Deepwater bridge tower column pile foundation construction monitoring method

Abstract

The invention belongs to the technical field of foundation structure test, and provides a deepwater bridge tower pile foundation construction monitoring method, which comprises the following steps: analyzing the fluctuation of water level data in different directions to obtain the fluctuation stability of the water level data in each direction; the change trend similarity between the bearing capacity data and the fluctuation stability is analyzed, and the influence degree of the fluctuation stability change on the bearing capacity data change is obtained; then, according to the fluctuation stability corresponding to different directions and in combination with the influence degree, the action difference of the deepwater environment in different directions of the steel casing is obtained; and finally, analyzing the included angle between the two directions corresponding to the maximum value of the action difference, obtaining the deviation risk degree of the steel casing, and completing construction monitoring. By analyzing the deviation risk degree of the steel casing, the construction process of the deepwater bridge tower column pile foundation is monitored, uncertainty caused by experience or rough estimation can be effectively avoided, and safe construction is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of infrastructure testing, in particular to a deep-water bridge tower column pile foundation construction monitoring method. BACKGROUND

[0002] In the construction of bridge tower column pile foundation in deep water environment, the construction process is easily affected by the complex and changeable deep water environment, resulting in unstable bridge tower column pile foundation and potential safety hazards. Advanced sensing technology and communication technology are usually used to monitor the pile foundation construction process with high precision to ensure construction quality. Remote monitoring technology is used to analyze data changes and make timely decisions and countermeasures to improve construction efficiency and safety.

[0003] The steel casing ensures accurate positioning of the pile foundation during construction, effectively isolates high pressure in water, prevents hole wall collapse and water inflow, and ensures efficient and safe construction. The displacement of the steel casing is usually monitored to evaluate the deep-water bridge tower column pile foundation construction process and ensure structural safety and meet design requirements. However, when the steel casing is offset, further processing may affect the production of the tower column pile foundation inside the steel casing, causing significant safety hazards or delaying construction progress. SUMMARY

[0004] To solve the above technical problems, the present application provides a deep-water bridge tower column pile foundation construction monitoring method.

[0005] According to the deep-water bridge tower column pile foundation construction monitoring method provided by the present application, the method comprises: Collecting water level data and bearing capacity data in different directions on the surface of the steel casing; Based on the water level data in the same direction, analyzing the fluctuation stability of the water level data in each direction to obtain the fluctuation stability of the water level data in each direction; Analyzing the change trend similarity between the bearing capacity data and the fluctuation stability to obtain the influence degree of the fluctuation stability change on the bearing capacity data change; According to the fluctuation stability corresponding to different directions, combining the influence degree, obtaining the difference in the action of the deep water environment in different directions of the steel casing; Analyzing the included angle between the two directions corresponding to the maximum value of the action difference to obtain the offset risk degree of the steel casing, and completing the construction monitoring.

[0006] In some embodiments of the present application, collecting water level data and bearing capacity data in different directions on the surface of the steel casing comprises: Water level meters are installed at eight equally spaced directions around the steel casing to collect water level data in different directions on the surface of the steel casing, and the installation height of the water level meter is the average height of the historical water level; A strain gauge sensor is attached to the surface of the steel casing in the middle directly below each water level gauge to collect bearing capacity data in different directions of the surface of the steel casing.

[0007] In some embodiments of the present application, the water level data is time series water level data. The fluctuation of each segment of water level data is analyzed to obtain the fluctuation stability of each water level data in each direction. The time series water level data is segmented using the APCA algorithm. The fluctuation of each segment of water level data is analyzed to obtain the fluctuation stability of each water level data in each direction.

[0008] In some embodiments of the present application, the fluctuation of each segment of water level data is analyzed to obtain the fluctuation stability of each water level data in each direction, including: The difference between the average water level data in the segment and the historical average water level height is analyzed, combined with the standard deviation and range of the water level data in the segment, to obtain the fluctuation stability of each water level data in each direction.

[0009] In some embodiments of the present application, the change trend similarity between the bearing capacity data and the fluctuation stability is analyzed to obtain the influence degree of the fluctuation stability change on the bearing capacity data change, including: The fluctuation stability-time curve and the bearing capacity data-time curve are drawn to obtain the fluctuation stability curve and the bearing capacity curve in each direction. The similarity between the fluctuation stability curve and the bearing capacity curve in the same direction is analyzed to obtain the first similarity in each direction. The change trend consistency degree of the fluctuation stability and the bearing capacity data in the same direction is analyzed to obtain the second similarity in each direction. According to the first similarity and the second similarity, the influence degree of the fluctuation stability change on the bearing capacity data change is obtained.

[0010] In some embodiments of the present application, the change trend consistency degree of the fluctuation stability and the bearing capacity data in the same direction is analyzed to obtain the second similarity in each direction, including: The absolute value of the difference between the slope of the fluctuation stability in the fluctuation stability curve and the slope of the bearing capacity data in the bearing capacity curve at the same time point in the same direction is calculated, and the mean value of the absolute value of the difference at all time points in the monitoring record is obtained to obtain the second similarity in each direction.

[0011] In some embodiments of the present application, according to the first similarity and the second similarity, the influence degree of the relief stability change on the bearing capacity data change is obtained, including: The product of the first similarity and the second similarity in the same direction is calculated, and the mean value of the products of all directions is obtained to obtain the influence degree of the relief stability change on the bearing capacity data change.

[0012] In some embodiments of the present application, according to the relief stability corresponding to different directions, the influence degree is combined to obtain the difference in the action of the deep water environment on the steel casing in different directions, including: According to the relief stability of the water level data corresponding to any one direction, the influence degree is combined to obtain the influence of the relief stability of the water level data corresponding to the direction on the steel casing; The absolute value of the difference of the influence of the water level data corresponding to any two directions is calculated to obtain the difference in the action of the deep water environment on the steel casing in different directions.

[0013] In some embodiments of the present application, the angle between the two directions corresponding to the maximum value of the difference in the action is analyzed to obtain the offset risk degree of the steel casing, and the construction monitoring is completed, including: The difference between the angle between the two directions corresponding to the maximum value of the difference in the action and 180 degrees is analyzed to obtain the offset risk degree of the steel casing; According to the offset risk degree, the risk emergency plan is started, and the construction monitoring is completed.

[0014] In some embodiments of the present application, according to the offset risk degree, the risk emergency plan is started, and the construction monitoring is completed, including: The offset risk degree threshold is set; It is judged whether the offset risk degree is greater than the offset risk degree threshold; If yes, the risk emergency plan is started, the offset direction of the steel casing is identified, the reinforcement measures are taken, and the construction monitoring is completed.

[0015] As can be seen from the above embodiments, the deep water bridge tower column pile foundation construction monitoring method provided by the embodiments of the present application has the following beneficial effects: The present application can discover potential unstable factors in time through analysis of the fluctuation stability of water level data; through analysis of the relationship between the change of the fluctuation stability of water level data around the steel casing and the change of bearing capacity data, the specific influence of water level data change in different directions on the bearing capacity of the steel casing is accurately quantified, which helps to understand how water level change affects the structural safety of the steel casing, so as to evaluate the stress condition of the steel casing in complex deep water environment according to the difference of the effect of deep water environment in different directions on the steel casing, identify the uneven external force received by the steel casing in different directions, further obtain the possible offset risk of the steel casing, provide accurate and reliable data support for construction, so as to monitor the construction process of the deep water bridge tower pile foundation, which can effectively avoid the uncertainty caused by experience or rough estimation, and ensure the safe construction.

[0016] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0018] Figure 1 A deep water bridge tower pile foundation construction monitoring method provided by the embodiment of the present application has a basic flowchart. DETAILED DESCRIPTION

[0019] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined object, the specific implementation, structure, features and effects of a deep water bridge tower pile foundation construction monitoring method according to the present application are described in detail as follows by combining with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The use of the terms "at least" and "one or more" suggests the inclusion of any other integer, whole or part, together with the discrete values that are expressly identified. As used herein, the singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. The terms "includes" and "including" should be interpreted broadly and encompass the inclusion of processes, compositions, ingredients and / or steps in addition to those recited. Past tense verbs should be interpreted to have present tense applicability where appropriate. The terms "example" and "exemplary" indicate functions, advantages, or characteristics that can be one of alternative means for accomplishing a given function or achieving a given result. Absent a specific contrast indicated otherwise, alternative means of accomplishing the same function or achieving the same results are contemplated and can be determined by adaptation or variation of other means to the specific contexts in which the alternative means are applied.

[0021] The specific scenario targeted by the embodiments of the present application is as follows: when a deep-water bridge tower column pile foundation is constructed, first, the construction area is surveyed, and after the position of the bridge pier is determined, in order to protect the drilling or piling operation in the pile foundation construction process, prevent the influence of the surrounding soil or water flow on the operation area, and at the same time provide a certain degree of structural support to ensure construction safety, a steel casing needs to be vertically placed and its stability needs to be ensured; then, drilling or piling operation is carried out in the steel casing by drilling or piling machinery to form the foundation of the bridge pier, and concrete is poured in the steel casing to form the main structure of the bridge pier; finally, the steel casing is extracted to facilitate subsequent construction of the bridge pier. However, the construction environment of the deep-water bridge tower column pile foundation is usually a deep-water area, which may be affected by strong water flow, tides, wind waves and other natural conditions, and these factors will bring additional difficulty and risk to the construction. In deep water, the deviation of the steel casing is mainly caused by water scouring and hydrodynamic action. Water scouring may cause the soil around the steel casing to be lost, reducing lateral support, while hydrodynamic action such as tidal flow, waves, etc. will generate horizontal forces on the steel casing, causing it to deviate.

[0022] Therefore, the purpose of the present application is to analyze the water level data and bearing capacity data of the steel casing to obtain the deviation risk degree of the steel casing, and to realize real-time monitoring of the construction of the deep-water bridge tower column pile foundation to ensure construction safety.

[0023] A deep-water bridge tower column pile foundation construction monitoring method provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0024] Please refer to Figure 1 which shows the basic flow of a deep-water bridge tower column pile foundation construction monitoring method provided by an embodiment of the present application.

[0025] As shown in Figure 1 , a deep-water bridge tower column pile foundation construction monitoring method provided by an embodiment of the present application specifically includes the following steps: S100: Collect water level data and bearing capacity data in different directions on the surface of the steel casing.

[0026] The water level data and bearing capacity data in different directions on the surface of the steel casing are collected. The specific implementation is that water level meters are installed at eight equally spaced directions around the steel casing, the water level data in different directions on the surface of the steel casing are collected, the installation height of the water level meter is the average height of the historical water level, and the water level meter can be a float type water level meter. At the same time, strain gauge sensors are attached to the surface of the steel casing in the middle directly below each water level meter to collect bearing capacity data in different directions on the surface of the steel casing. The strain gauge sensors and the float type water level meters are connected to a data transmission system, and the collected water level data and bearing capacity data are transmitted to a central monitoring system to obtain real-time monitoring water level data and bearing capacity data. The water level data is time series water level data, the bearing capacity data is time series bearing capacity data, and the time series of the water level data and the bearing capacity data correspond one by one. The water level data and the bearing capacity data are preprocessed by denoising, missing value filling and standardization to obtain processed water level data and bearing capacity data. It should be noted that the subsequent analysis is based on the processed water level data and bearing capacity data.

[0027] At this point, the water level data and bearing capacity data in different directions on the surface of the steel casing are obtained.

[0028] The stability of the water level directly affects the stress and bearing capacity of the steel casing, so it is necessary to first analyze the stability of the water level data over time and the environment; then by analyzing the corresponding change relationship between the fluctuation stability of the water level data and the bearing capacity data, the specific influence of water level fluctuation on the stress state of the steel casing is calculated; the steel casing is a columnar structure, and the steel casing is subjected to uneven external force in different directions, which produces a pressure difference to cause the offset of the steel casing, so according to the difference in the effect of the deep water environment on the steel casing in different directions, the offset risk degree of the steel casing is obtained, thereby realizing the monitoring of the deep water bridge tower pile foundation construction and ensuring the safety and reliability of the deep water bridge tower pile foundation construction process.

[0029] Based on the above analysis, the water level data and bearing capacity data of the steel casing are analyzed to obtain the offset risk degree of the steel casing, which includes S200 to S500.

[0030] S200: Based on the water level data in the same direction, the fluctuation of the water level data is analyzed to obtain the fluctuation stability of the water level data in each direction.

[0031] When the water level fluctuates greatly in the deep water environment, it indicates that the flow scouring power is strong, which may cause more serious soil loss around the steel casing, and also means that the water power effect is stronger, increasing the risk of steel casing offset. When the flow speed is too fast, the steel casing is continuously scoured, which will cause the rapid rise and violent fluctuation of the water level on the surface of the steel casing, directly affecting the stress and bearing capacity of the steel casing.

[0032] Therefore, in the embodiments of the present application, based on the water level data of the same direction, the fluctuation of the water level data is analyzed to obtain the fluctuation stability of the water level data of each direction. Further comprising: First, for the water level data and bearing capacity data in the past set time period (such as the past two hours), the APCA algorithm is used to segment the time series of water level data.

[0033] Then, the fluctuation of each water level data in the segment is analyzed to obtain the fluctuation stability of each water level data in each direction. The specific implementation is: the difference between the average water level data in the segment and the historical average water level is analyzed, combined with the standard deviation and the range of the water level data in the segment, to obtain the fluctuation stability of each water level data in each direction. The fluctuation stability calculation formula of the first water level data is constructed as follows: In the formula, represents the fluctuation stability of the first water level data; represents the standard deviation of all water level data in the segment of the first water level data; represents the average water level data of all water level data in the segment of the first water level data; represents the average water level data of all water level data in the segment of the first water level data, that is, the historical average water level; represents the range of all water level data in the segment of the first water level data; represents the exponential function with the natural constant

[0034] represents the difference between the average water level of the segment when the first water level data is monitored and the average water level in the historical monitoring record. The larger the value of this formula, the more the average water level data at this time is still at an abnormal level, which may be a continuous water level rise caused by continuous scouring of the steel pile, therefore, the fluctuation stability of the segment of the water level data is lower, that is, the fluctuation stability of the water level data is lower; represents the standard deviation of all water level data in the segment of the first water level data, which reflects the amplitude of the change of the water level around the average value. A larger standard deviation value indicates that the water level changes more dramatically, while a smaller standard deviation value indicates that the water level is relatively stable; represents the range of all water level data in the segment of the first The range of all water level data in the section where the water level data is located is the difference between the minimum value and the maximum value, and the range value can intuitively reflect the maximum fluctuation range of the water level in a certain period among the water level data in the section, and when the range is larger, the degree of fluctuation of the water level is higher, and the stability is lower.

[0035] S300: Analyzing the change trend similarity between the bearing capacity data and the fluctuation stability to obtain the influence degree of the fluctuation stability change on the bearing capacity data change.

[0036] When the strength of water flow scouring the steel casing is too large, the water level fluctuates violently, and the fluctuation change of the water level is directly related to the impact force of the water flow, so the fluctuation stability of the water level data is used to represent the degree of water flow scouring power, and when the water flow impact is larger, the bearing capacity of the steel casing will also increase correspondingly, and the increased bearing capacity may exceed the design bearing capacity of the steel casing, thereby possibly causing the steel casing to deviate. Once the steel casing deviates, it will directly affect the normal construction of the tower column pile foundation, and even may cause construction safety accidents. Therefore, in order to ensure the safety and smooth progress of the construction, it is necessary to analyze and obtain the specific influence effect of the fluctuation stability of the water level data on the bearing capacity of the steel casing, so as to timely adjust the construction scheme and take corresponding preventive measures, and ensure the stability and safety of the deep water bridge tower column pile foundation construction.

[0037] Based on the above analysis, the influence degree of the fluctuation stability change on the bearing capacity data change is obtained by analyzing the change trend similarity between the bearing capacity data and the fluctuation stability. Further comprising: Firstly, the fluctuation stability-time curve and the bearing capacity data-time curve are drawn to obtain the corresponding fluctuation stability curve and bearing capacity curve in each direction. The horizontal coordinate of the fluctuation stability curve is time, and the vertical coordinate is the fluctuation stability. The horizontal coordinate of the bearing capacity curve is time, and the vertical coordinate is the bearing capacity.

[0038] Then, the DTW similarity between the corresponding fluctuation stability curve and bearing capacity curve in the same direction is analyzed to obtain the first similarity corresponding to each direction. Wherein, DTW (Dynamic Time Warping) is an algorithm widely used in time series analysis, mainly used to measure the similarity between two time series with different lengths but similar patterns.

[0039] Simultaneously, the consistency of the changing trends of fluctuation stability and bearing capacity data in the same direction is analyzed to obtain the second similarity in each direction. The specific implementation includes: calculating the absolute value of the difference between the slope of the fluctuation stability curve and the slope of the bearing capacity data in the bearing capacity curve at the same time point in the same direction; averaging the absolute values ​​of these differences across all time points in the monitoring records to obtain the second similarity in each direction.

[0040] Finally, based on the first and second similarity scores, the degree of influence of fluctuation stability changes on bearing capacity data changes is obtained. Specifically, the product of the first and second similarity scores in the same direction is calculated, and the average of these products across all directions is taken to obtain the degree of influence of fluctuation stability changes on bearing capacity data changes. The formula for calculating the degree of influence of fluctuation stability changes on bearing capacity data changes is as follows: In the formula, This indicates the degree to which changes in the stability of water level data affect changes in bearing capacity data. Indicates the first in the historical monitoring record The stability curve of water level fluctuations in each direction; This indicates the first time the steel casing has been recorded in historical monitoring records. Bearing capacity curves in each direction; Indicates the number of monitoring directions; This indicates the number of time points collected in the historical monitoring records; Indicates the first The first direction The slope of the fluctuation stability of water level data at each time point in the fluctuation stability curve. Indicates the first The first direction The slope of the bearing capacity curve of the steel casing at each time point; Indicates the first in the historical monitoring record The similarity between the undulation stability curve and the bearing capacity curve in each direction; Represented by natural constant An exponential function with base 0.

[0041] Indicates the first The first direction The slope of the fluctuation stability of water level data at a given time point in the fluctuation stability curve represents the fluctuation change of water level data at that time point. Indicates the first The first direction The slope of the bearing capacity curve of the steel casing at each time point represents the trend of the bearing capacity data at that time point. Indicates the first in the historical monitoring record The similarity between the fluctuation stability curve and the bearing capacity curve in each direction is the smaller the value of the formula, the stronger the correlation between the two, and the greater the influence of the fluctuation stability of the water level data on the change of the bearing capacity of the steel casing. This indicates the degree of consistency between the fluctuation stability of water level data at all points in the historical monitoring records and the changing trend of the bearing capacity of the steel casing. The smaller the value of this formula, the more consistent the changing trends of the two are, and the greater the influence of the fluctuation stability of water level data on the change of the bearing capacity of the steel casing.

[0042] S400: Based on the undulation stability corresponding to different directions and combined with the degree of influence, the difference in the effect of the deep-water environment on the steel casing in different directions is obtained.

[0043] The cylindrical structure of the steel casing is subjected to the impact of water flow and external forces in deep-water environments. When the water flow is directed in one direction, it creates a non-uniform flow field around the steel casing, resulting in significant differences in the load-bearing capacity of the casing in different directions. When the water flow is directed towards one side of the casing, that side experiences greater hydrodynamic force, while the other side experiences relatively less. This uneven stress state causes the steel casing to be subjected to varying degrees of external force in different directions, thus affecting its overall stability and load-bearing capacity. Under the continuous action of the water flow, the steel casing may shift due to this uneven load-bearing capacity, affecting not only the positional accuracy of the casing but also potentially damaging its structural integrity, thereby impacting the construction quality and safety of the deep-water bridge tower pile foundation.

[0044] The load-bearing capacity data obtained by attaching strain gauge sensors at a certain location cannot represent the load-bearing capacity of the steel casing in that direction. By observing the fluctuations in water level depth and the changes in load-bearing capacity measured at the same time, the influence of water level fluctuations on the steel casing can be obtained, and the effect of water flow dynamics on the steel casing can be indirectly obtained.

[0045] Therefore, in the embodiments of the present invention, the difference in the effect of the deep-water environment on the steel casing in different directions is obtained based on the fluctuation stability corresponding to different directions and the degree of influence. Specifically, the implementation method is as follows: based on the fluctuation stability of the water level data corresponding to any one direction and the degree of influence, the influence of the fluctuation stability of the water level data corresponding to that direction on the steel casing is obtained; the absolute value of the difference in influence between the water level data corresponding to any two directions is calculated to obtain the difference in the effect of the deep-water environment on the steel casing in different directions. The method is to construct the first... The formula for calculating the difference in the effect of the fluctuation stability of water level data on the bearing capacity of steel casing is as follows: wherein, represents the difference of the fluctuation stability of the first water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing, i.e. the difference of the deep water environment in different directions of the steel casing; represents the fluctuation stability of the section where the first water level data obtained in any one monitoring direction of the steel casing is located; represents the influence degree of the change of the fluctuation stability of the water level data on the change of the bearing capacity data; represents the fluctuation stability of the section where the first water level data obtained in another monitoring direction of the steel casing is located.

[0046] represents the influence of the fluctuation stability of the section where the first water level data in any one monitoring direction is located on the steel casing; represents the influence of the fluctuation stability of the section where the first water level data in another monitoring direction is located on the steel casing; represents the difference between the influences of the fluctuation stabilities of the sections where the first water level data in any two monitoring directions of the steel casing is located on the steel casing, and the larger the formula is, the greater the difference is.

[0047] traversing the first water level data obtained in any two directions, the difference of the influences of the fluctuation stabilities of the sections where the water level data is located on the bearing capacity of the steel casing is obtained.

[0048] S500: analyzing the angle between the two directions corresponding to the maximum difference of the influences, obtaining the offset risk degree of the steel casing, and completing the construction monitoring.

[0049] When the difference of the influences of one direction and the opposite direction is large, the steel casing may be offset. Therefore, the difference of the influences of the deep water environment in different directions of the steel casing is obtained to obtain the offset risk degree of the steel casing. Therefore, by analyzing the angle between the two directions corresponding to the maximum difference of the influences, the offset risk degree of the steel casing is obtained, and the construction monitoring is completed. Further including: First, analyze the difference between the angle between the two directions corresponding to the maximum difference of the influences and 180 degrees to obtain the offset risk degree of the steel casing. The calculation formula of the offset risk degree of the steel casing when the first water level data is constructed as follows: wherein, represents the real-time monitoring of the first The offset risk degree of the steel casing when the water level data is obtained; The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing. The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing. The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing. The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing. The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing. The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing. The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing.

[0050] The maximum value of the difference in the effect of the fluctuation stability of the water level data obtained in different directions of the steel casing on the bearing capacity of the steel casing.

[0051] Then, according to the offset risk degree, a risk emergency plan is started, and construction monitoring is completed. The specific implementation is as follows: a threshold of the offset risk degree is set, and the value can be 0.7; it is determined whether the offset risk degree is greater than the threshold of the offset risk degree; if yes, that is, the offset risk degree of the steel casing exceeds the preset threshold of the offset risk degree 0.7, the risk emergency plan is started, the construction is suspended, and the construction team is notified to take corresponding treatment measures, the offset of the steel casing is analyzed in detail, the possible offset direction of the steel casing is identified, that is, the direction corresponding to the maximum difference in the effect of the deep water environment on the steel casing in different directions of the steel casing, and reinforcement measures such as increasing temporary support or using a reinforcement ring are taken to improve the stability of the steel casing. In addition, close communication is made with the design, supervision and construction units, detailed countermeasures are formulated according to the actual situation on site, and the construction safety is ensured, so that the offset risk of the steel casing is effectively controlled, and the safety and quality of the deep water bridge tower column pile foundation construction are ensured.

[0052] It should be noted that the above-mentioned order of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0053] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment mainly describes the differences from other embodiments.

Claims

1. A method for monitoring the construction of deep-water bridge tower pile foundations, characterized in that, The method includes: Collect water level and bearing capacity data from different directions on the surface of the steel casing; Based on the water level data in the same direction, the fluctuation of the water level data is analyzed to obtain the fluctuation stability of the water level data in each direction. By analyzing the similarity of the changing trends between the bearing capacity data and the fluctuation stability, the degree of influence of the fluctuation stability change on the bearing capacity data change can be obtained; Based on the fluctuation stability corresponding to different directions, and combined with the degree of influence, the difference in the effect of the deep-water environment on the steel casing in different directions is obtained; By analyzing the included angle between the two directions corresponding to the maximum difference in the effect, the offset risk of the steel casing is obtained, and construction monitoring is completed.

2. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 1, characterized in that, Collect water level and bearing capacity data from different directions on the surface of the steel casing, including: Water level gauges are installed at equal intervals in eight directions around the steel casing to collect water level data from different directions on the surface of the steel casing. The installation height of the water level gauges is the average height of the historical water level. Strain gauge sensors are attached to the surface of the steel casing directly below each water level gauge in the center to collect load-bearing capacity data in different directions on the surface of the steel casing.

3. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 1 or 2, characterized in that, The water level data is time-series water level data; Specifically, based on the water level data in the same direction, the fluctuation of the water level data is analyzed to obtain the fluctuation stability of the water level data in each direction, including: The APCA algorithm is used to segment the time series water level data; Analyze the fluctuation of each segment containing the water level data to obtain the fluctuation stability of each water level data in each direction.

4. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 3, characterized in that, Analyze the volatility of each segment containing the water level data to obtain the fluctuation stability of each water level data in each direction, including: By analyzing the difference between the average water level data within the segment where the water level data is located and the historical average water level height, and combining the standard deviation and range of the water level data within the segment where the water level data is located, the fluctuation stability of each water level data in each direction is obtained.

5. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 1, characterized in that, Analyzing the trend similarity between the bearing capacity data and the fluctuation stability, the degree of influence of the fluctuation stability change on the bearing capacity data change is obtained, including: Plot the fluctuation stability-time curve and the bearing capacity data-time curve to obtain the corresponding fluctuation stability curve and bearing capacity curve in each direction; Analyze the similarity between the fluctuation stability curve and the bearing capacity curve corresponding to the same direction to obtain the first similarity in each direction; By analyzing the consistency between the variation trend of the fluctuation stability and the bearing capacity data in the same direction, a second similarity is obtained for each direction. Based on the first similarity and the second similarity, the degree of influence of the fluctuation stability change on the bearing capacity data change is obtained.

6. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 5, characterized in that, Analyzing the consistency between the fluctuation stability and the bearing capacity data trends in the same direction yields a second similarity for each direction, including: Calculate the absolute value of the difference between the slope of the fluctuation stability in the fluctuation stability curve and the slope of the bearing capacity data in the bearing capacity curve at the same time point in the same direction. Then, average the absolute values ​​of the differences at all time points in the monitoring records to obtain the second similarity in each direction.

7. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 5, characterized in that, Based on the first similarity and the second similarity, the degree of influence of the fluctuation stability change on the bearing capacity data change is obtained, including: Calculate the product of the first similarity and the second similarity in the same direction, and average the products in all directions to obtain the degree of influence of the fluctuation stability change on the bearing capacity data change.

8. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 3, characterized in that, Based on the fluctuation stability corresponding to different directions, and combined with the degree of influence, the differences in the effects of the deep-water environment on the steel casing in different directions are obtained, including: Based on the fluctuation stability of the water level data corresponding to any direction, and combined with the degree of influence, the influence of the fluctuation stability of the water level data corresponding to that direction on the steel casing is obtained. Calculate the absolute value of the difference in influence between the water level data corresponding to any two directions to obtain the difference in the effect of the deep-water environment on the steel casing in different directions.

9. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 1, characterized in that, Analyzing the angle between the two directions corresponding to the maximum difference in action, the offset risk of the steel casing is obtained, and construction monitoring is completed, including: By analyzing the difference between the included angle between the two directions corresponding to the maximum difference in the effect and 180 degrees, the offset risk level of the steel casing is obtained; Based on the aforementioned risk level, activate the emergency response plan and complete construction monitoring.

10. The method for monitoring the construction of deep-water bridge tower pile foundations according to claim 9, characterized in that, Based on the aforementioned risk level, activate the emergency response plan and complete construction monitoring, including: Set the offset risk threshold; Determine whether the offset risk level is greater than the offset risk level threshold; If so, activate the risk emergency plan, identify the direction of the steel casing's offset, take reinforcement measures, and complete construction monitoring.

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