A method to reduce the monitoring error of uneven settlement in deep foundation pits

Abstract

This application relates to the field of settlement monitoring technology, specifically to a method for reducing the monitoring error of uneven settlement in deep foundation pits. The method includes: measuring the three-dimensional coordinate information of each monitoring point within the deep foundation pit area; obtaining the degree of interference synchronization of each monitoring point in each time period based on the synchronicity characteristics of the random fluctuations in the three-dimensional coordinate information of each monitoring point in each time period, and obtaining the duration of synchronous interference of each monitoring point based on the changing characteristics of the degree of interference synchronization of each monitoring point in all time periods; obtaining the significance coefficient of interference for each monitoring point by the average level and difference of the degree of interference synchronization of different monitoring points in a local area, and then combining the duration of synchronous interference to obtain the settlement reliability of each monitoring point to extract settlement points; and monitoring the uneven settlement of the deep foundation pit based on the differences in the coordinate distribution of each settlement point in the vertical direction. This application can improve the accuracy of settlement monitoring.

Description

Technical Field

[0001] This application relates to the field of settlement monitoring technology, specifically to a method for reducing the monitoring error of uneven settlement in deep foundation pits. Background Technology

[0002] Generally, uniform settlement of deep foundation pits has little impact on building structures. However, uneven settlement can cause additional stress in buildings, leading to cracks and even the risk of tilting or collapse. Therefore, to ensure the stability and safety of deep foundation pits, high-precision monitoring of uneven settlement is necessary. This allows for real-time monitoring of the settlement status and the implementation of appropriate measures to guarantee the construction quality and safety of the deep foundation pits.

[0003] In existing technologies, a stable reference coordinate system is established by using monitoring points within the deep foundation pit area and benchmark points on the ground surface. A total station is then used to measure the three-dimensional coordinates of each monitoring point within the deep foundation pit area in real time, and the data is analyzed to ultimately monitor the uneven settlement of the deep foundation pit. However, because the measurement of three-dimensional coordinates using a total station is easily affected by environmental factors such as atmospheric refraction and strong winds, existing technologies do not fully consider the degree of interference at different monitoring points when monitoring uneven settlement of deep foundation pits. This results in significant errors in the monitoring of uneven settlement, making it impossible to accurately assess the stability and safety of the deep foundation pit. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a method for reducing the monitoring error of uneven settlement in deep foundation pits, thereby resolving the existing issues.

[0005] The method for reducing monitoring errors of uneven settlement in deep foundation pits proposed in this application adopts the following technical solution:

[0006] One embodiment of this application provides a method for reducing the monitoring error of uneven settlement in deep foundation pits, comprising the following steps:

[0007] Measure the three-dimensional coordinate information of each monitoring point within the deep foundation pit area;

[0008] Based on the synchronicity characteristics of the random fluctuations of the three-dimensional coordinate information of each monitoring point in each time period, the degree of interference synchronization of each monitoring point in each time period is obtained, and based on the change characteristics of the degree of interference synchronization of each monitoring point in all time periods, the duration of synchronization interference of each monitoring point is obtained.

[0009] By analyzing the average level and degree of difference in the synchronization of different monitoring points in a local area, the interference significance coefficient of each monitoring point is obtained. Then, combined with the duration of the synchronization interference, the settlement confidence of each monitoring point is obtained, which is used to divide the monitoring points and extract settlement points.

[0010] Based on the differences in the coordinate distribution of each settlement point in the vertical direction, the uneven settlement of the deep foundation pit is monitored.

[0011] Preferably, the method for obtaining the degree of synchronization affected by interference at each monitoring point in each time period is further as follows:

[0012] In the formula, Let be the degree of synchronization affected by interference at the i-th monitoring point in the t-th time period. Let be the mean of the information entropy of all dimensional residual subsequences of the i-th monitoring point in the i-th time period. Let be the mean of the difference distances between all dimensional residual subsequences of the i-th monitoring point in the i-th time period. To avoid constants with a denominator of 0.

[0013] Preferably, the values ​​of each dimension in the three-dimensional coordinate information at all times of each monitoring point are arranged in chronological order, and each monitoring point obtains a three-dimensional data sequence. Each dimension data sequence of each monitoring point is evenly divided into multiple subsequences, which are used as the dimension data subsequences of each monitoring point in each time period.

[0014] Preferably, the data subsequences of each monitoring point in each dimension for each time period are decomposed into time series to obtain the residual subsequences of each monitoring point in each dimension for each time period.

[0015] Preferably, the method for obtaining the duration of synchronization interference at each monitoring point further comprises:

[0016] In the formula, Let be the duration of synchronization interference at the i-th monitoring point. Let be the number of elements in the synchronization interference sequence of the i-th monitoring point, i.e., the number of time periods. It is an exponential function with the natural constant as its base. and These are the j-th and (j-1)-th elements in the synchronization interference sequence of the i-th monitoring point, respectively. The synchronization interference sequence of each monitoring point is formed by arranging the synchronization degree of each monitoring point in all time periods according to the time sequence.

[0017] Preferably, the method for obtaining the significance coefficient of interference at each monitoring point is further as follows:

[0018] In the formula, Let be the significance coefficient of the interference at the i-th monitoring point. Here is the range normalization function. Let be the mean of the synchronization interference sequence at the i-th monitoring point. Let be the average difference distance between the i-th monitoring point and the synchronization interference sequences of all its neighboring monitoring points, where the synchronization interference sequence of each monitoring point is formed by arranging the synchronization interference degree of each monitoring point in time sequence across all time periods.

[0019] Preferably, the multiple monitoring points that are closest to each monitoring point are all considered as the nearest neighbor monitoring points of each monitoring point.

[0020] Preferably, the method for obtaining the settlement reliability of each monitoring point is further as follows: In the formula, Let i be the settlement confidence level of the i-th monitoring point. and represent the significance coefficient of interference and the duration of synchronous interference for the i-th monitoring point, respectively.

[0021] Preferably, the extraction of settlement points further includes: thresholding the settlement confidence of all monitoring points, and taking the monitoring points with settlement confidence greater than the threshold as settlement points.

[0022] Preferably, the monitoring of uneven settlement in deep foundation pits further includes:

[0023] Obtain the vertical dimension data sequence of each settlement point and calculate the first-order difference sequence. Take the sum of all elements in the first-order difference sequence as the settlement amount of each settlement point. Calculate the average absolute error of the settlement amount of all settlement points and normalize it. If the normalization result is less than the preset value, there is no uneven settlement in the deep foundation pit; otherwise, uneven settlement occurs in the deep foundation pit.

[0024] This application has at least the following beneficial effects:

[0025] This application addresses the issue that measuring three-dimensional coordinate information using a total station is easily affected by environmental factors. Existing technologies for monitoring uneven settlement in deep foundation pits do not adequately consider the degree of interference at different monitoring points, leading to significant errors in monitoring uneven settlement. Therefore, this application extracts random fluctuations and noise components from data across different time periods. By leveraging the complexity of these random fluctuations and noise components and the differences between them, it accurately measures the synchronicity characteristics of three-dimensional coordinate data affected by external environmental factors, thus avoiding high elevation variation errors at subsequently selected monitoring points.

[0026] Furthermore, this application analyzes the duration characteristics of the synchronous interference of external environmental factors on the three-dimensional coordinate information of each monitoring point by the upward trend of the synchronous interference between adjacent time periods, which is beneficial to the subsequent selection of settlement points more accurately.

[0027] Meanwhile, this application accurately measures the reliability of settlement at each monitoring point based on the duration of synchronous interference at each monitoring point and fully considers the significant characteristics of interference at the monitoring points. This allows for more accurate selection of suitable settlement points to monitor the uneven settlement of deep foundation pits, thereby avoiding interference caused by external environmental factors, reducing the error in monitoring uneven settlement of deep foundation pits, and improving the accuracy of monitoring uneven settlement of deep foundation pits. Attached Figure Description

[0028] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 A flowchart illustrating the steps of a method for reducing monitoring errors of uneven settlement in deep foundation pits, as provided in this application. Detailed Implementation

[0030] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method for reducing the monitoring error of uneven settlement in deep foundation pits according to this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0031] Unless otherwise defined, terms such as “comprising,” “including,” or any other variations thereof are intended to cover a non-exclusive inclusion, such that a circuit structure, article, or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the article or device that includes said element. Furthermore, the term “and / or” as used herein includes any and all combinations of one or more of the associated listed items. 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 pertains.

[0032] The following description, in conjunction with the accompanying drawings, details a specific scheme for a method to reduce the monitoring error of uneven settlement in deep foundation pits provided in this application.

[0033] This application provides an embodiment of a method for reducing monitoring errors in uneven settlement of deep foundation pits. For details, please refer to [link to specific documentation]. Figure 1 This includes the following steps:

[0034] Step 1: Measure the three-dimensional coordinate information of each monitoring point within the deep foundation pit area.

[0035] In the actual operation of deep foundation pits, in order to monitor the uneven settlement of the deep foundation pits, multiple representative monitoring points are evenly set up within the deep foundation pit area. At the same time, a stable point on the ground is selected as a reference point. A three-dimensional reference coordinate system is established with the reference point as the origin using a total station. The three-dimensional coordinate information of each monitoring point within the deep foundation pit area is measured in real time using the total station to obtain the three-dimensional coordinate information of each monitoring point at each moment. In this embodiment, the number of monitoring points is 50, the measurement time interval is 1 minute, and the measurement time is 24 hours. The implementer can make adaptive settings according to the actual situation.

[0036] Furthermore, in order to reduce the error in monitoring uneven settlement of deep foundation pits and achieve high-precision monitoring of uneven settlement of deep foundation pits, the values ​​of each dimension in the three-dimensional coordinate information of each monitoring point at all times are arranged in chronological order to obtain the data sequence of each dimension of each monitoring point within the deep foundation pit range. Each monitoring point can obtain three-dimensional data sequences.

[0037] Step 2: Based on the synchronicity characteristics of the random fluctuations in the three-dimensional coordinate information of each monitoring point in each time period, obtain the degree of interference synchronization of each monitoring point in each time period, and obtain the duration of synchronization interference of each monitoring point based on the changing characteristics of the degree of interference synchronization of each monitoring point in all time periods.

[0038] Because the measurement of three-dimensional coordinate information using a total station is easily affected by environmental factors, such as atmospheric refraction and strong winds, it is necessary to measure the degree of interference at each monitoring point within the deep foundation pit area, select monitoring points with higher reliability as settlement points, and conduct uneven settlement monitoring of the deep foundation pit. This reduces the error in monitoring uneven settlement of the deep foundation pit, thereby more accurately assessing the stability and safety of the deep foundation pit.

[0039] Since the data measured by the total station are affected by different external environmental factors at different time periods, the data sequence of each dimension of each monitoring point is uniformly divided into K subsequences. In this embodiment, K is 24, so that the time length of each subsequence is one hour. The implementer can adaptively select the value to obtain the data subsequence of each dimension of each monitoring point in each time period.

[0040] Since external environmental factors can affect the stability of the three-dimensional coordinate data at the monitoring point, for any monitoring point, the data subsequences of each dimension of the monitoring point in each time period are used as STL time series decomposition algorithm (Seasonal-Trend decomposition procedure based on Loess). The residual subsequences of each dimension of the monitoring point in each time period are obtained through the STL time series decomposition algorithm, which are used to reflect the degree of random fluctuation and noise components in the data subsequences of each dimension. The STL time series decomposition algorithm is a well-known technology, and the specific process will not be described in detail.

[0041] Generally, the more complex the random fluctuations and noise components of the data subsequences of each dimension in a certain time period, and the smaller the difference distance between all the residual subsequences of all dimensions in that time period, i.e., the higher the similarity, the more accurately it can reflect the synchronous characteristics of the three-dimensional coordinate data affected by external environmental factors in that time period, and the more likely it is to cause error interference to the subsequent monitoring of uneven settlement of deep foundation pits.

[0042] Therefore, for each monitoring point within the deep foundation pit area, the degree of synchronization affected by interference is calculated for each time period:

[0043] In the formula, Let be the degree of synchronization affected by interference at the i-th monitoring point in the t-th time period. Let be the mean of the information entropy of all dimensional residual subsequences of the i-th monitoring point in the i-th time period. Let be the mean of the difference distances between all dimensional residual subsequences of the i-th monitoring point in the i-th time period. To avoid constants with a denominator of 0, the value is taken within a small data range (0.001, 0.01), which has a negligible impact on the calculation result. In this embodiment, the value is taken as 0.005.

[0044] The calculation of information entropy and difference distance are both well-known techniques. The method for measuring difference distance can be DTW dynamic programming distance, Euclidean distance or Mahalanobis distance. In this embodiment, Mahalanobis distance is used to measure difference distance.

[0045] Understandably, the degree of interference reflects the synchronicity characteristics of three-dimensional coordinate data under the interference of external environmental factors in various time periods. The greater the degree of interference, the easier it is to cause errors in elevation changes at monitoring points, which will affect the accuracy of subsequent monitoring of uneven settlement of deep foundation pits.

[0046] Furthermore, the synchronization degree of each monitoring point within the deep foundation pit area is arranged in chronological order across all time periods to obtain the synchronization interference sequence of each monitoring point. This reflects the change in the synchronization characteristics affected by external environmental factors over time. If the upward trend of the synchronization degree of a certain monitoring point is higher, it indicates that the duration of the three-dimensional coordinate information of that monitoring point being affected by the synchronization interference of external environmental factors is longer, and it is less suitable as a representative point for monitoring uneven settlement in deep foundation pits.

[0047] Therefore, the duration of synchronous interference at each monitoring point within the deep foundation pit area is calculated:

[0048] In the formula, Let be the duration of synchronization interference at the i-th monitoring point. Let be the number of elements in the synchronization interference sequence of the i-th monitoring point, i.e., the number of time periods. It is an exponential function with the natural constant as its base. and These are the j-th and (j-1)-th elements in the synchronization interference sequence of the i-th monitoring point, respectively.

[0049] Among them, the duration of synchronous interference reflects the duration of synchronous interference of the three-dimensional coordinate information at the monitoring point with external environmental factors. The greater the duration of synchronous interference, the longer the duration of synchronous interference of the three-dimensional coordinate information at the monitoring point with external environmental factors, and the more likely it is to affect the accuracy of the settlement calculation at the monitoring location, thus causing monitoring errors of uneven settlement of deep foundation pits.

[0050] Step 3: By analyzing the average level and degree of difference in the synchronization of different monitoring points in the local area, the interference significance coefficient of each monitoring point is obtained. Then, combined with the duration of the synchronization interference, the settlement confidence of each monitoring point is obtained, which is used to divide the monitoring points and extract settlement points.

[0051] Under normal circumstances, the three-dimensional coordinate data measured at monitoring points within a local area are less affected by external environmental factors. However, if the synchronicity of the three-dimensional coordinate data at a certain monitoring point is greatly affected by external environmental factors, and the difference in the synchronicity of the interference between that monitoring point and other monitoring points within the local area is greater, it indicates that the interference characteristics of the three-dimensional coordinate data measured at that monitoring point are more significant, and it is less suitable as a settlement point for monitoring uneven settlement in deep foundation pits.

[0052] Therefore, within the deep foundation pit area, the M monitoring points that are closest to each monitoring point in terms of Euclidean distance are taken as the M nearest neighbor monitoring points of each monitoring point. In this embodiment, the value of M is 4, which represents the nearest local monitoring points in the four directions of the monitoring point. The implementer can adaptively select the value according to the actual situation.

[0053] Based on the above analysis, the disturbance significance coefficient of each monitoring point within the deep foundation pit area was calculated:

[0054] In the formula, Let be the significance coefficient of the interference at the i-th monitoring point. Let be the mean of the synchronization interference sequence at the i-th monitoring point. Let be the mean difference distance between the synchronization interference sequences of the i-th monitoring point and all its nearest neighbor monitoring points. This is the range normalization function.

[0055] Among them, the interference significance coefficient reflects the degree of interference of the three-dimensional coordinate information of each monitoring point within the deep foundation pit with external environmental factors. The larger the interference significance coefficient, the higher the degree of interference of the three-dimensional coordinate information of the monitoring point with external environmental factors, and the less suitable it is as a settlement point for monitoring uneven settlement of deep foundation pits.

[0056] Furthermore, the longer the duration of synchronous interference of the three-dimensional coordinate information of a certain monitoring point within the deep foundation pit is with external environmental factors, and the greater the significance of the interference of the three-dimensional coordinate information of the monitoring point with external environmental factors, the lower the reliability of the three-dimensional data measured by the total station at the monitoring point. In this case, the reliability of the settlement at the monitoring point is smaller, and it is less suitable as a settlement point for monitoring uneven settlement in deep foundation pits.

[0057] Therefore, based on the above analysis, the settlement reliability of each monitoring point within the deep foundation pit area is calculated:

[0058] In the formula, Let represent the settlement confidence level of the i-th monitoring point.

[0059] Settlement reliability reflects the reliability of settlement at each monitoring point within the deep foundation pit area. The lower the settlement reliability, the more severe the interference of external environmental factors on the three-dimensional coordinate information at the monitoring point, and the less suitable it is as a settlement point for monitoring uneven settlement in deep foundation pits. Conversely, the higher the settlement reliability, the less the interference of external environmental factors on the three-dimensional coordinate information at the monitoring point, and the more suitable it is as a settlement point for monitoring uneven settlement in deep foundation pits.

[0060] Therefore, in order to select monitoring points with higher measurement accuracy as settlement points, thereby reducing the error in monitoring uneven settlement of deep foundation pits and more accurately assessing the stability and safety of deep foundation pits, the settlement confidence level of all monitoring points within the deep foundation pit area is used as the input of the Otsu's inter-class variance algorithm. The Otsu's inter-class variance algorithm is used to obtain the segmentation threshold for settlement confidence level. The Otsu's inter-class variance algorithm is a well-known technique, and its specific process will not be elaborated further. Furthermore, monitoring points with settlement confidence levels greater than the segmentation threshold are designated as settlement points. In this embodiment, for ease of understanding and description, the set of all settlement points is referred to as the settlement point set.

[0061] Among them, the three-dimensional coordinate information of the monitoring points within the settlement point set is less affected by external environmental factors, which helps to reduce the error in monitoring uneven settlement of deep foundation pits and improve the accuracy of monitoring uneven settlement of deep foundation pits.

[0062] Step 4: Monitor the uneven settlement of the deep foundation pit based on the differences in the coordinate distribution of each settlement point in the vertical direction.

[0063] According to the above process in this embodiment, a set of settlement points can be extracted. All monitoring points included in the set of settlement points are settlement points. In order to more accurately monitor the uneven settlement of deep foundation pits, since the settlement amount focuses on the change of each settlement point in the vertical direction, the three-dimensional data sequence of each settlement point in the set of settlement points is used to obtain the dimensional data sequence of each settlement point in the set of settlement points in the vertical direction. The first-order difference sequence of the dimensional data sequence in the vertical direction is calculated to reflect the change of each settlement point in the vertical direction at different times. The sum of all elements in the first-order difference sequence is taken as the settlement amount of each settlement point in the set of settlement points.

[0064] Furthermore, the average absolute error of the settlement at all settlement points within the settlement point set is statistically analyzed and normalized to serve as the monitoring result for uneven settlement of the deep foundation pit. In this embodiment, a preset value of 0.6 is set. The smaller the normalization result, the smaller the uneven settlement characteristic of the deep foundation pit, and the higher the stability and safety of the deep foundation pit. In this embodiment, when the normalization result is less than the preset value, uneven settlement has not occurred in the deep foundation pit; otherwise, uneven settlement has occurred in the deep foundation pit. That is, the larger the normalization result, the more severe the uneven settlement of the deep foundation pit, and the lower the stability and safety of the deep foundation pit. In this case, corresponding measures need to be taken in a timely manner to ensure the construction quality and safety of the deep foundation pit.

[0065] It is understood that references to "one embodiment" or "some embodiments" in this specification mean that one or more embodiments of this application include the specific features, structures, or characteristics described in connection with that embodiment. Therefore, the appearance of phrases such as "in one embodiment," "in some embodiments," "in other embodiments," or "in still other embodiments" in different parts of this specification does not necessarily refer to the same embodiment, but rather means "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0066] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous. Moreover, the sequence numbers of the steps in the embodiments do not imply a specific order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments in this specification.

[0067] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for reducing the monitoring error of uneven settlement in deep foundation pits, characterized in that, Includes the following steps: Measure the three-dimensional coordinate information of each monitoring point within the deep foundation pit area; Based on the synchronicity characteristics of the random fluctuations of the three-dimensional coordinate information of each monitoring point in each time period, the degree of interference synchronization of each monitoring point in each time period is obtained, and based on the change characteristics of the degree of interference synchronization of each monitoring point in all time periods, the duration of synchronization interference of each monitoring point is obtained. By analyzing the average level and degree of difference in the synchronization of different monitoring points in a local area, the interference significance coefficient of each monitoring point is obtained. Then, combined with the duration of the synchronization interference, the settlement confidence of each monitoring point is obtained, which is used to divide the monitoring points and extract settlement points. Based on the differences in the coordinate distribution of each settlement point in the vertical direction, the uneven settlement of the deep foundation pit is monitored. The method for obtaining the degree of synchronization of each monitoring point under interference in each time period is further as follows: In the formula, Let be the degree of synchronization affected by interference at the i-th monitoring point in the t-th time period. Let be the mean of the information entropy of all dimensional residual subsequences of the i-th monitoring point in the i-th time period. Let be the mean of the difference distances between all dimensional residual subsequences of the i-th monitoring point in the i-th time period. To avoid constants with a denominator of 0; The method for obtaining the duration of synchronous interference at each monitoring point is further as follows: In the formula, Let be the duration of synchronization interference at the i-th monitoring point. Let be the number of elements in the synchronization interference sequence of the i-th monitoring point, i.e., the number of time periods. It is an exponential function with the natural constant as its base. and These are the j-th and (j-1)-th elements in the synchronization interference sequence of the i-th monitoring point, respectively. The synchronization interference sequence of each monitoring point is formed by arranging the synchronization of each monitoring point in time sequence across all time periods. The method for obtaining the significance coefficient of interference at each monitoring point is further as follows: In the formula, Let be the significance coefficient of the interference at the i-th monitoring point. Here is the range normalization function. Let be the mean of the synchronization interference sequence at the i-th monitoring point. Let be the average difference distance between the i-th monitoring point and the synchronization interference sequences of all its neighboring monitoring points, where the synchronization interference sequence of each monitoring point is formed by arranging the synchronization interference degree of each monitoring point in time sequence across all time periods. The method for obtaining the settlement reliability of each monitoring point is further as follows: In the formula, Let i be the settlement confidence level of the i-th monitoring point. and represent the significance coefficient of interference and the duration of synchronous interference for the i-th monitoring point, respectively.

2. The method for reducing monitoring errors of uneven settlement in deep foundation pits as described in claim 1, characterized in that, The values ​​of each dimension in the three-dimensional coordinate information at all times of each monitoring point are arranged in time sequence, and each monitoring point obtains a three-dimensional data sequence. Each dimension data sequence of each monitoring point is evenly divided into multiple subsequences, which are used as the dimension data subsequences of each monitoring point in each time period.

3. The method for reducing monitoring errors of uneven settlement in deep foundation pits as described in claim 2, characterized in that, The data subsequences of each monitoring point in each dimension for each time period are decomposed into time series to obtain the residual subsequences of each monitoring point in each dimension for each time period.

4. The method for reducing monitoring errors of uneven settlement in deep foundation pits as described in claim 1, characterized in that, The multiple monitoring points that are closest to each monitoring point are all designated as the neighboring monitoring points of each monitoring point.

5. The method for reducing monitoring errors of uneven settlement in deep foundation pits as described in claim 1, characterized in that, The extraction of settlement points further includes: thresholding the settlement confidence of all monitoring points, and taking the monitoring points with settlement confidence greater than the threshold as settlement points.

6. The method for reducing monitoring errors of uneven settlement in deep foundation pits as described in claim 2, characterized in that, The monitoring of uneven settlement in deep foundation pits further includes: Obtain the vertical dimension data sequence of each settlement point and calculate the first-order difference sequence. Take the sum of all elements in the first-order difference sequence as the settlement amount of each settlement point. Calculate the average absolute error of the settlement amount of all settlement points and normalize it. If the normalization result is less than the preset value, there is no uneven settlement in the deep foundation pit; otherwise, uneven settlement occurs in the deep foundation pit.

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