CN-121977421-A - High-precision GNSS slope displacement monitoring system and method suitable for loess collapsibility characteristics

CN121977421ACN 121977421 ACN121977421 ACN 121977421ACN-121977421-A

Abstract

The invention discloses a high-precision GNSS slope displacement monitoring system and method suitable for loess collapse characteristics, wherein the high-precision GNSS slope displacement monitoring system comprises a GNSS monitoring module, a data acquisition and transmission module and a cloud platform early warning center, wherein the GNSS monitoring module comprises at least one monitoring point and a datum point, the monitoring point is welded and fixed on an existing on-site protection steel pipe through an L-shaped mounting base, the data acquisition and transmission module is integrated in a waterproof box and comprises a data acquisition instrument, an MEMS sensor, a communication module and a power supply system which are electrically connected with the monitoring point, the cloud platform early warning center is used for receiving data transmitted by the communication module and carrying out data fusion, resolving and grading early warning, and the data fusion of the GNSS and the MEMS sensor is adopted to make up the limitation of a single technology, so that all-weather and all-condition high-precision continuous displacement monitoring is realized.

Inventors

XU DONGHUI
WU WANCHUN
PENG JIAWANG
LONG CAIHONG
ZHANG JING
FAN XIN
Shi Danye
NAN YONG
ZHONG YICONG
MA BEN
ZHANG HUIJUN

Assignees

上海勘测设计研究院有限公司
三峡(上海)工程检测有限公司

Dates

Publication Date: 20260505
Application Date: 20260114

Claims (15)

1. High accuracy GNSS side slope displacement monitoring system suitable for loess collapsible characteristic, its characterized in that includes: The GNSS monitoring module comprises at least one monitoring point and a datum point, wherein the monitoring point is welded and fixed on an existing field protection steel pipe through an L-shaped mounting base; The data acquisition and transmission module is integrated in the waterproof box and comprises a data acquisition instrument, an MEMS sensor, a communication module and a power supply system which are electrically connected with the monitoring point; and the cloud platform early warning center is used for receiving the data transmitted by the communication module and carrying out data fusion calculation and hierarchical early warning.
2. The high-precision GNSS slope displacement monitoring system applicable to loess collapsibility characteristics according to claim 1, wherein the burial depth of the protective steel pipe is not less than 1.5 meters.
3. The high-precision GNSS slope displacement monitoring system suitable for loess collapsible property according to claim 1, wherein the data acquisition instrument is provided with an intelligent wake-up algorithm, and the monitoring frequency is supported to be adjusted in a self-adaptive manner according to a vehicle passing event.
4. The high-precision GNSS slope displacement monitoring system suitable for loess collapsible property as claimed in claim 1, wherein the power supply system comprises a 60AH high-capacity lithium battery and an external solar charging panel, and forms a commercial power and solar complementary two-way power supply system.
5. The high-precision GNSS slope displacement monitoring system suitable for loess collapsible property according to claim 1, wherein the cloud platform early warning center has a function of fusion and calculation of GNSS and MEMS data, and is provided with yellow, orange and red three-level early warning thresholds.
6. The high-precision GNSS slope displacement monitoring system of claim 1, wherein the reference points comprise base station piles, the base station piles are laid on a stable foundation, and the base station comprises a steel plate base, welded steel pipes, triangular steel reinforcement structures and screw steel connectors, and the GNSS base station is installed on top.
7. The high-precision GNSS slope displacement monitoring system for loess collapsible characteristics as claimed in claim 1, wherein said monitoring points comprise sub-millimeter level GNSS receivers connected to an L-shaped mounting base by threaded bolts.
8. The high-precision GNSS slope displacement monitoring system applicable to loess collapsibility according to claim 1, wherein the protection level of the data acquisition and transmission module is IP65.
9. A monitoring method of the high-precision GNSS slope displacement monitoring system applicable to loess collapse characteristics as set forth in any of claims 1 to 8, comprising the steps of: step a, respectively arranging monitoring points and datum points in key positions and stable areas of the loess slope; B, installing a waterproof box at a monitoring point, integrating a data acquisition instrument, an MEMS sensor, a communication module and a lithium battery in the box, installing an antenna of a GNSS receiver on an L-shaped base, and connecting the antenna with the data acquisition instrument through an Ethernet interface; Step c, after the system is started, the data acquisition instrument automatically manages the working mode according to a built-in intelligent scheduling algorithm based on double-threshold hysteresis comparison; Step d, the acquired GNSS original observation data and MEMS original data are uploaded to a cloud platform in real time through a 4G module, and the platform carries out high-precision displacement calculation by adopting a tight coupling fusion algorithm based on extended Kalman filtering; step e, the cloud platform presets three-level early warning thresholds, namely yellow early warning, orange early warning and red early warning according to engineering safety criteria, and early warning triggering adopts joint judgment logic; Step f, when the GNSS signal is blocked or out of lock, the system is seamlessly switched to the MEMS pure inertial navigation mode, and at the moment, measurement update is suspended, and state extrapolation is performed only by means of an EKF time update link; And g, after the monitoring task is finished, rapidly disassembling each module of the system.
10. The high-precision GNSS slope displacement monitoring system for loess collapse characteristic as claimed in claim 9, wherein in said step a, the monitoring points are welded and fixed on the existing on-site protective steel pipe by L-shaped mounting base, the buried depth of the steel pipe is not less than 1.5 m to resist loess collapse and shallow disturbance, the reference points are arranged on the stable foundation, the GNSS base station is installed by the stable structure, and the accurate coordinates thereof are installed by the stable structure Through static observation for more than 48 hours, the method is obtained by adopting a precise single-point positioning algorithm for solving, and particularly, the method is used for carrying out iterative solution through a least square adjustment model: wherein: The accurate three-dimensional coordinate vector to be solved by the reference station; To the first Pseudo-range observations of the satellites; reference station position To the first Geometric distance of the satellites; The speed of light; first of all The satellite clock difference of the satellites is provided by the precise ephemeris; Model corrections for ionospheric delay and tropospheric delay, respectively; The number of the common view satellites; the coordinates will serve as a displacement solution reference for the entire monitoring network.
11. The high-precision GNSS slope displacement monitoring system according to claim 9, wherein in the step c, the data acquisition device automatically manages the operation mode according to the built-in intelligent scheduling algorithm based on dual-threshold hysteresis comparison, specifically including: ① Conventional Low frequency mode, system in sleep state, every time Wake-up to collect data once in seconds; ② Event detection and triggering, namely calculating signal energy output by MEMS accelerometer in real time : Wherein: time of day Acceleration signal energy value of (2); sliding the length of the time window; time of day An original output value of the triaxial accelerometer; the current time is; When (when) When the vibration event is judged to be effective, the vibration event is immediately switched to a high-frequency mode, and the acquisition period is shortened to Simultaneously adopts a mode switching hysteresis mechanism, adopts double-threshold hysteresis comparison for avoiding frequent switching, and is only used when And is provided with Continuous and continuous After a period, the system returns to the low frequency mode.
12. The high-precision GNSS slope displacement monitoring system suitable for loess collapsible property according to claim 9, wherein in the step d, the specific flow of the platform performing high-precision displacement calculation by adopting the tight coupling fusion algorithm based on the extended kalman filter is as follows: ① GNSS differential preprocessing, namely, double-difference combination is carried out on carrier phase observation values of a reference station b and a monitoring station r, and receiver clock differences and satellite clock differences are eliminated: wherein: the double difference operator, firstly, single difference between stations and then single difference between satellites; the carrier phase double difference observation values of the reference station b and the monitoring station r to the satellites p and q are phase values with length as a unit; The wavelength of the carrier signal; The geometric distance between the reference station and the monitoring station and the satellites p and q is double difference; The carrier phase integer ambiguity double difference; observing double differences of noise and unmodeled errors; the improved LAMBDA algorithm is adopted to fix the ambiguity: wherein: searching the obtained optimal integer ambiguity vector solution; Ambiguity resolution; A variance-covariance matrix of the ambiguity resolution; : the space of the dimensional integers, The number of double-difference ambiguities; ② State space model building defining state vectors The method comprises the steps of position, speed, attitude quaternion, accelerometer zero bias and gyroscope zero bias; ③ EKF time update prediction using last time state and MEMS angular velocity And acceleration Performing mechanical arrangement: wherein: time of day State predictors of (2); nonlinear state transfer function; time of day State estimation values of (2); time of day Control inputs (MEMS angular velocity versus specific force); time of day Is a prediction state error covariance matrix; State transfer function At the position of A jacobian matrix at; time of day State error covariance matrix of (2); process noise covariance matrix; ④ EKF measurement update, obtaining high-precision relative position increment after GNSS double-difference ambiguity is fixed As an observed quantity: The measurement equation is: Wherein the method comprises the steps of To measure noise, the kalman gain is then calculated and the state estimate is updated: wherein: time of day I.e. the calculated relative position of GNSSRTK; An observation matrix, mapping the state vector to an observation space; observing noise and obeying zero-mean Gaussian distribution; the Kalman gain matrix determines the weight of the observed quantity to the state update; Observing a noise covariance matrix; time of day Is a state optimal estimate of (1); time of day Is updated with the state error covariance matrix; Identity matrix; finally outputting the optimal three-dimensional displacement sequence of the side slope And instantaneous speed 。
13. The high-precision GNSS slope displacement monitoring system according to claim 9, wherein in step e, the early warning trigger employs joint judgment logic comprising: when the monitoring point is displaced And synthesis rate Simultaneously satisfies: wherein: time of day The combined displacement of the two is combined with the horizontal displacement and the vertical displacement; time of day Three-dimensional displacement components in the northeast coordinate system; Weight coefficient of the displacement of elevation direction; time of day Is used for the synthetic displacement rate; a displacement threshold value and a velocity threshold value of yellow early warning; the triggering conditions of orange and red early warning are similar, but the threshold value is higher, and the early warning information is automatically pushed to a preset responsible person list through a platform interface, a short message and a mail.
14. The high-precision GNSS slope displacement monitoring system according to claim 9, wherein in step f, the state extrapolation by means of the time update procedure of EKF specifically includes: wherein: when GNSS is out of lock, the predicted value is directly adopted As a final state estimate; The mode utilizes the high-precision relative displacement measurement capability of the MEMS in a short time to maintain continuous position output, simultaneously, the system records MEMS data in a GNSS interruption period, and performs data backtracking and correction through a forward smoothing algorithm after the signals are recovered, so that error accumulation is reduced to the maximum extent.
15. The high-precision GNSS slope displacement monitoring system applicable to loess collapsibility as set forth in claim 9, wherein in step g, the multiplexing rate of the system is Evaluation was carried out by the following formula: wherein: The equipment multiplexing rate is expressed as a percentage; The times of successful disassembly and repeated utilization of the equipment; The number of times the device is deployed.

Description

High-precision GNSS slope displacement monitoring system and method suitable for loess collapsibility characteristics Technical Field The invention relates to the technical field of slope safety monitoring, in particular to a high-precision GNSS slope displacement monitoring system and method suitable for loess collapsibility. Background Engineering construction is carried out in loess areas, such as large-scale equipment transportation of wind power generation projects, and the heavy vehicle load is extremely easy to induce the collapse and slippage of loess slopes. The traditional slope monitoring method mainly adopts total stations or simple GNSS points, and has the defects that monitoring points are usually buried independently, data distortion is easily caused by settlement or disturbance of the monitoring points in loess with poor structure, accurate capture of long-term static creep and instantaneous dynamic response cannot be achieved, data acquisition frequency is fixed, high-frequency capture is difficult to achieve in a critical event such as vehicle passing period, and early warning response is lagged. Disclosure of Invention The invention aims to overcome the defects, and provides a high-precision GNSS slope displacement monitoring system and method which are stable in structure, data fusion and intelligent response and are suitable for loess collapse characteristics, so as to solve the problems in the background technology. In order to solve the technical problems, the technical scheme adopted by the invention is that the high-precision GNSS slope displacement monitoring system suitable for loess collapsibility characteristics comprises: The GNSS monitoring module comprises at least one monitoring point and a datum point, wherein the monitoring point is welded and fixed on an existing field protection steel pipe through an L-shaped mounting base; The data acquisition and transmission module is integrated in the waterproof box and comprises a data acquisition instrument, an MEMS sensor, a communication module and a power supply system which are electrically connected with the monitoring point; and the cloud platform early warning center is used for receiving the data transmitted by the communication module and carrying out data fusion calculation and hierarchical early warning. Preferably, the burial depth of the protective steel pipe is not less than 1.5 meters. Preferably, an intelligent wake-up algorithm is built in the data acquisition instrument, and the monitoring frequency is supported to be adjusted in a self-adaptive mode according to a vehicle passing event. Preferably, the power supply system comprises a 60AH high-capacity lithium battery and an external solar charging plate, and forms a commercial power and solar complementary two-way power supply system. Preferably, the cloud platform early warning center has a function of fusion and calculation of GNSS and MEMS data, and is provided with yellow, orange and red early warning thresholds. Preferably, the datum point comprises a base station pile which is arranged on a stable foundation and comprises a steel plate base, a welded fixed steel pipe, a triangular steel reinforced structure and a threaded steel connecting piece, and the GNSS base station is installed on the top. Preferably, the monitoring point comprises a sub-millimeter GNSS receiver connected to an L-shaped mounting base by threaded bolts. Preferably, the protection level of the data acquisition and transmission module is IP65. The invention also discloses a monitoring method of the high-precision GNSS slope displacement monitoring system suitable for loess collapsible characteristics, which comprises the following steps: step a, respectively arranging monitoring points and datum points in key positions and stable areas of the loess slope; B, installing a waterproof box at a monitoring point, integrating a data acquisition instrument, an MEMS sensor, a communication module and a lithium battery in the box, installing an antenna of a GNSS receiver on an L-shaped base, and connecting the antenna with the data acquisition instrument through an Ethernet interface; Step c, after the system is started, the data acquisition instrument automatically manages the working mode according to a built-in intelligent scheduling algorithm based on double-threshold hysteresis comparison; Step d, the acquired GNSS original observation data and MEMS original data are uploaded to a cloud platform in real time through a 4G module, and the platform carries out high-precision displacement calculation by adopting a tight coupling fusion algorithm based on extended Kalman filtering; step e, the cloud platform presets three-level early warning thresholds, namely yellow early warning, orange early warning and red early warning according to engineering safety criteria, and early warning triggering adopts joint judgment logic; Step f, when the GNSS signal is blocked or out of lock, the system is seam