CN-121994190-A - Construction settlement monitoring method and device, equipment and storage medium

CN121994190ACN 121994190 ACN121994190 ACN 121994190ACN-121994190-A

Abstract

The application provides a construction settlement monitoring method, a device, equipment and a storage medium, which belong to the field of tunnel construction monitoring, wherein the method comprises the steps of acquiring plane settlement data and construction activity data carrying a time stamp; dividing a monitoring grid, marking space coordinates, matching two types of data to generate a construction settlement data set, identifying settlement change rate abnormal sections and differential settlement zones, extracting relevant time sequence characteristics and obtaining association coefficients of construction behaviors and settlement anomalies, calculating influence weights based on the association coefficients, and determining the construction behaviors causing the settlement anomalies. The construction settlement monitoring method, the construction settlement monitoring device, the construction settlement monitoring equipment and the storage medium can reduce the occurrence probability of construction settlement accidents.

Inventors

CAI XUBIN
YAN ZHANYOU
ZHAO CUNBAO
Xun Tengfei
ZHOU LIXIN
WANG RUNZE
Yuan Kehui
Yao Yanzheng
LI QINGCHUN
WEI YUQI
XU LIXIANG

Assignees

中交一公局集团有限公司
中交中南工程局有限公司
石家庄铁道大学

Dates

Publication Date: 20260508
Application Date: 20260410

Claims (10)

1. A construction settlement monitoring method, comprising: The method comprises the steps of obtaining planar sedimentation data and construction activity data of a construction tunnel region, wherein the planar sedimentation data and the construction activity data carry time stamps, the planar sedimentation data are data representing overall sedimentation distribution of the construction tunnel region and a peripheral preset region, and the construction activity data are data reflecting construction states and behavior parameters in the subway construction process; dividing a construction tunnel area into a plurality of monitoring grids, and labeling corresponding space coordinates for each monitoring grid; matching the construction activity data and the planar sedimentation data with the space coordinates of the corresponding monitoring grids to generate a construction sedimentation data set; Based on the construction settlement data set, identifying a continuous area corresponding to the monitoring grids with the settlement change rate exceeding a first preset threshold value as a settlement change rate abnormal section, and based on the settlement difference value between each monitoring grid and the adjacent monitoring grids, carrying out cluster analysis on all the monitoring grids, and identifying the continuous area with the settlement difference value exceeding a second preset threshold value as a differential settlement zone; Extracting the settlement time sequence characteristics and construction procedure time sequence characteristics associated with the settlement change rate abnormal section and the differential settlement zone, and obtaining association coefficients between each construction behavior and settlement abnormality based on the settlement time sequence characteristics and the construction procedure time sequence characteristics; And obtaining the influence weight of each construction behavior on differential settlement based on the correlation coefficient, and determining the construction behavior causing settlement abnormality based on the influence weight.
2. The construction settlement monitoring method as set forth in claim 1, wherein the identifying, based on the construction settlement data set, a continuous area corresponding to a monitoring grid whose settlement change rate exceeds a first preset threshold value as a settlement change rate abnormal section comprises: Calculating the sedimentation change rate of each monitoring grid on a time sequence based on the construction sedimentation data set, and generating a sedimentation change rate time sequence of each monitoring grid; In the sedimentation change rate time sequence, identifying a time sequence interval in which the sedimentation change rate continuously exceeds the first preset threshold value in a preset acquisition period; And carrying out space aggregation on the monitoring grids corresponding to the time sequence interval to obtain an abnormal section of the sedimentation change rate.
3. The construction settlement monitoring method as set forth in claim 1, wherein the performing cluster analysis on all the monitoring grids based on the settlement difference between each monitoring grid and the adjacent monitoring grids, identifying a continuous region where the settlement difference exceeds a second preset threshold as a differential settlement zone, comprises: Calculating the sedimentation difference value between each monitoring grid and all adjacent monitoring grids based on the construction sedimentation data set to obtain a sedimentation difference value set between each monitoring grid and all adjacent monitoring grids; Taking the statistical characteristics of the sedimentation difference value set corresponding to each monitoring grid as a clustering characteristic vector for representing the local uneven sedimentation degree of the monitoring grid; Performing cluster analysis on each cluster feature vector, and dividing the plurality of monitoring grids into a plurality of clusters; And screening out clusters, wherein the cluster feature vector average value exceeds the second preset threshold value, the clusters of the continuous surface are formed in space by the included monitoring grids, and the areas corresponding to the clusters are used as differential sedimentation zones.
4. The construction settlement monitoring method as set forth in claim 1, wherein the obtaining of the correlation coefficient between each construction behavior and settlement abnormality based on the settlement timing characteristic and the construction process timing characteristic comprises: Aligning and combining the sedimentation time sequence characteristics and the corresponding construction procedure time sequence characteristics according to time steps to obtain a combined time sequence characteristic sequence; Based on the combined time sequence feature sequence, the combined time sequence feature sequence is subjected to coding processing through a time sequence association model to obtain a depth association feature of construction behavior and sedimentation abnormality in a time dimension, wherein the time sequence association model is obtained by training based on a corresponding relation between a historical sedimentation time sequence feature and a historical construction procedure time sequence feature; Performing linear transformation on the depth correlation feature to map the depth correlation feature into a one-dimensional original correlation value; Nonlinear transformation is carried out on the one-dimensional original association value through a first formula so as to map the one-dimensional original association value into association coefficients between each construction behavior and sedimentation abnormality; wherein, the first formula is: ; Wherein, the And (3) representing the association coefficient between the ith construction behavior and the sedimentation anomaly, and Y representing the one-dimensional original association value.
5. The construction settlement monitoring method as set forth in claim 1, wherein the obtaining the influence weight of each construction behavior on the differential settlement based on the correlation coefficient comprises: carrying out importance analysis on the association coefficient corresponding to each construction behavior to obtain initial influence weight of each construction behavior; Acquiring time sequence change characteristics of construction activity data corresponding to each construction behavior in a history period associated with the differential settlement zone; And correcting the initial influence weight of each construction behavior based on the time sequence change characteristics to obtain the influence weight of each construction behavior on differential settlement.
6. The construction settlement monitoring method as set forth in claim 5, wherein said correcting the initial influence weight of each construction action based on the time series variation characteristic to obtain the influence weight of each construction action on differential settlement comprises: determining whether the construction parameters of each construction behavior have abnormal changes in the historical period according to the time sequence change characteristics, and acquiring the starting time and the change amplitude of the abnormal changes; According to the precedence relation between the starting time and the identified time point of the differential settlement zone and the deviation degree between the variation amplitude and the corresponding normal construction threshold range, dynamically adjusting the initial influence weight of each construction behavior to obtain the influence weight of each construction behavior on differential settlement; The dynamic adjustment comprises the steps of adjusting the initial influence weight to be high for construction behaviors with occurrence time earlier than the settlement abnormality identification time and change amplitude exceeding the normal construction threshold range by a preset multiple, and adjusting the initial influence weight to be low for construction behaviors with occurrence time later than the settlement abnormality identification time or change amplitude not exceeding the normal construction threshold range.
7. The construction settlement monitoring method as set forth in claim 1, wherein the determining a construction behavior causing settlement abnormality based on the influence weight comprises: sequencing all the construction behaviors according to the influence weight, and selecting the construction behaviors with the preset number ranked at the front as candidate construction behaviors; For each candidate construction behavior, acquiring time sequence change characteristics of corresponding construction activity data in a preset history period before the identified time point of the differential settlement zone, and determining abnormal starting time and abnormal change amplitude of the candidate construction behavior according to the time sequence change characteristics; If the abnormal starting time is earlier than the identified time point of the differential settlement zone, judging that a first time condition is met; And determining the candidate construction behaviors which simultaneously meet the first time condition and the second amplitude condition as the construction behaviors which lead to the settlement abnormality.
8. A construction settlement monitoring device, comprising: The system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring planar sedimentation data and construction activity data of a construction tunnel region, and the planar sedimentation data and the construction activity data both carry time stamps; The data set generation module is used for dividing a construction tunnel area into a plurality of monitoring grids and labeling corresponding space coordinates for each monitoring grid; The settlement analysis module is used for identifying continuous areas corresponding to the monitoring grids with the settlement change rate exceeding a first preset threshold value based on the construction settlement data set to be used as settlement change rate abnormal sections, carrying out cluster analysis on all the monitoring grids based on the settlement difference value between each monitoring grid and the adjacent monitoring grids, and identifying the continuous areas with the settlement difference value exceeding a second preset threshold value to be used as differential settlement zones; The association calculation module is used for extracting the sedimentation time sequence characteristics and the construction procedure time sequence characteristics associated with the sedimentation change rate abnormal section and the differential sedimentation zone, and obtaining association coefficients between each construction behavior and sedimentation abnormality based on the sedimentation time sequence characteristics and the construction procedure time sequence characteristics; and the settlement monitoring module is used for obtaining the influence weight of each construction behavior on differential settlement based on the correlation coefficient, and determining the construction behavior causing settlement abnormality based on the influence weight.
9. An electronic device comprising a memory and a processor, the memory having a computer program stored therein, the processor, when running the computer program, performing the construction settlement monitoring method of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein a computer program which, when executed by a processor, implements the construction settlement monitoring method according to any one of claims 1 to 7.

Description

Construction settlement monitoring method and device, equipment and storage medium Technical Field The application belongs to the technical field of tunnel construction monitoring, and particularly relates to a construction settlement monitoring method, a device, equipment and a storage medium. Background In the subway construction process, construction settlement monitoring is a key link for preventing and controlling construction safety risks, and the key requirement is to accurately position settlement abnormality inducement through associating construction behaviors with settlement abnormality, so that targeted management and control are realized. At present, in the existing construction settlement monitoring technology, quantitative analysis support is lacking in association between construction behaviors and settlement anomalies, qualitative judgment is mainly carried out by relying on manual experience, the influence degree of each construction behavior on the settlement anomalies cannot be accurately defined, and then the dominant construction behavior causing the settlement anomalies is difficult to lock. The judgment mode is easy to deviate, so that settlement abnormality treatment measures lack pertinence, the effectiveness of monitoring and controlling is insufficient, further development of settlement abnormality cannot be restrained in time, and the occurrence risk of construction settlement accidents is greatly increased, so that the problem needs to be solved so as to reduce the occurrence probability of the construction settlement accidents. Disclosure of Invention The embodiment of the application aims to provide a construction settlement monitoring method, a device, equipment and a storage medium, which can reduce the occurrence probability of construction settlement accidents. In order to achieve the above object, the technical solution provided by the embodiments of the present application is as follows: in a first aspect, a construction settlement monitoring method is provided, including: the method comprises the steps of obtaining planar sedimentation data and construction activity data of a construction tunnel region, wherein the planar sedimentation data and the construction activity data carry time stamps, the planar sedimentation data are data representing overall sedimentation distribution of the construction tunnel region and a peripheral preset region, and the construction activity data are data reflecting construction states and behavior parameters in the subway construction process; Dividing a construction tunnel area into a plurality of monitoring grids, and labeling corresponding space coordinates for each monitoring grid; matching the construction activity data and the planar sedimentation data with the space coordinates of the corresponding monitoring grids to generate a construction sedimentation data set; based on construction sedimentation data set, identifying continuous areas corresponding to the monitoring grids with sedimentation change rate exceeding a first preset threshold as abnormal sections of sedimentation change rate, and based on sedimentation difference values between each monitoring grid and adjacent monitoring grids, carrying out cluster analysis on all monitoring grids, and identifying continuous areas with sedimentation difference values exceeding a second preset threshold as differential sedimentation zones; Extracting the settlement time sequence characteristics and construction procedure time sequence characteristics associated with the settlement change rate abnormal section and the differential settlement zone, and obtaining association coefficients between each construction behavior and settlement abnormality based on the settlement time sequence characteristics and the construction procedure time sequence characteristics; And obtaining the influence weight of each construction behavior on differential settlement based on the correlation coefficient, and determining the construction behavior causing settlement abnormality based on the influence weight. In a second aspect, there is provided a construction settlement monitoring device comprising: The system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring planar sedimentation data and construction activity data of a construction tunnel region, wherein the planar sedimentation data and the construction activity data carry time stamps, the planar sedimentation data is data representing the integral sedimentation distribution of the construction tunnel region and a peripheral preset region, and the construction activity data is data reflecting construction states and behavior parameters in the subway construction process; The data set generation module is used for dividing the construction tunnel area into a plurality of monitoring grids and labeling corresponding space coordinates for each monitoring