Object data detection system and method

Abstract

An object data detection system. The system comprises: a scanning apparatus (110), a projection apparatus (130) and a processor (120), wherein the scanning apparatus (110) is configured to scan a target object to obtain target scanning data of the target object, and send the target scanning data to the processor (120); the processor (120) is configured to acquire standard object data corresponding to the target scanning data, determine, on the basis of a projection pose relationship between the projection apparatus (130) and the target object and the standard object data, target projection data corresponding to at least part of an object area of the target object, and send the target projection data to the projection apparatus (130); and the projection apparatus (130) is configured to project the target projection data onto the target object. The projection apparatus (130) projects target projection data onto the target object, such that workpiece deviation data can be directly observed, thereby improving the readability of the workpiece deviation data, and further improving the correction accuracy of the workpiece deviation data. Further disclosed is an object data detection method.

Description

An object data detection system and method Cross-references to related applications

[0001] This application claims priority to Chinese Patent Application No. 202411561721.X, filed on November 4, 2024, entitled "An Object Data Detection System and Method", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This invention relates to the field of data detection technology, and in particular to an object data detection system and method. Background Technology

[0003] With the rapid development of the manufacturing industry, the precision of manufactured workpieces has also greatly improved. However, in actual production, due to various factors, deviations still occur between the workpieces and standard workpieces. How to detect and correct these deviations has become an urgent problem to be solved.

[0004] In existing technologies, the workpiece is typically scanned, and the scanned data of the workpiece is compared with that of a standard workpiece to obtain the deviation data between the two. The deviation data of the workpiece is then displayed on a computer, and technicians correct the deviation of the workpiece based on their experience and the deviation data on the computer.

[0005] However, technicians rely on experience combined with deviation data from the computer to correct workpiece deviations, meaning they can only determine the location of the deviation based on experience. This method of determining the deviation location based on experience may lead to correction failures and further exacerbate the deviation between the workpiece and the standard workpiece. It also suffers from poor readability of workpiece deviation data and low accuracy in workpiece deviation correction. Summary of the Invention

[0006] This invention provides an object data detection system and method to solve the problems of poor readability and low accuracy of workpiece deviation data correction in the prior art.

[0007] According to one aspect of the present invention, an object data detection system is provided, comprising: a scanning device, a projection device, and a processor, wherein the scanning device is configured to scan a target object to obtain target scan data of the target object and send the target scan data to the processor; the processor is configured to acquire standard object data corresponding to the target scan data, determine target projection data corresponding to at least a portion of the object area of ​​the target object based on the projection pose relationship between the projection device and the target object and the standard object data, and send the target projection data to the projection device; the projection device is configured to project the target projection data onto the target object.

[0008] According to another aspect of the present invention, an object data detection method is provided, applied to an object data detection system. The method includes: scanning a target object with a scanning device to obtain target scan data of the target object, and sending the target scan data to a processor; acquiring standard object data corresponding to the target scan data through the processor; determining target projection data corresponding to at least a portion of the object area of ​​the target object based on the projection pose relationship between the projection device and the target object and the standard object data, and sending the target projection data to the projection device; and projecting the target projection data onto the target object through the projection device.

[0009] The technical solution of this invention involves scanning a target object using a scanning device to obtain target scan data, which is then sent to a processor. The processor then acquires standard object data corresponding to the target scan data and determines target projection data corresponding to at least a portion of the target object's area based on the projection pose relationship between the projection device and the target object, and the standard object data. Finally, the target projection data is sent to the projection device, which projects the target projection data onto the target object. This allows for direct observation of workpiece deviation data, improving its readability and further enhancing the accuracy of corrections.

[0010] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 is a schematic diagram of the structure of an object data detection system provided in Embodiment 1 of the present invention;

[0013] Figure 2 is a flowchart of an object data detection method according to Embodiment 2 of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] Example 1

[0017] Figure 1 is a schematic diagram of an object data detection system provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where target projection data is projected onto a target object. The system can be implemented in hardware and / or software. As shown in Figure 1, the object data detection system includes: a scanning device 110, a processor 120, and a projection device 130.

[0018] The scanning device 110 can be configured to scan the target object, obtain target scanning data of the target object, and send the target scanning data to the processor; the processor 120 can be configured to acquire standard object data corresponding to the target scanning data, determine target projection data corresponding to at least a portion of the object area of ​​the target object based on the projection pose relationship between the projection device and the target object and the standard object data, and send the target projection data to the projection device; the projection device 130 can be configured to project the target projection data onto the target object.

[0019] The target object can be an entity requiring deviation detection and correction, such as a workpiece, product, or other object whose conformity or accuracy needs to be evaluated. The target object can consist of multiple object regions, and a partial object region can be one or more object regions that make up the target object. A partial object region can be obtained by combining a single independent object region, multiple object regions, or all object regions in the target object. For example, if the target object consists of region 1, region 2, region 3, and region 4, then the partial object region can be a single object region of region 1 or region 2, or it can be an object region obtained by combining region 1 and region 2 or other regions, or it can be an object region composed of combining region 1, region 2, region 3, and region 4. By defining different object regions, deviation detection can be flexibly performed on different regions of the target object according to the user's actual inspection needs, improving the user's inspection experience.

[0020] The target scan data can be obtained by scanning the target object using a scanning device, and may include scan data of at least a portion of the target object's area. The target scan data can be used to characterize the current actual state of the target object. It may include detailed parameter data such as the target object's size, shape, and surface quality. Scanning the target object with a scanning device yields target scan data characterizing its actual state, providing a data basis for deviation detection and improving the accuracy of deviation detection.

[0021] The standard object data can be pre-set by technicians; it represents the production standard data of the target object and can be used to detect deviations from the target object. The projection pose relationship can be determined by the positional relationship between the target object and the projection device, characterizing the pose relationship between the target object and the projection device when the projection device projects the projection data onto the target object. There may be deviations between the target scan data and the standard object data.

[0022] The target projection data can be determined by the processor based on the projection pose relationship between the projection device and the target object and standard object data, and is the projection data projected onto the target object by the projection device. By processing the deviation data of the target object according to the projection pose relationship between the projection device and the target object, projection data corresponding to at least a portion of the target object's area can be obtained. By projecting the deviation data of the target object onto the corresponding area of ​​the target object through the projection device, technicians correcting the target object can intuitively observe the deviation data on the target object and then correct the deviation based on the deviation data. Projecting the target projection data onto the target object allows technicians to directly observe the deviations existing in the target object in the corresponding area, avoiding erroneous corrections by technicians, thereby improving both the efficiency and accuracy of deviation correction by technicians.

[0023] For example, when detecting and correcting deviations in a target object, a technician can scan the target object's data using a scanning device. After scanning the target object's data, the scanning device sends the scanned data to a processor. The processor receives the target scanned data from the scanning device and determines the corresponding standard object data based on the target scanned data's position information. Based on the comparison between the target scanned data and the corresponding standard object data, the deviation data of the target object is determined. The deviation data of the target object is then processed according to the projection pose relationship between the projection device and the target object to obtain target projection data corresponding to at least a portion of the target object's area. By processing the target object's deviation data according to the projection pose relationship between the projection device and the target object, target projection data corresponding to at least a portion of the target object's area can be obtained. After obtaining the target projection data corresponding to at least a portion of the target object's area, the target projection data can be sent to a projection device. The projection device can project the target object's deviation data onto the corresponding object area of ​​the target object. When correcting the target object, the technician can directly observe the projection data projected onto the target object and then correct the target object's deviation based on the projection data.

[0024] Specifically, the processor is configured to: determine a comparison chromatogram of the target object based on standard object data and target scan data, and determine target deviation data based on the comparison chromatogram, wherein the target scan data includes scan data of at least a portion of the object region of the target object.

[0025] The contrast chromatogram, determined by the processor after comparing standard object data and target scan data, is a chromatogram used to characterize the deviation data between the target scan data and the standard object data. The contrast chromatogram can represent the deviation between the target scan data and the standard object data. For example, different degrees of deviation can be distinguished by color gradients or different color regions. The target deviation data can be based on specific deviation information extracted from the contrast chromatogram, including deviation data information such as the location, magnitude, and direction of the deviation.

[0026] The processor is further configured to: determine the deviation points and corresponding deviation types in the target object based on the comparison chromatogram; determine the deviation markers corresponding to the deviation points based on the deviation types corresponding to the deviation points; and determine the target projection data based on the deviation points and the corresponding deviation markers.

[0027] Here, a deviation point can be a point on the target object that deviates from the data of a standard object. The deviation type can be the specific category of difference between the target object and the standard object data; deviation types can include dimensional deviation, shape deviation, positional deviation, color deviation, etc. A deviation marker can include at least one of the following: the deviation value under the deviation type, deviation correction guidance information corresponding to the deviation type, and a type identifier used to characterize the deviation type. A deviation marker can be a mark used to characterize the deviation type and deviation value of a deviation point, and can be used to assist deviation correction personnel in correcting the deviation points of the target object. The deviation value under the deviation type can be the specific amount or degree of difference between the target object and the standard object data under any deviation type.

[0028] The deviation value can be a specific numerical value used to quantify the magnitude of the deviation between the target object and the standard object data. For example, under the size deviation type, the deviation value might represent the difference between the actual size of the target object and the standard size; under the position deviation type, the deviation value might represent the offset between the actual position and the standard position of a feature point on the target object. When correcting the deviation of the target object, the correction personnel can directly determine the deviation status of the target object based on the deviation value.

[0029] The deviation correction guidance information can be a correction suggestion or correction step corresponding to any deviation type, with different deviation types corresponding to different deviation correction guidance information. The deviation correction guidance information can be pre-set correction measures based on the professional knowledge and experience of those skilled in the art. The deviation correction guidance information may include information such as adjustment methods, required tools or equipment, and correction steps. When correcting deviations of a target object, correction personnel can more effectively perform correction operations by following this guidance information to reduce or eliminate the deviation. Type identification can be identification information such as symbols, codes, or color codes used to correct deviation types. Correction personnel can quickly determine the nature and type of deviation by observing the type identification of the deviation point, and thus take appropriate measures.

[0030] The scanning device is configured to scan multiple local areas of a target object to obtain target scan data of the target object, and send the target scan data to a processor; the processor is configured to concatenate the target scan data of the multiple local areas into object scan data of the target object, and determine standard object data based on the object scan data; or, determine standard object data corresponding to the target scan data of each local area separately.

[0031] A target object can be a whole composed of multiple local regions. Before scanning the target object, it can be divided into multiple local regions to facilitate scanning by technicians. These local regions can be the object areas that make up the target object.

[0032] For example, when scanning a target object, a scanning device can sequentially scan multiple local regions that make up the target object. After receiving the local region scanning results of the target object sent by the scanning device, the processor can determine the scanning result of a single local region of the target object as the target scanning data, and determine the standard data corresponding to the single local region as the standard object data; or after receiving the local region scanning results of the target object sent by the scanning device, it can stitch together the scanning results of multiple local regions of the target object, determine the stitched data as the target scanning data, and determine the standard data corresponding to the object data obtained after stitching together the multiple local region scanning results as the standard object data.

[0033] The processor is specifically configured to: determine the target scaling ratio based on the object information of the target object, and scale the standard object data according to the target scaling ratio to obtain the target projection data.

[0034] The target scaling factor can be a scaling factor determined based on the difference between the actual size of the target object and the size in the standard object data. The target scaling factor is used to scale the deviation data to ensure that the data projected onto the target object matches the actual size of the target object.

[0035] By having the processor determine the target scaling ratio based on the object information of the target object, and then scaling the standard object data according to the target scaling ratio, the target projection data can be obtained, which can improve the adaptability and accuracy of the projection data, and optimize the visual effects and user experience.

[0036] The object data detection system also includes a tracking device. This tracking device is configured to identify marked feature points on the target object, determine the projection pose relationship between the projection device and the target object based on the identification results, and send the projection pose relationship to the processor. The number of tracking devices can be at least one, i.e., one or more, and the specific number can be set according to the size of the target object or the actual tracking requirements of the target object. Multiple tracking devices can be fixed in different directions on the target object, thereby achieving the purpose of identifying and tracking all marked feature points existing on the target object.

[0037] The marked feature points can be easily identifiable and locatable points or features on the target object. They can be pre-set markers or obvious feature points on the target object. These marked feature points are used to determine the projection pose relationship between the projection device and the target object. For example, feature points can be corners, edges, center points, or other significant features of the target object. By identifying these feature points, the tracking device can accurately calculate the relative position and orientation between the projection device and the target object. The identification result can be the information obtained by the tracking device after identifying the marked feature points on the target object. The identification result can include the position, number, and type of the feature points, and can be used to determine the projection pose relationship between the projection device and the target object.

[0038] By identifying marked feature points on the target object through a tracking device, the object region corresponding to the target scan data of the target object scanned by the scanning device is determined, and the projection pose relationship between the projection device and the target object is determined. The projected data is processed based on this projection pose relationship, and the processed projection data is determined as the target projection data, which improves projection accuracy and ensures that the projected image is accurately projected onto the corresponding area of ​​the target object.

[0039] Optionally, the projection device can be mounted on the tracking device. In cases involving multiple tracking devices, a corresponding projection device can be mounted on each tracking device, allowing the projection device to more accurately project all the image data to be projected onto any area of ​​the target object. By mounting the projection device on the tracking device, the projection area of ​​the projection device covers the tracking area of ​​the tracking device, ensuring that the range of the projection device is greater than or equal to the tracking range of the tracking device. This allows the projection device to project the target projection data onto any area of ​​the target object. This improves projection accuracy while ensuring that the projection range of the projection device covers the entire target object area.

[0040] The processor is further configured to: determine preliminary projection data based on standard object data, and perform pose transformation on the preliminary projection data according to the projection pose relationship between the projection device and the target object to obtain target projection data.

[0041] The preliminary projection data can be generated by comparing standard object data and target scan data, without undergoing pose transformation. The preliminary projection data is used to characterize the deviation projection data between the target object and the standard object data.

[0042] Pose transformation can be a process of adjusting and transforming preliminary projection data according to the actual pose relationship between the projection device and the target object. Through pose transformation, it can be ensured that the projection data can be accurately aligned and cover the corresponding area of ​​the target object. Pose transformation can include at least one of the transformation operations such as translation, rotation, and scaling.

[0043] The processor determines preliminary projection data based on standard object data, and then performs pose transformation on the preliminary projection data according to the projection pose relationship between the projection device and the target object to obtain the target projection data. This allows for the acquisition of projection data corresponding to various local areas of the target object, thereby enhancing the projection adaptability of the projection device and optimizing its projection effect.

[0044] The object data detection system further includes: a display device; wherein the display device is configured to display target deviation data of the target object; a processor is further configured to respond to a user's deviation data projection command, determine target deviation projection data according to the deviation data projection command, and project the target deviation projection data onto the target object; the projection device is further configured to project the target deviation projection data onto the target object.

[0045] The deviation data projection instruction can be a command generated by a technician after clicking on the target deviation data displayed on the display device, to project the deviation data. The target deviation projection data can be the identification information corresponding to the deviation projection data selected by the user in the deviation data projection instruction. The deviation data projection instruction can include the identification information of the target deviation projection data.

[0046] For example, the target deviation data displayed on the display device includes deviation data of deviation point A, deviation data of deviation point B, deviation data of deviation point C, and deviation data of deviation point D. The user can click on the deviation data of deviation point A and determine the deviation data of deviation point A as the target deviation projection data. After receiving the target deviation projection data sent by the processor, the projection device can project the target deviation projection data onto the target object.

[0047] Displaying the target deviation data of the target object on a display device allows users to macroscopically observe the deviations of the target object, facilitating an overall assessment of its condition. Users can issue deviation data projection commands to select one or more target deviation data points for projection, avoiding interference from simultaneous projection of multiple data points and further improving the speed of target deviation data correction.

[0048] The technical solution of this embodiment scans the target object using a scanning device to obtain scan data corresponding to multiple local regions of the target object. When the processor performs deviation detection on the target object, the scan data corresponding to a single local region or a region composed of multiple local regions can be determined as the target scan data, and the standard object data corresponding to the target scan data can be determined. By using the target scan data and the standard object data corresponding to the target scan data to perform deviation detection on the target object, the object region to be detected each time in the target object can be flexibly determined. After determining the target deviation data of the target object, the target deviation data can be transformed and scaled by combining the projection pose relationship between the projection device and the target object to obtain the target projection data. Then, according to the user's deviation data projection command, the target deviation projection data is determined, and the target deviation projection data is projected onto the target object by the projection device. This avoids the interference caused by the simultaneous projection of multiple target deviation data to the user's correction work, further improving the correction speed and accuracy of the target deviation data.

[0049] Example 2

[0050] Figure 2 is a flowchart of an object data detection method provided in Embodiment 2 of the present invention. As shown in Figure 2, the method includes:

[0051] S110. The target object is scanned by the scanning device to obtain the target scan data of the target object, and the target scan data is sent to the processor.

[0052] S120: Obtain standard object data corresponding to the target scanning data through the processor, determine target projection data corresponding to at least a part of the object area of ​​the target object based on the projection pose relationship between the projection device and the target object and the standard object data, and send the target projection data to the projection device.

[0053] S130. Project the target projection data onto the target object using a projection device.

[0054] The technical solution of this invention involves scanning a target object using a scanning device to obtain target scan data, which is then sent to a processor. The processor acquires standard object data corresponding to the target scan data. Based on the projection pose relationship between the projection device and the target object, and the standard object data, it determines target projection data corresponding to at least a portion of the target object's area, and sends this target projection data to the projection device. The projection device then projects the target projection data onto the target object. This allows for intuitive observation of workpiece deviation data, improving its readability and further enhancing the accuracy of corrections.

[0055] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0056] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention. Industrial applicability

[0057] The technical solution of this invention involves scanning a target object using a scanning device to obtain target scan data, which is then sent to a processor. The processor then acquires standard object data corresponding to the target scan data and determines target projection data corresponding to at least a portion of the target object's area based on the projection pose relationship between the projection device and the target object, and the standard object data. Finally, the target projection data is sent to the projection device, which projects the target projection data onto the target object. This allows for direct observation of workpiece deviation data, improving its readability and further enhancing the accuracy of corrections.

Claims

1. An object data inspection system, comprising: The scanning device, the projection device, and the processor, among which, The scanning device is configured to scan a target object, obtain target scanning data of the target object, and send the target scanning data to the processor; The processor is configured to acquire standard object data corresponding to the target scanning data, determine target projection data corresponding to at least a portion of the object region of the target object based on the projection pose relationship between the projection device and the target object and the standard object data, and send the target projection data to the projection device. The projection device is configured to project the target projection data onto the target object.

2. The object data detection system according to claim 1, wherein, The processor is specifically configured as follows: A comparison chromatogram with the target object is determined based on the standard object data and the target scan data, and target deviation data is determined based on the comparison chromatogram, wherein the target scan data includes scan data of at least a portion of the object region of the target object.

3. The object data detection system according to claim 2, wherein, The processor is further configured to: Based on the comparative chromatogram, the deviation points in the target object and the deviation types corresponding to the deviation points are determined. Based on the deviation types corresponding to the deviation points, the deviation markers corresponding to the deviation points are determined. Based on the deviation points and the deviation markers corresponding to the deviation points, the target projection data is determined.

4. The object data detection system according to claim 3, wherein, The deviation marker includes at least one of the following: a deviation value under the deviation type, deviation correction guidance information corresponding to the deviation type, and a type identifier for characterizing the deviation type.

5. The object data detection system according to any one of claims 1 to 4, wherein: The scanning device is configured to scan multiple local areas of a target object to obtain target scanning data of the target object, and send the target scanning data to a processor; The processor is configured to concatenate the target scan data of multiple local regions into object scan data of the target object, and determine standard object data based on the object scan data; or, to determine standard object data corresponding to the target scan data of each local region respectively.

6. The object data detection system according to any one of claims 1 to 5, wherein, The processor is specifically configured as follows: The target scaling ratio is determined based on the object information of the target object, and the standard object data is scaled according to the target scaling ratio to obtain the target projection data.

7. The object data detection system according to any one of claims 1 to 6, wherein, It also includes: a tracking device; wherein, The tracking device is configured to identify marked feature points on the target object, determine the projection pose relationship between the projection device and the target object based on the identification result, and send the projection pose relationship to the processor.

8. The object data detection system according to any one of claims 1 to 7, wherein, The processor is further configured to: Preliminary projection data is determined based on the standard object data, and the preliminary projection data is transformed according to the projection pose relationship between the projection device and the target object to obtain the target projection data.

9. The object data detection system according to any one of claims 1 to 8, wherein, It also includes: a display device; wherein, The display device is configured to display target deviation data of the target object; The processor is also configured to respond to a user's deviation data projection instruction, determine target deviation projection data according to the deviation data projection instruction, and project the target deviation projection data into the device. The projection device is further configured to project the target deviation projection data onto the target object.

10. An object data detection method, applied to the object data detection system as described in any one of claims 1 to 9, the method comprising: The target object is scanned by a scanning device to obtain target scan data of the target object, and the target scan data is sent to the processor; The processor acquires standard object data corresponding to the target scanning data, determines target projection data corresponding to at least a portion of the object area of ​​the target object based on the projection pose relationship between the projection device and the target object and the standard object data, and sends the target projection data to the projection device. The target projection data is projected onto the target object using a projection device.

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