Real-time twinning method of settlement cloud picture

Abstract

The invention discloses a real-time twinning method for a settlement nephogram, which comprises the following steps of: acquiring coordinates of each settlement point and a real-time settlement value in real time from settlement monitoring equipment; constructing a BIM model of the building in the twinborn scene, adjusting to a settlement cloud picture display mode, and replacing a shader of the BIM model with a settlement cloud picture calculation shader; transmitting the coordinates of each settlement point and the real-time settlement value into a twin engine to obtain a settlement point set, and submitting the settlement point set to a GPU (Graphics Processing Unit); calculating a vertex model space coordinate value of the building BIM model through the vertex shader, and transmitting the vertex model space coordinate value to the fragment shader; and calculating a current pixel settlement value based on a Kriging interpolation algorithm in the fragment shader, and endowing different settlement values with different colors to form a settlement cloud picture. The method has the advantages that the BIM model of the original building structure is reused in the digital twinning scene, the real-time settlement data is directly processed based on the real-time settlement data, and the processed real-time settlement data is processed by the GPU and displayed in the twinning scene in real time.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of real-time twin technology, and in particular to a real-time twin method for a settlement cloud map. BACKGROUND

[0002] As an important means of safety prevention, settlement observation is applied in various fields. The data of each monitoring point in settlement observation is often difficult to intuitively present the current overall settlement situation, and requires professional and experienced engineers to analyze and understand the health status of the structure. The data of each monitoring point from collection to analysis of conclusions often also takes a certain time, resulting in a certain lag in the data value of settlement observation.

[0003] At present, the common settlement observation analysis is to generate a settlement cloud map containing the data of each monitoring point by using related professional software or to obtain settlement data to visual presentation through modeling and a series of complex data processing processes, thereby causing a certain lag from settlement observation data to visualization, which brings major risks in the field of major safety engineering such as dams, and requires additional large amount of time and labor cost. SUMMARY

[0004] The present application aims to provide a real-time twin method for a settlement cloud map, which is used to solve the problem of being unable to present the settlement cloud map in real time.

[0005] To achieve the above-mentioned purpose, the present application adopts the following technical solutions: The real-time twin method for a settlement cloud map according to the present application comprises the following steps: S1. Real-time acquisition of the coordinates of each settlement point and the real-time settlement value from the settlement monitoring equipment; real-time presentation of the settlement situation on the twin scene based on real-time data.

[0006] S2. Construction of a BIM model of the building in the twin scene, adjustment to the settlement cloud map display mode, and replacement of the shader of the BIM model with a settlement cloud map calculation shader; S3. Transmission of the coordinates of each settlement point and the real-time settlement value into the twin engine, obtaining of the settlement point set, and submission to the GPU; matching of each settlement point data with the twin scene, and submission to the image processor for visual processing.

[0007] S4. Calculation of the vertex model space coordinate value of the BIM model of the building by the vertex shader, and transmission to the fragment shader; determination of the coordinates of each actual settlement monitoring point, and acquisition of the settlement situation of each point in the entire region by the difference method.

[0008] S5. Calculation of the current pixel settlement value in the fragment shader based on the Kriging interpolation algorithm, assignment of different colors to different settlement values, and formation of a settlement cloud map.

[0009] Further, in S3, after each settlement point coordinate and real-time settlement value is transmitted into the twin engine, each settlement point coordinate is converted to the twin scene coordinate, the twin scene area corresponding to the settlement point coordinate set is calculated, the four corner points of the twin scene area are set as new settlement points, the settlement value is set to 0, and the settlement point set is composed of each settlement point coordinate and real-time settlement value converted to the twin scene.

[0010] The advantage of the present application is that by directly reusing the BIM model of the original building in the digital twin scene, relying on real-time settlement data, directly processing real-time settlement data in the digital twin engine, and presenting the processed real-time settlement data to the twin scene through GPU processing, the real-time visualization of the settlement cloud map is realized, continuous dynamic settlement monitoring results can be presented, and faster and more efficient decision-making basis is provided for simulation, and the whole settlement cloud map presentation process does not require manual participation and the process is simple. BRIEF DESCRIPTION OF DRAWINGS

[0011] Figure 1 The flowchart of the method of the present application is shown.

[0012] Figure 2 The effect diagram of the method of the present application is shown. DETAILED DESCRIPTION

[0013] The technical solutions in the embodiments of the present application will be described clearly and completely below. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0014] As shown in Figure 1 The real-time twin method of the settlement cloud map of the present application includes the following steps: S1, real-time acquisition of each settlement point coordinate and real-time settlement value from the settlement monitoring device. The monitoring results of the settlement monitoring device can be stored in the database in real time, and the current each settlement point coordinate and real-time settlement value can be acquired in real time through the interface, thereby providing a data basis for real-time presentation of the settlement cloud map in the twin scene.

[0015] S2, construction of the BIM model of the building in the twin scene, adjustment to the settlement cloud map display mode, and replacement of the shader of the BIM model with the settlement cloud map calculation shader. If the BIM model of the existing building is available, no repeated modeling is needed, and the BIM model of the building can be directly reused in the twin scene.

[0016] S3, transmission of each settlement point coordinate and real-time settlement value into the twin engine, obtaining of the settlement point set, and submission to the GPU.

[0017] Specifically, after the coordinates of each settlement point and the real-time settlement value are input into the twin engine, the coordinates of each settlement point need to be first converted to the twin scene coordinates to obtain the coordinates of each settlement point and the real-time settlement value in the twin scene. Then, the twin scene area corresponding to the coordinate set of each settlement point in the twin scene is calculated. The twin scene area is generally square, and four corner points of the twin scene area are determined. The four corner points are The twin scene area corresponding to the coordinate set of each settlement point is calculated, the four corner points of the twin scene area are set as new settlement points, the settlement value is set to 0, and the coordinates of each settlement point converted to the twin scene and the real-time settlement value form a settlement point set. The settlement point set is submitted to the GPU (graphics processor). The data structure submitted to the GPU (graphics processor) includes the number of effective settlement observation points, the coordinate value and the settlement value of the settlement point, and the parameters for Kriging interpolation calculation.

[0018] S4, in the image processor, the vertex model space coordinate value of the building BIM model is calculated by the vertex shader and passed to the fragment shader.

[0019] S5, in the fragment shader, the current pixel settlement value is calculated based on the Kriging interpolation algorithm, different colors are assigned to different settlement values, a settlement cloud chart is formed, and the settlement result is more intuitively presented. In each fragment, the GPU automatically performs linear interpolation on the settlement value, and different color values are assigned to different parts of the model for different settlement values, so that the settlement situation is intuitively displayed, as shown in Figure 2 .

[0020] The present application directly reuses the original building BIM model in the digital twin scene, relies on real-time settlement data, directly processes the real-time settlement data in the digital twin engine, processes the processed real-time settlement data through the GPU, and presents the real-time visualization of the settlement cloud chart in the twin scene, realizes the continuous and dynamic settlement monitoring result presentation, provides faster and more efficient decision-making basis for simulation, and the whole settlement cloud chart presentation process does not need human participation and the process is simple.

[0021] The continuous and dynamic visualization of the settlement cloud chart in the present application helps engineers and decision-makers better understand the health status of the structure, discover potential problems in time, and take preventive measures, thereby ensuring the safety and stability of buildings and infrastructure.

Claims

1. A real-time twinning method for sedimentation cloud images, characterized in that: The following steps are involved: S1, obtain the coordinates of each settlement point and the real-time settlement value from the settlement monitoring equipment in real time; S2: Build a BIM model of the building in the twin scene, adjust it to the settlement cloud display mode, and use the settlement cloud calculation shader to replace the BIM model shader; S3: The coordinates of each settlement point and the real-time settlement value are passed to the Twin Engine, and the settlement point set is obtained and submitted to the GPU; S4, calculate the vertex model space coordinate values ​​of the building BIM model through the vertex shader and pass them to the fragment shader; S5, in the fragment shader, calculates the current pixel sedimentation value based on the Kriging interpolation algorithm, assigns different sedimentation values ​​to different colors, and forms a sedimentation cloud map.

2. The real-time twinning method of the subsidence cloud map according to claim 1 is characterized by: In step S3, after the coordinates of each settlement point and the real-time settlement value are passed into the twin engine, the coordinates of each settlement point are converted to the twin scene coordinates, and the twin scene area corresponding to the settlement point coordinate set is calculated. The four corner points of the twin scene area are used as new settlement points, and the settlement value is set to 0. Together with the settlement point coordinates and real-time settlement values ​​converted to the twin scene, they form a settlement point set.

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