CN113626906A - Underground supporting structure deformation monitoring method based on data mining and control chart - Google Patents
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Abstract
The invention provides an underground supporting structure deformation monitoring method based on data mining and control charts, which comprises the steps of determining that a data mining target is underground supporting structure deformation, setting wall deformation measuring points on an underground continuous wall, and collecting underground supporting structure deformation data to establish a target data set; cleaning data and replacing outliers; calculating the difference value between the cumulative deformation of the supporting structure on the current day and the cumulative deformation on the previous day, and converting the cumulative deformation data set of the supporting structure into a daily deformation data set; summarizing the daily deformation data sets, dividing sections according to working conditions, and respectively calculating statistical parameters of the data sets of the sections and the data sets of the total body; and respectively determining the control limits of the mean-standard deviation control chart and the standard deviation-standard deviation control chart according to the statistical parameters, and sequentially analyzing whether a warning value exists in the control chart of the target data set to obtain the deformation monitoring result of the underground supporting structure. The invention realizes relatively scientific monitoring and early warning by setting a data mining target and applying a control chart method.
Description
Technical Field
The invention relates to the field of subway construction data processing, in particular to an underground supporting structure deformation monitoring method based on data mining and control charts.
Background
The concept of statistical process control is proposed by Walter a Shewhart in 1924 in western electrical laboratories in the united states, and shows that a control chart can be used in the statistical process control process, and the product quality of the production process is stabilized mainly by applying the method of the control chart so as to achieve the purpose of prevention. However, how to analyze the warning in the deformation data of the underground supporting structure has no mature method, which brings difficulty to further prediction and control of engineering risks.
Therefore, there is a need to develop a more practical intelligent underground supporting structure deformation monitoring method.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention provides an underground supporting structure deformation monitoring method based on data mining and control charts, which can analyze whether warning values exist in a target data set or not by setting a data mining target and applying the control charts.
The technical scheme of the invention provides an underground supporting structure deformation monitoring method based on data mining and control charts, which comprises the following steps:
1) determining a data mining target as underground supporting structure deformation, setting a plurality of wall deformation measuring points on an underground continuous wall, and acquiring deformation data of the underground supporting structure to establish a target data set;
2) performing data cleaning on the target data set, and replacing outliers;
3) converting the support structure accumulated deformation data set into a daily deformation data set by calculating the difference value between the accumulated deformation of the support structure on the current day and the accumulated deformation of the support structure on the previous day;
4) summarizing the daily deformation data set, dividing the data set into a plurality of sections according to working conditions, and respectively calculating the statistical parameters of the data set of each section and the total data set;
5) and respectively determining the control limits of the mean-standard deviation control chart and the standard deviation-standard deviation control chart according to the statistical parameters of the data sets of the sections and the total data set, and sequentially analyzing whether the warning values exist in the control charts of the target data set to obtain the deformation monitoring result of the underground supporting structure.
And moreover, the method for acquiring the deformation data of the underground supporting structure is realized by setting a wall deformation measuring point at the position of the underground continuous wall and monitoring the wall deformation data every other preset distance from the top to the bottom of the wall every day.
Furthermore, the target data set is an underground supporting structure deformation data set.
And performing data cleaning according to the target data set, wherein the data cleaning comprises replacing the deviation value by the mean value of two data adjacent to the deviation value.
Also, the sections include a dig segment, a transition segment, and a smooth segment.
And the statistical parameters of the data sets of the sections and the total data set comprise the mean value and the standard deviation of the daily deformation data sets of the supporting structure of the excavation section, the transition section and the stable section, and the standard deviation of the daily deformation data sets of the supporting structure during monitoring.
Further, the control limits of the mean-standard deviation control chart and the standard deviation-standard deviation control chart are determined as follows,
selecting the mean value and the standard deviation of the daily deformation data set of the transition section supporting structure as the parameter mu of the control limit of the control chart by using the mean value-standard deviation control chart1And σ1Respectively obtaining the upper control limit UCL of the mean-standard deviation control chart1＝μ1+3σ1Lower control limit LCL1＝μ1-3σ1The control chart is used as a unified upper limit and a unified lower limit of a mean-standard deviation control chart;
selecting standard deviation of daily deformation data set of transition section supporting structure and standard deviation of daily total daily deformation supporting structure data set as parameter sigma of control limit of control chart2And mu2Separately obtaining the upper control UCL of the standard deviation-standard deviation control chart2＝μ2+3σ2Lower part ofControl limit LCL2＝μ2-3σ2。
And when the mean value of daily deformation of the supporting structure in the mean value-standard deviation control chart exceeds the control limit of the control chart, or the standard deviation of daily deformation of the supporting structure in the standard deviation-standard deviation control chart exceeds the control limit of the control chart, the mean value and the standard deviation are regarded as warning values.
The invention analyzes whether the target data set has the warning value or not by setting a data mining target and applying a control chart method on the basis of engineering monitoring. Conventionally, a qualitative method based on engineering experience is difficult to identify the warning values of mass monitoring data of large-scale engineering, the method provided by the invention can carry out quantitative calculation on warning threshold values based on the mean value and standard deviation of the mass data, realizes relatively scientific monitoring and early warning, and has good applicability to early warning of mass monitoring data in modern engineering construction.
The scheme of the invention is simple and convenient to implement, has strong practicability, solves the problems of low practicability and inconvenient practical application of the related technology, can improve the user experience, and has important market value.
Drawings
Fig. 1 is a flow chart of a method for monitoring deformation of an underground supporting structure based on data mining and control charts in the embodiment of the invention.
FIG. 2 is a graph showing a mean-standard deviation control of a measured point CX06 location support daily deformation data set according to a specific application example of the method of the embodiment of the present invention.
FIG. 3 is a graph showing a mean-standard deviation control of a measured point CX32 location support daily deformation data set according to an example of specific application of the method of the embodiment of the present invention.
FIG. 4 is a standard deviation-standard deviation control chart of a measuring point CX06 location support structure daily deformation data set according to a specific application example of the method of the embodiment of the invention.
FIG. 5 is a standard deviation-standard deviation control chart of a measuring point CX32 location support structure daily deformation data set according to a specific application example of the method of the embodiment of the invention.
Detailed Description
The technical solution of the present invention is specifically described below with reference to the accompanying drawings and examples.
Referring to fig. 1, the method for monitoring deformation of an underground supporting structure based on data mining and control chart of the embodiment of the invention comprises the following steps:
1) determining a data mining target and establishing a target data set;
the data mining target is deformation of an underground supporting structure, the target data set is horizontal displacement of the underground continuous wall caused by construction influence in the foundation pit construction process of the underground supporting structure deformation data set, and the underground supporting structure deformation data set is a data set of horizontal deformation of the underground continuous wall. Therefore, preferably, wall deformation measuring points are mainly set at the positions of the underground continuous walls, and wall deformation data are monitored once every 0.5m every day from the top to the bottom of the wall.
In the embodiment, in the process of foundation pit construction, the underground continuous wall is subjected to horizontal displacement caused by construction influence, and the deformation data set of the underground supporting structure is a data set consisting of 83201 horizontal deformation data obtained by monitoring 13 measuring points of the underground continuous wall. Wall deformation measuring points are mainly set at the positions of the underground continuous walls, and wall deformation data are monitored once every 0.5m every day from the top to the bottom of the wall.
2) Performing data cleaning on the target data set, and replacing a more obvious outlier;
in the embodiment, for a more obvious outlier, the average of two data adjacent to the outlier is used instead of the outlier.
3) Converting the support structure accumulated deformation data set into a daily deformation data set (the difference value of the accumulated deformation of the support structure on the day and the accumulated deformation on the previous day is the daily deformation of the support structure on the day);
4) summarizing the daily deformation data set, dividing the data set into a plurality of sections according to working conditions, and respectively calculating statistical parameters of the data set of each section and the total data set (the excavation section comprises excavation of each layer of soil body and construction of supports, the transition section comprises a foundation pit bottom laying cushion layer and a pouring bottom plate, and the stable section comprises the foundation pit supports which are removed till the monitoring is finished);
in the embodiment, the plurality of sections comprise an excavation section, a transition section and a stable section, wherein the date of the excavation section is from the first layer of soil body excavation and first support application of the foundation pit to the fifth layer of soil body excavation and fifth support application of the foundation pit. And combining the site construction working condition and the daily deformation trend of the wall body, and finishing the period of the transition section from the pouring of the cushion layer at the bottom of the foundation pit to the 8 th day before the removal of the fourth and fifth supports of the foundation pit. And the date of the stable section of the wall deformation is approximately from 8 days after the fourth and the fifth supports of the foundation pit are dismantled to the end of monitoring. ).
Further, the statistical parameters of the data sets of the sections and the data sets of the whole comprise the mean value and the standard deviation of the daily deformation data sets of the supporting structure of the excavation section, the transition section and the stable section and the standard deviation of the daily deformation data sets of the supporting structure during monitoring.
(the calculation formula of the three parameters is:
mean value:
mean of absolute values:
standard deviation:
wherein, Xi(i ═ 1,2, … …, n) denotes the selected data value, | XiI (i ═ 1,2, … …, n) denotes the absolute values of the extracted data values, and μ, v, and σ denote the mean, mean of the absolute values, and standard deviation of the extracted data values. )
5) Respectively determining the control limits of a mean-standard deviation control chart and a standard deviation-standard deviation control chart according to the statistical parameters of the data sets of the sections and the total data set, sequentially analyzing whether a warning value exists in the control chart of the target data set, and outputting an automatic warning signal according to the analysis result; in particular, the automatic alarm signal can be set to be sent to the communication equipment of the relevant responsible user.
In an embodiment, the control limits of the mean-standard deviation control map and the standard deviation-standard deviation control map comprise:
selecting the mean value and the standard deviation of the daily deformation data set of the transition section supporting structure as the parameter mu of the control limit of the control chart by using the mean value-standard deviation control chart1And σ1Respectively obtaining the upper control limit UCL of the mean-standard deviation control chart1＝μ1+3σ1Lower control limit LCL1＝μ1-3σ1And the upper limit and the lower limit are unified as a mean-standard deviation control chart (a control center line in the mean-standard deviation control chart is generally the mean value of sample data, and the standard deviation which is 3 times the upper limit and the lower limit of the control chart is about 3 times of the control center line. Selecting standard deviation of daily deformation data set of transition section supporting structure and standard deviation of daily total daily deformation supporting structure data set as parameter sigma of control limit of control chart2And mu2Respectively obtaining the upper control limit UCL of the standard deviation-standard deviation control chart2＝μ2+3σ2Lower control limit LCL2＝μ2-3σ2. (the standard deviation of the standard deviation-standard deviation control chart is usually the standard deviation of sample data, the standard deviation of the daily total daily deformation support structure data set which is 3 times the distance from the control center line is used as the upper limit and the lower limit of the control chart, if a point in the standard deviation-standard deviation control chart falls outside the control limit range of the UCL and the LCL, the point is indicated to have a warning value.)
The method is more suitable for analyzing warning values in the deformation data of the underground supporting structure.
Example mean-standard deviation control of the parameter μ of the map control limits1And σ1Parameters σ for the control limits of the map, standard deviation-standard deviation, of-0.02 and 0.60, respectively2And mu20.60 and 0.30, respectively.
In an embodiment, presenting the alert value in the control chart includes:
the average value of daily deformation of the supporting structure in the average-standard deviation control chart exceeds the control limit of the control chart, and the standard deviation of daily deformation of the supporting structure in the standard deviation-standard deviation control chart exceeds the control limit of the control chart, which are all regarded as warning values.
The method analyzes whether the warning value exists in the target data set or not by setting a data mining target and applying a control chart method.
To facilitate understanding of the solution of the embodiments of the present invention and the effects thereof, a specific application example is given below. It will be understood by those skilled in the art that this example is merely for the purpose of facilitating an understanding of the present invention and that any specific details thereof are not intended to limit the invention in any way.
FIG. 2 is a graph showing a mean-standard deviation control of a measured point CX06 location support daily deformation data set according to a specific application example of the method of the embodiment of the present invention.
In the mean-standard deviation control chart of the measuring point CX06 shown in FIG. 2, the daily deformation mean value of the supporting structure monitored daily has a small fluctuation amplitude, and the mean value fluctuation is within the range specified by the upper and lower control limits, and no warning value appears.
FIG. 3 is a graph showing a mean-standard deviation control of a measured point CX32 location support daily deformation data set according to an example of specific application of the method of the embodiment of the present invention.
As shown in fig. 3, point CX32 is identified in the control map by 3 warning values, which appear on days 60, 116 and 130, respectively, from the start of the monitoring. On day 60, the average daily deformation of the support structure was-2.04 mm, which exceeded the control limit of 0.22mm under the control chart. On day 130, the average daily deformation of the supporting structure is 1.91mm, which exceeds the upper control limit of the control chart by 0.13 mm. However, no special conditions occurred on the construction site at days 60 and 130. On day 116, the average daily deformation of the support structure was 2.07mm, 0.29mm above the control limit on the control chart. Since the deformation of the supporting structure is not monitored on the 115 th day and the daily deformation of the supporting structure monitored on the 116 th day is actually daily deformation of two consecutive days, the daily deformation of the supporting structure on the day is large, and the average value far exceeds the control range of the control chart.
FIG. 4 is a standard deviation-standard deviation control chart of a measuring point CX06 location support structure daily deformation data set according to a specific application example of the method of the embodiment of the invention.
As shown in FIG. 4, the standard deviation-standard deviation control chart of the measuring point CX06 on the west side of the foundation pit has small daily deformation fluctuation of the supporting structure, and in the control chart, the daily deformation fluctuation amplitude of the supporting structure monitored every day is small, and the standard deviation fluctuation is within the range specified by the control limit, so that no warning value appears.
FIG. 5 is a standard deviation-standard deviation control chart of a measuring point CX32 location support structure daily deformation data set according to a specific application example of the method of the embodiment of the invention.
As shown in fig. 5, the measurement point CX32 is identified by 3 warning values in the standard deviation-standard deviation control chart, which are respectively present on the 109 th, 111 th and 112 th days from the start of monitoring. On days 109, 111, and 112, the standard deviations of daily deformation of the supporting structures were 2.09mm, 1.79mm, and 2.05mm, respectively, exceeding the control limits of the control chart by 0.59mm, 0.29mm, and 0.55 mm. On day 110, the standard deviation of daily deformation of the supporting structure is also large, and the standard deviation is 1.50mm, but the control limit of the control chart is not exceeded. The daily deformation of the supporting structure has larger standard deviation fluctuation in 4 consecutive days, but no special working condition is generated on the construction site in the period.
In summary, the invention calculates the control limit of the control chart by setting the data mining target and applying the method of the control chart, and analyzes whether the warning value exists in the target data set. The upper and lower control limits of the mean-standard deviation control chart are respectively 1.78mm and-1.82 mm, the upper and lower control limits of the standard deviation-standard deviation control chart are respectively 1.50mm and-0.30 mm, and if the target data in the control chart exceeds the control limits, the target data exceeding the control limits can be judged as warning values.
For ease of reference, the effects are now provided as follows:
the mean-standard deviation control chart and the standard deviation-standard deviation control chart are used for analyzing the 13 measuring points, and the number of the alarm values recognized by each section is shown in the table.
In specific implementation, a person skilled in the art can implement the automatic operation process by using a computer software technology, and a system device for implementing the method, such as a computer-readable storage medium storing a corresponding computer program according to the technical solution of the present invention and a computer device including a corresponding computer program for operating the computer program, should also be within the scope of the present invention.
In some possible embodiments, there is provided an underground supporting structure deformation monitoring system based on data mining and control charts, comprising the following modules,
the system comprises a first module, a second module and a third module, wherein the first module is used for determining that a data mining target is underground supporting structure deformation and acquiring underground supporting structure deformation data to establish a target data set;
a second module, configured to perform data cleaning on the target data set, and replace outliers;
the third module is used for converting the support structure accumulated deformation data set into a daily deformation data set by calculating the difference value between the accumulated deformation of the support structure on the current day and the accumulated deformation of the support structure on the previous day;
the fourth module is used for summarizing the daily deformation data set, dividing the data set into a plurality of sections according to working conditions, and respectively calculating the statistical parameters of the data sets of the sections and the total data set;
and the fifth module is used for respectively determining the control limits of the mean-standard deviation control chart and the standard deviation-standard deviation control chart according to the statistical parameters of the data sets of the sections and the total data sets, and sequentially analyzing whether the warning values exist in the control charts of the target data sets to obtain the deformation monitoring result of the underground supporting structure.
In some possible embodiments, the underground support structure deformation monitoring system based on the data mining and control graph comprises a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the stored instructions in the memory to execute the underground support structure deformation monitoring method based on the data mining and control graph.
In some possible embodiments, an underground supporting structure deformation monitoring system based on data mining and control graph is provided, which includes a readable storage medium, and a computer program is stored on the readable storage medium, and when the computer program is executed, the underground supporting structure deformation monitoring system based on data mining and control graph realizes the underground supporting structure deformation monitoring method based on data mining and control graph.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (8)
1. A method for monitoring deformation of an underground supporting structure based on data mining and control charts is characterized by comprising the following steps:
1) determining a data mining target as underground supporting structure deformation, setting a plurality of wall deformation measuring points on an underground continuous wall, and acquiring deformation data of the underground supporting structure to establish a target data set;
2) performing data cleaning on the target data set, and replacing outliers;
3) converting the support structure accumulated deformation data set into a daily deformation data set by calculating the difference value between the accumulated deformation of the support structure on the current day and the accumulated deformation of the support structure on the previous day;
4) summarizing the daily deformation data set, dividing the data set into a plurality of sections according to working conditions, and respectively calculating the statistical parameters of the data set of each section and the total data set;
5) and respectively determining the control limits of the mean-standard deviation control chart and the standard deviation-standard deviation control chart according to the statistical parameters of the data sets of the sections and the total data set, and sequentially analyzing whether the warning values exist in the control charts of the target data set to obtain the deformation monitoring result of the underground supporting structure.
2. The underground supporting structure deformation monitoring method based on data mining and control chart as claimed in claim 1, wherein: the method for acquiring the deformation data of the underground supporting structure comprises the steps of setting wall deformation measuring points at the positions of the underground continuous walls, and monitoring the wall deformation data every other preset distance every day from the top to the bottom of the wall.
3. The underground supporting structure deformation monitoring method based on data mining and control chart as claimed in claim 2, wherein: the target data set is an underground supporting structure deformation data set.
4. A method for monitoring deformation of underground supporting structure based on data mining and control chart according to claim 1,2 or 3, characterized by: and performing data cleaning according to the target data set, wherein the data cleaning comprises replacing the outlier by the mean value of two data adjacent to the outlier.
5. A method for monitoring deformation of underground supporting structure based on data mining and control chart according to claim 1,2 or 3, characterized by: the sections include excavation sections, transition sections, and calming sections.
6. A method for monitoring deformation of underground supporting structure based on data mining and control chart according to claim 1,2 or 3, characterized by: the statistical parameters of the data sets of the sections and the total data set comprise the mean value and the standard deviation of the daily deformation data sets of the supporting structure of the excavation section, the transition section and the stable section and the standard deviation of the daily deformation data sets of the supporting structure during monitoring.
7. A method for monitoring deformation of underground supporting structures based on data mining and control charts according to claim 1 or 2 or 3, characterized in that: the control limits of the mean-standard deviation control map and the standard deviation-standard deviation control map are determined as follows,
selecting the mean value and the standard deviation of the daily deformation data set of the transition section supporting structure as the parameter mu of the control limit of the control chart by using the mean value-standard deviation control chart1And σ1Respectively obtaining the upper control limit UCL of the mean-standard deviation control chart1＝μ1+3σ1Lower control limit LCL1＝μ1-3σ1The control chart is used as a unified upper limit and a unified lower limit of a mean-standard deviation control chart;
selecting standard deviation of daily deformation data set of transition section supporting structure and standard deviation of daily total daily deformation supporting structure data set as parameter sigma of control limit of control chart2And mu2Separately obtaining the upper control UCL of the standard deviation-standard deviation control chart2＝μ2+3σ2Lower control limit LCL2＝μ2-3σ2。
8. The method of monitoring deformation of an underground supporting structure based on data mining and control charts of claim 7, wherein: and when the mean value of daily deformation of the supporting structure in the mean value-standard deviation control chart exceeds the control limit of the control chart, or the standard deviation of daily deformation of the supporting structure in the standard deviation-standard deviation control chart exceeds the control limit of the control chart, the mean value and the standard deviation are taken as warning values.
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