TWI810688B - Intelligent displacement monitoring system and method thereof - Google Patents

Abstract

An intelligent displacement monitoring system is disclosed. The intelligent displacement monitoring system includes at least one Lidar scanner, a point cloud construction engine, a displacement analysis engine and an output device. The Lidar scanner is adapted to scan a monitored surface and output a first scanning data at a first timing and output a second scanning data at a second timing. The point cloud construction engine is adapted to output a first point cloud data according to the first scanning data, and output a second point cloud data according to the second scanning data. The displacement analysis engine is adapted to analyze the first point cloud data and the second point cloud data, thereby outputting a displacement data. The output device is adapted to receive the displacement data and display the displacement data in visual. An intelligent displacement monitoring method is further disclosed.

Description

Intelligent displacement monitoring system and method

The present invention provides a monitoring system and method, especially an intelligent displacement monitoring system and method established by a LiDAR scanner.

During the construction of artificial facilities, the half-built structure must be monitored to prevent destructive displacement. In addition, facilities installed in high-risk areas also need to be regularly monitored after construction to prevent them from being damaged by natural phenomena such as earthquakes or wind disasters. Critical surfaces can be measured regularly with LiDAR scanners, however, if destructive displacements occur during the gaps between measurements and cause further disasters, it is often irreparable.

The inventor then exhausted his mind to study carefully, and then developed an intelligent displacement monitoring system and method, in order to achieve the purpose of real-time monitoring and early warning.

A first aspect of the present invention provides an intelligent displacement monitoring system, which includes at least one LiDAR scanner, a point cloud construction engine, a displacement analysis engine, and an output device. The lidar scanner is suitable for scanning a monitored surface, and outputs a first scan data at a first time, and outputs a second scan data at a second time. The point cloud construction engine is coupled to the lidar scanner and is adapted to output a first point cloud data and a second point cloud data according to the first scan data and the second scan data. The displacement analysis engine is coupled to the point cloud construction engine, and is suitable for analyzing the first point cloud data and the second point cloud data to output a displacement data. The output device is coupled to the displacement analysis engine and is suitable for receiving the displacement data and displaying the displacement data in a visual manner.

The second aspect of the present invention provides an intelligent displacement monitoring method, which includes the following steps: providing at least one LiDAR scanner, and using the LiDAR scanner to scan a monitored surface to output a The first scan data, and output a second scan data at a second time; provide a point cloud construction engine, the point cloud construction engine is based on the first scan data and the second scan data output a first point cloud data and the second scan data A second point cloud data; providing a displacement analysis engine, the displacement analysis engine analyzes the first point cloud data and the second point cloud data to output a displacement data; and provides an output device, The output device receives the displacement data and displays the displacement data in a visual manner.

In one embodiment, the point cloud construction engine performs a noise filtering process on the first scan data and the second scan data to output the first point cloud data and the second point cloud data.

In one embodiment, the noise filtering process is to analyze the first point cloud data and the second point cloud by using a multiscale model to model cloud comparison (M3C2) algorithm. data.

In one embodiment, the displacement analysis engine compares the displacement data with a displacement threshold, and outputs a displacement alarm to the output device when the displacement data exceeds the displacement threshold.

In one embodiment, the visualization method includes displaying the displacement status of the monitored surface through the distribution of colors.

In one embodiment, the output device is a mobile communication device or a display.

In one embodiment, the monitored surface is a surface of an artificial structure.

In this way, the intelligent displacement monitoring system and method of the present invention can maintain monitoring of the monitored surface, so as to issue an early warning when destructive displacement occurs.

1: Intelligent displacement monitoring system

10:Lidar Scanner

11: Point cloud construction engine

12: Displacement analysis engine

13: Output device

13A: Display

13B: Mobile communication device

4: Data storage and real-time calculation server

5: retaining wall

50: surface

6: Building foundation

8: Buildings

80: Exterior wall

D/2: Radius

d/2: radius

G1: The first point cloud group

G2: The second point cloud group

i: core point

i ₁ : point

i ₂ : point

L: distance

:平面法線方向

: plane normal direction

R1: Green area

R2: Yellow area

R3: red zone

S ₁ : the first fitting plane

S ₂ : the second fitting plane

S101: step

S102: step

S103: step

S104: step

FIG. 1 is a schematic block diagram of an intelligent displacement monitoring system according to a specific embodiment of the present invention.

Fig. 2 is a schematic flowchart of a smart displacement monitoring method according to a specific embodiment of the present invention.

Fig. 3 is a schematic diagram of the application of the intelligent displacement monitoring system of the specific embodiment of the present invention in monitoring landslides.

Fig. 4 is a schematic diagram of the application of the intelligent displacement monitoring system of the specific embodiment of the present invention in monitoring buildings.

FIG. 5A is a first schematic diagram of noise filtering performed by the point cloud construction engine applied in the present invention.

FIG. 5B is a second schematic diagram of noise filtering applied to the point cloud construction engine of the present invention.

FIG. 6 is a schematic diagram of displaying visual displacement data by an output device of an intelligent displacement monitoring system according to a specific embodiment of the present invention.

In order to fully understand the purpose, features and effects of the present invention, the present invention will be described in detail through the following specific embodiments and accompanying drawings, as follows:

As shown in FIG. 1 , the first aspect of the present invention is to provide an intelligent displacement monitoring system 1 . The intelligent displacement monitoring system 1 includes at least one LiDAR scanner 10 , a point cloud construction engine 11 , a displacement analysis engine 12 and an output device 13 . The LiDAR scanner 10 is adapted to scan a surface to be monitored, and output a first scan data at a first time, and output a second scan data at a second time. The point cloud construction engine 11 is coupled to the LiDAR scanner 10 and is adapted to output a first point cloud data and a second point cloud data according to the first scan data and the second scan data. The displacement analysis engine 12 is coupled to the The point cloud construction engine 11 is suitable for analyzing the first point cloud data and the second point cloud data to output a displacement data. The output device 13 is coupled to the displacement analysis engine 12 and is suitable for receiving the displacement data so as to display the displacement data in a visual manner.

As shown in Figure 1 and Figure 2, the second aspect of the present invention is to provide an intelligent displacement monitoring method, which includes the following steps:

S101: Provide at least one LiDAR scanner (such as the LiDAR scanner 10 shown in FIG. 1), and use the LiDAR scanner to scan a monitored surface to output a first scan data at a first time, and Outputting a second scan data at a second time.

S102: Provide a point cloud construction engine (such as the point cloud construction engine 11 shown in FIG. point cloud data.

S103: Provide a displacement analysis engine (such as the displacement analysis engine 12 shown in FIG. 1 ), the displacement analysis engine analyzes the first point cloud data and the second point cloud data to output a displacement data.

S104: Provide an output device (such as the output device 13 shown in FIG. 1 ), the output device receives the displacement data, and displays the displacement data in a visual manner.

As mentioned above, the intelligent displacement monitoring system 1 and method of the present invention can maintain monitoring of the monitored surface, so as to issue an early warning when destructive displacement occurs.

As shown in Figure 1, in one embodiment, the displacement analysis engine 12 compares the displacement data with a displacement threshold, and when the displacement data exceeds the displacement threshold, the output device 13 Outputting a displacement alarm, such as a warning window and/or an alarm sound.

As shown in FIGS. 1 and 3 , in one embodiment, the monitored surface may be a surface of an artificial structure, such as a surface 50 of a retaining wall 5 used to prevent landslides. In this embodiment, multiple LiDAR scanners 10 are used to scan the surface 50 at different angles. The point cloud construction engine 11 and the displacement analysis engine 12 can be integrated in a data storage and real-time calculation server 4 , such as software or application programs installed in the data storage and real-time calculation server 4 . The data storage and real-time calculation server 4 can be set in a machine room (not shown) near the landslide, and connected to the LiDAR scanners 10 by wires. The data storage and real-time calculation server 4 can also be set at the remote end, and the computer room near the landslide can only be provided with computers (not shown) used to connect the lidar scanners 10, and then connect the lidar scanners 10 through the network. 10 The scanned data is transmitted to the data storage and real-time calculation server 4 for analysis. The LiDAR scanners 10 scan the slope once an hour, once a day or other frequencies to obtain scanning data. The output device 13 can be a display 13A electrically connected to the data storage and real-time calculation server 4, or a mobile communication device 13B connected to the data storage and real-time calculation server 4 through the Internet. When there are multiple monitors, in addition to the display 13A, the data storage and real-time calculation server 4 can also transmit the displacement data and related images to the mobile communication devices 13B of multiple monitors through the Internet. In addition, the point cloud construction engine 11 and the displacement analysis engine 12 can also be stored in a non-transitory multimedia storage device (not shown), such as an optical disc or a portable hard disk, for execution.

As shown in Figures 1 and 4, in one embodiment, the monitored surface monitored by the intelligent displacement monitoring system 1 of the present invention may also be the outer wall surface 80 of the building 8 adjacent to the building foundation 6 and the building foundation 6 By monitoring the displacement of the outer wall surface 80 and the wall surface of the building foundation 6, it is known whether the excavation of the building foundation 6 has caused damage to the nearby buildings 8.

As shown in FIG. 1, the LiDAR scanner 10 can emit laser wavelengths between about 850 nm to 950 nm (preferably about 905 nm), and has dustproof and waterproof characteristics, and the wavelength of this range thunder Shooting does not cause damage to the human eye. The scanning angle of the LiDAR scanner 10 may be about 70 degrees in the horizontal direction, and about 77 degrees in the vertical direction. The lidar scanner 10 can scan about 720,000 points of point cloud data per second, and is suitable for a distance greater than about 3 meters from the surface to be monitored.

As shown in Figures 1 and 6, in one embodiment, the visualization mode output by the output device 13 includes displaying the displacement status of the monitored surface through the distribution of colors, so that the monitor can quickly view the displacement of the monitored surface from the distribution of colors. Understand the degree of displacement and the displacement area, such as the visual displacement data received by the mobile communication device 13B shown in FIG. The yellow region R2 and the red region R3 represented by solid circles represent different displacement amounts, respectively.

。如圖5B所示，接著在平面法線方向

上定義半徑為d/2的一圓柱範圍，並計算核心點i所投影到第一擬合平面S₁與第二擬合平面S₂的複數組點雲距離，包括從第一擬合平面S₁往第二擬合平面S₂的投影距離以及從第二擬合平面S₂往第一擬合平面S₁的投影距離，兩投 影距離的平均值可為圖5B所示的點i₁與點i₂之間的距離L，而藉由兩投影距離的兩倍標準差可計算出點雲粗糙度(cloud roughness)，從而將雜訊濾除。 As shown in FIG. 1 and FIG. 5A to FIG. 5B, in one embodiment, the point cloud construction engine 11 performs a noise filtering process on the first scan data and the second scan data to output the first point cloud data and the second point cloud data. Preferably, the noise filtering program analyzes the first point cloud data and the second point cloud data by using a Multiscale Model to Model Cloud Comparison (M3C2) algorithm. As shown in FIG. 5A, the first point cloud data and the second point cloud data captured at the first time and the second time respectively can be represented as a first point cloud group G1 and a point cloud group G1 in the point cloud construction engine 11. The second point cloud group G2. The first point cloud group G1 and the second point cloud group G2 respectively include a first fitting plane S ₁ and a second fitting plane S ₂ . First, take a core point i in the first point cloud group G1, and define a radius of D/2 around the core point i, and find out the direction of the first point cloud group G1 towards the second point cloud group G2 (that is, the normal direction of a plane perpendicular to the first fitting plane S ₁ )

. As shown in Figure 5B, then in the plane normal direction

Define the range of a cylinder with a radius of d/2 above, and calculate the complex group point cloud distance projected from the core point i to the first fitting plane S ₁ and the second fitting plane S ₂ , including from the first fitting plane S The projection distance from ₁ to the second fitting plane _S2 and the projection distance from the second fitting plane _S2 to the first fitting plane _S1 , the average of the two projection distances can be the points i1 and ₁ shown in Figure 5B The distance L between point i ₂ , and the point cloud roughness (cloud roughness) can be calculated by twice the standard deviation of the two projection distances, so as to filter out noise.

As shown in Figures 1 to 4, in summary, in the intelligent displacement monitoring system 1 and method of the present invention, the user can customize the scanning frequency of the LiDAR scanner 10, and use the LiDAR scanner 10 to target flat and The surface of the artificial structure of a single material is scanned, and then monitored and analyzed by the point cloud construction engine 11 and the displacement analysis engine 12. The intelligent displacement monitoring system 1 and method of the present invention can calculate the displacement up to plus or minus 5 kilometers The average error degree of centimeters, especially for the destructive displacement of slow sliding (about two centimeters per day), can achieve the effect of instant detection and early warning.

The present invention has been disclosed above with preferred embodiments, but those skilled in the art should understand that the embodiments are only used to describe the present invention, and should not be construed as limiting the scope of the present invention. It should be noted that all changes and substitutions equivalent to the embodiment should be included in the scope of the present invention. Therefore, the scope of protection of the present invention should be defined by the scope of the patent application.

1: Intelligent displacement monitoring system

10:Lidar Scanner

11: Point cloud construction engine

12: Displacement analysis engine

13: Output device

4: Data storage and real-time calculation server

Claims (10)

An intelligent displacement monitoring system, comprising: at least one LiDAR scanner, which is suitable for scanning a monitored surface, and outputs a first scan data at a first time, and outputs a second scan data at a second time Data; a point cloud construction engine, which is coupled to the LiDAR scanner, and is adapted to output a first point cloud data and a second point cloud data according to the first scan data and the second scan data; a displacement an analysis engine, which is coupled to the point cloud construction engine, and is suitable for analyzing the first point cloud data and the second point cloud data to output a displacement data; and an output device, which is coupled to the The displacement analysis engine is suitable for receiving the displacement data and displaying the displacement data in a visual manner. The intelligent displacement monitoring system as described in claim 1, wherein the point cloud construction engine performs a noise filtering process on the first scan data and the second scan data to output the first point cloud data and the The second point cloud data. The intelligent displacement monitoring system as described in claim 2, wherein the noise filtering program analyzes the first The point cloud data and the second point cloud data. The intelligent displacement monitoring system as described in claim item 1, wherein the displacement analysis engine compares the displacement data with a displacement threshold, and when the displacement data exceeds the displacement threshold, the The output device outputs a displacement alarm. The intelligent displacement monitoring system as described in claim 1, wherein the visualization method includes displaying the displacement status of the monitored surface through the distribution of colors. The intelligent displacement monitoring system according to claim 1, wherein the output device is a mobile communication device or a display. The intelligent displacement monitoring system according to claim 1, wherein the monitored surface is a surface of an artificial structure. A smart displacement monitoring method, comprising the following steps: providing at least one LiDAR scanner, and using the LiDAR scanner to scan a monitored surface to output a first scan data at a first time, and at a first time Output a second scan data at two times; provide a point cloud construction engine, and the point cloud construction engine outputs a first point cloud data and a second point cloud data based on the first scan data and the second scan data; provide a point cloud construction engine. a displacement analysis engine, which analyzes the first point cloud data and the second point cloud data to output a displacement data; and provides an output device, which receives the displacement data, And display the displacement data in a visual way. The intelligent displacement monitoring method as described in claim 8, wherein the point cloud construction engine performs a noise filtering process on the first scan data and the second scan data to output the first point cloud data and the The second point cloud data. The intelligent displacement monitoring method as described in claim item 9, wherein the noise filtering program analyzes the first The point cloud data and the second point cloud data.