CN-121702357-B - Three-dimensional topographic mapping method based on unmanned aerial vehicle

CN121702357BCN 121702357 BCN121702357 BCN 121702357BCN-121702357-B

Abstract

The invention discloses a three-dimensional topographic mapping method based on unmanned aerial vehicle, which relates to the unmanned aerial vehicle mapping field, the method uniformly divides a dam body into regular dam face monitoring units on the basis of performing multi-period unmanned aerial vehicle three-dimensional topographic mapping on a tailing dam, and simultaneously extracting dam face response parameters on the scale of each monitoring unit, and calculating and outputting an initial risk index R after normalization processing, so that the comprehensive deviation degree of each monitoring unit in three dimensions of deformation, seepage and microstructure is quantitatively represented on the fine space scale of 2m multiplied by 2 m. Compared with the traditional mode of carrying out safety evaluation by only depending on a small amount of monitoring sections or single deformation indexes, the method provided by the invention has the advantages that through multi-parameter fusion and product type risk index construction, early symptoms such as local deformation acceleration, seepage abnormality, micro-topography disturbance and the like can be enhanced and reflected on the initial risk index R, and the sensitivity and the accuracy of identifying hidden dangers of the tailing dam are improved.

Inventors

ZHANG XINWEI
ZOU BING
GAO XIAOWANG
LIU TIANXIANG
RAO XIANMING
Ji Jiansan
GUO CHAO
ZHU PENG
YANG SHIPING

Assignees

成都威尔奇空间信息技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260210

Claims (8)

1. A three-dimensional topographic mapping method based on an unmanned aerial vehicle is characterized by comprising the following steps: S1, performing multi-period three-dimensional topographic mapping on a tailing dam by an unmanned aerial vehicle according to a preset route, obtaining a multi-period three-dimensional topographic model under a unified coordinate system, dividing the tailing dam into regular grids, and defining each regular grid as a monitoring unit; S2, extracting dam face response parameters of each monitoring unit in different mapping periods, and calculating an initial risk index R of dam face multidimensional response based on the dam face response parameters; S3, performing time comparison and space comparison on the initial risk index R of the monitoring unit to obtain a candidate risk monitoring unit set Hx, dividing the tailing dam into a plurality of engineering dam segments Br along the axial direction of the dam, counting the candidate risk monitoring unit set Hx in each engineering dam segment Br to obtain a dam segment comprehensive risk index R Br , comparing the dam segment comprehensive risk index R with a preset trigger threshold Rth, and determining the engineering dam segment Br where the self-adaptive monitoring zone is located; The S3 comprises S31; s31, performing time comparison and space comparison on an initial risk index R of the monitoring unit to obtain a candidate risk monitoring unit set Hx; The time comparison is carried out by forming a time sequence for an initial risk index R j (tk) of a jth monitoring unit corresponding to a multi-period mapping period at each monitoring unit, calculating a difference value delta R j (tk) of two adjacent periods of initial risk indexes R, and marking the monitoring unit as a time risk monitoring unit when the difference value delta R j (tk) of the two adjacent periods of initial risk indexes R is larger than a preset time change threshold delta Rs and positive values continuously appear in a preset period number; The space comparison is carried out by carrying out space statistics on an initial risk index R j (tk) of a jth monitoring unit of monitoring units in the same dam segment in the same mapping period, and calculating a local average value and a local standard deviation, wherein a monitoring unit, of the monitoring units in the same dam segment, of which the initial risk index R j (tk) of the jth monitoring unit in the tk mapping period is larger than a space threshold value formed by weighted combination of the local average value and the local standard deviation is marked as a space high-value monitoring unit; The monitoring units meeting the time risk marks and the space high-value marks at the same time are analyzed and aggregated through space connectivity to obtain a high-value zone which is continuously distributed along the dam surface, and all the monitoring units in the high-value zone form a candidate risk monitoring unit set Hx; The step S3 further comprises the step S32; S32, extracting a dam crest center line of the tailing dam from a dam body reference coordinate system, sequentially setting a plurality of boundary points on the dam crest center line according to engineering design pile numbers, and defining a space region corresponding to the dam crest center line between any two adjacent boundary points as an engineering dam segment Br; Selecting all monitoring units with centers of gravity falling in the projection range from the dam body reference coordinate system of each engineering dam segment Br in the direction of the dam axis to the direction perpendicular to the slope to form a monitoring unit set contained in the engineering dam segment Br, screening monitoring units belonging to the current engineering dam segment Br from the candidate risk monitoring unit set Hx in each engineering dam segment Br, extracting an initial risk index R j (tk) of a jth monitoring unit in a tk mapping period, sequencing the initial risk indexes R j (tk) of the jth monitoring units in the tk mapping period from small to large according to the value, and taking the initial risk index R j (tk) of the jth monitoring unit in the upper four-position after sequencing as a comprehensive risk index R Br (tk) of the engineering dam segment Br in the tk mapping period; s4, executing an adaptive monitoring zone generation strategy on the candidate risk monitoring unit set Hx, adjusting the retest time based on the comprehensive risk index RBr, obtaining retest intervals T, and executing three-dimensional topographic mapping in the non-adaptive monitoring zone area according to the reference route scheme and the retest reference intervals.
2. The three-dimensional topographic survey method based on an unmanned aerial vehicle of claim 1, wherein S1 comprises S11; S11, performing multi-period three-dimensional topographic mapping on the tailing dam according to a preset route by using an unmanned aerial vehicle carrying an optical camera and an inertial measurement unit; The preset route comprises an upper-layer dam body integral control route covering the whole tailing dam area and a lower-layer dam slope detail route distributed along a dam slope, and a forward-looking oblique photographing route and a backward-looking oblique photographing route are arranged near a tailing dam water-facing slope and a stacking shoreline; In each mapping task, controlling the unmanned aerial vehicle to fly along a preset route in sequence, and acquiring three-dimensional terrain data through a mapping module carried by the unmanned aerial vehicle; the mapping module comprises an optical camera, an inertial measurement unit and a flight control log; the three-dimensional terrain data includes image data, acceleration data and log data, And transmitting the three-dimensional terrain to a cloud mapping server through a wireless network, performing aerial triangulation and beam adjustment on the three-dimensional terrain data in the cloud mapping server, and uniformly resolving the three-dimensional terrain data obtained by mapping in each period into the same dam body reference coordinate system to form a multi-period three-dimensional terrain model under a uniform coordinate system.
3. The three-dimensional topographic mapping method based on the unmanned aerial vehicle according to claim 2, wherein S1 further comprises S12; And S12, uniformly projecting a tailing dam water-facing slope, a dam top and a downstream slope in a multi-stage three-dimensional terrain model under a uniform coordinate system to a dam body reference coordinate system plane, dividing the dam axis direction and the slope direction into regular grids, defining the units of each regular grid as dam surface monitoring units, setting the ground resolution and the three-dimensional resolution precision of the unmanned aerial vehicle to be 2m multiplied by 2m by the regular grids, enabling each dam surface monitoring unit to have complete point cloud and image coverage in each stage of three-dimensional terrain model, and extracting the three-dimensional coordinates of the corresponding dam surface monitoring unit and image data associated with the current dam surface monitoring unit in each three-dimensional terrain model.
4. The three-dimensional topographic mapping method based on a unmanned aerial vehicle of claim 3, wherein S2 comprises S21; s21, extracting dam face response parameters in different mapping periods based on a three-dimensional terrain model in each monitoring unit; The dam face response parameters comprise a vertical deformation rate parameter V j (tk) of a jth monitoring unit in a tk mapping period, a deformation increment trend parameter A j (tk) of the jth monitoring unit in the tk mapping period, a seepage vision indication parameter Q j (tk) of the jth monitoring unit in the tk mapping period and a micro-topography disturbance parameter M j (tk) of the jth monitoring unit in the tk mapping period; and normalizing the dam face response parameters by using a maximum value and minimum value normalization method, and eliminating the unit dimension of all parameters in the dam face response parameters.
5. The three-dimensional topographic survey method based on an unmanned aerial vehicle of claim 4, wherein S2 further comprises S22; s22, substituting the dam face response parameters after normalization processing into a dam face multidimensional response initial risk index formula, calculating and outputting an initial risk index R, and quantitatively analyzing the comprehensive deviation degree of the dam body in three dimensions of deformation, seepage and microstructure; the initial risk index R is calculated and output through the following dam face multidimensional response initial risk index formula; ; where R j (tk) represents the initial risk index of the jth monitoring unit at the tk mapping period.
6. The three-dimensional topographic survey method based on the unmanned aerial vehicle of claim 1, wherein S3 further comprises S33; S33, based on distribution of comprehensive risk indexes R Br of engineering dam segments Br in a plurality of historical mapping periods of the tailing dam under normal operation conditions, counting sample sets of comprehensive risk indexes R Br (tk) of each engineering dam segment Br in a tk mapping period, calculating products of historical maximum values of the sample sets and safety margin coefficients, and determining a trigger threshold Rth; Comparing a comprehensive risk index R Br (tk) of the engineering dam segment Br acquired in real time in a tk mapping period with a trigger threshold Rth, judging the comprehensive risk condition of the current engineering dam segment Br, and triggering a self-adaptive monitoring zone generation request based on a comparison result, wherein the specific comparison contents are as follows: When the comprehensive risk index R Br (tk) of the engineering dam segment Br in the tk mapping period is more than or equal to the trigger threshold Rth, the whole risk of the current engineering dam segment Br is abnormal, triggering a self-adaptive monitoring zone generation request aiming at the engineering dam segment Br, determining the engineering dam segment Br as a dam segment where the self-adaptive monitoring zone is located, and expanding adjacent monitoring units in the current engineering dam segment Br along the dam axis direction and the slope vertical direction by taking the monitoring units in the candidate risk monitoring unit set Hx as the center in the current engineering dam segment Br to form a self-adaptive monitoring zone region Hd; When the comprehensive risk index R Br (tk) of the engineering dam segment Br in the tk mapping period is not less than the trigger threshold Rth, the whole risk of the current engineering dam segment Br is normal, and no operation is generated.
7. The three-dimensional topographic survey method based on an unmanned aerial vehicle of claim 6, wherein S4 comprises S41; S41, after triggering a self-adaptive monitoring zone generation request aiming at an engineering dam segment Br, forming a self-adaptive monitoring zone area Hd for the engineering dam segment Br, and executing a self-adaptive monitoring generation strategy, wherein the self-adaptive monitoring zone generation strategy comprises a bandwidth and position generation strategy, a monitoring in-zone acquisition point encryption strategy and a monitoring out-of-zone area sparsification strategy; The bandwidth and position generation strategy is used for generating an engineering dam segment Br of a request by determining a self-adaptive monitoring band, wherein monitoring units in a candidate risk monitoring unit set Hx in the engineering dam segment Br are used as centers, and at least 3 adjacent monitoring units and at least 5 adjacent monitoring units are respectively expanded to the upstream and downstream in the dam axis direction in a dam body reference coordinate system; Expanding the self-adaptive monitoring zone from the dam crest to the dam foot in a dam body reference coordinate system along the dam slope direction, so that the self-adaptive monitoring zone at least covers a height range accounting for 60% -100% of the dam height from the dam crest in the dam slope direction, and ensures that the upper area of the water-facing slope and the toe area are both contained in the self-adaptive monitoring zone area Hd, and adjusting the coverage height range to 80% -100% of the dam height for reaching the designed water line dam section, thereby determining the space position and the bandwidth of the self-adaptive monitoring zone area Hd; The in-monitoring-zone acquisition point encryption strategy is characterized in that in a self-adaptive monitoring zone region Hd, the line distance of an unmanned aerial vehicle is adjusted from a reference line distance D0 to 0.5D0-0.8D0, and at least one layer of any one of lines with different flying heights and different inclination angles is added on the basis of the original flying heights; the out-of-monitoring band region sparsification strategy maintains a reference pattern scheme or adjusts pattern spacing from a reference pattern spacing D0 to 1.1D0-1.4D0 within an engineering dam segment that is not determined to be the dam segment in which the adaptive monitoring band is located.
8. The three-dimensional topographic survey method based on the unmanned aerial vehicle of claim 7, wherein S4 further comprises S42; S42, calculating and outputting a retest interval T according to an original retest period Tjz and a comprehensive risk index R Br (tk) of the engineering dam segment Br in a tk mapping period aiming at the engineering dam segment Br in the self-adaptive monitoring zone region Hd, introducing the retest interval T into a mission degree layer of the unmanned plane, and retesting the current engineering dam segment Br according to the retest interval T; The retest interval T is calculated and output through the following algorithm formula; ; wherein T Br (tk+1) represents the retest interval of engineering dam segment Br in the next tk+1 mapping period, g represents the period compression coefficient, and the value range is (0, 1).

Description

Three-dimensional topographic mapping method based on unmanned aerial vehicle Technical Field The invention relates to the technical field of unmanned aerial vehicle mapping, in particular to a three-dimensional topographic mapping method based on an unmanned aerial vehicle. Background With the expansion of mining scale and the increase of the number of tailing ponds, high-precision three-dimensional topographic mapping is carried out on the surfaces of the tailing dam bodies, traditional manual leveling and total station measurement are gradually carried out, an unmanned plane carrying an optical camera and an inertial measurement unit is adopted to carry out aerial photogrammetry tasks, and a high-precision multi-period three-dimensional topographic model of the tailing dam areas is established through aerial triangulation and beam adjustment technology. Under the specific application scene, how to utilize the unmanned aerial vehicle three-dimensional topography mapping method to carry out high space-time resolution monitoring to the deformation characteristics of tailing dam body surface to provide reliable data support for the safe operation of tailing dam, become the specific problem that engineering world and mapping technical field are concerned. The method is generally adopted at the present stage, namely, a relatively fixed unmanned aerial vehicle route and a fixed mapping period are designed for the whole tailing dam, the dam body is subjected to full-coverage three-dimensional topographic mapping, and then deformation conditions are analyzed through a small number of characteristic sections or discrete monitoring points. On one hand, the method has the defects that the route design and mapping period are fixed in advance, the coupling with the historical deformation evolution process of the dam body is weak, the spatial density and time frequency of mapping cannot be adaptively adjusted according to the accelerating trend of the local deformation of the dam body, on the other hand, the traditional method takes 'uniform coverage' as a core target, even if the whole tailing dam is stable, only in the area with concentrated deformation occurs in a few engineering dam sections, the system still needs to repeatedly map the whole dam range according to the uniform density, so that the excessive collection and data redundancy of the stable area are caused, and the repeated measurement frequency and the three-dimensional resolving redundancy are difficult to timely improve for the dam sections which are in the actual accelerating deformation state, and the resource allocation is rough and lacks pertinence. Under the current situation, once the whole tailing dam is in a general stable state, and the deformation vector field and the deformation acceleration of the local engineering dam section are obviously increased, because the traditional method only relies on the whole dam mapping of a fixed route and a fixed period, the key stage of the evolution of the local dam section from slow deformation to accelerated deformation is difficult to capture in time, and the situation that risk identification lags and even the stability of the whole dam body is misjudged easily occurs. When the deformation of a local dam segment rapidly develops between two fixed mapping periods, the monitoring system may still perform tasks according to the conventional period, so that three-dimensional topographic data support with enough time sequence density is lacked in the dangerous development stage, thereby being unfavorable for finding out instability symptoms such as abnormal sinking, swelling, sliding and the like of the dam body in advance, meanwhile, as mapping resources are uniformly distributed in the whole dam range, a stable area occupies a large amount of tracks and processing capacity for a long time, a truly high-risk area is difficult to obtain enough encrypted tracks and a shortened retest period, and the local instability risk of the tailing dam is possibly amplified into an overall potential safety hazard, thereby bringing serious adverse consequences to the downstream environment and personnel safety. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a three-dimensional topographic mapping method based on an unmanned aerial vehicle, which solves the problems in the background art. In order to achieve the purpose, the invention is realized by the following technical scheme that the three-dimensional topographic mapping method based on the unmanned aerial vehicle comprises the following steps: S1, performing multi-period three-dimensional topographic mapping on a tailing dam by an unmanned aerial vehicle according to a preset route, obtaining a multi-period three-dimensional topographic model under a unified coordinate system, dividing the tailing dam into regular grids, and defining each regular grid as a monitoring unit; S2, extracting dam face response parameters of each