227 results about "Loess" patented technology

The invention discloses a loess slope stability intelligent monitoring method and system, and the method comprises the steps: carrying out the regional differentiation modeling of multi-source data of a target region, and outputting slope change data; according to the period-by-period displacement time sequence data, a slope deformation trend is obtained through prediction based on an LSTM algorithm; and inputting the slope change data, the slope deformation trend and the meteorological rainfall data into a slope stability evaluation model to predict a safety coefficient, and if the safety coefficient is lower than a preset threshold value, issuing early warning information. According to the loess slope stability intelligent monitoring method and system provided by the invention, data such as gradient change and deformation trend are accurately extracted, multi-source data and meteorological rainfall data are fused by means of cross-modal attention, a random forest model is used for learning a multi-factor coupling rule, and finally multi-factor data prediction is integrated to obtain a safety coefficient for early warning. The problem of low early warning reliability caused by difficulty in accurately evaluating the slope stability by fusing multiple factors such as gradient, deformation and meteorological rainfall can be solved.

The invention relates to an iron tower foundation safety analysis method considering the dry-wet cycle effect. The method comprises the following steps that 1, a soil body strength degradation constitutive model is established; 2, determining iron tower foundation structure parameters and soil body parameters; 3, establishing an iron tower foundation-soil body three-dimensional geometric model by utilizing three-dimensional modeling software and rock-soil finite element simulation software; 4, applying a load transmitted to the iron tower foundation by the power transmission iron tower in the iron tower foundation-soil body three-dimensional geometric model, defining initial parameters, and establishing a rainwater seepage and dry-wet cycle coupling effect analysis model; 5, analyzing and predicting the cycle index when the safety coefficient of the iron tower foundation is reduced to a threshold value from the two aspects of tower foundation ultimate bearing performance and iron tower foundation-soil body interaction on the basis of a rainwater seepage and dry-wet cycle coupling effect analysis model; according to the method, an efficient and accurate numerical analysis means can be provided for safety assessment of the power transmission tower foundation in the collapsible loess area.

The invention discloses an accurate monitoring system for linear deformation of a loess tunnel portal side upward slope, and relates to the technical field of geotechnical engineering and surveying and mapping. The system comprises a sensing network layer, a data acquisition and transmission layer, a cloud platform and data analysis layer and an application display layer, displacement data of discrete monitoring points are reconstructed into continuous full-field displacement and strain distribution through Kriging interpolation, then a displacement vector field is regarded as a whole to be analyzed, the maximum shear strain field of the displacement vector field is calculated, an abnormal area with the deformation gradient abrupt change is accurately positioned, and the deformation gradient abrupt change accuracy is improved. The abnormal point sets are merged into independent clusters according to spatial proximity and deformation consistency, and the geometric trajectory of a potential slip crack surface or crack is accurately outlined through curve fitting, so that the technical path fundamentally changes the limitation of point-mode monitoring, and can automatically identify a hidden linear failure trend which is difficult to find by naked eyes in a non-contact manner, so as to improve the detection accuracy of the hidden linear failure trend. And refined data support is provided for slope stability evaluation.

The invention provides a method suitable for water retention of soil with different textures. In order to better perform size matching between the biochar and soil particles, particle size grading is performed on the biochar according to the size of soil aggregates, and three kinds of biochar with the particle size larger than 2.0 mm, the particle size ranging from 0.25 mm to 2.0 mm and the particle size smaller than 0.25 mm are obtained. The three kinds of biochar with different particle sizes are used in different types of soil respectively, and 5% of biochar with the particle size of 0.25-2.0 mm is selectively applied according to the water retention requirement of the arid area loam farmland; according to the drainage requirements of loam waterlogging areas with more rainfall, 5% of biochar with the particle size larger than 2.0 mm is selectively applied; and 5% of biochar with the particle size smaller than 0.25 mm is selectively applied for water and soil conservation of sandy soil in the arid region. By scientifically regulating and controlling the particle size and the application amount of the biochar, the biochar is matched with the specific properties of the soil, so that the water retention capacity of the soil is improved, and the soil efficiency is improved.

The invention relates to the technical field of geotechnical engineering material modification and industrial solid waste resource utilization, in particular to an industrial solid waste curing agent formula screening method for salinized loess improvement, which comprises the following steps: constructing a curing system with different industrial solid waste (such as fly ash, slag and steel slag) composite proportions, identifying the salt type and salt concentration of salinized loess, and determining the salt concentration of the salinized loess. The method comprises the following steps: preparing, maintaining and curing a sample, carrying out unconfined compressive strength test and X-ray diffraction (XRD) analysis, extracting peak areas of main reaction products, and calculating a structure-performance coupling mechanism index Mi = S / f7 (S is the XRD peak area, and f7 is the compressive strength of 7 days). The Mi value and the 28-day strength are used as judgment criteria, and a preferable formula with good structural product master control and strength development is screened out. The screening method provided by the invention has the advantages of distinguishable mechanism, quantifiable index, generalizable process and the like, and is suitable for formula design and engineering application of the industrial solid waste-based curing agent under the conditions of different salt concentrations and ion types.

The invention provides a method for predicting settlement of a transformer substation in a collapsible loess area based on a neural network, and relates to the technical field of geological engineering monitoring. Then, settlement characteristic indexes such as collapsibility, bearing capacity influence and deformation stability are obtained through analysis, a prediction model is established with soil mass mechanical data as input and the settlement characteristic indexes as output, the model performance is optimized through a particle swarm optimization algorithm and a loss function, and finally a fitness function is constructed according to the settlement characteristic indexes. And calculating the settlement fitness value of each sub-region, evaluating the settlement amount in combination with load time sequence data, setting a settlement threshold value, and carrying out risk marking on the sub-regions exceeding the threshold value. The settlement risk of the loess area where the transformer substation is located is effectively evaluated and controlled by establishing the settlement characteristic index prediction model and the dynamic monitoring mechanism.

The invention provides a slope displacement monitoring method and system for a high and steep slope in a loess area, and the method comprises the steps: carrying out the preprocessing of data through a point cloud denoising algorithm according to an initial point cloud data set, filtering noise points and irrelevant reflection points caused by a complex terrain, and generating an optimized refined point cloud data set; aiming at the refined point cloud data set, constructing a digital surface model of the side slope by utilizing a three-dimensional reconstruction algorithm, carrying out local detail correction on the model in combination with soil loosening characteristics of a loess area, and determining a preliminary morphological structure of the side slope; performing time sequence data acquisition on the preliminary morphological structure to obtain slope three-dimensional model data of multiple time periods, and analyzing the dynamic evolution trend of morphological change to obtain slope deformation feature distribution; according to the slope deformation characteristic distribution, a finite element analysis method is adopted to conduct simulation calculation on stress distribution of the high and steep slope, the stability risk of a deformation area is judged, and potential landslide risk points are determined.

The invention relates to the technical field of geotechnical engineering safety evaluation, and discloses a collapsible water sensitivity index evaluation method based on loess engineering. The method comprises the following steps: acquiring time sequence data of multiple monitoring points of a loess engineering site to form a fusion feature vector; driving the collapsibility mode discrimination model, separating steady-state and transient collapsibility mode features from the collapsibility mode discrimination model, generating a water sensitivity evolution graph according to the features, and constructing a logic decision tree; and performing incremental dynamic coupling analysis, matching the decision tree path with a collapsing development path in a historical engineering case library, calculating a path similarity weight, and performing weighted correction on the water sensitivity evolution graph according to the path similarity weight to obtain a corrected graph. And deducing collapse risk probability distribution under a plurality of time nodes in the future based on the corrected map. Integrating the atlas, the decision tree path and the risk distribution to form a final loess engineering collapsibility water sensitivity evaluation report. According to the invention, mechanism separation and dynamic intelligent prediction of the collapsing process are realized.

The invention belongs to the technical field of mine goaf filling materials, and particularly discloses flow-state solidified loess for coal mine filling and a preparation method and application of the flow-state solidified loess. According to the method, rich loess resources in the loess plateau area are used for preparing the flow-state solidified loess for coal mine filling, the coal mine recovery rate can be increased, the filling material cost is reduced, the problem that stones in the loess plateau area are insufficient is solved, the toughness and dry shrinkage resistance of the solidified flow-state solidified loess can be improved, and the problem that the loess is soft and swelled when meeting water is effectively solved. The curing agent for the fluid-state cured loess is developed according to the characteristics of loess of loess plateau and the characteristics of early strength, fluidity, pumpability, crack resistance and the like required by filling of the fluid-state cured loess, the alkali excitation mechanism, the pozzolanic effect, the secondary hydration reaction and other mechanisms are utilized, and proper functional components such as early strength, water retention and crack resistance are compounded, so that the curing agent for the fluid-state cured loess is prepared. The curing agent can effectively solve the common problems of air shrinkage, easy cracking, low strength and the like when a commercially available curing agent is used for preparing flow-state cured loess.

The invention discloses a loess collapsibility evaluation method and system based on a geophysical prospecting test technology, and relates to the field of land exploration, and the method comprises the steps: laying regular detection grids in a to-be-evaluated loess site, and constructing a site geographic coordinate system; collecting Rayleigh wave signals in real time, inverting a transverse wave velocity profile, and collecting apparent resistivity data; a shallow soil sample is drilled, soil property parameters are measured, and a model is constructed according to the mapping relation between the field geophysical prospecting parameters and the soil property parameters; inputting the acquired data into the wave velocity-water content correlation model and the resistivity-dry density correlation model to generate a water content distribution field and a dry density distribution field; and calculating the collapsibility of loess in each detection grid based on a geophysical prospecting response equation of the collapsibility coefficient, outputting a collapsibility coefficient contour cloud picture, and judging the collapsibility grade of each grid and the distribution range of collapsed loess. The method has the advantages that the collapsibility distribution field and the contour cloud picture are generated through accurate non-intrusive data acquisition and model analysis, and a scientific basis is provided for engineering construction.

The invention belongs to the technical field of river and lake water ecological restoration, and particularly discloses equipment and a method suitable for river and lake endogenous polluted sediment treatment, the equipment suitable for river and lake endogenous polluted sediment treatment comprises a material stirring unit and a curing granulation unit, the material stirring unit comprises a horizontal stirring machine box and is used for stirring and mixing raw materials, and the curing granulation unit is used for curing and granulating the raw materials; one side of the horizontal stirring machine box is connected with a loess spiral feeder, a bottom mud spiral feeder and a curing agent spiral feeder, and a loess crusher is connected between the loess spiral feeder and the horizontal stirring machine box. According to the method, the polluted bottom mud is efficiently converted into the ecological restoration matrix which is resistant to water flow scouring and stable in physical structure through a curing granulation process, the matrix can be directly applied to an underwater environment, and the core problem that existing ecological planting soil prepared through bottom mud recycling cannot be stabilized in a water area is solved; and a key matrix material is provided for in-situ construction of an underwater ecological system such as an underwater forest.

The invention discloses a loess slope top power transmission tower instability prediction method based on the landform effect, and belongs to the technical field of power transmission tower stability prediction.The loess slope top power transmission tower instability prediction method comprises the following steps that landform parameter data and landform parameter data of a loess slope around a power transmission tower foundation are obtained, and correction preprocessing of the parameter data is carried out; discrete element software is adopted to establish geometric models of the loess slope, wherein the geometric models comprise three-dimensional structure models of the earth surface, the loess layer and the tower footing; introducing a fluid-solid coupling algorithm, carrying out finite element numerical analysis on the geometric model, and simulating a deformation failure process of the loess slope and an interaction relationship of power transmission tower foundation stress through dynamic simulation and time coupling; and calculating stress field distribution of the power transmission tower foundation through finite element numerical analysis, and verifying and optimizing the model in combination with field monitoring data. According to the method, the limitation of the prior art in the aspect of loess slope power transmission tower instability prediction is overcome, the accuracy, real-time performance and comprehensiveness of prediction are realized, and the disaster loss is reduced.

The invention discloses a deep learning-based collapsibility grade automatic discrimination method. The method comprises the following steps of S1, generating a preprocessed loess geological engineering index data set; s2, obtaining a loess sampling unit graph structure data set with a weighted adjacent matrix; s3, forming a loess sampling unit weighted graph structure data set with node attributes; s4, constructing a multi-target comprehensive fitness function; s5, randomly generating differential flower pollination algorithm population individuals, and performing global search and local search on the differential flower pollination algorithm initial population to obtain an optimal graph attention network hyper-parameter vector and an optimal node feature selection mask vector; and S6, obtaining an optimized graph attention network model, deducing the loess sampling unit weighted graph structure data set with node attributes, and outputting a collapsibility grade prediction result of each sampling unit. According to the method, the influence of misjudgment of different collapsibility levels on engineering safety is dynamically evaluated, so that the algorithm is guided to preferentially improve the recognition accuracy of high-risk levels.

The invention provides a landslide identification method and system for a collapsible loess slope, a terminal and a storage medium, and the method comprises the steps: inputting a loess slope collection image into a landslide identification model, carrying out the haze concentration estimation and defogging processing, obtaining a collection recovery image, carrying out the feature extraction of the collection recovery image, and obtaining a collection feature map; carrying out landslide identification on the loess slope collection image according to the collection feature map to obtain a collection identification result, and carrying out parameter updating on the landslide identification model according to the collection identification result; and inputting the to-be-identified slope image into the converged landslide identification model for landslide identification to obtain a landslide identification result. According to the embodiment of the invention, defogging processing is carried out on the loess slope acquisition image through the haze estimation value, so that the converged landslide identification model can effectively carry out defogging on the to-be-identified slope image, and the landslide identification accuracy is improved.

The invention relates to the technical field of foundation treatment, in particular to a loess collapsible foundation treatment method based on porosity dynamic monitoring, which comprises the following steps: carrying out initial investigation on a loess collapsible foundation to obtain an initial investigation result, including the soil particle specific gravity, the moisture content, the density, the initial porosity and the collapsibility coefficient of foundation loess; according to the initial investigation result, a foundation treatment scheme is designed, and the scheme comprises determination of the treatment depth, the treatment range and a selected treatment method; foundation treatment is conducted according to the scheme, and in the foundation treatment process, the change of the loess porosity is monitored in real time through a porosity monitoring device; and according to the real-time monitoring data of the porosity, a foundation treatment scheme is adjusted or additional treatment measures are taken until the foundation porosity reaches a preset range and the foundation meets design requirements. The dynamic change of the loess porosity can be monitored in real time, foundation treatment measures can be adjusted in time according to the change of the porosity, and the loess collapsible foundation treatment effect and reliability can be improved.

The invention provides a loess slope deformation monitoring data processing method based on MEMS inertial sensor data and GNSS data, and relates to the technical field of slope deformation monitoring, and the method specifically comprises the following steps: calculating relative displacement and relative displacement, generating an accumulated displacement amount, and collecting rainfall characteristic parameters; iteratively optimizing the clusters and the cluster center points, confirming the number of each cluster sample, merging or splitting the clusters when a number threshold is not met until a preset threshold is met, and determining a final cluster and a cluster center point; determining a cluster to which the feature vector in the current time period belongs, and screening out similar historical time periods; and predicting the accumulated displacement in the next time period, and carrying out instability risk grade evaluation. According to the method, the clustering iteration method is adopted to continuously update the clustering and the clustering center point, the clustering structure is dynamically adjusted, the situation of excessive subdivision or excessive combination of the clustering is effectively avoided, and the loess slope instability risk level can be accurately predicted by means of the dynamic clustering optimization mechanism.

The invention provides a loess slope deformation monitoring and early warning method based on MEMS inertial sensor data and GNSS data, and relates to the technical field of geological deformation monitoring. Related parameters of a target loess slope area are collected, a loess slope geometric model is established, and the maximum arc surface section is screened; and performing stress analysis on the arc and the bottom edge of the arc surface section, determining the positions of first and second key measuring points, collecting angle change data and deformation displacement at the first and second key measuring points, finally setting threshold values of a deformation inclination angle and displacement variation, and if the monitoring data exceed a preset threshold value, giving an early warning by the system in time. Accurate monitoring and risk early warning of loess slope deformation are realized. According to the method, through combination of finite element mechanical model analysis and real-time monitoring of the MEMS inertial sensor and GNSS data, accurate identification and timely early warning of loess slope deformation are realized.

The invention provides a loess foundation dry-wet cycle settlement dynamic monitoring device and a using method thereof, and relates to the technical field of foundation settlement monitoring. The loess foundation dry-wet cycle settlement dynamic monitoring device comprises a first datum point, a liquid spraying assembly and a mounting base; the number of the first datum points and the number of the second datum points are both two, the two first datum points and the two second datum points are both fixed to the detected ground, and the two second datum points are located on the rear sides of the two first datum points. The mounting base and the liquid spraying assembly are both mounted on the ground, the liquid spraying assembly is composed of a mounting base, a mounting block, a liquid spraying pipe and an electric cylinder, the mounting base is fixed to the ground, the mounting block is slidably arranged on the mounting base, and the liquid spraying pipe is fixed to the right end face of the mounting block. According to the device, the two first datum points and the two second datum points are arranged and matched with the liquid spraying assembly, soil around the second datum points can be accurately wetted, foundation dry-wet cycle settlement monitoring is achieved, the monitoring range is effectively expanded, and a foundation is provided for comprehensively mastering the foundation settlement condition.

The invention discloses a loess region key section water and soil loss treatment method comprising the following steps: 1, carrying out landform analysis on a loess region to accurately identify a key section area with high risk of water and soil loss; step 2, carrying out terrace transformation on the key section by adopting a terrace type land reclamation technology, and introducing a water and soil conservation system and a drainage system at the same time; step 3, constructing a soil erosion prevention and control system mainly based on biological measures, including but not limited to vegetation restoration and application of a soil conditioner; 4, a water and soil loss monitoring system is established to monitor the treatment effect, regular maintenance is conducted through a maintenance mechanism, and the problems that a traditional water and soil loss treatment method is low in efficiency and not lasting in treatment effect are solved.

The application provides a loess slope stability evaluation method and system based on GNSS, and relates to the technical field of loess slope stability evaluation.The application first divides the slope area into grids, obtains geological feature data of each grid, divides super nodes according to the geological feature data, determines monitoring points and monitors soil moisture content to analyze the soil moisture content at different depths.Secondly, the original displacement is monitored by using GNSS, the displacement is corrected based on the Fredlund unsaturated soil shear strength theory to obtain the actual displacement, the influence of cumulative rainfall on the soil strength parameter is analyzed, and the soil strength parameter is corrected in real time, the corrected soil strength parameter and the actual displacement are coupled, the safety factor is calculated, and the early warning state is judged according to the rainfall sensitivity coefficient.Finally, the stability of the slope is comprehensively judged according to the early warning state.The method improves the accuracy of the slope stability evaluation through comprehensive analysis of multiple parameters.

The present invention belongs to the field of geological monitoring and discloses a device and method for observing the terminal channel of preferential seepage in large pores and constant water head in loess. The device comprises a camera, a funnel, foam glue, a first burette, a second burette, a three-way pipe for constant water head, a water bottle, a first iron stand, and a second iron stand. One end of the camera is fixed to the first iron stand. A permeable stone is set in the middle of the large opening of the funnel. The surface of the permeable stone is used to fix the original loess sample and the support tube. The space between the support tube and the loess sample is filled with foam glue. The first and third ends of the three-way pipe for constant water head are respectively connected to the water bottle and the first burette. The first burette and the second burette are connected by the second and third three-way pipes. Without disturbing the soil sample and with a fixed water head height, the terminal channel of preferential seepage in large pores and the water supply degree can be quickly observed. The work efficiency is high and the device is flexible and detachable. The device effectively solves the current problems of difficulty in capturing the preferential seepage large pore channels in loess and difficulty in measuring the water supply degree of original loess.

The invention discloses a foundation deep layer deformation observation device for a pile foundation in collapsible loess, and relates to the technical field of pile foundation deep layer observation, the device comprises a fixed shell and a control module, the upper side of the fixed shell is of a cylindrical structure, the lower side of the fixed shell is of a hemispherical structure, the lower side of the fixed shell is provided with a moving window, and the moving window is connected with the control module. A moving window is arranged in the fixed shell, a millimeter wave distance measuring module is arranged in the moving window and used for measuring the distance of the pile foundation, and a reinspection mechanism is arranged in the fixed shell and used for driving the millimeter wave distance measuring module to rotate. By means of the preset drilling hole arrangement mode, large-scale excavation, needed by a traditional method, around the pile is avoided, the purpose of implementing non-intrusive deep deformation observation on the built pile foundation is achieved, and the method has the advantage of conducting lossless observation on deep stratification deformation of the foundation.

The invention discloses a water-preserved coal mining method for water-proof soil layer reconstruction, which comprises the following steps: before coal mining, measuring the water level difference of an upper water-containing layer and a lower water-containing layer of a water-proof soil layer and the average natural permeability coefficient of the water-proof soil layer, and sealing a measured drill hole after measurement; directional drilling is carried out on the underlying stratum of the water-proof soil layer bottom plate, directional drilling holes penetrate through the coal mining subsidence area, and the horizontal sections of the directional drilling holes are located at the positions downwards away from the water-proof soil layer bottom plate; freezing in the implemented directional drill by adopting a freezing technology; vertical drilling is carried out on the ground; mixed liquid of loess and water is injected into all the vertical drill holes; the electric field set seepage field is connected through a vertical drill hole to pull the loess; after at least 10 days, performing a conventional water injection experiment on all the vertical drill holes every day, and determining the average permeability coefficient of the reconstructed waterproof soil layer; and after the standard is reached, freezing is stopped, and all the drilled holes are sealed. The method is economical, reasonable, easy to construct, free of pollution and short in effective period.

The invention belongs to the field of geological monitoring, and discloses a loess macropore seepage observation device and method based on a loess digital reconstruction body, and the loess macropore seepage observation device comprises the loess digital reconstruction body, a coloring agent container and a water discharging bottle; the bottom of the loess digital reconstruction body is provided with a permeable stone layer, and the top is provided with a hermetically connected top cover; a plurality of image acquisition devices are arranged around the loess digital reconstruction body; one sides of the drainage bottle and the permeable stone layer are communicated with the bottom of the coloring agent container; the first end of the three-way pipe is communicated with the interior of the top cover, the second end of the three-way pipe is provided with a pressure meter, and the third end of the three-way pipe is communicated with the atmosphere. The loess digital reconstruction body duplicates the macropore structure of the loess sample, the water flow migration process in the macropores of the loess digital reconstruction body can be rapidly observed, the water-driven gas process in the macropores of the loess digital reconstruction body can be rapidly determined, the working efficiency is high, the device is flexible and detachable, and the cost is low. The problem that the three-dimensional migration process of the water flow in the unsaturated loess macropores is difficult to accurately capture at present can be effectively solved.

The invention discloses a loess-mudstone landslide sliding grading displacement measurement method and system, and the method comprises the following steps: collecting the multi-point displacement data of a landslide body, and carrying out the preprocessing of the data, and generating a standardized multi-measurement-point displacement data sequence; obtaining overall and local deformation states; extracting evolution trend, space consistency and sliding loss features to form a displacement feature set; inputting an improved continuous time hidden Markov landslide state model, and generating a sliding state evolution sequence; analyzing the evolution sequence to generate a grading judgment result; an included angle threshold method and a shear displacement gradient method are adopted to recognize a concave-convex body and a sliding belt, and a key area identification result is generated; and outputting a sliding grading judgment result, a displacement feature set and a key area identification result. According to the invention, fine grading identification of the landslide state and accurate locking of the key area are realized, and the accuracy and foresight of monitoring and early warning are improved.

This invention discloses a multi-field coupled analysis method for loess slopes considering the influence of porosity, comprising: geometric modeling using finite element software; establishing a constitutive model related to porosity; introducing a porosity random field and atmospheric boundary conditions; calculating the slope safety factor using an improved strength reduction method; and obtaining the safety factor. The advantage of this invention is that the improved strength reduction method can be better used for calculating the slope safety factor and better simulates the stability of loess slopes under hydraulic coupling conditions.

The invention discloses a vibration-free foundation construction method for collapsible loess. The construction method provided by the invention comprises the following steps: dividing a construction area into grids, taking the intersection points of the grids as compaction points, detecting the initial dry density of the compaction points, drawing a density distribution thermodynamic diagram according to the initial dry density, and setting the initial pressure of compaction treatment on each compaction point according to the density distribution thermodynamic diagram; according to the initial pressure, compaction treatment is carried out at the compaction point, and gradient pressurization is carried out in the compaction treatment process until the preset depth is reached; regulating the water content to 18-22% according to the water content of the loess in the construction area; and the compaction point and the soil body compactness around the compaction point and the vibration acceleration of buildings around the construction area are monitored in real time, and when the soil body compactness change rate is smaller than 1% and the vibration acceleration is smaller than 0.1 g in at least three continuous detection periods, foundation treatment reaches the standard.

The invention relates to the technical field of pipeline monitoring, and discloses a loess mountainous area buried pipeline landslide disaster monitoring and early warning system and method.The loess mountainous area buried pipeline landslide disaster monitoring and early warning system comprises a monitoring system module, a data transmission system module and an early warning system module; inductive factors, pipeline deformation and landslide displacement are monitored through the monitoring system module, rainfall data, deformation data and landslide displacement data are obtained, and then the monitoring data are transmitted to the early warning system module in real time through the data transmission system module. The early warning system module judges the landslide disaster risk level according to the received monitoring data and sends out an early warning signal of the corresponding level, high-precision, real-time and all-weather monitoring can be carried out on a disaster point, the micro-deformation condition of the disaster point can be mastered in time, alarming of different levels is carried out according to the deformation degree, graded monitoring, graded early warning and graded risk avoiding are achieved, and the safety of the landslide disaster is improved. And effective disaster prevention and reduction effects are achieved.

This invention discloses a system and method for testing the collapsibility coefficient of undisturbed loess. The system includes a constant-force jacking device, a humidification and maintenance device, and a collapsibility coefficient determination device. The constant-force jacking device is installed at the annular soil mass within the test hole to apply a constant horizontal jacking force to the annular soil mass. The humidification and maintenance device covers the outside of the annular soil mass to gradually humidify it and obtain its moisture content. The collapsibility coefficient determination device is connected to the constant-force jacking device and the humidification and maintenance device to determine the collapsibility coefficient or self-weight collapsibility coefficient of the annular soil mass at different moisture contents based on the jacking distance of the constant-force jacking device. This invention utilizes undisturbed annular loess in the field, eliminating the need for sampling and indoor testing to obtain the collapsibility coefficient or self-weight collapsibility coefficient. It preserves the original structure of the loess, resulting in more accurate collapsibility test results that meet the needs of engineering design and disaster management.