Fractal theory-based foundation pit maintenance structure deformation prediction method, system, device and storage medium

Abstract

The application provides a foundation pit maintenance structure deformation prediction method, system and device based on fractal theory and a storage medium, and relates to the technical field of tunnel and underground engineering monitoring and prediction. The method comprises the following steps: measuring the horizontal coordinates of a fixed measuring point on a certain day, and calculating the deformation displacement value compared with the previous day; obtaining the foundation pit cumulative displacement value based on the deformation displacement value; regarding the foundation pit cumulative displacement value as a section of evenly spaced time series, calculating the time series index; judging the foundation pit displacement change trend of the next period according to the time series index; constructing a fractal distribution model, fitting the time series by the least square method, obtaining the displacement cumulative prediction value of the next period, calculating the proportion of the displacement cumulative prediction value reaching the early warning threshold in the predetermined period, and issuing the foundation pit reinforcement notice if the proportion threshold is reached. The method introduces the fractal theory into the foundation pit deformation prediction, is easy to implement, and can also be used for the prediction of the vertical displacement of the foundation pit.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunnel and underground engineering monitoring and prediction, and particularly relates to a foundation pit maintenance structure deformation prediction method, system and device based on fractal theory and a storage medium. BACKGROUND

[0002] With the acceleration of urban development, the underground space engineering of various purposes is developed and utilized in the limited ground space of the urban core area. In tunnel engineering, the shield launching and receiving also generally need to excavate foundation pits. The foundation pit is reinforced before excavation, and steel support and concrete support are commonly used to control the deformation of the foundation pit during excavation. The instability of the foundation pit will cause ground collapse, pipeline damage, damage to the supporting structure and other consequences, which will have very serious consequences on the surrounding environment and personnel. Monitoring the deformation of the foundation pit is a necessary means to control the deformation of the foundation pit. With the expansion of the excavation depth and area of the foundation pit, the deformation control monitoring of the foundation pit becomes more and more important.

[0003] At present, the deformation monitoring of the foundation pit mainly summarizes the deformation law of the current stage, analyzes the cumulative deformation of the foundation pit, and predicts the deformation value, which will help to take emergency measures in advance.

[0004] The traditional experience prediction model such as Peck formula is based on statistical law, and it is difficult to reflect the dynamic changes of time and space effect. The prediction of BP neural network needs to consider the initial weight and threshold value of the network during network training and external factors. SUMMARY

[0005] The present application aims to provide a foundation pit maintenance structure deformation prediction method based on fractal theory, and further provides a system, device and storage medium for realizing the prediction method to solve the above problems existing in the prior art.

[0006] To achieve the above-mentioned purpose, the first aspect of the present application provides a foundation pit maintenance structure deformation prediction method based on fractal theory, which comprises the following steps:

[0007] S1, measuring the horizontal coordinates of a fixed measuring point on the kth day, and calculating the deformation displacement value compared with the (k-1)th day ;

[0008] S2, obtaining the cumulative displacement value of the foundation pit on the kth day based on the deformation displacement value ; ;

[0009] S3, regarding the cumulative displacement value of the foundation pit as a time series with uniform intervals, and calculating the time series index H ;

[0010] S4, judging the displacement change trend of the next period of foundation pit according to the time series index H, if 0≤H≤1, entering step S5; if H>1, judging that the data does not conform to the fractal distribution model or the calculation process is wrong, returning to step S1 to recalculate, if it is verified that the calculation is correct, not using the method;

[0011] S5, constructing a fractal distribution model, fitting the time series by the least square method to obtain the displacement cumulative prediction value of the next period, calculating the proportion of the displacement cumulative prediction value reaching the early warning threshold in the predetermined period, if the proportion threshold is reached, issuing a foundation pit reinforcement notice.

[0012] In further embodiments of the first aspect, the horizontal coordinates of the fixed measuring point a on the kth day are measured by a field measurement personnel through a total station . The horizontal coordinates of the kth day are compared with the horizontal coordinates of the previous day . The deformation displacement value of the kth day is calculated .

[0013] The cumulative displacement value of the kth day of the foundation pit is calculated . .

[0014] In further embodiments of the first aspect, the calculation of the time series index H satisfies the following relationship:

[0015]

[0016] In the formula, The time series range is represented; The time series standard deviation is represented.

[0017] In further embodiments of the first aspect, the time series range .

[0018] In the formula, The time series cumulative dispersion is represented . , The maximum and minimum values of the time series cumulative dispersion are represented respectively; The average cumulative displacement of the foundation pit in the total time interval K is represented, and k is the current time day.

[0019] In further embodiments of the first aspect, the time series standard deviation .

[0020] In the formula, The average cumulative displacement of the foundation pit in the total time interval K is represented, and k is the current time day.

[0021] In a further embodiment of the first aspect, the average cumulative pit displacement in the total time interval K is The calculation formula is as follows:

[0022]

[0023] In the formula, K is the total time interval, k is the current time day, is the cumulative pit displacement value on the kth day.

[0024] In a further embodiment of the first aspect, the pit displacement change trend of the next time period is determined according to the time series index H:

[0025] If H < 0, it is determined that the next time series displacement change value is the same as the previous sequence trend.

[0026] If H > 0, it is determined that the next time series displacement change value is opposite to the previous sequence trend.

[0027] If H = 0, it is determined that the next time series displacement change value is randomly distributed.

[0028] If 1 < H, it is determined that the data does not conform to the fractal distribution model or the calculation process is wrong, and the step S1 is returned to recalculate.

[0029] In a further embodiment of the first aspect, before the fractal distribution model is constructed, the following steps are further included:

[0030] is the time series of the cumulative pit displacement value A non-negative constant is added to each array in the time series so that all the arrays in it are positive values, forming the assigned sequence ;

[0031] A second-order cumulative sum is constructed for the sequence to obtain the sequence , which constitutes the data points ; wherein is the first-order cumulative sum of the sequence , that is, , , ; represents the time day.

[0032] In a further embodiment of the first aspect, the fractal distribution model satisfies the following expression:

[0033]

[0034] After deformation, it has: ;

[0035] In the formula,​​​ is a constant; D is a fractal dimension;

[0036] In a double logarithmic coordinate system, take as the horizontal axis, as the vertical axis, establish the data point relationship, and obtain the D value and the value by the least square method.

[0037] In a further embodiment of the first aspect, according to the measured cumulative displacement value on the kth day, the cumulative displacement prediction value on the k+1th day is calculated as ;

[0038] According to the iterative calculation, there is , wherein , is directly calculated by the fractal distribution model, , to obtain the displacement value ;

[0039] The cumulative displacement value of the displacement is obtained by iterative calculation , and each value obtained is subtracted by the constant C2 to obtain the cumulative displacement prediction value .

[0040] The second aspect of the present application provides a foundation pit maintenance structure deformation prediction system, which is used for automatically executing the foundation pit maintenance structure deformation prediction method based on the fractal theory disclosed in the first aspect. The foundation pit maintenance structure deformation prediction system comprises:

[0041] A measurement unit is configured to measure the horizontal coordinate of a fixed measurement point on the kth day, and calculate the deformation displacement value compared with the k-1th day ;

[0042] A calculation unit is configured to obtain the cumulative displacement value of the foundation pit on the kth day based on the deformation displacement value ; and consider the cumulative displacement value of the foundation pit as a time sequence with uniform intervals, and calculate the time sequence index H. A judgment unit is configured to judge the displacement change trend of the foundation pit in the next period according to the time sequence index H, and notify a prediction unit if 0≤H≤1; and if H>1, it is determined that the data does not conform to the fractal distribution model or the calculation process is wrong, and the calculation unit is returned to recalculate.

[0043] A prediction unit is configured to realize prediction according to the fractal distribution model obtained in advance, fit the time sequence by the least square method, and obtain the cumulative displacement prediction value of the next period.

[0044]

[0045] ​​The notification unit is configured to obtain a proportion of displacement cumulative prediction values reaching a warning threshold in a predetermined period of time, and issue a foundation pit reinforcement notification if the proportion reaches a proportion threshold.

[0046] In a third aspect, the present application provides an electronic device, comprising a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface being capable of communicating with each other through the communication bus; the memory is configured to store a plurality of executable instructions, the executable instructions causing the processor to execute the fractal theory-based foundation pit maintenance structure deformation prediction method of the first aspect.

[0047] In a fourth aspect, the present application provides a computer-readable storage medium, the storage medium storing a plurality of executable instructions, the executable instructions causing an electronic device to execute the fractal theory-based foundation pit maintenance structure deformation prediction method of the first aspect when the electronic device runs the executable instructions.

[0048] Beneficial effects: The fractal theory is introduced into the foundation pit deformation prediction, the next period of displacement cumulative quantity of the foundation pit horizontal displacement monitoring quantity is predicted, and whether the prediction value is out of limit is analyzed to provide a reference for the on-site construction personnel, so that the safety accidents can be avoided by early processing and deployment. The method is easy to implement, and can also be used for the prediction of the vertical displacement of the foundation pit. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 FIG. 1 is a flowchart of the foundation pit maintenance structure deformation prediction method in the embodiment.

[0050] Figure 2 FIG. 2 is a flowchart of the horizontal displacement value prediction calculation in the embodiment.

[0051] Figure 3 FIG. 3 is a flowchart of the warning triggering judgment in the embodiment. DETAILED DESCRIPTION

[0052] In the following description, a large number of specific details are given to provide a more thorough understanding of the present application. However, it is obvious to those skilled in the art that the present application can be implemented without one or more of these details. In other examples, some technical features known in the art are not described in order not to obscure the present application.

[0053] In view of the problems that the existing tunnel engineering and other underground space engineering foundation pit deformation monitoring mainly relies on manual reading of monitoring data and is easily affected by the environment, and lacks monitoring data prediction and insufficient pre-disposal time, the fractal theory is used to predict the precast value of the horizontal displacement cumulative quantity of the foundation pit enclosure structure and judge whether emergency disposal measures need to be taken, and the method can also be used for the prediction of the vertical displacement.

[0054] This embodiment discloses a method for predicting the deformation of foundation pit retaining structures based on fractal theory, see [link to relevant documentation]. Figure 1 , Figure 2 , Figure 3 The specific steps are as follows:

[0055] First, the on-site surveyors used a total station to measure the plane coordinates of a fixed measuring point 'a' on day k, and then converted the horizontal coordinates of the measurement results into... Compared to the previous day's horizontal plane By comparing the coordinates, the deformation displacement value on day k is obtained. (k≥2), then the cumulative displacement value When k=1, the cumulative displacement w k =0.

[0056] The retaining structure of the foundation pit is measured daily, with measurements taken within a specific timeframe whenever possible. The cumulative displacement of the foundation pit can be considered as a uniformly spaced time series. The cumulative average displacement within the time interval K is At time K, the cumulative deviation of the time series is At time K, the range is Standard deviation is .

[0057] There exists a computation that satisfies the following: The equation coefficients H are the Hurst exponents of the time series, where C is the natural constant. For ease of calculation in this method, we let C = C1. H C1 is set to 0.5 for subsequent calculations. There are various methods for calculating H; in this method, the equation is transformed... .

[0058] Let y = , For the cumulative displacement of the foundation pit over a period of K (≥10) days, the values ​​are calculated sequentially, and the slope of the fitted straight line can be obtained using the least squares method, which is the estimated value of H.

[0059] The H-value is obtained for analysis and judgment. Generally, the correlation between the H-value and the sequence is as follows: 0.5 < H ≤ 1, the displacement change value of the next time series is likely to have a similar trend to the previous series; H = 0.5 indicates a random distribution; 0 ≤ H ≤ 0.5, the displacement change value of the next time series is likely to have an opposite trend to the previous series. H-index analysis can provide a preliminary assessment of the horizontal displacement of the foundation pit, facilitating initial measures by on-site management personnel and indicating the presence of a fractal structure, allowing for further calculation of predicted values.

[0060] For the original cumulative horizontal displacement (w) i r i ),(i=1,2,…k),ri For time day, i.e. the first day is r1. Its basic sequence (i=1,2,…k), a first-order cumulative sum sequence, a second-order cumulative sum, a third-order cumulative sum, etc. can be constructed. When making a prediction later, the logarithmic operation needs to be calculated, and w i And the cumulative sum is positive, add a non-negative constant C2 (C2>0) to the horizontal displacement value of the foundation pit supporting structure, in this method, C2 is 5. That is, the offset cumulative displacement value , form the assigned basic sequence , in this method, the second-order cumulative sum is selected, that is, the sequence Data points (S2 i , r i ). is a first-order cumulative sum, in calculation , , .

[0061] In this method, the fractal distribution data satisfy the model: , C3 is a constant to be determined, and D is the fractal dimension. For fractal deformation , in the double logarithmic coordinate system, take as the horizontal axis, as the vertical axis, establish the relationship of data points, and get the value of D and by the least square method.

[0062] If only the cumulative displacement measured value on the kth day is available, the cumulative offset displacement prediction value of k+1 is calculated (i=k), according to the iterative calculation , where , can be directly calculated by the fractal distribution model, , the offset displacement value can be obtained.

[0063] Referring to the above method, the offset cumulative displacement value , …, is obtained by iterative calculation, subtract the constant to be determined C2 from each value obtained, and the cumulative displacement prediction value , , …, is obtained.

[0064] The proportion of the horizontal displacement prediction value reaching the warning threshold M is calculated, if it reaches 60%, the foundation pit reinforcement treatment measures are taken. Here, 60% can be modified according to the actual situation on site, and is not specifically limited.

[0065] In practical applications, the fractal theory-based deformation prediction method for foundation pit retaining structures disclosed in the above embodiments is designed as a system and applied at shield tunneling construction sites. This system consists of a measurement unit, a calculation unit, a judgment unit, a prediction unit, and a notification unit. It is suitable for deformation trend analysis and risk warning of foundation pit retaining structures in urban deep foundation pits and soft soil areas.

[0066] The measurement unit is used to measure the horizontal coordinate of a fixed measuring point on day k and calculate the deformation displacement value compared to day k-1. .

[0067] The calculation unit is based on the deformation displacement value Obtain the cumulative displacement value of the foundation pit on day k. The cumulative displacement value of the foundation pit Consider it as a time series with uniform intervals, and calculate the time series exponent H.

[0068] The judgment unit determines the trend of foundation pit displacement change in the next period based on the time series index H. If 0≤H≤1, the prediction unit is notified; if H>1, the data is determined to be inconsistent with the fractal distribution model or the calculation process is incorrect, and the calculation unit is returned to recalculate.

[0069] The prediction unit makes predictions based on a pre-constructed fractal distribution model, and uses the least squares method to fit the time series to obtain the cumulative predicted displacement value for the next period.

[0070] The notification unit is used to calculate the proportion of cumulative predicted displacement values ​​that reach the warning threshold within a predetermined time period. If the proportion threshold is reached, a foundation pit reinforcement notification is issued.

[0071] The system can automatically execute the fractal theory-based deformation prediction method for foundation pit maintenance structures disclosed in the above embodiments, which will not be elaborated here.

[0072] The logical approach behind the fractal theory-based deformation prediction method for foundation pit maintenance structures disclosed in the above embodiments can be implemented entirely or partially through software, hardware, firmware, or any other combination. When implemented in software, the above embodiments can be implemented entirely or partially in the form of a computer program product. A computer program product includes one or more computer instructions or computer programs.

[0073] All or part of the processes or functions according to embodiments of the present application can be produced when computer instructions or computer programs are loaded or executed on a computer. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium, or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transferred from one website site, computer, server or data center to another website site, computer, server or data center through wired (for example, infrared, wireless, microwave, etc.) manner. The computer readable storage medium can be any available medium that can be accessed by the computer or a data storage device such as a server, data center, etc. containing one or more available medium sets. The available medium can be a magnetic medium (for example, floppy disk, hard disk, magnetic tape), an optical medium (for example, DVD), or a semiconductor medium. The semiconductor medium can be a solid state disk.

[0074] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general purpose computer, a special purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the flow Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks. Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks.

[0075] These computer program instructions can also be stored in a computer readable storage medium that can guide the computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer readable storage medium produce a product including instruction devices, which implement the flow Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks. Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks.

[0076] These computer program instructions can also be loaded into a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer implemented process, so that the instructions executed on the computer or other programmable device provide a process for implementing the flow Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks. Figure 1 The device that implements the function specified in one flow or multiple flows and / or blocks.

[0077] The preferred embodiments of the application disclosed above are only to facilitate the elucidation of the application. The preferred embodiments do not describe all the details of the application and limit the application to the specific embodiments. Obviously, many modifications and variations can be made in light of the teachings above. The description is chosen and described in order to provide the best illustration of the application and its practical application to those skilled in the art and to enable those skilled in the art to best utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A method for predicting deformation of a foundation pit support structure based on fractal theory, characterized by, Comprising the following steps: S1, measure the horizontal coordinate of a certain fixed measuring point on the kth day, calculate the deformation displacement value compared with the (k-1)th day ; S2, based on the deformation displacement value obtain the cumulative displacement value of the foundation pit on the kth day ; S3、cumulative displacement value of the foundation pit The time series index H is calculated as a uniform time series of a certain interval, and the time series index H satisfies the following relationship: ； wherein denotes the time series range; denotes the time series standard deviation; S4, judging the displacement change trend of the next time period according to the time series index H, if 0≤H≤1, entering step S5, wherein if , it is determined that the next time series displacement change value is the same as the previous sequence trend; if , it is determined that the next time series displacement change value is randomly distributed; and if , it is determined that the next time series displacement change value is opposite to the previous sequence trend; If H>1, it is determined that the data does not conform to the fractal distribution model or the calculation process is wrong, and step S1 is returned to recalculate, and if the calculation is verified to be correct, the method is not used; S5, time series of cumulative displacement values of the foundation pit adding a non-negative constant to each array in so that all arrays in are positive, forming the assigned sequence ; for the sequence The second order cumulants are constructed to obtain the sequence of data points ; where is the first order cumulants of the sequence , i.e. , , ; denotes the time day; A fractal distribution model is constructed, and the fractal distribution model satisfies the following expression: ； Deformed has: ; wherein is a constant to be determined; D is the fractal dimension; In a double logarithmic coordinate system, the horizontal axis is and the vertical axis is , the data points are related, and the D value and value are obtained by the least square method. The time series is fitted by the least square method to obtain the displacement cumulative prediction value of the next period, the proportion of the displacement cumulative prediction value reaching the early warning threshold in the predetermined period is calculated, and if the proportion threshold is reached, a foundation pit reinforcement notice is issued.

2. The method of claim 1, wherein, The horizontal coordinate of the fixed measuring point a on the kth day is measured by a total station by a field surveyor The horizontal coordinate of the kth day is compared with the horizontal coordinate of the previous day The horizontal coordinate of the kth day is compared with the horizontal coordinate of the previous day The deformation displacement value of the kth day is calculated ; then the cumulative displacement value of the foundation pit on the kth day , k = 1, .

3. The method according to claim 1, wherein, the time series range ; wherein, denotes the cumulative deviation of the time series ; , are the maximum and minimum values of the cumulative deviation of the time series, respectively; is the average cumulative displacement of the foundation pit within the total time interval K, k is the current time day; the time series standard deviation ; wherein, is the average displacement of the foundation pit accumulated in the total time interval K, k is the current time day; average of the cumulative displacement of the foundation pit in the total time interval K The calculation formula is as follows: ； In the formula, K is the total time interval, k is the current time day, is the cumulative displacement value of the foundation pit on the kth day.

4. The method according to claim 1, wherein, According to the measured value of the accumulated displacement on the kth day, the predicted value of the accumulated displacement on the (k+1)th day is calculated ; According to the iterative calculation has wherein , is directly calculated by the fractal distribution model, , the offset displacement value ; The offset accumulated displacement value is obtained by iterative calculation Subtracting a constant C2 from each of the obtained values gives the displacement accumulated prediction value .

5. A deformation prediction system for a foundation pit support structure, characterized by, The fractal theory-based foundation pit maintenance structure deformation prediction method for automatically performing any one of claims 1 to 4, the foundation pit maintenance structure deformation prediction system comprising: a measuring unit for measuring the horizontal coordinate of a certain fixed measuring point on the kth day, calculating the deformation displacement value compared with the (k-1)th day ; a computing unit configured to calculate a cumulative displacement value of the foundation pit based on the deformation displacement values obtain a cumulative displacement value of the foundation pit on the kth day ; the cumulative displacement value of the foundation pit regard as a segment interval uniform time series, calculate time series index H; A judgment unit determines the foundation pit displacement change trend in the next period according to the time series index H, and notifies the prediction unit if 0≤H≤1; if H>1, it is determined that the data does not conform to the fractal distribution model or the calculation process is wrong, and the calculation unit is returned to recalculate; A prediction unit realizes prediction according to the fractal distribution model constructed in advance, and fits the time series by the least square method to obtain the displacement cumulative prediction value of the next period; A notification unit is used to calculate the proportion of the displacement cumulative prediction value reaching the early warning threshold in the predetermined period, and issue a foundation pit reinforcement notice if the proportion threshold is reached.

6. An electronic device, comprising: Comprising: A processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete mutual communication through the communication bus; The memory is used to store a plurality of executable instructions, and the executable instructions make the processor execute the fractal theory-based foundation pit maintenance structure deformation prediction method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The storage medium has a plurality of executable instructions stored therein, and the executable instructions make the electronic device execute the fractal theory-based foundation pit maintenance structure deformation prediction method according to any one of claims 1 to 4 when running on the electronic device.

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