A high slope deformation early warning method based on a Beidou system

Abstract

This invention relates to the field of environmental early warning technology, and discloses a high slope deformation early warning method based on the BeiDou system. The method includes the following steps: data acquisition, data preprocessing, deformation analysis, risk assessment, and signal transmission. This invention utilizes a BeiDou positioning terminal to accurately collect the location information of high slope monitoring points; the data preprocessing is scientific and effective, accurately identifying and replacing outliers by calculating displacement vectors and direction vectors, ensuring data quality and continuity; the deformation analysis is comprehensive, deriving multiple characteristic parameters to reflect the deformation status and changing trends of the high slope; the risk assessment is accurate, generating different levels of early warning signals by comparing with preset characteristic thresholds, enabling relevant departments to take targeted protective measures; and the efficient signal transmission ensures that early warning signals are delivered to relevant departments in a timely manner, improving emergency response efficiency, reducing the risk of high slope disasters, and providing strong technical support for high slope safety management.

Description

Technical Field

[0001] This invention relates to the field of environmental early warning technology, specifically to a method for early warning of high slope deformation based on the BeiDou system. Background Technology

[0002] With the continuous advancement of infrastructure construction, high slopes are becoming increasingly common in highway, railway, and water conservancy projects. The stability of high slopes is crucial to the safe operation of these projects; deformation or even landslides on high slopes pose a serious threat to people's lives and property and to engineering facilities. Traditional high slope monitoring methods mainly rely on manual measurement, which is not only inefficient but also has limited accuracy, making it difficult to meet the needs for real-time and accurate monitoring of high slopes. With the continuous development and improvement of the BeiDou Navigation Satellite System, its high-precision positioning function provides a new solution for high slope deformation monitoring.

[0003] The BeiDou Navigation Satellite System boasts advantages such as global coverage, high-precision positioning, and real-time monitoring, enabling all-weather, continuous monitoring of high slopes. By setting up monitoring points on high slopes and using BeiDou positioning terminals to collect the location information of these points, including longitude, latitude, and elevation, the deformation of the high slopes can be monitored in real time. However, due to various factors, the collected location information may contain outliers, which can affect the accuracy of deformation analysis. Therefore, it is necessary to preprocess the collected location information to remove outliers and improve data quality.

[0004] Furthermore, to promptly identify risks on high slopes, deformation analysis of the slopes is necessary, followed by risk assessment based on the analysis results, generating corresponding risk warning signals. Finally, the warning signals are sent to relevant departments so that timely protective measures can be taken to ensure the safety and stability of the high slopes.

[0005] In conclusion, the high slope deformation early warning method based on the BeiDou system has important practical significance and application value. Summary of the Invention

[0006] The purpose of this invention is to provide a method for early warning of high slope deformation based on the BeiDou system, which solves the technical problems mentioned in the background art.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A method for early warning of deformation of high slopes based on the BeiDou system includes the following steps:

[0009] Step 1: Data Collection

[0010] Monitoring points were set up on high slopes using BeiDou positioning terminals, and the location information of the monitoring points, including longitude, latitude and elevation, was collected regularly.

[0011] The collection frequency for regular collection is preset by relevant personnel.

[0012] Step 2: Data Preprocessing

[0013] The location information of the monitoring points is preprocessed, and then outliers in the location information are replaced based on the preprocessing results.

[0014] Step 3: Deformation Analysis

[0015] Based on the preprocessed location information, deformation analysis is performed on the high slope, and then the characteristic parameters of the high slope are obtained based on the analysis results.

[0016] Step 4: Risk Assessment

[0017] The characteristic parameters of the high slope are extracted, compared and judged in combination with the preset characteristic thresholds, and based on the comparison and judgment results, it is determined whether the high slope has a risk and a warning signal of the corresponding level is generated.

[0018] Step 5: Signal Transmission

[0019] The generated early warning signals will be sent to relevant departments so that they can take timely protective measures for high slopes.

[0020] As a further aspect of the present invention, the preprocessing method is as follows:

[0021] SS1. Acquire multiple sets of location information collected within a specified period and mark them as E according to the time sequence. i = (X i Y i Z i );

[0022] Where i = 1, 2, ..., n, n represents the number of location information collected from the monitoring point periodically within the specified period;

[0023] Where n is obtained by n=T0 / μ, where T0 is the total duration within the specified period, μ is the sampling frequency of periodic collection, and n also represents the number of sampling time nodes within the specified period;

[0024] Among them, X i This indicates which data collection point within a specified period yields the longitude, Y. i This indicates which data collection time point within a specified period yields the latitude, Z. i This indicates which data collection time point within a specified period yielded the elevation.

[0025] SS2. Obtain location information from adjacent acquisition time nodes;

[0026] Then through Calculate the displacement vector W corresponding to the location information of each adjacent acquisition time node. i ;

[0027] Subsequently passed Calculate the magnitude |W| of the displacement vector corresponding to the location information of each adjacent acquisition time node. i |;

[0028] Then through Calculate the direction vector W1 of the location information corresponding to each adjacent acquisition time node. i ;

[0029] SS3. Calculate the direction vector W1 corresponding to the location information of all adjacent acquisition time nodes. i The average value is used to label the principal direction vector WP.

[0030] in,

[0031] ;

[0032] SS4, Pass

[0033] The corresponding E is calculated. i The cosine value of the corresponding angle;

[0034] Among them, |W1 i | and |WP| are respectively W1 i And the WP model;

[0035] Then through

[0036] Calculate the corresponding E i corresponding angle ;

[0037] SS5, subsequently Angle threshold with preset Comparison:

[0038] like ≤ Then determine the location information E i = (X i Y i Z i This is not an outlier;

[0039] like > Then determine the location information E i = (X i Y i Z i ) is an outlier;

[0040] Subsequently, the location information obtained from two adjacent acquisition time nodes corresponding to this location information is acquired: E i-1 = (X i-1 Y i-1 Z i-1 ) and E i+1 = (X i+1 Y i+1 Z i+1 );

[0041] and through

[0042] Calculate the replacement value ET for the location information corresponding to the acquisition time point;

[0043] Next, the location information E corresponding to the time node will be collected. i Replace with ET.

[0044] As a further aspect of the present invention, the deformation analysis method is as follows:

[0045] SK1 will re-mark multiple sets of preprocessed location information within a specified period according to the time sequence as U i = (A i B i C i );

[0046] Among them, A i Corresponding to X i B i Corresponding to Y i C i Corresponding to Z i ;

[0047] SK2. Obtain location information from adjacent acquisition time points;

[0048] Then through Calculate the first shape variable D corresponding to each adjacent data collection time point of the monitoring point. i ;

[0049] At the same time Calculate the second deformation D0 of the high slope corresponding to the monitoring point within the specified period;

[0050] SK3. Determine the interval between adjacent acquisition time nodes based on the acquisition frequency, and mark it as t;

[0051] Then through V i =D i / t, calculate the U corresponding to the monitoring point on the high slope. i The first deformation rate V at the corresponding acquisition time pointi ;

[0052] At the same time, the second deformation rate V0 of the high slope corresponding to the monitoring point in the specified period is calculated by V0=D0 / T0;

[0053] SK4, via J i =V i -V i-1 / t, calculate the corresponding monitoring point for the high slope at U i Deformation acceleration J at the corresponding acquisition time point i ;

[0054] Among them, V i-1 For U i The deformation rate at the time node adjacent to the previous time node corresponding to the acquisition time node.

[0055] As a further aspect of the present invention, the comparison and determination method is as follows:

[0056] SY1, Extract the corresponding preset first deformation threshold D y1 First deformation threshold 2D2 y1 and the first deformation threshold 3D3 y1 And D y1 <D2 y1 <D3 y1 ;

[0057] Simultaneously, the corresponding preset second deformation threshold D is extracted. y2 Second deformation threshold D2 y2 Second deformation threshold threeD3 y2 And D y2 <D2 y2 <D3 y2 ;

[0058] Simultaneously, extract the corresponding preset first rate threshold V. y1 First rate threshold 2V2 y1 and the first rate threshold three V3 y1 And V y1 <V2 y1 <V3 y1 ;

[0059] Simultaneously, extract the corresponding preset second rate threshold V. y2 Second rate threshold V2 y2 Second rate threshold three V3 y2 And V y2 <V2 y2 <V3 y2 ;

[0060] At the same time, the corresponding preset deformation acceleration J is extracted.y Deformation acceleration J2 y and deformation acceleration three J3 y And J y <J2 y <J3 y ;

[0061] SY2, Extract the first form variable D i Second deformation D0, first deformation rate V i Second deformation rate V0, deformation acceleration J i ;

[0062] SY3, change the first shape variable D i Second deformation D0, first deformation rate V i Second deformation rate V0, deformation acceleration J i Defined as eigenvector factor G∈[D] i ,D0,V i ,V0,J i ]

[0063] The first deformation threshold D y1 Second deformation threshold D y2 First rate threshold V y1 Second rate threshold V y2 Deformation acceleration J y Defined as the feature vector threshold - G y ∈[D y1 D y2 V y1 V y2 J y ];

[0064] The first deformation threshold is D2. y1 Second deformation threshold D2 y2 First rate threshold 2V2 y1 First rate threshold 2V2 y1 Deformation acceleration J2 y Defined as the feature vector threshold G2 y ∈[D2 y1 D2 y2 V2 y1 V2 y2 J2 y ];

[0065] The first deformation threshold is 3D3 y1 Second deformation threshold threeD3 y2 First rate threshold three V3 y1 Second rate threshold three V3 y2 Deformation acceleration three J3y Defined as the feature vector threshold three G3 y ∈[D3 y1 D3 y2 V3 y1 V3 y2 J3 y ];

[0066] SY4, Combine the eigenvector factor G with the eigenvector threshold G. y Feature vector thresholding G2 y , Feature vector threshold three G3 y Comparison:

[0067] When G≤G y And D i ≤D y1 ,D0≤D y2 V i ≤V y1 V0≤V y2 J i ≤J y If all conditions are met, no warning signal will be generated;

[0068] If in D i ≤D y1 ,D0≤D y2 V i ≤V y1 V0≤V y2 J i ≤J y If any one of the following is false:

[0069] When G y <G≤G2 y If so, a Level 1 warning signal will be generated, which indicates that there is a slight risk to the high slope;

[0070] When G2 y <G≤G3 y If so, a Level II warning signal will be generated, which indicates that the high slope has a medium risk.

[0071] When G > G3 y If this occurs, a Level 3 warning signal will be generated, indicating that there is a serious risk to the high slope.

[0072] The beneficial effects of this invention are:

[0073] This invention utilizes a BeiDou positioning terminal to set up monitoring points on high slopes, enabling precise collection of longitude, latitude, and elevation information of the monitoring points, providing an accurate data foundation for high slope deformation analysis.

[0074] This invention, through preprocessing of monitoring point location information, can effectively identify and replace outliers, ensuring the accuracy of subsequent deformation analysis.

[0075] This invention calculates the displacement vector, magnitude, and direction vector of adjacent acquisition time nodes, and obtains the main direction vector by averaging them, thereby determining whether the position information is an anomaly and improving the reliability of the data.

[0076] This invention uses location information from two adjacent data collection time points to calculate and replace outliers, further ensuring the continuity and accuracy of the data.

[0077] This invention performs deformation analysis on preprocessed location information and calculates characteristic parameters of high slopes at various data acquisition time points, such as the first deformation, second deformation, first deformation rate, second deformation rate, and deformation acceleration, to comprehensively reflect the deformation of high slopes.

[0078] This invention determines the interval between adjacent acquisition time nodes based on the acquisition frequency, and then calculates the deformation rate and deformation acceleration, making the analysis results more scientific and reasonable.

[0079] This invention presets different levels of feature thresholds, including a first deformation threshold, a second deformation threshold, a first rate threshold, a second rate threshold, and a deformation acceleration threshold. By comparing the feature vector factors of a high slope with these thresholds, the risk level of the high slope can be accurately determined.

[0080] This invention generates corresponding early warning signals based on risk levels, divided into Level 1, Level 2, and Level 3 warnings, providing clear risk alerts to relevant departments and facilitating timely implementation of protective measures.

[0081] This invention sends the generated early warning signal to relevant departments to ensure that they can promptly understand the risk situation of high slopes, so as to respond quickly and take effective protective measures to reduce the safety hazards caused by high slope deformation. Attached Figure Description

[0082] The invention will now be further described with reference to the accompanying drawings.

[0083] Figure 1 This is a system block diagram of a high slope deformation early warning method based on the Beidou system according to the present invention. Detailed Implementation

[0084] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0085] Example 1

[0086] Please see Figure 1 As shown, this invention is a method for early warning of high slope deformation based on the BeiDou system, comprising the following steps:

[0087] Step 1: Data Collection

[0088] Monitoring points were set up on high slopes using BeiDou positioning terminals, and the location information of the monitoring points, including longitude, latitude and elevation, was collected regularly.

[0089] In this embodiment, the sampling frequency is adjusted according to the actual situation. In this embodiment, the sampling frequency is once per hour.

[0090] Step 2: Data Preprocessing

[0091] The location information of the monitoring points is preprocessed, and then outliers in the location information are replaced based on the preprocessing results.

[0092] The specific method is as follows:

[0093] SS1. Acquire multiple sets of location information collected within a specified period and mark them as E according to the time sequence. i = (X i Y i Z i );

[0094] Where i = 1, 2, ..., n, n represents the number of location information collected from the monitoring point periodically within the specified period;

[0095] In this embodiment, n is obtained by n=T0 / μ, where T0 is the total duration within the specified period, μ is the sampling frequency of periodic sampling, and n also represents the number of sampling time nodes within the specified period.

[0096] Among them, X i This indicates which data collection point within a specified period yields the longitude, Y. i This indicates which data collection time point within a specified period yields the latitude, Z. i This indicates which data collection time point within a specified period yielded the elevation.

[0097] SS2. Obtain location information from adjacent acquisition time nodes;

[0098] Then through Calculate the displacement vector W corresponding to the location information of each adjacent acquisition time node. i ;

[0099] Subsequently passed Calculate the magnitude |W| of the displacement vector corresponding to the location information of each adjacent acquisition time node. i |;

[0100] Then through Calculate the direction vector W1 of the location information corresponding to each adjacent acquisition time node. i ;

[0101] SS3. Calculate the direction vector W1 corresponding to the location information of all adjacent acquisition time nodes. i The average value is used to label the principal direction vector WP.

[0102] in,

[0103] ;

[0104] SS4, Pass

[0105] The corresponding E is calculated. i The cosine value of the corresponding angle;

[0106] Among them, |W1 i | and |WP| are respectively W1 i And the WP model;

[0107] Then through

[0108] Calculate the corresponding E i corresponding angle ;

[0109] SS5, subsequently Angle threshold with preset Comparison:

[0110] like ≤ Then determine the location information E i = (X i Y i Z i This is not an outlier;

[0111] like > Then determine the location information E i = (Xi Y i Z i ) is an outlier;

[0112] Subsequently, the location information obtained from two adjacent acquisition time nodes corresponding to this location information is acquired: E i-1 = (X i-1 Y i-1 Z i-1 ) and E i+1 = (X i+1 Y i+1 Z i+1 );

[0113] and through

[0114] Calculate the replacement value ET for the location information corresponding to the acquisition time point;

[0115] Next, the location information E corresponding to the time node will be collected. i Replace with ET;

[0116] Step 3: Deformation Analysis

[0117] Based on the preprocessed location information, deformation analysis is performed on the high slope. Then, based on the analysis results, it is determined whether there is a risk to the high slope and a risk warning signal is generated.

[0118] The deformation analysis method is as follows:

[0119] SK1 will re-mark multiple sets of preprocessed location information within a specified period according to the time sequence as U i = (A i B i C i );

[0120] Among them, A i Corresponding to X i B i Corresponding to Y i C i Corresponding to Z i ;

[0121] SK2. Obtain location information from adjacent acquisition time points;

[0122] Then through The first deformation D corresponding to each adjacent data collection time point of the high slope was calculated. i ;

[0123] At the same time Calculate the second deformation D0 of the high slope corresponding to the monitoring point within the specified period;

[0124] SK3. Determine the interval between adjacent acquisition time nodes based on the acquisition frequency, and mark it as t;

[0125] Then through V i =D i / t, calculate U corresponding to the monitoring point on the high slope. i The first deformation rate V at the corresponding acquisition time point i ;

[0126] At the same time, the second deformation rate V0 of the high slope corresponding to the monitoring point in the specified period is calculated by V0=D0 / T0;

[0127] SK4, via J i =V i -V i-1 / t, calculate the corresponding monitoring point for the high slope at U i Deformation acceleration J at the corresponding acquisition time point i ;

[0128] Among them, V i-1 For U i The deformation rate at the time node immediately preceding the corresponding acquisition time node;

[0129] SK5, change the first deformation variable D i Second deformation D0, first deformation rate V i Second deformation rate V0, deformation acceleration J i Each is compared with the preset first deformation threshold D y1 Second deformation threshold D y2 First rate threshold V y1 Second rate threshold V y2 Deformation acceleration J y Comparison:

[0130] When the first deformation D i >First deformation threshold D y1 If so, an early warning signal will be generated;

[0131] When the second deformation D0 > the second deformation threshold D y2 If so, an early warning signal will be generated;

[0132] When the first deformation rate V i >First rate threshold V y1 If so, an early warning signal will be generated;

[0133] When the second deformation rate V0 > the second rate threshold V y2 If so, an early warning signal will be generated;

[0134] When the deformation acceleration Ji >Deformation acceleration J y If so, an early warning signal will be generated;

[0135] If none of the above comparison results are true, no warning signal will be generated;

[0136] Step 4: Signal Transmission

[0137] The generated early warning signals will be sent to relevant departments so that they can take timely protective measures for high slopes.

[0138] This embodiment utilizes a BeiDou positioning terminal to set up monitoring points on high slopes to collect location information, enabling precise monitoring of high slopes. By periodically collecting location information, the deformation dynamics of high slopes can be grasped in a timely manner. Preprocessing the location information and replacing outliers improves the accuracy and reliability of the data, providing a more reliable data foundation for subsequent deformation analysis. Deformation analysis of high slopes can determine whether there are risks and generate risk warning signals based on the analysis results, facilitating relevant departments to take timely protective measures for high slopes and effectively prevent the occurrence of high slope disasters.

[0139] Example 2

[0140] As a second embodiment of the present invention, in specific implementation, the technical solution of this embodiment differs from that of embodiment one only in that:

[0141] It also has a corresponding value greater than the first deformation threshold D. y1 The first deformation threshold is D2 y1 and the first deformation threshold 3D3 y1 And D y1 <D2 y1 <D3 y1 ;

[0142] When D i ≤D y1 If not, no warning signal will be generated;

[0143] When D y1 <D i ≤D2 y1 If so, a Level 1 warning signal will be generated, which indicates that there is a slight risk to the high slope;

[0144] When D2 y1 <D i ≤D3 y1 If so, a Level II warning signal will be generated, which indicates that the high slope has a medium risk.

[0145] When D i >D3 y1If so, a Level 3 warning signal will be generated, which indicates that there is a serious risk to the high slope;

[0146] It also corresponds to a value greater than the second deformation threshold D. y2 The second deformation threshold is D2 y2 Second deformation threshold threeD3 y2 And D y2 <D2 y2 <D3 y2 ;

[0147] When D0≤D y2 If not, no warning signal will be generated;

[0148] When D y2 <D0≤D2 y2 If so, a Level 1 warning signal will be generated;

[0149] When D2 y2 <D0≤D3 y2 If so, a level-two warning signal will be generated;

[0150] When D0>D3 y2 Then a level three warning signal will be generated;

[0151] It also has a corresponding value greater than the first rate threshold V. y1 The first rate threshold is V2 y1 and the first rate threshold three V3 y1 And V y1 <V2 y1 <V3 y1 ;

[0152] When V i ≤V y1 If not, no warning signal will be generated;

[0153] When V y1 <V i ≤V2 y1 If so, a Level 1 warning signal will be generated;

[0154] When V2 y1 <V i ≤V3 y1 If so, a level-two warning signal will be generated;

[0155] When V i >V3 y1 Then a level three warning signal will be generated;

[0156] It also corresponds to a rate threshold V greater than the second rate threshold. y2 The second rate threshold is V2 y2 Second rate threshold three V3 y2 And V y2 <V2y2 <V3 y2 ;

[0157] When V0≤V y2 If not, no warning signal will be generated;

[0158] When V y2 <V0≤V2 y2 If so, a Level 1 warning signal will be generated;

[0159] When V2 y2 <V0≤V3 y2 If so, a level-two warning signal will be generated;

[0160] When V0 > V3 y2 Then a level three warning signal will be generated;

[0161] It also has a corresponding setting greater than the deformation acceleration J y Deformation acceleration J2 y and deformation acceleration three J3 y And J y <J2 y <J3 y ;

[0162] When J i ≤J y If not, no warning signal will be generated;

[0163] When J y <J i ≤J2 y If so, a Level 1 warning signal will be generated;

[0164] When J2 y <J i ≤J3 y If so, a level-two warning signal will be generated;

[0165] When J i >J3 y If so, a Level 3 warning signal will be generated.

[0166] This embodiment further refines the early warning levels based on Embodiment 1. By setting multiple different levels of deformation thresholds, rate thresholds, and deformation acceleration thresholds, the risk level of high slopes can be assessed more accurately, providing more specific guidance for relevant departments to take targeted protective measures. The generation of early warning signals at different levels enables relevant departments to rationally allocate resources according to the early warning level, conduct hierarchical management of high slopes, and improve the efficiency and effectiveness of protective measures.

[0167] Example 3

[0168] As a third embodiment of the present invention, in specific implementation, compared with embodiments one and two, the technical solution of this embodiment is to combine the solutions of embodiments one and two. The only difference between the technical solution of this embodiment and embodiments one and two is that in this embodiment, multiple monitoring points are set up on the high slope using a Beidou positioning terminal, and then multi-point early warning is carried out according to the solutions of embodiments one and two, so as to avoid the problem that the safety hazards of the high slope cannot be detected in time due to the abnormality of the Beidou positioning terminal corresponding to a single monitoring point.

[0169] This embodiment combines the advantages of Embodiments 1 and 2, and simultaneously sets up multiple monitoring points on the high slope for multi-point early warning. This avoids the problem of failing to detect potential safety hazards on the high slope in a timely manner due to anomalies in the BeiDou positioning terminal corresponding to a single monitoring point, thus improving the reliability and accuracy of monitoring. Multi-point early warning allows for a more comprehensive understanding of the overall deformation of the high slope, providing stronger protection for the safety management of high slopes.

[0170] Example 4

[0171] As a fourth embodiment of the present invention, in specific implementation, compared with embodiments one, two and three, the technical solution of this embodiment is to combine the solutions of embodiments one, two, three and four.

[0172] This embodiment combines the advantages of Embodiments 1, 2, and 3, further improving the high slope deformation early warning method. By combining multiple schemes, the accuracy, reliability, and comprehensiveness of the early warning are improved; it can better adapt to the actual conditions of different high slopes, providing a more effective solution for the safety protection of high slopes.

[0173] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0174] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for early warning of deformation of high slopes based on the BeiDou system, characterized in that, Includes the following steps: Step 1: Data Collection Monitoring points were set up on high slopes using BeiDou positioning terminals, and the location information of the monitoring points, including longitude, latitude and elevation, was collected regularly. Step 2: Data Preprocessing The location information of the monitoring points is preprocessed, and then outliers in the location information are replaced based on the preprocessing results. The preprocessing method is as follows: SS1. Acquire multiple sets of location information collected within a specified period and mark them as E according to the time sequence. i = (X i Y i Z i ); Where i = 1, 2, ..., n, n represents the number of location information collected from the monitoring point periodically within the specified period; Among them, X i This indicates which data collection point within a specified period yields the longitude, Y. i This indicates which data collection time point within a specified period yields the latitude, Z. i This indicates which data collection time point within a specified period yielded the elevation. SS2. Obtain location information from adjacent acquisition time nodes; Then through Calculate the displacement vector W corresponding to the location information of each adjacent acquisition time node. i ; Subsequently passed Calculate the magnitude |W| of the displacement vector corresponding to the location information of each adjacent acquisition time node. i |; Then through Calculate the direction vector W1 of the location information corresponding to each adjacent acquisition time node. i ; SS3. Calculate the direction vector W1 corresponding to the location information of all adjacent acquisition time nodes. i The average value is used to label the principal direction vector WP. in, ； SS4, Pass The corresponding E is calculated. i The cosine value of the corresponding angle; Among them, |W1 i | and |WP| are respectively W1 i And the WP model; Then through Calculate the corresponding E i Corresponding angle ; SS5, subsequently Angle threshold with preset Comparison: like > Then determine the location information E i = (X i Y i Z i ) is an outlier; Subsequently, the location information obtained from two adjacent acquisition time nodes corresponding to this location information is acquired: E i-1 = (X i-1 Y i-1 Z i-1 ) and E i+1 = (X i+1 Y i+1 Z i+1 ); and through Calculate the replacement value ET for the location information corresponding to the collection time node; Next, the location information E corresponding to the time node will be collected. i Replace with ET; Step 3: Deformation Analysis Based on the preprocessed location information, deformation analysis is performed on the high slope, and then the characteristic parameters of the high slope are obtained based on the analysis results. Step 4: Risk Assessment The characteristic parameters of the high slope are extracted, compared and judged in combination with the preset characteristic thresholds, and based on the comparison and judgment results, it is determined whether the high slope has a risk and a warning signal of the corresponding level is generated. Step 5: Signal Transmission The generated early warning signals will be sent to relevant departments so that they can take timely protective measures for high slopes.

2. The method for early warning of high slope deformation based on the BeiDou system according to claim 1, characterized in that, In SS5, if ≤ Then determine the location information E i = (X i Y i Z i () is not an outlier.

3. The method for early warning of high slope deformation based on the BeiDou system according to claim 1, characterized in that, in, n is obtained by n=T0 / μ, where T0 is the total duration within the specified period, μ is the sampling frequency of periodic sampling, and n also represents the number of sampling time nodes within the specified period.

4. The method for early warning of high slope deformation based on the BeiDou system according to claim 3, characterized in that, The deformation analysis method is as follows: SK1 will re-mark multiple sets of preprocessed location information within a specified period according to the time sequence as U i = (A i B i C i ); Among them, A i Corresponding to X i B i Corresponding to Y i C i Corresponding to Z i ; SK2. Obtain location information from adjacent acquisition time points; Then through Calculate the first shape variable D corresponding to each adjacent data collection time point of the monitoring point. i ; At the same time Calculate the second deformation D0 of the high slope corresponding to the monitoring point within the specified period; SK3. Determine the interval between adjacent acquisition time nodes based on the acquisition frequency, and mark it as t; Then through V i =D i / t, calculate the monitoring point U i The first deformation rate V at the corresponding acquisition time point i ; At the same time, the second deformation rate V0 of the high slope corresponding to the monitoring point in the specified period is calculated by V0=D0 / T0; SK4, via J i =V i -V i-1 / t, calculate the corresponding monitoring point for the high slope at U i Deformation acceleration J at the corresponding acquisition time point i ; Among them, V i-1 For U i The deformation rate at the time node adjacent to the previous time node corresponding to the acquisition time node.

5. The method for early warning of high slope deformation based on the BeiDou system according to claim 1, characterized in that, in, The collection frequency is preset by relevant personnel.

6. The method for early warning of high slope deformation based on the BeiDou system according to claim 4, characterized in that, The preset feature thresholds include: the first deformation D i Corresponding to the preset first deformation threshold D y1 First deformation threshold 2D2 y1 and the first deformation threshold 3D3 y1 And D y1 <D2 y1 <D3 y1 The second deformation threshold D corresponds to the second deformation variable D0. y2 Second deformation threshold D2 y2 Second deformation threshold threeD3 y2 And D y2 <D2 y2 <D3 y2 ; and the first deformation rate V i Corresponding to the preset first rate threshold V y1 First rate threshold 2V2 y1 and the first rate threshold three V3 y1 And V y1 <V2 y1 <V3 y1 The second deformation rate V0 corresponds to a preset second rate threshold V. y2 Second rate threshold V2 y2 Second rate threshold three V3 y2 And V y2 <V2 y2 <V3 y2 ; and deformation acceleration J i Corresponding to the preset deformation acceleration J y Deformation acceleration J2 y and deformation acceleration three J3 y And J y <J2 y <J3 y .

7. A method for early warning of high slope deformation based on the BeiDou system according to claim 6, characterized in that, The comparison and determination method is as follows: SY1, change the first shape variable D i Second deformation D0, first deformation rate V i Second deformation rate V0, deformation acceleration J i Defined as eigenvector factor G∈[D] i ,D0,V i ,V0,J i ] SY2, set the first deformation threshold D y1 Second deformation threshold D y2 First rate threshold V y1 Second rate threshold V y2 Deformation acceleration J y Defined as the feature vector threshold - G y ∈[D y1 D y2 V y1 V y2 J y ]; SY3, set the first deformation threshold to D2. y1 Second deformation threshold D2 y2 First rate threshold 2V2 y1 First rate threshold 2V2 y1 Deformation acceleration J2 y Defined as the feature vector threshold G2 y ∈[D2 y1 D2 y2 V2 y1 V2 y2 J2 y ]; SY4, set the first deformation threshold to 3D3 y1 Second deformation threshold threeD3 y2 First rate threshold three V3 y1 Second rate threshold three V3 y2 Deformation acceleration three J3 y Defined as the feature vector threshold three G3 y ∈[D3 y1 D3 y2 V3 y1 V3 y2 J3 y ]; SY5. Combine the eigenvector factor G with the eigenvector threshold G. y Feature vector thresholding G2 y , Feature vector threshold three G3 y The risk level of the high slope is determined by comparison, and the corresponding warning signal is obtained based on the comparison results.

8. A method for early warning of high slope deformation based on the BeiDou system according to claim 7, characterized in that, In SY5, When G y <G≤G2 y If so, a Level 1 warning signal will be generated, which indicates that there is a slight risk to the high slope; When G2 y <G≤G3 y If so, a Level II warning signal will be generated, which indicates that the high slope has a medium risk. When G > G3 y If this occurs, a Level 3 warning signal will be generated, indicating that there is a serious risk to the high slope.

9. A method for early warning of high slope deformation based on the BeiDou system according to claim 7, characterized in that, In SY5, when G≤G y And D i ≤D y1 ,D0≤D y2 V i ≤V y1 V0≤V y2 J i ≤J y If all conditions are met, no warning signal will be generated.

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