurrence data matching value from the database based on the high-risk mechanical equipment event occurrence data matching value.

[0014] A construction site risk operation data management method and system device, including: a historical normal operation data acquisition module, a current construction site risk data acquisition module, and a high-risk event content data classification and archiving module, wherein: the historical normal operation data acquisition module is used to acquire historical normal operation data stored in a database, analyze the historical normal operation data, and obtain normal operation historical data parameter factors; the current construction site risk data acquisition module is used to acquire current construction site risk data, and based on the current construction site risk data combined with normal operation historical data parameter factors, classify the risk level of the operation event corresponding to the current construction site risk data, the current construction site risk data includes construction site environment data and construction site machinery and equipment data; if the risk level is judged to be low, the operation event corresponding to the current construction site risk data is recorded as a low-risk event; if the risk level is judged to be high, the operation event corresponding to the current construction site risk data is recorded as a high-risk event; the high-risk event content data classification and archiving module is used to acquire high-risk event content data based on high-risk events, and classify and archive the high-risk event content data.

[0015] This construction site risk operation data management method and system achieves automated assessment of operation events through intelligent data analysis and risk level classification mechanism, thereby improving the accuracy and real-time performance of risk assessment. At the same time, based on the archiving and classification of high-risk event content, it can provide more systematic data support for subsequent safety prevention and control, solving the problem that traditional construction data management methods usually rely on only a single factor for classification and archiving, resulting in the inability to flexibly classify according to specific event characteristics when facing risk events of different types and degrees.

[0016] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The present invention is a flow chart of the construction site risk operation data management method.

[0018] Figure 2 This is a flow chart of the construction site risk operation data management system of the present invention. DETAILED DESCRIPTION

[0019] The embodiment of the present application realizes the automated assessment of operation events through intelligent data analysis and risk level classification mechanism through the construction site risk operation data management method and system, thereby improving the accuracy and real-time performance of risk assessment; at the same time, based on the archiving and classification of high-risk event content, it can provide more systematic data support for subsequent safety prevention and control.

[0020] See also Figure 1 The embodiment of the present invention provides a technical solution: a construction site risk operation data management method and system, comprising the following steps: obtaining historical normal operation data stored in a database, analyzing the historical normal operation data, and obtaining normal operation historical data parameter factors.

[0021] Specifically, the historical normal operation data includes historical construction site normal environment data and historical construction site normal mechanical equipment data; obtaining the normal operation historical data parameter factors includes the following steps: obtaining the environmental indicator weight data set and the mechanical equipment weight data set from the database; obtaining the normal operation historical data parameter coefficient corresponding to each historical normal operation data based on the environmental indicator weight data set, the mechanical equipment weight data set, the historical construction site normal environment data and the historical construction site normal mechanical equipment data; summing up the various normal operation historical data parameter coefficients and then calculating the average value to obtain the normal operation historical data parameter factor.

[0022] In this implementation plan, historical normal operation data includes historical construction site normal environment data. and historical construction site normal mechanical equipment data , i is the number of historical normal operation data, , is the first environmental data indicator of the normal environmental data of the historical construction site in the i-th historical normal operation data. is the second environmental data indicator of the normal environmental data of the historical construction site in the i-th historical normal operation data. It is the ath environmental data indicator of the historical construction site normal environment data in the i-th historical normal operation data.

[0023] , is the first mechanical equipment data indicator of the normal mechanical equipment data of the historical construction site in the i-th historical normal operation data. is the second mechanical equipment data indicator of the normal mechanical equipment data of the historical construction site in the i-th historical normal operation data. It is the bth mechanical equipment data indicator of the historical construction site normal mechanical equipment data in the i-th historical normal operation data.

[0024] Environmental data indicators include but are not limited to wind speed and air quality at the construction site. Mechanical equipment data indicators include but are not limited to equipment load rate and equipment vibration frequency.

[0025] By combining the historical normal environment data and the historical normal mechanical equipment data of the construction site with their corresponding weights, the parameter coefficients of each historical normal operation data are obtained, which reflects the situation of each normal operation data. As the basis for subsequent risk assessment, it is judged whether the operation events at the current construction site are in a normal state and whether there are potential risks.

[0026] The calculation formula for the parameter coefficient of normal operation historical data is: ; In the formula, is the parameter coefficient of the normal operation historical data corresponding to the i-th historical normal operation data, a is the number of the environmental data indicator, a=1, 2, ..., A, for The weight factor is: A is the total number of environmental data indicators in the historical normal environmental data of the construction site, b is the number of the mechanical equipment data indicator, b = 1, 2, ..., B, for , and B is the total number of mechanical equipment data indicators in the historical construction site normal environment data.

[0027] The denominator is the sum of all environmental and mechanical equipment weights, which is used to normalize the weighted sum so that the final parameter coefficient can be within a reasonable range. The weights in the formula reflect the degree of influence of different environmental and mechanical equipment indicators on historical operation data.

[0028] The current construction site risk data is obtained, and based on the current construction site risk data combined with the normal operation history data parameter factors, the operation events corresponding to the current construction site risk data are classified into risk level categories. The current construction site risk data includes construction site environment data and construction site machinery and equipment data. If the risk level is judged to be low, the operation event corresponding to the current construction site risk data is recorded as a low-risk event. If the risk level is judged to be high, the operation event corresponding to the current construction site risk data is recorded as a high-risk event. Based on the high-risk events, the high-risk event content data is obtained, and the high-risk event content data is classified and archived.

[0029] Obtaining environmental indicator weight data set and mechanical equipment weight data set from the database; The environmental indicator weight data set is processed comprehensively with the construction site environmental data to obtain the environmental assessment value; the mechanical equipment weight data set is processed comprehensively with the construction site mechanical equipment data to obtain the mechanical equipment assessment value; the environmental assessment value is combined with the mechanical equipment assessment value to obtain the risk assessment factor corresponding to the current construction site risk data.

[0030] The environmental assessment value is the cumulative result FA of multiplying each weight factor in the environmental index weight data set with each corresponding environmental data index in the construction site environmental data; The mechanical equipment evaluation value is the cumulative result FB of multiplying each weight factor in the mechanical equipment weight data set with each corresponding mechanical equipment data index in the construction site mechanical equipment data; The risk assessment factor is calculated by adding FA and FB and dividing it by the sum of the weight factors in the environmental indicator weight data set and the weight factors in the mechanical equipment weight data set.

[0031] The risk assessment factor is compared with the reference factor of normal operation historical data to determine whether the risk assessment factor is greater than the reference factor of normal operation historical data; if the risk assessment factor is greater than the reference factor of normal operation historical data, the risk level is judged to be high, and the operation event corresponding to the current construction site risk data data is recorded as a high-risk event; if the risk assessment factor is not greater than the reference factor of normal operation historical data, the risk level is judged to be low, and the operation event corresponding to the current construction site risk data data is recorded as a low-risk event.

[0032] In this implementation plan, the environmental indicator weight data set and the mechanical equipment weight data set are obtained. The environmental indicator weight data set and the mechanical equipment weight data set reflect the degree of influence of different environmental factors and mechanical equipment parameters on operation safety and risk assessment. The risk assessment factor of the current construction site is obtained by combining the construction site environmental data and mechanical equipment data with the corresponding weight data set. The current risk assessment factor is compared and analyzed with the parameter factors of historical normal operation data to determine whether the current construction site operation conditions exceed the normal range, thereby affecting the risk level of the operation.

[0033] Specifically, the high-risk event content information data is compared with the high-risk event content information matching data corresponding to each risk type stored in the database to obtain a high-risk event comparison value, the high-risk event content information data including high-risk environment indicator data and high-risk machinery and equipment indicator data, and the high-risk event content information matching data corresponding to each risk type includes high-risk environment indicator matching values ​​and high-risk machinery and equipment indicator matching values; the high-risk event content information matching data corresponding to the minimum high-risk event comparison value is determined, and the risk type corresponding to the high-risk event content information matching data is obtained from the database based on the high-risk event content information matching data.

[0034] In this implementation scheme, first, the current high-risk event content information data is compared with the high-risk event content information matching data of different risk types in the database to obtain a high-risk event comparison value. The comparison value represents the degree of closeness between the current high-risk event data and the matching data of different risk types. The smaller the difference between the environmental data and the status of mechanical equipment at the current construction site and the matching data, the smaller the comparison value, indicating that the current event is closer to the historical event type. Find the minimum value in the comparison value. Then find the closest high-risk event content information matching data based on the minimum comparison value, so as to classify the high-risk event content information data into the risk type corresponding to the closest high-risk event content information matching data. Each risk type reflects the potential danger of working under specific environmental conditions and mechanical conditions.

[0035] Specifically, the high-risk environment indicator matching allowable deviation is obtained; the high-risk environment indicator matching allowable deviation and the high-risk environment indicator data are compared with the high-risk environment indicator matching data corresponding to each risk type to obtain the high-risk environment indicator matching value.

[0036] Obtain the allowable deviation of high-risk mechanical equipment indicator matching; compare the allowable deviation of high-risk mechanical equipment indicator matching and the high-risk mechanical equipment indicator data with the high-risk mechanical equipment indicator matching data corresponding to each risk type to obtain the high-risk mechanical equipment indicator matching value.

[0037] The high-risk environment indicator matching value and the high-risk mechanical equipment indicator matching value are combined to obtain the high-risk event comparison value.

[0038] In this implementation scheme, the allowable deviation of high-risk environmental indicators is obtained. The allowable deviation is used for the dynamic and complexity of the construction site environment. Different environmental conditions will fluctuate in actual operation, but they are still within the safe and acceptable range. For each environmental indicator data, the environmental data of the current construction site is compared with the environmental data of each risk type stored in the database, and the high-risk environmental indicator matching value is calculated in combination with the allowable deviation range.

[0039] The allowable deviation of mechanical equipment index matching is used to ensure that the data of mechanical equipment within the normal fluctuation range will fluctuate, but still within the safe and acceptable range. After obtaining the allowable deviation of high-risk mechanical equipment index matching, it is compared with the current construction site mechanical equipment data and the high-risk mechanical equipment index matching data corresponding to each risk type to obtain the high-risk mechanical equipment index matching value. Then, the high-risk environmental index matching value and the high-risk mechanical equipment index matching value are combined to obtain the final high-risk event comparison value.

[0040] The calculation method of the high-risk environment indicator matching value is as follows: the similarity between the high-risk environment indicator data and the high-risk environment indicator matching data is calculated by the Euclidean distance formula, and then the similarity is calculated by the ratio of the high-risk environment indicator matching allowable deviation to obtain the high-risk environment indicator matching value; High-risk environmental indicator data reflects the current environmental conditions of the construction site and the risks to the construction site. High-risk environmental indicator matching data is the standard environmental data under each risk type, which is used as a baseline to compare the risk level of the current environmental conditions with the standard environment. The calculation of the high-risk environmental indicator matching value can determine which type of risk type the risk environmental indicator data is closest to.

[0041] The calculation method of the high-risk mechanical equipment indicator matching value is the same as that of the high-risk environmental indicator matching value, which can determine which type of risk type the high-risk mechanical equipment indicator data is closest to.

[0042] The calculation formula for the high-risk event comparison value is: ; In the formula, is the high-risk event comparison value, C is the high-risk environment indicator matching value, is the weight factor of C, F is the matching value of high-risk mechanical equipment indicators, is the weight factor of F.

[0043] This formula is used to measure the closeness between the current high-risk event data and the matching data of different risk types. C and F respectively reflect the matching degree between the current high-risk event data and the environmental and mechanical equipment data of each risk type. C and F are calculated by the difference with the corresponding risk type matching data. The smaller the difference, the higher the matching degree. Then, use the weight factor and Adjust the impact of environmental data and equipment data in the final comparison value. The comparison value D is obtained by weighted summation, which reflects the closeness of the current high-risk event to each risk type. Finally, by selecting the smallest comparison value D, it is possible to determine which risk type the current high-risk event belongs to, and achieve accurate risk classification and event archiving.

[0044] Specifically, obtaining the allowable deviation of high-risk environmental indicator matching, the specific analysis process is: obtaining high-risk environmental event occurrence data, the high-risk environmental event occurrence data including the number of high-risk environmental event occurrences, the frequency of high-risk environmental event occurrences and the minimum time interval between two adjacent high-risk environmental events; obtaining a high-risk environmental event occurrence data matching set stored in a database, the high-risk environmental event occurrence data matching set including a plurality of high-risk environmental event occurrence data matching values, the high-risk environmental event occurrence data matching values ​​including a high-risk environmental event occurrence number matching value, a high-risk environmental event occurrence frequency matching value and a minimum time interval matching value between two adjacent high-risk environmental events; comparing the high-risk environmental event occurrence data with each high-risk environmental event occurrence data matching value stored in the database one by one to determine each environmental event occurrence comparison value; determining the high-risk environmental event occurrence data matching value corresponding to the minimum environmental event occurrence comparison value, and obtaining the high-risk environmental indicator matching allowable deviation corresponding to the high-risk environmental event occurrence data matching value from the database based on the high-risk environmental event occurrence data matching value.

[0045] In this implementation plan, the number of high-risk environmental events is the total number of high-risk environmental events that occurred at the construction site. The frequency of high-risk environmental events is the frequency of high-risk environmental events occurring within a period of time, reflecting the density of environmental risk. The minimum time interval between two adjacent high-risk environmental events is the time interval between two high-risk environmental events, reflecting the frequency and suddenness of environmental risk events.

[0046] Compare the current high-risk environmental event occurrence data with the high-risk environmental event occurrence data matching values ​​in the database one by one. The purpose of the comparison process is to find the matching degree between the high-risk environmental event occurrence data at the current construction site and the records in the historical database, and to determine which historical event data is closest to the current data. The result of the comparison will produce multiple comparison values, calculate the difference in the matching value of each high-risk environmental event occurrence data, and find the smallest environmental event occurrence comparison value, indicating that the high-risk environmental event data at the current site is closest to the historical data. Each high-risk environmental event occurrence data matching value will correspond to a high-risk environmental indicator matching allowable deviation.

[0047] The calculation formula of the environmental event occurrence comparison value is: ; In the formula, is the comparison value of the environmental event. is the number of high-risk environmental events. is the number of occurrences of high-risk environmental events, The frequency of high-risk environmental events. Matching value for the frequency of occurrence of high-risk environmental events, is the minimum time interval between two consecutive high-risk environmental events. It is the minimum time interval matching value between two adjacent high-risk environmental events.

[0048] The formula quantifies the degree of difference by calculating the absolute deviation between the number of occurrences, frequency, and intervals of current high-risk environmental events and the matching data. Each deviation is normalized by dividing it by the corresponding matching value to eliminate the influence of different magnitudes. The function compresses the sum of the deviations, reducing the impact of larger deviations and making the overall calculation result more stable. The addition of 1 ensures that the formula is still valid when the deviation is zero.

[0049] Specifically, obtaining the allowable deviation of high-risk mechanical equipment index matching, the specific analysis process is: obtaining high-risk mechanical equipment event data, the high-risk mechanical equipment event data includes the number of high-risk mechanical equipment events, the frequency of high-risk mechanical equipment events and the average number of mechanical equipment damages; obtaining a high-risk mechanical equipment event data matching set stored in a database, the high-risk mechanical equipment event data matching set includes multiple high-risk mechanical equipment event data matching values, the high-risk mechanical equipment event data matching values ​​include the number of high-risk mechanical equipment events matching value, the high-risk mechanical equipment event frequency matching value, and the average number of mechanical equipment damages matching value; comparing the high-risk mechanical equipment event data with each high-risk mechanical equipment event data matching value stored in the database, and determining each mechanical equipment event occurrence comparison value; determining the high-risk mechanical equipment event data matching value corresponding to the minimum mechanical equipment event occurrence comparison value, and obtaining the high-risk mechanical equipment index matching allowable deviation corresponding to the high-risk mechanical equipment event data matching value from the database based on the high-risk mechanical equipment event data matching value. In this implementation scheme, the number of high-risk mechanical equipment events represents the total number of high-risk mechanical equipment events. The frequency of occurrence of high-risk mechanical equipment events refers to the frequency of the number of events that occur within the time of high-risk mechanical equipment events. The average number of mechanical equipment damages refers to the average number of equipment damages when a high-risk mechanical equipment event occurs. The high-risk mechanical equipment event occurrence data is compared with the matching values ​​of each high-risk mechanical equipment event occurrence data stored in the database one by one to obtain the mechanical equipment event occurrence comparison value, and compare the similarity between the current high-risk equipment event and the historical event to further judge the degree of risk. The minimum value means that among all comparisons, the current event has the greatest similarity with a historical event. Based on the minimum comparison value, find the historical event record that is most similar to the current event. According to the closest historical event data matching value, obtain the allowable deviation corresponding to the matching value.

[0050] The calculation formula for the mechanical equipment event occurrence comparison value is: ; In the formula, It is the comparison value of mechanical equipment event occurrence. is the number of high-risk mechanical equipment incidents. is the number of occurrences of high-risk mechanical equipment events. The frequency of high-risk mechanical equipment events, is the frequency matching value of high-risk mechanical equipment events, is the average number of damaged mechanical equipment, is the matching value of the average number of damaged mechanical equipment.

[0051] The formula calculates the relative difference between the current high-risk mechanical equipment events and historical data to obtain the mechanical equipment event occurrence comparison value. The number of event occurrences, frequency of occurrence, and amount of equipment damage in the formula measure the degree of difference between the current event and the matching value. The constant term ensures that the calculation result is valid and avoids the abnormal situation where the comparison value is zero.

[0052] See also Figure 2 A construction site risk operation data management system includes: a historical normal operation data acquisition module, a current construction site risk data acquisition module, and a high-risk event content data classification and archiving module, wherein: the historical normal operation data acquisition module is used to acquire the historical normal operation data stored in the database, analyze the historical normal operation data, and obtain the normal operation historical data parameter factors; the current construction site risk data acquisition module is used to acquire the current construction site risk data, and based on the current construction site risk data combined with the normal operation historical data parameter factors, classify the risk level of the operation event corresponding to the current construction site risk data, the current construction site risk data includes construction site environment data and construction site machinery and equipment data; if the risk level is judged to be low, the operation event corresponding to the current construction site risk data is recorded as a low-risk event; if the risk level is judged to be high, the operation event corresponding to the current construction site risk data is recorded as a high-risk event; the high-risk event content data classification and archiving module is used to acquire high-risk event content data based on high-risk events, and classify and archive the high-risk event content data.

[0053] In a specific embodiment, in the parameter determination coefficient of the normal operation history data, is 6, 7, 8, 5, 7, is 5, 6, 7, 6, 8, A is 5, B is 5, is 1, is 1, and the parameter coefficient of normal operation historical data is calculated to be 6.5.

[0054] Among the high-risk environment indicator matching values, is 75, is 70, is 5, and the high-risk environment indicator matching value is calculated to be 1.

[0055] Among the high-risk mechanical equipment index matching values, is 120, is 100, is 10, and the calculated matching value of the high-risk environment indicator is 2.

[0056] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented 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.

[0057] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0058] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0059] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0060] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0061] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A construction site risk operation data management method, characterized in that: The following steps are involved: Obtain the historical normal operation data stored in the database, analyze the historical normal operation data, and obtain the parameter factors of the normal operation historical data; Acquire current construction site risk data, and classify the risk level of the operation events corresponding to the current construction site risk data based on the current construction site risk data combined with the normal operation history data parameter factors, wherein the current construction site risk data includes construction site environment data and construction site machinery and equipment data; If the risk level is judged to be low, the operation event corresponding to the current construction site risk data is recorded as a low-risk event; If the risk level is judged to be high, the operation event corresponding to the current construction site risk data is recorded as a high-risk event; Obtain high-risk event content data based on high-risk events, and classify and archive the high-risk event content data.

2. A construction site risk operation data management method according to claim 1, characterized in that: The historical normal operation data includes historical construction site normal environment data and historical construction site normal mechanical equipment data; Obtaining the parameter factors of normal operation history data includes the following steps: Obtaining environmental indicator weight data set and mechanical equipment weight data set from the database; Based on the environmental index weight data set, the mechanical equipment weight data set, the historical construction site normal environmental data and the historical construction site normal mechanical equipment data, the normal operation historical data parameter coefficient corresponding to each historical normal operation data is obtained; The normal operation historical data parameter coefficients are summed up and the average value is obtained to obtain the normal operation historical data parameter factor.

3. A construction site risk operation data management method according to claim 2, characterized in that: The calculation formula of the parameter coefficient of the normal operation historical data is: ； In the formula, is the parameter coefficient of the normal operation historical data corresponding to the i-th historical normal operation data, is the ath environmental data indicator of the normal environmental data of the historical construction site in the ith historical normal operation data, a is the number of the environmental data indicator, a=1, 2, ..., A, A is the total number of environmental data indicators, for The weight factor of is the bth mechanical equipment data index of the normal mechanical equipment data of the historical construction site in the i-th historical normal operation data, b is the number of the mechanical equipment data index, b=1, 2, ..., B, B is the total number of mechanical equipment data indexes, for The weight factor of .

4. A construction site risk operation data management method according to claim 1, characterized in that: Based on the current construction site risk data combined with the normal operation history data parameter factors, the risk level of the operation events corresponding to the current construction site risk data is classified. The specific analysis process is as follows: Obtaining environmental indicator weight data set and mechanical equipment weight data set from the database; The environmental index weight data set is processed comprehensively with the construction site environmental data to obtain the environmental assessment value; The mechanical equipment weight data set is processed comprehensively with the mechanical equipment data of the construction site to obtain the mechanical equipment evaluation value; Combine the environmental assessment value with the mechanical equipment assessment value to obtain the risk assessment factor corresponding to the current construction site risk data; Compare the risk assessment factor with the parameter factor of normal operation historical data to determine whether the risk assessment factor is greater than the parameter factor of normal operation historical data; If the risk assessment factor is greater than the parameter factor of the normal operation historical data, the risk level is judged to be high, and the operation event corresponding to the current construction site risk data is recorded as a high-risk event; If the risk assessment factor is not greater than the parameter factor of the normal operation historical data, the risk level is judged to be low, and the operation event corresponding to the current construction site risk data is recorded as a low-risk event.

5. A construction site risk operation data management method according to claim 1, characterized in that: Acquiring high-risk event content data based on high-risk events and classifying and archiving the high-risk event content data includes the following steps: Compare the high-risk event content material data with the high-risk event content material matching data corresponding to each risk type stored in the database to obtain a high-risk event comparison value, wherein the high-risk event content material data includes high-risk environment indicator data and high-risk mechanical equipment indicator data, and the high-risk event content material matching data corresponding to each risk type includes a high-risk environment indicator matching value and a high-risk mechanical equipment indicator matching value; The high-risk event content material matching data corresponding to the minimum high-risk event comparison value is determined, and the risk type corresponding to the high-risk event content material matching data is obtained from a database based on the high-risk event content material matching data.

6. A construction site risk operation data management method according to claim 5, characterized in that: Obtaining a high-risk event comparison value includes the following steps: Obtain the allowable deviation for matching high-risk environmental indicators; The high-risk environmental indicator matching allowable deviation is compared with the high-risk environmental indicator data and the high-risk environmental indicator matching data corresponding to each risk type to obtain the high-risk environmental indicator matching value; Obtain the allowable deviation of high-risk mechanical equipment indicators; The high-risk mechanical equipment index matching allowable deviation and the high-risk mechanical equipment index data are compared with the high-risk mechanical equipment index matching data corresponding to each risk type to obtain the high-risk mechanical equipment index matching value; The high-risk environment indicator matching value and the high-risk mechanical equipment indicator matching value are combined to obtain the high-risk event comparison value.

7. A construction site risk operation data management method according to claim 6, characterized in that: The calculation formula of the high-risk event comparison value is: ； In the formula, is the high-risk event comparison value, C is the high-risk environment indicator matching value, is the weight factor of C, F is the matching value of high-risk mechanical equipment indicators, is the weight factor of F.

8. A construction site risk operation data management method according to claim 6, characterized in that: Obtain the allowable deviation of high-risk environmental indicators. The specific analysis process is as follows: Acquire high-risk environmental event occurrence data, wherein the high-risk environmental event occurrence data includes the number of high-risk environmental events, the frequency of high-risk environmental events, and the minimum time interval between two adjacent high-risk environmental events; Obtain a high-risk environmental event occurrence data matching set stored in a database, wherein the high-risk environmental event occurrence data matching set includes a plurality of high-risk environmental event occurrence data matching values, wherein the high-risk environmental event occurrence data matching values ​​include a high-risk environmental event occurrence number matching value, a high-risk environmental event occurrence frequency matching value, and a minimum time interval matching value between two adjacent high-risk environmental events; Compare the high-risk environmental event occurrence data with the matching values ​​of each high-risk environmental event occurrence data stored in the database one by one to determine the occurrence comparison value of each environmental event; Determine the high-risk environmental event occurrence data matching value corresponding to the minimum environmental event occurrence comparison value, and based on the high-risk environmental event occurrence data matching value, obtain the high-risk environmental indicator matching allowable deviation corresponding to the high-risk environmental event occurrence data matching value from the database.

9. A construction site risk operation data management method according to claim 8, characterized in that: Obtain the allowable deviation of the index matching of high-risk mechanical equipment. The specific analysis process is as follows: Acquire high-risk mechanical equipment event occurrence data, wherein the high-risk mechanical equipment event occurrence data includes the number of high-risk mechanical equipment events, the frequency of high-risk mechanical equipment events, and the average number of mechanical equipment damages; Acquire a high-risk mechanical equipment event occurrence data matching set stored in a database, wherein the high-risk mechanical equipment event occurrence data matching set includes a plurality of high-risk mechanical equipment event occurrence data matching values, wherein the high-risk mechanical equipment event occurrence data matching values ​​include a high-risk mechanical equipment event occurrence number matching value, a high-risk mechanical equipment event occurrence frequency matching value, and a mechanical equipment average damage quantity matching value; Compare the high-risk mechanical equipment event occurrence data with the matching values ​​of each high-risk mechanical equipment event occurrence data stored in the database one by one to determine the occurrence comparison value of each mechanical equipment event; Determine the high-risk mechanical equipment event occurrence data matching value corresponding to the minimum mechanical equipment event occurrence comparison value, and based on the high-risk mechanical equipment event occurrence data matching value, obtain the high-risk mechanical equipment indicator matching allowable deviation corresponding to the high-risk mechanical equipment event occurrence data matching value from the database.

10. A construction site risk operation data management system, applied to a construction site risk operation data management method according to any one of claims 1 to 9, characterized in that: include: Historical normal operation data acquisition module, current construction site risk data acquisition module, high-risk event content data classification and archiving module, including: The historical normal operation data acquisition module is used to acquire the historical normal operation data stored in the database, analyze the historical normal operation data, and obtain the normal operation historical data parameter factors; The current construction site risk data acquisition module is used to acquire the current construction site risk data, and based on the current construction site risk data combined with the normal operation history data parameter factors, the operation event corresponding to the current construction site risk data is classified into risk level, wherein the current construction site risk data includes construction site environment data and construction site machinery and equipment data; if the risk level is judged to be low, the operation event corresponding to the current construction site risk data is recorded as a low-risk event; if the risk level is judged to be high, the operation event corresponding to the current construction site risk data is recorded as a high-risk event; The high-risk event content information classification and archiving module is used to obtain high-risk event content information data based on high-risk events, and classify and archive the high-risk event content information data.

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