WO2019176836A1 - Système de surveillance de pente, procédé de surveillance de pente et support d'enregistrement - Google Patents

Système de surveillance de pente, procédé de surveillance de pente et support d'enregistrement Download PDF

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Publication number
WO2019176836A1
WO2019176836A1 PCT/JP2019/009609 JP2019009609W WO2019176836A1 WO 2019176836 A1 WO2019176836 A1 WO 2019176836A1 JP 2019009609 W JP2019009609 W JP 2019009609W WO 2019176836 A1 WO2019176836 A1 WO 2019176836A1
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safety factor
current
slope
soil
risk level
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PCT/JP2019/009609
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English (en)
Japanese (ja)
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梓司 笠原
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日本電気株式会社
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    • E—FIXED CONSTRUCTIONS
    • E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
    • E02D—FOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
    • E02D17/00—Excavations; Bordering of excavations; Making embankments
    • E02D17/20—Securing of slopes or inclines

Definitions

  • the present invention relates to a slope monitoring system, a slope monitoring method, and a recording medium for monitoring slopes on topography such as mountains and valleys.
  • the safety factor is used as an index for evaluating the safety of the risk of collapse of slopes in terrain such as mountains and valleys, or the degree of no risk of slope collapse during heavy rain.
  • the safety factor is an index for evaluating the safety of a slope, and is represented by a ratio in which a sliding force for sliding down the slope is used as a denominator and a resistance force for preventing the sliding is used as a numerator. When this value is less than 1, that is, when the sliding force becomes larger than the resistance force, it is evaluated that there is a possibility of collapse.
  • Patent Documents 1 and 2 disclose this type of slope safety monitoring technology.
  • the slope monitoring system disclosed in Patent Document 1 changes the moisture content of the test layer measured from a test environment having a test layer that is substantially the same material layer as the material layer constituting the monitored slope. Measure each value of a predetermined analytical expression variable. Then, the slope monitoring system constructs a model that defines the relationship between the amount of water and the value of each analytical expression variable for each of the analytical expression variables based on the value of each analytical expression variable and the amount of water. The slope monitoring system calculates the value of each analytical expression variable when measuring the water content of the monitored slope using the constructed model, and based on the calculated value of each analytical expression variable, the slope stability analysis Calculate the safety factor of the slope to be monitored using the formula.
  • the disaster prediction system disclosed in Patent Document 2 acquires the amount of moisture in the soil at a specific point, and acquires the amount of water on the ground surface in a certain range including the specific point. And the disaster prediction system is based on the moisture content in the soil at a specific point and the moisture content on the ground surface in a certain range. Estimate the parameters representing the characteristics of the soil at any point included.
  • the disaster prediction system determines that there is a risk of landslide disaster in the area when the safety factor calculated using the slope stability analysis formula gradually decreases and approaches 1, and lives in the vicinity of the point By issuing evacuation advisories and evacuation instructions to residents, it is intended to realize timely warnings that do not miss time.
  • Patent Document 1 and Patent Document 3 calculate the value of each analytical expression variable when the moisture content of the monitored slope is measured using the constructed model, and the calculated analytical expression variable
  • the safety factor of the slope to be monitored is calculated using the slope stability analysis formula based on the value, and an alarm is issued if it falls below a predetermined threshold.
  • Patent Document 1 and Patent Document 3 do not disclose a configuration in which the degree of danger is determined in two stages, that is, the safety factor is equal to or less than a predetermined threshold value, and a gradual evaluation in more stages is possible.
  • Patent Document 2 discloses a configuration in which it is determined that there is a risk of a landslide disaster when the safety factor approaches 1, and an evacuation recommendation or evacuation instruction is issued. There is no disclosure of a configuration that can perform stepwise evaluation in more stages than two stages of near risk or not.
  • a slope monitoring system is based on a measurement unit that measures a soil parameter in association with a moisture content of a material layer that constitutes a monitored slope, and based on the measured soil parameter and the moisture content.
  • a modeling unit that generates a model equation, an optimal state water amount estimation unit that estimates the optimal amount of water with the maximum safety factor based on the soil parameter, and a current water amount on the monitored slope.
  • a moisture meter to be measured a current safety factor calculation unit that calculates a current safety factor using a current soil parameter estimated from the current moisture content based on the model equation; and the optimum state based on the model equation
  • An optimum state safety factor calculation unit that calculates the optimum factor safety factor using an optimum soil parameter estimated from the water content of the water, the current safety factor and the optimum factor safety factor
  • a risk output unit for outputting the risk level of the current relative to the said optimum state based on.
  • a soil layer is measured by associating a moisture content with a substance layer constituting a slope to be monitored, and a model formula is based on the measured soil parameter and the moisture content.
  • Generating an optimal amount of water with a maximum safety factor based on the soil parameter measuring the current amount of water on the slope to be monitored, and based on the model formula
  • Calculate the current safety factor using the current soil parameter estimated from calculate the optimal state safety factor using the optimal soil parameter estimated from the water content of the optimal state based on the model formula, Based on the current safety factor and the optimum safety factor, a current risk level based on the optimum state is output.
  • a recording medium that generates, on a computer, a model formula based on a soil parameter measured in association with a moisture content and a moisture content of a material layer constituting a monitoring target slope.
  • a process for estimating the optimum amount of water that maximizes the safety factor based on the soil parameter a process for obtaining the current amount of water on the slope to be monitored, and the current amount of water based on the model formula Processing to calculate the current safety factor using the estimated current soil parameter, processing to calculate the safety factor of the optimal state using the optimal soil parameter estimated from the water content of the optimal state based on the model formula And a process for outputting a current risk level based on the optimum state based on the current safety factor and the optimum factor safety factor.
  • the safety factor and the degree of danger that change according to the amount of moisture in the soil can be grasped step by step, and step by step warning and evacuation can be issued.
  • FIG. 1 is a block diagram illustrating an example of the configuration of the first embodiment.
  • FIG. 2 is a flowchart illustrating an example of a method for acquiring soil parameters related to slope stability of the measurement unit in FIG.
  • FIG. 3 is a flowchart showing details of the triaxial compression test (shear test) in step S11 of FIG.
  • FIG. 4 is a flowchart illustrating an example of a water addition test of the measurement unit in FIG.
  • FIG. 5 is a flowchart showing an example of the modeling operation of FIG. 1 and the operation of estimating the optimum amount of water.
  • FIG. 6 is a flowchart showing the safety factor calculation operation of the first embodiment.
  • FIG. 1 is a block diagram illustrating an example of the configuration of the first embodiment.
  • FIG. 2 is a flowchart illustrating an example of a method for acquiring soil parameters related to slope stability of the measurement unit in FIG.
  • FIG. 3 is a flowchart showing details of the triaxial compression test (shear test)
  • FIG. 7 is a diagram illustrating an example of the current risk level output based on the optimum state of the risk output unit of FIG.
  • FIG. 8 is a block diagram illustrating an example of the configuration of the second embodiment.
  • FIG. 9 is a diagram illustrating a first setting example of each risk level.
  • FIG. 10 is a diagram illustrating a second setting example of each risk level.
  • FIG. 11 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • FIG. 2 is a diagram illustrating a third setting example of each risk level.
  • FIG. 13 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • FIG. 14 is a diagram illustrating an example of a configuration of a computer that implements each unit of each embodiment.
  • Fs is the safety factor
  • ⁇ is the slope angle
  • C, W, u, and ⁇ are the soil parameters representing the properties of the soil, adhesive strength, mass weight, pore water pressure, and internal friction angle, respectively.
  • the shear stress of each divided piece (such as a lump) is represented by the lump weight W as the gravity applied to the divided piece and the slope gradient angle ⁇ (see the denominator of equation (1)). ).
  • the shear resistance of each divided piece is expressed by the adhesive force C of the divided piece (clump) and the resistance force ((Wu) cos ⁇ ⁇ tan ⁇ ) based on the vertical stress (of the equation (1)) See molecule).
  • the safety of a slope is evaluated by a safety factor Fs calculated using a ratio of a shear stress acting in the slope direction of each divided piece and a shear resistance force that prevents sliding due to the shear stress.
  • FIG. 1 is a block diagram showing an example of the configuration of the first embodiment.
  • the slope monitoring system 1 includes a measurement unit 11, a modeling unit 12, an optimum state moisture amount estimation unit 13, and a storage unit 14.
  • the measurement part 11 measures the soil parameter relevant to slope stability previously linked
  • the soil parameters related to the slope stability are the adhesive force C, the internal friction angle ⁇ , the pore water pressure u, and the clot weight W.
  • soil parameters for a specimen (soil mass) of one or more water amounts m 1 , m 2 ,..., Max which are created using a material layer (sediment) collected in advance from a slope to be monitored and have different water content ratios, That is, adhesive forces C 1 , C 2 ,...
  • FIG. 2 is a flowchart showing an example of a method for acquiring soil parameters related to the slope stability of the measurement unit in FIG.
  • the measuring unit 11 performs a triaxial compression test (shear test) to calculate the adhesive force C and the internal friction angle ⁇ (step S11).
  • FIG. 3 is a flowchart showing details of the triaxial compression test (shear test) in step S11 of FIG.
  • a test body soil mass
  • the soil of the test body is the same as the soil of the actual slope.
  • a plurality of test bodies are formed by changing the water content ratio of soil blocks made of soil having the same type, dry density and compaction as the soil on the actual slope.
  • the measuring unit 11 measures the water content of the prepared earth clot using a moisture meter (step S112).
  • the measurement unit 11 performs compression by setting the prepared soil block in a triaxial compression test apparatus including a stress sensor included in the measurement unit 11, and calculates the vertical stress ⁇ and shear stress ⁇ during compression. Measurement is performed (step S113).
  • step S114 the compression and stress measurement in steps S112 to S113 is repeated (step S114). Usually at least three compression and stress measurements are performed. Thereby, the normal stress data and the shear stress data at the time of shearing corresponding to at least a plurality of vertical loads are obtained for one soil block.
  • the measurement unit 11 obtains moisture amount data, and normal stress data and shear stress data during shearing corresponding to a plurality of vertical loads, for each of the soil blocks having different moisture contents.
  • the measuring unit 11 is obtained. Based on the normal stress data and the shear stress data, the adhesive force C and the internal friction angle ⁇ are calculated (step S12 in FIG. 2).
  • the shear strength s is represented by the sum of the adhesive force C of the soil and the resistance force ( ⁇ tan ⁇ ) based on the normal stress ⁇ acting on the shear surface.
  • tan ⁇ is an effective friction coefficient based on the internal friction angle ⁇ , which is one of the soil parameters representing the properties of the soil.
  • s C + ⁇ tan ⁇
  • the measuring unit 11 sets the shear stress at the time of fracture of the soils having moisture amounts m 1 , m 2 ,..., Max to the shear strength s 1 , s 2 ,. , ⁇ 1 , ⁇ 2 ,... ⁇ max .
  • the water content m 1, m 2 corresponds to ⁇ ⁇ ⁇ m max, adhesion C 1, C 2, ⁇ C max, internal friction angle phi 1, phi 2 ... ⁇ max can be calculated.
  • the measurement part 11 implements a hydration test using the test body (soil mass) which is the same as the soil used in the shear test in Step S11, that is, a soil (soil mass) made of soil of the same type, dry density and compaction degree ( Step S13).
  • FIG. 4 is a flowchart showing an example of the water addition test of the measurement unit in FIG.
  • a specimen made of soil of the same type, dry density and compaction as the soil used in the shear test and having a relatively low water content is prepared (Ste S131).
  • the test body a soil block adjusted so as to have a test layer with a lower water content ratio than a test body having a test layer with the minimum water content ratio among the test bodies used in the shear test is used.
  • the measurement unit 11 sets the prepared clot on a test machine including the moisture meter, the pore water pressure meter, and the weight meter included in the measurement unit 11, and measures the moisture content, the pore water pressure, and the clot weight. (Steps S132 to S134). As a result, at least the water content, pore water pressure, and soil weight of the soil mass in a state where the water content ratio before the addition is known are obtained.
  • moisture content data, pore water pressure data, and soil mass weight data of the soil mass in each state (before and after each addition) in the hydrolysis process until the soil is saturated are acquired.
  • saturated of the soil specifically means a state where water does not soak into the soil.
  • the measurement unit 11 has one or more water amounts m 1 , m 2 ,..., M max that differ in water content ratios created using the material layer (earth and sand) collected from the slope to be monitored by the water test.
  • Pore water pressures u 1 , u 2 ,... U max , and clot weights W 1 , W 2 ,... W max are acquired (step S14).
  • the water test is performed after the shear test, but the order of the test is not particularly limited.
  • the measurement unit 11 is, for example, a soil parameter obtained by measuring in advance in association with the water content m 1 , m 2 ,... M max , that is, adhesive force, internal friction angle, pore water pressure, and soil mass.
  • the weight and a plurality of moisture amounts m 1 , m 2 ,... M max may be associated with each other and stored in a storage unit (not shown).
  • the modeling unit 12 uses, for example, an adhesive force-moisture amount model, an internal friction angle-moisture amount model, based on an adhesive force, an internal friction angle, a clot weight, and a pore water pressure that are acquired from a storage unit (not shown).
  • the optimum state moisture amount estimation unit 13 calculates a safety factor for each moisture amount based on, for example, the adhesive force, the internal friction angle, the clot weight, and the pore water pressure obtained by linking each moisture amount from a storage unit (not shown). Estimate the optimal amount of water that maximizes the safety factor.
  • the storage unit 14 stores the model formula generated by the modeling unit 12 and the optimal amount of water estimated by the optimal state water amount estimation unit 13.
  • the slope monitoring system 1 also includes a moisture meter 15 installed on the monitored slope, and a current safety factor calculation unit 16 that calculates the current safety factor from the current moisture amount mt measured on the monitored slope. .
  • the slope monitoring system 1 includes an optimum state safety factor calculating unit 17 that calculates the safety factor of the optimum state from the amount of moisture in the optimum state, and the current state of the safety factor and the safety factor of the optimum state calculated based on the calculated current safety factor.
  • a risk output unit 18 for determining the risk is provided.
  • the current safety factor calculation unit 16 and the optimum state safety factor calculation unit 17 obtain in advance the slope length l of the slope to be monitored, the slope inclination angle ⁇ of the slope, and the slip layer depth d. Further, the current safety factor calculation unit 16 stores a soil parameter (current soil parameter) corresponding to the moisture amount mt measured on the monitoring target slope, that is, the adhesive force Ct, the internal friction angle ⁇ t, the pore water pressure ut, and the clot weight Wt. 14 based on the model formula stored in FIG.
  • the current safety factor calculation unit 16 calculates the current safety factor of the slope according to the equation (1) using the estimated soil parameters, that is, the adhesive force Ct, the internal friction angle ⁇ t, the pore water pressure ut, and the clot weight Wt.
  • the optimum state safety factor calculation unit 17 is a soil parameter (optimum soil parameter) corresponding to the optimum amount of water stored in the storage unit 14, that is, adhesive force Ct, internal friction angle ⁇ t, pore water pressure ut, and lump weight Wt. Is estimated based on the model formula stored in the storage unit 14. Then, the optimum state safety factor calculation unit 17 uses the soil parameters corresponding to the estimated optimum amount of water, that is, the adhesive force Ct, the internal friction angle ⁇ t, the pore water pressure ut, and the mass of the soil mass Wt according to the equation (1). Calculate the optimal safety factor.
  • the risk output unit 18 determines the risk of the slope to be monitored based on the calculated current safety factor and the optimum safety factor.
  • each component of the slope monitoring system of 1st embodiment shown in FIG. 1 and other embodiment mentioned later has shown the block of the functional unit. Part or all of the components of the slope monitoring system of each embodiment may be realized by any combination of a computer 50 and a program as shown in FIG. 14, for example.
  • the computer 50 includes the following configuration as an example.
  • CPU Central Processing Unit
  • ROM Read Only Memory
  • RAM Random Access Memory
  • a program 54 loaded into the RAM 53
  • a storage device 55 for storing the program 54
  • a drive device 57 that reads and writes the recording medium 56
  • Each component of each embodiment is implement
  • the modeling unit 12 uses the model based on the soil parameter and the water content measured by the CPU 51 that has acquired the program 54 in association with the water content based on the program 54.
  • a function may be realized by performing processing for generating an expression.
  • the optimum state water amount estimation unit 13 estimates the optimum amount of water with the maximum safety factor based on the above-mentioned soil parameters based on the program 54, and the CPU 51 that has acquired the program 54 calculates the optimum amount of water.
  • the function may be realized by performing processing stored in the storage device 55.
  • the CPU 51 that has acquired the program 54 performs processing for acquiring the current water content measured on the slope to be monitored based on the program 54.
  • CPU51 which acquired the program 54 performs the process which estimates a soil parameter (present soil parameter) based on said model formula memorize
  • CPU51 which acquired the program 54 performs the process which calculates the present safety factor using the estimated soil parameter based on the program54.
  • the function of the current safety factor calculation unit 16 may be realized by performing these processes.
  • the CPU 51 that has acquired the program 54 stores the optimum state stored in the storage device 55 based on the model formula stored in the storage device 55 based on the program 54.
  • the soil parameter (optimum soil parameter) is estimated from the water content of the soil.
  • CPU51 which acquired the program 54 performs the process which calculates the safety factor of an optimal state using the estimated soil parameter based on the program54.
  • the function of the optimum state safety factor calculation unit 17 may be realized by performing these processes.
  • the risk output unit 18 obtains the current risk level based on the optimum state based on the current safety factor and the optimum state safety factor calculated as described above based on the program 54 by the CPU 51 that has acquired the program 54.
  • a function may be realized by performing a process of outputting a level.
  • the program 54 that realizes the function of each component of each embodiment is stored in advance in the storage device 55, the ROM 52, or the RAM 53, for example, and may be configured to be read by the CPU 51 as necessary.
  • the program 54 may be supplied to the CPU 51 via the communication network 59, or may be stored in advance in the recording medium 56, and the drive device 57 may read the program and supply it to the CPU 51.
  • FIG. 5 is a flowchart showing the soil parameter modeling and optimum state determination operation of the first embodiment.
  • the modeling unit 12 constructs a soil mass-water content model and a pore water pressure-water content model from the soil mass weight and pore water pressure obtained in association with the moisture content. That is, the modeling unit 12 creates a model formula that expresses the mass of the mass (density) and the pore water pressure as a function of the water content (step S16).
  • the modeling unit 12 constructs an adhesive force-water amount model and an internal friction angle-water amount model from the adhesive force and the internal friction angle acquired in association with the water amount. That is, the modeling unit 12 creates a model formula that expresses the adhesive force and the internal friction angle as a function of the water content (step S17).
  • the optimum state moisture amount estimation unit 13 estimates the moisture amount in the optimum state using soil parameters obtained in association with a plurality of moisture amounts. Specifically, the optimum state moisture amount estimation unit 13 acquires the slope length, the slope angle, and the slip layer depth in advance based on the investigation result on the monitoring target slope, and is obtained in association with a plurality of moisture amounts.
  • the safety factor is calculated based on the formula (1) from the adhesive strength, the internal friction angle, the mass of the clot (density), and the pore water pressure. Then, from the increase / decrease of the safety factor with respect to the moisture content, the moisture content when the safety factor becomes the highest is estimated and set as the optimum moisture content (step S18).
  • the modeling unit 12 stores the created adhesive strength-water content model, internal friction angle-water content model, clot weight (density) -water content model, pore water pressure-water content model in the storage unit 14, and the optimal state moisture
  • the amount estimation unit 13 stores the optimal amount of water and the optimal state safety factor in the storage unit 14 (step S19).
  • FIG. 6 is a flowchart showing the risk degree calculation operation of the first embodiment.
  • the moisture meter 15 measures the current moisture content mt on the slope to be monitored (step S21).
  • the current safety factor calculation unit 16 substitutes the moisture amount mt measured on the monitoring target slope into the four model formulas stored in the storage unit 14, so that four analytical formulas at the time of measuring the moisture amount on the monitoring target slope are obtained.
  • variables current soil parameters
  • that is, adhesive force, internal friction angle, mass of clot (density), and pore water pressure are estimated (step S22).
  • the current safety factor calculation unit 16 acquires the slope length l of the slope to be monitored, the slope slope angle ⁇ of the slope, and the slip layer depth d in advance, and the estimated soil parameters, that is, the adhesive force Ct and the internal friction angle.
  • the current safety factor Fs of the slope is calculated by Equation (1) using ⁇ t, pore water pressure ut, and lump weight Wt (step S23).
  • the optimum state safety factor calculation unit 17 substitutes the estimated amount of water in the optimum state into the four model formulas stored in the storage unit 14 to obtain four analytical equation variables (optimum in the optimum state of the slope to be monitored).
  • (Soil parameters) that is, values of adhesive force, internal friction angle, soil mass weight (density), and pore water pressure are estimated (step S24).
  • the optimum state safety factor calculation unit 17 obtains in advance the slope length l of the slope to be monitored, the slope slope angle ⁇ of the slope, and the slip layer depth d, and provides four analytical formula variables in the optimum state of the slope to be monitored. That is, the safety factor Fsopt of the optimum state of the slope is calculated by the equation (1) using the adhesive force, the internal friction angle, the pore water pressure, and the mass of the clot (step S25).
  • FIG. 7 is a diagram illustrating an example of the current risk level output based on the optimum state of the risk output unit of FIG.
  • the risk output unit 18 displays the current safety factor Fs together with the optimum safety factor Fsop on a display unit (not shown) as shown in FIG. 7, for example (step S26).
  • the risk output unit 18 determines whether the measurement is completed, and if it is determined that the measurement is not completed, the process returns to step S21. Thus, the process of step S21 to S26 is repeated until a measurement is complete
  • the current safety factor Fs calculated from the amount of water mt measured on the slope to be monitored is displayed together with the safety factor Fsopt in the optimum state, so the safety factor Fsopt in the optimum state is displayed.
  • the current safety factor Fs which changes according to the amount of moisture in the soil, can be grasped step by step, and step-by-step warning and evacuation can be issued.
  • the risk output unit 18 has been described as displaying the current safety factor Fs together with the safety factor Fsopt in the optimum state.
  • the present invention is not limited to this, and various methods for outputting the risk level are conceivable.
  • a plurality of risk levels may be set, and the risk level determined from the current safety factor Fs based on the safety factor Fsopt in the optimum state may be output.
  • FIG. 8 is a block diagram showing the configuration of the second embodiment.
  • the risk output unit 18 includes a level range setting unit 181, a risk level determination unit 182, and a display unit 183.
  • the level range setting unit 181 sets a predetermined number of stages, for example, five risk levels in advance.
  • the level range setting unit 181 sets the range of the current safety factor Fs corresponding to each risk level based on the safety factor Fsopt in the optimum state.
  • the risk level determination unit 182 determines which of the risk levels the current safety factor Fs calculated from the amount of water mt measured on the slope to be monitored corresponds.
  • the display unit 183 displays a risk level corresponding to the current safety factor Fs.
  • FIG. 9 is a diagram illustrating a first setting example of each risk level.
  • the risk level determination unit 182 calculates the risk level D from the current safety rate Fs based on the safety factor Fsopt in the optimum state, and the level range setting unit 181 sets the range of the risk level D for each risk level. May be.
  • the risk level determination unit 182 calculates the risk level from the ratio of the current safety factor Fs and the optimum safety factor Fsopt as shown in the following equation (3).
  • D (Fs-1) / (Fsopt-1) (3)
  • the level range setting unit 181 sets a predetermined number of levels, for example, five levels as the risk level, and sets the range of the risk D calculated by the above equation (3) for each risk level. Set.
  • the level range setting unit 181 sets a predetermined number of levels, for example, five levels as the risk level, and sets the range of the risk D calculated by the above equation (3) for each risk level. Set.
  • the level range setting unit 181 sets the risk D range of each risk level as follows.
  • the risk level determination unit 182 Is used to calculate the risk level D, and the corresponding risk level is determined based on the risk level range set by the level range setting unit 181 and displayed on the display unit 183.
  • the second embodiment based on the current safety factor Fs and the optimum safety factor Fopt, for example, it is determined which of the five risk levels is set. Since it is displayed on the display unit, it is possible to clearly grasp the level of the risk level of the slope to be monitored, and to perform step-by-step warning and evacuation.
  • FIG. 10 is a diagram illustrating a second setting example of each risk level. As shown in FIG. 10, the second example is an example in which the width of the safety factor range at the high risk level is set narrower than the low risk level.
  • FIG. 11 is a block diagram showing the configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • the risk output unit 19 of the present modified example sets the ratio of the width of the safety factor range of each risk level so that the width of the safety factor range at the high risk level becomes narrower than the low risk level.
  • a range ratio setting unit 191 to be set is provided, and the level range setting unit 192 is different from the configuration of FIG. 8 in that the width of the safety factor range of each risk level is set based on the set ratio.
  • the range ratio setting unit 191 has a safety level at each risk level so that the range of the safety factor range at the high risk level is narrower than the low risk level for the N risk levels.
  • the range ratio setting unit 191 sets, for example, the width of level N, the width of level N ⁇ 1,..., The width of level 2 and the width of level 1 of 1: 2:. : N ratio is set.
  • the range ratio setting unit 191 sets the ratio of the range from the level 5 with the highest risk to the level 1 to 1: 2: 3: 4: 5.
  • the level range setting unit 192 sets the range of the risk level D of each risk level as follows so that the range from the level 5 with the highest risk level to the level 1 becomes 1: 2: 3: 4: 5. .
  • the risk level determination unit 182 Is used to calculate the risk level D, and the corresponding risk level is determined based on the risk level range set by the level range setting unit 192 and displayed on the display unit 183.
  • the range of the risk level with a high risk level is set narrower than the width of the risk level with a low risk level, so the possibility of false alarms at the highest risk level is reduced.
  • FIG. 12 is a diagram illustrating a third setting example of each risk level.
  • the third example is an example in which a caution safety factor that is the upper limit of the highest risk level is set.
  • FIG. 13 is a block diagram showing a configuration of a risk output unit that sets the width of each risk level as shown in FIG.
  • the degree-of-risk output unit 20 of the present modification includes a caution safety factor setting unit 201 and a range ratio setting unit 202.
  • the caution safety factor setting unit 201 sets the caution safety factor that is the upper limit of the risk level with the highest risk.
  • the range ratio setting unit 202 sets the width of the safety factor range of each risk level so that the width of the safety factor range at the risk level other than the risk level with the highest risk level becomes narrower as the risk level with the higher risk level. Set the ratio.
  • the level range setting unit 203 sets the width of the safety factor range of each risk level based on the attention safety factor and the set ratio.
  • the risk output unit 20 of this modification is different from the configurations of FIGS. 8 and 11 in these respects.
  • the width of the safety factor range equal to or higher than the second highest risk level is an example in which the range of the high risk level is set narrower than the low risk level as in the second example.
  • the range from the risk level N-1 having the second highest risk level to the risk level 1 is 2: 3: ...: N-1: N It is set to become the ratio.
  • the level range setting unit 203 has the risk level D of the highest risk level D.
  • the level range setting unit 203 sets the risk level D of each risk level so that the range of the risk level 1 from the risk level 4 having the second highest risk level becomes a ratio of 2: 3: 4: 5. Set the range.
  • the level range setting unit 203 sets the range of the risk level D of each risk level as follows.
  • the range of the risk level with the highest risk can be set arbitrarily, appropriate warning and evacuation can be issued according to the region and weather conditions.

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  • Life Sciences & Earth Sciences (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Paleontology (AREA)
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  • Pit Excavations, Shoring, Fill Or Stabilisation Of Slopes (AREA)

Abstract

L'invention concerne un système de surveillance de pente 1 qui, afin de permettre de saisir, de manière progressive, un facteur de sécurité et un degré de danger qui varient en fonction de la teneur en humidité dans le sol et de permettre l'émission d'avertissements et d'ordres d'évacuation en étapes, comprend : une unité de mesure 11 qui mesure les paramètres du sol en association avec une teneur en humidité concernant une couche de matériau constituant une pente devant être surveillée ; une unité de modélisation 12 qui génère une formule modèle sur la base des paramètres de sol mesurés et de la teneur en humidité ; une unité d'estimation de teneur en humidité d'état optimal 13 qui estime une teneur en humidité d'état optimal pour laquelle un facteur de sécurité maximal est obtenu ; un dispositif de mesure d'humidité 15 qui mesure la teneur en humidité actuelle dans la pente devant être surveillée ; une unité de calcul de facteur de sécurité actuel 16 qui calcule un facteur de sécurité à l'aide des paramètres de sol estimés à partir de la teneur en humidité actuelle ; une unité de calcul de facteur de sécurité d'état optimal 17 qui calcule un facteur de sécurité à l'aide des paramètres de sol estimés à partir de la teneur en humidité d'état optimal ; et une unité de sortie de degré de danger 18 qui délivre en sortie un niveau de degré de danger actuel dans lequel l'état optimal est utilisé comme référence.
PCT/JP2019/009609 2018-03-13 2019-03-11 Système de surveillance de pente, procédé de surveillance de pente et support d'enregistrement WO2019176836A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20220341827A1 (en) * 2019-06-04 2022-10-27 Nippon Telegraph And Telephone Corporation Parameter Determining Device, Parameter Determining Method, and Parameter Determining Program

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WO2015133076A1 (fr) * 2014-03-05 2015-09-11 日本電気株式会社 Système de réponse en cas de catastrophe, procédé de réponse en cas de catastrophe, dispositif de détection de catastrophe, et procédé de traitement associé
JP2016056505A (ja) * 2014-09-05 2016-04-21 西日本高速道路株式会社 羽根付き有孔鋼管を用いた地盤補強工法
WO2017047061A1 (fr) * 2015-09-14 2017-03-23 日本電気株式会社 Système de prédiction de catastrophe, dispositif de prédiction d'humidité, procédé de prédiction de catastrophe, et support d'enregistrement de programme

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015133076A1 (fr) * 2014-03-05 2015-09-11 日本電気株式会社 Système de réponse en cas de catastrophe, procédé de réponse en cas de catastrophe, dispositif de détection de catastrophe, et procédé de traitement associé
JP2016056505A (ja) * 2014-09-05 2016-04-21 西日本高速道路株式会社 羽根付き有孔鋼管を用いた地盤補強工法
WO2017047061A1 (fr) * 2015-09-14 2017-03-23 日本電気株式会社 Système de prédiction de catastrophe, dispositif de prédiction d'humidité, procédé de prédiction de catastrophe, et support d'enregistrement de programme

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20220341827A1 (en) * 2019-06-04 2022-10-27 Nippon Telegraph And Telephone Corporation Parameter Determining Device, Parameter Determining Method, and Parameter Determining Program

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