A tower crane control system for prefabricated buildings

Abstract

The present invention relates to a tower crane control system for prefabricated buildings. The present invention installs reflective positioning points on prefabricated building modules. The main controller uses a calculation module to compare the position coordinates of the building modules with the coordinates in a model library. The main controller uses the calculation module to calculate the position adjustment amount that the tower crane control module needs to adjust based on the coordinate deviation. The tower crane control module controls the tower crane to drive the prefabricated building modules to move, so that the prefabricated building modules are placed in the correct position. The model library stores the overall 3D model library of the prefabricated building and the series of installation and construction action processes for each prefabricated building module. The series of installation and construction action processes for each prefabricated building module include the position coordinates of each prefabricated building module at different steps. This solves the defect in the prior art that prefabricated buildings must be monitored throughout the entire process, and can achieve unmanned automatic assembly.

Description

Technical Field

[0001] The present invention relates to the field of building construction, and in particular to a tower crane control system for assembled buildings. Background Art

[0002] Prefabricated buildings refer to buildings that transfer a large amount of on-site work in traditional construction methods to factories, where building components and accessories (such as floor slabs, wall panels, stairs, balconies, etc.) are processed and manufactured in the factory, transported to the construction site, and assembled and installed on site through reliable connection methods.

[0003] Application number CN202110081704.6 provides a method for scheduling tower crane hoisting services for prefabricated concrete structures. The method includes calculating the tower crane hoisting time for material request tasks based on the characteristics of the prefabricated concrete hoisting structure; establishing a multi-objective scheduling optimization model for tower crane hoisting service scheduling based on the tower crane hoisting time, with the goal of minimizing the tower crane hoisting completion time and delay penalties; and solving the multi-objective scheduling optimization model using a dynamic search heuristic algorithm to obtain the execution process of the tower crane hoisting service sequence for all material request tasks.

[0004] However, during the assembly process, it is difficult to ensure that the entire process is carried out in full compliance with the standard requirements. Multiple technical workers must be on duty throughout the construction process. On the one hand, the on-duty work requires a large amount of manpower, and on the other hand, the safety risks involved in the on-duty work are very high. Although some existing technologies can be installed remotely, due to the absence of on-site inspection, on the one hand, the assembly accuracy is difficult to guarantee, and on the other hand, the operation is very inconvenient. Summary of the Invention

[0005] In view of the above content, in order to solve the above problems, a tower crane control system for prefabricated buildings is provided, which includes a master controller, a model library, a position measurement module, a tower crane control module and a calculation module;

[0006] The position measurement module is connected to the main controller and is used to detect the position coordinates of the prefabricated building modules and send the detected coordinates of the prefabricated building modules to the main controller;

[0007] The main controller uses the calculation module to compare the position coordinates of the building module with the coordinates in the model library and calculate the coordinate deviation;

[0008] The tower crane control module is connected to the main controller, and the main controller calculates the position adjustment amount that the tower crane control module needs to adjust based on the coordinate deviation using the calculation module; the tower crane control module controls the tower crane to drive the prefabricated building module to move, so that the prefabricated building module is placed in the correct position.

[0009] The position measurement module includes an illumination light source, a shooting camera and a reflective positioning point; the illumination light source emits infrared light of a fixed wavelength and projects it onto the reflective positioning point; the reflective positioning point is installed on the surface of the prefabricated building module, and the reflective positioning point diffusely reflects the received infrared light; the diffusely reflected light is photographed by the shooting camera; the position measurement module calculates the coordinates of the reflective positioning point based on the position of the reflective positioning point photographed by the shooting camera.

[0010] The model library stores the overall 3D model library of prefabricated buildings, as well as the installation and construction action series processes of each prefabricated building module;

[0011] The installation and construction action series of each prefabricated building module includes the position coordinates of each prefabricated building module at different steps;

[0012] The positions of the illumination source and camera in the position measurement module are known, from which the spatial vector of each pixel position in the image captured by the camera can be calculated; that is, each pixel point in the image captured by the camera corresponds to a straight line in the actual spatial coordinates;

[0013] The surface of each prefabricated building module is equipped with multiple reflective positioning points. The position measurement module identifies all reflective positioning points in the image and identifies the positional relationship of the corresponding pixels of each reflective positioning point. By further inputting the actual distance between the reflective positioning points, the actual coordinates of each reflective positioning point can be calculated.

[0014] The specific calculation method of the reflective positioning point is:

[0015] Assume that the distance between two adjacent reflective positioning points P1 and P2 on the prefabricated building module is L1; the pixel positions in the image captured by the camera are M1 and M2; it can be obtained that the two positioning points P1 and P2 must be located on the two rays s1 and s2 starting from the shooting point of the camera;

[0016] The distance between P2 on the prefabricated building module and another reflective positioning point P3 that is not collinear with P1 and P2 is L2; ​​the pixel positions in the image captured by the camera are M2 and M3; it can be concluded that the two positioning points P2 and P3 must be located on the two rays s2 and s3 starting from the shooting point of the camera;

[0017] Since the relative positions of P1, P2, and P3 are fixed, there must be only one set of coordinates of P1, P2, and P3 that meets the following conditions:

[0018] The distance between P1 and P2 is L1;

[0019] The distance between P3 and P2 is L2;

[0020] P1 is located on ray s1;

[0021] P2 is located on ray s2;

[0022] P3 is located on ray s3;

[0023] According to the above conditions, a set of coordinates of P1, P2, and P3 can be obtained by using analytic geometry algorithms.

[0024] The specific structure of the reflective positioning point is flip-type. The reflective positioning point is a rotating sphere. Half of the sphere is coated with reflective material, and the other half is coated with light-absorbing material. The rotation speed of each sphere is different. The shooting camera takes continuous images. The pixels at the position of the reflective positioning point in the continuous image will flash. The position measurement module obtains the position relationship of the corresponding pixels of each reflective positioning point according to the different flashing frequencies of the sphere.

[0025] The reflective positioning points include a sphere, a rotating motor and a rotating shaft.

[0026] The minimum number of reflective positioning points is 3.

[0027] The tower crane control module is equipped with a vibration detector, which detects the vibration of the tower crane arm and sends the detected vibration frequency and direction to the main controller in real time. The main controller extracts the vibration characteristics based on the vibration frequency and direction detected by the vibration detector, and inputs the vibration characteristics into the risk coefficient calculation model in the calculation module; the risk coefficient calculation model calculates the construction risk coefficient based on the vibration characteristics and outputs the risk coefficient to the main controller.

[0028] The vibration detector is an acceleration type vibration detector, including an X-direction vibration detector, a Y-direction vibration detector and a Z-direction vibration detector, and the vibration detector detects the vibration waveform of the tower crane mechanical arm;

[0029] The main controller processes the vibration waveform of each direction vibration detector and extracts the frequency spectrum of the vibration waveform;

[0030] The main controller performs noise reduction on the spectrum and inputs it into the risk coefficient calculation model, which is a deep neural network model;

[0031] The method for establishing the risk coefficient calculation model is to extract the spectrum of the vibration waveform of the tower crane when various faults occur in advance and use it as a training sample. The training sample spectrum is used as input, and the fault type of the training sample is used as output to train the deep neural network model.

[0032] During actual operation, the detected spectrum is input into the risk coefficient calculation model to obtain the fault type. Each fault type corresponds to its own risk coefficient, so that the operation risk coefficient can be obtained.

[0033] The beneficial effects of the present invention are:

[0034] The present invention installs reflective positioning points on prefabricated building modules. A master controller uses a calculation module to compare the position coordinates of the building modules with those in a model library. The master controller then uses the calculation module to calculate the position adjustment amount required by the tower crane control module based on the coordinate deviation. The tower crane control module then controls the tower crane to move the prefabricated building modules, thereby placing the prefabricated building modules in the correct position. The model library stores the overall 3D model library of the prefabricated building, as well as a series of installation and construction process steps for each prefabricated building module. The series of installation and construction process steps for each prefabricated building module includes the position coordinates of each prefabricated building module at different steps. This overcomes the drawback of the prior art that prefabricated buildings must be fully supervised throughout the entire process, enabling unmanned automatic assembly.

[0035] The tower crane control module of the present invention is provided with a vibration detector, which detects the vibration of the tower crane arm and sends the detected vibration frequency and direction to the main controller in real time. The main controller extracts vibration characteristics according to the vibration frequency and direction detected by the vibration detector, and inputs the vibration characteristics into the risk coefficient calculation model in the calculation module; the risk coefficient calculation model calculates the construction risk coefficient according to the vibration characteristics, and outputs the risk coefficient to the main controller.

[0036] The specific structure of the reflective positioning point is flip-type. The reflective positioning point is a rotating sphere. Half of the sphere is coated with reflective material, and the other half is coated with light-absorbing material. The rotation speed of each sphere is different. The shooting camera takes continuous images. The pixels at the position of the reflective positioning point in the continuous image will flash. The position measurement module obtains the position relationship of the corresponding pixels of each reflective positioning point according to the different flashing frequencies of the sphere. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a schematic diagram of the overall architecture of the present invention;

[0038] Figure 2 Schematic diagram of the reflective positioning point structure of the present invention DETAILED DESCRIPTION

[0039] The advantages, features and methods of achieving the above objects of the present invention will become clear from the accompanying drawings and the following detailed description.

[0040] Combine Figure 1 and Figure 2 , a tower crane control system for prefabricated buildings, including a master controller, a model library, a position measurement module, a tower crane control module and a calculation module;

[0041] The position measurement module is connected to the main controller and is used to detect the position coordinates of the prefabricated building modules and send the detected coordinates of the prefabricated building modules to the main controller;

[0042] The main controller uses the calculation module to compare the position coordinates of the building module with the coordinates in the model library and calculate the coordinate deviation;

[0043] The tower crane control module is connected to the main controller, and the main controller calculates the position adjustment amount that the tower crane control module needs to adjust based on the coordinate deviation using the calculation module; the tower crane control module controls the tower crane to drive the prefabricated building module to move, so that the prefabricated building module is placed in the correct position.

[0044] The position measurement module includes an illumination light source, a shooting camera and a reflective positioning point; the illumination light source emits infrared light of a fixed wavelength and projects it onto the reflective positioning point; the reflective positioning point is installed on the surface of the prefabricated building module, and the reflective positioning point diffusely reflects the received infrared light; the diffusely reflected light is photographed by the shooting camera; the position measurement module calculates the coordinates of the reflective positioning point based on the position of the reflective positioning point photographed by the shooting camera.

[0045] The model library stores the overall 3D model library of prefabricated buildings, as well as the installation and construction action series processes of each prefabricated building module;

[0046] The installation and construction action series of each prefabricated building module includes the position coordinates of each prefabricated building module at different steps;

[0047] The positions of the illumination source and camera in the position measurement module are known, from which the spatial vector of each pixel position in the image captured by the camera can be calculated; that is, each pixel point in the image captured by the camera corresponds to a straight line in the actual spatial coordinates;

[0048] The surface of each prefabricated building module is equipped with multiple reflective positioning points. The position measurement module identifies all reflective positioning points in the image and identifies the positional relationship of the corresponding pixels of each reflective positioning point. By further inputting the actual distance between the reflective positioning points, the actual coordinates of each reflective positioning point can be calculated.

[0049] The specific calculation method of the reflective positioning point is:

[0050] Assume that the distance between two adjacent reflective positioning points P1 and P2 on the prefabricated building module is L1; the pixel positions in the image captured by the camera are M1 and M2; it can be obtained that the two positioning points P1 and P2 must be located on the two rays s1 and s2 starting from the shooting point of the camera;

[0051] The distance between P2 on the prefabricated building module and another reflective positioning point P3 that is not collinear with P1 and P2 is L2; ​​the pixel positions in the image captured by the camera are M2 and M3; it can be concluded that the two positioning points P2 and P3 must be located on the two rays s2 and s3 starting from the shooting point of the camera;

[0052] Since the relative positions of P1, P2, and P3 are fixed, there must be only one set of coordinates of P1, P2, and P3 that meets the following conditions:

[0053] The distance between P1 and P2 is L1;

[0054] The distance between P3 and P2 is L2;

[0055] P1 is located on ray s1;

[0056] P2 is located on ray s2;

[0057] P3 is located on ray s3;

[0058] According to the above conditions, a set of coordinates of P1, P2, and P3 can be obtained by using analytic geometry algorithms.

[0059] The specific structure of the reflective positioning point is flip-type. The reflective positioning point is a rotating sphere. Half of the sphere is coated with reflective material, and the other half is coated with light-absorbing material. The rotation speed of each sphere is different. The shooting camera takes continuous images. The pixels at the position of the reflective positioning point in the continuous image will flash. The position measurement module obtains the position relationship of the corresponding pixels of each reflective positioning point according to the different flashing frequencies of the sphere.

[0060] The reflective positioning points include a sphere, a rotating motor and a rotating shaft.

[0061] The minimum number of reflective positioning points is 3.

[0062] The tower crane control module is equipped with a vibration detector, which detects the vibration of the tower crane arm and sends the detected vibration frequency and direction to the main controller in real time. The main controller extracts the vibration characteristics based on the vibration frequency and direction detected by the vibration detector, and inputs the vibration characteristics into the risk coefficient calculation model in the calculation module; the risk coefficient calculation model calculates the construction risk coefficient based on the vibration characteristics and outputs the risk coefficient to the main controller.

[0063] The vibration detector is an acceleration type vibration detector, including an X-direction vibration detector, a Y-direction vibration detector and a Z-direction vibration detector, and the vibration detector detects the vibration waveform of the tower crane mechanical arm;

[0064] The main controller processes the vibration waveform of each direction vibration detector and extracts the frequency spectrum of the vibration waveform;

[0065] The main controller performs noise reduction on the spectrum and inputs it into the risk coefficient calculation model, which is a deep neural network model;

[0066] The method for establishing the risk coefficient calculation model is to extract the spectrum of the vibration waveform of the tower crane when various faults occur in advance and use it as a training sample. The training sample spectrum is used as input, and the fault type of the training sample is used as output to train the deep neural network model.

[0067] During actual operation, the detected spectrum is input into the risk coefficient calculation model to obtain the fault type. Each fault type corresponds to its own risk coefficient, so that the operation risk coefficient can be obtained.

[0068] Example 2:

[0069] This embodiment introduces the specific application of the system;

[0070] When assembling a prefabricated building, first, the 3D model of each assembly module is stored in the model library, and the reflective positioning mark points on the 3D model of each module are marked;

[0071] Then, in the model library, the installation process of each module of the prefabricated building is divided into multiple installation steps, and the coordinates of the reflective positioning mark points on each 3D model in each step are obtained, that is, the standard coordinates of each step are obtained;

[0072] Then, reflective positioning points are installed on the actual surface of the module of the prefabricated building, and the flashing frequency of each positioning point is marked, so that the flashing frequency of each reflective positioning point and the distance between each positioning point can be input into the position measurement module;

[0073] The tower crane hoists the module of the prefabricated building. The position measurement module obtains the position coordinates of the module and compares them with the standard coordinates in the corresponding step to calculate the coordinate deviation. The tower crane is controlled to adjust its position based on the deviation so that the module of the prefabricated building moves to the standard coordinates.

[0074] In each assembly step, the module is repeatedly measured to obtain the position coordinates of the module, and compared with the standard coordinates in the corresponding step to calculate the coordinate deviation. The tower crane is controlled to adjust its position based on the deviation so that the module of the prefabricated building is moved to the standard coordinates; until the assembly of the building is completed.

[0075] During the assembly process, the vibration detector detects the vibration of the tower crane arm and sends the detected vibration frequency and direction to the main controller in real time. The main controller extracts the vibration characteristics based on the vibration frequency and direction detected by the vibration detector, and inputs the vibration characteristics into the risk coefficient calculation model in the calculation module; the risk coefficient calculation model calculates the construction risk coefficient based on the vibration characteristics and outputs the risk coefficient to the main controller. When the risk coefficient is higher than the threshold, an alarm is issued and the machine is shut down immediately.

[0076] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A tower crane control system for prefabricated buildings, comprising a master controller, a model library, a position measurement module, a tower crane control module, and a calculation module; characterized in that: The position measurement module is connected to the main controller and is used to detect the position coordinates of the prefabricated building modules and send the detected coordinates of the prefabricated building modules to the main controller; The main controller uses the calculation module to compare the position coordinates of the building module with the coordinates in the model library and calculate the coordinate deviation; The tower crane control module is connected to the main controller, and the main controller calculates the position adjustment amount that the tower crane control module needs to adjust based on the coordinate deviation using the calculation module; the tower crane control module controls the tower crane to drive the prefabricated building module to move, so that the prefabricated building module is placed in the correct position; The position measurement module includes an illumination source, a camera, and a reflective positioning point. The illumination source emits infrared light of a fixed wavelength, which is projected onto the reflective positioning point. The reflective positioning point is installed on the surface of the prefabricated building module and diffusely reflects the infrared light received. The diffusely reflected light is captured by the camera. The position measurement module calculates the coordinates of the reflective positioning point based on the position of the reflective positioning point captured by the camera. The model library stores the overall 3D model library of prefabricated buildings, as well as the installation and construction action series processes of each prefabricated building module; The installation and construction action series of each prefabricated building module includes the position coordinates of each prefabricated building module at different steps; The positions of the illumination source and camera in the position measurement module are known, so the spatial vector of each pixel in the image captured by the camera can be calculated; that is, each pixel in the image captured by the camera corresponds to a straight line in the actual spatial coordinates; The surface of each prefabricated building module is equipped with multiple reflective positioning points. The position measurement module identifies all the reflective positioning points in the image and identifies the positional relationship of the corresponding pixels of each reflective positioning point. By further entering the actual distance between the reflective positioning points, the actual coordinates of each reflective positioning point can be calculated.

2. The tower crane control system for prefabricated buildings according to claim 1, characterized in that: The tower crane control module is equipped with a vibration detector, which detects the vibration of the tower crane arm and sends the detected vibration frequency and direction to the main controller in real time. The main controller extracts vibration characteristics based on the vibration frequency and direction detected by the vibration detector and inputs the vibration characteristics into the risk coefficient calculation model in the calculation module; The risk coefficient calculation model calculates the construction risk coefficient according to the vibration characteristics and outputs the risk coefficient to the main controller.

3. The tower crane control system for prefabricated buildings according to claim 1, characterized in that: The specific calculation method of the reflective positioning point is: Assume that the distance between two adjacent reflective positioning points P1 and P2 on the prefabricated building module is L1; the pixel positions in the image captured by the camera are M1 and M2; then it can be obtained that the two positioning points P1 and P2 must be located on the two rays s1 and s2 starting from the shooting point of the camera; The distance between P2 on the prefabricated building module and another reflective positioning point P3 that is not collinear with P1 and P2 is L2; ​​the pixel positions in the image captured by the camera are M2 and M3; it can be determined that the two positioning points P2 and P3 must be located on two rays s2 and s3 starting from the shooting point of the camera; Since the relative positions of P1, P2, and P3 are fixed, there must be only one set of coordinates of P1, P2, and P3 that meets the following conditions: The distance between P1 and P2 is L1; The distance between P3 and P2 is L2; P1 is located on ray s1; P2 is located on ray s2; P3 is located on ray s3; According to the above conditions, a set of coordinates of P1, P2, and P3 can be obtained by using analytic geometry algorithms.

4. The tower crane control system for prefabricated buildings according to claim 3, characterized in that: The specific structure of the reflective positioning point is flip-type. The reflective positioning point is a rotating sphere. Half of the sphere is coated with reflective material, and the other half is coated with light-absorbing material. The rotation speed of each sphere is different. The shooting camera takes continuous images. The pixels at the position of the reflective positioning point in the continuous image will flash. The position measurement module obtains the position relationship of the corresponding pixels of each reflective positioning point according to the different flashing frequencies of the sphere.

5. The tower crane control system for prefabricated buildings according to claim 4, characterized in that: The reflective positioning points include a sphere, a rotating motor and a rotating shaft.

6. The tower crane control system for prefabricated buildings according to claim 4, characterized in that: The minimum number of reflective positioning points is 3.

7. The tower crane control system for prefabricated buildings according to claim 2, characterized in that: The vibration detector is an acceleration type vibration detector, including an X-direction vibration detector, a Y-direction vibration detector and a Z-direction vibration detector, and the vibration detector detects the vibration waveform of the tower crane mechanical arm; The main controller processes the vibration waveform of each direction vibration detector and extracts the frequency spectrum of the vibration waveform; The main controller performs noise reduction on the spectrum and inputs it into the risk coefficient calculation model, which is a deep neural network model; The method for establishing the risk coefficient calculation model is to extract the spectrum of the vibration waveform of the tower crane when various faults occur in advance and use it as a training sample. The training sample spectrum is used as input, and the fault type of the training sample is used as output to train the deep neural network model. During actual operation, the detected spectrum is input into the risk coefficient calculation model to obtain the fault type. Each fault type corresponds to its own risk coefficient, so that the operation risk coefficient can be obtained.

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