CN111768125A - Foundation pit deformation safety assessment method and system - Google Patents
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Abstract
The invention discloses a method and a system for evaluating the deformation safety of a foundation pit, and belongs to the technical field of foundation pit engineering. The invention utilizes the grey correlation theory to analyze the correlation between the deformation monitoring data of the foundation pit supporting structure and the sedimentation spatial-temporal evolution rule of the soil body on the periphery of the foundation pit supporting structure, and utilizes the entropy method to carry out objective weighted coupling on the correlation, thereby obtaining the deformation safety state of the foundation pit. The method can objectively and effectively evaluate the safety of the foundation pit, avoids misleading influence caused by human factors, and provides guidance for safety protection of the foundation pit.
Description
Technical Field
The invention relates to the technical field of foundation pit engineering, in particular to a method and a system for evaluating the deformation safety of a foundation pit.
Background
The underground space operation is carried out under increasingly complex environments, the foundation pit deformation safety is very important, and a reasonable foundation pit deformation safety evaluation method is explored to become a hotspot in the field of foundation pit engineering. The foundation pit deformation safety assessment plays a significant role in engineering safety. In the process of excavation of the foundation pit, the control link of soil deformation is more important. Due to stress release and other reasons, the soil body deforms, so that the deformation of the foundation pit is influenced, and the stability of the foundation pit and the surrounding soil body are influenced to different degrees. When the deformation of the foundation pit reaches a certain degree, the instability of the foundation pit can occur, namely, the engineering accident of the foundation pit.
The foundation pit safety mainly depends on retaining structures such as foundation pit supports, when the foundation pit support structures incline, soil bodies in a certain peripheral area range are influenced, so that the soil bodies around the foundation pit are influenced to be settled, the time-space law of deformation of the foundation pit support structures and the settlement time-space law of the peripheral soil bodies influenced by the deformation of the foundation pit support structures are similar and even consistent, and when the time-space evolution laws of the foundation pit support structures and the settlement time-space laws of the peripheral soil bodies are closer, the foundation pit is more dangerous.
Therefore, the scientific safety assessment method can make correct evaluation on the safety condition of the foundation pit, can give early warning on the possible danger of the foundation pit in time and provides necessary conditions for the safety protection of the foundation pit.
However, most existing foundation pit deformation safety evaluation methods have too many artificial influence factors, and cannot perform objective and reasonable foundation pit deformation safety evaluation, so that the evaluation result cannot accurately reflect the safety state of the foundation pit at present.
Disclosure of Invention
In order to overcome the defects of the prior art, a foundation pit deformation safety assessment method and a foundation pit deformation safety assessment system are provided, and are applied to foundation pit engineering.
In order to achieve the purpose, the invention provides the following technical scheme: a foundation pit deformation safety assessment method comprises the following steps:
s101: arranging a plurality of equidistant settlement measuring points at the top of the foundation pit support along the top of the foundation pit support;
s102: taking the settlement measuring point at the top of the foundation pit support in the step S101 as an initial point, and arranging a plurality of soil settlement observation lines which are equidistant and parallel to each other outside the foundation pit in a direction perpendicular to the direction of the foundation pit support, wherein for convenience of statistics, the names of the observation lines are a, b, c, d and e … … respectively;
s103: a plurality of soil settlement observation cross sections which are equidistant are arranged outwards along the observation line in the step S102, the cross sections are perpendicular to the observation line and parallel to the foundation pit support, the observation line is named as a No. 1 cross section, the second cross section is a No. 2 cross section, and the rest is done in the same way, and m cross sections are counted;
s104: each intersection point of the observation line and the observation section is provided with a soil body settlement measuring point(ii) a For example, the settlement measuring point at the top of the foundation pit support on the observation line a is named as a0The intersection point of the observation line a and the No. 1 observation section is the first measuring point of the observation line and is named as a1Point; the intersection point of the observation line a and the No. 2 observation section is the second measuring point of the observation line and is named as a2The intersection point of the point, the observation line b and the No. 1 section is the first measuring point of the observation line and is named as b1Point, and so on;
s105: and acquiring original settlement data sequences of all observation points within a period of time by using the monitoring sensing module.
And gray correlation calculation, comprising:
s201: classifying the original settlement data sequences in the step S105, defining the original settlement data sequences of the settlement measuring points at the top of the foundation pit support as system behavior characteristic sequences, and defining the original settlement data sequences of each soil settlement measuring point on the observation line corresponding to the original settlement data sequences as evaluation sequences;
s202: obtaining the initial image sequence of each sequence in the step S201;
s203: calculating the absolute value sequence of the difference of the components corresponding to the initial image sequence in the step S202;
s204: solving the maximum value and the minimum value of all the numerical values in the sequence obtained in the step S203;
s205: solving the correlation coefficient of the system behavior characteristic sequence and the evaluation sequence and calculating the gray correlation numerical value of each soil settlement measuring point;
and (3) performing coupled evaluation on the grey relevance and entropy method, wherein the coupled evaluation comprises the following steps:
s301: establishing a gray correlation value matrix by using the gray correlation values in step S205
S302, performing data translation on the grey correlation degree values of the measuring points;
s303: calculating the proportion of the relevance value of each soil settlement measuring point on the same observation line;
s304; calculating an entropy value and a difference coefficient of each observation line;
s305; calculating the weight of each observation line;
s306: and calculating the comprehensive score of each observation section and calculating the average value of the comprehensive scores to obtain the safety evaluation score.
Step S201, defining an original settlement data sequence of settlement measurement points at the top of a foundation pit support as a system behavior feature sequence, and defining an original settlement data sequence of each soil settlement measurement point on an observation line corresponding to the original settlement data sequence as an evaluation sequence, taking an observation line a as an example, including:
the system behavior characteristic sequence is Xa0＝(xa0(1),xa0(2),xa0(3)…xa0(n))，
Wherein n is an observation time; xa0＝(xa0(1),xa0(2),xa0(3)…xa0(n)) represents a data sequence of a settlement measuring point at the top of the foundation pit support in the observation line at the time of 1,2,3 … … n;
evaluation sequence is Xai＝(xai(1),xai(2),xai(3)…xai(n))，
Wherein, i is 1,2,3 … … m, n is observation time, m is observation section number or measurement point number in a observation point circuit; xai＝(xai(1),xai(2),xai(3)…xai(n)) represents a data sequence of the ith soil body settlement measuring point in the observation line a at the time of 1,2 and 3 … … n.
The step S202 of obtaining the initial image sequence of each sequence, taking an observation line a as an example, includes:
a, an initial image sequence calculation method of an initial settlement data sequence of a settlement measuring point at the top of a foundation pit support in an observation line comprises the following steps,
a, the initial image sequence calculation method of the original settlement data sequence of each soil settlement measuring point in the observation line comprises the following steps,
The calculating of the absolute value sequence of the difference between the components corresponding to the initial image sequence in step S203, taking a observation line as an example, includes:
Δai(k)＝|x'a0(k)-x'ai(k) 1, |, where i ═ 1,2,3 … … m; k is 1,2,3 … … n, m is
Number of measured section or measured point in a line, n is the observation time, Deltaai(k) Absolute value of difference between components corresponding to initial images of system behavior characteristic sequence and evaluation sequence
The step S204 of calculating the maximum value and the minimum value of all the values in the sequence obtained in the step S203 includes, for example, taking the a observation line:
In step S205, the calculating of the correlation coefficient between the system behavior feature sequence and the evaluation sequence and the calculating of the correlation of each soil settlement measurement point, taking the observation line a as an example, includes:
wherein i is 1,2,3 … … m; k is 1,2,3 … … n, m is an observation section number or a measurement point number in an observation line, and n is an observation time; gamma ray0iAnd (b) observing the degree of association between each soil body settlement measuring point in the line and the foundation pit support top settlement measuring point.
In the calculation in steps S201 to S205, each observation line is independently calculated without interfering with each other, and the calculation method of each observation line, such as a, b, c, d, e … …, is the same as the above method.
The smaller the grey correlation degree is, the better the grey correlation degree is, the smaller the.
The establishing of the gray correlation data matrix in step S301 includes: defining the gray correlation degrees of soil settlement measuring points in each observation line as gammaai、γbi、γci… …, where i is 1,2,3 … … m, m is observation section number or measurement point number in each observation line, then establishing gray correlation degree data matrix A as
The data translation of the gray correlation degree values of the measuring points in the step S302 includes:
for the observation line a, the data processing method is,
For the b observation line, the data processing method is,
wherein i is 1,2,3 … … m;
X′bidata obtained after data translation is carried out on gray correlation degree values of all soil settlement measuring points on the b observation line
c. The observed line calculations for d, e … …, etc. are the same, and so on.
Step S303, calculating the proportion of the association degree value of each soil settlement measurement point on the same observation line, includes:
for the observation line a, the proportion calculation method of each soil settlement measuring point comprises the following steps,
for the observation line b, the proportion calculation method of each soil settlement measuring point comprises the following steps,
c. the observed line calculations for d, e … …, etc. are the same, and so on.
Step S304, calculating the entropy and the difference coefficient of each observation line, includes:
for the a observation line, its entropy value is
the coefficient of difference is ga＝1-eaWherein, gaThe difference coefficient of the line is observed for a.
b. The observation lines c, d, e … …, etc. are calculated the same, and so on.
Calculating the weight of each observation line in the step S305, including; for the a observation line, the weight is
Wherein, WaThe weight of the observation line a is used, the numerator of the formula is the difference coefficient of the observation line a, and the denominator of the formula is the sum of the difference coefficients of all the lines; b. the observation lines c, d, e … …, etc. are calculated the same, and so on.
Step S306, calculating the score of each observation section and calculating the average value thereof to obtain the safety assessment result, including:
Si＝X'ai·Wa+X'bi·Wb+X'ci·Wc… where i is 1,2,3 … … m, m is the observation section number or the number of the measuring points in each observation line, SiScoring the evaluation of each observation section;
The invention also provides a foundation pit deformation safety evaluation system, which comprises: the monitoring system comprises a data storage module, a monitoring sensing module, a central processing module, a display module and a network sharing module.
Further, the data storage module comprises a grating array signal processor and a high-speed solid state disk, the monitoring sensing module comprises a plurality of grating array sensors, and the grating array sensors are buried on each measuring point according to the steps S101-S104 and are connected with the data storage module.
Furthermore, the grating array sensor measures settlement data of the measuring point once every 30 minutes and transmits the settlement data to the data storage module for storage.
Further, the central processing module is connected with the data storage module, the central processing module extracts settlement data of all the measuring points within a period of time from the data storage module as an original settlement data sequence in the step S105, and establishes a gray correlation analysis and entropy method coupling model according to the steps S201 to S205 and the steps S301 to S306 to perform foundation pit deformation safety evaluation.
Further, the central processing module extracts all latest settlement observation data within 48 hours from the storage device every 60 minutes as the original settlement data sequence described in step S105 to perform foundation pit deformation safety assessment.
Furthermore, the display module is connected with the data storage module, and technicians can visually see fluctuation conditions of the original settlement data uploaded to the data storage module through the display module.
Furthermore, the display module is connected with the central processing module, technicians can visually see the gray correlation degree value of each soil settlement measuring point calculated by the central processing module and the foundation pit deformation safety dynamic evaluation result at different time points through the display module, and the technicians can observe the development trend of the foundation pit safety through the display module.
Furthermore, the network sharing module is connected with the central processing module and the data storage module, and shares the original settlement data and the foundation pit safety evaluation result with other related projects in real time.
Furthermore, when the central processing module extracts the original settlement data sequence of each settlement measuring point, a metabolism method is utilized, new observation data is added into the data sequence along with the time, the data sequence is removed from the original old data, the dimension of each settlement measuring point data sequence is guaranteed to be unchanged, namely, the latest data sequence in a period of time is adopted in each calculation, and the evaluation precision is guaranteed.
Furthermore, new observation data are added, old observation data are removed, original data sequences of all settlement measuring points are changed, the foundation pit deformation safety evaluation score is dynamically changed along with the original data sequences, the foundation pit deformation safety evaluation score is combined with a time axis to draw a dynamic trend line, and the future development trend of the foundation pit safety can be judged.
Furthermore, the safety of the foundation pit mainly depends on retaining structures such as a foundation pit support and the like, when the foundation pit support structure inclines, soil bodies in a certain peripheral area range of the foundation pit support structure are influenced, so that the peripheral soil bodies of the foundation pit are influenced to generate sedimentation, the deformation space-time law of the foundation pit support structure and the sedimentation space-time law of the peripheral soil bodies influenced by the deformation space-time law will have similarity and even consistency, and when the space-time evolution laws of the foundation pit support structure and the deformation space-time law are closer, the foundation pit is more dangerous, namely the gray correlation degree of.
Further, the lower the foundation pit deformation safety evaluation score is, the more dangerous the foundation pit is, the worse the safety is, when a dynamic trend line drawn by combining the foundation pit deformation safety evaluation score and time is lowered, the foundation pit safety is indicated to be lowered, otherwise, the safety is improved.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, the gray correlation analysis method is used for accurately analyzing the similarity of the deformation space-time law of the foundation pit supporting structure and the influenced peripheral soil body sedimentation space-time law, and the analysis result is coupled with the entropy method, so that the foundation pit safety can be objectively and effectively evaluated, misleading influence caused by human factors is avoided, and more powerful guidance is provided for foundation pit safety protection.
Drawings
FIG. 1 is a schematic view of the settlement point arrangement of the present invention;
FIG. 2 is a schematic view of the observation point setting process of the present invention;
FIG. 3 is a security assessment model of the present invention;
FIG. 4 is a schematic diagram of the security assessment system of the present invention.
In the figure: 1. supporting a foundation pit; 2. a soil body settlement observation line; 3. soil body settlement observation section; 4. supporting a top settlement measuring point of a foundation pit; 5. measuring a soil body settlement point; m1, monitoring a sensing module; m2, a data storage module; m3, a display module; m4, network sharing module; m5, central processing module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1-2, the present invention provides a technical solution: a foundation pit deformation safety assessment method, observation measuring point setting principle and sequence, includes:
s101: 7 foundation pit support top settlement measuring points (4) which are equidistant are arranged along the top of the foundation pit support (1);
s102: taking the settlement measuring point (4) at the top of the foundation pit support in the step S101 as an initial point, and setting a plurality of soil settlement observation lines (2) which are equidistant and parallel to each other to the outside of the foundation pit in a direction perpendicular to the foundation pit support (1), wherein for convenience of statistics, the names of the observation lines (2) are a, b, c, d, e, f and g respectively;
s103: a plurality of soil settlement observation cross sections (3) which are equidistant are arranged outwards along the observation line (2) in the step S102, the cross sections are perpendicular to the observation line (2), are parallel to the foundation pit support (1), are named as No. 1 cross sections, the second is No. 2 cross sections, and the like, and 5 cross sections are arranged in total;
s104: each intersection point of the observation line (2) and the observation section (3) is provided with a soil body settlement measuring point (5); for example, a settlement measuring point (4) at the top of the foundation pit support on the observation line (2) is named as a0The intersection point of the observation line (2) and the No. 1 observation section (3) is the first measuring point of the observation line (2) and is named as a1Point; the intersection point of the observation line (2) and the No. 2 observation section (3) is the second measuring point of the observation line (2) and is named as a2The intersection point of the observation line (2) and the No. 1 section is the first measurement point of the observation line (2) and is named as b1Point, and so on;
s105: and acquiring original sedimentation data sequences of all the phase 8 observation moments by using a monitoring sensing module (M1).
The gray correlation calculation, as shown in fig. 3, includes:
s201: classifying the original settlement data sequences in the step S105, defining the original settlement data sequences of the settlement measuring points (4) at the top of the foundation pit support as system behavior characteristic sequences, and defining the original settlement data sequences of each soil settlement measuring point (5) on the observation line (2) corresponding to the original settlement data sequences as evaluation sequences;
s202: obtaining the initial image sequence of each sequence in the step S201;
s203: calculating the absolute value sequence of the difference of the components corresponding to the initial image sequence in the step S202;
s204: solving the maximum value and the minimum value of all the numerical values in the sequence obtained in the step S203;
s205: solving the correlation coefficient of the system behavior characteristic sequence and the evaluation sequence and calculating the gray correlation numerical value of each soil settlement measuring point (5);
the grey relevance and entropy coupled evaluation, as shown in fig. 3, includes:
s301: establishing a gray correlation value matrix by using the gray correlation values in step S205
S302, performing data translation on the grey correlation degree values of the measuring points;
s303: calculating the proportion of the association degree value of each soil body settlement measuring point (5) on the same observation line (2);
s304; calculating an entropy value and a difference coefficient of each observation line (2);
s305; calculating the weight of each observation line (2);
s306: and calculating the comprehensive score of each observation section (3) and calculating the average value of the comprehensive scores to obtain the safety evaluation score.
The present invention provides a calculation example according to the above steps
In step 201, the original settlement data sequence of the settlement measuring point (4) at the top of the foundation pit support is defined as a system behavior characteristic sequence, the original settlement data sequence of each soil settlement measuring point (5) on the observation line (2) corresponding to the original settlement data sequence is defined as an evaluation sequence, taking the observation line a as an example, the original settlement data sequence at the observation time of 8 th stage of the settlement measuring point (4) at the top of the foundation pit support is as follows:
Xa0＝(4.68 5.98 6.67 7.01 7.64 8.31 7.52 6.88)
the original settlement data sequence of the soil settlement measuring point (5) at the observation time of the 8 th period is as follows:
Xa1＝(-6.15 -6.39 -6.57 -6.56 -6.56 -6.7 -6.81 -6.65)
Xa2＝(-5.79 -5.84 -5.74 -6.04 -5.88 -5.76 -5.98 -5.93)
Xa3＝(-6.74 -6.66 -6.56 -6.4 -6.63 -6.47 -6.54 -6.54)
Xa4＝(-5.16 -5.44 -5.53 -5.49 -5.45 -5.45 -5.51 -5.41)
Xa5＝(-2.21 -2.22 -2.41 -2.26 -2.23 -2.52 -2.49 -2.49)
the calculation equation is that,
the result of the calculation is as follows,
X'a0＝(1 1.28 1.43 1.5 1.63 1.78 1.61 1.47)
X'a1＝(1 1.04 1.07 1.07 1.07 1.09 1.11 1.08)
X'a2＝(1 1.01 0.99 1.04 1.02 0.99 1.03 1.02)
X'a3＝(1 0.99 0.97 0.95 0.98 0.96 0.97 0.97)
X'a4＝(1 1.05 1.07 1.06 1.06 1.06 1.07 1.05)
X'a5＝(1 1 1.09 1.02 1.01 1.14 1.13 1.13)
in step S203, the absolute value sequence of the difference between the components corresponding to the initial image sequence is obtained, taking the a observation line as an example, and the calculation equation is:
Δai(k)＝|x'a0(k)-x'ai(k) if the calculation result is as follows
Δa1＝(0,0.24,0.36,0.43,0.57,0.69,0.5,0.39)
Δa2＝(0,0.27,0.43,0.45,0.62,0.78,0.57,0.45)
Δa3＝(0,0.29,0.45,0.55,0.65,0.82,0.64,0.50)
Δa4＝(0,0.22,0.35,0.43,0.58,0.72,0.54,0.42)
Δa5＝(0,0.27,0.33,0.48,0.62,0.64,0.48,0.34)
In step S204, the maximum and minimum values of all the values in the sequence obtained in step S203 are obtained, taking the observation line a as an example, and the calculation equation is:
M＝0.82；m＝0；
in step S205, the correlation coefficient between the system behavior feature sequence and the evaluation sequence is obtained and the correlation of each soil settlement measuring point (5) is calculated, taking the observation line a as an example, the calculation equation is as follows:
then the result of the calculation is gamma01＝0.55；γ02＝0.52，γ03＝0.51，γ04＝0.55，γ05＝0.55
In the calculation in steps S201 to S205, each observation line (2) is independently calculated without interfering with each other, the calculation method of each observation line (2) of a, b, c, d, e, f is the same as the above method, no calculation example is provided here, and the final gray correlation calculation results of each observation line (2) of b, c, d, e, f are listed as shown in table 1.
TABLE 1 Grey correlation value of soil settlement measuring point (5)
The smaller the grey correlation degree is, the better the grey correlation degree is, the smaller the.
Step S301, establishing a gray correlation data matrix, which is shown as follows
The gray correlation degree values of the various measuring points are subjected to data translation in the step S302,
the equation used is that,
the calculation results are shown in Table 2
Table 2 data translation results
Step S303, calculating the proportion of the relevance value of each soil body settlement measuring point (5) on the same observation line (2),
the calculation equation is that,
the calculation results are shown in table 3:
TABLE 3 results of specific gravity calculation
In the step S304, the entropy and the difference coefficient of each observation line (2) are calculated, and the calculation equation is:
wherein i is 1,2,3 … … m, eaB, the entropy value of an observation line (2) is a, k is 1/ln (t), and t is the number of observation sections (3);
the calculation results are shown in Table 4
TABLE 4 entropy value of each observation line (2)
The difference coefficient is calculated asa＝1-eaThe calculation results are shown in table 5.
TABLE 5 Difference coefficient for each observation line (2)
The calculation equation for calculating the weight of each observation line (2) in step S305 is
Wherein, WaThe weight of the observation line (2) is a, the numerator of the formula is the difference coefficient of the observation line (2) a, and the denominator of the formula is the sum of the difference coefficients of all lines; b. the observation lines (2) c, d, e … …, etc. are calculated the same, and so on.
The results of the calculations are shown in table 6,
TABLE 6 weight per observation line (2)
Step S306, calculating the score of each observation section (3) and calculating the average value of the scores to obtain a safety evaluation result, wherein the calculation equation is as follows:
Si＝X'ai·Wa+X'bi·Wb+X'ci·Wc… where i is 1,2,3 … … m, m is the observation section number or the number of the measuring points in each observation line, SiScoring the evaluation of each observation section;
The calculation results are shown in Table 7
TABLE 7 score for each observation section (3)
Description of the drawings: for calculation convenience, the score of each observation section (3) is multiplied by 100
The comprehensive evaluation of the deformation safety of the foundation pit comprises the following steps: 46.97
The results of calculating the gray correlation of the measured points in the latest 8 th period with the lapse of time are shown in Table 8
TABLE 8 Grey correlation value of soil settlement measuring point (5) in latest 8-stage
And continuously repeating the calculation process to obtain the comprehensive evaluation score of the deformation safety of the foundation pit as follows: 35.38 points. The reason for the reduction of the score is that the deformation of the foundation pit support occurs along with the time, and the surrounding soil body is influenced, so that the deformation rule of the surrounding soil body is highly similar to the deformation rule of the foundation pit, and the gray correlation degree of the data measured by the measuring points of the foundation pit support and the foundation pit support is high. Finally, the safety score of the foundation pit is reduced, and the danger of the foundation pit is improved.
The invention also provides a foundation pit deformation safety evaluation system, which comprises: a data storage module (M2), a monitoring sensing module (M1), a central processing module (M5), a display module (M3) and a network sharing module (M4), as shown in fig. 4.
The data storage module (M2) comprises a raster array signal processor and a high-speed solid state disk.
The monitoring sensing module (M1) comprises a plurality of grating array sensors, and the grating array sensors are buried on each measuring point according to the steps S101-S104 and are connected with the data storage module (M2).
The grating array sensor measures settlement data of the measuring point every 30 minutes and transmits the settlement data to the data storage module (M2) for storage.
The central processing module (M5) is connected with the data storage module (M2), the central processing module (M5) extracts settlement data of all measuring points in a period of time from the data storage module (M2) to serve as an original settlement data sequence in the step S105, and a gray correlation analysis and entropy method coupling model is established according to the steps S201-S205 and the steps S301-S306 to perform foundation pit deformation safety assessment.
And the central processing module (M5) extracts all latest settlement observation data within 48 hours from the storage equipment every 60 minutes as the original settlement data sequence in the step S105 to perform foundation pit deformation safety evaluation.
The display module (M3) and the data storage module (M2) are connected with each other, and a technician can visually see the fluctuation condition of the original settlement data uploaded to the data storage module (M2) through the display module (M3).
The display module (M3) and the central processing module (M5) are connected with each other, the display module (M3) can enable technicians to visually see the gray correlation degree value of each soil settlement measuring point (5) obtained through calculation of the central processing module (M5) and the foundation pit deformation safety dynamic evaluation results at different time points, and the technicians can observe the development trend of the foundation pit safety through the display module (M3).
The network sharing module (M4) is connected with the central processing module (M5) and the data storage module (M2) to share the original settlement data and the foundation pit safety evaluation result with other related projects in real time.
When the central processing module (M5) extracts the original settlement data sequence of each settlement measuring point, a metabolism method is utilized, new observation data are added into the data sequence along with the time, the data sequence is removed from the original old data, the dimension of each settlement measuring point data sequence is guaranteed to be unchanged, namely, the latest data sequence in a period of time is adopted in each calculation, and the evaluation precision is guaranteed.
And adding new observation data, removing old observation data, changing the original data sequence of each settlement measuring point, dynamically changing the foundation pit deformation safety evaluation score, and combining the foundation pit deformation safety evaluation score with a time axis to draw a dynamic trend line so as to judge the future development trend of the foundation pit safety.
The lower the foundation pit deformation safety evaluation score is, the more dangerous the foundation pit is, the worse the safety is, when a dynamic trend line drawn by combining the foundation pit deformation safety evaluation score and time is reduced, the foundation pit safety is reduced, otherwise, the safety is improved.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A foundation pit deformation safety assessment method is characterized by comprising the following steps: the method comprises the following steps:
s101: arranging a plurality of equidistant settlement measuring points at the top of the foundation pit support along the top of the foundation pit support;
s102: taking the settlement measuring point at the top of the foundation pit support in the step S101 as an initial point, and arranging a plurality of soil settlement observation lines which are equidistant and parallel to each other outside the foundation pit in a direction perpendicular to the direction of the foundation pit support, wherein for convenience of statistics, the names of the observation lines are a, b, c, d and e … … respectively;
s103: a plurality of soil settlement observation cross sections which are equidistant are arranged outwards along the observation line in the step S102, the cross sections are perpendicular to the observation line and parallel to the foundation pit support, the observation line is named as a No. 1 cross section, the second cross section is a No. 2 cross section, and the rest is done in the same way, and m cross sections are counted;
s104: each intersection point of the observation line and the observation section is provided with a soil body settlement measuring point; for example, the settlement measuring point at the top of the foundation pit support on the observation line a is named as a0The intersection point of the observation line a and the No. 1 observation section is the first measuring point of the observation line and is named as a1Point; the intersection point of the observation line a and the No. 2 observation section is the second measuring point of the observation line and is named as a2The intersection point of the point, the observation line b and the No. 1 section is the first measuring point of the observation line and is named as b1Point, and so on;
s105: acquiring original settlement data sequences of all observation points within a period of time by using a monitoring sensing module;
and gray correlation calculation, comprising:
s201: classifying the original settlement data sequences in the step S105, defining the original settlement data sequences of the settlement measuring points at the top of the foundation pit support as system behavior characteristic sequences, and defining the original settlement data sequences of each soil settlement measuring point on the observation line corresponding to the original settlement data sequences as evaluation sequences;
s202: obtaining the initial image sequence of each sequence in the step S201;
s203: calculating the absolute value sequence of the difference of the components corresponding to the initial image sequence in the step S202;
s204: solving the maximum value and the minimum value of all the numerical values in the sequence obtained in the step S203;
s205: solving the correlation coefficient of the system behavior characteristic sequence and the evaluation sequence and calculating the gray correlation numerical value of each soil settlement measuring point;
and (3) performing coupled evaluation on the grey relevance and entropy method, wherein the coupled evaluation comprises the following steps:
s301: establishing a gray correlation value matrix by using the gray correlation values in step S205
S302, performing data translation on the grey correlation degree values of the measuring points;
s303: calculating the proportion of the relevance value of each soil settlement measuring point on the same observation line;
s304; calculating an entropy value and a difference coefficient of each observation line;
s305; calculating the weight of each observation line;
s306: and calculating the comprehensive score of each observation section and calculating the average value of the comprehensive scores to obtain the safety evaluation score.
Step S201, defining an original settlement data sequence of settlement measurement points at the top of a foundation pit support as a system behavior feature sequence, and defining an original settlement data sequence of each soil settlement measurement point on an observation line corresponding to the original settlement data sequence as an evaluation sequence, taking an observation line a as an example, including:
the system behavior characteristic sequence is Xa0＝(xa0(1),xa0(2),xa0(3)…xa0(n))，
Wherein n is an observation time; xa0＝(xa0(1),xa0(2),xa0(3)…xa0(n)) represents a data sequence of a settlement measuring point at the top of the foundation pit support in the observation line at the time of 1,2,3 … … n;
evaluation sequence is Xai＝(xai(1),xai(2),xai(3)…xai(n))，
Wherein, i is 1,2,3 … … m, n is observation time, m is observation section number or measurement point number in a observation point circuit; xai＝(xai(1),xai(2),xai(3)…xai(n)) represents a data sequence of the ith soil body settlement measuring point in the observation line a at the time of 1,2 and 3 … … n.
The step S202 of obtaining the initial image sequence of each sequence, taking an observation line a as an example, includes:
a, an initial image sequence calculation method of an initial settlement data sequence of a settlement measuring point at the top of a foundation pit support in an observation line comprises the following steps,
a, the initial image sequence calculation method of the original settlement data sequence of each soil settlement measuring point in the observation line comprises the following steps,
The calculating of the absolute value sequence of the difference between the components corresponding to the initial image sequence in step S203, taking a observation line as an example, includes:
Δai(k)＝|x'a0(k)-x'ai(k) 1, |, where i ═ 1,2,3 … … m; k is 1,2,3 … … n, m is observation section number or a measurement point number in observation line, n is observation time, deltaai(k) Absolute value of difference between components corresponding to initial images of system behavior characteristic sequence and evaluation sequence
The step S204 of calculating the maximum value and the minimum value of all the values in the sequence obtained in the step S203 includes, for example, taking the a observation line:
In step S205, the calculating of the correlation coefficient between the system behavior feature sequence and the evaluation sequence and the calculating of the correlation of each soil settlement measurement point, taking the observation line a as an example, includes:
wherein i is 1,2,3 … … m; k is 1,2,3 … … n, m is an observation section number or a measurement point number in an observation line, and n is an observation time; gamma ray0iAnd (b) observing the degree of association between each soil body settlement measuring point in the line and the foundation pit support top settlement measuring point.
In the calculation in steps S201 to S205, each observation line is independently calculated without interfering with each other, and the calculation method of each observation line, such as a, b, c, d, e … …, is the same as the above method.
The smaller the grey correlation degree is, the better the grey correlation degree is, the smaller the.
The establishing of the gray correlation data matrix in step S301 includes: defining the gray correlation degrees of soil settlement measuring points in each observation line as gammaai、γbi、γci… …, where i is 1,2,3 … … m, m is observation section number or measurement point number in each observation line, then establishing gray correlation degree data matrix A as
The data translation of the gray correlation degree values of the measuring points in the step S302 includes:
for the observation line a, the data processing method is,
For the b observation line, the data processing method is,
wherein i is 1,2,3 … … m;
X′bidata obtained after data translation is carried out on gray correlation degree values of all soil settlement measuring points on the b observation line
c. The observed line calculations for d, e … …, etc. are the same, and so on.
Step S303, calculating the proportion of the association degree value of each soil settlement measurement point on the same observation line, includes:
for the observation line a, the proportion calculation method of each soil settlement measuring point comprises the following steps,
for the observation line b, the proportion calculation method of each soil settlement measuring point comprises the following steps,
c. the observed line calculations for d, e … …, etc. are the same, and so on.
Step S304, calculating the entropy and the difference coefficient of each observation line, includes:
for the a observation line, its entropy value is
the coefficient of difference is ga＝1-eaWherein, gaThe difference coefficient of the line is observed for a.
b. The observation lines c, d, e … …, etc. are calculated the same, and so on.
Calculating the weight of each observation line in the step S305, including; for a observation line, its weightIs composed of
Wherein, WaThe weight of the observation line a is used, the numerator of the formula is the difference coefficient of the observation line a, and the denominator of the formula is the sum of the difference coefficients of all the lines; b. the observation lines c, d, e … …, etc. are calculated the same, and so on.
Step S306, calculating the score of each observation section and calculating the average value thereof to obtain the safety assessment result, including:
Si＝X'ai·Wa+X'bi·Wb+X'ci·Wc… where i is 1,2,3 … … m, m is the observation section number or the number of the measuring points in each observation line, SiScoring the evaluation of each observation section;
2. The foundation pit deformation safety evaluation system according to claim 1, wherein: the method comprises the following steps: the monitoring system comprises a data storage module, a monitoring sensing module, a central processing module, a display module and a network sharing module.
3. The foundation pit deformation safety evaluation system according to claim 2, wherein: the data storage module comprises a grating array signal processor and a high-speed solid state disk, the monitoring sensing module comprises a plurality of grating array sensors, and the grating array sensors are buried on each measuring point according to the steps S101-S104 and are connected with the data storage module.
4. The foundation pit deformation safety evaluation system according to claim 2, wherein: the grating array sensor measures settlement data of the measuring point once every 30 minutes and transmits the settlement data to the data storage module for storage.
5. The foundation pit deformation safety evaluation system according to claim 2, wherein: the central processing module is connected with the data storage module, the central processing module extracts settlement data of all the measuring points within a period of time from the data storage module to serve as an original settlement data sequence in the step S105, and a gray correlation analysis and entropy method coupling model is established according to the steps S201-S205 and the steps S301-S306 to conduct foundation pit deformation safety assessment.
6. The foundation pit deformation safety evaluation system according to claim 2, wherein: and the central processing module extracts all latest settlement observation data within 48 hours from the storage equipment every 60 minutes to serve as the original settlement data sequence in the step S105 to perform foundation pit deformation safety evaluation once.
7. The foundation pit deformation safety evaluation system according to claim 2, wherein: the display module is connected with the data storage module, and technicians can visually see fluctuation conditions of the original settlement data uploaded to the data storage module through the display module.
8. The foundation pit deformation safety evaluation system according to claim 2, wherein: the display module is connected with the central processing module, technicians can visually see the gray correlation degree value of each soil settlement measuring point calculated by the central processing module and the foundation pit deformation safety dynamic evaluation results at different time points, and the technicians can observe the development trend of the foundation pit safety through the display module.
9. The foundation pit deformation safety evaluation system according to claim 2, wherein: and the network sharing module is mutually connected with the central processing module and the data storage module, and shares the original settlement data and the foundation pit safety evaluation result with other related projects in real time.
10. The foundation pit deformation safety evaluation system according to claim 2, wherein: when the central processing module extracts the original settlement data sequence of each settlement measuring point, a metabolism method is utilized, new observation data is added into the data sequence along with the time, the data sequence is removed from the original old data, the dimension of each settlement measuring point data sequence is guaranteed to be unchanged, namely the latest data sequence in a period of time is adopted in each calculation, and the evaluation precision is guaranteed.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117057632A (en) * | 2023-10-11 | 2023-11-14 | 北京城建勘测设计研究院有限责任公司 | Method for evaluating precipitation recharging feasibility of pebble layer deep foundation pit |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006022600A (en) * | 2004-07-09 | 2006-01-26 | Shimizu Corp | Settlement prediction method and settlement prediction program |
| CN105653871A (en) * | 2016-01-06 | 2016-06-08 | 电子科技大学 | Symbolic multi-quality-characteristic analysis method based on relative entropy and grey relational degree |
| CN107402043A (en) * | 2017-07-24 | 2017-11-28 | 沈阳工业大学 | Half cover and cut method Construction of City Tunnel monitoring method and monitoring system |
| CN108537600A (en) * | 2018-04-17 | 2018-09-14 | 华北电力大学 | A kind of electricity market postitallation evaluation method and computing device |
| CN111027881A (en) * | 2019-12-17 | 2020-04-17 | 福州大学 | Transmission tower natural disaster loss evaluation method based on improved grey correlation degree |
-
2020
- 2020-07-14 CN CN202010673732.2A patent/CN111768125A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006022600A (en) * | 2004-07-09 | 2006-01-26 | Shimizu Corp | Settlement prediction method and settlement prediction program |
| CN105653871A (en) * | 2016-01-06 | 2016-06-08 | 电子科技大学 | Symbolic multi-quality-characteristic analysis method based on relative entropy and grey relational degree |
| CN107402043A (en) * | 2017-07-24 | 2017-11-28 | 沈阳工业大学 | Half cover and cut method Construction of City Tunnel monitoring method and monitoring system |
| CN108537600A (en) * | 2018-04-17 | 2018-09-14 | 华北电力大学 | A kind of electricity market postitallation evaluation method and computing device |
| CN111027881A (en) * | 2019-12-17 | 2020-04-17 | 福州大学 | Transmission tower natural disaster loss evaluation method based on improved grey correlation degree |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117057632A (en) * | 2023-10-11 | 2023-11-14 | 北京城建勘测设计研究院有限责任公司 | Method for evaluating precipitation recharging feasibility of pebble layer deep foundation pit |
| CN117057632B (en) * | 2023-10-11 | 2024-01-19 | 北京城建勘测设计研究院有限责任公司 | Method for evaluating precipitation recharging feasibility of pebble layer deep foundation pit |
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