Anti-collision method for tower crane

Abstract

The invention relates to the field of tower cranes, and provides a tower crane anti-collision method in order to avoid collision of tower cranes, which comprises the following steps: step 1, acquiring coordinate and size information of a load lifting hook; step 2, acquiring boundary coordinate information of a hoisted object; step 3, constructing a BIM model including an environment, a tower crane and a hoisted object; 4, predicting position information of the hoisted object and the front end of the suspension arm at the moment t; and 5, judging whether collision occurs or not based on the environment BIM model, the hoisted object and the position information of the front end of the tower crane at the moment t, and if yes, prompting a driver to carry out adjustment. The BIM model is established, collision judgment is completed by predicting the position information of the hoisted object and the front end of the suspension arm at the moment t, if the judgment result is that collision can occur, a driver is prompted to perform adjustment in time, collision is avoided, and the safety is higher.

Description

Technical Field

[0001] The invention relates to the field of tower cranes, in particular to a tower crane anti-collision method. Background Art

[0002] Tower crane, also known as tower crane, is an indispensable and important equipment in modern construction. The characteristics of tower crane are its large working range and lifting height. The boom is installed on the top of the tower body to form a T-shaped working space with a high utilization range, generally up to 80% of the full range. At the same time, it has a variety of working speeds, stable movement, safety and reliability, which greatly improves the construction efficiency. This makes the tower crane play an irreplaceable role in the construction of high-rise buildings and large buildings. As the main equipment for high-altitude operations, the operation status of the tower crane is directly related to the progress of the project and the life safety of the operator. How to effectively avoid the collision of tower cranes has become an urgent problem to be solved. Summary of the invention

[0003] In order to avoid collision of tower cranes, the present application provides a tower crane anti-collision method.

[0004] The technical solution adopted by the present invention to solve the above problems is:

[0005] A tower crane anti-collision method, comprising:

[0006] Step 1: Obtain the coordinates and size information of the load hook;

[0007] Step 2: Obtain boundary coordinate information of the hoisted object;

[0008] Step 3: Build a BIM model including the environment, tower crane and hoisted objects;

[0009] Step 4, predicting the position information of the hoisted object and the front end of the boom at time t;

[0010] Step 5: Based on the environmental BIM model, the hoisted object and the position information of the front end of the tower crane at time t, determine whether a collision will occur. If so, prompt the driver to make adjustments.

[0011] Furthermore, step 1 uses a UWB positioning method to obtain coordinate information.

[0012] Furthermore, step 2 is specifically as follows:

[0013] Step 21, collecting an image including both the hoisted object and the load hook;

[0014] Step 22: using edge detection algorithm to extract the contours of the hoisted object and the load hook respectively;

[0015] Step 23: establishing a conversion relationship between the actual size and the pixel size based on the size information of the load hook and the contour information of the load hook;

[0016] Step 24: Obtain boundary coordinate information of the hoisted object based on the contour of the hoisted object and the conversion relationship between the actual size and the pixel size.

[0017] Furthermore, step 21 collects images through cameras installed at the front end of the boom and close to the cab end.

[0018] Furthermore, the edge detection algorithm adopts the Canny algorithm.

[0019] Furthermore, step 4 specifically includes:

[0020] Step 41, obtaining the coordinate data of the hoisted object at present and one second ago;

[0021] Step 42, calculating the speed and acceleration in each direction according to the two coordinate data;

[0022] Step 43, calculating the position of the hoisted object at time t;

[0023] Step 44: Calculate the position of the front end of the boom according to the position of the hoisted object.

[0024] Furthermore, step 5 also includes: reminding the operators within a first preset distance directly below the hoisted object and within a second preset distance from the landing point of the hoisted object.

[0025] Furthermore, the first preset distance is 3m, and the second preset distance is 2m.

[0026] Furthermore, the position information of the operator is obtained through a positioning unit installed on the safety helmet.

[0027] Furthermore, a reminder unit is also provided on the safety helmet.

[0028] Compared with the prior art, the present invention has the following beneficial effects: a BIM model is established, and collision judgment is completed by predicting the position information of the hoisted object and the front end of the boom at time t. If the judgment result is that a collision will occur, the driver is prompted to make adjustments in time to avoid the collision, thereby improving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The figure is a flow chart of the tower crane anti-collision method. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0031] like Figure 1As shown, a tower crane anti-collision method comprises:

[0032] Step 1: Obtain the coordinates and size information of the load hook. The coordinates are obtained using UWB positioning technology, and other positioning technologies can also be used, without limitation; the size information is provided by the manufacturer or measured on site.

[0033] Step 2, obtain the boundary coordinate information of the hoisted object. Manually measuring the boundary information of the hoisted object is cumbersome and time-consuming. Therefore, the present application adopts a detection algorithm to obtain the boundary coordinate information of the hoisted object. Specifically including: collecting an image that contains both the hoisted object and the load hook; using an edge detection algorithm to extract the contours of the hoisted object and the load hook respectively; establishing a conversion relationship between the actual size and the pixel size based on the size information of the load hook and the contour information of the load hook; obtaining the boundary coordinate information of the hoisted object based on the contour of the hoisted object and the conversion relationship between the actual size and the pixel size.

[0034] In order to obtain images containing hoisted objects and load hooks, cameras are installed at the front end of the boom and near the cab in this embodiment. The cameras can rotate in the vertical plane to collect images. The images collected by the two cameras at different angles are jointly analyzed to obtain the object contour analysis results. The edge detection algorithm adopts the Canny algorithm, which mainly includes the following steps:

[0035] (1) Preprocessing: The images captured by two cameras at different angles are stitched together according to the existing stitching method, and the images are smoothed using a Gaussian filter to remove noise.

[0036] (2) Calculate the gradient: Use the Sobel operator, Prewitt operator, or Roberts operator to calculate the gradient of the image and obtain the first-order derivatives in the horizontal and vertical directions.

[0037] (3) Non-maximum suppression: In the gradient direction, each pixel is compared with the pixels in its neighborhood, the local maximum is retained, and the pseudo-responses are removed.

[0038] (4) Double threshold segmentation: Use two thresholds (high threshold and low threshold) for edge detection. Edges above the high threshold are considered strong edges, edges below the low threshold are considered weak edges, and edges between the two need to be further checked to see if they are connected to strong edges.

[0039] (5) Hysteresis threshold: tracks strong edges, suppresses weak edges and discontinuous edges, and ensures that the edges are continuous curves.

[0040] Step 3: Build a BIM model that includes the environment, tower crane and hoisted objects. The environment includes objects that exist in the actual working environment of the tower crane, such as engineering entities and formwork frames.

[0041] Step 4: predicting the position information of the hoisted object and the front end of the boom at time t, including:

[0042] Get the coordinate data of the hoisted object at present and one second ago, which are (x0, y0, z0) and (x′, y′, z′) respectively;

[0043] Calculate the speed and acceleration in each direction based on the two coordinate data: v x =x′-x0,v y =y′-y0,v z = z′-z0,a x =v x -v x ′,a y =v y -v y ′,a z =v z -v z ′,v x 、v y 、v z are the velocities in the x, y, and z directions at a certain moment, v x ′、v y ′、v z ′ is the speed in the x, y, and z directions one second before a certain moment, a x ,y x 、z x is the acceleration in the x, y, and z directions at a certain moment;

[0044] Calculate the position of the hoisted object at time t:

[0045] The position of the front end of the boom is calculated according to the position of the hoisted object. There is a geometric relationship between the hoisted object and the boom. The position of the front end of the boom can be obtained based on the geometric relationship. The specific calculation process will not be described here.

[0046] Step 5: Based on the environmental BIM model, the position information of the hoisted object and the front end of the tower crane at time t, determine whether a collision will occur. If so, prompt the driver to make adjustments, and remind the operators within the first preset distance (such as 3m) directly below the hoisted object and the second preset distance (such as 2m) from the landing point of the hoisted object. The preset distance can be set according to actual needs. The position information of the operator is obtained through the positioning unit installed on the safety helmet, and the safety helmet is also provided with a reminder unit, such as a sound reminder and / or an alarm light reminder.

Claims

1. A tower crane anti-collision method, characterized in that: include: Step 1: Obtain the coordinates and size information of the load hook; Step 2: Obtain boundary coordinate information of the hoisted object; Step 3: Build a BIM model including the environment, tower crane and hoisted objects; Step 4, predicting the position information of the hoisted object and the front end of the boom at time t; Step 5: Based on the environmental BIM model, the hoisted object and the position information of the front end of the tower crane at time t, determine whether a collision will occur. If so, prompt the driver to make adjustments.

2. A tower crane anti-collision method according to claim 1, characterized in that: Step 1: Use UWB positioning method to obtain coordinate information.

3. A tower crane anti-collision method according to claim 1, characterized in that: Step 2 is as follows: Step 21, collecting an image including both the hoisted object and the load hook; Step 22: using edge detection algorithm to extract the contours of the hoisted object and the load hook respectively; Step 23: establishing a conversion relationship between the actual size and the pixel size based on the size information of the load hook and the contour information of the load hook; Step 24: Obtain boundary coordinate information of the hoisted object based on the contour of the hoisted object and the conversion relationship between the actual size and the pixel size.

4. A tower crane anti-collision method according to claim 3, characterized in that: Step 21 collects images through cameras installed at the front end of the boom and near the cab end.

5. A tower crane anti-collision method according to claim 3, characterized in that: The edge detection algorithm uses the Canny algorithm.

6. A tower crane anti-collision method according to claim 1, characterized in that: Step 4 specifically includes: Step 41, obtaining the coordinate data of the hoisted object at present and one second ago; Step 42, calculating the speed and acceleration in each direction according to the two coordinate data; Step 43, calculating the position of the hoisted object at time t; Step 44: Calculate the position of the front end of the boom according to the position of the hoisted object.

7. A tower crane anti-collision method according to any one of claims 1 to 6, characterized in that: Step 5 also includes: reminding the operators within a first preset distance directly below the hoisted object and within a second preset distance from the landing point of the hoisted object.

8. A tower crane anti-collision method according to claim 7, characterized in that: The first preset distance is 3m, and the second preset distance is 2m.

9. A tower crane anti-collision method according to claim 7, characterized in that: The worker's position information is obtained through a positioning unit installed on the helmet.

10. A tower crane anti-collision method according to claim 9, characterized in that: The safety helmet is also provided with a reminder unit.

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