Evaluation support device, evaluation support method, and evaluation support program

Abstract

To provide an evaluation support device, an evaluation support method, and an evaluation support program to support evaluation of ground hardness.SOLUTION: A controller 21 of an evaluation support device 20 stores first probability, second probability, third probability, and probability information. The first probability is probability determining reach on a support layer for a hardness index, the second probability is probability determining reach on the support layer for an excavation measured value, and the third probability is probability determining reach on the support layer for the excavation measured value upon reach on the support layer on the basis of explanatory variable for the hardness index. The probability information is the information exhibiting reach probability on the support layer calculated through Bayes estimation using the first, the second, and the third probability per the explanatory variable. The controller 21 specifies reach probability on the support layer on the basis of a new excavation measured value by using the probability information when acquiring the new excavation measured value for a new excavation.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an evaluation support device, an evaluation support method, and an evaluation support program that support evaluation of ground hardness. [Background technology]

[0002] A building is constructed using piles that have reached the supporting layer. In order to check this supporting layer, a management device for evaluating the firmness of the ground has been considered (see Patent Document 1). The control unit of the management device described in this document acquires measurement values ​​from a drilling depth measuring instrument, a flow measuring instrument, a current measuring instrument, and a vibration measuring instrument. The control unit then calculates a multiple regression equation by performing a multivariate analysis using the acquired measurement values ​​and firmness index value as explanatory variables and objective variables. When measurement values ​​regarding the excavation conditions of the hole to be evaluated are acquired, the firmness index value of the ground is estimated using the multiple regression equation. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-80737 Summary of the Invention [Problem to be solved by the invention]

[0004] In the technology described in Patent Document 1, a hardness index is calculated based on a measurement value. However, it may be difficult to understand the possibility of reaching the support layer based only on the numerical value indicating the hardness. [Means for solving the problem]

[0005] The evaluation support device for solving the above problem includes a measurement information storage unit that records excavation measurement values ​​during excavation of the ground, a ground information storage unit that records a ground hardness index obtained by a ground investigation result, and a control unit connected to a measurement unit that measures the excavation measurement values. The control unit holds a first probability (P(β)) of determining that the bearing layer has been reached in the hardness index, a second probability (P(α)) of determining that the bearing layer has been reached in the excavation measurement values, a third probability (P(α|β)) of determining that the bearing layer has been reached in the excavation measurement values ​​when the bearing layer has been reached in the hardness index based on explanatory variables, and probability information indicating the possibility of reaching the bearing layer calculated by Bayesian estimation using the first, second, and third probabilities for each explanatory variable, and when a new excavation measurement value is obtained in a new excavation, the control unit uses the probability information to determine the probability of reaching the bearing layer based on the new excavation measurement value. Here, "P(α|β)" is the probability that an event α occurs when an event β occurs. Effect of the Invention

[0006] The present invention can assist in the assessment of ground firmness. [Brief description of the drawings]

[0007] [Figure 1] FIG. 1 is an explanatory diagram of an evaluation system according to a first embodiment. [Diagram 2] FIG. 2 is an explanatory diagram of a hardware configuration of the first embodiment. [Diagram 3] FIG. 2 is an explanatory diagram of data used in the first embodiment, where (a) is an explanatory diagram of data recorded in a ground information recording unit, and (b) is an explanatory diagram of data recorded in a measurement information recording unit. [Figure 4] FIG. 2 is an explanatory diagram of a processing procedure in the first embodiment. [Diagram 5] FIG. 4 is an explanatory diagram of a count table in the first embodiment. [Figure 6] FIG. 2 is an explanatory diagram showing the relationship between explanatory variables and probabilities in the first embodiment. [Figure 7] FIG. 2 is an explanatory diagram of a processing procedure in the first embodiment. [Figure 8] FIG. 2 is an explanatory diagram of the effect in the first embodiment, where (a) is a diagram illustrating a hard layer that is actually measured, and (b) is a diagram illustrating the probability that the layer is hard. [Figure 9] FIG. 11 is an explanatory diagram of a processing procedure in the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] (First embodiment) Hereinafter, an embodiment of the evaluation support device, the evaluation support method, and the evaluation support program will be described with reference to Figs. 1 to 8. In this embodiment, when drilling a pile hole, the reduced shear wave velocity, which is an observed event, is expressed as the likelihood that it has reached the hard support layer, which is the matter to be estimated (the causal event that causes it), using Bayesian estimation. Here, the "observed event" is an observed fact or a value calculated from that fact. The ground, the hardness of which is to be estimated, includes bedrock.

[0009] 1 shows an excavator 10 as an excavation device for excavating a pile hole h0. The excavator 10 includes a base machine 10a, a mast 10b, and an auger machine 10c. The base machine 10a includes a lower traveling body including a crawler 10d, and an upper rotating body including an operation room 10e.

[0010] The mast 10b is erected on the base machine 10a. Wires for measuring depth and speed are provided inside the mast 10b. An auger machine 10c is attached to the mast 10b so that it can be raised and lowered. The auger machine 10c is equipped with a drive motor housed in a box and a drilling rod 10f that is driven and rotated by the drive motor. A drilling head 10g is attached to the tip (lower end) of the drilling rod 10f. The elevation of this drilling head 10g is controlled by an operator in the operation room 10e.

[0011] A drilling water supply device (not shown) that supplies drilling water to the drilling head 10g is connected to the drilling machine 10. The amount of drilling water is adjusted by the operator in the operation room 10e depending on the drilling conditions.

[0012] The excavator 10 is equipped with a measurement unit 11 (measurement section) that measures obtainable information such as the excavation state and excavation conditions. This measurement unit 11 is connected to a management device 20. In this embodiment, the measurement unit 11 is equipped with a depth measuring instrument 111, a flow rate measuring instrument 112, a current measuring instrument 113, and a vibration measuring instrument 114. Each measuring instrument (111 to 114) of the measurement unit 11 continuously performs measurements during excavation and transmits the measurement values ​​to the management device 20.

[0013] The depth measuring device 111 measures the amount of wire let out from within the mast 10b. The depth measuring device 111 then measures the depth corresponding to the position of the drilling head 10g at each time in accordance with the amount of wire let out.

[0014] The flow rate meter 112 measures the injection flow rate (injection amount) of drilling water supplied from the drilling water supply device at each time. The current meter 113 measures the current value of the load current of the drive motor of the auger machine 10c at each time point.

[0015] The vibration measuring device 114 measures vibrations at the installation location at each time. In this embodiment, the vibration measuring device 114 is installed on the mast 10b, and measures vibration characteristics in three directions of the base machine 10a, namely, the front-rear direction, the left-right direction, and the up-down direction. The installation location of the vibration measuring device 114 is not limited to the mast 10b. For example, it may be installed in the operation room 10e, etc.

[0016] (Hardware configuration description) 2, a hardware configuration of an information processing device H10 constituting the management device 20 will be described. The information processing device H10 includes a communication device H11, an input device H12, a display device H13, a storage device H14, and a processor H15. Note that this hardware configuration is an example, and it is also possible to realize the information processing device H10 using other hardware.

[0017] The communication device H11 is an interface that establishes a communication path with other devices and transmits and receives data. The input device H12 is a device that accepts input of various information, such as a mouse, a keyboard, etc. The display device H13 is a display or the like that displays various information.

[0018] The storage device H14 is a storage device (ROM, RAM, hard disk, etc.) that stores data and various programs for executing various functions of the management device 20. The processor H15 is a device (such as a CPU or MPU) that uses programs and data stored in the storage device H14 to control each process in the management device 20. The processor H15 loads programs stored in a ROM or the like into a RAM and executes various processes for each process. The processor H15 may be realized by a dedicated hardware circuit (such as an application specific integrated circuit).

[0019] (Functions of management device 20) Next, each function of the management device 20 (evaluation support device) will be described with reference to FIG. The management device 20 is a computer system that estimates the probability of reaching the bearing layer from each measurement value during excavation. The management device 20 includes a control unit 21, a ground information storage unit 22, a measurement information storage unit 23, and a probability information storage unit 24.

[0020] The control unit 21 performs various processes (processes such as a learning stage, an acquisition stage, and an estimation stage). To this end, the control unit 21 functions as a learning unit 211, an acquisition unit 212, and an estimation unit 213 by executing an evaluation support program.

[0021] The learning unit 211 executes a process of calculating the relationship between the threshold of the converted shear wave velocity and the probability of reaching the support layer using Bayesian estimation. The learning unit 211 holds a hardness determination table that determines the index value of hardness based on the soil type and the N value. For example, in the hardness determination table, for soil type "sand", the index value "1" is set for the N value of "0 or more and less than 10", the index value "2" is set for the N value of "10 or more and less than 30", and the index value "3" is set for the N value of "30 or more". Also, for soil type "clay", the index value "1" is set for the N value of "0 or more and less than 4", the index value "2" is set for the N value of "4 or more and less than 8", and the index value "3" is set for the N value of "8 or more".

[0022] The acquisition unit 212 acquires various measurement values ​​from the measurement unit 11. The acquisition unit 212 records the measurement values ​​acquired from the measurement unit 11 in association with each measurement time in the measurement information storage unit 23. Specifically, the acquisition unit 212 acquires the depth, the amount of injected water, the current value, and the vibration characteristics. In addition, in a hard stratum, the drilling head 10g may be pulled up once just before drilling. Therefore, the actual depth of the drilling head 10g does not necessarily increase monotonically with the elapsed time. Therefore, the acquisition unit 212 uses the measurement value of the substantial time period required for drilling by subtracting the period during which the drilling head 10g is pulled up or stopped from the total work time. The acquisition unit 212 records the depth range (start depth, end depth) in association with the drilling speed, the amount of injected water, the integral current value, and the vibration characteristics according to the measurement time.

[0023] The estimation unit 213 estimates the hardness of the ground by using the measurement values ​​acquired when a new pile hole is excavated and the prediction formula recorded in the probability information storage unit 24.

[0024] As shown in Fig. 3(a), ground management data 220 acquired by boring survey results (ground survey results) is recorded in the ground information storage unit 22. The ground management data 220 records depth, N value, and soil type classification in association with a site identifier and survey position coordinates.

[0025] The site identifier data area records data regarding an identifier for identifying the excavation work site where the boring survey was conducted. The survey location coordinate data area records data relating to the coordinates of the location where the boring survey was carried out at the excavation site.

[0026] In the depth data area, data on the depth that specifies the N value and soil type at this boring survey position is recorded. In this embodiment, for example, data is recorded in units of 0.1 m, and the depth range (end depth and start depth) is recorded.

[0027] The N value data area records data regarding the N value at this depth. The soil classification data area records data regarding an identifier for identifying the soil classification at this depth.

[0028] As shown in Fig. 3(b), the measurement information storage unit 23 records the measurement management data 230, which records the excavation measurement values ​​in association with the site identifier and pile number. The measurement management data 230 is recorded when the pile hole is excavated. In this embodiment, values ​​related to the integral current value, excavation speed, water injection amount, and vibration are used for each depth.

[0029] The site identifier data area records data regarding an identifier for identifying the drilling site of this pile hole. The pile number data area and pile coordinate data area store data on the number for identifying the excavated pile and the position coordinates of the pile. Using the pile coordinates and the survey position coordinates in the ground information storage unit 22, the excavation measurement management data can be associated with the ground management data of the nearest position where a boring survey was performed.

[0030] In the depth data area, data on the depth of the measured value obtained in the hole is recorded. In this embodiment, for example, the data is recorded in units of 0.1 m, and the depth range (start depth, end depth) is recorded.

[0031] The integral current value data area, drilling speed data area, and water injection amount data area respectively record data regarding the integral current value calculated from the measured current value, the drilling speed of the drilling head 10g during drilling, and the injection flow rate of drilling water.

[0032] The vibration data area records data regarding the direction of vibration (front / back, left / right, up / down) and the amplitude at each vibration frequency.

[0033] The probability information storage unit 24 stores probability information indicating the relationship between explanatory variables and probabilities. This probability information is stored during learning processing. The probability information storage unit 24 stores data indicating the probability of reaching the support layer for each explanatory variable.

[0034] As shown in FIG. 6, a graph 510 is recorded in which the probability is set on the vertical axis against the explanatory variable value on the horizontal axis. The explanatory variable is a variable for determining whether the wave reaches the support layer. In the present embodiment, the reduced shear wave velocity is used as the explanatory variable. The probability is the likelihood (probability) of reaching the support layer based on the explanatory variable values, which are the observed events.

[0035] (Evaluation support method) 4 to 7, an evaluation support method using the above-mentioned management device 20 will be described. In this embodiment, the reduced shear wave velocity is used as an explanatory variable to generate probability information for calculating the possibility of reaching the support layer.

[0036] (Learning process) First, the learning process will be described with reference to Fig. 4. In the learning process, probability information is generated using information recorded in the ground information storage unit 22 and the measurement information storage unit 23, i.e., measurement information from past excavation works.

[0037] Here, the control unit 21 of the management device 20 executes a process of associating the measurement information with the ground investigation results (step S11). Specifically, the learning unit 211 of the control unit 21 associates the measurement information with the ground investigation results (soil quality, N value) for each depth.

[0038] Next, the control unit 21 of the management device 20 executes a firmness determination process according to the ground investigation (step S12). Specifically, the learning unit 211 of the control unit 21 uses a firmness determination table to obtain an index value according to the soil type and N value. In this embodiment, if the firmness index is "3", it is determined to be "Actual result: firm", and if the firmness index is "1" or "2", it is determined to be "Actual result: not firm".

[0039] Next, the control unit 21 of the management device 20 executes an estimation process of the reduced shear wave velocity (step S13). Specifically, the learning unit 211 of the control unit 21 estimates the reduced shear wave velocity for each depth from the measurement information. For example, the technology described in Patent Document 1 can be used to calculate the reduced shear wave velocity.

[0040] Next, the control unit 21 of the management device 20 repeats the following process for each explanatory variable value while sequentially changing the explanatory variable value. This explanatory variable value is a reduced shear wave velocity provisionally set as a threshold value for determining that the support layer has been reached.

[0041] Here, the control unit 21 of the management device 20 executes a process of comparing the magnitude with the converted shear wave velocity (step S14). Specifically, the learning unit 211 of the control unit 21 compares the explanatory variable value of the processing target with the converted shear wave velocity, and records a judgment result according to the comparison result. If the "explanatory variable value" ≦ "converted shear wave velocity", the judgment result is recorded as "prediction: firm", and if the "explanatory variable value" > "converted shear wave velocity", the judgment result is recorded as "prediction: not firm". Note that if the "explanatory variable value" < "converted shear wave velocity", the judgment result may be "prediction: firm", and if the "explanatory variable value" ≧ "converted shear wave velocity", the judgment result may be "prediction: not firm".

[0042] Next, the control unit 21 of the management device 20 executes a counting process (step S15). Specifically, the learning unit 211 of the control unit 21 counts the number of "firm" and "not firm" predictions and actual results. In this case, a counting table 500 as shown in Figure 5 is generated. In this counting table 500, at depths that have been determined to be "firm" or "not firm" in the actual results, either "firm" or "not firm" in the prediction is counted and recorded. In the following, for all depths, it is counted to see which of the following combinations it belongs to. Here, "actual results: firm" is represented as "RH", "actual results: not firm" as "RS", "prediction: firm" as "PH", and "prediction: not firm" as "PS".

[0043] Next, the control unit 21 of the management device 20 executes a probability calculation process (step S16). Specifically, the learning unit 211 of the control unit 21 calculates the probability in the explanatory variables using the following formula.

[0044] P(RH|PH) =P(PH|RH) × P(RH) / P(PH) =P(PH|RH)×P(RH) / {P(PH|RH)×P(RH)+P(PH|RS)×P(RS)} =P(PH|RH)×P(RH) / {P(PH|RH)×P(RH)+P(RH|RS)×(1-P(RH))} =[N1 / (N1+N3)]×P(RH) / {[N1 / (N1+N3)]×P(RH)+[N2 / (N2+N4)]×(1-P(RH))}

[0045] Here, P(α|β) is the probability that event α occurs given that event β occurs. "P(RH)" is the probability that a solid bearing layer will be found based on the results of ground investigation up to a given depth.

[0046] This is then repeated until all explanatory variable values ​​have been considered. In this case, a graph 510 (probability information) shown in Fig. 6 is generated. Then, the control unit 21 of the management device 20 records the generated probability information in the probability information storage unit 24.

[0047] (Estimation processing) Next, the estimation process will be described with reference to FIG. Here, the control unit 21 of the management device 20 executes a measurement information acquisition process (step S21). Specifically, the acquisition unit 212 of the control unit 21 acquires new excavation measurement values ​​(water injection amount, excavation speed, integral current value, vibration direction, and amplitude value at each vibration frequency) measured by each measurement unit 11 when a new pile hole is excavated using the excavator 10. Then, the acquisition unit 212 records the excavation measurement values ​​according to the depth during the time period when the excavation actually proceeded in the measurement information storage unit 23 in association with the depth.

[0048] Next, the control unit 21 of the management device 20 executes an estimation process of the reduced shear wave velocity (step S22). Specifically, the estimation unit 213 of the control unit 21 calculates the reduced shear wave velocity in accordance with the measurement information.

[0049] Next, the control unit 21 of the management device 20 executes a probability acquisition process (step S23). Specifically, the estimation unit 213 of the control unit 21 acquires a probability corresponding to the reduced shear wave velocity (explanatory variable value) from the probability information (FIG. 6) recorded in the probability information storage unit 24. Then, the estimation unit 213 outputs the acquired probability to the display device H13.

[0050] According to this embodiment, the following effects can be obtained. (1-1) In this embodiment, the control unit 21 of the management device 20 executes a process of associating the measurement information with the ground investigation result (step S11). This makes it possible to associate the measurement information used for prediction with the actual hardness of the ground using the depth.

[0051] (1-2) In this embodiment, the control unit 21 of the management device 20 executes a process of determining hardness in response to the ground survey (step S12), thereby making it possible to identify the depth at which the ground can be determined to be hard.

[0052] (1-3) In this embodiment, the control unit 21 of the management device 20 executes a process of estimating the reduced shear wave velocity (step S13), thereby making it possible to calculate the reduced shear wave velocity for determining the stiffness.

[0053] (1-4) In this embodiment, the control unit 21 of the management device 20 executes a process of comparing the magnitude with the reduced shear wave velocity (step S14) and a process of calculating the probability (step S16). This makes it possible to generate information for expressing the reduced shear wave velocity as the likelihood that the reduced shear wave velocity has reached the hard support layer.

[0054] (1-5) In this embodiment, the control unit 21 of the management device 20 executes a process of acquiring measurement information (step S21), a process of estimating the reduced shear wave velocity (step S22), and a process of acquiring a probability (step S23). This allows the observed event to be expressed as the likelihood of reaching the support layer.

[0055] Figure 8(a) shows areas judged to have a firmness index of "3" (actual result: firm) against the depth on the vertical axis, based on the ground management data 220 (ground survey results) recorded in the ground information storage unit 22.

[0056] 8(b) shows the probability of being predicted as solid versus the depth on the vertical axis. It can be seen that the solid region 501 near the depth of "25m" coincides with the region 502 where the probability is 75% or higher.

[0057] Second embodiment In the first embodiment, one explanatory variable (reduced shear wave velocity) is expressed as the probability of reaching the hard support layer. In addition, it may be expressed as the probability of reaching the hard support layer by Bayesian updating. In this case, the probability when the second explanatory variable is added to the probability calculated by the first explanatory variable is calculated by Bayesian updating.

[0058] In this case, a learning process is performed using a second explanatory variable (e.g., vibration) in addition to the first explanatory variable (reduced shear wave velocity) to generate information (graph) showing the relationship between the second explanatory variable and probability.

[0059] The estimation process will be explained with reference to FIG. Here, the control unit 21 of the management device 20 executes the process of acquiring measurement information (step S31), similarly to step S21.

[0060] Next, the control unit 21 of the management device 20 executes a calculation process of the first explanatory variable (step S32). When the reduced shear wave velocity is used as the first explanatory variable, the estimation unit 213 of the control unit 21 calculates the reduced shear wave velocity according to the measurement information, similar to step S22.

[0061] Next, the control unit 21 of the management device 20 executes a process of acquiring the first probability (step S33). Specifically, the estimation unit 213 of the control unit 21 acquires the first probability corresponding to the reduced shear wave velocity (first explanatory variable value) from the first probability information recorded in the probability information storage unit 24.

[0062] Next, the control unit 21 of the management device 20 executes a calculation process of the second explanatory variable (step S34). Specifically, the estimation unit 213 of the control unit 21 acquires the second explanatory variable value. Next, the control unit 21 of the management device 20 executes a process of acquiring the second probability (step S35). Specifically, the estimation unit 213 of the control unit 21 acquires a second probability corresponding to the second explanatory variable value (e.g., a vibration value) in the second probability information recorded in the probability information storage unit 24.

[0063] Next, the control unit 21 of the management device 20 executes a Bayesian update process (step S36). Specifically, the estimation unit 213 of the control unit 21 calculates a posterior probability by performing a Bayesian update on the first probability (prior probability) calculated using the first explanatory variable, using the second probability based on the second explanatory variable.

[0064] According to this embodiment, in addition to the effects of the first embodiment, the following effects can be obtained. (2-1) The control unit 21 of the management device 20 executes a Bayesian update process (step S36). This makes it possible to more accurately calculate the probability of reaching the support layer by using the second probability calculated using the second explanatory variable (e.g., vibration) in comparison with the first probability calculated using the first explanatory variable (reduced shear wave speed).

[0065] This embodiment can be modified as follows: This embodiment and the following modifications can be combined with each other to the extent that there is no technical contradiction. In each of the above embodiments, the reduced shear wave velocity is used as the observed phenomenon. The observed phenomenon is not limited to the reduced shear wave velocity. Instead of the reduced shear wave velocity, other indices such as N value and soil quality may be used. Other excavation measurement values ​​such as the amount of water injected, the excavation speed, the integrated current value, the vibration direction and the amplitude value at each vibration frequency may be used as long as they are effective information for determining the hardness. In addition, the rate of change of the excavation speed, the rate of change of the vibration magnitude, etc. may be used.

[0066] In each of the above embodiments, the control unit 21 of the management device 20 performs the learning process. This process may be performed manually. In the second embodiment, Bayesian updating is performed based on different measurement information acquired in the same excavation. Alternatively, Bayesian updating may be performed based on measurement information acquired in different excavations. For example, variables in the measurement information in past excavations are used as the first explanatory variables. Then, variables in the measurement information in the preceding excavation at the current excavation site are used as the second explanatory variables. In this case, new probability information is generated based on the measurement information acquired at the current excavation site and the ground investigation results, and is recorded as the second probability information in the probability information storage unit 24. This allows the explanatory variables at different past excavation sites to be updated with the explanatory variables at the current excavation site.

[0067] Next, the technical ideas that can be understood from the above embodiment and other examples will be described below. (a) the control unit, Using the drilling measurement information, a reduced shear wave velocity is calculated; 2. The management device according to claim 1, wherein the reduced shear wave velocity is used as an explanatory variable.

[0068] (b) setting a first explanatory variable and a second explanatory variable in the excavation measurement information; A second probability of determining that the first explanatory variable has reached the support layer; and holding, for each of the first explanatory variables, first probability information indicating a possibility of reaching the support base, the first probability information being calculated by Bayesian estimation using the first, second, and third probabilities; A second probability of determining that the second explanatory variable has reached the support layer; and retaining second probability information indicating a possibility of reaching the support base, the second probability information being calculated by Bayesian estimation using the first, second, and third probabilities for each of the second explanatory variables; The management device according to claim 1 or (a), characterized in that a probability of reaching the support layer is determined by Bayesian updating using the first probability information and the second probability information.

[0069] (c) The management device according to (b), wherein the first explanatory variable and the second explanatory variable are different types of excavation measurement values ​​for the same pile hole. (d) The management device described in (b), characterized in that the first explanatory variable and the second explanatory variable are the same type of excavation measurement values ​​for excavations at different excavation work sites.

[0070] (e) The management device described in (d), characterized in that the first explanatory variable is an excavation measurement value from an older excavation period, and the second explanatory variable is an excavation measurement value from the same excavation work site as the current excavation. [Explanation of symbols]

[0071] 10...excavator, 11...measurement unit, 111...depth measuring instrument, 112...flow measuring instrument, 113...current measuring instrument, 114...vibration measuring instrument, 20...management device, 21...control unit, 211...measurement value management unit, 212...calculation unit, 213...estimation unit, 22...ground information memory unit, 23...measurement information memory unit, 24...probability information memory unit.

Claims

1. a measurement information storage unit that records excavation measurement values ​​during excavation of the ground; a ground information storage unit that records a ground hardness index obtained by the ground survey results; A control unit connected to a measurement unit that measures excavation measurement values, and an evaluation support device that supports evaluation of ground hardness, The control unit is a first probability of determining that the support layer has been reached in the stiffness index; and a second probability of determining that the supporting layer has been reached based on the drilling measurement; and a third probability of determining that the supporting layer has been reached in the excavation measurement value when the supporting layer has been reached based on an explanatory variable in the hardness index; storing probability information indicating a possibility of reaching the support base, the probability information being calculated by Bayesian estimation using the first, second, and third probabilities, for each of the explanatory variables; An evaluation support device characterized in that, when new excavation measurement values ​​are obtained in new excavation, the device uses the probability information to determine the probability of reaching the supporting layer based on the new excavation measurement values.

2. a measurement information storage unit that records excavation measurement values ​​during excavation of the ground; a ground information storage unit that records a ground hardness index obtained by the ground survey results; A method for supporting evaluation of ground hardness using an evaluation support device that supports evaluation of ground hardness, the method comprising: The control unit: a first probability of determining that the support layer has been reached in the stiffness index; and a second probability of determining that the supporting layer has been reached based on the drilling measurement; and a third probability of determining that the supporting layer has been reached in the excavation measurement value when the supporting layer has been reached based on an explanatory variable in the hardness index; storing probability information indicating a possibility of reaching the support base, the probability information being calculated by Bayesian estimation using the first, second, and third probabilities, for each of the explanatory variables; An evaluation support method characterized in that, when new excavation measurement values ​​are obtained in new excavation, the probability information is used to determine the probability of reaching the supporting layer based on the new excavation measurement values.

3. a measurement information storage unit that records excavation measurement values ​​during excavation of the ground; a ground information storage unit that records a ground hardness index obtained by the ground survey results; A program for supporting evaluation of ground hardness using an evaluation support device that supports evaluation of ground hardness, the program comprising: The control unit, a first probability of determining that the support layer has been reached in the stiffness index; and a second probability of determining that the supporting layer has been reached based on the drilling measurement; and a third probability of determining that the supporting layer has been reached in the excavation measurement value when the supporting layer has been reached based on an explanatory variable in the hardness index; storing probability information indicating a possibility of reaching the support base, the probability information being calculated by Bayesian estimation using the first, second, and third probabilities, for each of the explanatory variables; An evaluation support program characterized by using the probability information to function as a means for determining the probability of reaching the supporting layer based on the new excavation measurement values ​​when new excavation measurement values ​​are obtained in new excavation.

Images