Part warehousing size detection system and method based on three-dimensional scanning

Abstract

The invention relates to the technical field of part detection, in particular to a part warehousing size detection system and method based on three-dimensional scanning, and the system comprises a scanning control module which obtains the feedback data of a correlation area in real time, and generates a scanning control signal according to the feedback data; the camera shooting module adjusts the scanning state of the to-be-scanned part according to the scanning control signal, and obtains a point cloud data set based on a triangulation method; the data processing module generates a three-dimensional point cloud model based on the point cloud data set, performs size calculation based on the three-dimensional point cloud model to obtain shape and position size parameters, and is further used for generating a detection result corresponding to the to-be-scanned part according to the shape and position size parameters and preset parameters; and the part classification mechanism performs classification operation on the to-be-scanned parts according to the detection result. The camera shooting module is prevented from being in a continuous scanning state, so that the service life of the camera shooting module can be prolonged.

Description

Technical Field

[0001] The present application relates to the technical field of parts detection, and in particular to a system and method for detecting the dimensions of parts entering the warehouse based on three-dimensional scanning. Background Art

[0002] Quality control is crucial in the complex and critical process of automotive parts production and supply. Current quality inspection methods for parts produced by suppliers have significant limitations. The commonly used sampling inspection method only scans and reports on key components. This inability to fully cover all parts allows a large number of potentially substandard products to enter subsequent processes. In automotive manufacturing, the dimensional accuracy and shape accuracy of components are directly related to the performance and safety of the entire vehicle. Once components with substandard dimensions or incorrect shapes enter the dimensional matching process, they can cause serious problems. Firstly, the dimensional matching process is extremely time-consuming and labor-intensive, requiring constant adjustments to accommodate substandard parts. Secondly, the qualified rate of assembled vehicles is significantly reduced, which in turn reduces vehicle safety and can even lead to serious quality incidents, resulting in immeasurable economic losses for automotive manufacturers. At present, in response to the problem of low wheel hub detection efficiency in the existing technology, a wheel hub size automatic detection device is disclosed, which includes a base plate and a support plate. The support plate is fixed to one side of the top surface of the base plate. A robotic arm is fixedly installed on one side of the support plate. A three-dimensional scanner is installed on the movable end of the robotic arm. A driving motor is fixedly installed on the top surface of the base plate. A turntable is fixed on the output end of the driving motor. A plurality of mounting slots are evenly arranged on the top surface of the turntable. Through the arrangement of the driving motor and the turntable, in combination with the three-dimensional scanner and the robotic arm, the size of multiple wheel hubs can be detected in sequence and uninterruptedly.

[0003] However, although the use of a 3D camera to inspect the wheel hub mechanism can achieve object detection through the rotating mechanism, the camera is constantly scanning in the inspection gap between the two north-side hubs. This causes the camera to be in a high-load working stage at all times, resulting in a reduced service life and increased costs. At the same time, a large amount of meaningless point cloud data will be obtained, which increases the workload of subsequent point cloud processing. Summary of the Invention

[0004] In order to increase the service life of the camera, obtain higher-precision point cloud data, and reduce the workload of subsequent point cloud processing, the present application provides a parts warehousing size detection system and method based on three-dimensional scanning.

[0005] In the first aspect, the present application provides a system for detecting the dimensions of parts entering the warehouse based on three-dimensional scanning, which adopts the following technical solutions: A 3D scanning-based parts storage dimension detection system, comprising: A scanning control module, the scanning control module is used to obtain feedback data of the shooting area in real time and generate a scanning control signal according to the feedback data; a camera shooting module, the camera shooting module being connected to the scanning control module through a network to receive the scanning control signal, and adjusting a scanning state of the part to be scanned according to the scanning control signal, and acquiring a point cloud data set based on a triangulation method, the point cloud data set including point cloud data corresponding to different angles of the part to be scanned; a data processing module, the data processing module being connected to the camera shooting module through a network to receive the point cloud data set, generating a three-dimensional point cloud model based on the point cloud data set, and performing size calculations based on the three-dimensional point cloud model to obtain shape and position dimensional parameters, the data processing module being further configured to generate a detection result corresponding to the part to be scanned based on the shape and position dimensional parameters and preset parameters; A parts classification mechanism is connected to the data processing module to receive the detection result and perform a classification operation on the parts to be scanned according to the detection result.

[0006] By adopting the above technical solution, the scanning control module obtains feedback data from the parts to be scanned that enter the shooting area, and generates a scanning control signal based on the feedback data, so that the camera shooting module adjusts the scanning state of the parts to be scanned according to the scanning control signal. The camera shooting module is only started when there are parts to be scanned in the shooting area, thereby avoiding the camera shooting module from being in a state of continuous scanning, thereby improving the service life of the camera shooting module. Only by scanning the parts to be scanned, higher-precision point cloud data can be obtained, reducing the workload of the data processing module in processing point cloud data, and improving the efficiency of size detection of the parts to be scanned.

[0007] In some embodiments, the scanning control signal includes a scanning trigger signal and a scanning stop signal corresponding to the scanning trigger signal, and the feedback data includes a first feedback and a second feedback. The scanning control module includes a first scanning unit and a second scanning unit. The first scanning unit is used to obtain a first feedback of a first shooting area in real time and determine whether the first feedback is blocked. If blocked, the first scanning unit generates the scanning trigger signal and sends the scanning trigger signal to the camera shooting module to control the camera shooting module to scan the part to be scanned. The second scanning unit is used to obtain the second feedback of the corresponding second shooting area in real time, and determine whether the second feedback is blocked. If so, the second scanning unit generates the scanning stop signal and sends the scanning stop signal to the camera shooting module to control the camera shooting module to stop scanning the part to be scanned.

[0008] By adopting the above technical solution, the first scanning unit performs real-time scanning on the first shooting area and the second scanning unit performs real-time scanning on the second shooting area to obtain corresponding feedback data, and by judging whether there is a blockage between the first feedback and the second feedback, if there is a blockage between the first feedback, the first scanning unit generates a scanning trigger signal to control the camera shooting module to scan the part to be scanned; if there is a blockage between the second feedback, the second scanning unit generates a scanning stop signal to control the camera shooting module to stop scanning the part to be scanned, and the feedback data obtained in real time by the first scanning unit and the second scanning unit can be used to determine the scanning start time and the scanning end time of the part to be scanned. When a complete point cloud data set is obtained, the startup or shutdown of the camera shooting module can be adjusted to improve the service life of the camera and obtain point cloud data with higher precision.

[0009] In some embodiments, the scanning control module further includes a signal conversion unit, which is configured to receive the first feedback signal or the second feedback signal and generate a corresponding scanning control signal based on the first feedback signal or the second feedback signal.

[0010] By adopting the above-mentioned technical solution, based on the signal conversion unit, the received first feedback signal or the second feedback signal is converted into a corresponding scanning control signal, so that the camera shooting module can be controlled to start scanning or stop scanning the part to be scanned, which is convenient for adjusting the working state of the camera shooting module, and then the scanning operation can be confirmed according to the current position of the part to be scanned, thereby improving the scanning accuracy of the camera shooting module and increasing the service life of the camera shooting module.

[0011] In some embodiments, the camera shooting module includes a first orientation camera, a second orientation camera, and a third orientation camera, and starts the first orientation camera, the second orientation camera, and the third orientation camera to scan the part to be scanned based on the scanning trigger signal, and turns off the first orientation camera, the second orientation camera, and the third orientation camera to stop scanning the part to be scanned based on the scanning stop signal.

[0012] By adopting the above technical solution, a multi-directional camera is set up to scan the part to be scanned, and then point cloud data of multiple surfaces of the part to be scanned is collected from multiple directions and in all directions, thereby avoiding single data collection, and being able to perform comprehensive inspection of the part to be scanned, thereby improving the efficiency of dimensional inspection of the part to be scanned.

[0013] In some of the embodiments, the data processing module includes a model generation unit, a parameter calculation unit, and a detection and judgment unit; The model generation unit obtains point cloud data corresponding to different angles based on the point cloud data set, and aligns the point cloud data at different angles in three-dimensional space based on a point cloud registration algorithm to obtain a three-dimensional point cloud model; The parameter calculation unit obtains linear dimensions and key points based on the three-dimensional point cloud module, calculates the linear dimensions based on the Euclidean distance formula, and calculates the deviation of the key points based on the least squares method to obtain shape and position dimension parameters; The detection and judgment unit generates a detection result corresponding to the part to be scanned based on the shape, position and size parameters and preset parameters.

[0014] By adopting the above technical solution, the point cloud data set is processed based on the data processing module, and the obtained data is compared with the original value to generate the detection results of the parts to be scanned, thereby reducing manual operations and improving the efficiency of dimensional detection of the parts to be scanned.

[0015] In some embodiments, the data processing module also includes a signal generating unit, which is used to receive the detection result sent by the detection and judgment unit, and determine whether the detection result is qualified; if so, a qualified signal is generated, and based on the qualified signal, the parts classification mechanism is controlled to start according to the first preset mode; if not, an unqualified signal is generated, and based on the unqualified signal, the parts classification mechanism is controlled to start according to the second preset mode.

[0016] By adopting the above technical solution, the parts classification mechanism is automatically classified according to the detection results, which can reduce manual operations, realize automatic detection of the parts to be scanned, and improve the efficiency of size detection of the parts to be scanned.

[0017] In a second aspect, the present application provides a method for detecting the dimensions of parts entering the warehouse based on three-dimensional scanning, which adopts the following technical solutions: A method for detecting the dimensions of incoming parts based on three-dimensional scanning is applied to a device for detecting the dimensions of incoming parts based on three-dimensional scanning. The device includes a conveyor belt for transporting parts to be scanned, and includes the following steps: Acquire feedback data of the beam area in real time, and generate a scanning control signal based on the feedback data; Adjusting the scanning state of the part to be scanned according to the scanning control signal, and acquiring a point cloud data set based on a triangulation method, wherein the point cloud data set includes point cloud data corresponding to different angles of the part to be scanned; Generating a three-dimensional point cloud model based on the point cloud data set, and performing size calculation based on the three-dimensional point cloud model to obtain shape and position size parameters; Generate a detection result corresponding to the part to be scanned based on the shape, position and size parameters and preset parameters, and perform a classification operation on the part to be scanned based on the detection result.

[0018] In some embodiments, before generating a three-dimensional point cloud model based on the point cloud data set, the following steps are further included: Obtaining the part type and running position of the part to be scanned, and obtaining corresponding feature point cloud data from a preset database based on the part type; Matching the feature point cloud data in the point cloud data set and determining whether corresponding data can be matched; If the corresponding data cannot be matched, a stop signal is generated, and the conveyor belt is controlled to stop based on the stop signal; The part to be scanned is rescanned based on the operating position to obtain updated point cloud data corresponding to the operating position, and the updated point cloud data replaces the point cloud data corresponding to the operating position.

[0019] By adopting the above technical solution, during the operation of the part to be scanned, it is necessary to detect in real time whether the point cloud data set taken at the corresponding operating position is complete. If it is incomplete, it is timely re-scanned at the operating position to obtain updated point cloud data, and the updated point cloud data replaces the point cloud data taken at the previous operating position, thereby improving the accuracy of the point cloud data set data, thereby reducing the workload of the data processing module in processing the point cloud data, and improving the efficiency of the size detection of the part to be scanned.

[0020] In some embodiments, after rescanning the part to be scanned based on the operating position, the method further includes the following steps: Acquiring a scanning state of the camera shooting module based on the rescan signal, and determining whether the scanning state belongs to a scanning delay; If the scanning state belongs to scanning delay, adjusting the transport speed of the conveyor belt according to the rescanning signal; If the scanning state does not belong to scanning delay, the response time of the camera shooting module is updated according to the re-scanning signal.

[0021] By adopting the above technical solution, when re-scanning is required, it is necessary to determine whether there is a scanning delay in the current camera shooting module, or other situations cause omissions in the scanning data of the parts to be scanned, thereby ensuring that the point cloud data set scanned for each part to be scanned is accurate, thereby improving the dimensional detection accuracy of the parts to be scanned.

[0022] In some embodiments, the feedback data includes a first feedback signal, and updating the response time of the camera module according to the rescan signal includes the following steps: updating a scanning control signal according to a delayed response duration of the camera shooting module and based on the delayed response duration and a first feedback signal; The scanning state of the part to be scanned is adjusted based on the updated scanning control signal.

[0023] By adopting the above technical solution, if there is a delayed response in the camera shooting module, it is necessary to timely adjust the scanning control signal of the next part to be scanned according to the delayed response duration and the first feedback signal, so that during the size detection process of the part to be scanned, the detection accuracy of the size detection system can be adjusted in time to prevent qualified parts from being judged as unqualified parts and wasting resources.

[0024] In summary, this application includes at least one of the following beneficial technical effects: It can efficiently and comprehensively obtain the 3D point cloud data of the parts to be scanned. At the same time, it can also perform data comparison, determine the qualified products and classify the parts to be scanned, realize the whole process of warehousing the parts to be scanned, and ensure the qualified rate of the parts entering the warehouse. The scanning control module obtains feedback data from the parts to be scanned that enter the shooting area, and generates a scanning control signal based on the feedback data, so that the camera shooting module adjusts the scanning state of the parts to be scanned according to the scanning control signal. The camera shooting module is only started when there are parts to be scanned in the shooting area, thereby avoiding the camera shooting module being in a state of continuous scanning, thereby improving the service life of the camera shooting module. By only scanning the parts to be scanned, high-precision point cloud data can be obtained, reducing the workload of the data processing module in processing point cloud data, and improving the efficiency of dimensional detection of the parts to be scanned; During the operation of the part to be scanned, it is necessary to detect in real time whether the point cloud data set taken at the corresponding operating position is complete. If it is incomplete, it is necessary to rescan at the operating position in time to obtain updated point cloud data, and replace the updated point cloud data with the point cloud data taken at the previous operating position to improve the accuracy of the point cloud data set data, thereby reducing the workload of the data processing module in processing point cloud data and improving the efficiency of size detection of the part to be scanned. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a schematic diagram of the structure of a parts warehousing size detection system based on three-dimensional scanning provided in an embodiment of the present application; Figure 2 This is a schematic diagram of the structure of a component storage dimension detection device based on three-dimensional scanning disclosed in an embodiment of the present application; Figure 3This is a block diagram of a method for detecting the dimensions of incoming parts based on three-dimensional scanning provided in an embodiment of the present application; Figure 4 This is another method block diagram provided by an embodiment of the present application; Figure 5 This is a flow chart of a method for detecting the dimensions of parts entering the warehouse based on three-dimensional scanning provided in an embodiment of the present application.

[0026] Explanation of the accompanying drawings: 10. Scanning control module; 11. First scanning unit; 12. Second scanning unit; 13. Signal conversion unit; 20. Camera shooting module; 21. First orientation camera; 22. Second orientation camera; 23. Third orientation camera; 30. Data processing module; 31. Model generation unit; 32. Parameter calculation unit; 33. Detection and judgment unit; 34. Signal generation unit; 40. Parts classification mechanism; 51. Conveyor belt; 52. Parts to be scanned; 53. Sensor No. 1; 54. Camera mounting bracket; 55. Sensor No. 2; 56. Qualified conveyor belt; 57. Unqualified conveyor belt. DETAILED DESCRIPTION

[0027] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. However, it should be understood by those skilled in the art that the present application can be implemented without these details. In some cases, in order to avoid unnecessary descriptions that make various aspects of the present application obscure, the well-known methods, processes, systems, components and / or circuits that have been described at a higher level will not be described in detail. It is obvious to those skilled in the art that various changes can be made to the embodiments disclosed in the present application, and the general principles defined in the present application can be applied to other embodiments and application scenarios without departing from the principles and scope of the present application. Therefore, the present application is not limited to the embodiments shown, but conforms to the broadest scope consistent with the scope claimed for protection in the present application.

[0028] The embodiment of the present application discloses a component warehousing dimension detection system based on three-dimensional scanning.

[0029] Reference Figure 1 and Figure 2A 3D scanning-based component warehousing dimension inspection system includes a scanning control module 10, a camera module 20, a data processing module 30, and a parts classification mechanism 40. The scanning control module 10 is configured to obtain feedback data from the scanning area in real time and generate a scanning control signal based on the feedback data. The camera module 20 is connected to the scanning control module 10 through a network to receive the scanning control signal and adjust the scanning state of the part 52 to be scanned based on the scanning control signal. A point cloud data set is obtained based on triangulation. The point cloud data set includes point cloud data corresponding to different angles of the part 52 to be scanned. The data processing module 30 is connected to the camera module 20 through a network to receive the point cloud data set, generate a 3D point cloud model based on the point cloud data set, and perform dimensional calculations based on the 3D point cloud model to obtain geometric and positional dimensional parameters. The data processing module 30 is further configured to generate an inspection result corresponding to the part 52 to be scanned based on the geometric and positional dimensional parameters and preset parameters. The parts classification mechanism 40 is connected to the data processing module 30 to receive the inspection result and classify the part 52 to be scanned based on the inspection result.

[0030] The "cross-beam area" represents the area where the scanning control module 10 scans the part 52 to be scanned. The scanning control module 10 uses a beam sensor, with a transmitter and receiver positioned on either side of the conveyor belt 51 along the width of the conveyor belt. As the part 52 to be scanned moves along the conveyor belt 51, it passes through the area where the transmitter and receiver face each other, which is referred to as the "cross-beam area." Feedback data is primarily generated by the transmitter transmitting infrared, laser, or visible light in real time into the cross-beam area, and the receiver detecting the optical signal emitted by the transmitter.

[0031] Specifically, when the part to be scanned 52 enters the corresponding reflection area and blocks the light emitted by the transmitter, the receiver detects the signal change and generates corresponding feedback data, and generates a scanning control signal through the feedback data, thereby adjusting the scanning state of the camera shooting module 20 on the part to be scanned 52.

[0032] The scanning control signal is an electrical signal that is transmitted to the camera control module at a very high speed via a data transmission line that can be transmitted using TTL, RS-485, CAN bus, and Ethernet. The signal is then used to control the camera control module to adjust the scanning state of the part 52 to be scanned, including starting and stopping the scan.

[0033] Reference Figure 1 and Figure 2The camera module 20 includes cameras positioned above the conveyor belt 51 and on both sides of the conveyor belt 51 along the wide-band direction. The cameras scan the part 52 to be scanned, specifically using a 3D line structured light camera. When the camera module 20 initiates scanning of the part 52 via a scanning control signal, it acquires a point cloud data set based on triangulation. The point cloud data set includes point cloud data corresponding to different angles of the part 52 to be scanned.

[0034] The triangulation method described here is a measurement technique based on the principles of geometric triangulation. It calculates the position of a target point using known reference points and angle or distance relationships. Specifically, angle intersection and distance intersection methods can be used. In this embodiment, three 3D line structured light cameras located above and on both sides of conveyor belt 51 simultaneously receive a trigger command and immediately initiate scanning. The operating principle of 3D line structured light cameras is based on triangulation. The camera emits structured light stripes with a specific pattern, such as sinusoidal stripes or Gray code stripes. When these stripes are projected onto the surface of a part, the reflected light carries the three-dimensional information of the part surface due to the geometric fluctuations of the part surface. The camera lens accurately captures the reflected light. By analyzing the deformation of the reflected light pattern and using the principle of triangulation, the three-dimensional coordinates of each point on the part surface can be calculated, thereby obtaining point cloud data.

[0035] Reference Figure 1 and Figure 2 In one embodiment, the data processing module 30 includes a model generation unit 31, a parameter calculation unit 32, and a detection and judgment unit 33. The model generation unit 31 is based on a point cloud data set, and obtains point cloud data corresponding to different angles based on the point cloud data set. The point cloud data of different angles are aligned in three-dimensional space based on a point cloud registration algorithm to obtain a three-dimensional point cloud model. The parameter calculation unit 32 obtains linear dimensions and key points based on the three-dimensional point cloud model, and calculates the linear dimensions based on the Euclidean distance formula and calculates the deviation of the key points based on the least squares method to obtain shape and position dimension parameters. The detection and judgment unit 33 generates a detection result corresponding to the part to be scanned 52 based on the shape and position dimension parameters and preset parameters.

[0036] The model generation unit 31 receives a set of point cloud data and generates a 3D point cloud model based on the point cloud data of the part to be scanned 52. Using a point cloud registration algorithm, the unit finds characteristic point pairs in different point cloud data sets, such as those based on curvature and normal orientation, and applies an iterative closest point algorithm and its improved algorithms to accurately align the point cloud data acquired from different angles in 3D space. After registration, the software performs a point cloud stitching operation, fusing the aligned point cloud data into a complete 3D point cloud model of the part, fully restoring the part's true geometry.

[0037] It should be noted here that the point cloud registration algorithm aligns 3D point cloud data acquired from different perspectives or times into the same coordinate system through spatial transformation, and then generates a corresponding three-dimensional point cloud model.

[0038] The parameter calculation unit 32 also uses a built-in geometric dimension calculation algorithm to conduct a detailed analysis of the three-dimensional point cloud model of the part. Regarding the linear dimensions of the part, such as length, width, and height, the data processing module 30 identifies the spatial distance between corresponding feature points in the point cloud model and uses mathematical methods such as the Euclidean distance formula to perform precise calculations. In terms of shape and position calculations of key points, such as calculating the position accuracy, cylindricity, flatness, and other form and position tolerances of holes, the parameter calculation unit 32 uses the local geometric feature analysis of the point cloud model, combined with algorithms such as least squares fitting, to determine the deviation between the theoretical position and actual position of the key points, thereby obtaining accurate shape and position parameters.

[0039] It should be noted here that the geometric dimension calculation algorithm, Euclidean distance formula, least squares algorithm and iterative closest point algorithm can all use existing algorithms, which will not be described in detail here. It is sufficient to obtain the detection results corresponding to the part 52 to be scanned through the above algorithms.

[0040] Reference Figure 1 and Figure 2 In one embodiment, the data processing module 30 further includes a signal generating unit 34 configured to receive the test result sent by the detection and judgment unit 33 and determine whether the test result is qualified. If so, a qualified signal is generated, and based on the qualified signal, the part classification mechanism 40 is controlled to operate in a first preset mode. If not, a failed signal is generated, and based on the failed signal, the part classification mechanism 40 is controlled to operate in a second preset mode.

[0041] The detection result is specifically obtained by comparing the shape and position size parameters with the preset parameters to determine whether the shape and position size parameters of the part to be scanned 52 are within the range of the preset parameters. If so, the detection result of the part to be scanned 52 is that the part is qualified; if not, the detection result of the part to be scanned 52 is that the part is unqualified.

[0042] Furthermore, the preset parameters are the preset dimensional tolerances corresponding to the geometric and positional dimensional parameters. Since geometric and positional dimensional parameters contain at least one numerical value, the corresponding preset parameters also include at least one corresponding preset dimensional tolerance. During the comparison process, reasonable dimensional tolerance ranges are pre-set based on industry standards and production process requirements. For example, for length dimensions, the preset tolerance is set to . For aperture dimensions, the preset tolerance is set to . The specific value is set based on the standard requirements of the specific part.

[0043] It should be noted here that the first preset mode and the second preset mode are modes activated based on the detection results. The first preset mode refers to the use of a mechanical structure to guide the parts to be scanned to the qualified conveyor belt 56, and the second preset mode refers to the use of a mechanical structure to guide the parts to be scanned to the unqualified conveyor belt 57.

[0044] Reference Figure 1 and Figure 2 The parts classification mechanism 40 is connected to the data processing module 30 to receive the test results and perform classification operations on the scanned parts 52 based on the test results. If all parameters of the shape, position and size parameters are within the tolerance range, the part is judged to be qualified, and the data processing module 30 generates a qualified signal and transmits the signal to the control system of the parts classification mechanism 40 through the data communication interface. After receiving the qualified signal, the parts classification mechanism 40 controls the corresponding mechanical structure, such as an electric push rod or a pneumatic valve, to guide the part to the qualified product conveyor belt 56. On the contrary, if any parameter exceeds the tolerance range, the data processing module 30 determines that the part is unqualified. The data processing module 30 generates an unqualified signal and transmits it to the parts classification mechanism 40. The control system of the parts classification mechanism 40 drives the mechanical structure to move and transfer the part to the unqualified product conveyor belt 57, completing the automatic classification process of the parts and achieving efficient and accurate control of the quality of the incoming parts.

[0045] Reference Figure 1 and Figure 2 In one embodiment, the scanning control module 10 includes a first scanning unit 11 and a second scanning unit 12. The first scanning unit 11 is configured to acquire a first feedback signal from a first exposure area in real time and determine whether the first feedback signal is blocked. If so, the first scanning unit 11 generates a scan trigger signal and sends the scan trigger signal to the camera capture module 20 to control the camera capture module 20 to scan the part 52 to be scanned. The second scanning unit 12 is configured to acquire a second feedback signal from a corresponding second exposure area in real time and determine whether the second feedback signal is blocked. If so, the second scanning unit 12 generates a scan stop signal and sends the scan stop signal to the camera capture module 20 to control the camera capture module 20 to stop scanning the part 52 to be scanned.

[0046] The scanning control signal includes a scanning trigger signal and a scanning stop signal corresponding to the scanning trigger signal, and the feedback data includes a first feedback signal and a second feedback signal. The scanning trigger signal represents a signal that controls the camera capture module 20 to start scanning the part 52 to be scanned, while the scanning stop signal represents a signal that controls the camera capture module 20 to stop scanning the part 52 to be scanned.

[0047] Reference Figure 1 and Figure 2The first scanning unit 11 and the second scanning unit 12 are each equipped with a set of sensors, each sensor set including a transmitter and a corresponding receiver. The first scanning unit 11 and the second scanning unit 12 are located on either side of the camera module 20 along the length of the conveyor belt 51. The first feedback signal and the second feedback signal are both optical signals transmitted by the receivers of the first scanning unit 11 and the second scanning unit 12. The first scanning unit 11 includes sensor 1 53, and the second scanning unit includes sensor 2 56.

[0048] In order to ensure that the acquired point cloud data set can accurately correspond to a single part to be scanned 52, when the part to be scanned 52 continues to move along the conveyor belt 51 until it completely passes through the second sensor of the second scanning unit 12, the second sensor repeats the above-mentioned photoelectric conversion process, scans the stop signal and transmits it to the camera shooting module 20 to control the camera shooting module 20 to stop scanning the part to be scanned 52.

[0049] It should be noted here that the scan trigger signal and the scan stop signal appear in pairs. After the corresponding scan trigger signal is generated, the scan stop signal is used to monitor the second feedback signal of the second shooting area in real time by the second scanning unit 12 .

[0050] Reference Figure 1 and Figure 2 In one embodiment, the scan control signal further includes a signal conversion unit 13, which is configured to receive the first feedback signal or the second feedback signal and generate a corresponding scan control signal based on the first feedback signal or the second feedback signal.

[0051] Since the first feedback signal or the second feedback signal generated by the receiver of the sensor is an optical signal, in order to facilitate signal processing, the optical signal is converted into an electrical signal for easy storage and transportation.

[0052] Reference Figure 1 and Figure 2 In one embodiment, the camera shooting module 20 includes a first orientation camera 21, a second orientation camera 22 and a third orientation camera 23. The first orientation camera 21, the second orientation camera 22 and the third orientation camera 23 are started to scan the part 52 to be scanned based on a scanning trigger signal, and the first orientation camera 21, the second orientation camera 22 and the third orientation camera 23 are turned off to stop scanning the part 52 to be scanned based on a scanning stop signal.

[0053] The first orientation camera 21 is set directly above the conveyor belt 51, the second orientation camera 22 and the third orientation camera 23 are located on both sides of the first orientation camera 21, and the first orientation camera 21, the second orientation camera 22 and the third orientation camera 23 are in the same vertical plane.

[0054] Reference Figure 1 and Figure 2 In another embodiment, to more accurately scan the part 52 to be scanned, the first, second, and third azimuth cameras 21, 22, and 23 can all rotate back and forth along the length of the conveyor belt 51. When the part 52 to be scanned moves along the conveyor belt 51 toward the second scanning unit 12 and directly below the first azimuth camera 21, the first, second, and third azimuth cameras 21, 22, and 23 rotate along the direction of movement of the conveyor belt 51. When the part 52 to be scanned arrives at the second scanning area along the conveyor belt 51, the first, second, and third azimuth cameras 21, 22, and 23 stop rotating. When the part 52 to be scanned leaves the second scanning area along the conveyor belt 51, the first, second, and third azimuth cameras 21, 22, and 23 transmit the scanned data to the data processing module 30. The first, second, and third azimuth cameras 21, 22, and 23 simultaneously rotate in the opposite direction of the conveyor belt 51's movement until they return to their initial positions and scan the next part 52 to be scanned.

[0055] Reference Figure 2 and Figure 3 The present application also discloses a method for detecting the dimensions of incoming parts based on 3D scanning, which is applied to a device for detecting the dimensions of incoming parts based on 3D scanning. The device includes a conveyor belt 51, a sensor No. 1 53, a sensor No. 2 55, a qualified conveyor belt 56, and a failed conveyor belt 57. The first azimuth camera 21, the second azimuth camera 22, and the third azimuth camera 23 are all mounted on a camera mounting bracket 54, which is mounted above the conveyor belt 51. The conveyor belt 51 moves along the F direction. The conveyor belt 51 is used to transport the part 52 to be scanned, passing through the sensor No. 1, the three-azimuth camera, and the sensor No. 2 in sequence.

[0056] like Figure 3 As shown in FIG, the method for detecting the size of parts entering the warehouse based on three-dimensional scanning includes the following steps: S100 , obtaining feedback data of the beaming area in real time, and generating a scanning control signal according to the feedback data.

[0057] S200 , adjusting the scanning state of the part to be scanned according to the scanning control signal, and acquiring a point cloud data set based on a triangulation method.

[0058] S300: Generate a three-dimensional point cloud model based on the point cloud data set, and perform size calculation based on the three-dimensional point cloud model to obtain shape and position size parameters.

[0059] S400: Generate a detection result corresponding to the part to be scanned based on the shape, position and size parameters and preset parameters, and perform a classification operation on the part to be scanned based on the detection result.

[0060] Among them, the point cloud data set includes point cloud data corresponding to different angles of the part 52 to be scanned. The technical features described in the above steps S100 to S400 are the same or similar to the corresponding features in the component warehousing dimension detection system based on three-dimensional scanning described above, so they will not be repeated here.

[0061] Reference Figure 4 In one embodiment, before generating a three-dimensional point cloud model based on the point cloud data set, the method further includes the following steps: S210 , obtaining the part type and the running position of the part to be scanned, and obtaining corresponding feature point cloud data from a preset database based on the part type.

[0062] S220 , matching the feature point cloud data in the point cloud data set, and determining whether corresponding data can be matched.

[0063] S230: If the corresponding data cannot be matched, a stop signal is generated, and the conveyor belt is controlled to stop based on the stop signal.

[0064] S240 , rescanning the part 52 to be scanned based on the operating position to obtain updated point cloud data corresponding to the operating position, and replacing the point cloud data corresponding to the operating position with the updated point cloud data.

[0065] The part type represents the product type of the part 52 to be scanned. Based on the part type, corresponding feature point cloud data is obtained from a preset database. Scanning features corresponding to each product type are obtained from the preset database. These scanning features are used to determine whether the acquired point cloud data set has been fully scanned. Scanning features can be obtained by scanning each product type using the first azimuth camera 21, the second azimuth camera 22, and the third azimuth camera 23. The products are divided accordingly based on the scanning routes of the first azimuth camera 21, the second azimuth camera 22, and the third azimuth camera 23. A set of data points is obtained on a plane perpendicular to the same scanning route, and one of the data points is selected from the set as a scanning feature.

[0066] The operating position is a scanning confirmation position set for the part 52 to be scanned. When reaching this position, the conveying speed of the conveyor belt 51 can be reduced to facilitate the data processing module 30 to process the acquired point cloud data set to determine whether the scan is incomplete. If so, an operation stop signal is generated, and the conveyor belt 51 is controlled to stop based on the operation stop signal. The part 52 to be scanned is rescanned based on the operating position to obtain updated point cloud data corresponding to the operating position, and the updated point cloud data replaces the point cloud data corresponding to the operating position.

[0067] The operation stop signal is a signal generated by the data processing module 30 when no corresponding feature point cloud data is matched in the point cloud data set. The updated point cloud data represents the data re-scanned at the operation position, and the re-scanned data replaces the original point cloud data at the operation position.

[0068] It should be noted that when rescanning is required, it is necessary to determine whether the first, second, and third cameras 21, 22, 23 have been rotated. If they have not been rotated, the scan can be repeated. If they have been rotated, they can be rotated in the opposite direction by a certain angle. The rotation angle can be set to 1 or 2 degrees and can be adjusted accordingly.

[0069] If the corresponding data can be matched, it means that the scanning data of the first orientation camera 21, the second orientation camera 22 and the third orientation camera 23 for the scanned parts are complete and do not need to be scanned repeatedly. Therefore, subsequent scanning is performed directly at the original moving speed of the conveyor belt 51.

[0070] In one embodiment, after rescanning the part 52 to be scanned based on the operating position, the following steps are further included: S241 , obtaining a scanning state of the camera shooting module 20 based on the rescanning signal, and determining whether the scanning state belongs to a scanning delay.

[0071] S242: If the scanning state is scanning delay, the transport speed of the conveyor belt 51 is adjusted according to the re-scanning signal.

[0072] S243: If the scanning state does not belong to the scanning delay, the response time of the camera shooting module 20 is updated according to the re-scanning signal.

[0073] The scanning status represents the scanning status of the camera 55 of the camera capture module 20, and includes scanning delay and normal scanning. For scanning delay of the camera capture module 20, when the first, second, and third cameras 21, 22, 23 are activated to scan the part 52 to be scanned, the conveyor belt 51's transport speed can be reduced based on a rescan signal. This allows the first, second, and third cameras 21, 22, 23 to scan the part 52 to be scanned, allowing them to scan the part 52 as needed.

[0074] The extent to which the conveyor belt 51's transport speed is reduced depends on the amount of scan data loss from the first, second, and third cameras 21, 22, and 23. If the loss is significant, the conveyor belt 51's transport speed can be reduced or the first, second, and third cameras 21, 22, and 23 can be replaced. If the loss is minor, the conveyor belt 51's transport speed can be appropriately reduced. The specific values ​​can be set based on actual conditions and will not be elaborated on here. It should be noted that the comparisons of "more" and "less" are based on preset values.

[0075] In one embodiment, updating the response time of the camera module 20 according to the rescan signal includes the following steps: S244 , updating the scanning control signal according to the delayed response time of the camera shooting module 20 and based on the delayed response time and the first feedback signal.

[0076] S245 , adjusting the scanning state of the part 52 to be scanned based on the updated scanning control signal.

[0077] Among them, the feedback data includes a first feedback signal, and the delayed response time represents the delay time for the first orientation camera 21, the second orientation camera 22 and the third orientation camera 23 to be turned on. When the first orientation camera 21, the second orientation camera 22 and the third orientation camera 23 are delayed in turning on, the scanning control signal can be updated accordingly according to the delayed response time and the first feedback signal. The specific updating method is to obtain the first feedback signal, add a corresponding waiting time to the first feedback signal, and then perform corresponding signal conversion on the first feedback signal to generate a scanning control signal.

[0078] The implementation principle is: Reference Figure 2 and Figure 5When a part 52 to be scanned is placed on conveyor belt 51, the conveyor process begins. Sensors 53, located on either side of conveyor belt 51, utilize transmissive photoelectric sensing technology. When a part enters the area of ​​sensor 53, the light path is blocked. The photoelectric conversion element within sensor 53 rapidly responds, converting the optical signal into an electrical signal, generating a scan trigger signal. This scan trigger signal is transmitted to the camera of camera module 20 at extremely high speeds via a dedicated data transmission line.

[0079] At this time, the three 3D line structured light cameras located above and on the left and right sides of the conveyor belt 51 receive the scanning trigger signal at the same time and immediately start the scanning operation to obtain a point cloud data set.

[0080] As part 52 to be scanned continues to move along conveyor belt 51 until it completely passes through first scanning unit 11, sensor No. 2 55 repeats the aforementioned photoelectric conversion process, generating a scanning stop signal and transmitting it to camera module 20. Upon receiving this signal, all three cameras immediately stop scanning, ensuring that the acquired data accurately corresponds to a single part.

[0081] The data processing module 30 then processes the scattered point cloud data obtained by the three cameras using an advanced point cloud registration algorithm. Using the iterative closest point algorithm and its improved algorithm, the point cloud data acquired from different angles are precisely aligned in three-dimensional space. After registration, the data processing module 30 performs a point cloud stitching operation, fusing the aligned point cloud data into a complete three-dimensional point cloud model of the part, fully restoring the true geometry of the scanned part 52.

[0082] Next, the data processing module 30 uses its built-in geometric dimension calculation algorithm to conduct a detailed analysis of the 3D point cloud model. By identifying the spatial distances between corresponding feature points in the point cloud model, it uses mathematical methods such as the Euclidean distance formula to perform precise calculations. For the shape and position calculations of key points, the deviation between their theoretical and actual positions is determined, thereby deriving accurate shape and position dimension parameters.

[0083] After calculating the geometric and dimensional parameters, the data processing module 30 carefully compares the test results obtained with the pre-stored initial data of the part. During the comparison process, a reasonable dimensional tolerance range is pre-set based on industry standards and production process requirements.

[0084] If all parameters are within tolerance, the part is deemed acceptable, and the part sorting mechanism 40 generates a pass signal and transmits this signal to the part sorting mechanism 40 via the data communication interface. Upon receiving the pass signal, the part sorting mechanism 40 controls the corresponding mechanical structure to guide the part onto the acceptable conveyor belt 56. If any parameter exceeds the tolerance, the part is deemed unacceptable by the part sorting mechanism 40. The part sorting mechanism 40 generates a fail signal and transmits it to the part sorting mechanism 40. The part sorting mechanism 40 then activates the mechanical structure to transfer the part 52 to be scanned onto the fail conveyor belt 57, completing the automatic classification process for the part 52 to be scanned, achieving efficient and accurate control of the quality of incoming parts.

[0085] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps and they may be performed in other orders.

[0086] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A parts storage size detection system based on three-dimensional scanning, characterized in that: include: A scanning control module (10), the scanning control module (10) is used to obtain feedback data of the corresponding area in real time and generate a scanning control signal based on the feedback data; A camera shooting module (20) is connected to the scanning control module (10) via a network to receive the scanning control signal, and adjusts the scanning state of the part to be scanned (52) according to the scanning control signal, and obtains a point cloud data set based on a triangulation method, wherein the point cloud data set includes point cloud data corresponding to different angles of the part to be scanned (52); A data processing module (30), the data processing module (30) is connected to the camera shooting module (20) via a network to receive the point cloud data set, generate a three-dimensional point cloud model based on the point cloud data set, and perform size calculation based on the three-dimensional point cloud model to obtain shape and position size parameters, and the data processing module (30) is further used to generate a detection result corresponding to the part to be scanned (52) based on the shape and position size parameters and preset parameters; A parts classification mechanism (40) is connected to the data processing module (30) to receive the detection result and perform a classification operation on the parts to be scanned (52) according to the detection result.

2. The 3D scanning-based parts storage size detection system according to claim 1 is characterized in that: The scanning control signal includes a scanning trigger signal and a scanning stop signal corresponding to the scanning trigger signal, and the feedback data includes a first feedback signal and a second feedback signal. The scanning control module (10) includes a first scanning unit (11) and a second scanning unit (12). The first scanning unit (11) is used to obtain a first feedback signal of a first shooting area in real time and determine whether the first feedback signal is blocked. If blocked, the first scanning unit (11) generates the scanning trigger signal and sends the scanning trigger signal to the camera shooting module (20) to control the camera shooting module (20) to scan the part (52) to be scanned; The second scanning unit (12) is used to obtain the second feedback signal of the corresponding second shooting area in real time, and to determine whether the second feedback signal is blocked. If so, the second scanning unit (12) generates the scanning stop signal and sends the scanning stop signal to the camera shooting module (20) to control the camera shooting module (20) to stop scanning the part to be scanned (52).

3. The 3D scanning-based parts storage size detection system according to claim 2 is characterized in that: The scanning control module (10) further comprises a signal conversion unit (13), wherein the signal conversion unit (13) is used to receive the first feedback signal or the second feedback signal and generate a corresponding scanning control signal based on the first feedback signal or the second feedback signal.

4. The 3D scanning-based parts storage size detection system according to claim 2 is characterized in that: The camera shooting module (20) includes a first orientation camera (21), a second orientation camera (22) and a third orientation camera (23), and starts the first orientation camera (21), the second orientation camera (22) and the third orientation camera (23) to scan the part (52) to be scanned based on the scanning trigger signal, and shuts down the first orientation camera (21), the second orientation camera (22) and the third orientation camera (23) to stop scanning the part (52) to be scanned based on the scanning stop signal.

5. The 3D scanning-based parts storage size detection system according to claim 1 is characterized in that: The data processing module (30) includes a model generation unit (31), a parameter calculation unit (32) and a detection and judgment unit (33); The model generation unit (31) obtains point cloud data corresponding to different angles based on the point cloud data set, and aligns the point cloud data at different angles in three-dimensional space based on a point cloud registration algorithm to obtain a three-dimensional point cloud model; The parameter calculation unit (32) obtains linear dimensions and key points based on the three-dimensional point cloud module, calculates the linear dimensions based on the Euclidean distance formula, and calculates the deviation of the key points based on the least squares method to obtain shape and position dimension parameters; The detection judgment unit (33) generates a detection result corresponding to the part to be scanned (52) based on the shape, position and size parameters and preset parameters.

6. The 3D scanning-based parts storage size detection system according to claim 5 is characterized in that: The data processing module (30) further includes a signal generating unit (34), the signal generating unit (34) being used to receive the detection result sent by the detection and judgment unit (33) and to judge whether the detection result is qualified; if so, a qualified signal is generated, and based on the qualified signal, the parts classification mechanism (40) is controlled to start according to a first preset mode; if not, an unqualified signal is generated, and based on the unqualified signal, the parts classification mechanism (40) is controlled to start according to a second preset mode.

7. A method for detecting the size of parts entering the warehouse based on three-dimensional scanning, applied to a device for detecting the size of parts entering the warehouse based on three-dimensional scanning, wherein the device comprises a conveyor belt (51) for transporting parts to be scanned, and is characterized in that: The following steps are involved: Acquire feedback data of the beam area in real time, and generate a scanning control signal based on the feedback data; Adjusting the scanning state of the part to be scanned according to the scanning control signal, and acquiring a point cloud data set based on a triangulation method, wherein the point cloud data set includes point cloud data corresponding to different angles of the part to be scanned; Generating a three-dimensional point cloud model based on the point cloud data set, and performing size calculation based on the three-dimensional point cloud model to obtain shape and position size parameters; Generate a detection result corresponding to the part to be scanned based on the shape, position and size parameters and preset parameters, and perform a classification operation on the part to be scanned based on the detection result.

8. The method for detecting the size of parts entering the warehouse based on three-dimensional scanning according to claim 7, characterized in that: Before generating a three-dimensional point cloud model based on the point cloud data set, the following steps are also included: Obtaining the part type and running position of the part to be scanned, and obtaining corresponding feature point cloud data from a preset database based on the part type; Matching the feature point cloud data in the point cloud data set and determining whether corresponding data can be matched; If the corresponding data cannot be matched, a stop signal is generated, and the conveyor belt (51) is controlled to stop based on the stop signal; The part to be scanned is rescanned based on the operating position to obtain updated point cloud data corresponding to the operating position, and the updated point cloud data replaces the point cloud data corresponding to the operating position.

9. The method for detecting the size of parts entering the warehouse based on three-dimensional scanning according to claim 8, characterized in that: After rescanning the part to be scanned based on the operating position, the method further includes the following steps: Acquiring a scanning state of the camera shooting module (20) based on a rescanning signal, and determining whether the scanning state belongs to a scanning delay; If the scanning state belongs to scanning delay, adjusting the transport speed of the conveyor belt (51) according to the rescanning signal; If the scanning state does not belong to scanning delay, the response time of the camera shooting module (20) is updated according to the rescanning signal.

10. The method for detecting the size of parts entering the warehouse based on three-dimensional scanning according to claim 9, characterized in that: The feedback data includes a first feedback signal, and the updating of the response time of the camera shooting module (20) according to the rescanning signal includes the following steps: updating a scanning control signal according to a delayed response time of the camera shooting module (20), and based on the delayed response time and a first feedback signal; The scanning state of the part to be scanned is adjusted based on the updated scanning control signal.

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