Hydraulic engineering construction potential safety hazard monitoring system based on Internet of Things

Abstract

The invention discloses a hydraulic engineering construction potential safety hazard monitoring system based on the Internet of Things, relates to the technical field of hydraulic engineering construction, and solves the problem that a systematic potential safety hazard monitoring mode is not adopted for comprehensive monitoring. The method comprises the following steps of: acquiring an external stress change curve, locking an abnormal section with regular change in time in the change curve on the basis of a corresponding analysis process, and optimizing and calibrating the abnormal section on the basis of a standard value confirmed in the curve, so that the influence of external waves on the stress hidden danger monitoring process is avoided, and a relatively accurate external stress change curve is obtained; and then the potential safety hazard is determined based on the difference value change condition of the external stress and the internal stress confirmed at the same time, so that the accuracy of the numerical value can be effectively guaranteed in the potential safety hazard determination mode, and a relatively comprehensive potential safety hazard monitoring effect can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project construction, and in particular to a water conservancy project construction safety hazard monitoring system based on the Internet of Things. Background Art

[0002] Before the construction of water conservancy projects, the design drawings and construction plans of water conservancy projects need to be reviewed in detail. This includes checking whether the scale and layout of the project meet the requirements of water conservancy planning. Cofferdams are temporary water retaining structures. During the construction of water conservancy projects (such as dams, sluices, pumping stations, etc.), in order to create dry land construction conditions, it is necessary to separate the construction area from the water body, and cofferdams play this role.

[0003] During the construction of water conservancy projects, for the specific construction process of the cofferdam, generally when pouring concrete, the cofferdam is evaluated based on the corresponding human observation to determine whether it is safe and meets the standards. However, in actual application, the deformation and changes in many areas are invisible to the human eye. Therefore, when monitoring the actual safety compliance issues, there are too many human factors interfering, and a better safety hazard monitoring effect cannot be achieved. In addition, a systematic safety hazard monitoring method has not been adopted for comprehensive monitoring, and its construction safety hazards need to be strengthened. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a water conservancy project construction safety hazard monitoring system based on the Internet of Things, which solves the problem of not adopting a systematic safety hazard monitoring method for comprehensive monitoring.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A water conservancy project construction safety hazard monitoring system based on the Internet of Things, comprising:

[0006] The stress monitoring terminal monitors the stress data on both sides of the cofferdam casting bin in real time and transmits the real-time monitored stress data to the stress data processing terminal, where the stress data is monitored by a specific strain gauge;

[0007] The stress data processing terminal performs numerical processing on the stress data of the cofferdam casting bin during the casting process, and confirms the three-dimensional model of the cofferdam casting bin from the constructed cofferdam model, confirms the specific direction of its related stress, and then determines the comprehensive external stress and comprehensive internal stress during the casting process based on the different directions of different stresses on the surface of the cofferdam casting bin. The specific method is as follows:

[0008] Confirm the cofferdam casting bin during the casting process, and select the model body of the cofferdam casting bin from the pre-built 3D model. Based on the stress data monitored by the strain gauge, confirm the specific position of the strain gauge in the model body, and identify whether the strain gauge is an external strain gauge or an internal strain gauge.

[0009] If this strain gauge is an external strain gauge, the currently monitored stress data is calibrated as Yw k , where k represents different external strain gauges, and based on the specific position of the strain gauge in the model body, a related vertical line A perpendicular to the specific position is constructed, and then the center point of the outer surface of the model body is confirmed, and a related vertical line B perpendicular to the center point is constructed. The related vertical line A and the related vertical line B are moved to combine the vertical points of A and B, and the angle Jab between A and B is determined, using: W k ab=Yw k ÷cosJab confirms this stress data Yw k The associated external stress W k ab, and process other external strain gauges on the outer surface of the cofferdam casting bin in the same way, confirm the relevant external stresses associated with their stress data in turn, and then sum up several relevant external stresses to confirm the comprehensive external stress associated at the current moment;

[0010] If this strain gauge is an internal strain gauge, the currently monitored stress data is calibrated as Yn i , where i represents different internal strain gauges, and based on the specific position of the strain gauge in the model body, a related vertical line C perpendicular to the specific position is constructed, and then the center point of the inner surface of the model body is confirmed, and a related vertical line D perpendicular to the center point is constructed, and the related vertical line C is moved with the related vertical line D to combine the vertical points of C and D, and the angle Jcd between C and D is determined, and the comprehensive internal stress associated with the cofferdam casting bin at the current moment is confirmed in the same way as the comprehensive external stress;

[0011] Based on the stress data monitored in real time during the pouring process, the comprehensive external stress and comprehensive internal stress of the cofferdam pouring bin are confirmed in real time, and the real-time confirmed comprehensive external stress and comprehensive internal stress are transmitted to the stress curve confirmation terminal;

[0012] The stress curve confirmation terminal generates a comprehensive external stress change curve and a comprehensive internal stress change curve based on the comprehensive external stress and comprehensive internal stress confirmed in real time and based on different stresses associated at different times;

[0013] The external stress curve optimization terminal confirms the abnormal change segment inside the curve based on the generated comprehensive external stress change curve, and preferentially identifies whether the corresponding abnormal change segment belongs to the curve segment to be optimized based on the numerical change trend and change cycle of the abnormal change segment, and then optimizes the confirmed curve segment to be optimized to obtain the comprehensive external stress standard curve. The specific method is as follows:

[0014] A stress climbing segment is confirmed from the comprehensive external stress change curve, and the comprehensive external stress inside the stress climbing segment gradually increases with the gradual change of time, and the external stress change value Bz between adjacent moments is identified from the confirmed stress climbing segment, where Bz=comprehensive external stress at the later moment-comprehensive external stress at the previous moment, and the cluster set is locked from the confirmed several external stress change values ​​Bz, and the several change values ​​Bz are sorted in the manner of small to large values, and the sorting sequence is confirmed, and then data is confirmed in the sorting sequence based on the preset value range, and the process stops when the number of confirmed data reaches the maximum, and the corresponding cluster set is confirmed. If there are multiple cluster sets, the cluster set is randomly selected for mean processing, and the several related Bz in the cluster set are processed for mean value to determine the standard value;

[0015] The determined standard value is calibrated as BB, and a set of variation ranges is determined based on the standard value BB: [BB-Y1, BB+Y1], where Y1 is a preset value, and Y1 is half of the preset value range. Then, the variation value Zz between adjacent moments is identified from the comprehensive external stress variation curve. o , where o represents different adjacent moments, Zz o The corresponding moments that do not belong to [BB-Y1, BB+Y1] are marked as abnormal moments, and the curve segments associated with the consecutive abnormal moments are marked as abnormal change segments;

[0016] Based on the several abnormal change segments confirmed in the comprehensive external stress change curve, the specific duration S of the corresponding abnormal change segment is determined. q , where q represents different abnormal change segments, S q The abnormal change segments with a value of ≤Y2 are marked as the segments to be processed, where Y2 is the preset value, and then the interval time period between adjacent segments to be processed is identified, S q >No calibration is performed on the abnormal change section of Y2:

[0017] If the time difference between the interval time periods confirmed successively before and after meets the requirement of being less than 2 seconds, the interval time periods confirmed successively will be marked as the same type of periods, and the confirmed to-be-processed segments will be marked as the curve segments to be optimized;

[0018] If the time difference between the confirmations is more than 2 seconds, no calibration will be performed;

[0019] The change value between adjacent moments in the curve segment to be optimized is adjusted to BB, and the curve segment is controlled to change in association, and the comprehensive external stress change curve after optimization is calibrated as a comprehensive external stress standard curve;

[0020] The safety hazard assessment center, based on the determined comprehensive external stress standard curve and the comprehensive internal stress change curve, identifies the stress difference generated at the same time from the two sets of curves, and based on the specific confirmation results, identifies whether there are safety hazards in the cofferdam casting bin. The specific method is as follows:

[0021] The comprehensive external stress associated with different moments in the comprehensive external stress standard curve is calibrated as ZY t , where t represents different moments, the corresponding comprehensive internal stress at the corresponding moment is identified from the comprehensive internal stress change curve and calibrated as ZN t ;

[0022] Using Cz t =|ZY t -ZN t |Determine its stress difference Cz t ;

[0023] Identify the presence of Cz t > The relevant moment of Y3, where Y3 is a preset value. If it exists, the total duration of the relevant moment is recorded. If the total duration exceeds 5 seconds, a safety hazard signal is generated for display. Otherwise, no display is performed;

[0024] If there is no relevant time, no processing is performed.

[0025] The present invention provides a water conservancy project construction safety hazard monitoring system based on the Internet of Things. Compared with the prior art, it has the following beneficial effects:

[0026] The present invention can achieve better stress monitoring effect by monitoring the stress of the cofferdam casting bin corresponding to the water conservancy project and confirming the corresponding comprehensive stress based on the corresponding three-dimensional model, and facilitate the identification of hidden dangers, and the accuracy and precision of the identification can be effectively guaranteed;

[0027] Based on the corresponding external stress monitored, the stress change curve generated is analyzed, and based on the corresponding analysis process, the abnormal segments with regular time changes in the change curve are locked, and based on the standard values ​​confirmed in the curve, such abnormal segments are optimized and calibrated to avoid the impact of external waves on the stress hidden danger monitoring process, and a more accurate external stress change curve is obtained. Based on the difference changes in the external stress and internal stress confirmed at the same time, the safety hazard is determined. This method of determining safety hazards can effectively guarantee the accuracy of the numerical value and achieve a more comprehensive safety hazard monitoring effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0029] Figure 2It is a top view schematic diagram of the cofferdam casting bin of the present invention. DETAILED DESCRIPTION

[0030] 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.

[0031] See also Figure 1 , the present application provides a water conservancy project construction safety hazard monitoring system based on the Internet of Things, including a stress monitoring terminal, a stress data processing terminal, a stress curve confirmation terminal, an external stress curve optimization terminal and a safety hazard assessment center;

[0032] The stress monitoring terminal is electrically connected to the input node of the stress data processing terminal, the stress data processing terminal is electrically connected to the input node of the stress curve confirmation terminal, and the stress curve confirmation terminal is electrically connected to the external stress curve optimization terminal or the input node of the safety hazard assessment center, and the external stress curve optimization terminal is electrically connected to the input node of the safety hazard assessment center;

[0033] Among them, the stress monitoring terminal monitors the stress data on both sides of the cofferdam casting bin in real time, and transmits the real-time monitored stress data to the stress data processing terminal, wherein the stress data is monitored by a specific strain gauge, and the sensor is arranged in advance by the relevant operator at the connection point inside the corresponding casting bin. Generally, a strain gauge is used. When the inner wall of the cofferdam is deformed, the resistance value of the strain gauge will change, thereby completing the specific monitoring of the stress related to the corresponding contact point;

[0034] Among them, the stress data processing terminal performs numerical processing on the stress data of the cofferdam casting bin during the casting process, and confirms the three-dimensional model of the cofferdam casting bin from the constructed cofferdam model, confirms the specific direction of its relevant stress, and then determines the comprehensive external stress and comprehensive internal stress during the casting process based on the different directions of different stresses on the surface of the corresponding cofferdam casting bin. Specifically, in the actual casting process, as concrete is gradually poured into the cofferdam, relevant stress will be generated inside the cofferdam to the inner and outer walls of the cofferdam bin. Under normal circumstances, the values ​​of the external and internal stresses generated should be within a specific range of values, but due to internal connection points or other unexpected situations, there will be a large difference between the internal and external stresses. In this case, there are corresponding safety hazards, and relevant processing is required to timely understand and deal with the safety hazards;

[0035] The specific method for determining the comprehensive external stress and comprehensive internal stress during the pouring process is:

[0036] Confirm the cofferdam casting bin during the casting process, and select the model body of the cofferdam casting bin from the pre-built 3D model. Based on the stress data monitored by the strain gauge, confirm the specific position of the strain gauge in the model body, and identify whether the strain gauge is an external strain gauge or an internal strain gauge.

[0037] If this strain gauge is an external strain gauge, the currently monitored stress data is calibrated as Yw k , where k represents different external strain gauges, and based on the specific position of the strain gauge in the model body, a related vertical line A perpendicular to the specific position is constructed, and then the center point of the outer surface of the model body is confirmed, and a related vertical line B perpendicular to the center point is constructed. The related vertical line A and the related vertical line B are moved to combine the vertical points of A and B, and the angle Jab between A and B is determined, using: W k ab=Yw k ÷cosJab (here the trigonometric function is used to confirm the comprehensive external stress of several stress data in the same direction) confirm this stress data Yw k The associated external stress W k ab, and process other external strain gauges on the outer surface of the cofferdam casting bin in the same way, confirm the relevant external stresses associated with their stress data in turn, and then sum up several relevant external stresses to confirm the comprehensive external stress associated at the current moment;

[0038] If this strain gauge is an internal strain gauge, the currently monitored stress data is calibrated as Yn i , where i represents different internal strain gauges, and based on the specific position of the strain gauge in the model body, a related vertical line C perpendicular to the specific position is constructed, and then the center point of the inner surface of the model body is confirmed, and a related vertical line D perpendicular to the center point is constructed, and the related vertical line C is moved with the related vertical line D to combine the vertical points of C and D, and the angle Jcd between C and D is determined, and the comprehensive internal stress associated with the cofferdam casting bin at the current moment is confirmed in the same way as the comprehensive external stress;

[0039] Based on the stress data monitored in real time during the pouring process, the comprehensive external stress and comprehensive internal stress of the cofferdam pouring bin are confirmed in real time, and the real-time confirmed comprehensive external stress and comprehensive internal stress are transmitted to the stress curve confirmation terminal;

[0040] Combination Figure 2 , Figure 2It is only a related top-view schematic diagram of the corresponding cofferdam casting bin. The cofferdam is spliced ​​by several cofferdam casting bins. The corresponding strain gauges are set on the inner and outer surfaces of the cofferdam casting bin. The stresses at the corresponding points on the inner and outer surfaces are monitored to confirm the corresponding external stress and internal stress. Based on the relevant center points of the corresponding inner and outer surfaces, the corresponding vertical lines are specifically confirmed. Based on the specific directions of the corresponding external stress and internal stress and the specific angles with the corresponding vertical lines, the comprehensive force of multiple stresses converging at one place can be confirmed, that is, the corresponding comprehensive external stress and comprehensive internal stress.

[0041] Among them, the stress curve confirmation terminal generates a comprehensive external stress change curve and a comprehensive internal stress change curve based on the comprehensive external stress and comprehensive internal stress confirmed in real time and based on different stresses associated at different times, and transmits the comprehensive external stress change curve to the external stress curve optimization terminal for curve optimization. The horizontal coordinate axis of the corresponding change curve is the timeline, and the vertical coordinate axis is the stress data;

[0042] Its external stress curve optimization terminal confirms the abnormal change segment inside the curve based on the generated comprehensive external stress change curve, and preferentially identifies whether the corresponding abnormal change segment belongs to the curve segment to be optimized based on the numerical change trend and change cycle of the abnormal change segment, and then optimizes the confirmed curve segment to be optimized. Specifically, the outside of the cofferdam is in contact with the corresponding water source. During pouring, its outer surface will be impacted by the external water source, which will generate a set of internal stresses, so the internal and external stresses will offset each other, but there is a time law when the water waves impact, and the corresponding cycles generated by the front and rear waves will not differ greatly. Therefore, there is a corresponding abnormal change segment with a time cycle in the corresponding comprehensive external stress change curve. Such abnormal change segments can be directly corrected, so relevant optimization is required to ensure that the corresponding comprehensive external stress change curve can be fully optimized to ensure the specific accuracy of subsequent numerical confirmation and achieve the overall effect of safety hazard assessment;

[0043] Among them, the specific method of optimizing the comprehensive external stress change curve is:

[0044] The stress climbing section is confirmed from the comprehensive external stress change curve, and the comprehensive external stress inside the stress climbing section gradually increases with the gradual change of time (the gradual change of time means that time gradually changes backward. Due to the gradual change of time, the pouring volume will gradually increase. The more the pouring volume, the greater the comprehensive external stress generated, so the comprehensive external stress will gradually increase), and the external stress change value Bz between adjacent moments is identified from the confirmed stress climbing section, where Bz = comprehensive external stress at the later moment - comprehensive external stress at the previous moment, and the cluster set is locked from the confirmed several external stress change values ​​Bz, and the several change values ​​Bz are sorted in the order of small to large values ​​to confirm the sorting sequence, and then the data is confirmed in the sorting sequence based on the preset value range, and it stops when the number of confirmed data reaches the maximum (that is, the number of data belonging to this value range reaches the maximum), and the corresponding cluster set is confirmed. If there are multiple cluster sets, the cluster set is randomly selected Perform mean processing, perform mean processing on several related Bz in the cluster set to determine the standard value, and propose to confirm the sorting sequence as {0.1, 1, 1.1, 1.2, 1.3.1.4, 1.31, 4, 5, 6}, and propose to determine the numerical range as 3. Then, starting from the first group of numerical ranges 0-3, confirm that there are corresponding data columns {0.1, 1, 1.1, 1.2, 1.3.1.4, 1.31}, and then change 0-3 to 1-4, then there are corresponding data columns {1, 1.1, 1.2, 1.3.1.4, 1.31, 4}, and so on. The subsequent corresponding data columns can be confirmed in turn, so that the corresponding cluster set can be confirmed. Although there are other abnormal external stresses in several Bz, under normal construction and pouring conditions, the external stress should increase normally, so there are relatively clustered Bz values, so that the corresponding cluster set can be confirmed, so as to carry out specific confirmation of the numerical value;

[0045] The determined standard value is calibrated as BB, and a set of variation ranges is determined based on the standard value BB: [BB-Y1, BB+Y1], where Y1 is a preset value, and Y1 is half of the preset value range. Then, the variation value Zz between adjacent moments is identified from the comprehensive external stress variation curve. o , where o represents different adjacent moments, Zz o The corresponding moments that do not belong to [BB-Y1, BB+Y1] are marked as abnormal moments, and the curve segments associated with the consecutive abnormal moments are marked as abnormal change segments;

[0046] Based on the several abnormal change segments confirmed in the comprehensive external stress change curve, the specific duration S of the corresponding abnormal change segment is determined. q , where q represents different abnormal change segments, S q≤Y2 is calibrated as the processing segment, otherwise, no calibration is performed, where Y2 is a preset value, and its specific value is determined by the operator based on experience. When the wave impacts, it usually ends within two seconds, so Y2 is generally taken as 2, and then the interval time period between adjacent processing segments is identified. If the interval time period confirmed in sequence satisfies the time difference of less than 2 seconds (here it can be understood that there are three processing segments A, B and C, where the time interval between AB is 4 seconds, and the time interval between BC is 3.9 seconds, and the difference between 4 seconds and 3.9 seconds is 0.1 seconds, which is less than 2 seconds, then the AB segment and the BC segment belong to the corresponding curve segment to be optimized, and the interval time period here is less than 2 seconds. Including 2 seconds), if the interval time periods confirmed successively before and after meet the time difference of more than 2 seconds, no calibration is performed, then the interval time periods confirmed successively are calibrated as the same type of periods, and the confirmed to-be-processed segments are calibrated as the curve segments to be optimized. Specifically, there are corresponding interval times between adjacent to-be-processed segments, and there will be time differences between the interval times. When the time difference is close, it means that the corresponding to-be-processed segments appear regularly, so the corresponding to-be-processed segments can be calibrated. Under normal pouring conditions, there is no corresponding regular situation for abnormal stress changes. It is only because of the corresponding wave impact that such a situation exists. Therefore, this method can be used to determine the curve segments to be optimized;

[0047] The change value between adjacent moments in the curve segment to be optimized is adjusted to BB, and the curve segment is controlled to change in association, and the comprehensive external stress change curve after optimization is calibrated as the comprehensive external stress standard curve. Specifically, the corresponding curve segment to be optimized is proposed to be ABC, then the points B and C will change again, because the change value between them is adjusted from the original parameter to BB, then point B will definitely be adjusted upward, and similarly, the corresponding point C will also change accordingly.

[0048] Among them, the safety hazard assessment center, based on the determined comprehensive external stress standard curve and the comprehensive internal stress change curve, identifies the stress difference generated at the same time from the two sets of curves, and based on the specific confirmation results, identifies whether there are safety hazards in the cofferdam casting bin. The specific method of identification is:

[0049] The comprehensive external stress associated with different moments in the comprehensive external stress standard curve is calibrated as ZY t , where t represents different moments, the corresponding comprehensive internal stress at the corresponding moment is identified from the comprehensive internal stress change curve and calibrated as ZN t ;

[0050] Using Cz t =|ZY t -ZN t |Determine its stress difference Cz t ;

[0051] Identify the presence of Cz t >The relevant moment of Y3, where Y3 is a preset value, and its specific value is determined by the operator based on experience. If it exists, the total duration of the relevant moment is recorded. If the total duration exceeds 5 seconds, a safety hazard signal is generated for display, otherwise, no display is performed;

[0052] If there is no relevant moment, no processing is performed;

[0053] Based on this safety hazard signal, external relevant personnel reinforced this type of casting silo again to avoid safety hazards in the future.

[0054] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0055] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A water conservancy project construction safety hazard monitoring system based on the Internet of Things, characterized in that: include: The stress monitoring terminal monitors the stress data on both sides of the cofferdam casting bin in real time and transmits the real-time monitored stress data to the stress data processing terminal, where the stress data is monitored by a specific strain gauge; The stress data processing terminal performs numerical processing on the stress data of the cofferdam casting bin during the casting process, and confirms the three-dimensional model of the cofferdam casting bin from the constructed cofferdam model, confirms the specific direction of its relevant stress, and then determines the comprehensive external stress and comprehensive internal stress during the casting process based on the different directions of different stresses on the surface of the cofferdam casting bin; The stress curve confirmation terminal generates a comprehensive external stress change curve and a comprehensive internal stress change curve based on the comprehensive external stress and comprehensive internal stress confirmed in real time and based on different stresses associated at different times; The external stress curve optimization terminal confirms the abnormal change segment inside the curve based on the generated comprehensive external stress change curve, and preferentially identifies whether the corresponding abnormal change segment belongs to the curve segment to be optimized based on the numerical change trend and change cycle of the abnormal change segment, and then optimizes the confirmed curve segment to be optimized to obtain the comprehensive external stress standard curve; The safety hazard assessment center, based on the determined comprehensive external stress standard curve and the comprehensive internal stress change curve, identifies the stress difference generated at the same time from the two sets of curves, and based on the specific confirmation results, identifies whether there are safety hazards in the cofferdam casting bin.

2. According to the Internet of Things-based water conservancy project construction safety hazard monitoring system according to claim 1, it is characterized in that: The stress data processing terminal determines the comprehensive external stress and the comprehensive internal stress during the pouring process in the following specific manner: Confirm the cofferdam casting bin during the casting process, and select the model body of the cofferdam casting bin from the pre-built 3D model. Based on the stress data monitored by the strain gauge, confirm the specific position of the strain gauge in the model body, and identify whether the strain gauge is an external strain gauge or an internal strain gauge. If this strain gauge is an external strain gauge, the currently monitored stress data is calibrated as Yw k , where k represents different external strain gauges, and based on the specific position of the strain gauge in the model body, a related vertical line A perpendicular to the specific position is constructed, and then the center point of the outer surface of the model body is confirmed, and a related vertical line B perpendicular to the center point is constructed. The related vertical line A and the related vertical line B are moved to combine the vertical points of A and B, and the angle Jab between A and B is determined, using: W k ab=Yw k ÷cosJab confirms this stress data Yw k The associated external stress W k ab, and process other external strain gauges on the outer surface of the cofferdam casting bin in the same way, confirm the relevant external stresses associated with their stress data in turn, and then sum up several relevant external stresses to confirm the comprehensive external stress associated at the current moment; If this strain gauge is an internal strain gauge, the currently monitored stress data is calibrated as Yn i , where i represents different internal strain gauges, and based on the specific position of the strain gauge in the model body, a related vertical line C perpendicular to the specific position is constructed, and then the center point of the inner surface of the model body is confirmed, and a related vertical line D perpendicular to the center point is constructed, and the related vertical line C is moved with the related vertical line D to combine the vertical points of C and D, and the angle Jcd between C and D is determined, and the comprehensive internal stress associated with the cofferdam casting bin at the current moment is confirmed in the same way as the comprehensive external stress; Based on the stress data monitored in real time during the pouring process, the comprehensive external stress and comprehensive internal stress of the cofferdam pouring bin are confirmed in real time, and the real-time confirmed comprehensive external stress and comprehensive internal stress are transmitted to the stress curve confirmation terminal.

3. According to the Internet of Things-based water conservancy project construction safety hazard monitoring system of claim 1, it is characterized in that: The specific method of confirming the abnormal change section inside the curve by the external stress curve optimization terminal is: A stress climbing segment is confirmed from the comprehensive external stress change curve, and the comprehensive external stress inside the stress climbing segment gradually increases with the gradual change of time, and the external stress change value Bz between adjacent moments is identified from the confirmed stress climbing segment, where Bz=comprehensive external stress at the later moment-comprehensive external stress at the previous moment, and the cluster set is locked from the confirmed several external stress change values ​​Bz, and the several change values ​​Bz are sorted in the manner of small to large values, and the sorting sequence is confirmed, and then data is confirmed in the sorting sequence based on the preset value range, and the process stops when the number of confirmed data reaches the maximum, and the corresponding cluster set is confirmed. If there are multiple cluster sets, the cluster set is randomly selected for mean processing, and the several related Bz in the cluster set are processed for mean value to determine the standard value; The determined standard value is calibrated as BB, and a set of variation ranges is determined based on the standard value BB: [BB-Y1, BB+Y1], where Y1 is a preset value, and Y1 is half of the preset value range. Then, the variation value Zz between adjacent moments is identified from the comprehensive external stress variation curve. o , where o represents different adjacent moments, Zz o The corresponding moments that do not belong to [BB-Y1, BB+Y1] are marked as abnormal moments, and the curve segments associated with the continuously occurring abnormal moments are marked as abnormal change segments.

4. According to the Internet of Things-based water conservancy project construction safety hazard monitoring system of claim 3, it is characterized in that: The specific method of performing curve optimization at the external stress curve optimization terminal is as follows: Based on the several abnormal change segments confirmed in the comprehensive external stress change curve, the specific duration S of the corresponding abnormal change segment is determined. q , where q represents different abnormal change segments, S q The abnormal change segments with a value of ≤Y2 are marked as the segments to be processed, where Y2 is the preset value, and then the interval time period between adjacent segments to be processed is identified: If the time difference between the interval time periods confirmed successively before and after meets the requirement of being less than 2 seconds, the interval time periods confirmed successively will be marked as the same type of periods, and the confirmed to-be-processed segments will be marked as the curve segments to be optimized; If the time difference between the confirmations is more than 2 seconds, no calibration will be performed; The change value between adjacent moments in the curve segment to be optimized is adjusted to BB, and the curve segment is controlled to change in association, and the comprehensive external stress change curve after optimization is calibrated as the comprehensive external stress standard curve.

5. According to the Internet of Things-based water conservancy project construction safety hazard monitoring system of claim 4, it is characterized in that: The S q >No calibration is performed on the abnormal change segment related to Y2.

6. The water conservancy project construction safety hazard monitoring system based on the Internet of Things according to claim 1 is characterized in that: The specific method for the safety hazard assessment center to identify whether there are safety hazards in its cofferdam casting bin is: The comprehensive external stress associated with different moments in the comprehensive external stress standard curve is calibrated as ZY t , where t represents different moments, the corresponding comprehensive internal stress at the corresponding moment is identified from the comprehensive internal stress change curve and calibrated as ZN t ; Using Cz t =|ZY t -ZN t |Determine its stress difference Cz t ; Identify the presence of Cz t > The relevant moment of Y3, where Y3 is a preset value. If it exists, the total duration of the relevant moment is recorded. If the total duration exceeds 5 seconds, a safety hazard signal is generated for display. Otherwise, no display is performed; If there is no relevant time, no processing is performed.

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