An Internet of Things-based hidden danger monitoring system for water conservancy project construction

Abstract

The present invention discloses a safety hazard monitoring system for water conservancy project construction based on the Internet of Things. The present invention relates to the technical field of water conservancy project construction, and solves the problem that a systematic safety hazard monitoring method is not adopted for comprehensive monitoring. The present invention analyzes the stress change curve generated by it, and based on the corresponding analysis process, locks the abnormal section with regular time changes in the change curve, and based on the standard value confirmed in the curve, optimizes and calibrates such abnormal sections to avoid the influence caused by external waves during the stress hazard monitoring process, obtains a relatively accurate external stress change curve, and then determines the safety hazard based on the change situation of the difference between the external stress and the internal stress confirmed at the same time. For this way of determining the safety hazard, the accuracy of its value can be effectively guaranteed, and a relatively comprehensive 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 specifically to a water conservancy project construction safety hazard monitoring system based on the Internet of Things. Background Technique

[0002] Before the construction of a water conservancy project, it is necessary to conduct a detailed review of the design drawings and construction plans of the water conservancy project. This includes checking whether the scale and layout of the project meet the requirements of the water conservancy plan. A cofferdam is a temporary water retaining structure. During the construction of water conservancy projects (such as dams, sluices, pumping stations, etc.), in order to create dry construction conditions, it is necessary to isolate the construction area from the water body, and the cofferdam plays this role.

[0003] During the construction of a water conservancy project, for the specific construction process of the cofferdam, generally during concrete pouring, based on corresponding manual observations, it is evaluated whether the cofferdam is safe and up to standard. However, in the actual application process, the deformations and changes in many areas are invisible to the human eye. Therefore, during the monitoring of actual safety compliance issues, there are too many interference factors of human influence, and a good safety hazard monitoring effect cannot be achieved. Moreover, a systematic safety hazard monitoring method has not been adopted for comprehensive monitoring, and the construction safety hazards still need to be strengthened. Summary of the Invention

[0004] Aiming at the deficiencies 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 realized through the following technical solutions: A water conservancy project construction safety hazard monitoring system based on the Internet of Things, including:

[0006] A stress monitoring terminal, which monitors the stress data on both sides inside the cofferdam pouring 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 specific strain gauges;

[0007] A stress data processing terminal, which numerically processes the stress data during the pouring process of the cofferdam pouring bin, confirms the three-dimensional model of this cofferdam pouring bin from the constructed cofferdam model, confirms the specific direction of the relevant stress, and then determines the comprehensive external stress and comprehensive internal stress during the pouring process based on the different orientations of different stresses on the surface of the corresponding cofferdam pouring bin. The specific method is as follows:

[0008] Confirm the cofferdam pouring bin during the pouring process, select the model body of this cofferdam pouring bin from the pre-constructed three-dimensional model, confirm the specific position of this strain gauge on this model body based on the stress data monitored by the strain gauge, and identify whether this strain gauge belongs to an external strain gauge or an internal strain gauge;

[0009] If this strain gauge belongs to the external strain gauge, calibrate the currently monitored stress data as Yw k , where k represents different external strain gauges. Based on the specific position of this strain gauge on this model body, construct the relevant perpendicular line A perpendicular to the specific position, then confirm the center point of the outer surface of this model body, and construct the relevant perpendicular line B perpendicular to this center point. Move the relevant perpendicular line A and the relevant perpendicular line B so that the perpendicular points of A and B are combined, and determine the included angle Jab between A and B. Use: W k ab = Yw k ÷cosJab to confirm this stress data Yw k The associated relevant external stress W k ab, and process other external strain gauges on the outer surface of the concrete placement bin of this cofferdam in the same way, successively confirm the relevant external stresses associated with their stress data, and then sum up several relevant external stresses to confirm the comprehensive external stress associated with the current moment;

[0010] If this strain gauge belongs to the internal strain gauge, calibrate the currently monitored stress data as Yn i , where i represents different internal strain gauges. Based on the specific position of this strain gauge on this model body, construct the relevant perpendicular line C perpendicular to the specific position, then confirm the center point of the inner surface of this model body, and construct the relevant perpendicular line D perpendicular to this center point. Move the relevant perpendicular line C and the relevant perpendicular line D so that the perpendicular points of C and D are combined, and determine the included angle Jcd between C and D, and use the same method as confirming the comprehensive external stress to confirm the comprehensive internal stress associated with the current moment of the concrete placement bin of this cofferdam;

[0011] And based on the stress data monitored in real time during the pouring process, confirm the comprehensive external stress and comprehensive internal stress of this cofferdam concrete placement bin in real time, and transmit the confirmed comprehensive external stress and comprehensive internal stress to the stress curve confirmation terminal;

[0012] The stress curve confirmation terminal, based on the comprehensively confirmed external stress and internal stress in real time, and based on the different stresses associated with different moments, generates its comprehensive external stress change curve and comprehensive internal stress change curve;

[0013] The external stress curve optimization terminal, based on the generated comprehensive external stress change curve, confirms the abnormal change segments inside the curve. First, based on the numerical change trend and change period of the abnormal change segments, identify whether the corresponding abnormal change segments belong to the curve segments to be optimized, and then optimize the confirmed curve segments to be optimized to obtain the comprehensive external stress standard curve. The specific method is:

[0014] Identify the stress climbing section from this comprehensive external stress change curve. The comprehensive external stress inside the stress climbing section gradually increases with the passage of time. Identify the external stress change value Bz between adjacent moments from the identified stress climbing section, where Bz = the comprehensive external stress at the later moment - the comprehensive external stress at the previous moment. Lock its clustering set from the identified several external stress change values Bz, sort the several change values Bz in ascending order of numerical value to confirm the sorting sequence, and then perform data confirmation within the sorting sequence based on a preset numerical range. Stop when the number of confirmed data reaches the maximum, confirm the corresponding clustering set. If there are multiple groups of clustering sets, randomly select a clustering set for mean processing, and perform mean processing on several relevant Bz within the clustering set to determine the standard value;

[0015] Calibrate the determined standard value as BB, and determine a set of change ranges based on the standard value BB: [BB - Y1, BB + Y1], where Y1 is a preset value, and Y1 is half of the preset numerical range. Then identify the change value Zz between adjacent moments from this comprehensive external stress change curve o , where o represents different adjacent moments. Mark the corresponding moments when Zz o does not belong to [BB - Y1, BB + Y1] as abnormal moments, and mark the curve segment associated with continuously occurring abnormal moments as a change abnormal segment;

[0016] Based on several change abnormal segments confirmed within this comprehensive external stress change curve, and determine the specific duration S of the corresponding change abnormal segment q , where q represents different change abnormal segments. Mark the related change abnormal segments with S q ≤ Y2 as segments to be processed, where Y2 is a preset value. Then identify the interval time period between adjacent segments to be processed, S q > Y2 for the related change abnormal segments without any marking:

[0017] If the time difference between the sequentially confirmed interval time periods is less than 2 seconds, mark the sequentially confirmed interval time periods as the same type of period, and mark the confirmed segments to be processed as segments of the curve to be optimized;

[0018] If the time difference between the sequentially confirmed interval time periods exceeds 2 seconds, do not perform any marking;

[0019] Adjust the change value between adjacent moments within the segment of the curve to be optimized to BB, and control the curve segment for associated changes. Mark the optimized comprehensive external stress change curve as the 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 between the same moments from the two groups of curves, and based on the specific confirmation results, identifies whether there are safety hazards in its cofferdam pouring bin. The specific method is as follows:

[0021] Calibrate the comprehensive external stress associated with different moments in the comprehensive external stress standard curve as ZY t , where t represents different moments, identify the corresponding comprehensive internal stress at the corresponding moment from the comprehensive internal stress change curve, and calibrate it as ZN t ;

[0022] Adopt Cz t =|ZY t -ZN t | to determine its stress difference Cz t ;

[0023] Identify whether there are relevant moments when Cz t >Y3, where Y3 is a preset value. If there are, record the total duration when the relevant moments appear. If the total duration exceeds 5 seconds, generate a safety hazard signal for display. Otherwise, do not perform any display;

[0024] If there are no relevant moments, do not perform any processing either.

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

[0026] By monitoring the stress of the cofferdam pouring bin corresponding to the water conservancy project and confirming the corresponding comprehensive stress based on the corresponding three-dimensional model, the present invention can achieve a better stress monitoring effect, facilitate hazard identification, and effectively guarantee the accuracy and precision of its identification;

[0027] Based on the monitored corresponding external stress, analyze the stress change curve generated by it, and based on the corresponding analysis process, lock the abnormal segments with regular changes in time in its change curve, and based on the standard values confirmed in the curve, optimize and calibrate such abnormal segments to avoid the influence caused by external waves during the stress hazard monitoring process, obtain a more accurate external stress change curve, and then determine the safety hazard based on the difference change situation of the external stress and the internal stress confirmed at the same moment. The accuracy of the numerical value of this safety hazard determination method can be effectively guaranteed, and a more comprehensive safety hazard monitoring effect can be achieved. Description of the Drawings

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

[0029] Figure 2This is a top view schematic diagram of the cofferdam pouring bin of the present invention. Detailed implementation mode

[0030] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work belong to the scope of protection of the present invention.

[0031] Please refer to Figure 1 , this application provides a safety hazard monitoring system for water conservancy project construction 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] Among them, 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 respectively electrically connected to the input node of the external stress curve optimization terminal or 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 inside the cofferdam pouring bin in real time, and transmits the real-time monitored stress data into the stress data processing terminal. The stress data is monitored by specific strain gauges, and the sensors are arranged by relevant operators in advance at the connection points inside the corresponding pouring bin, generally using strain gauges. When the inner wall of the cofferdam deforms, the resistance value of the strain gauge will change, so that the specific monitoring of the stress at the corresponding contact point can be completed;

[0034] Among them, the stress data processing terminal numerically processes the stress data during the pouring process of the cofferdam pouring bin, confirms the three-dimensional model of this cofferdam pouring 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 its pouring process based on the different orientations of different stresses on the surface of the corresponding cofferdam pouring bin. Specifically, during the actual pouring process, as the concrete is gradually poured into the cofferdam, relevant stresses will be generated inside the cofferdam towards the inner wall and outer wall of the cofferdam bin. Normally, the values of the generated external stress and internal stress should be within a specific numerical range, but due to internal connection points or other unexpected situations, there will be a large difference between the internal and external stresses. Then such a situation has corresponding safety hazards and requires relevant treatment to timely detect and handle the safety hazards;

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

[0036] Identify the cofferdam placement bay during the pouring process, select the model body of this cofferdam placement bay from the pre-constructed 3D model, based on the stress data monitored by the strain gauges, confirm the specific location of this strain gauge on this model body, and identify whether this strain gauge belongs to an external strain gauge or an internal strain gauge;

[0037] If this strain gauge belongs to an external strain gauge, calibrate the currently monitored stress data as Yw k , where k represents different external strain gauges, and based on the specific location of this strain gauge on this model body, construct the relevant perpendicular line A perpendicular to the specific location, then confirm the center point of the outer surface of this model body, and construct the relevant perpendicular line B perpendicular to this center point. Move the relevant perpendicular lines A and B so that the perpendicular points of A and B are combined, and determine the angle Jab between A and B. Use: W k ab = Yw k ÷cosJab (here trigonometric functions are used to confirm the comprehensive external stress of several stress data in the same orientation) to confirm this stress data Yw k The associated relevant external stress W k ab, and process other external strain gauges on the outer surface of this cofferdam placement bay in the same way, sequentially confirm the relevant external stresses associated with their stress data, and then sum up several relevant external stresses to confirm the comprehensive external stress associated with the current moment;

[0038] If this strain gauge belongs to an internal strain gauge, calibrate the currently monitored stress data as Yn i , where i represents different internal strain gauges, and based on the specific location of this strain gauge on this model body, construct the relevant perpendicular line C perpendicular to the specific location, then confirm the center point of the inner surface of this model body, and construct the relevant perpendicular line D perpendicular to this center point. Move the relevant perpendicular lines C and D so that the perpendicular points of C and D are combined, and determine the angle Jcd between C and D, and use the same method to confirm the comprehensive internal stress associated with this cofferdam placement bay at the current moment as for confirming the comprehensive external stress;

[0039] And based on the stress data monitored in real time during the pouring process, confirm the comprehensive external stress and comprehensive internal stress of this cofferdam placement bay in real time, and transmit the real-time confirmed comprehensive external stress and comprehensive internal stress to the stress curve confirmation terminal;

[0040] Combine Figure 2 , Figure 2It is only a relevant top view schematic diagram corresponding to the cofferdam pouring bin. The cofferdam is composed of several spliced cofferdam pouring bins. The corresponding strain gauges are arranged on the inner and outer surfaces of the cofferdam pouring bin to monitor the stresses at the corresponding points on both the inner and outer surfaces, so as to confirm the corresponding external stress and internal stress. Then, based on the relevant central points of the corresponding inner and outer surfaces, the specific vertical lines are confirmed. And based on the specific orientations of the corresponding external stress and internal stress and the specific angles with the corresponding vertical lines, the resultant force where multiple stresses converge can be confirmed, that is, the corresponding resultant external stress and resultant internal stress.

[0041] Among them, the stress curve confirmation terminal, based on the real-time confirmed resultant external stress and resultant internal stress, and based on the different stresses associated with different times, generates the resultant external stress change curve and the resultant internal stress change curve, and transmits the resultant external stress change curve to the external stress curve optimization terminal for curve optimization. The horizontal axis of the corresponding change curve is the time line, and the vertical axis is the stress data;

[0042] For its external stress curve optimization terminal, based on the generated resultant external stress change curve, it confirms the abnormal change segments inside the curve. First, based on the numerical change trend and change period of the abnormal change segment, it identifies whether the corresponding abnormal change segment belongs to the curve segment to be optimized, 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, thus generating a set of internal stresses. Therefore, the internal and external stresses will cancel each other out. However, the impact of water waves has a time pattern, and the corresponding periods generated by the front and back waves will not differ greatly. Therefore, there are corresponding abnormal change segments with time periods in the corresponding resultant external stress change curve. Such change abnormal segments can be directly corrected, so relevant optimization is required to ensure that the corresponding resultant external stress change curve can be fully optimized, to ensure the specific accuracy of subsequent numerical confirmation, and to achieve the overall effect of safety hazard assessment;

[0043] Among them, the specific method for optimizing the resultant external stress change curve is as follows:

[0044] Identify the stress climbing section from this comprehensive external stress change curve. The comprehensive external stress within the stress climbing section gradually increases as time gradually changes (the gradual change in time means that time gradually moves forward. Due to the gradual change in 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). Identify the external stress change value Bz between adjacent moments from the identified stress climbing section, where Bz = the comprehensive external stress at the later moment - the comprehensive external stress at the previous moment. Lock the clustering set from the identified several external stress change values Bz. Sort the several change values Bz in ascending order of numerical value to confirm the sorting sequence. Then, based on a preset numerical range, perform data confirmation within the sorting sequence. Stop when the number of confirmed data reaches the maximum (that is, the number of data belonging to this numerical range reaches the maximum). Confirm the corresponding clustering set. If there are multiple groups of clustering sets, randomly select a clustering set for mean processing. Perform mean processing on several relevant Bz within the clustering set to determine the standard value. Assume the confirmed sorting sequence is {0.1, 1, 1.1, 1.2, 1.3, 1.4, 1.31, 4, 5, 6}, and assume the determined numerical range is 3. Then, start from the first group of numerical range 0 - 3. Confirm the corresponding data column {0.1, 1, 1.1, 1.2, 1.3, 1.4, 1.31}. Subsequently, change 0 - 3 to 1 - 4, and there will be a corresponding data column {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, and thus the corresponding clustering set can be confirmed. Although there are other abnormal external stresses among several Bz, under normal construction pouring conditions, the external stress should increase normally. Therefore, there are Bz values corresponding to clustering, and thus the corresponding clustering set can be confirmed to specifically confirm the numerical value;

[0045] Calibrate the determined standard value as BB. Based on the standard value BB, determine a set of change ranges: [BB - Y1, BB + Y1], where Y1 is a preset value, and Y1 is half of the preset numerical range. Then, identify the change value Zz between adjacent moments from this comprehensive external stress change curve o , where o represents different adjacent moments. For Zz o that does not belong to [BB - Y1, BB + Y1], calibrate the corresponding moment as an abnormal moment, and calibrate the curve segment associated with the continuously occurring abnormal moments as a change abnormal segment;

[0046] Based on several change abnormal segments confirmed within this comprehensive external stress change curve, determine the specific duration S of the corresponding change abnormal segment q , where q represents different change abnormal segments. For S qThe relevant abnormal change segments of ≤Y2 are marked as segments to be processed. Conversely, no marking is performed, where Y2 is a preset value, and its specific value is determined by the operator according to experience. When it is impacted by waves, it generally ends within two seconds, so Y2 generally takes the value of 2. Then, identify the time interval period between adjacent segments to be processed. If the time difference between the successively confirmed time interval periods meets the condition that it is less than 2 seconds (here it can be understood that: there are three segments to be processed, A, B, and C. The time interval between A and B is 4 seconds, and the time interval between B and C is 3.9 seconds. The difference between 4 seconds and 3.9 seconds is 0.1 second, which is less than 2 seconds. Then both the AB segment and the BC segment belong to the corresponding curve segments to be optimized. Here, less than includes 2 seconds). If the time difference between the successively confirmed time interval periods meets the condition that it exceeds 2 seconds, no marking is performed, and the successively confirmed time interval periods are marked as the same type of period, and the confirmed segments to be processed are marked as curve segments to be optimized. Specifically, there is a corresponding time interval between adjacent segments to be processed, and there will be a time difference between the time intervals. When the time difference is relatively close, it means that the corresponding segments to be processed appear regularly, and thus the corresponding segments to be processed can be marked. Under normal pouring conditions, there is no corresponding regular situation for abnormal stress changes, and 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] Adjust the change value between adjacent moments within the curve segment to be optimized to BB, and control the curve segment to perform associated changes. Mark the comprehensive external stress change curve after the optimization process as the comprehensive external stress standard curve. Specifically, assume that the corresponding curve segment to be optimized is A - B - C. Then the positions of B and C will change again. Since the change value between them is adjusted from the original parameter to BB, the point B will definitely move up, 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 between the same moments from the two groups of curves. Based on the specific confirmation results, it identifies whether there are safety hazards in the cofferdam pouring bin. Among them, the specific method for identification is as follows:

[0049] Mark the comprehensive external stress associated with different moments in the comprehensive external stress standard curve as ZY t , where t represents different moments, identify the comprehensive internal stress corresponding to the corresponding moment from the comprehensive internal stress change curve, and mark it as ZN t ;

[0050] Use Cz t =|ZY t -ZN t | to determine the stress difference Cz t ;

[0051] Identify whether Cz exists t Related moments greater than Y3, where Y3 is a preset value, and its specific value is determined by the operator according to experience. If they exist, record the total duration when the related moments occur. If the total duration exceeds 5 seconds, generate a safety hazard signal for display; otherwise, do not perform any display;

[0052] If there are no related moments, do not perform any processing either;

[0053] Based on this safety hazard signal, external relevant personnel reinforce such pouring bins again to avoid potential safety hazard problems in the later stage.

[0054] Some data in the above formula are numerically calculated after removing their dimensions, and the content not described in detail in this specification belongs 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 of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced 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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