Rotor core skew angle detection method

Abstract

The invention discloses a method for detecting the skew angle of a rotor core, and belongs to the field of motor manufacturing, images of the upper end and the lower end of a rotor are collected respectively, and each image comprises a plurality of continuous aluminum grooves and at least one buckling point; carrying out edge enhancement on each image, extracting a plurality of aluminum groove straight edges and buckling point edges, taking buckling points as feature points, and carrying out upper and lower end face image registration; calculating the displacement difference X of the corresponding edges of the upper and lower end faces of the same aluminum groove through gray gradient interpolation, and obtaining a mean value delta X of the displacement differences of the multiple aluminum grooves; measuring the height H of the rotor by adopting a laser range finder or a three-coordinate measuring instrument; the skew angle is calculated through the pictures collected by the cameras at the upper end and the lower end, the measurement error is low, the efficiency is high, and measurement is convenient.

Description

Technical Field

[0001] The present invention relates to the field of motor manufacturing, and in particular to a method for detecting a skew angle of a rotor core. Background Art

[0002] During rotor manufacturing, the aluminum slots are arranged in a way that makes them no longer completely parallel to the rotor axis, but rather tilted at a certain angle, known as skew. This skew in the rotor core can be used to suppress motor harmonics, weakening the additional torque caused by harmonic magnetic fields and reducing motor vibration and noise. Therefore, rotor skew size is a key factor in ensuring rotor performance.

[0003] However, due to the particularity of the rotor skew size, there is currently no direct method to measure the skew size. It can only be roughly measured by using the height caliper marking method. The measurement error is large, the efficiency is low, it is not conducive to controlling product quality, and it is easy to cause batch defective products. Summary of the Invention

[0004] In order to overcome the deficiencies of the prior art, one of the objectives of the present invention is to provide a method for detecting the skew angle of a rotor core with low measurement error and high efficiency.

[0005] One of the purposes of the present invention is achieved by the following technical solution:

[0006] A method for detecting a rotor core skew angle comprises the following steps:

[0007] Image acquisition: Collect images of the upper and lower ends of the rotor respectively, each image includes multiple continuous aluminum grooves and at least one buckle point;

[0008] Image preprocessing: Perform edge enhancement on each image, extract multiple straight edges of aluminum grooves and edges of buckle points, use the buckle points as feature points, and perform upper and lower end face image registration;

[0009] Displacement difference calculation: Calculate the displacement difference X of the corresponding edges of the upper and lower end surfaces of the same aluminum slot through grayscale gradient interpolation, and take the average ΔX of the displacement differences of multiple aluminum slots;

[0010] Height measurement: Use a laser rangefinder or a three-coordinate measuring machine to measure the rotor height H;

[0011] Calculate the skew angle: skew angle θ = arctan (H / ΔX).

[0012] Furthermore, in the image preprocessing step, the buckle point is used as a feature point to perform upper and lower end face image registration. Specifically, according to the annular distribution characteristics of the aluminum groove, a unique code is assigned to each aluminum groove near the buckle point, and a slot mapping table of the upper and lower end faces is established.

[0013] Furthermore, when registering the upper and lower end surface images, matching is performed from the upper end surface to the lower end surface, and the same matching process is performed in reverse from the lower end surface to the upper end surface. When the bidirectional matching results are consistent, it is determined to be a correct correspondence.

[0014] Furthermore, the uniform distribution characteristics of the aluminum slots are used to check whether the angular intervals of adjacent slots are consistent, thus eliminating isolated mismatches.

[0015] Furthermore, the rotor core skew angle detection method also includes a calibration step, which is specifically as follows: after detecting the skew angle of a preset rotor core each time, a standard rotor core with a known skew angle is inserted to perform system calibration to correct image registration drift caused by mechanical vibration or temperature change.

[0016] Furthermore, in the image acquisition step, the light source uses coaxial light or an annular LED light source to evenly illuminate the end surface of the aluminum groove to avoid reflection interference and enhance the straight edge contrast; the camera uses a telecentric lens to eliminate perspective distortion.

[0017] Furthermore, the image preprocessing step also includes denoising filtering, which is located before the edge enhancement step for each image. The denoising filtering step specifically includes: using Gaussian filtering or median filtering to eliminate image noise.

[0018] Furthermore, in the image acquisition step, the rotor is formed by a plurality of laminations stacked in a height direction, and the buckling points of the plurality of laminations are located on the same straight line and the straight line is parallel to the rotor axis.

[0019] Compared with the existing technology, the rotor core skew angle detection method of the present invention collects images of the upper and lower ends of the rotor respectively, each image including multiple continuous aluminum slots and at least one buckle point; performs edge enhancement on each image, extracts multiple straight edges of the aluminum slots and the edges of the buckle points, uses the buckle points as feature points, and performs upper and lower end face image registration; calculates the displacement difference X of the corresponding edges of the upper and lower end faces of the same aluminum slot through grayscale gradient interpolation, and takes the average ΔX of the displacement differences of multiple aluminum slots; measures the rotor height H using a laser rangefinder or a three-dimensional coordinate measuring instrument; calculates the skew angle θ = arctan(H / ΔX), and calculates the skew angle using images collected by the upper and lower end cameras. The measurement error is low, the efficiency is high, and the measurement is convenient. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a three-dimensional diagram of a rotor to be detected in the rotor core skew angle detection method of the present invention;

[0021] Figure 2 for Figure 1 A three-dimensional cross-sectional view of a rotor;

[0022] Figure 3Schematic diagram of the principle of the rotor core skew angle detection method of the present invention;

[0023] Figure 4 This is a flow chart of the rotor core skew angle detection method of the present invention.

[0024] In the figure: 10, rotor; 11, aluminum slot; 110, first side; 111, second side; 12, buckle point slot. DETAILED DESCRIPTION

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0026] It should be noted that when a component is referred to as being "fixed to" another component, it may be directly on the other component or there may be another intermediate component through which it is fixed. When a component is considered to be "connected to" another component, it may be directly connected to the other component or there may be another intermediate component at the same time. When a component is considered to be "set on" another component, it may be directly set on the other component or there may be another intermediate component at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0028] like Figure 1 as well as Figure 2 As shown, the rotor core skew angle detection method of the present application is used to measure the skew angle of the aluminum slot 11 of the rotor 10. The rotor 10 is formed by stacking a plurality of laminations. During the stacking process of the plurality of laminations, the adjacent laminations rotate by a preset fixed angle, causing the aluminum slot 11 to be skewed. The skew of the rotor 10 can be used to suppress the harmonics of the motor, weaken the additional torque caused by the harmonic magnetic field, and reduce the vibration and noise of the motor. However, during the core manufacturing process, it is necessary to measure the skew angle to detect the quality of the rotor. However, the circumferential side of the aluminum slot 11 is not connected to the outside, which makes it difficult to measure the skew angle of the aluminum slot 11.

[0029] like Figure 3 as well as Figure 4 As shown, a method for detecting the skew angle of a rotor core comprises the following steps:

[0030] Image acquisition: Images of the upper and lower ends of the rotor 10 are collected respectively, each image including a plurality of continuous aluminum grooves 11 and at least one buckle point;

[0031] Image preprocessing: Perform edge enhancement on each image, extract multiple straight edges of aluminum grooves and edges of buckle points, use the buckle points as feature points, and perform upper and lower end face image registration;

[0032] Displacement difference calculation: Calculate the displacement difference X of the corresponding edges of the upper and lower end surfaces of the same aluminum slot through grayscale gradient interpolation, and take the average ΔX of the displacement differences of multiple aluminum slots;

[0033] Height measurement: Use a laser rangefinder or a three-coordinate measuring machine to measure the height H of the rotor 10;

[0034] Calculate the skew angle: skew angle θ = arctan (H / ΔX).

[0035] The image acquisition steps are as follows:

[0036] The camera's light source uses coaxial light or a ring-shaped LED light source, uniformly illuminating the end surface of the aluminum slot 11 to avoid reflection interference and enhance the contrast of straight edges. A telecentric lens is used to eliminate perspective distortion and ensure image scale accuracy. The camera's axis is perpendicular to the end surface of the rotor 10, and the camera uses a high-resolution industrial camera with greater than 5 million pixels. The image captured by the camera includes multiple continuous aluminum slots 11 and at least one buckle slot 12. Due to skew in the aluminum slots 11, when only one aluminum slot 11 is included in the image, the aluminum slot 11 patterns captured by the upper and lower cameras are likely different aluminum slots 11, not the same aluminum slot 11. Therefore, it is necessary to capture multiple aluminum slots 11 and use the buckle slot 12 as a feature point to align the multiple aluminum slots 11, ensuring that the calculated displacement difference is the displacement difference between the corresponding edges at the upper and lower ends of the same aluminum slot 11. The buckle slot 12 formed by the buckle point is not skewed and is a straight slot. The axis of the buckle slot 12 is parallel to the axis of the rotor, so the buckle slot 12 can be used as a feature point to locate the aluminum slot 11 on the upper and lower end surfaces. Furthermore, by collecting images of a plurality of continuous aluminum troughs 11 , subsequent mean value calculation can be performed to reduce the calculation error caused by a single aluminum trough 11 .

[0037] The image preprocessing steps are as follows:

[0038] The specific steps for edge enhancement of each image are as follows: converting the acquired image into a grayscale image to simplify the subsequent processing dimension; using a Gaussian filter (such as a 5×5 kernel) to smooth the image, suppress high-frequency noise interference, and avoid false detection of false edges; if the contrast between the aluminum groove 11 and the background is low, using histogram equalization (such as the CLAHE algorithm) to enhance the grayscale difference in the edge area and improve the edge significance.

[0039] When extracting multiple straight edges of aluminum grooves and buckle points, use the Sobel operator or Canny edge detection algorithm to extract the straight edges of the aluminum grooves. Perform a closing operation (first dilation and then corrosion) on the binary edge image to fill the broken areas of the aluminum groove straight edges. Apply a Laplacian filter or a custom sharpening kernel to enhance edge sharpness.

[0040] The Sobel operator is used as follows: the horizontal and vertical gradients are calculated respectively, the two-way gradients are integrated, an edge intensity map is generated, a threshold is set to filter the weak gradient response, and the straight edge feature of the aluminum groove 11 is retained.

[0041] The Canny edge detection algorithm is specifically:

[0042] Calculate image gradient: Use the Sobel operator to calculate the gradient values of the grayscale image in the horizontal and vertical directions, thereby obtaining the gradient strength and direction of each pixel;

[0043] Non-maximum suppression: For each pixel, compare the gradient values of the two adjacent pixels in the gradient direction, and only retain the pixels with the largest gradient value in the gradient direction, which helps to eliminate the blur effect on the edge;

[0044] Double threshold processing: Pixels are divided into three categories: strong edge, weak edge, and non-edge. When the gradient value of a pixel is higher than the upper threshold, it is classified as a strong edge; when the gradient value of a pixel is lower than the lower threshold, it is classified as a non-edge; when the gradient value of a pixel is between the upper and lower thresholds, it is classified as a weak edge.

[0045] Edge connection: connect weak edges with surrounding strong edges to form complete edges.

[0046] Using the buckle points as feature points, the upper and lower end face image registration is performed as follows:

[0047] Based on the annular distribution of the aluminum slots 11, each aluminum slot 11 near the buckle point is assigned a unique code, and a slot mapping table for the upper and lower end faces is established. When aligning the upper and lower end face images, the image is matched from the upper end face to the lower end face, and the same matching process is performed in reverse from the lower end face to the upper end face. A correct match is determined when the bidirectional matching results are consistent. If the matching fails three times in a row, an automatic retake process is triggered, adjusting the light source intensity or camera focus and recapturing the image. The evenly distributed annular aluminum slots 11 are used to check the consistency of the angular spacing between adjacent slots to eliminate isolated mismatches.

[0048] The specific steps for calculating the displacement difference are:

[0049] like Figure 3As shown, according to the upper and lower end surface image alignment results, the first edge 110 of the upper end surface and the second edge 111 of the lower end surface corresponding to the same aluminum groove 11 are found, the displacement difference X between the first edge 110 of the upper end surface and the second edge 111 of the lower end surface is calculated, and the average ΔX of the displacement differences of multiple aluminum grooves 11 is taken.

[0050] The rotor core skew angle detection method also includes a calibration step. Specifically, after detecting the skew angles of a preset number of rotor cores (10), a standard rotor core (10) with a known skew angle is inserted for system calibration to correct image registration drift caused by mechanical vibration or temperature changes. In this embodiment, the preset number of rotors (10) detected is 50. That is, after detecting the skew angles of 50 rotors (10), a standard rotor core (10) with a known skew angle is inserted for system calibration.

[0051] Compared with the existing technology, the rotor core skew angle detection method of the present invention collects images of the upper and lower ends of the rotor 10 respectively, each image including multiple continuous aluminum slots 11 and at least one buckle point; performs edge enhancement on each image, extracts multiple straight edges of the aluminum slots 11 and the edges of the buckle points, uses the buckle points as feature points, and performs upper and lower end face image registration; calculates the displacement difference X of the corresponding edges of the upper and lower end faces of the same aluminum slot 11 through grayscale gradient interpolation, and takes the average ΔX of the displacement differences of multiple aluminum slots; uses a laser rangefinder or a three-dimensional coordinate measuring instrument to measure the height H of the rotor 10; calculates the skew angle θ = arctan(H / ΔX), and calculates the skew angle using images collected by the upper and lower end cameras, with low measurement error, high efficiency, and convenient measurement.

[0052] The above embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patented invention. It should be noted that those skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention. These variations and improvements are equivalent modifications and improvements to the above embodiments based on the essential technology of the present invention and fall within the scope of protection of the present invention.

Claims

1. A method for detecting a rotor core skew angle, characterized in that: The following steps are involved: Image acquisition: Collect images of the upper and lower ends of the rotor respectively, each image includes multiple continuous aluminum grooves and at least one buckle point; Image preprocessing: Perform edge enhancement on each image, extract multiple straight edges of aluminum grooves and edges of buckle points, use the buckle points as feature points, and perform upper and lower end face image registration; Displacement difference calculation: Calculate the displacement difference X of the corresponding edges of the upper and lower end surfaces of the same aluminum slot through grayscale gradient interpolation, and take the average ΔX of the displacement differences of multiple aluminum slots; Height measurement: Use a laser rangefinder or a three-coordinate measuring machine to measure the rotor height H; Calculate the skew angle: skew angle θ = arctan (H / ΔX).

2. The rotor core skew angle detection method according to claim 1, characterized in that: In the image preprocessing step, the buckle point is used as a feature point to perform upper and lower end face image registration. Specifically, according to the annular distribution characteristics of the aluminum groove, a unique code is assigned to each aluminum groove near the buckle point, and a slot mapping table of the upper and lower end faces is established.

3. The rotor core skew angle detection method according to claim 2, wherein: When registering the upper and lower end face images, the images are matched from the upper end face to the lower end face, and the same matching process is performed in reverse from the lower end face to the upper end face. When the bidirectional matching results are consistent, it is determined to be a correct correspondence.

4. The rotor core skew angle detection method according to claim 3, wherein: Utilize the uniform distribution of the aluminum grooves to check whether the angle intervals of adjacent grooves are consistent and eliminate isolated mismatches.

5. The rotor core skew angle detection method according to claim 1, wherein: The rotor core skew angle detection method also includes a calibration step, which specifically includes: after detecting the skew angle of a preset rotor core each time, inserting a standard rotor core with a known skew angle to perform system calibration to correct image registration drift caused by mechanical vibration or temperature change.

6. The rotor core skew angle detection method according to claim 1, wherein: In the image acquisition step, the light source uses coaxial light or an annular LED light source to evenly illuminate the end surface of the aluminum groove to avoid reflection interference and enhance the straight edge contrast; the camera uses a telecentric lens to eliminate perspective distortion.

7. The rotor core skew angle detection method according to claim 1, wherein: The image preprocessing step further includes denoising filtering, which is located before the edge enhancement step for each image. The denoising filtering step specifically includes: using Gaussian filtering or median filtering to eliminate image noise.

8. The rotor core skew angle detection method according to claim 1, wherein: In the image acquisition step, the rotor is formed by stacking a plurality of laminations in a height direction, and the buckling points of the plurality of laminations are located on the same straight line and the straight line is parallel to the rotor axis.

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