WO2018119880A1 - 一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置 - Google Patents

一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置 Download PDF

Info

Publication number
WO2018119880A1
WO2018119880A1 PCT/CN2016/113021 CN2016113021W WO2018119880A1 WO 2018119880 A1 WO2018119880 A1 WO 2018119880A1 CN 2016113021 W CN2016113021 W CN 2016113021W WO 2018119880 A1 WO2018119880 A1 WO 2018119880A1
Authority
WO
WIPO (PCT)
Prior art keywords
rainfall
slope
rainfall intensity
target
soil
Prior art date
Application number
PCT/CN2016/113021
Other languages
English (en)
French (fr)
Inventor
柳成荫
许春川
陆钊
Original Assignee
柳成荫
许春川
陆钊
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 柳成荫, 许春川, 陆钊 filed Critical 柳成荫
Priority to CN201680084612.0A priority Critical patent/CN109074719A/zh
Priority to PCT/CN2016/113021 priority patent/WO2018119880A1/zh
Publication of WO2018119880A1 publication Critical patent/WO2018119880A1/zh

Links

Images

Classifications

    • GPHYSICS
    • G08SIGNALLING
    • G08BSIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02Alarms for ensuring the safety of persons
    • G08B21/10Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes

Definitions

  • the invention relates to the field of internet of things, and particularly relates to an early warning method and device for rainfall type landslide based on rainfall and soil moisture.
  • the prior art also has an early warning scheme for rainfall landslides. They only analyze the slope stability with a total rainfall or rainfall intensity, and then provide early warning based on the analysis results.
  • the embodiment of the invention provides an early warning method and device for rainfall-type landslide based on rainfall and soil moisture, which can accurately predict rainfall landslides.
  • the first aspect of the invention discloses an early warning method for a rainfall type landslide based on rainfall and soil moisture, the method comprising:
  • the warning information is issued.
  • the method before the obtaining the current rainfall intensity and the soil moisture of the slope surface, the method further includes:
  • the target rainfall intensity is determined based on the rainfall intensity and the rainfall duration curve.
  • the soil structural parameters of the slope include the type of soil layer and the depth of each type of soil layer.
  • the method further includes:
  • the method further includes:
  • the target rainfall intensity is fitted to the rainfall duration to determine the rainfall intensity versus rainfall duration curve.
  • the formula of the rainfall intensity and rainfall duration curve is:
  • the second aspect of the invention discloses an early warning device for a rainfall type landslide based on rainfall and soil moisture, and the early warning device for the rainfall type landslide comprises:
  • a determining unit configured to determine whether the soil moisture is greater than a target soil moisture threshold when the current rainfall intensity is greater than a target rainfall intensity
  • the issuing unit is configured to issue the early warning information when the soil moisture threshold is greater than the target soil moisture threshold.
  • the early warning device for the rainfall type landslide further includes a modeling unit and a determining unit;
  • the acquiring unit is configured to acquire a soil layer structure parameter and a soil parameter of the slope
  • the modeling unit is configured to establish a model of the slope according to the soil layer structure parameter and the soil parameter;
  • the determining unit is configured to determine an initial safety factor of the slope according to a model of the slope
  • the determining unit is further configured to determine a rainfall intensity and a rain duration curve according to the preset target safety factor and the initial safety factor;
  • the determining unit is further configured to determine a target rainfall intensity according to the rainfall intensity and a rainfall duration curve.
  • the obtaining unit is further configured to acquire historical data of rainfall intensity of the area to which the slope belongs;
  • the determining unit is further configured to determine a target rainfall intensity according to the historical data of the rainfall intensity
  • the determining unit is further configured to determine, according to a preset target safety factor, the initial safety factor The duration of rainfall corresponding to each target rainfall intensity;
  • the determining unit is further configured to fit the target rainfall intensity to the rainfall duration to determine the rainfall intensity and rainfall duration curve.
  • the formula for the rainfall intensity and rainfall duration curve is:
  • the issuing unit includes an acquiring subunit, determining a subunit, and releasing Subunit
  • the acquiring subunit is configured to acquire a displacement amount of the target monitoring point
  • the determining subunit is configured to determine an early warning type according to the displacement amount and the displacement amount threshold of the target monitoring point;
  • the issuing subunit is configured to issue the alert type.
  • the third aspect of the invention discloses an early warning device for a rainfall type landslide based on rainfall and soil moisture, and the early warning device for the rainfall type landslide comprises:
  • a processor coupled to the memory
  • the processor invokes the executable program code stored in the memory to perform the method of the third aspect.
  • the current rainfall intensity and the soil moisture of the slope surface are obtained; when the current rainfall intensity is greater than the target rainfall intensity, determining whether the soil moisture is greater than the target soil a humidity threshold; when the soil moisture threshold is greater than the target soil humidity threshold, the warning information is issued. It can be seen that by implementing the embodiments of the present invention, combined with rainfall and soil moisture, an accurate warning can be made for rainfall-type landslides.
  • 1a is a schematic flow chart of an early warning method for a rainfall type landslide based on rainfall and soil moisture according to an embodiment of the present invention
  • FIG. 1b is a schematic diagram of a numerical analysis model of a slope and a pseudo-monitoring point according to an embodiment of the present invention
  • FIG. 1c is a schematic diagram of an initial safety factor of a slope according to an embodiment of the present invention.
  • FIG. 1d is a graph of fitting a rainfall intensity and rainfall duration data according to an embodiment of the present invention.
  • FIG. 1e is a schematic diagram of an initial total stress of a slope according to an embodiment of the present invention.
  • FIG. 1f is a fitting curve diagram of a safety factor and an A-point displacement increment according to an embodiment of the present invention
  • FIG. 1g is a fitting curve diagram of a safety factor and a C-point displacement increment according to an embodiment of the present invention
  • 1h is a schematic structural diagram of a rainfall type landslide warning system according to an embodiment of the present invention.
  • FIG. 1 is a schematic plan view showing a plane arrangement of a landslide monitoring point according to an embodiment of the present invention
  • FIG. 1 is a summary of a wire sensor type and a detail thereof arranged inside a pipe according to an embodiment of the present invention
  • FIG. 2 is a schematic flow chart of another early warning method for rainfall-type landslides based on rainfall and soil moisture according to an embodiment of the present invention
  • FIG. 3 is a schematic structural diagram of an early warning device for a rainfall type landslide based on rainfall and soil moisture according to an embodiment of the present invention
  • FIG. 4 is another rainfall type landslide based on rainfall and soil moisture according to an embodiment of the present invention. Schematic diagram of the early warning device;
  • FIG. 5 is a schematic diagram showing the physical structure of an early warning device for a rainfall type landslide based on rainfall and soil moisture according to an embodiment of the present invention.
  • the embodiments of the present invention provide an early warning method and device for rainfall-type landslides based on rainfall and soil moisture, which can accurately predict rainfall landslides.
  • an early warning method for rainfall-type landslides based on rainfall and soil moisture comprising: obtaining current rainfall intensity and soil moisture on a slope surface; when the current rainfall intensity is greater than When the target rainfall intensity is determined, it is determined whether the soil moisture is greater than a target soil moisture threshold; when the soil moisture threshold is greater than the target soil moisture threshold, an early warning information is issued.
  • FIG. 1a illustrates an early warning method for rainfall-type landslides based on rainfall and soil moisture according to an embodiment of the present invention.
  • the method specifically includes:
  • the slope needs to be modeled to obtain the target rainfall intensity and the target rainfall humidity.
  • the slope needs to be surveyed to obtain the soil structural parameters and soil parameters of the slope.
  • the soil layer of a slope is divided into four layers: artificial fill layer, silty clay layer, gravel clay layer and fully weathered granite, then it is necessary to measure the depth of each soil layer and each soil. The relevant parameters of the layer.
  • the following table shows the seepage analysis parameters for each soil layer of a slope.
  • the types of parameters that need to be acquired include, but are not limited to, the types shown in the following table.
  • the table below shows the soil parameters for a slope slope stability analysis.
  • the types of parameters that need to be obtained include, but are not limited to, the types shown in the table below.
  • the relevant parameters are input into the finite element analysis software to establish a finite element model of the slope.
  • the initial safety factor is then calculated from the finite element model.
  • a section of the slope geological survey of the landslide monitoring area can be drawn, as shown in Figure 1b.
  • the proposed monitoring points A, B, C and D are indicated in Figure 1b, with points A and C monitoring the horizontal displacement.
  • the boundary conditions of the slope model are set: the interface between the fully weathered granite and the strongly weathered granite is set as the groundwater boundary, and the left and right sides of the slope are set as impervious borders.
  • the surface of the slope is set as the rainfall infiltration boundary, and the rainfall at the slope is taken according to the law of the rainfall intensity.
  • the initial average seepage condition of the slope was obtained by using the average annual rainfall of 2000 mm in the area where the slope was located.
  • the slope was observed by SEEP/W software and then introduced into the SLOPE/W module.
  • the slope was finally obtained by the Morgenstern-Price method and the Bishop method.
  • the initial safety factor Fs is 1.340, as shown in Figure 1c.
  • the monitoring points for slopes are generally placed on the top, bottom and slope of the slope. There is no limit to the specific location. It can be understood that after modeling, the slope model can be simulated by using different rainfall intensity of the slope as input conditions.
  • the safety factor of the slope when the safety factor of the slope is reduced from 1.34 to a critical value of 1.2, it can be analyzed.
  • the duration of rainfall corresponding to different rainfall intensities is as follows (rainfall intensity - rainfall duration curve data).
  • the relationship between the rainfall intensity shown in the above table and the duration of rainfall can be fitted, and the rainfall intensity-rainfall duration curve of the slope can be fitted by MATLAB.
  • the rainfall time corresponding to the rainfall intensity exceeding 4.5 mm/h is 218 h, and the corresponding formula results are:
  • the critical cumulative rainfall can be obtained according to the curve.
  • the cumulative rainfall at the data point is obtained when the rainfall intensity I is between 2 mm/h and 4 mm/h.
  • the average value is 749mm.
  • the slope can be determined to enter the displacement warning stage.
  • the finite element numerical analysis method can be used to obtain the displacement warning threshold of the slope to be monitored.
  • the finite element numerical method can be used to analyze the change in the safety factor of the same slope under rainfall.
  • the horizontal direction of the left and right ends of the slope is displaced to zero, and the vertical direction is free; the horizontal and vertical displacements of the lower boundary of the slope are both zero, and the constitutive model of the elastic-plastic molar coulomb failure criterion is adopted, and
  • the initial stress-strain module of the slope is established by the seepage state of the slope with an annual rainfall of 2000 mm.
  • the fluid-solid coupling analysis of the slope is carried out, and the displacement information of the slope monitoring point is obtained, and the warning threshold of the slope displacement is drawn.
  • the typical rainfall when the rainfall warning threshold is obtained is applied to the rainfall infiltration boundary of the slope.
  • the slope of each rainfall stage is obtained.
  • the safety factor and the displacement increment data corresponding to the monitoring points A and C are shown in the following table.
  • the risk factor p of the slope is defined, that is, the reduction value of the slope safety factor caused by rainfall and the ratio of the safety reserve value of the slope.
  • F s represents the stability coefficient of the initial state of the slope, the slope is 1.34;
  • F si represents the change of the safety factor of the slope when it actually suffers from rainfall;
  • F 0 represents the critical safety factor of the slope, and the slope takes 1.20.
  • the following table shows the staged warning of the A-point at the top of the slope.
  • the following table shows the staged warning of the C-point at the bottom of the slope.
  • the starting points A1, A2, A3 and A4 of each displacement stage of the slope top monitoring point A are marked, as shown in Fig. 1f.
  • the starting points C1, C2, C3 and C4 of each displacement stage of the slope bottom monitoring point C are marked, as shown in Fig. 1g.
  • the points A1 and C1 are the starting points of the slope entering the uniform displacement stage, and the points A2 and C2 are the starting points of the slope entering the initial acceleration displacement stage, and the points A3 and C3 are edges.
  • the slope enters the starting point of the mid-acceleration displacement phase, and the A4 and C4 points are the starting points of the slope entering the acceleration displacement stage.
  • the finite element calculation results of the slope model can obtain the safety factor, the rainfall of the slope, the displacement of the slope monitoring point and the water content of the slope monitoring point.
  • the rainfall intensity-rainfall duration curve, and then the rainfall warning threshold and displacement warning threshold of the proposed slope under different safety factors are given.
  • the issuing the warning information includes: acquiring a displacement amount of the target monitoring point; determining an early warning type according to the displacement amount and the displacement amount threshold of the target monitoring point; and issuing the early warning type.
  • early warning include attention level, warning level, warning level and alarm level.
  • the current rainfall intensity in steps S101 and 102 and the soil moisture on the slope surface can be obtained by the monitoring system.
  • the network architecture diagram may include a sensor, a wireless sensor terminal node, a wireless sensor routing node, a wireless sensor gateway node, and a remote monitoring center.
  • the sensor includes a wired sensor and a wireless sensor, and the wired sensor and the wireless sensor pass through Through the serial port connection, combined into a wireless sensor terminal node, the monitoring data is transmitted to the base station, and the base station connects to the remote monitoring and early warning center through the wireless mobile phone network module to realize the real-time remote transmission of the monitoring data, and builds a rainfall type landslide based on the wireless sensor network.
  • the early warning system is a real, feasible and effective implementation of remote real-time monitoring of slope landslides.
  • a multi-hop tree cluster type wireless sensor monitoring network is established, wherein the wireless sensor terminal node I, the terminal node II and the terminal node III send the collected data to the routing node I, the wireless sensor terminal node IV and the terminal.
  • the node V sends the collected data to the routing node II, and the routing node I and the routing node II forward the aggregated data to the gateway node, and the gateway node sends the data to the remote monitoring center through the wireless communication of the mobile phone network.
  • the remote monitoring center can be the execution body of S101-S103.
  • wireless sensor terminal nodes routing nodes and gateway nodes
  • the wireless sensor terminal node is an important component, which is relatively complex, and is composed of an acquisition module, a processor module, a wireless communication function module, and an intelligent power module.
  • the wireless sensor routing node has no acquisition module that can be connected to the wired sensor. Its function is to aggregate the data transmitted by the terminal node and forward it to the gateway node. At the same time, the routing node can also transmit the instruction sent by the gateway node to the terminal node.
  • the internal sensor layout plan for the slope pipeline is planned.
  • the on-site installation layout is as follows: A tilt sensor is embedded in the inclined tube at the A and A' points of the slope to measure the horizontal displacement, and the inclined tube has been embedded. At the top of the slope, there is a hole E parallel to A and A'. At this monitoring point, a PVC pipe is drilled on the side to place the liquid level sensor. The PVC pipe has been buried. Drill a 2m borehole at the B and B' points to embed the soil moisture sensor to measure soil saturation. The location of the drill point in the slope is shown.
  • a tilt sensor is embedded in the inclined tube at points C and C' to measure the horizontal displacement of the soil layer, and the inclined tube has been embedded.
  • a PVC pipe with a side-drilled hole is placed at point D to place the liquid level sensor, thereby obtaining the water table at the measuring point, and the PVC pipe has been buried.
  • the whole rainfall landslide warning system consists of wireless sensor terminal nodes, routing nodes, gateway nodes and remote monitoring and early warning centers.
  • the wireless sensors are used to transmit data to realize the monitoring and warning of rainfall landslides.
  • an early warning method for a rainfall type landslide based on rainfall and soil moisture comprising:
  • the soil layer structure parameters and soil parameters can be obtained by surveying the slope.
  • the area can be an administrative area, such as belonging to a town, or a city, and so on.
  • the target rainfall intensity is generally within the range of historical data.
  • S212 Determine an early warning type according to the displacement amount and the displacement amount threshold of the target monitoring point; and issue the early warning type.
  • the current rainfall intensity and the soil moisture of the slope surface are obtained; when the current rainfall intensity is greater than the target rainfall intensity, determining whether the soil moisture is greater than the target soil moisture threshold; When the soil moisture threshold is greater than the target soil humidity threshold, the warning information is issued. It can be seen that by implementing the embodiments of the present invention, combined with rainfall and soil moisture, an accurate warning can be made for rainfall-type landslides.
  • FIG. 3 depicts a specific structure of a rainfall type landslide warning device 300 based on rainfall and soil moisture, wherein the device 300 can be a remote monitoring center in FIG. 1h, and the device 300 includes:
  • the obtaining unit 301 is configured to acquire the current rainfall intensity and the soil moisture of the slope surface
  • the determining unit 302 is configured to determine, when the current rainfall intensity is greater than the target rainfall intensity, whether the soil moisture is greater than a target soil moisture threshold;
  • the issuing unit 303 is configured to issue the early warning information when the soil moisture threshold is greater than the target soil moisture threshold.
  • the obtaining unit 301, the determining unit 302, and the issuing unit 303 may be used to perform the method described in the steps S101 to S103 in the first embodiment. For details, refer to the description of the method in the embodiment 1, and details are not described herein again.
  • FIG. 4 depicts a specific structure of a rainfall type landslide warning device based on rainfall and soil moisture, wherein the device 400 may be a remote monitoring center in FIG. 1h, and the device 400 includes:
  • An obtaining unit 401 configured to acquire a soil layer structure parameter and a soil parameter of the slope
  • a modeling unit 404 configured to establish a model of the slope according to the soil layer structure parameter and the soil parameter
  • a determining unit 405, configured to determine an initial safety factor of the slope according to a model of the slope
  • the obtaining unit 401 is further configured to acquire historical data of the rainfall intensity of the area to which the slope belongs;
  • the determining unit 405 is further configured to determine a target rainfall intensity according to the historical data of the rainfall intensity; and configured to determine a rain duration corresponding to each target rainfall intensity according to the preset target safety factor and the initial safety factor; a unit, which is further configured to fit the target rainfall intensity to the rainfall duration to determine the rainfall intensity and rainfall duration curve; and to determine a target rainfall intensity according to the rainfall intensity and rainfall duration curve ;
  • An obtaining unit 401 configured to acquire current rainfall intensity and soil moisture on a slope surface
  • the determining unit 402 is configured to determine, when the current rainfall intensity is greater than the target rainfall intensity, whether the soil moisture is greater than a target soil moisture threshold;
  • the issuing unit 403 is configured to issue the early warning information when the soil moisture threshold is greater than the target soil moisture threshold.
  • the issuing unit 403 includes an obtaining subunit, a determining subunit, and a publishing subunit;
  • the acquiring subunit is configured to acquire a displacement amount of the target monitoring point
  • the determining subunit is configured to determine an early warning type according to the displacement amount and the displacement amount threshold of the target monitoring point;
  • the issuing subunit is configured to issue the alert type.
  • the obtaining unit 401, the determining unit 402, the issuing unit 403, the modeling unit 404, and the determining unit 405 can be used to perform the methods described in steps S201 to S214 in Embodiment 2. For details, see Embodiment 2 for the method. The description is not repeated here.
  • the device 500 includes a CPU 501, a memory 502, and a bus 503.
  • the CPU 501 executes a program that is stored in the memory 502 in advance, and the execution process specifically includes:
  • the warning information is issued.
  • the performing process further includes:
  • the target rainfall intensity is determined based on the rainfall intensity and the rainfall duration curve.
  • the performing process further includes:
  • the method further includes:
  • the target rainfall intensity is fitted to the rainfall duration to determine the rainfall intensity versus rainfall duration curve.
  • the issuing the warning information includes:
  • the current rainfall intensity and the soil moisture of the slope surface are obtained; when the current rainfall intensity is greater than the target rainfall intensity, determining whether the soil moisture is greater than a target soil moisture threshold; When the soil moisture threshold is greater than the target soil moisture threshold, the warning information is issued. It can be seen that by implementing the embodiments of the present invention, combined with rainfall and soil moisture, an accurate warning can be made for rainfall-type landslides.
  • each step method flow can be implemented based on the structure of the device.
  • each unit function can be implemented based on the structure of the apparatus.
  • the disclosed apparatus may be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be electrical or otherwise.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
  • the technical solution of the present invention which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium.
  • a number of instructions are included to cause a computer device (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a U disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, and the like. .

Abstract

一种基于降雨量及土壤湿度的降雨型滑坡的预警方法及装置(300,400,500)。所述方法包括:获取当前降雨强度以及边坡表面的土壤湿度(S101);当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值(S102);当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息(S103)。可见,通过实施本方法,结合降雨强度和土壤湿度能够对降雨型滑坡进行准确预警。

Description

一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置 技术领域
本发明涉及物联网领域,具体涉及了一种基于降雨量及土壤湿度的降雨型滑坡的预警方法及装置。
背景技术
我国是一个山体滑坡频繁的国家,山体滑坡破坏基础设施,给国家现代化建设和人民的生活造成了严重的影响。每年全国有相当多的城市及村镇遭受山体滑坡的危害,每年造成的经济损失不计其数。据统计,约90%的山体滑坡与降雨有关,如何使用降雨信息这一滑坡诱导因素进行预警成为目前亟待解决的问题。
现有技术也有降雨型滑坡的预警方案,他们只以一个总降雨量或者降雨强度对边坡稳定性进行分析,然后根据分析结果进行预警。
需要指出的是,仅仅以总降雨量或者降雨强度对边坡稳定性进行分析是片面的,得到的分析结果导致预警不准确。
发明内容
本发明实施例提供了一种基于降雨量及土壤湿度的降雨型滑坡的预警方法及装置,能够对降雨型滑坡进行准确预警。
本发明第一方面公开了一种基于降雨量及土壤湿度的降雨型滑坡的预警方法,所述方法包括:
获取当前降雨强度以及边坡表面的土壤湿度;
当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
结合本发明第一方面,在本发明第一方面的第一种可行的实施方式中,所述获取当前降雨强度以及边坡表面的土壤湿度之前,所述方法还包括:
获取所述边坡的土层结构参数和土体参数;
根据所述土层结构参数和所述土体参数建立所述边坡的模型;
根据边坡的模型确定所述边坡的初始安全系数;
根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线;
根据所述降雨强度与降雨持续时间曲线确定目标降雨强度。
其中,需要指出的是,所述边坡的土层结构参数包括土层的类型以及每种类型的土层的深度。
结合本发明第一方面的第一种可行的实施方式,在本发明第一方面的第二种可行的实施方式中,所述根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线之前,所述方法还包括:
获取所述边坡所属区域的降雨强度的历史数据;
根据所述降雨强度的历史数据确定目标降雨强度;
所述根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线之前,所述方法还包括:
根据预设的目标安全系数、所述初始安全系数确定与每个目标降雨强度相对应的降雨持续时间;
将所述目标降雨强度与所述降雨持续时间进行拟合以确定所述降雨强度与降雨持续时间曲线。
结合本发明第一方面的第二种可行的实施方式,在本发明第一方面的第三种可行的实施方式中,所述降雨强度与降雨持续时间曲线的公式为:
Figure PCTCN2016113021-appb-000001
其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和b是根据边坡土层结构参数和土体参数确定的;
其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时, 随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定。
结合本发明第一方面或第一方面的上述任一种可能的实现方式,在本发明第一方面的第四种可行的实施方式中,所述发布预警信息包括:
获取目标监测点的位移量;
根据所述目标监测点的位移量与位移量阈值确定预警类型;
发布所述预警类型。
本发明第二方面公开了一种基于降雨量及土壤湿度的降雨型滑坡的预警装置,所述降雨型滑坡的预警装置包括:
获取单元,用于获取当前降雨强度以及边坡表面的土壤湿度;
判断单元,用于当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
发布单元,用于当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
结合本发明第二方面,在本发明第二方面的第一种可行的实施方式中,所述降雨型滑坡的预警装置还包括建模单元和确定单元;
所述获取单元,用于获取所述边坡的土层结构参数和土体参数;
所述建模单元,用于根据所述土层结构参数和所述土体参数建立所述边坡的模型;
所述确定单元,用于根据边坡的模型确定所述边坡的初始安全系数;
所述确定单元,还用于根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线;
所述确定单元,还用于根据所述降雨强度与降雨持续时间曲线确定目标降雨强度。
结合本发明第二方面第一种可行的实施方式,在本发明第二方面的第二种可行的实施方式中,
所述获取单元,还用于获取所述边坡所属区域的降雨强度的历史数据;
所述确定单元,还用于根据所述降雨强度的历史数据确定目标降雨强度;
所述确定单元,还用于根据预设的目标安全系数、所述初始安全系数确定 与每个目标降雨强度相对应的降雨持续时间;
所述确定单元,还用于将所述目标降雨强度与所述降雨持续时间进行拟合以确定所述降雨强度与降雨持续时间曲线。
结合本发明第二方面的第二种可行的实施方式,所述降雨强度与降雨持续时间曲线的公式为:
Figure PCTCN2016113021-appb-000002
其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和b是根据边坡土层结构参数和土体参数确定的;
其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时,随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定。
结合本发明第二方面或第二方面的上述任一种可行的实施方式,在本发明第二方面的第四种可行的实施方式中,所述发布单元包括获取子单元、确定子单元和发布子单元;
所述获取子单元,用于获取目标监测点的位移量;
所述确定子单元,用于根据所述目标监测点的位移量与位移量阈值确定预警类型;
所述发布子单元,用于发布所述预警类型。
本发明第三方面公开了一种基于降雨量及土壤湿度的降雨型滑坡的预警装置,所述降雨型滑坡的预警装置包括:
存储有可执行程序代码的存储器;
与所述存储器耦合的处理器;
所述处理器调用所述存储器中存储的所述可执行程序代码,执行如第三方面所述的方法。
本发明实施例的方案中,获取当前降雨强度以及边坡表面的土壤湿度;当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤 湿度阈值;当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。可见,通过实施本发明实施例,结合降雨量和土壤湿度能够对降雨型滑坡进行准确预警。
附图说明
为了更清楚地说明本发明实施例中的技术方案,下面将对实施例中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。
图1a为本发明实施例提供的一种基于降雨量及土壤湿度的降雨型滑坡的预警方法的流程示意图;
图1b为本发明实施例提供的一种边坡数值分析模型与拟监测点示意图;
图1c为本发明实施例提供的一种边坡初始安全系数示意图;
图1d为本发明实施例提供的一种降雨强度与降雨持续时间数据拟合曲线图;
图1e为本发明实施例提供的一种边坡初始总应力示意图;
图1f为本发明实施例提供的一种安全系数与A点位移增量的拟合曲线图;
图1g为本发明实施例提供的一种安全系数与C点位移增量的拟合曲线图;
图1h为本发明实施例提供的一种降雨型滑坡预警系统的架构示意图;
图1i为本发明实施例提供的一种滑坡监测点平面布置示意图;
图1j为本发明实施例提供的一种管道内部布置的有线传感器类型及其细节汇总表;
图2为本发明实施例提供的另一种基于降雨量及土壤湿度的降雨型滑坡的预警方法的流程示意图;
图3为本发明实施例提供的一种基于降雨量及土壤湿度的降雨型滑坡的预警装置的结构示意图;
图4为本发明实施例提供的另一种基于降雨量及土壤湿度的降雨型滑坡 的预警装置的结构示意图;
图5为本发明实施例提供的一种基于降雨量及土壤湿度的降雨型滑坡的预警装置的物理结构示意图。
具体实施方式
本发明实施例提供了本发明实施例提供了一种基于降雨量及土壤湿度的降雨型滑坡的预警方法及装置,能够对降雨型滑坡进行准确预警。
为了使本技术领域的人员更好地理解本发明方案,下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚地描述,显然,所描述的实施例是本发明一部分的实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都应当属于本发明保护的范围。
本发明说明书、权利要求书和附图中出现的术语“第一”、“第二”和“第三”等是用于区别不同的对象,而并非用于描述特定的顺序。此外,术语“包括”和“具有”以及它们任何变形,意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元,而是可选地还包括没有列出的步骤或单元,或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
在本发明的一个实施例中公开了一种基于降雨量及土壤湿度的降雨型滑坡的预警方法,所述方法包括:获取当前降雨强度以及边坡表面的土壤湿度;当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
请参阅图1a,图1a是本发明一个实施例提供的一种基于降雨量及土壤湿度的降雨型滑坡的预警方法。该方法具体包括:
S101、获取当前降雨强度以及边坡表面的土壤湿度;
S102、当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
S103、当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
需要指出的是,在执行S101至S103的步骤之前,还需要对边坡进行建模,以获取目标降雨强度和目标降雨湿度。
可以理解的是,在对边坡建模之前,需要对边坡进行勘测以获取所述边坡的土层结构参数和土体参数。
举例来说,比如某边坡的土层分为人工填土层、粉质黏土层、砾质黏土层和全风化花岗岩这四层,那么就需要测量每个土层的深度,以及每个土层的相关参数。
具体的,参见下表,下表为某边坡各个土层渗流分析参数。其中,需要指出的是,所需要获取的参数类型包括但不限于下表所示的类型。
Figure PCTCN2016113021-appb-000003
具体的,参见下表,下表为某边坡边坡稳定性分析的土体参数。所需要获取的参数类型包括但不限于下表所示的类型。
Figure PCTCN2016113021-appb-000004
Figure PCTCN2016113021-appb-000005
进一步,需要指出的是,在获取边坡的相关参数后,将所述相关参数输入到有限元分析软件,建立边坡的有限元模型。然后根据有限元模型计算初始安全系数。
举例来说,根据勘测的数据可以绘制滑坡监测区的边坡地质勘测的剖面,如图1b所示。在图1b中标出了拟监测点A、B、C和D,其中A和C点监测水平位移。根据地质勘测结果以及边坡实际情况,设定出边坡模型的边界条件:将全风化花岗岩与强风化花岗岩的交界面设定为地下水边界,边坡的左右两侧设定为不透水边界,边坡表面设定为降雨入渗边界,其中斜坡处降雨量按照降雨强度的法相取值。采用边坡所在区域的年平均降雨量为2000mm获得边坡初始渗流状况,通过SEEP/W软件获得边坡渗流后将其导入SLOPE/W模块中,通过Morgenstern-Price法和Bishop法最终得到边坡初始安全系数Fs均为1.340,如图1c所示。
其中,需要指出的是,对于边坡的监测点一般设置在边坡的顶部、底部和边坡上。对于具体的位置在此不做限制。可以理解的是,在进行建模后,可以以边坡的不同降雨强度为输入条件,针对该边坡模型进行模拟。
所述降雨强度与降雨持续时间曲线的公式为:
Figure PCTCN2016113021-appb-000006
其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和b是根据边坡土层结构参数和土体参数确定的;其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时,随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定。
举例来说,边坡的安全系数都从1.34减少到临界值1.2时,可以分析得 到不同降雨强度对应的降雨持续时长,如下表(降雨强度-降雨持续时间曲线数据)。
Figure PCTCN2016113021-appb-000007
在获取降雨强度-降雨持续时间曲线数据后,可以将上表中所示的降雨强度与降雨持续时长的关系进行拟合,通过MATLAB可以拟合出该边坡的降雨强度-降雨持续时间曲线,其中,超过4.5mm/h的降雨强度对应的降雨时间均值为218h,对应的算式结果为:
Figure PCTCN2016113021-appb-000008
式中k1——降雨强度限值,界限定为4.5mm/h;k2——降雨强度限值,界限定为1.5mm/h。其中,得到如图1d所示降雨强度与降雨时长的拟合曲线。
可以理解的是,在获取降雨强度与降雨时长的拟合曲线之后,可以根据该曲线获取临界累积降雨量。
举例来说,根据该边坡的降雨强度-降雨持续时间拟合曲线以及典型降雨工况的累积降雨量可得:当降雨强度I在2mm/h~4mm/h时,数据点的累积降雨量的平均值为749mm。为了保证边坡位移阶段的预判,当前期有效降雨量达到临界累积降雨量的30%时(即225mm),可以确定该边坡进入位移预警阶段。
另一方面,需要指出的是,可以采用有限元数值分析方法,获得边坡拟监测部位的位移预警阈值。
举例来说,如图1e所示,可以采用有限元数值方法,分析同一边坡在降雨下的安全系数变化。将边坡的左右两端边界的水平方向位移为零,竖直方向自由;边坡的下边界的水平和竖直方向位移均为零,采用弹塑性摩尔库伦破坏准则的本构模型,并以年降雨量为2000mm的边坡渗流状态建立边坡初始应力应变模块,边坡的初始总应力(单位为Kpa)和位移监测点A、C。以初始应力和初始渗流为基础对边坡进行流固耦合分析,最终获取边坡监测点位移信息进而拟定边坡位移预警阈值。
具体的,以边坡初始渗流和应力为基础,在边坡的降雨入渗边界上施加获取降雨预警阈值时的典型降雨,通过对边坡进行流固耦合分析,获得了各个降雨阶段边坡的安全系数以及对应监测点A、C的位移增量数据,如下表所示。
Figure PCTCN2016113021-appb-000009
可以理解的是,根据安全系数与A点和C点位移增量的关系,应用MATLAB可以拟合出两者之间的关系,拟合方程为:
ΔX=8.857e9×Fs -96.94+3.913;
ΔX=2.225e10×Fs -98.88+8.232;
式中ΔX表示位移增量(mm);Fs表示边坡安全系数。
为了体现降雨对边坡的损伤程度,定义了边坡的危险系数p,即降雨引起的边坡安全系数的减少值以及边坡具备的安全储备值的比值,公式为
Figure PCTCN2016113021-appb-000010
式中Fs表示边坡初始状态的稳定系数,本边坡为1.34;Fsi表示边坡在实际遭受降雨时的安全系数改变值;F0表示边坡临界安全系数,本边坡取1.20。
举例来说,用p=0.3作为边坡进入匀速位移阶段起征点的限值,此时的安全系数Fsi=1.298,在拟合的曲线中可以得到A1和C1点;用p=0.6作为边坡进入初加速位移阶段起征点的限值,此时的安全系数Fsi=1.256,在拟合的曲线中可以得到A2和C2点;用p=0.8作为边坡进入中加速位移阶段起征点的限值,此时的安全系数Fsi=1.228,在拟合的曲线中可以得到A3和C3点;用p=0.9作为边坡进入加加速位移阶段起征点的限值,此时的安全系数Fsi=1.214,在拟合的曲线中可以得到A4和C4点。
需要指出的是,根据边坡各个阶段的演变规律以及边坡预警级别的准则,可以获得坡顶A点和坡底C点的位移增量预警阈值界定值,如下表所示。
下表为坡顶A点阶段式预警。
Figure PCTCN2016113021-appb-000011
下表为坡底C点阶段式预警。
Figure PCTCN2016113021-appb-000012
具体的,根据边坡位移演变阶段的特点,标出了边坡坡顶监测点A各个位移阶段的起征点A1、A2、A3以及A4,如图1f所示。
具体的,根据边坡位移演变阶段的特点,标出了边坡坡底监测点C各个位移阶段的起征点C1、C2、C3以及C4,如图1g所示。
从图1f和图1g中可以看出,A1和C1点是边坡进入匀速位移阶段的起征点,A2和C2点是边坡进入初加速位移阶段的起征点,A3和C3点是边坡进入中加速位移阶段的起征点,A4和C4点是边坡进入加加速位移阶段的起征点。
由上所述,边坡模型的有限元计算结果可以同时得到安全系数、边坡的降雨情况、边坡拟监测点的位移和边坡监测点的含水率多少,通过分析可以获得拟监测边坡的降雨强度-降雨持续时间曲线,进而给出不同安全系数下的拟监测边坡的降雨预警阈值、位移预警阈值。
结合步骤S103和上述位移量阈值,所述发布预警信息包括:获取目标监测点的位移量;根据所述目标监测点的位移量与位移量阈值确定预警类型;发布所述预警类型。其中,常见的预警类型包括注意级、警示级,警戒级以及警报级。
另外,需要指出的是,步骤S101和102中的当前降雨强度以及边坡表面的土壤湿度可以通过监测系统来获取。
为了更好理解本发明,在本发明的实施例中公开的一种降雨型滑坡的监测系统,下面先对本发明实施例适用的网络构架进行描述。如图1h所示,该网络构架示意图可以包括传感器、无线传感器终端节点、无线传感器路由节点、无线传感器网关节点、远程监控中心。
其中,传感器包括有线传感器和无线传感器,有线传感器与无线传感器通 过串口相连,结合成无线传感器终端节点,把监测数据传送给基站,基站通过无线手机网络模块连接至远程监控预警中心实现了监测数据的实时远程传输,搭建起了基于无线传感器网络的降雨型滑坡预警系统,真实、可行、有效的实施远程实时监控边坡滑坡。
根据监测方案的要求,建立多跳树簇型的无线传感器监测网,其中,无线传感器终端节点Ⅰ、终端节点Ⅱ和终端节点Ⅲ将采集的数据发送给路由节点Ⅰ,无线传感器终端节点Ⅳ和终端节点Ⅴ将采集的数据发送给路由节点Ⅱ,路由节点Ⅰ和路由节点Ⅱ将汇聚的数据转发给网关节点,网关节点通过手机网络无线通信的方式发送给远程监控中心。
可以理解的是,该远程监控中心可以是S101-S103的执行主体。
无线传感器终端节点、路由节点和网关节点的硬件开发是以自主开发的无线传感器节点板为基础的。其中,无线传感器终端节点为重要的组成部分,较为复杂,由采集模块、处理器模块、无线通信功能模块以及智能电源模块组成。无线传感器路由节点没有可以接有线传感器的采集模块,它的功能是将终端节点传来的数据进行汇聚并将其转发给网关节点,同时,路由节点还可以传达网关节点发送给终端节点的指令。
具体的,根据滑坡监测区拟监测边坡的地质勘探结果,制定了拟监测边坡管道内部传感器布置方案,如图1i所示,对拟监测边坡进行了钻孔施工和管道安装,监测点现场安装布置情况如下:在边坡的A和A'点的倾斜管中埋置倾角传感器用来测量水平位移,目前已经埋置倾斜管。在边坡顶端与A和A'平行处有一个钻孔E,在此监测点埋置侧面钻孔的PVC管用来放置液位传感器,目前已经埋置PVC管。在B和B'点处钻取2m钻孔埋置土壤湿度传感器用来测量土壤饱和度,钻孔点在边坡中的位置如图所示。在C和C'点的倾斜管中埋置倾角传感器用来测量土层水平位移,目前已经埋置倾斜管。在D点处埋置侧面钻孔的PVC管用来放置液位传感器,进而获得测点处地下水位,目前已经埋置PVC管。
具体布置方案如下:
(1)在A(A')点和C(C')点处边坡内部10m土层内,每隔2m安装一 个倾角传感器;在B和B'点处边坡内部2m土层内,每隔1m埋置一个土壤湿度传感器;
(2)在D点处10m深处安装一个液位传感器,在E点处20m深处安装一个液位传感器,所采集的数据通过无线传感器终端节点发送给网关节点,网关节点通过手机网络无线通信方式将接收到的数据发送给远程监控中心。
其中,在管道内部布置的有线传感器类型及其细节汇总在图1j中。整个降雨型滑坡预警系统由无线传感器终端节点、路由节点、网关节点和远程监控预警中心组成,应用无线传感器传输数据进而实现对降雨型滑坡的监测预警。
如图2所示,在本发明的另一实施例中,提供了一种基于降雨量及土壤湿度的降雨型滑坡的预警方法,该方法包括:
S201、获取所述边坡的土层结构参数和土体参数;
其中,土层结构参数和土体参数可以通过对边坡进行勘测获得。
S202、根据所述土层结构参数和所述土体参数建立所述边坡的模型;
S203、根据边坡的模型确定所述边坡的初始安全系数;
具体确定的过程请参见上述实施例。
S204、获取所述边坡所属区域的降雨强度的历史数据;
其中,该区域可以是行政区域,比如属于某个镇,或者某个市等等。
S205、根据所述降雨强度的历史数据确定目标降雨强度;
其中,目标降雨强度一般在历史记录的数据的范围内。
S206、根据预设的目标安全系数、所述初始安全系数确定与每个目标降雨强度相对应的降雨持续时间;
S207、将所述目标降雨强度与所述降雨持续时间进行拟合以确定所述降雨强度与降雨持续时间曲线;
所述降雨强度与降雨持续时间曲线的公式为:
Figure PCTCN2016113021-appb-000013
其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和 b是根据边坡土层结构参数和土体参数确定的;
其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时,随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定;
S208、根据所述降雨强度与降雨持续时间曲线确定目标降雨强度;
S209、获取当前降雨强度以及边坡表面的土壤湿度;
S210、当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
S211、当所述土壤湿度阈值大于所述目标土壤湿度阈值时,获取目标监测点的位移量;
S212、根据所述目标监测点的位移量与位移量阈值确定预警类型;并发布所述预警类型。
从上可知,通过实施本发明实施例提供的方法,获取当前降雨强度以及边坡表面的土壤湿度;当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。可见,通过实施本发明实施例,结合降雨量和土壤湿度能够对降雨型滑坡进行准确预警。
如图3所示,图3描述了一种基于降雨量及土壤湿度的降雨型滑坡预警装置300的具体结构,其中,该装置300可以是图1h中的远程监控中心,该装置300包括:
获取单元301,用于获取当前降雨强度以及边坡表面的土壤湿度;
判断单元302,用于当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
发布单元303,用于当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
其中,获取单元301、判断单元302以及发布单元303可以用于执行实施例1中步骤S101至S103所述的方法,具体描述详见实施例1对所述方法的描述,在此不再赘述。
如图4所示,图4描述了一种基于降雨量及土壤湿度的降雨型滑坡预警装置的具体结构,其中,该装置400可以是图1h中的远程监控中心,该装置400包括:
获取单元401,用于获取所述边坡的土层结构参数和土体参数;
建模单元404,用于根据所述土层结构参数和所述土体参数建立所述边坡的模型;
确定单元405,用于根据边坡的模型确定所述边坡的初始安全系数;
获取单元401,还用于获取所述边坡所属区域的降雨强度的历史数据;
确定单元405,还用于根据所述降雨强度的历史数据确定目标降雨强度;还用于根据预设的目标安全系数、所述初始安全系数确定与每个目标降雨强度相对应的降雨持续时间;定单元,还用于将所述目标降雨强度与所述降雨持续时间进行拟合以确定所述降雨强度与降雨持续时间曲线;还用于根据所述降雨强度与降雨持续时间曲线确定目标降雨强度;
其中,所述降雨强度与降雨持续时间曲线的公式为:
Figure PCTCN2016113021-appb-000014
其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和b是根据边坡土层结构参数和土体参数确定的;
其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时,随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定。
获取单元401,用于获取当前降雨强度以及边坡表面的土壤湿度;
判断单元402,用于当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
发布单元403,用于当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
具体的,发布单元403包括获取子单元、确定子单元和发布子单元;
所述获取子单元,用于获取目标监测点的位移量;
所述确定子单元,用于根据所述目标监测点的位移量与位移量阈值确定预警类型;
所述发布子单元,用于发布所述预警类型。
其中,获取单元401、判断单元402、发布单元403、建模单元404以及确定单元405可以用于执行实施例2中步骤S201至S214所述的方法,具体描述详见实施例2对所述方法的描述,在此不再赘述。
请参阅图5,在本发明的另一个实施例中,提供一种基于降雨量及土壤湿度的降雨型滑坡的预警装置的具体结构。所述装置500包括CPU501、存储器502、总线503。
其中,CPU501执行预先存储在存储器502中的程序,该执行过程具体包括:
获取当前降雨强度以及边坡表面的土壤湿度;
当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
可选的,所述获取当前降雨强度以及边坡表面的土壤湿度之前,所述执行过程还包括:
获取所述边坡的土层结构参数和土体参数;
根据所述土层结构参数和所述土体参数建立所述边坡的模型;
根据边坡的模型确定所述边坡的初始安全系数;
根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线;
根据所述降雨强度与降雨持续时间曲线确定目标降雨强度。
可选的,所述根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线之前,所述执行过程还包括:
获取所述边坡所属区域的降雨强度的历史数据;
根据所述降雨强度的历史数据确定目标降雨强度;
所述根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线之前,所述方法还包括:
根据预设的目标安全系数、所述初始安全系数确定与每个目标降雨强度相对应的降雨持续时间;
将所述目标降雨强度与所述降雨持续时间进行拟合以确定所述降雨强度与降雨持续时间曲线。
需要指出的是,所述降雨强度与降雨持续时间曲线的公式为:
Figure PCTCN2016113021-appb-000015
其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和b是根据边坡土层结构参数和土体参数确定的;
其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时,随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定。
可选的,所述发布预警信息包括:
获取目标监测点的位移量;
根据所述目标监测点的位移量与位移量阈值确定预警类型;
发布所述预警类型。
可以看出,本发明实施例的方案中,获取当前降雨强度以及边坡表面的土壤湿度;当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。可见,通过实施本发明实施例,结合降雨量和土壤湿度能够对降雨型滑坡进行准确预警。
前述图1、图2所示的实施例中,各步骤方法流程可以基于该装置的结构实现。
前述图3、图4所示的实施例中,各单元功能可以基于该装置的结构实现。
在上述实施例中,对各个实施例的描述都各有侧重,某个实施例中没有详 述的部分,可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中,应该理解到,所揭露的装置,可通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如所述单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个单元或组件可以结合或者可以集成到另一个系统,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口,装置或单元的间接耦合或通信连接,可以是电性或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的,作为单元显示的部件可以是或者也可以不是物理单元,即可以位于一个地方,或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外,在本发明各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现,也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读取存储介质中。基于这样的理解,本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质中,包括若干指令用以使得一台计算机设备(可为个人计算机、服务器或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括:U盘、只读存储器(ROM,Read-Only Memory)、随机存取存储器(RAM,Random Access Memory)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述,以上实施例仅用以说明本发明的技术方案,而非对其限制;尽管参照前述实施例对本发明进行了详细的说明,本领域的普通技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分 技术特征进行等同替换;而这些修改或者替换,并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (10)

  1. 一种基于降雨量及土壤湿度的降雨型滑坡的预警方法,其特征在于,所述方法包括:
    获取当前降雨强度以及边坡表面的土壤湿度;
    当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
    当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
  2. 根据权利要求1所述的方法,其特征在于,所述获取当前降雨强度以及边坡表面的土壤湿度之前,所述方法还包括:
    获取所述边坡的土层结构参数和土体参数;
    根据所述土层结构参数和所述土体参数建立所述边坡的模型;
    根据边坡的模型确定所述边坡的初始安全系数;
    根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线;
    根据所述降雨强度与降雨持续时间曲线确定目标降雨强度。
  3. 根据权利要求2所述的方法,其特征在于,所述根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线之前,所述方法还包括:
    获取所述边坡所属区域的降雨强度的历史数据;
    根据所述降雨强度的历史数据确定目标降雨强度;
    所述根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线之前,所述方法还包括:
    根据预设的目标安全系数、所述初始安全系数确定与每个目标降雨强度相对应的降雨持续时间;
    将所述目标降雨强度与所述降雨持续时间进行拟合以确定所述降雨强度与降雨持续时间曲线。
  4. 根据权利要求3所述的方法,其特征在于,所述降雨强度与降雨持续时间曲线的公式为:
    Figure PCTCN2016113021-appb-100001
    其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和b是根据边坡土层结构参数和土体参数确定的;
    其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时,随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定。
  5. 根据权利要求1至4任一所述的方法,其特征在于,所述发布预警信息包括:
    获取目标监测点的位移量;
    根据所述目标监测点的位移量与位移量阈值确定预警类型;
    发布所述预警类型。
  6. 一种基于降雨量及土壤湿度的降雨型滑坡的预警装置,其特征在于,所述降雨型滑坡的预警装置包括:
    获取单元,用于获取当前降雨强度以及边坡表面的土壤湿度;
    判断单元,用于当所述当前降雨强度大于目标降雨强度时,判断所述土壤湿度是否大于目标土壤湿度阈值;
    发布单元,用于当所述土壤湿度阈值大于所述目标土壤湿度阈值时,发布预警信息。
  7. 根据权利要求6所述的降雨型滑坡的预警装置,其特征在于,所述降雨型滑坡的预警装置还包括建模单元和确定单元;
    所述获取单元,用于获取所述边坡的土层结构参数和土体参数;
    所述建模单元,用于根据所述土层结构参数和所述土体参数建立所述边坡的模型;
    所述确定单元,用于根据边坡的模型确定所述边坡的初始安全系数;
    所述确定单元,还用于根据预设的目标安全系数、所述初始安全系数确定降雨强度与降雨持续时间曲线;
    所述确定单元,还用于根据所述降雨强度与降雨持续时间曲线确定目标降雨强度。
  8. 根据权利要求7所述的降雨型滑坡的预警装置,其特征在于,
    所述获取单元,还用于获取所述边坡所属区域的降雨强度的历史数据;
    所述确定单元,还用于根据所述降雨强度的历史数据确定目标降雨强度;
    所述确定单元,还用于根据预设的目标安全系数、所述初始安全系数确定与每个目标降雨强度相对应的降雨持续时间;
    所述确定单元,还用于将所述目标降雨强度与所述降雨持续时间进行拟合以确定所述降雨强度与降雨持续时间曲线。
  9. 根据权利要求8所述的降雨型滑坡的预警装置,其特征在于,所述降雨强度与降雨持续时间曲线的公式为:
    Figure PCTCN2016113021-appb-100002
    其中,所述I表示降雨强度(mm/h);D表示降雨持续时间(h);参数a和b是根据边坡土层结构参数和土体参数确定的;
    其中,当降雨强度达到土体表面土层的渗透系数ks1时,增加降雨强度并不 会显著改变边坡的整体稳定;当降雨强度低于边坡二级土层的渗透系数ks2时,随着降雨时间的持续增长,此时的降雨强度并不会显著影响边坡的整体稳定。
  10. 根据权利要求6至9任一所述的降雨型滑坡的预警装置,其特征在于,所述发布单元包括获取子单元、确定子单元和发布子单元;
    所述获取子单元,用于获取目标监测点的位移量;
    所述确定子单元,用于根据所述目标监测点的位移量与位移量阈值确定预警类型;
    所述发布子单元,用于发布所述预警类型。
PCT/CN2016/113021 2016-12-29 2016-12-29 一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置 WO2018119880A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201680084612.0A CN109074719A (zh) 2016-12-29 2016-12-29 一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置
PCT/CN2016/113021 WO2018119880A1 (zh) 2016-12-29 2016-12-29 一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2016/113021 WO2018119880A1 (zh) 2016-12-29 2016-12-29 一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置

Publications (1)

Publication Number Publication Date
WO2018119880A1 true WO2018119880A1 (zh) 2018-07-05

Family

ID=62710146

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2016/113021 WO2018119880A1 (zh) 2016-12-29 2016-12-29 一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置

Country Status (2)

Country Link
CN (1) CN109074719A (zh)
WO (1) WO2018119880A1 (zh)

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110110277A (zh) * 2019-04-10 2019-08-09 固安京蓝云科技有限公司 降雨有效持水量比例计算方法及装置
CN111159907A (zh) * 2019-12-31 2020-05-15 同济大学 一种暴雨作用下的边坡模拟方法
CN111259605A (zh) * 2020-02-14 2020-06-09 中铁二院工程集团有限责任公司 一种土质滑坡监测预警评估方法
CN111855121A (zh) * 2020-08-17 2020-10-30 昆明理工大学 一种以降雨和地震为诱因的边坡失稳实验装置及实验方法
CN111877417A (zh) * 2020-08-20 2020-11-03 河南省第二建设集团有限公司 降雨参数弱化型基坑边坡失稳临界含水率的测定方法
CN111931369A (zh) * 2020-08-05 2020-11-13 长安大学 降雨型滑坡稳定性分析及运动距离测算方法、设备及介质
CN112505297A (zh) * 2020-11-23 2021-03-16 中建八局第一建设有限公司 一种路基环境监测平台制作方法及环境监测平台
CN113079483A (zh) * 2021-03-25 2021-07-06 广州市地狗灵机环境监测有限公司 一种无线雨量传感器系统
CN113378582A (zh) * 2021-07-15 2021-09-10 重庆交通大学 一种基于语义信息驱动的滑坡位移预测模型及方法
CN113433290A (zh) * 2021-06-21 2021-09-24 安徽理工大学 一种模拟间歇型强降雨条件下黄土滑坡监测装置及方法
CN114067534A (zh) * 2022-01-11 2022-02-18 山东省国土空间生态修复中心 基于机器视觉的地质灾害预警方法及系统
CN114236095A (zh) * 2021-12-02 2022-03-25 山东高速集团四川乐宜公路有限公司 一种山区高速公路沿线降雨诱发滑坡分区分级预警方法
CN114264789A (zh) * 2021-11-15 2022-04-01 武汉科技大学 一种边坡软弱夹层上方相邻岩层的监测方法和系统
CN114627623A (zh) * 2022-03-15 2022-06-14 中科海慧(北京)科技有限公司 一种基于时空大数据分析的地质灾害监测系统
CN114658079A (zh) * 2022-04-06 2022-06-24 长江勘测规划设计研究有限责任公司 一种基于雨强的排土场弃土堆放方法
CN114840904A (zh) * 2022-05-23 2022-08-02 广西北投交通养护科技集团有限公司 一种土质边坡自动监测及稳定判定方法
CN114912181A (zh) * 2022-05-21 2022-08-16 武汉泰佰腾建筑劳务有限公司 一种基于人工智能的路面边坡安全监测分析系统
CN115034506A (zh) * 2022-06-29 2022-09-09 珠江水利委员会珠江水利科学研究院 基于降雨数据的防洪方案生成方法、装置、设备及介质
CN117194928A (zh) * 2023-11-07 2023-12-08 湖南中云图地理信息科技有限公司 基于gnss的地理形变监测系统
CN117516430A (zh) * 2024-01-04 2024-02-06 南京师范大学 一种基于多元特征的滑坡形变降雨阈值计算方法
CN114840904B (zh) * 2022-05-23 2024-04-16 广西北投交通养护科技集团有限公司 一种土质边坡自动监测及稳定判定方法

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110363963A (zh) * 2019-07-05 2019-10-22 中国矿业大学(北京) 一种基于弹性波波速的降雨型滑坡预警系统
CN112967475A (zh) * 2021-01-29 2021-06-15 深圳市安泰数据监测科技有限公司 一种智能化区域性滑坡监测管理方法及装置

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101477207A (zh) * 2009-01-20 2009-07-08 中国科学院水利部成都山地灾害与环境研究所 一种智能型地质灾害综合监测系统及多级预报分析方法
US20150339911A1 (en) * 2014-05-22 2015-11-26 West Corporation System and method for monitoring, detecting and reporting emergency conditions using sensors belonging to multiple organizations
CN105185043A (zh) * 2015-09-15 2015-12-23 成都汉康信息产业有限公司 山体滑坡灾害监测终端
CN105844858A (zh) * 2016-04-05 2016-08-10 南信大影像技术工程(苏州)有限公司 Gnss滑坡监测与预警系统

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103714661B (zh) * 2013-11-14 2016-06-08 浙江省国土资源厅信息中心 降雨阈值自适应的滑坡实时预警方法
CN104318103B (zh) * 2014-10-23 2017-12-15 中国科学院、水利部成都山地灾害与环境研究所 一种滑坡灾害监测预警降雨阈值判定方法
JP2016216989A (ja) * 2015-05-19 2016-12-22 株式会社東芝 災害監視システムおよび災害監視装置
CN105761436B (zh) * 2016-03-10 2018-06-29 成都理工大学 一种红层地区滑坡预警方法及其应用

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101477207A (zh) * 2009-01-20 2009-07-08 中国科学院水利部成都山地灾害与环境研究所 一种智能型地质灾害综合监测系统及多级预报分析方法
US20150339911A1 (en) * 2014-05-22 2015-11-26 West Corporation System and method for monitoring, detecting and reporting emergency conditions using sensors belonging to multiple organizations
CN105185043A (zh) * 2015-09-15 2015-12-23 成都汉康信息产业有限公司 山体滑坡灾害监测终端
CN105844858A (zh) * 2016-04-05 2016-08-10 南信大影像技术工程(苏州)有限公司 Gnss滑坡监测与预警系统

Cited By (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110110277B (zh) * 2019-04-10 2023-05-05 固安京蓝云科技有限公司 降雨有效持水量比例计算方法及装置
CN110110277A (zh) * 2019-04-10 2019-08-09 固安京蓝云科技有限公司 降雨有效持水量比例计算方法及装置
CN111159907A (zh) * 2019-12-31 2020-05-15 同济大学 一种暴雨作用下的边坡模拟方法
CN111259605B (zh) * 2020-02-14 2023-04-07 中铁二院工程集团有限责任公司 一种土质滑坡监测预警评估方法
CN111259605A (zh) * 2020-02-14 2020-06-09 中铁二院工程集团有限责任公司 一种土质滑坡监测预警评估方法
CN111931369A (zh) * 2020-08-05 2020-11-13 长安大学 降雨型滑坡稳定性分析及运动距离测算方法、设备及介质
CN111931369B (zh) * 2020-08-05 2024-04-09 长安大学 降雨型滑坡稳定性分析及运动距离测算方法、设备及介质
CN111855121A (zh) * 2020-08-17 2020-10-30 昆明理工大学 一种以降雨和地震为诱因的边坡失稳实验装置及实验方法
CN111855121B (zh) * 2020-08-17 2024-03-01 昆明理工大学 一种以降雨和地震为诱因的边坡失稳实验装置及实验方法
CN111877417A (zh) * 2020-08-20 2020-11-03 河南省第二建设集团有限公司 降雨参数弱化型基坑边坡失稳临界含水率的测定方法
CN112505297A (zh) * 2020-11-23 2021-03-16 中建八局第一建设有限公司 一种路基环境监测平台制作方法及环境监测平台
CN113079483B (zh) * 2021-03-25 2022-06-17 广州市地狗灵机环境监测有限公司 一种无线雨量传感器系统
CN113079483A (zh) * 2021-03-25 2021-07-06 广州市地狗灵机环境监测有限公司 一种无线雨量传感器系统
CN113433290A (zh) * 2021-06-21 2021-09-24 安徽理工大学 一种模拟间歇型强降雨条件下黄土滑坡监测装置及方法
CN113378582B (zh) * 2021-07-15 2022-04-26 重庆交通大学 基于语义信息驱动的滑坡位移预测模型构建及使用方法
CN113378582A (zh) * 2021-07-15 2021-09-10 重庆交通大学 一种基于语义信息驱动的滑坡位移预测模型及方法
CN114264789A (zh) * 2021-11-15 2022-04-01 武汉科技大学 一种边坡软弱夹层上方相邻岩层的监测方法和系统
CN114236095A (zh) * 2021-12-02 2022-03-25 山东高速集团四川乐宜公路有限公司 一种山区高速公路沿线降雨诱发滑坡分区分级预警方法
CN114236095B (zh) * 2021-12-02 2024-03-19 山东高速集团四川乐宜公路有限公司 一种山区高速公路沿线降雨诱发滑坡分区分级预警方法
CN114067534A (zh) * 2022-01-11 2022-02-18 山东省国土空间生态修复中心 基于机器视觉的地质灾害预警方法及系统
CN114627623A (zh) * 2022-03-15 2022-06-14 中科海慧(北京)科技有限公司 一种基于时空大数据分析的地质灾害监测系统
CN114658079A (zh) * 2022-04-06 2022-06-24 长江勘测规划设计研究有限责任公司 一种基于雨强的排土场弃土堆放方法
CN114658079B (zh) * 2022-04-06 2023-08-29 长江勘测规划设计研究有限责任公司 一种基于雨强的排土场弃土堆放方法
CN114912181B (zh) * 2022-05-21 2023-10-13 武汉泰佰腾建筑劳务有限公司 一种基于人工智能的路面边坡安全监测分析系统
CN114912181A (zh) * 2022-05-21 2022-08-16 武汉泰佰腾建筑劳务有限公司 一种基于人工智能的路面边坡安全监测分析系统
CN114840904A (zh) * 2022-05-23 2022-08-02 广西北投交通养护科技集团有限公司 一种土质边坡自动监测及稳定判定方法
CN114840904B (zh) * 2022-05-23 2024-04-16 广西北投交通养护科技集团有限公司 一种土质边坡自动监测及稳定判定方法
CN115034506B (zh) * 2022-06-29 2023-02-07 珠江水利委员会珠江水利科学研究院 基于降雨数据的防洪方案生成方法、装置、设备及介质
CN115034506A (zh) * 2022-06-29 2022-09-09 珠江水利委员会珠江水利科学研究院 基于降雨数据的防洪方案生成方法、装置、设备及介质
CN117194928A (zh) * 2023-11-07 2023-12-08 湖南中云图地理信息科技有限公司 基于gnss的地理形变监测系统
CN117194928B (zh) * 2023-11-07 2024-01-26 湖南中云图地理信息科技有限公司 基于gnss的地理形变监测系统
CN117516430A (zh) * 2024-01-04 2024-02-06 南京师范大学 一种基于多元特征的滑坡形变降雨阈值计算方法
CN117516430B (zh) * 2024-01-04 2024-03-19 南京师范大学 一种基于多元特征的滑坡形变降雨阈值计算方法

Also Published As

Publication number Publication date
CN109074719A (zh) 2018-12-21

Similar Documents

Publication Publication Date Title
WO2018119880A1 (zh) 一种基于降雨量及土壤湿度的降雨型滑坡预警方法及装置
CN107832931B (zh) 一种平原水网地区内涝风险的模块化分析方法
KR101843007B1 (ko) 산사태 모니터링 및 예·경보를 위한 무선 센서 네트워크 계측 시스템 및 계측방법
CN106781291B (zh) 一种基于位移量的降雨型滑坡预警方法及装置
Tang et al. Three modes of rainfall infiltration inducing loess landslide
CN103234490B (zh) 一种水封地下储油洞库水封效果测控装置
CN107747936B (zh) 一种在线监测地下单独空间地表沉降变形的方法
Wang et al. Hydraulic barrier function of the underground continuous concrete wall in the pit of subway station and its optimization
CN105912798A (zh) 基于超深基坑抽水的地面沉降智能预警方法及监测系统
CN103226732A (zh) 一种基于gms的矿区不同开采中段的地下水渗流场预测方法
JP5473760B2 (ja) 間隙水圧測定装置、それを用いた軟弱地盤の改良工法、地下埋設物が埋設される地盤の動態把握方法、及び盛土構造物が造成される地盤の動態把握方法
CN110927821A (zh) 一种基于bim+gis的隧道施工超前地质预报信息系统
CN103471647B (zh) 一种盾构隧道远程自动化监测方法
CN108195346B (zh) 一种实时监测地下多层次空间地表沉降变形的方法
CN106033637A (zh) 无线缆、可长期独立工作的滑坡灾害监测预警方法及系统
Hansen et al. Groundwater dynamics and effect of tile drainage on water flow across the redox interface in a Danish Weichsel till area
Lau et al. Monitoring of rainfall-induced landslides at Songmao and Lushan, Taiwan, using IoT and big data-based monitoring system
CN103046525A (zh) 深基坑力学稳定性远程智能监测及三维预警方法与设施
CN211123324U (zh) 一种基于bim+gis的隧道施工超前地质预报信息系统
CN103195046B (zh) 一种一孔多孔隙水压力计埋设方法
JP2021174101A (ja) 物体検出システム
Gian et al. Monitoring of landslides in mountainous regions based on FEM modelling and rain gauge measurements
Wang et al. Analysis of drainage efficiency under extreme precipitation events based on numerical simulation
CN110702171A (zh) 建筑废弃物受纳场监测方法、装置及系统
CN203164690U (zh) 基于物联网的桥梁建设用监控系统

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16925152

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16925152

Country of ref document: EP

Kind code of ref document: A1