Smart engineering safety supervision method and system based on image monitoring

Abstract

The present invention relates to the technical field of engineering safety supervision, and specifically discloses an intelligent engineering safety supervision method and system based on image monitoring, which comprises the following steps: step S1: dividing a scaffold into several areas, and obtaining historical maintenance records, and recording the time period between each two adjacent maintenance dates as a maintenance interval; step S2: obtaining the usage frequency value of the area within the maintenance interval, setting a frequency threshold, and dividing the area within the maintenance interval into a low-frequency area and a high-frequency area according to the frequency threshold; step S3: for the low-frequency area, obtaining the historical temperature, establishing a date-temperature curve, and obtaining a temperature influence coefficient according to the historical maintenance records; step S4: for the high-frequency area, obtaining the usage frequency value and duration within the maintenance interval, and obtaining the usage frequency influence coefficient according to the date-temperature curve; step S5: obtaining the temperature and usage frequency value of each day after the construction time in real time, and obtaining a recommended maintenance day.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering safety supervision, and in particular to an intelligent engineering safety supervision method and system based on image monitoring. Background Art

[0002] Engineering safety supervision is a comprehensive management system involving multiple aspects, which aims to ensure the safe production of construction projects through laws, regulations and administrative measures, and to prevent and reduce safety accidents in engineering construction. Engineering safety supervision covers multiple aspects, mainly including construction safety, design safety, environmental safety and equipment safety.

[0003] Equipment safety is an important part of construction site engineering safety management, which is directly related to the life safety of construction workers and the quality of the project. Equipment safety at construction sites mainly includes matters related to scaffolding safety inspections, involving stability inspections, structural integrity inspections, load-bearing capacity assessments, regular inspections and maintenance, etc.

[0004] In the prior art, the regular inspection and maintenance of scaffolding at construction sites is mainly carried out according to the fixed inspection cycle recommended by relevant personnel during construction, or when a worker finds that the scaffolding is worn or has other hidden dangers, the scaffolding is inspected immediately; but since scaffolding is usually constructed of metal materials, and metal materials have the physical property of thermal expansion and contraction, in actual use, when encountering weather conditions with frequent temperature changes, metal fatigue will increase and the corrosion of the scaffolding will be accelerated; and for the same workbench, the frequency of use of different areas is different, resulting in different life consumption in different areas. Summary of the invention

[0005] The purpose of the present invention is to provide a smart engineering safety supervision method and system based on image monitoring to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] The smart engineering safety supervision method based on image monitoring includes the following steps:

[0008] Step S1: Divide the scaffold into several areas and obtain historical maintenance records, where the historical maintenance records are the maintenance dates of each area; the time period between each two adjacent maintenance dates is recorded as the maintenance interval;

[0009] Step S2: Obtaining the usage frequency value of the area within the maintenance interval Where pop is the total number of workers present in the region during the maintenance interval, t i is the working time of the i-th worker in the area; and a frequency threshold is set, and the area within the maintenance interval is divided into a low-frequency area and a high-frequency area according to the frequency threshold;

[0010] Step S3: For the low-frequency area, obtain the historical temperature and establish a date-temperature curve; according to the historical maintenance records, obtain the duration T of each maintenance interval on the date-temperature curve, and obtain the curve segment corresponding to the maintenance interval, select a number of sample points at equal intervals in the curve segment, obtain the derivative value D at each sample point, and then obtain the temperature influence coefficient Where ε is the primary correction coefficient and ε<0, D0 is the absolute value of the standard derivative, T0 is the standard maintenance interval, T i is the duration of the ith maintenance interval, |D| ave-i is the average value of the absolute value of the derivative of the i-th curve segment, and n is the total number of maintenance intervals in the low-frequency region;

[0011] Step S4: For high-frequency areas, obtain the usage frequency value and duration within the maintenance interval, and obtain the derivative value at each sample point of the curve segment according to the date-temperature curve to obtain the usage frequency influence coefficient Where ω is the quadratic correction coefficient and ω<0, Uf0 is the standard operating frequency value, Uf i is the usage frequency value of the ith maintenance interval, and m is the total number of maintenance intervals in the high-frequency area;

[0012] Step S5: Obtain the erection time of the scaffolding, and obtain the temperature and usage frequency values ​​of each day after the erection time in real time; establish the current date-temperature curve, and obtain the recommended maintenance date Date=Date in real time based on the current date-temperature curve and usage frequency value C +T0+μ*Uf k +λ*|D| ave-k , where Date C To build time, Uf k is the frequency value of scaffold usage between the construction time and the current time, |D| ave-k It is the average value of the absolute value of the derivative of each sample point on the current date-temperature curve.

[0013] As a further solution of the present invention: the process of dividing the scaffold includes dividing the scaffold into layers, recording scaffolds of different layers as one area, or recording each independent scaffold as one area.

[0014] As a further solution of the present invention: the process of obtaining the working hours of the workers in the area includes:

[0015] Obtain the worker's identity information and image information, match each worker's identity information with the image information one by one, and establish a worker information database;

[0016] When a worker enters the area, the area image is acquired in real time, the entry time is recorded, and when the worker leaves the area, the exit time is recorded; the worker's sub-working time period St is obtained from the entry time and the exit time; the worker's identity information is identified based on the area image and the worker information database, and the worker's identity information is associated with the sub-working time period, and then all the sub-working time periods of each worker are obtained within the maintenance interval, which are recorded as {St1, St2, ..., St num}, where St1 is the first sub-working time period in the maintenance interval, and num is the total number of sub-working time periods of the worker in the maintenance interval; then the worker's working time is obtained

[0017] As a further solution of the present invention: the process of setting the frequency threshold includes:

[0018] According to the historical maintenance records, the duration of each maintenance interval is obtained, and the areas with the same maintenance interval duration are selected, and the areas with consistent maintenance intervals are selected from these areas and recorded as sample areas; the consistent maintenance interval means that the dates corresponding to the maintenance intervals are consistent;

[0019] Get the usage frequency value in the sample area, recorded as {Uf1, Uf2, ..., Uf N}, where Uf1 is the usage frequency value of the first sample area, and N is the total number of sample areas; then the frequency threshold

[0020] As a further solution of the present invention: the process of dividing the area within the maintenance interval according to the frequency threshold includes:

[0021] The frequency threshold is recorded as F; if the usage frequency value Uf of the area within the maintenance interval is less than F, the area under the maintenance interval is recorded as a low-frequency area; if the usage frequency value Uf of the area within the maintenance interval is greater than or equal to F, the area under the maintenance interval is recorded as a high-frequency area.

[0022] As a further solution of the present invention: the selection of the sample points includes two end points of the curve segment.

[0023] As a further solution of the present invention: the absolute value of the standard derivative Wherein total is the total number of all maintenance intervals in the historical maintenance records, the standard maintenance interval duration is the average duration of all maintenance intervals in the historical maintenance records, and the standard usage frequency value is the average usage frequency value of all maintenance intervals in the historical maintenance records.

[0024] As a further solution of the present invention: a smart engineering safety supervision system based on image monitoring includes:

[0025] Historical data collection module: divide the scaffolding into several areas and obtain historical maintenance records, which are the maintenance dates of each area; record the time period between each two adjacent maintenance dates as the maintenance interval;

[0026] Area division module: Get the usage frequency value of the area within the maintenance interval Where pop is the total number of workers present in the region during the maintenance interval, t i is the working time of the i-th worker in the area; and a frequency threshold is set, and the area within the maintenance interval is divided into a low-frequency area and a high-frequency area according to the frequency threshold;

[0027] Low-frequency area analysis module: For low-frequency areas, obtain historical temperatures and establish a date-temperature curve; according to the historical maintenance records, obtain the duration T of each maintenance interval on the date-temperature curve, and obtain the curve segment corresponding to the maintenance interval, select a number of sample points at equal intervals in the curve segment, obtain the derivative value D at each sample point, and then obtain the temperature influence coefficient Where ε is the primary correction coefficient and ε<0, D0 is the absolute value of the standard derivative, T0 is the standard maintenance interval, T i is the duration of the ith maintenance interval, |D| ave-i is the average value of the absolute value of the derivative of the i-th curve segment, and n is the total number of maintenance intervals;

[0028] High-frequency area analysis module: For high-frequency areas, obtain the usage frequency value and duration within the maintenance interval, and obtain the derivative value at each sample point of the curve segment based on the date-temperature curve to obtain the usage frequency influence coefficient Where ω is the quadratic correction coefficient and ω<0, Uf0 is the standard operating frequency value, Uf i is the usage frequency value of the ith maintenance interval, and m is the total number of maintenance intervals in the high-frequency area;

[0029] Maintenance day recommendation module: obtain the scaffolding construction time, and obtain the temperature and usage frequency values ​​of each day after the construction time in real time; establish the current date-temperature curve, and obtain the recommended maintenance day Date=Date in real time based on the current date-temperature curve and usage frequency value C +T0+μ*Uf k +λ*|D| ave-k , where Date C To build time, Uf k is the frequency value of scaffold usage between the construction time and the current time, |D| ave-k It is the average value of the absolute value of the derivative of each sample point on the current date-temperature curve.

[0030] Beneficial effects of the present invention:

[0031] In the prior art, the regular inspection and maintenance of scaffolding at construction sites is mainly carried out according to the fixed inspection cycle recommended by relevant personnel during construction, or when a worker finds that the scaffolding is worn or has other hidden dangers, the scaffolding is inspected immediately; but since scaffolding is usually constructed of metal materials, and metal materials have the physical property of thermal expansion and contraction, in actual use, when encountering weather conditions with frequent temperature changes, metal fatigue will increase and the corrosion of the scaffolding will be accelerated; and for the same workbench, the frequency of use of different areas is different, resulting in different life consumption in different areas.

[0032] Compared with the prior art, the present invention automatically calculates the usage frequency and maintenance interval of each area of ​​the workbench through image monitoring and historical data, thereby reducing manual intervention; dynamically adjusts the maintenance cycle according to the usage frequency and temperature curve, making maintenance more scientific and reasonable, and avoiding excessive or insufficient maintenance; timely maintenance suggestions can improve the operating safety of the equipment and prevent safety accidents caused by untimely maintenance; by reasonably arranging maintenance time, unnecessary shutdowns and maintenance costs can be reduced, and the utilization rate of equipment can be improved; the present invention combines image monitoring technology and data analysis, which can effectively improve the level of intelligence in engineering safety supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The present invention will be further described below in conjunction with the accompanying drawings.

[0034] Figure 1 It is a structural schematic diagram of the intelligent engineering safety supervision method and system based on image monitoring of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] See also Figure 1 As shown, the present invention is a smart engineering safety supervision method based on image monitoring, comprising the following steps:

[0037] Step S1: Divide the scaffold into several areas and obtain historical maintenance records, where the historical maintenance records are the maintenance dates of each area; the time period between each two adjacent maintenance dates is recorded as the maintenance interval;

[0038] The process of dividing the scaffold includes dividing the scaffold into layers, recording scaffolds of different layers as one region, or recording each independent scaffold as one region;

[0039] It is understandable that by dividing the scaffolding into independent areas, it is helpful to systematically check the safety of each part. After dividing the areas, different maintenance cycles and plans are formulated for different areas; and according to the different usage frequencies of different areas, it is helpful to analyze the maintenance cycles of different areas in the future, and provide more data as a reference for the subsequent analysis;

[0040] Step S2: Obtaining the usage frequency value of the area within the maintenance interval Where pop is the total number of workers present in the region during the maintenance interval, t i is the working time of the i-th worker in the area; and a frequency threshold is set, and the area within the maintenance interval is divided into a low-frequency area and a high-frequency area according to the frequency threshold;

[0041] It can be understood that by calculating the total working hours of workers in a specific area, the total usage frequency of the area within the maintenance interval is obtained; according to the calculated usage frequency value Uf, it is compared with the preset frequency threshold, and the area is divided into a low-frequency area and a high-frequency area; if the area is a low-frequency area, the main factor affecting the area is the climate condition, that is, the temperature change; if the area is a high-frequency area, the main factors affecting the area are not only the climate condition but also the usage frequency;

[0042] The process of obtaining the working hours of workers in the area includes:

[0043] Obtain the worker's identity information and image information, match each worker's identity information with the image information one by one, and establish a worker information database;

[0044] When a worker enters the area, the area image is acquired in real time, the entry time is recorded, and when the worker leaves the area, the exit time is recorded; the worker's sub-working time period St is obtained from the entry time and the exit time; the worker's identity information is identified based on the area image and the worker information database, and the worker's identity information is associated with the sub-working time period, and then all the sub-working time periods of each worker are obtained within the maintenance interval, which are recorded as {St1, St2, ..., St num}, where St1 is the first sub-working time period in the maintenance interval, and num is the total number of sub-working time periods of the worker in the maintenance interval; then the worker's working time is obtained

[0045] It should be noted that the establishment process of the worker information database involves face recognition or biometric technology to ensure the accuracy of identity information and image information; when a worker enters the area, the monitoring device obtains the captured image, and the worker's identity information is obtained based on the captured image and the worker information database, and the time when the worker enters and leaves the area is recorded to obtain the sub-working time period, and the worker's identity information is associated with the sub-working time period; finally, all the sub-working time of the workers with the same identity information is added together to obtain the working time of the workers with different identity information;

[0046] The frequency threshold setting process includes:

[0047] According to the historical maintenance records, the duration of each maintenance interval is obtained, and the areas with the same maintenance interval duration are selected, and the areas with consistent maintenance intervals are selected from these areas and recorded as sample areas; the consistent maintenance interval means that the dates corresponding to the maintenance intervals are consistent;

[0048] Get the usage frequency value in the sample area, recorded as {Uf1, Uf2, ..., Uf N}, where Uf1 is the usage frequency value of the first sample area, and N is the total number of sample areas; then the frequency threshold

[0049] It is understandable that a reasonable frequency threshold is set through statistical methods for subsequent regional classification, i.e., the division of low-frequency areas and high-frequency areas; and the threshold is dynamically adjusted based on actual data, so as to more accurately reflect the usage and maintenance requirements of different areas;

[0050] It should be noted that the process of determining whether the maintenance intervals are the same in duration includes:

[0051] An error threshold range is set, and a difference between two maintenance intervals is obtained. If the absolute value of the difference falls within the error threshold range, the two maintenance intervals are recorded as being the same; if the absolute value of the difference does not fall within the error threshold range, the two maintenance intervals are recorded as being different.

[0052] Similarly, the process of determining whether the maintenance interval is consistent includes:

[0053] Obtain the maintenance dates at both ends of the maintenance interval, and record them as the start date and the end date respectively; for any two maintenance intervals, obtain the number of days between the start dates of the two maintenance intervals, day1, and obtain the number of days between the end dates of the two maintenance intervals, day2, and obtain the total number of days between the two maintenance intervals, day=day1+day2; if the total number of days between the two maintenance intervals is less than the preset number of days, the two maintenance intervals are recorded as consistent; if the total number of days between the two maintenance intervals is greater than or equal to the preset number of days, the two maintenance intervals are recorded as inconsistent;

[0054] The process of dividing the area within the maintenance interval according to the frequency threshold includes:

[0055] The frequency threshold is recorded as F; if the usage frequency value Uf of the area within the maintenance interval is less than F, the area under the maintenance interval is recorded as a low-frequency area; if the usage frequency value Uf of the area within the maintenance interval is greater than or equal to F, the area under the maintenance interval is recorded as a high-frequency area;

[0056] Step S3: For the low-frequency area, obtain the historical temperature and establish a date-temperature curve; according to the historical maintenance records, obtain the duration T of each maintenance interval on the date-temperature curve, and obtain the curve segment corresponding to the maintenance interval, select a number of sample points at equal intervals in the curve segment, obtain the derivative value D at each sample point, and then obtain the temperature influence coefficient Where ε is the primary correction coefficient and ε<0, D0 is the absolute value of the standard derivative, T0 is the standard maintenance interval, T i is the duration of the ith maintenance interval, |D| ave-i is the average value of the absolute value of the derivative of the i-th curve segment, and n is the total number of maintenance intervals in the low-frequency region;

[0057] The selection of the sample points includes two endpoints of the curve segment;

[0058] It should be noted that the process of establishing the date-temperature curve includes:

[0059] Obtain the temperature corresponding to each past date in the historical maintenance record, and establish a rectangular coordinate system with the date as the horizontal coordinate and the temperature as the vertical coordinate; convert the date and its corresponding temperature into coordinate points of corresponding positions on the rectangular coordinate system, and connect the coordinate points with a smooth curve to obtain a date-temperature curve;

[0060] It should be noted that in is the average value of the change in each maintenance interval compared to the standard maintenance interval in all low-frequency areas; is the average value of the change in the absolute value of the derivative of each curve segment compared to the absolute value of the standard derivative in all low-frequency regions; the average value of the absolute value of the derivative of the curve segment represents the change in temperature within the maintenance interval. If the average value of the absolute value of the derivative is larger, the temperature change within the maintenance interval is more frequent or the amount of change is larger; in the above formula, the temperature influence coefficient is used to quantify the impact of temperature change on the maintenance interval. If the temperature influence coefficient is larger, it means that the maintenance interval is more affected by temperature change.

[0061] Step S4: For high-frequency areas, obtain the usage frequency value and duration within the maintenance interval, and obtain the derivative value at each sample point of the curve segment according to the date-temperature curve to obtain the usage frequency influence coefficient Where ω is the quadratic correction coefficient and ω<0, Uf0 is the standard operating frequency value, Uf i is the usage frequency value of the ith maintenance interval, and m is the total number of maintenance intervals in the high-frequency area;

[0062] It should be noted that the frequency impact coefficient is used to measure the impact of changes in usage frequency on the maintenance interval; where:

[0063]

[0064] in is the average value of the change in each maintenance interval compared to the standard maintenance interval in all high-frequency areas; The average value of the change in the usage frequency value of each maintenance interval compared to the standard usage frequency value in all high-frequency areas; For all high-frequency areas, each maintenance interval is affected by temperature changes;

[0065] The standard derivative absolute value Wherein, total is the total number of all maintenance intervals in the historical maintenance records, the standard maintenance interval duration is the average duration of all maintenance intervals in the historical maintenance records, and the standard usage frequency value is the average usage frequency value of all maintenance intervals in the historical maintenance records;

[0066] It can be understood that the derivative here refers to the slope of the temperature curve at each point, reflecting the rate of temperature change; the standard maintenance interval duration refers to the average duration of the maintenance interval in all historical maintenance activities, which serves as a benchmark for evaluating the maintenance interval duration; the standard usage frequency value is the average value of the usage frequency values ​​of all maintenance intervals in the historical maintenance records, which represents the average usage frequency level of the region;

[0067] Step S5: Obtain the erection time of the scaffolding, and obtain the temperature and usage frequency values ​​of each day after the erection time in real time; establish the current date-temperature curve, and obtain the recommended maintenance date Date=Date in real time based on the current date-temperature curve and usage frequency value C +T0+μ*Uf k +λ*|D| ave-k , where Date C To build time, Uf k is the frequency value of scaffold usage between the construction time and the current time, |D| ave-k It is the average value of the absolute value of the derivative of each sample point on the current date-temperature curve.

[0068] The intelligent engineering safety supervision system based on image monitoring includes:

[0069] Historical data collection module: divide the scaffolding into several areas and obtain historical maintenance records, which are the maintenance dates of each area; record the time period between each two adjacent maintenance dates as the maintenance interval;

[0070] Area division module: Get the usage frequency value of the area within the maintenance interval Where pop is the total number of workers present in the region during the maintenance interval, t i is the working time of the i-th worker in the area; and a frequency threshold is set, and the area within the maintenance interval is divided into a low-frequency area and a high-frequency area according to the frequency threshold;

[0071] Low-frequency area analysis module: For low-frequency areas, obtain historical temperatures and establish a date-temperature curve; according to the historical maintenance records, obtain the duration T of each maintenance interval on the date-temperature curve, and obtain the curve segment corresponding to the maintenance interval, select a number of sample points at equal intervals in the curve segment, obtain the derivative value D at each sample point, and then obtain the temperature influence coefficient Where ε is the primary correction coefficient and ε<0, D0 is the absolute value of the standard derivative, T0 is the standard maintenance interval, T i is the duration of the ith maintenance interval, |D| ave-i is the average value of the absolute value of the derivative of the i-th curve segment, and n is the total number of maintenance intervals in the low-frequency region;

[0072] High-frequency area analysis module: For high-frequency areas, obtain the usage frequency value and duration within the maintenance interval, and obtain the derivative value at each sample point of the curve segment based on the date-temperature curve to obtain the usage frequency influence coefficient Where ω is the quadratic correction coefficient and ω<0, Uf0 is the standard operating frequency value, Uf i is the usage frequency value of the ith maintenance interval, and m is the total number of maintenance intervals in the high-frequency area;

[0073] Maintenance day recommendation module: obtain the scaffolding construction time, and obtain the temperature and usage frequency values ​​of each day after the construction time in real time; establish the current date-temperature curve, and obtain the recommended maintenance day Date=Date in real time based on the current date-temperature curve and usage frequency value C +T0+μ*Uf k +λ*|D| ave-k , where Date C To build time, Uf k is the frequency value of scaffold usage between the construction time and the current time, |D| ave-kIt is the average value of the absolute value of the derivative of each sample point on the current date-temperature curve.

[0074] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A smart engineering safety supervision method based on image monitoring, characterized in that: The following steps are involved: Step S1: Divide the scaffold into several areas and obtain historical maintenance records, where the historical maintenance records are the maintenance dates of each area; the time period between each two adjacent maintenance dates is recorded as the maintenance interval; Step S2: Obtaining the usage frequency value of the area within the maintenance interval Where pop is the total number of workers present in the region during the maintenance interval, t i is the working time of the i-th worker in the area; and setting a frequency threshold, and dividing the area within the maintenance interval into a low-frequency area and a high-frequency area according to the frequency threshold; Step S3: For the low-frequency area, obtain the historical temperature and establish a date-temperature curve; according to the historical maintenance records, obtain the duration T of each maintenance interval on the date-temperature curve, and obtain the curve segment corresponding to the maintenance interval, select a number of sample points at equal intervals in the curve segment, obtain the derivative value D at each sample point, and then obtain the temperature influence coefficient Where ε is the primary correction coefficient and ε<0, D0 is the absolute value of the standard derivative, T0 is the standard maintenance interval, T i is the duration of the ith maintenance interval, |D| ave-i is the average value of the absolute value of the derivative of the i-th curve segment, and n is the total number of maintenance intervals in the low-frequency region; Step S4: For high-frequency areas, obtain the usage frequency value and duration within the maintenance interval, and obtain the derivative value at each sample point of the curve segment according to the date-temperature curve to obtain the usage frequency influence coefficient Where ω is the quadratic correction coefficient and ω<0, Uf0 is the standard operating frequency value, Uf i is the usage frequency value of the ith maintenance interval, and m is the total number of maintenance intervals in the high-frequency area; Step S5: Obtain the erection time of the scaffolding, and obtain the temperature and usage frequency values ​​of each day after the erection time in real time; establish the current date-temperature curve, and obtain the recommended maintenance date Date=Date in real time based on the current date-temperature curve and usage frequency value C +T0+μ*Uf k +λ*|D| ave-k , where Date C To build time, Uf k is the frequency value of scaffold usage between the construction time and the current time, |D| ave-k It is the average value of the absolute value of the derivative of each sample point on the current date-temperature curve.

2. The method for intelligent engineering safety supervision based on image monitoring according to claim 1 is characterized in that: In step S1, the division process of the scaffold includes dividing the scaffold into layers, recording scaffolds of different layers as one region, or recording each independent scaffold as one region.

3. The method for intelligent engineering safety supervision based on image monitoring according to claim 1 is characterized in that: In step S2, the process of obtaining the working hours of the workers in the area includes: Obtain the worker's identity information and image information, match each worker's identity information with the image information one by one, and establish a worker information database; When a worker enters the area, the area image is acquired in real time, the entry time is recorded, and when the worker leaves the area, the exit time is recorded; the worker's sub-working time period St is obtained from the entry time and the exit time; the worker's identity information is identified based on the area image and the worker information database, and the worker's identity information is associated with the sub-working time period, and then all the sub-working time periods of each worker are obtained within the maintenance interval, which are recorded as {St1, St2, ..., St num }, where St1 is the first sub-working time period in the maintenance interval, and num is the total number of sub-working time periods of the worker in the maintenance interval; then the worker's working time is obtained 4. The method for intelligent engineering safety supervision based on image monitoring according to claim 1 is characterized in that: In step S2, the frequency threshold setting process includes: According to the historical maintenance records, the duration of each maintenance interval is obtained, and the areas with the same maintenance interval duration are selected, and the areas with consistent maintenance intervals are selected from these areas and recorded as sample areas; the consistent maintenance interval means that the dates corresponding to the maintenance intervals are consistent; Get the usage frequency value in the sample area, recorded as {Uf1, Uf2, ..., Uf N }, where Uf1 is the usage frequency value of the first sample area, and N is the total number of sample areas; then the frequency threshold 5. The method for intelligent engineering safety supervision based on image monitoring according to claim 1 is characterized in that: In step S2, the process of dividing the area within the maintenance interval according to the frequency threshold includes: The frequency threshold is recorded as F; if the usage frequency value Uf of the area within the maintenance interval is less than F, the area under the maintenance interval is recorded as a low-frequency area; if the usage frequency value Uf of the area within the maintenance interval is greater than or equal to F, the area under the maintenance interval is recorded as a high-frequency area.

6. The method for intelligent engineering safety supervision based on image monitoring according to claim 1 is characterized in that: In step S3, the sample points are selected including two end points of the curve segment.

7. The method for intelligent engineering safety supervision based on image monitoring according to claim 1 is characterized in that: In step S4, the standard derivative absolute value Wherein total is the total number of all maintenance intervals in the historical maintenance records, the standard maintenance interval duration is the average duration of all maintenance intervals in the historical maintenance records, and the standard usage frequency value is the average usage frequency value of all maintenance intervals in the historical maintenance records.

8. The intelligent engineering safety supervision system based on image monitoring is characterized by: include: Historical data collection module: divide the scaffolding into several areas and obtain historical maintenance records, which are the maintenance dates of each area; record the time period between each two adjacent maintenance dates as the maintenance interval; Area division module: Get the usage frequency value of the area within the maintenance interval Where pop is the total number of workers present in the region during the maintenance interval, t i is the working time of the i-th worker in the area; and setting a frequency threshold, and dividing the area within the maintenance interval into a low-frequency area and a high-frequency area according to the frequency threshold; Low-frequency area analysis module: For low-frequency areas, obtain historical temperatures and establish a date-temperature curve; according to the historical maintenance records, obtain the duration T of each maintenance interval on the date-temperature curve, and obtain the curve segment corresponding to the maintenance interval, select a number of sample points at equal intervals in the curve segment, obtain the derivative value D at each sample point, and then obtain the temperature influence coefficient Where ε is the primary correction coefficient and ε<0, D0 is the absolute value of the standard derivative, T0 is the standard maintenance interval, T i is the duration of the ith maintenance interval, |D| ave-i is the average value of the absolute value of the derivative of the i-th curve segment, and n is the total number of maintenance intervals in the low-frequency region; High-frequency area analysis module: For high-frequency areas, obtain the usage frequency value and duration within the maintenance interval, and obtain the derivative value at each sample point of the curve segment based on the date-temperature curve to obtain the usage frequency influence coefficient Where ω is the quadratic correction coefficient and ω<0, Uf0 is the standard operating frequency value, Uf i is the usage frequency value of the ith maintenance interval, and m is the total number of maintenance intervals in the high-frequency area; Maintenance day recommendation module: obtain the scaffolding construction time, and obtain the temperature and usage frequency values ​​of each day after the construction time in real time; establish the current date-temperature curve, and obtain the recommended maintenance day Date=Date in real time based on the current date-temperature curve and usage frequency value C +T0+μ*Uf k +λ*|D| ave-k , where Date C To build time, Uf k is the frequency value of scaffold usage between the construction time and the current time, |D| ave-k It is the average value of the absolute value of the derivative of each sample point on the current date-temperature curve.

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