CN-122017773-A - Debris flow detection method and related device

CN122017773ACN 122017773 ACN122017773 ACN 122017773ACN-122017773-A

Abstract

The application discloses a debris flow detection method and a related device, wherein the debris flow detection method comprises the steps of acquiring a plurality of cloud frames to be detected at a place to be detected by utilizing Lei Dayi order to form a cloud sequence to be detected, extracting actual motion pattern characteristics of plant clusters of the place to be detected from the cloud sequence to be detected, wherein one plant cluster comprises at least one plant, and determining whether debris flow events occur at the place to be detected based on the actual motion pattern characteristics of the plant clusters. According to the scheme, whether the debris flow event occurs can be determined through the actual motion mode of the plant clusters of the to-be-detected place.

Inventors

LI DONGDONG
LI QIANKUN
ZHANG KAI
GAO YUSHUANG
YIN JUN

Assignees

浙江大华技术股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260105

Claims (12)

1. A debris flow detection method, comprising: Collecting a plurality of cloud frames of the to-be-detected points by Lei Dayi sequences to form a cloud sequence of the to-be-detected points; extracting actual movement pattern characteristics of a plant cluster of the to-be-detected place from the cloud sequence of to-be-detected points, wherein one plant cluster comprises at least one plant; and determining whether a debris flow event occurs in the to-be-detected place based on the actual movement pattern characteristics of the plant clusters.
2. The method according to claim 1, wherein the extracting actual movement pattern features of the plant clusters of the locus to be detected from the cloud sequence of points to be detected comprises: respectively acquiring sub-motion mode characteristics of the plant clusters between every two adjacent cloud frames at the to-be-detected point; and counting all the sub-movement pattern features of the plant cluster to obtain the actual movement pattern features of the plant cluster.
3. The method according to claim 2, wherein the sub-motion pattern features include sub-motion amplitude features and sub-motion direction features, and the respectively acquiring sub-motion pattern features of the plant cluster between every two adjacent cloud frames to be detected includes: respectively acquiring three-dimensional areas of the plant clusters in each cloud frame to be detected, wherein the three-dimensional areas of the plant clusters represent the outline of three-dimensional points belonging to the plant clusters in the cloud frame to be detected; for each two adjacent cloud frames to be detected, acquiring the overlapping degree of the three-dimensional areas of the plant clusters in the two adjacent cloud frames to be detected as the sub-motion amplitude characteristic, and Acquiring sub-motion direction features of three-dimensional areas of the plant clusters in two adjacent cloud frames to be detected, wherein the sub-motion direction features are first motion direction features when a previous distance is larger than a next distance, the sub-motion direction features are second motion direction features when the previous distance is smaller than the next distance, the first motion direction features and the second motion direction features represent opposite motion directions, the previous distance is a distance from the three-dimensional areas of the plant clusters in the cloud frame to be detected to the radar, and the next distance is a distance from the three-dimensional areas of the plant clusters in the cloud frame to be detected to the radar.
4. The method according to claim 2, wherein the actual movement pattern features include movement pattern concentration trend features and movement pattern discrete degree features, and the counting of the sub-movement pattern features of the plant cluster to obtain the actual movement pattern features of the plant cluster includes: And respectively carrying out concentrated trend statistics and discrete degree statistics on each sub-motion mode characteristic of the plant cluster, and correspondingly obtaining the concentrated trend characteristic and the discrete degree characteristic of the motion mode.
5. The method of claim 1, wherein the determining whether the debris flow event occurs at the location to be detected based on the actual movement pattern characteristics of the plant cluster comprises: acquiring the actual wind speed of the plant cluster in the acquisition time period of the cloud sequence of the to-be-detected point; Acquiring an actual association relation between the actual wind speed of the plant cluster and the actual movement pattern feature, and acquiring a reference association relation between the reference wind speed of the plant cluster and the reference movement pattern feature, wherein the reference wind speed and the reference movement pattern feature are obtained under the condition that the debris flow event does not occur; And determining whether the debris flow event occurs in the to-be-detected place based on the degree of difference between the actual association relationship and the reference association relationship.
6. The method of claim 5, wherein the determining whether the debris flow event occurs at the location to be detected based on the degree of difference between the actual association and the reference association comprises: calculating an F estimated value by taking the same actual association relationship and the same reference association relationship as the original assumption of F test; inquiring an F theoretical value in an F distribution table by utilizing the rejection threshold value of the original hypothesis, the molecular degree of freedom and the denominator degree of freedom of the F estimated value; Determining that the debris flow event occurs in the to-be-detected place in response to the F estimated value being larger than the F theoretical value; And determining that the debris flow event does not occur in the to-be-detected place in response to the F estimated value being not greater than the F theoretical value.
7. The method of claim 1, wherein prior to the determining whether the debris flow event occurs at the location to be detected based on the actual movement pattern characteristics of the plant clusters, comprising: acquiring an attitude angle of the radar in an acquisition time period of the cloud sequence of the to-be-detected point; Combining the attitude angle of the radar with the actual motion pattern feature of the plant cluster to update the actual motion pattern feature of the plant cluster.
8. The method according to claim 1, wherein the method further comprises: Collecting a current detection point Yun Zhen to be detected; Judging whether the current cloud frame of the detection point meets the surface extraction condition or not, wherein the surface extraction condition comprises at least one of the surface of the place to be detected, the current three-dimensional area which can be extracted from the current cloud frame of the detection point to the surface of the earth, and the area of the current three-dimensional area of the surface of the earth being larger than an area threshold; Determining whether the debris flow event occurs according to the current three-dimensional area of the earth surface in response to the earth surface extraction condition being met; and responding to the condition that the ground surface extraction condition is not met, forming the cloud sequence of the to-be-detected point by utilizing the current cloud frame of the to-be-detected point and the adjacent preset number of cloud frames of the historical to-be-detected point, and executing the steps of extracting the actual motion mode characteristics of the plant clusters of the to-be-detected place from the cloud sequence of the to-be-detected point and the following steps.
9. The method of claim 1, wherein the locus to be detected comprises a plurality of the plant clusters, and determining whether a debris flow event occurs at the locus to be detected based on actual movement pattern characteristics of the plant clusters comprises: For each plant cluster, determining whether the debris flow event occurs based on the actual motion pattern characteristics of the plant cluster, and obtaining an event determination result corresponding to the plant cluster; and finally determining that the debris flow event occurs in the to-be-detected place under the condition that the event determination result corresponding to the plant clusters with the preset proportion is that the debris flow event occurs.
10. An electronic device comprising a memory and a processor for executing program instructions stored in the memory to implement the method of any one of claims 1-9.
11. A computer readable storage medium, characterized in that it has stored thereon program instructions, which when executed by a processor, implement the method of any of claims 1-9.
12. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the method of any of claims 1-9.

Description

Debris flow detection method and related device Technical Field The application relates to the technical field of point cloud data processing, in particular to a debris flow detection method and a related device. Background Debris flow refers to a special flood carrying a large amount of solid substances such as muddy sand, stones and boulders, which is generated on gully or hillside due to (sudden huge amount of) precipitation, and belongs to a disastrous geological phenomenon. Currently, there is a need for a debris flow detection method to detect debris flow events to respond in time in the event of a debris flow event. Disclosure of Invention The application provides a debris flow detection method and a related device, which can detect whether a debris flow event occurs. The application provides a debris flow detection method, which comprises the steps of acquiring a plurality of cloud frames to be detected at a place to be detected by Lei Dayi sequences to form a cloud sequence to be detected, extracting actual motion pattern characteristics of plant clusters of the place to be detected from the cloud sequence to be detected, wherein one plant cluster comprises at least one plant, and determining whether a debris flow event occurs at the place to be detected based on the actual motion pattern characteristics of the plant clusters. The application provides a debris flow detection device which comprises an acquisition module, an extraction module and a determination module. The system comprises an acquisition module, an extraction module and a determination module, wherein the acquisition module is used for acquiring a plurality of cloud frames of a to-be-detected point by utilizing Lei Dayi sequences to form a cloud sequence of the to-be-detected point, the extraction module is used for extracting actual motion pattern characteristics of a plant cluster of the to-be-detected point from the cloud sequence of the to-be-detected point, one plant cluster comprises at least one plant, and the determination module is used for determining whether a debris flow event occurs in the to-be-detected point based on the actual motion pattern characteristics of the plant cluster. The application provides an electronic device comprising a memory and a processor for executing program instructions stored in the memory to implement the above method. The present application provides a computer readable storage medium having stored thereon program instructions which, when executed by a processor, implement the above-described method. The present application provides a computer program product comprising a computer program which, when executed by a processor, implements the above method. According to the scheme, on one hand, the cloud sequence of the to-be-detected points acquired by the radar at the to-be-detected places is utilized to determine whether debris flow events occur at the to-be-detected places in real time. Compared with the image acquisition equipment, the radar is not influenced by environmental illumination change and weather change, so that the radar can be used for realizing all-weather all-day real-time debris flow detection, and the installation requirement is low. On the other hand, the actual motion pattern characteristics of the plant clusters of the to-be-detected places are extracted from the cloud sequences of the to-be-detected points, and whether debris flow events occur in the to-be-detected places is determined based on the actual motion pattern characteristics of the plant clusters. The actual movement pattern features characterize the actual movement pattern of the plant clusters, so that it is possible to determine whether a debris flow event occurs through the actual movement pattern of the plant clusters at the location to be detected. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed. Drawings The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. FIG. 1 is a schematic flow chart of a first embodiment of a debris flow detection method according to the present application; FIG. 2 is a schematic diagram of a cloud frame to be detected according to the present application; FIG. 3 is a schematic flow chart of a second embodiment of the debris flow detection method according to the present application; fig. 4 is a schematic flow chart of a third embodiment of a debris flow detection method according to the present application; FIG. 5 is a schematic flow chart of a fourth embodiment of a debris flow detection method according to the present application; FIG. 6 is a schematic flow chart of a debris flow detection method according to a fifth embodiment of the present appli