Non-contact spring testing device and method

Abstract

This invention relates to a non-contact spring inspection device and method, comprising a 3D camera for acquiring 3D images of the spring end face and a linear motion unit for moving the 3D camera. A left linear motion unit and a right linear motion unit are arranged on both sides of a spring transmission line. A left 3D camera is arranged on the left linear motion unit, and a right 3D camera is arranged on the right linear motion unit. The left and right 3D cameras face the spring on the spring transmission line. The 3D cameras, arranged on both sides of the spring transmission line, acquire 3D images of the spring end face. The 3D images are processed, and 3D point cloud data of the spring surface is obtained through 3D scanning. Dimensional features are extracted from the 3D point cloud, the spring length and the diameters of the two end faces are calculated, and the feature measurement results are compared with reference values. Defective products whose dimensions exceed a set threshold are automatically rejected, achieving automated quality inspection.

Description

Technical Field

[0001] This invention relates to a non-contact spring detection device and method. Background Technology

[0002] Currently, quality inspection in the spring industry is mainly carried out manually using customized inspection tools or dimensional measuring equipment. Manual inspection has the following problems: 1) Each type of spring requires customized inspection, resulting in a large number of inspection tools, high costs, and complicated tool management, calibration, and verification; 2) Manual measurement using measuring equipment results in poor consistency, low measurement efficiency, and the inability to digitize the inspection results.

[0003] Therefore, there is an urgent need to design an automatic testing device for the spring industry to replace manual testing.

[0004] Machine vision-based non-contact inspection avoids the use of fixtures, and the inspection system can be integrated into the production line to achieve 100% online measurement. Currently available methods all employ 2D inspection, which is only suitable for planar inspection. The surface morphology of springs is complex, and 2D inspection cannot measure critical 3D dimensions, thus failing to meet quality inspection requirements. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a non-contact spring detection device and method.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] The non-contact spring detection device is characterized by including a 3D camera for acquiring 3D images of the spring end face and a linear motion unit for carrying the 3D camera. A left linear motion unit and a right linear motion unit are arranged on both sides of the spring transmission line. A left 3D camera is arranged on the left linear motion unit and a right 3D camera is arranged on the right linear motion unit. The left and right 3D cameras face the spring on the spring transmission line.

[0008] Furthermore, in the aforementioned non-contact spring detection device, the left linear motion unit and the right linear motion unit are arranged parallel to the spring transmission line.

[0009] Furthermore, in the aforementioned non-contact spring detection device, the left 3D camera and the right 3D camera are line laser contour cameras or photographic structured light cameras.

[0010] The non-contact spring detection method of the present invention includes the following steps:

[0011] 1) Calibrate the left and right 3D cameras and obtain the camera coordinate system transformation relationship T(r, t) between the two 3D cameras, where r is a 3×3 rotation matrix and t is a 3×1 translation matrix;

[0012] 2) After the spring transmission line (102) sends out the spring position signal, the left linear motion unit and the right linear motion unit drive the left 3D camera and the right 3D camera to perform 3D scanning on the two end faces of the spring, and obtain the 3D point cloud data P1 and P2 of the two end faces.

[0013] 3) Calculate the diameters D1 and D2 of the left and right end faces of point clouds P1 and P2 respectively; the steps are as follows:

[0014] 3.1 Template Collection

[0015] Collect 3D point cloud data of the standard spring end face of the type of spring to be measured, and save it as the template point cloud of that type of spring, or select a spring CAD model to be converted into a 3D point cloud as the template point cloud;

[0016] According to the requirements for measuring the geometric dimensions of the spring, ROIs, i.e. regions of interest, are marked on the 3D point cloud data; using 4 ROIs, 2 pairs are formed, with ROI No. 2 and ROI No. 4 as one pair, and ROI No. 3 and ROI No. 5 as another pair, where ROI No. 2 is located at the end of the spring, and the ROI pairs are saved.

[0017] 3.2 Online Measurement

[0018] Collect the point cloud of the spring end face online and match it with the point cloud of the spring template collected in step 3.1;

[0019] After successful matching, the collected point cloud is transformed into the template point cloud coordinate system. For ROIs 2-5, cylindrical fitting is performed on the point cloud data contained in each ROI to obtain the center c2-c5 of the fitted cylinder.

[0020] Calculate the center distances D1 and D2 of the two pairs of ROI fitted cylinders, and use them as the measurement of the spring end face diameter;

[0021] D1 = |c2 - c4|

[0022] D2 = |c3 - c5|

[0023] 3.3 The two end face 3D point cloud data are concatenated together using the following formula to obtain the complete point cloud P;

[0024] P = P1 + T * P2

[0025] 3.4 On the complete point cloud P, calculate the distance L from the farthest end to the end in the length direction of the spring;

[0026] 3.5 Compare the dimensional feature measurements D1, D2, and L with their respective reference values ​​and save all measurement results;

[0027] 4) By comparing the calculated spring length and the diameter of the two end faces with the set threshold, products whose dimensions exceed the set threshold are considered unqualified.

[0028] Furthermore, in the above-mentioned non-contact spring detection method, step 1) utilizes multiple calibration spheres with precisely known relative positions to ensure that there are three spheres within the field of view of two 3D cameras. The two 3D cameras scan the 3D point cloud data of the spheres respectively, perform spherical fitting on the 3D point cloud of each sphere, and obtain the position c1-c6 of the center of each fitted sphere in the camera coordinate system. The transformation relationship T(r, t) between the two 3D camera coordinate systems is calculated using the least squares method.

[0029] Compared with the prior art, the present invention has significant advantages and beneficial effects, specifically reflected in the following aspects:

[0030] This invention utilizes machine vision for non-contact inspection. 3D cameras are positioned on both sides of the spring transmission line to acquire 3D images of the spring end faces. These images are processed to obtain 3D point cloud data of the spring surface through 3D scanning. Dimensional features are extracted from the 3D point cloud, and the spring length and the diameters of the two end faces are calculated. The feature measurement results are compared with reference values, and defective products exceeding a set threshold are automatically rejected, achieving automated quality inspection. Compared to manual inspection, this method offers higher measurement accuracy and repeatability for measuring 3D dimensions related to spring quality.

[0031] It is easy to integrate into the production line, avoids the use of inspection tools, and truly achieves 100% fully automated online inspection. It boasts high measurement efficiency, meets production cycle requirements, and provides 100% digitized measurement results, supporting result traceability and quality analysis. In contrast, 2D inspection is only suitable for planar inspection. Due to the complex surface morphology of springs, 2D inspection cannot measure critical 3D dimensions and therefore cannot meet quality inspection requirements.

[0032] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing specific embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 Template creation diagram;

[0035] Figure 2 : Schematic diagram of the detection device of the present invention;

[0036] Figure 3 : Diagram of two-camera calibration. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0038] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, directional and ordinal terms are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0039] like Figure 2 , Figure 3 As shown, the non-contact spring detection device includes a 3D camera for acquiring 3D images of the spring end face and a linear motion unit for moving the 3D camera. A left linear motion unit 101 and a right linear motion unit 103 are arranged on both sides of the spring transmission line 102, parallel to the spring transmission line 102. A left 3D camera 104 is mounted on the left linear motion unit 101, and a right 3D camera 105 is mounted on the right linear motion unit 103. The left and right 3D cameras 104 and 105 face the spring 106 on the spring transmission line 102. The left and right 3D cameras 104 and 105 are line laser contour cameras or photographic structured light cameras.

[0040] The specific steps of the non-contact spring testing method are as follows:

[0041] 1) Calibrate the left 3D camera (104) and the right 3D camera (105) to obtain the camera coordinate system transformation relationship T(r, t) between the two 3D cameras, where r is a 3×3 rotation matrix and t is a 3×1 translation matrix;

[0042] Using multiple calibration spheres with precisely known relative positions, three spheres are made within the field of view of two 3D cameras. The two 3D cameras scan the 3D point cloud data of the spheres respectively, and perform sphere fitting on the 3D point cloud of each sphere to obtain the position c1-c6 of the center of each fitted sphere in the camera coordinate system. The transformation relationship T(r, t) between the two 3D camera coordinate systems is calculated using the least squares method.

[0043] 2) After the spring transmission line (102) sends out the spring position signal, the left linear motion unit (101) and the right linear motion unit (103) drive the left 3D camera (104) and the right 3D camera (105) to perform 3D scanning on the two end faces of the spring, and obtain the 3D point cloud data P1 and P2 of the two end faces.

[0044] 3) Calculate the diameters D1 and D2 of the left and right end faces of point clouds P1 and P2 respectively; the steps are as follows:

[0045] 3.1 Template Collection

[0046] Collect 3D point cloud data of the standard spring end face of the type of spring to be measured, and save it as the template point cloud of that type of spring, or select a spring CAD model to be converted into a 3D point cloud as the template point cloud;

[0047] Based on the spring's geometric dimensions, Regions of Interest (ROIs) are marked on the 3D point cloud data. Four ROIs are used to form two pairs: ROI 2 and 4 form one pair, and ROI 3 and 5 form another. ROI 2 is located at the spring's end. Each ROI pair is saved, with 1 indicating the 3D point cloud data and 6 indicating the spring's end position. Figure 1 ;

[0048] 3.2 Online Measurement

[0049] Collect the point cloud of the spring end face online and match it with the point cloud of the spring template collected in step 3.1;

[0050] After successful matching, the collected point cloud is transformed into the template point cloud coordinate system. For ROIs 2-5, cylindrical fitting is performed on the point cloud data contained in each ROI to obtain the center c2-c5 of the fitted cylinder.

[0051] Calculate the center distances D1 and D2 of the two pairs of ROI fitted cylinders, and use them as the measurement of the spring end face diameter;

[0052] D1 = |c2 - c4|

[0053] D2 = |c3 - c5|

[0054] 3.3 The two end face 3D point cloud data are concatenated together using the following formula to obtain the complete point cloud P;

[0055] P = P1 + T * P2

[0056] 3.4 On the complete point cloud P, calculate the distance L from the farthest end to the end in the length direction of the spring;

[0057] 3.5 Compare the dimensional feature measurements D1, D2, and L with their respective reference values ​​and save all measurement results;

[0058] 4) By comparing the calculated spring length and the diameter of the two end faces with the set threshold, products whose dimensions exceed the set threshold are considered unqualified.

[0059] In summary, this invention utilizes machine vision for non-contact inspection. 3D cameras are positioned on both sides of the spring transmission line to acquire 3D images of the spring end faces. These images are processed to obtain 3D point cloud data of the spring surface through 3D scanning. Dimensional features are extracted from the 3D point cloud, and the spring length and the diameters of the two end faces are calculated. The feature measurement results are compared with reference values, and defective products exceeding a set threshold are automatically rejected, achieving automated quality inspection. Compared to manual inspection, this method offers higher measurement accuracy and repeatability for measuring 3D dimensions related to spring quality.

[0060] It is easy to integrate into the production line, avoids the use of inspection tools, and truly achieves 100% fully automated online inspection. It boasts high measurement efficiency, meets production cycle requirements, and provides 100% digitized measurement results, supporting result traceability and quality analysis. In contrast, 2D inspection is only suitable for planar inspection. Due to the complex surface morphology of springs, 2D inspection cannot measure critical 3D dimensions and therefore cannot meet quality inspection requirements.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the scope of protection of the invention. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0062] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

[0063] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A non-contact spring detection method, characterized by: The non-contact spring detection device comprises a 3D camera for collecting 3D images of spring end faces and a linear motion unit for carrying the motion of the 3D camera, and a left linear motion unit (101) and a right linear motion unit (103) are arranged on both sides of a spring transmission line (102), a left 3D camera (104) is arranged on the left linear motion unit (101), a right 3D camera (105) is arranged on the right linear motion unit (103), and the left 3D camera (104) and the right 3D camera (105) face the spring (106) on the spring transmission line (102); comprising the following steps: 1) calibrating the left 3D camera (104) and the right 3D camera (105) to obtain the camera coordinate system conversion relationship T (r, t) between the two 3D cameras, wherein r is a 3*3 rotation matrix and t is a 3*1 translation matrix; 2) after the spring transmission line (102) sends a spring to position signal, the left linear motion unit (101) and the right linear motion unit (103) drive the left 3D camera (104) and the right 3D camera (105) to perform 3D scanning on the two end faces of the spring to obtain 3D point cloud data P1 and P2 of the two end faces; 3) calculating the left end face diameter D1 and the right end face diameter D2 from the point clouds P1 and P2; the steps are: 3.1 template collection Collecting 3D point cloud data of the standard spring end face of the measured type of spring and saving it as a template point cloud of the type of spring, or selecting a spring CAD model to convert it into a 3D point cloud as a template point cloud; According to the spring geometric size measurement requirements, mark the ROI, i.e. the region of interest, on the 3D point cloud data; use four ROIs to form two pairs, with No. 2 ROI and No. 4 ROI as one pair and No. 3 ROI and No. 5 ROI as the other pair, wherein No. 2 ROI is at the spring end position, and the ROI pairs are saved; 3.2 online measurement Collecting spring end face point cloud data online and matching it with the spring template point cloud collected in step 3.1; After successful matching, transform the collected point cloud data to the template point cloud coordinate system, and for ROIs 2-5, perform cylindrical fitting on the point cloud data contained in each ROI to obtain fitting cylindrical centers c2-c5; Calculate the distance D1 and D2 between the fitting cylindrical centers of the two ROI pairs as the spring end face diameter measurement; D1 = |c2 – c4| D2 = |c3 – c5| 3.3 splice the two end face 3D point cloud data together through the following formula to obtain the complete point cloud P; P = P1 + T*P2 3.4 calculate the farthest end-to-end distance L in the length direction of the spring on the complete point cloud P; 3.5 compare the size feature measurement values D1, D2 and L with their respective reference values respectively, and save all measurement results; 4) compare the calculated spring length and the two end face diameters with the set threshold value, and regard the size exceeding the set threshold value as unqualified products.

2. The non-contact spring inspection method of claim 1, wherein: In step 1), three balls are arranged in the field of view of two 3D cameras by using multiple calibration balls with relatively accurate known positions, the 3D point cloud data of the balls are scanned by the two 3D cameras respectively, the 3D point cloud of each ball is fitted with a spherical ball, the positions of the centers of the fitted spherical balls in the coordinate system of the cameras are obtained as c1-c6, and the conversion relationship T(r,t) between the coordinate systems of the two 3D cameras is calculated by using the least square method.

3. The non-contact spring inspection method of claim 1, wherein: The left linear motion unit (101) and the right linear motion unit (103) are arranged in parallel with the spring transmission line (102).

4. The non-contact spring inspection method of claim 1, wherein: The left 3D camera (104) and the right 3D camera (105) are line laser profile cameras or photographing structured light cameras.

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