JPH08151633A - Execution management system for earth retaining work - Google Patents

Abstract

PURPOSE: To safely and reasonably conduct the earth retaining work. CONSTITUTION: The first processing means 42 performs the repetitive extended Kalman filter process based on the measured data including the displacement of a wall body and the axial force of a strut and the prescribed assumed value including the back face side pressure of a wall to be estimated and the initial value of the ground reaction coefficient. A weighting means 44 weights the error covariance value of the obtained estimated value. The second processing means 45 performs the repetitive extended Kalman filter process based on the estimated value obtained by the first processing means 42 and the weighted covariance value as the initial values. A convergence judging means 46 judges the convergence of the estimated value to obtain the optimum estimated value. A prediction analysis section 6 predicts the deformation and stress state of an earth retaining frame based on the optimum estimated value or the like.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for managing excavation work for a mountain retaining structure, and more particularly to a method for managing a construction work for a mountain retaining structure using information obtained by performing an inverse analysis based on a measured value of the mountain retaining frame for managing the construction. It is a thing.

[0002]

2. Description of the Related Art The excavation work carried out in recent years has been large in construction with large cross section and large depth, construction on ultra-soft ground, and construction on dense urban areas. In order to ensure safety and economy in such mountain retaining work, various measurements are performed at the construction site, the current state of the mountain retaining frame is confirmed from the measured values, and the state of the future excavation stage or demolition of the mountain retaining structure is predicted. It is especially important to manage the construction work. Mountain retaining construction based on such management is generally called mountain retaining information processing construction.

[0003] In the construction of computerized mountain retaining, various processes are performed on the measured values of the frame retaining frame by using a computer,
You have the information you need to manage your construction. This process is usually
It can be broadly divided into three categories: current situation analysis, reverse analysis, and predictive analysis.

In the current analysis, the inclination angle of the mountain retaining wall and the axial force of the truss are used as the measured values of the mountain retaining frame, and the displacement of the wall, the bending moment of the wall, etc. are obtained by a mathematical method. In addition, in the inverse analysis, the displacement of the wall body and the axial force of the girder obtained in the current analysis based on the measured values are used to perform the inverse analysis by the nonlinear optimization method based on, for example, the elasto-plastic method, and the design is performed. The parameters are the backside pressure of the wall and the ground reaction force coefficient of the earth retaining frame. Further, in the prediction analysis, using the back side pressure and the ground reaction force coefficient obtained by the inverse analysis, predict the behavior of the mountain retaining at each future excavation stage and the mountain retaining dismantling, the expected displacement of the wall body,
The bending moment of the wall and the axial force of the beam are calculated.

Among these processes, the current condition analysis and the predictive analysis are relatively easy to carry out because the analysis methods are almost established and the time required for the process is short. However, the inverse analysis requires complicated processing, a large scale, and a long processing time. Further, since the measurement values that are the basis of the inverse analysis are obtained by performing measurements at the construction site, there are many variations in general, and good analysis results are often not obtained. In order to solve such a problem, it is possible to apply control theory to inverse analysis.

The analysis of the frequency domain using the stationary signal by Wiener is called classical control theory. On the other hand, Kalman (Kalman, RE: A new a
pproach to linear filtering and prediction problem
s, Trans. ASME, J. Basic Eng., Vol. 82, pp. 35-45,
1960., and Kalman, RE and RS Bucy: Newre
sult in linear filtering and prediction theory, Tr
nas, ASME, J. BasicEng., Vol. 83, pp. 95-108, 196
Linear system theory based on time series analysis and state space display by 1.) is called modern control theory, and is widely used in various fields. The Kalman filter based on this control theory is particularly effective when the parameters and parameters of the linear dynamic system are to be inversely analyzed and estimated based on the data and the input / output data when the variations and errors are large. Then, when the Kalman filter is applied, the process is a sequential process while sequentially inputting data, so that it is possible to obtain results with good followability to fluctuations and the calculation scale is small, so even a computer such as a personal computer Processing can be completed in a short time.

The extended Kalman filter is an extension of the Kalman filter so that it can be more generally applied to nonlinear systems. Therefore, it has a wider range of applications and is used in various situations. For example, DG Carmichael
(Carmichael, DG: The state estimation problem
m in experimental structural mechanics, Applicatio
n of statistics & probability soil and strctural e
ngineering, 3rd Inter.Conf. pp. 802-815, 1979-2.
) Has applied the extended Kalman filter to concrete creep problems and linear one-degree-of-freedom dynamic problems. Also, CB. Yun (Yun, CB. And M. Shinozuka:
Identification of nonlinear structuraldynamic sys
tems, J. Struct. Mech. 8 (2), pp. 182-203, 1980.)
Et al. Have applied it to the analysis of offshore structures, assuming that observation data of each mass point can be obtained for a multi-degree-of-freedom system.

[0008]

However, in these application examples, accurate estimation results can be obtained even when the number of measurement values is limited, and good estimation is possible even when the initial value setting range is wide. It does not guarantee that results will be obtained. Therefore, although the extended Kalman filter has excellent characteristics, even if this filter is simply applied to the back analysis in the mountain retaining information construction, good results are not always obtained.

It is an object of the present invention to solve the above problems and to carry out mountain retaining work so that a small computer such as a personal computer can complete the processing in a short time and always perform an inverse analysis with high accuracy. To provide a management system.

[0010]

In order to solve the above-mentioned problems, a first aspect of the present invention is to measure a behavior of a mountain retaining frame, perform an inverse analysis based on the measured value, and operate a mountain retaining wall on a back surface. In the construction management system of the mountain retaining work, which estimates the lateral pressure and the ground reaction force coefficient and predicts the displacement and stress state of the next mountain retaining frame based on the obtained analysis results to manage the mountain retaining excavation work, A measuring device that measures the behavior of the current mountain retaining frame including at least the inclination angle and the axial force of the truss to be inserted between the mountain retaining walls, and the current state of the mountain retaining frame based on these measurement data input from the measuring device. Current state analysis means for analyzing the stress state of, the analysis value obtained by the current state analysis means, the assumed value of the backside pressure and the ground reaction force coefficient acting on the mountain retaining wall to be estimated, and the error with respect to the assumed value The covariance value and the covariance value of the noise included in the analysis value are taken as input data, the extended side Kalman filter is repeated a predetermined number of times and the estimated value of the backside pressure and the ground reaction force coefficient acting on the mountain retaining wall and its error First analysis means for analyzing the covariance value of, the analysis value obtained by the current status analysis means, the estimated value analyzed by the first analysis means, and the error co-multiplied by a predetermined weight. Second analyzing means for taking the variance value as an initial value and repeating the extended Kalman filter a predetermined number of times again to analyze the backside pressure acting on the mountain retaining wall, the estimated value of the ground reaction force coefficient, and the covariance value of its error. And the initially set backside pressure acting on the mountain retaining wall and the hypothetical value of the ground reaction force coefficient, and the estimated value analyzed by the second analyzing means, and both are within a predetermined error level. Are matched by Itoki is to execute the second analysis unit again multiplied by a predetermined weight to the error covariance value, when they match within a predetermined error level,
At least the determination means that uses the estimated value analyzed by the second analysis means as the optimal estimated value, and the optimal estimated value of the backside pressure acting on the mountain retaining wall body and the ground reaction force coefficient that are obtained by the determination means. Output that outputs the analysis results obtained by the input analysis data including the input data including the prediction analysis means for predicting the deformation and stress state of the mountain retaining frame in the next step by elasto-plastic analysis And a device.

The second aspect of the invention is obtained by measuring the behavior of the earth retaining frame and performing an inverse analysis based on the measured values to estimate the back side pressure acting on the mountain retaining wall and the ground reaction force coefficient. In the construction management system of the mountain retaining work that predicts the displacement and stress state of the next mountain retaining frame based on the analysis results and manages the mountain excavation work, the inclination angle of the mountain retaining wall and the cut between the mountain retaining walls. A measuring device for measuring the current behavior of the mountain retaining frame including at least the axial force of the beam, and a current state analyzing means for analyzing the current stress state of the mountain retaining frame based on these measurement data input from the measuring device, The analysis value obtained by the present analysis means, the assumed value of the backside pressure and the ground reaction force coefficient acting on the mountain retaining wall to be estimated, the covariance value of the error with respect to the assumed value, and the noise included in the analyzed value First, the hypothetical value of the covariance value is taken as input data, and the extended Kalman filter is repeated a predetermined number of times to analyze the backside pressure acting on the mountain retaining wall, the estimated value of the ground reaction force coefficient, and the covariance value of its error. Of the analysis means, the analysis value obtained by the current status analysis means, the estimated value analyzed by the first analysis means, and the error covariance value multiplied by a predetermined weight are taken in as initial values and re-acquired. Second analysis means for repeating the extended Kalman filter a predetermined number of times to analyze the backside pressure acting on the mountain retaining wall, the estimated value of the ground reaction force coefficient, and the covariance value of the error, and the second analysis means. Evaluating means for calculating a value of a predetermined evaluation function with respect to the estimated value of the backside pressure acting on the mountain retaining wall and the ground reaction force coefficient, and the value of the evaluation function calculated by the evaluating means is a predetermined reference. Meet When no is,
When the value of the evaluation function satisfies a predetermined criterion by multiplying the error co-division value by a predetermined weight and the second analysis means is executed again, the estimated value analyzed by the second analysis means And an input value including at least the optimum estimated value of the backside pressure acting on the mountain retaining wall body obtained by the determination means and the ground reaction force coefficient obtained by the determination means, and the elasto-plastic analysis is performed next. The present invention is characterized by comprising a predicting means for predicting a deformation and a stress state of the mountain retaining frame at a stage, and an output device for outputting an analysis result obtained by the present condition analyzing means, the judging means, and the predictive analyzing means.

In the mountain retaining work construction management system according to the first and second aspects of the present invention, the back side pressure acting on the mountain retaining wall and the estimated values of the ground reaction force coefficient obtained by the repeated extended Kalman filter process of the second analyzing means, It is possible to obtain a very stable estimated value by repeatedly executing the extended Kalman filter processing with the error covariance value multiplied by the weight as the initial value, and the number of measurement values is limited. Even if the noise component included in the measured value is large, the estimated value can be efficiently obtained with high accuracy without limiting the initial value to be given to a narrow range.

Since it is the inverse analysis based on the iterative extended Kalman filter processing, the processing is a sequential processing while successively inputting data, high followability to fluctuations is obtained, and the calculation time is short, The scale is also small. Therefore, at the site of excavation work for earth retaining works, it is possible to input the measured values of the earth retaining structure to a small computer such as a personal computer and quickly carry out an inverse analysis. Can be accurately predicted. Further, a small computer is sufficient, which is advantageous in terms of cost.

[0014]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Next, a first embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 is a functional block diagram showing a schematic configuration of a construction management system for mountain retaining work according to the first invention. This system is for managing a mountain excavation work, and includes an input device 1 such as a keyboard, an analysis device 8 having a current state analysis unit 2, an inverse analysis unit 4, a prediction analysis unit 6, and a display device 10 such as a CRT display. Consists of.

The current state analysis section 2 is composed of a curve fitting means 22, a smoothing processing means 24, and a current state analysis value calculation means 26. The inverse analysis unit 4 includes first iterative extended Kalman filter processing means 42 (hereinafter referred to as first processing means), weighting means 44, and
Second iterative extended Kalman filter processing means 45 (hereinafter referred to as second processing means), convergence determination means 46,
It is constituted by the confirmation value calculation means 49. The prediction analysis unit 6 is composed of the mountain retaining elasto-plasticity analysis means 62.

Current state analysis section 2, inverse analysis section 4, prediction analysis section 6
Is provided as hardware or software in the analysis device 8 which constitutes a computer such as a personal computer (personal computer).

The mountain retaining frame formed in the mountain excavating work will be described with reference to FIG. 2 which schematically shows a cross section thereof. In FIG. 2, 102 is the ground surface,
108 is an excavation surface. Mountain retaining wall bodies (hereinafter referred to as wall bodies) 104a and 104b are driven into both sides of the excavation surface 108 to prevent debris and the like from collapsing. Both walls 1
A crossbeam 106 is passed between 04a and 104b to reinforce the wall body 106 against earth pressure. Wall 104
A and 104b are made of steel sheet pile or formed by RC continuous underground wall. The excavation work for mountain retaining begins with driving the walls 104a and 104b into the ground.
After that, excavation proceeds between the walls. Then, as the excavation progresses, the girders 106 are sequentially installed from the shallow one at appropriate intervals.

The construction management system for the earth retaining work according to the present embodiment has the inclination angles of the walls 104a and 104b and the girder 106.
Is input from the input device 1 as an input measurement value. The inclinometer 110 measures the inclination angle of the wall bodies 104a and 104b.
a, 110b, along the wall in the depth direction, for example, 1
The inclination is measured at intervals of ~ 2m. Further, the axial force of the cutting beam is measured by using the measuring device 112 for each cutting beam 106. The inclinometers 110a and 110b are the wall bodies 104a,
Plural are installed in 104b.

The curve fitting means 22 is provided on the ground surface 1.
When the measured values of the tilt angle and the axial force, which are functions of the depth from 02, are taken in from the input device 1, curve fitting using a cubic spline function is performed for each.
The smoothing means 24 further smooths the result of this curve fitting using the Hanning window. By such curve fitting and smoothing, even if the measurement data includes variations or noise, its influence can be mitigated. Further, even if the number of measurement data is small, the number of data can be increased by interpolation. Therefore, appropriate data can be obtained as the data for the current analysis of the mountain retaining frame, and a good result can be obtained in the inverse analysis performed later.

The present analysis value calculation means 26 includes a wall 104.
a, 104b material, wall 104a, 104b thickness,
In addition, data including the depth of the excavated surface 108 is provided as basic data necessary for the current state analysis. The current state analysis value calculation means 26 uses these data, the inclination angle data of the walls 104a and 104b received from the smoothing means 24, and the axial force data of the truss 106, and the wall bodies 104a and 104b by a known mathematical method. Calculate the displacement, bending moment, and bending rigidity. For example, the wall 104
The displacements of a and 104b are obtained by function integration of the inclination angles of the wall bodies 104a and 104b. Also, the wall 10
The bending moments of 4a and 104b are obtained by functionally differentiating the inclination angles of the walls 104a and 104b under the assumption of the bending rigidity of the walls.

The present state analysis value calculation means 26 outputs the physical quantity thus obtained together with the inclination angle data of the wall bodies 104a and 104b and the axial force data of the truss as data for the present state analysis of the mountain retaining frame. , CRT display or the like to display in a predetermined format. The display of the mountain retaining work enables the builder to recognize the current state of the mountain retaining work, and can be useful for efficient implementation of work and ensuring safety.

At the same time, the current state analysis value calculating means 26
The calculated displacements, bending stiffnesses, and bending moments of the wall bodies 104a and 104b, and each data of the axial force of the cutting beam 106 are output to the inverse analysis unit 4.

In the inverse analysis unit 4, the first iterative extended Kalman filter processing means 42 firstly displaces the wall bodies 104a and 104b from the current analysis value calculation means 26, bends rigidity,
In addition, the bending moment and each data of the axial force of the girder 106 are received as the measured values of the system whose state is to be estimated. In addition to these measured values, the design values of the backside pressures of the walls 104a and 104b are input to the first processing means 42 as measured values, and further, the structural dimensions of the mountain retaining frame, the cut beam spring constant, and the cut beam position. The data such as the pre-displacement, the pre-load of the beam, and the boundary conditions at both ends of the wall are input as the basic data required for the inverse analysis. Data necessary for these inverse analyzes are input via the input device 1.

Then, the first filter processing means 42 is
As schematically shown in FIG. 3, the depth direction distribution A of the pressure applied to the back surface of the wall bodies 104a and 104b, that is, the back surface side pressure a, and the ground reaction force coefficient B distribution in the same depth direction are repeatedly expanded. The estimation is performed by the Kalman filter processing, that is, the processing in which the local iteration is incorporated in the extended Kalman filter. Analysis by this extended Kalman filter can be performed using, for example, “Jazwinski, AH: Stochastic proce
sses and filtering theory, Academic Press, 1970. ”
Can be done by In the analysis using the extended Kalman filter, the initial values of the back side pressure a and the estimated value of the ground reaction force coefficient B, the covariance values of those errors, the displacements of the mountain retaining wall bodies 104a and 104b, which are the measured values, and the girder 10
The initial value of the covariance value of the noise included in the axial force of 6 is taken in, and the first processing means 42 repeatedly performs extended Kalman filter processing using these initial value and the measured value, and the back side pressure a and The optimum estimated value of the ground reaction force coefficient B and the covariance value of those errors are obtained. As specific values of the initial values, in this example, assumed values (design values) are used for the back side pressure a and the ground reaction force B, the error covariance value is 30%, and the noise covariance value is 50%. And

The first processing means 42 executes the analysis processing based on the following equation.

[0026]

[Equation 1]

Further, each conversion matrix is represented by the following equation.

[0028]

[Equation 2]

The weighting means 44 is the first processing means 42.
The estimated value and the error covariance value of the back side pressure a and the ground reaction force coefficient B obtained by the analysis by the extended Kalman filter are received from the first processing means 42, and the estimated value and the error covariance value are multiplied by a predetermined weight. And the second processing means 4
5 is output.

The second processing means 45 is also the first processing means 4
The extended Kalman filter process is repeated as in the case of 2.
The second processing means 45 takes in the measurement data described above, the estimated values of the backside pressure a and the ground reaction force coefficient B obtained by the first processing means 42, and the error co-fractional value obtained by multiplying a predetermined weight. Then, iteratively extended Kalman filtering is performed,
The estimated values of the back surface side pressure a and the ground reaction force coefficient B and the covariance values of those errors are calculated and output to the convergence determination means 46. The weighting means 44 and the second processing means 45 carry out the processing in the second filter processing step of the present invention.

The convergence determination means 46 is
The estimated value (back side pressure a and ground reaction force coefficient B) obtained by the second processing means 45 and the estimated value (back side pressure a and ground reaction force coefficient B) obtained by the first processing means 42 are Compare. Then, if the comparison does not match within a certain level of the allowable error range, the extended Kalman filter process is repeatedly performed as a global iteration.
The weighting means 44 again weights the error covariance values in a predetermined manner. Then, the second processing means 45 repeatedly executes the extended Kalman filter processing again as described above,
The result is output to the convergence determination means 46.

The convergence determining means 46 again calculates the estimated values (rear surface side pressure a and ground reaction force coefficient B) obtained by the second processing means 45 and the estimated values (rear surface) by the first processing means 42. Lateral pressure a and ground reaction force coefficient B) are compared, and if the two do not match within a certain level of allowable error, until the two match within a certain level of allowable error. Perform similar processing. Then, the first processing means 42 and the second
When the respective estimated values obtained by the processing means 45 of No. 2 match with each other within a certain level of the allowable error range, it is considered that the estimated values obtained by the second processing means 45 have converged. The estimated values of the back surface side pressure a and the ground reaction force coefficient B obtained by the processing means 45 are output as optimum estimated values, displayed on the display device 10 such as a CRT display, and at the same time output to the confirmation value calculation means 49. FIG. 5 shows the back side pressure a and the ground reaction force coefficient B which are unknown parameters obtained by the second processing means 45.
It is a figure showing an estimated value (dotted line) and an actual measurement value (solid line) of
If the iterative extended Kalman filter according to the present invention is used, the estimated values (rear surface side pressure a and ground reaction force coefficient B rear surface) can be obtained very close to the measured values by repeating several times (for example, four times or more). It was

Upon receipt of these estimation results, the confirmation value calculating means 49 uses the known mathematical method based on the estimation results to calculate the displacements of the walls 104a and 104b, the bending moments, and the axial force of the cutting beam 106. The calculated value is output as a confirmation value and displayed on the display device 10. The operator of this system judges the validity of the estimation result by looking at these confirmation values.

Then, the mountain retaining elasto-plastic analyzing means 62 of the prediction analyzing section 6 estimates the back side pressure a and the ground reaction force coefficient B received from the convergence determining means 46 of the inverse analyzing section 4, and the mountain retaining wall bodies 104a and 104b. Bending rigidity, displacement, bending moment, spring constant of the cutting beam 106, preceding load of the cutting beam, and pre-displacement of the wall at the cutting beam position are acquired, and elasto-plastic analysis is performed by a known mathematical method, and the next period is calculated. Display device for calculating data such as displacement and bending moment of wall bodies 104a and 104b at the construction stage, axial force of beam and plastic region, and obtaining and outputting these data as mountain retaining behavior at the time of disassembling mountain retaining frame Display on 10. By looking at the display, the builder of the mountain retaining work can predict the safety of the future work and proceed with the work safely and rationally.
FIG. 6 is a diagram showing the displacements of the mountain retaining wall bodies 104a and 104b and the predicted values (solid lines) and the measured values (circle marks) of the bending retaining walls 104a and 104b in the next construction stage, which are obtained by the predictive analysis unit 6.
It was possible to obtain a predicted value that corresponds very well to the measured value.

Next, a second embodiment of the present invention will be described. FIG. 4 is a functional block diagram showing a schematic configuration of a mountain retaining information computerized construction management system to which an inverse analysis method according to the second invention is applied. The same parts as those in the embodiment shown in FIG. 1 are designated by the same reference numerals and the description thereof will be omitted. In this embodiment, the inverse analysis unit 5 is composed of a first processing means 42, a weighting means 44, a second processing means 45, an evaluation function calculation means 47, and a convergence determination means 48. Therefore, here, only the evaluation function calculation means 47, the convergence determination means 48, and the parts related thereto will be described, and the description of the other parts will be omitted. In this embodiment, the analysis processing up to the second processing means 45 is the same as that of the first embodiment shown in FIG.

The evaluation function calculating means 47 includes the back side pressure a and the ground reaction force coefficient B shown in FIG. 3 from the second processing means 45.
When the estimated value and the error covariance value are received from the second processing means 45, the estimated value of the back side pressure a and the ground reaction force coefficient B is used to calculate the value of the evaluation function represented by the following equation, The result is output to the convergence determination unit 48 together with the estimated value and the error covariance value. The value of this evaluation function is a function of the normalized mean square of the difference between the measured value and the estimated value.

[0037]

(Equation 3)

Upon receiving the value of the evaluation function from the evaluation function calculation means 47, the convergence judgment means 48 judges whether or not it is the minimum value.
In order to perform the iteration, the weighting means 44 again weights the error covariance value with a predetermined weight.

Then, the second processing means 45 repeatedly executes the extended Kalman filter processing in the same manner as described above, and outputs the result to the evaluation function calculation means 47.

The evaluation function calculation means 47 again calculates the value of the evaluation function, and outputs the result to the convergence determination unit 48 together with the estimated value and the error covariance value. Then, when the convergence determination unit 48 receives the value of this evaluation function, the convergence determination unit 48 determines whether or not it is the minimum value.
When the weighting means 445 is instructed to perform weighting, and when the value is the minimum value, it is considered that the estimation result has converged, and the back surface side pressure a and the ground reaction force coefficient obtained by the evaluation function calculating means 47 are obtained. The estimated value of B is output as the optimal estimated value,
It is displayed on the display device 10 and is also output to the confirmation value calculation means 49 at the same time. The subsequent processing is similar to that of the embodiment shown in FIG.

In this embodiment, since it is determined whether or not the estimation result has converged by using the evaluation function as described above, the above-mentioned FIG.
Even if the first embodiment shown in FIG.
The estimation result can be converged, and the estimated value close to the true value can be obtained. Although each of the above-described embodiments was applied to excavation work for mountain retaining, it is also applicable to embankment work on soft ground, for example.

[0042]

As described above in detail based on the embodiments, the mountain retaining work construction management system according to the present invention acts on the mountain retaining wall body obtained by the repeated extended Kalman filter process of the second analyzing means. It is possible to obtain a very stable estimated value by repeatedly executing extended Kalman filtering with the estimated values of the backside pressure and the ground reaction force coefficient and the error covariance value multiplied by the weight as initial values. Therefore, even if the number of measured values is limited and the noise component included in the measured values is large, the estimated value can be efficiently obtained with high accuracy without limiting the initial value to be given to a narrow range. .

Since the inverse analysis is based on the iterative extended Kalman filter process, the process is a sequential process while sequentially inputting data, high followability for fluctuations is obtained, and the calculation time is short, The scale is also small. Therefore, it is possible to input the measured values of the mountain retaining frame to a small computer such as a personal computer at the site of the mountain retaining structure and quickly perform an inverse analysis.Based on this analysis result, the deformation and stress state of the mountain retaining frame at the next stage can be calculated. Since it is possible to accurately predict, it is possible to carry out the mountain retaining work stably and rationally.

[Brief description of drawings]

FIG. 1 is a block diagram showing an example of a construction management system for mountain retaining work according to a first invention.

FIG. 2 is a cross-sectional view for explaining a mountain retaining frame.

FIG. 3 is a schematic cross-sectional view for explaining a physical quantity to be estimated in the mountain retaining frame of FIG.

FIG. 4 is a block diagram showing an example of a construction management system for mountain retaining work according to a second invention.

FIG. 5 is a diagram showing a comparison between an estimated value and an actually measured value of the backside pressure and the ground reaction force coefficient obtained by the construction management system for mountain retaining work according to the present invention.

FIG. 6 is a diagram showing a comparison between the predicted value and the measured value of the displacement and bending moment of the mountain retaining wall body obtained by the construction management system for mountain retaining work according to the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Input device 2 Current condition analysis part 4, 5 Inverse analysis part 6 Prediction analysis part 8 Analysis device 10 Display device 22 Curve fitting means 24 Smoothing means 26 Current condition analysis value calculation means 42 First iterative extended Kalman filter processing means 44 Weighting means 45 Second iterative extended Kalman filter processing means 46, 48 Convergence determination means 47 Evaluation function calculation means 49 Confirmation value calculation means 62 Earth retaining elasto-plastic analysis means 102 Ground surface 104 Wall body 106 Cutting beam 108 Excavation surface

Claims (4)

[Claims] 1. The behavior of a mountain retaining frame is measured, and an inverse analysis is performed based on the measured value to estimate the backside pressure acting on the mountain retaining wall and the ground reaction force coefficient, and based on the obtained analysis results. In the construction management system of the mountain retaining work that predicts the displacement and stress state of the mountain retaining frame at the next stage and manages the mountain retaining excavation work, at least the inclination angle of the mountain retaining wall and the axial force of the girder to be inserted between the mountain retaining walls should be at least A measuring device for measuring the behavior of the current mountain retaining frame, including a current state analyzing means for analyzing the current stress state of the mountain retaining frame based on these measurement data input from the measuring device, and the current state analyzing means. Analysis value, hypothetical value of backside pressure acting on the retaining wall and the ground reaction force coefficient to be estimated, covariance value of error with respect to the hypothetical value, and covariance value of noise included in the analysis value are input. First analyzing means for analyzing the back side pressure acting on the mountain retaining wall and the estimated value of the ground reaction force coefficient and the covariance value of the error by repeating the extended Kalman filter a predetermined number of times, and the present condition analysis. The analysis value obtained by the means, the estimated value analyzed by the first analysis means, and the error covariance value multiplied by a predetermined weight are taken in as initial values, and the extended Kalman filter is repeated a predetermined number of times to repeat the above. Second analysis means for analyzing the back side pressure acting on the mountain retaining wall body, the estimated value of the ground reaction force coefficient and the covariance value of the error thereof, and the back side pressure acting on the mountain retaining wall body set first and the ground reaction The assumed value of the force coefficient is compared with the estimated value analyzed by the second analyzing means, and when the two do not match within a predetermined error level, a predetermined weight is given to the error covariance value. Multiply again When the two are matched within a predetermined error level, the determination means that makes the estimated value analyzed by the second analysis means an optimum estimated value, and the determination means obtained by the determination means The input data including at least the optimum estimated value of the back side pressure acting on the mountain retaining wall and the ground reaction force coefficient is taken in, and the deformation of the mountain retaining frame in the next stage by elasto-plastic analysis, a prediction analysis means for predicting a stress state, A construction management system for mountain retaining work, comprising: an output device that outputs the analysis results obtained by the current state analysis means, the determination means, and the prediction analysis means. 2. The behavior of the earth retaining frame is measured, and the back side pressure acting on the mountain retaining wall and the ground reaction force coefficient are estimated by performing an inverse analysis based on the measured value, and based on the obtained analysis result. In the construction management system of the mountain retaining work that predicts the displacement and stress state of the mountain retaining frame at the next stage and manages the mountain retaining excavation work, at least the inclination angle of the mountain retaining wall and the axial force of the girder to be inserted between the mountain retaining walls should be at least A measuring device for measuring the behavior of the current mountain retaining frame, including a current state analyzing means for analyzing the current stress state of the mountain retaining frame based on these measurement data input from the measuring device, and the current state analyzing means. Analysis value, hypothetical value of backside pressure acting on the retaining wall and the ground reaction force coefficient to be estimated, covariance value of error with respect to the hypothetical value, and covariance value of noise included in the analysis value are input. First analyzing means for analyzing the back side pressure acting on the mountain retaining wall and the estimated value of the ground reaction force coefficient and the covariance value of the error by repeating the extended Kalman filter a predetermined number of times, and the present condition analysis. The analysis value obtained by the means, the estimated value analyzed by the first analysis means, and the error covariance value multiplied by a predetermined weight are taken in as initial values, and the extended Kalman filter is repeated a predetermined number of times to repeat the above. Second analysis means for analyzing the back side pressure acting on the mountain retaining wall body, the estimated value of the ground reaction force coefficient and the covariance value of its error, and the second retaining means acting on the mountain retaining wall body analyzed by the second analyzing means. Evaluation means for calculating a value of a predetermined evaluation function for the estimated value of the back side pressure and the ground reaction force coefficient, when the value of the evaluation function calculated by the evaluation means does not satisfy a predetermined reference, the error Both When the value of the evaluation function satisfies a predetermined criterion by multiplying the minute value by a predetermined weight and executing the second analysis means again, the estimated value analyzed by the second analysis means is optimally estimated. The determination means to be a value, and the input data including at least the optimum estimated value of the back side pressure acting on the mountain retaining wall body and the ground reaction force coefficient obtained by the determination means is taken in, and the elasto-plastic analysis is performed to the next step. Construction management for mountain retaining work, comprising: a predicting means for predicting the deformation and stress state of the mountain retaining frame, and an output device for outputting the analysis result obtained by the present condition analyzing means, the determining means, and the predictive analyzing means. system. 3. The analysis value obtained by the current state analysis means includes the displacement of the mountain retaining wall body, the bending rigidity of the mountain retaining wall body, the bending moment of the mountain retaining wall body, and the axial force of the cutting beam. Claim 1 or 2 characterized by the following.
Construction management system for mountain retaining work described. 4. The earth retaining work management system according to claim 2, wherein the evaluation function is a function of a normalized mean square of a difference between the measured value and the estimated value.