Amplitude detection device of vibrating screening machine
By combining a tripod structure with triangulation laser ranging and image feature recognition technology, the problem of low accuracy in measuring the amplitude and frequency of the vibrating screen was solved, and high-precision vibration parameter detection was achieved.
Patent Information
- Application Number
- CN202520583777.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-31
- Publication Date
- 2026-02-03
- Estimated Expiration
- 2035-03-31
AI Technical Summary
Existing methods for measuring the amplitude and frequency of vibrating screens have low accuracy and cannot meet the growing demand for high-precision testing, especially as they are greatly affected by actual testing environmental factors.
The vibration amplitude detection device for a vibrating screen machine, which adopts a tripod structure, combines triangulation laser ranging and image feature recognition technology to achieve high-precision detection of the vibration amplitude and frequency of the vibrating screen machine through the analysis of the vibration signal of the target.
It enables high-precision measurement of the amplitude and frequency of the vibrating screen, meets the requirements of high-precision detection, and provides effective conditions for the vibration parameter control of the vibrating screen.
Smart Images
Figure CN223870186U_ABST
Abstract
Description
Technical Field
[0001] This utility model relates to the field of automatic detection technology for vibrating screen machines, specifically to a vibrating screen machine amplitude detection device. Background Technology
[0002] As the market for vibrating screens continues to expand, the demand for vibration parameter testing is also increasing. To ensure the reliability of screening results, vibration parameters need to be controlled during the screening process, and accurate detection of vibration parameters is a necessary prerequisite for achieving this control.
[0003] However, current domestic and international methods for measuring the amplitude and frequency of vibrating screens mainly rely on the binocular vision principle. These methods are subject to limitations due to objective factors such as the actual testing environment, resulting in low accuracy and failing to meet the growing demand for high-precision vibration parameter testing.
[0004] In view of this, improvements are needed to address the aforementioned deficiencies.
[0005] The information disclosed in this background section is intended only to enhance the understanding of the overall background of this utility model and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Utility Model Content
[0006] The technical problem to be solved by this utility model is to overcome the above-mentioned defects and provide a vibration amplitude detection device for a vibrating screen.
[0007] To solve the above-mentioned technical problems, the technical solution of the vibration amplitude detection device for a vibrating screen machine in this utility model is as follows:
[0008] A vibrating screen amplitude detection device includes a tripod, which includes a vertical telescopic adjustment rod. The upper end of the vertical telescopic adjustment rod is rotatably equipped with a mounting cantilever whose rotation axis extends in the vertical direction. The mounting cantilever is a telescopic cantilever structure with adjustable length. A cross slide is installed at the cantilever end of the mounting cantilever. The cross slide includes a transverse slide and a longitudinal slide arranged vertically. The longitudinal slide includes a longitudinal sliding slider that can reciprocate longitudinally under the drive of a motor. The movement direction of the longitudinal slide slider is consistent with the length extension direction of the mounting cantilever. A camera and a laser sensor are installed side by side at the bottom of the longitudinal slide slider and facing the target at the top of the vibrating screen.
[0009] Furthermore, the vertical telescopic adjustment rod includes a lower rod body and an upper rod body that telescopically cooperates with the lower rod body. The lower rod body is connected to a telescopic rod support leg, and a cantilever is installed at the top of the upper rod body.
[0010] Furthermore, a vertically oriented mounting hole is provided at the top of the upper rod section, and a mounting post is provided on the mounting cantilever that rotates and engages with the mounting hole. The mounting post is a hollow structure. A bolt is provided between the mounting cantilever and the upper rod section for fixing the mounting cantilever after rotational adjustment. The bolt includes a threaded rod that passes through the inner hole of the mounting post and a bolt head located at the lower end of the threaded rod. A washer is provided between the bolt head and the lower edge of the mounting hole. The upper end of the threaded rod protrudes from the upper side of the mounting cantilever, and a nut is threaded onto the threaded rod and connected to the upper side of the mounting cantilever.
[0011] Furthermore, the mounting cantilever includes a cantilever body and a telescopic cantilever that telescopically engages with the cantilever body along the length of the mounting cantilever. The telescopic cantilever is threaded with a tightening screw for fixing the position of the telescopic cantilever after telescopic adjustment.
[0012] In this invention, the amplitude detection device involves attaching a target to the top of a vibrating screen. The vertical telescopic adjustment rod is then adjusted according to the height of the vibrating screen, thereby adjusting the height of the mounting cantilever. Rotating the mounting cantilever moves the camera and laser sensor to the upper side of the vibrating screen. The position of the camera and laser sensor is initially adjusted by extending and retracting the telescopic cantilever. Then, a cross slide is used to fine-tune the position of the camera and laser sensor, ultimately ensuring that the camera and laser sensor face the target.
[0013] The detection method of this invention's amplitude detection device can be found in the automatic detection method for the amplitude of a vibrating screen machine described in the specific embodiments of the specification. The amplitude of the target in the vertical direction is determined by identifying the approximate maximum and minimum values of the target's vertical movement; the vibration frequency of the target in the vertical direction is determined by identifying the original signal frequency of the target's vertical vibration; the alignment quality between the camera and the target is evaluated using a preset score evaluation index to adjust the alignment; then, based on image feature recognition, the center coordinates of each horizontal vibration of the target captured by the camera are identified and recorded, ultimately determining the vibration frequency of the target in the horizontal direction. This invention achieves high-precision detection of the amplitude and frequency of the vibrating screen machine in the vertical direction, as well as its vibration frequency in the horizontal direction, providing effective conditions for subsequent analysis and adjustment, and meeting the growing demand for high-precision vibration parameter detection. Attached Figure Description
[0014] Figure 1 This is a schematic diagram of one embodiment of the vibration amplitude detection device for a vibrating screen machine according to this utility model;
[0015] Figure 2 yes Figure 1 Enlarged view of point A in the image;
[0016] Figure 3 yes Figure 1 A schematic diagram showing the interaction between the central cross slide, camera, and laser sensor;
[0017] Figure 4 This is a schematic diagram of the triangulation laser ranging principle;
[0018] Figure 5 This is a three-dimensional structural diagram of the vibration amplitude detection device for a vibrating screen provided in one embodiment of the present invention.
[0019] Figure 6 This is a flowchart illustrating a method for automatic amplitude detection of a vibrating screen machine according to one embodiment of the present invention.
[0020] Figure 7 This utility model describes the theoretical shape of the target captured by the camera when the camera's optical axis is perpendicular to the horizontal motion plane of the target.
[0021] Figure 8 This utility model describes the theoretical shape of the target captured by the camera when the camera's optical axis is not perpendicular to the horizontal motion plane of the target, or when the camera's optical axis is perpendicular to the horizontal motion plane of the target.
[0022] Figure 9 This utility model Figure 8 A schematic diagram after grayscale conversion;
[0023] Figure 10 This is a schematic diagram of the binarized RGB image of the target captured by the camera in this utility model;
[0024] Figure 11 This is a schematic diagram illustrating the calculation of the gradient in the horizontal and vertical directions of the binarized grayscale image using the Sobel operator in this invention.
[0025] Figure 12 This is a schematic diagram illustrating the gradient directions in the horizontal and vertical directions of a binarized grayscale image calculated using the Sobel operator in this invention.
[0026] Figure 13 This is the edge map obtained by traversing all pixels in the edge image in this utility model;
[0027] Figure 14 This is a schematic diagram of the alignment adjustment between the camera and the target in this utility model;
[0028] Figure 15 This is a schematic diagram of the circular template in this utility model;
[0029] Figure 16This is a schematic diagram showing the center coordinates of the target image whose local regions have the highest similarity to the template in this utility model.
[0030] Figure 17 This is a schematic diagram of the accelerated image processing method in this utility model.
[0031] Figure label:
[0032] 1. Device support frame; 2. Tripod; 3. Vibrating screen; 4. Camera; 5. Target; 6. Laser sensor; 7. Vertical telescopic adjustment rod; 7-1. Lower rod section; 7-2. Upper rod section; 8. Telescopic rod support leg; 9. Mounting cantilever; 10. Cross slide; 10-1. Horizontal slide; 10-2. Longitudinal slide; 11. Tightening screw; 12. Telescopic cantilever; 13. Cantilever body; 14. Pad; 15. Nut; 16. Bolt; 16-1. Screw; 16-2. Bolt head; 17. Mounting hole; 18. Mounting column. Detailed Implementation
[0033] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses consistent with some aspects of this disclosure as detailed in the appended claims.
[0034] As mentioned earlier, current methods for measuring the amplitude and frequency of vibrating screens, both domestically and internationally, mainly rely on the binocular vision principle. These methods are limited by objective factors such as the actual testing environment, resulting in low accuracy and failing to meet the growing demand for high-precision vibration parameter detection. To address this, this invention provides a vibrating screen amplitude detection device, solving the aforementioned problems. This invention achieves its solution through the following methods.
[0035] Example 1:
[0036] To address the aforementioned problems, this utility model provides a vibration amplitude detection device for a vibrating screen, such as... Figures 1 to 5As shown, in this embodiment, the vibration amplitude detection device of the vibrating screen includes a device support 1, a tripod 2, and a vertical telescopic adjustment rod 7. The upper end of the vertical telescopic adjustment rod 7 is rotatably equipped with a mounting cantilever 9 whose rotation axis extends in the vertical direction. The mounting cantilever 9 is a telescopic cantilever structure with adjustable length. A cross slide 10 is installed at the cantilever end of the mounting cantilever. The cross slide 10 includes a horizontal slide 10-1 and a vertical slide 10-2 arranged vertically. The vertical slide 10-2 includes a vertical sliding slider that can reciprocate vertically under the drive of a motor. The moving direction of the vertical slide slider is consistent with the length extension direction of the mounting cantilever 9. A camera 4 and a laser sensor 6 are arranged side by side and facing the target at the upper end of the vibrating screen.
[0037] The cross slide itself is existing technology. Its horizontal slide includes a horizontal slide block that can be moved and adjusted laterally, and a vertical slide is installed at the bottom of the horizontal slide block. The horizontal slide block is also driven by its own corresponding motor to achieve horizontal movement and adjustment.
[0038] The vertical telescopic adjustment rod includes a lower rod section 7-1 and an upper rod section 7-2 that telescopically engages with the lower rod section 7-1. A telescopic rod support leg 8 is connected to the lower rod section 7-1, and a cantilever arm 9 is mounted on the top of the upper rod section 7-2. The telescopic engagement between the upper rod section 7-2 and the lower rod section 7-1 is existing technology. When the height of the cantilever arm 9 needs to be adjusted, the upper rod section 7-2 can extend or retract relative to the lower rod section 7-1. After the upper rod section is adjusted, its position can be fixed using horizontally positioned tightening screws.
[0039] The top of the upper rod section has a vertically oriented mounting hole 17. A mounting post 18, which rotatably engages with the mounting hole, is provided on the mounting cantilever. The mounting post 18 is a hollow structure. A bolt 16 is provided between the mounting cantilever 9 and the upper rod section 7-2 to fix the mounting cantilever after rotational adjustment. The bolt 16 includes a threaded rod 16-1 passing through the inner hole of the mounting post and a bolt head 16-2 located at the lower end of the threaded rod. A washer 14 is provided between the bolt head 16-2 and the lower edge of the mounting hole. The upper end of the threaded rod 16-1 protrudes from the upper side of the mounting cantilever 9, and a nut 15 is threaded onto the threaded rod 16-1 and connected to the upper side of the mounting cantilever 9. In use, loosening the nut 15 allows the mounting cantilever 9 to rotate. After the mounting cantilever 9 is rotated and adjusted to the correct position, tightening the nut 15 locks the mounting cantilever in place.
[0040] The mounting cantilever includes a cantilever body 13 and a telescopic cantilever 12 that telescopically engages with the cantilever body along the length of the mounting cantilever. A tightening screw 11 is threaded onto the telescopic cantilever 12 to fix its position after telescopic adjustment. This tightening screw is vertically positioned. Loosening the tightening screw 11 allows for telescopic adjustment of the cantilever, while tightening the tightening screw 11 fixes its position.
[0041] This invention, through the aforementioned device and based on the principle of triangulation laser ranging, can directly measure the target 5 on the amplitude surface of the vibrating screen 3. The principle of triangulation laser ranging is as follows: Figure 4 As shown, the laser sensor 6 includes a photosensitive element, an emitter, and a receiving lens. When the emitter emits laser light, the laser light is reflected from the target object and then strikes the photosensitive element through the receiving lens. When the position of the target object changes, the position of the reflected laser light focused on the photosensitive element by the receiving lens also changes accordingly. Using this principle, the vertical vibration amplitude of the vibrating screen 3 can be directly measured.
[0042] The automatic detection method for the amplitude of a vibrating screen using this vibrating screen amplitude detection device includes the following steps:
[0043] S100. According to the time sequence, obtain the measured value of the distance between the laser sensor 6 and the target 5.
[0044] S200. Based on the measured values, determine the approximate maximum and minimum values of the vertical movement of the target 5, and determine the amplitude of the target 5 in the vertical direction according to the approximate maximum and minimum values.
[0045] S300. Based on the measured value, determine the original signal frequency of the target 5 vibrating in the vertical direction, and determine the vibration frequency of the target 5 in the vertical direction according to the original signal frequency.
[0046] S400: Based on the RGB image of the target 5 captured by the camera 4, and using a preset score evaluation index, evaluate the alignment quality of the camera 4 and the target 5, and adjust the alignment of the camera 4 and the target 5.
[0047] S500: Based on image feature recognition, identify and record the center coordinates of the horizontal vibration of the target 5 captured by the camera 4 each time, and determine the vibration frequency of the target 5 in the horizontal direction based on the center coordinates.
[0048] S600: Analyze the amplitude and frequency of the target 5 in the vertical direction and the frequency of the target 5 in the horizontal direction to improve the accuracy of vibration parameter detection of the vibrating screen.
[0049] The method described in this invention can accurately measure the amplitude and frequency of the target in the vertical direction, as well as the amplitude in the horizontal direction, on the vibrating screen 3 using a laser sensor 6 and a camera 4. This meets the growing demand for high-precision vibration parameter detection.
[0050] Example 3:
[0051] Based on Embodiment 2, in order to provide a clearer and more complete description of the technical solution therein, this utility model also provides Embodiment 3. For example... Figures 7 to 17 As shown, in Embodiment 3, step S200 further includes:
[0052] S210. Based on the acquired measurement values, determine an approximate zero point.
[0053] For example, in this third embodiment, starting from time 0, the distance between the amplitude plane of the target 5 and the measuring device is measured at several time points using the laser sensor 6, and the measurements are continuously recorded. Data regarding time is obtained, as shown in the following formula:
[0054] (1)
[0055] (2)
[0056] in, Representing several moments, The defined value representing the distance between the amplitude plane where the target 5 is located and the measuring device 1 is denoted as The set of the measured values obtained above is recorded as . .
[0057] In this third embodiment, for The arithmetic mean is calculated as follows:
[0058] (3)
[0059] in, for The calculated arithmetic mean is also close to The value of zero is used Subtract each item That is, we get:
[0060] (4)
[0061] in, Let represent the measured value at the i-th moment of the distance between the amplitude plane where target 5 is located and the measuring device 1. Let be the variance value at time i.
[0062] Set a sufficiently small ,when At that time, it was believed that For the set of measured values An approximate zero point.
[0063] S220. Based on the determined approximate zero point, determine the peaks and troughs between two adjacent approximate zero points.
[0064] For example, and continuing from the above example, in this third embodiment, based on the above-obtained... An approximate zero point, obtaining a set of measurement values. All approximate zeros, i.e. Therefore, there must be a peak or trough between two adjacent zeros.
[0065] S230. Based on the peaks and troughs between two adjacent approximate zero points, determine the approximate maximum and minimum values of the vertical vibration of target 5.
[0066] For example, and continuing from the above example, in this third embodiment, the set of measured values... For each approximate zero point in sequence , To the next adjacent approximate zero , Sum of all measurements between, denoted as As shown in the following formula:
[0067] (5)
[0068] (6)
[0069] like Then it is considered to be approximately zero. To the next adjacent approximate zero There are peaks between them, find arrive The maximum value between them is used as the measurement value. An approximate maximum value, denoted as As shown in the following formula:
[0070] (7)
[0071] like Then it is considered to be approximately zero. Next adjacent approximate zero There are troughs between them. Find... arrive The minimum value between is used as the measured value An approximate minimum value of is denoted as . As shown in the following formula:
[0072] (8)
[0073] S240. Based on the obtained approximate maximum and approximate minimum values, determine the amplitude of target 5 in the vertical direction.
[0074] For example, and continuing from the above example, in this third embodiment, for the obtained... Approximate maximum values and Calculate the arithmetic mean of the approximate minimum values, where ,get , As shown in the following formula:
[0075] (9)
[0076] (10)
[0077] in, It is the maximum approximate maximum value. It is the minimum approximate minimum value.
[0078] The vertical amplitude is then expressed as follows:
[0079] (11)
[0080] For example, in Embodiment 3, S300 may include:
[0081] The set of measurement values measured by laser sensor 6 The Discrete Fourier Transform (DFT) is performed, and the transformation formula is shown below:
[0082] (12)
[0083] It is a length of The discrete time series, i.e., the measurements from the laser sensor. , It is the frequency domain sequence after DFT transformation. It is a frequency index, with a value range of 100%. .
[0084] for Calculate separately The result of the DFT transformation of the original sensor measurements is shown in the following formula:
[0085] (13)
[0086] Among them, the frequency corresponding to the DFT coefficient with the largest amplitude is the main frequency component of the signal, and the original signal frequency can be approximated by the main frequency, as shown in the following formula:
[0087] (14)
[0088] The original signal's main frequency is shown in the following formula:
[0089] (15)
[0090] in, It is the index of the DFT coefficient with the largest amplitude. The length of the sequence after DFT transformation. It is the sampling frequency of the original signal, i.e. , This represents the sampling time interval for the laser sensor.
[0091] Will Multiply by 60 to get the number of vertical vibrations per minute. As shown in the following formula:
[0092] (16)
[0093] Horizontal displacement and frequency are measured using camera 4. Camera 4 requires the assistance of target 5; this invention uses a circular target, such as... Figure 7 As shown, during measurement, to facilitate subsequent calculations, the optical axis of camera 4 needs to be perpendicular to the horizontal motion plane of target 5. Therefore, an alignment score evaluation index is proposed to evaluate the alignment quality and ensure the alignment effect. Its principle is as follows:
[0094] When the optical axis of camera 4 is perpendicular to the horizontal motion plane of target 5, the theoretical shape of target 5 captured by camera 4 is a perfect circle, such as... Figure 7 As shown. When the optical axis of camera 4 is not perpendicular to the horizontal motion plane of target 5, the theoretical shape of the target captured by the camera is an ellipse, as shown. Figure 8 As shown.
[0095] Therefore, in embodiment three, S400 may further include:
[0096] S410. Preprocess the RGB image to convert it into a grayscale image;
[0097] For example, and continuing from the previous example, in this third embodiment, an RGB image captured by a camera can be converted into a grayscale image. Each pixel in a grayscale image has only one value representing brightness, typically represented by one byte (e.g., 8 bits), with a value range from 0 (black) to 255 (white). The most commonly used method is the weighted average method, which assigns different weights to each color channel based on the human eye's sensitivity to different colors. As shown in the following formula:
[0098] (17)
[0099] in, This represents the pixel value after grayscale conversion. , , These are the pixel values in the red, green, and blue channels of the corresponding pixels in the original image. Figure 8 After grayscale conversion, as Figure 9 As shown.
[0100] S420: Based on the Canny edge detection algorithm, a Gaussian filter is used to smooth the grayscale image;
[0101] For example, and continuing from the above example, in this third embodiment, a binarization method can be used to process the image: First, a threshold is set (based on the threshold set in this experimental paper) to distinguish between the black circular target and the white background. A new image of the same size as the original image is created, denoted as binary_image. Each pixel of the grayscale image is compared with the manually set threshold. If the grayscale value of a pixel in the original image is less than the set threshold, the grayscale value of that pixel in the new image is set to 1; otherwise, it is set to 0. The specific formula is as follows:
[0102] (18)
[0103] Compare each pixel of the entire image sequentially with the set threshold. By comparing and recording the results, a binarized image can be obtained. For example... Figure 10 As shown.
[0104] S430. Use the Sobel operator to calculate the gradient values of the binarized grayscale image in the horizontal and vertical directions, and calculate the gradient image based on the obtained gradient values.
[0105] For example, and continuing from the above example, in this third embodiment, after obtaining the binarized image, the Sobel operator can be used to calculate the gradient values of the binarized grayscale image in the horizontal and vertical directions. Its horizontal gradient convolution kernel... and vertical gradient convolution kernel The following formulas are shown respectively:
[0106] (19)
[0107] (20)
[0108] The specific calculation formula is as follows:
[0109] (twenty one)
[0110] (twenty two)
[0111] Obtain the horizontal gradient and vertical gradient The gradient magnitude for each pixel is then calculated, as shown in the following formula:
[0112] (twenty three)
[0113] The gradient direction is shown in the following equation:
[0114] (twenty four)
[0115] The calculated gradient image is as follows Figure 11 As shown.
[0116] S440: Refine the edges of the gradient image to obtain edge coordinates. In this embodiment three, S440 may further include: S441: Perform non-maximum suppression and double threshold detection on the edges of the gradient image to classify edge pixels;
[0117] For example, and continuing from the previous example, in this third embodiment, after obtaining the gradient image and magnifying it, it was found that the image edges were rather cluttered. To further refine the edges and improve the accuracy of edge detection, non-maximum suppression, dual threshold detection pairs, and edge connectivity are also required.
[0118] Non-maximum suppression refers to comparing the gradient values of each pixel with those of its neighboring pixels along the gradient direction, and retaining only the pixels with the largest gradient values along the gradient direction, which helps to eliminate blurring effects on edges.
[0119] In practical applications, starting from a certain pixel along the gradient direction, there may not be a true pixel, but rather a sub-pixel, such as... Figure 12As shown in the diagram. Pixels 1-9 are actual pixels, and A and B are sub-pixels. At this point, the gradient direction is used to select neighboring pixels for comparison. Assume the gradient direction is represented by angles, ranging from 0° to 360°. Typically, the gradient direction is quantized into several main directions (e.g., 0°, 45°, 90°, 135°) for processing. Based on the gradient direction, neighboring pixels are selected for comparison. If the gradient direction is 0° (horizontal), the pixels to the left and right of the current pixel are compared. If the gradient direction is 90° (vertical), the pixels to the top and bottom of the current pixel are compared. If the gradient direction is 45° or 135°, the pixels along the diagonal are compared. If the gradient magnitude of the current pixel is a local maximum in its direction, the gradient magnitude of that pixel is retained; otherwise, its gradient magnitude is set to 0. The specific formula is shown below:
[0120] (25)
[0121] in , These are the offsets in the gradient direction, respectively.
[0122] Dual threshold processing utilizes two thresholds, a higher threshold and a lower threshold. and low threshold The edges are divided into strong edge points, weak edge points, and non-edge points. If the gradient value of a pixel is greater than a high threshold... If the gradient value of a pixel is less than the high threshold, then the pixel is considered a strong edge point; And greater than the low threshold If the gradient value of a pixel is less than the low threshold, then the pixel is considered a weak edge point. Therefore, the pixel is considered not an edge point. The mathematical formula is:
[0123] (26)
[0124] S442. Perform edge connection on the classified edge pixels to obtain an edge map.
[0125] S443. Traverse all pixels in the edge image to obtain the edge coordinates.
[0126] For example, and continuing from the previous example, in this third embodiment, after classifying the edge pixels, edge connection is also required. An edge map of the same size as the original image, with all pixels initially set to 0, is created to store the final edge detection results. All pixels considered strong edges are set to 1 (marked as edges). Starting from the strong edge, adjacent edge points are checked. If a weak edge exists among the adjacent pixels, these weak edge points are connected to the strong edge and also marked as edges in the edge map. If a weak edge is not connected to any strong edge, it is discarded, because an isolated weak edge without strong edge support is likely noise or an unrealistic edge. This process is repeated until all edge points have been traversed to obtain a more accurate edge map. Figure 13 As shown.
[0127] S450. Convert the acquired edge coordinates to coordinates in the XY coordinate system;
[0128] For example, and continuing from the previous example, in this third embodiment, all pixels in the edge image can be traversed, and pixels with a value of 1 represent the edges of the image. The edge coordinates can then be obtained. The edge coordinates obtained at this time These are coordinates in the RC (row and column) coordinate system. For ease of subsequent calculations, they need to be converted to coordinates in the XY coordinate system. The specific conversion formula is as follows:
[0129] (27)
[0130] in This represents the number of rows (height) in the edge image matrix.
[0131] S460. Perform circle fitting on the transformed coordinates and calculate the fitting error;
[0132] S470. Based on the calculated fitting error, calculate the alignment score to determine the alignment status.
[0133] For example, and continuing from the above example, in this third embodiment, the converted... Group The coordinates are used for circle fitting, and the fitting error is calculated. The least squares method is used for circle fitting, and the specific steps are as follows:
[0134] Let the coordinates of the center of the fitted circle be... , radius is
[0135] The least squares error function is then:
[0136] (28)
[0137] The optimal solution of the error function is obtained using the gradient descent method.
[0138] The average of all edge coordinates is used as the initial value for the iteration of the center coordinates. ,right and The range and then the average of the coordinate values of each direction are used as the initial value for the radius iteration. .
[0139] Error functions respectively for , , Taking the partial derivative, we get , ,
[0140] but:
[0141] (29)
[0142] (30)
[0143] (31)
[0144] in The iteration step size is used to control the magnitude of the update.
[0145] The iterative result is ( and Repeat the above steps as a new initial value for iteration until the error function is small enough; or set the number of iterations and stop iterating after reaching the specified number.
[0146] At this point, the coordinates of the center of the fitted circle can be obtained. and .
[0147] Then the fitting error is:
[0148] (32)
[0149] This is the sum of the squares of the radial distances from all actual measurement points to the fitted circle.
[0150] Alignment score:
[0151] (33)
[0152] When the image captured by the timing camera is aligned, it should be a perfect circle; at this point, the fitting error... Approaching 0, aligned scores Tend to When the camera is not aligned, the fitting error... Non-zero, aligned score The camera's alignment can be determined based on the alignment score.
[0153] Considering the complexity of actual measurement environments, if the scores are aligned... If the value is greater than the threshold, it is considered positive.
[0154] If it is not aligned, it needs to be adjusted. Micro stage, such as Figure 14 As shown, the measuring device can rotate along the blue line. After adjustment, perform the alignment check again until it is aligned.
[0155] In embodiment three, S500 may further include:
[0156] S510, Obtain the ratio between each pixel and its corresponding physical distance.
[0157] S510 may further include:
[0158] S511 obtains the true radius of target 5 and determines the pixel radius of target 5 based on the obtained true radius.
[0159] Based on the obtained pixel radius and true radius of target 5, S512 determines the ratio between each pixel and the corresponding physical distance.
[0160] For example, and continuing from the above example, in Embodiment 3, after the camera aligns with the horizontal moving plane of the target, it is necessary to calculate the physical distance corresponding to each pixel in the image captured by the camera under the current measurement state. The pixel radius of the target, in pixels, can be obtained from the circle fitted in the previous step. The true radius of the target can be obtained through prior measurement. The ratio between each pixel and its corresponding physical distance can be calculated, as shown in the following formula:
[0161] (34)
[0162] S520. Based on the ratio between each acquired pixel and the corresponding physical distance, determine the specific location of the target 5 in the RGB image captured by the camera 4 during the horizontal vibration of the target 5.
[0163] In embodiment three, S520 may further include:
[0164] S522. Based on a pre-created circular template similar to the target 5, determine the similarity between the circular template and a local region of the RGB image captured by the camera 4.
[0165] For example, and continuing from the above example, in Embodiment 3, the similarity between the template and the local region of the image captured by the camera is obtained by means of normalized cross-correlation. The mathematical formula for normalized cross-correlation is expressed as follows:
[0166] (35)
[0167] in, This is a template, and its size is [size missing]. , For the target image, It refers to a local region in the target image that is aligned with the template. (Molecule) It's a template. Local regions of the target image The sum of the pixel-by-pixel differences measures the correlation between templates and their local regions. The denominator is... It is the variance of a local region of the target image. This represents the variance of the template. Normalization of the denominator ensures that the matching results are unaffected by changes in image brightness and contrast.
[0168] S523. Based on the pixel coordinates of the local region with the highest similarity, determine the center coordinates of the target 5RGB image where the local region is located;
[0169] For example, and continuing from the above example, in Embodiment 3, the similarity between each local region of the target image and the template can be calculated sequentially, and the pixel coordinates of the local region with the highest similarity can be output. The matching result is as follows: Figure 15 As shown. Record the coordinates of the circle's center.
[0170] A series of center pixel coordinates for time were obtained by continuously taking pictures and calculating them:
[0171] (36)
[0172] (37)
[0173] (38)
[0174] S524. Based on the determined center coordinates, determine the radius of rotation of the target RGB image in the horizontal direction, and based on this radius of rotation, determine the true radius of rotation of target 5.
[0175] S525. Based on the determined true radius of rotation, determine the vibration frequency of target 5 in the horizontal direction.
[0176] S530. Based on the specific location collected, record the center of the target circle at that location;
[0177] S540. Based on the coordinates of the center of the circle, determine the vibration frequency of the target 5 in the horizontal direction.
[0178] For example, and continuing from the above example, in Embodiment 3, the measured... The radius of gyration can be calculated from the coordinates, using the following formula:
[0179] Let the equation of the circular motion at the center of the target be:
[0180] (39)
[0181] Right now:
[0182] (40)
[0183] make:
[0184] (41)
[0185] We can obtain:
[0186] (42)
[0187] Solve for parameters The coordinates of the center of the circle can then be obtained. and radius .
[0188] in,
[0189] (43)
[0190] The sample points obtained by measurement ( Distance to the center of the circle:
[0191] (44)
[0192] The difference between it and the sum of squares of the fitted radii:
[0193] (45)
[0194] make for The sum of squares, then:
[0195] (46)
[0196] Solving makes When taking the minimum value, the parameter The value of can be used to determine the coordinates of the center and radius of the fitted circle. .
[0197] The true radius of gyration is equal to the fitted radius of gyration multiplied by the scale. The formula is expressed as follows:
[0198] (47)
[0199] The measured results and The horizontal rotation frequency can be obtained by performing a Discrete Fourier Transform (DFT) and taking the arithmetic mean. Multiplying this by 60 gives the number of horizontal vibrations per minute. The specific calculation method is as follows:
[0200] The calculated series of geometric centers coordinates and The coordinates are subjected to Discrete Fourier Transform (DFT) respectively, and the transformation formula is as follows:
[0201] (48)
[0202] in, It is a length of The discrete-time series, i.e., the geometric center, is obtained. coordinates or coordinate , It is the frequency domain sequence after DFT transformation. It is a frequency index, with a value range of 100%. .
[0203] for Calculate separately The result of the original sequence after DFT transformation is:
[0204] (49)
[0205] Among them, the frequency corresponding to the DFT coefficient with the largest amplitude is the main frequency component of the signal, and the main frequency can be used to approximate the original signal frequency.
[0206] (50)
[0207] Original signal main frequency:
[0208] (51)
[0209] in, It is the index of the DFT coefficient with the largest amplitude. The length of the sequence after DFT transformation. It is the sampling frequency of the original signal, that is, the shooting frequency of the camera.
[0210] Calculate separately coordinates and Coordinate frequency and By calculating the arithmetic mean, the horizontal vibration frequency can be obtained. .
[0211] (52)
[0212] Will Multiply by 60 to get the number of horizontal vibrations per minute.
[0213] (53)
[0214] In embodiment three, S520 may further include:
[0215] S521 employs pyramid technology, which constructs a pyramid structure by downsampling and reducing the size of the RGB image and proportionally reducing the size of the circular template. The position is then mapped frame by frame at the top of the pyramid, gradually refining the position of the target object in the original image and improving image processing speed.
[0216] For example, and continuing from the above example, in Embodiment 3, when analyzing the images captured by the camera, considering that the original images are large and frame-by-frame searching is slow, a pyramid technique is used to accelerate the process. First, the image is gradually reduced in size through sampling. Assuming the original image's pixel value is... The pixel value after average pooling is:
[0217] (54)
[0218] in This is the size (side length) of the pooling window. and These are the local coordinates within the pooling window.
[0219] Simultaneously, the template is scaled down proportionally to construct a pyramid structure. When the image is sufficiently small, a frame-by-frame search is performed at the top of the pyramid. Then, based on the positional correspondence between pixels in each layer of the pyramid, the positions obtained from the search in the upper layer are mapped to the lower layer. This limits the search range of the lower layer to a local area composed of a small number of pixels, allowing for a further search of the lower layer to pinpoint the exact location of the target object. This process continues until the bottom of the pyramid is reached, obtaining the location of the target object in the original image, thus completing the segmentation. Specific image processing methods are as follows: Figure 16 As shown.
[0220] In the foregoing description of this specification, unless otherwise expressly specified and limited, the terms "fixed," "installed," "connected," or "linked" should be interpreted broadly. For example, the term "linked" can refer to a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; or it can refer to the internal communication of two components or the interaction between two components. Therefore, unless otherwise expressly limited in this specification, those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.
[0221] Based on the above description in this specification, those skilled in the art will also understand that terms used, such as "upper," "lower," "front," "rear," "left," "right," "length," "width," "thickness," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," "circumferential," "center," "longitudinal," "transverse," "clockwise," or "counterclockwise," are terms indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings of this specification. They are only for the purpose of facilitating the explanation of the present invention and simplifying the description, and do not imply that the devices or elements involved must have the specific orientation, or be constructed and operated in a specific orientation. Therefore, the above-mentioned orientation or positional relationship terms should not be understood or interpreted as limitations on the present invention.
[0222] Furthermore, the terms "first" or "second," etc., used in this specification to refer to numbers or ordinal numbers are for descriptive purposes only and should not be construed as indicating, explicitly or implicitly, relative importance or specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this specification, "a plurality of" means at least two, such as two, three, or more, unless otherwise explicitly specified.
[0223] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A vibrating screen amplitude detection device, characterized in that, The system includes a tripod, which includes a vertical telescopic adjustment rod. The upper end of the vertical telescopic adjustment rod is rotatably fitted with a mounting cantilever whose rotation axis extends vertically. The mounting cantilever is a telescopic cantilever structure with adjustable length. A cross slide is installed at the extended end of the mounting cantilever. The cross slide includes a horizontal slide and a vertical slide, which are arranged vertically. The vertical slide includes a vertical sliding block that can reciprocate vertically under the drive of a motor. The movement direction of the vertical slide block is consistent with the length extension direction of the mounting cantilever. A camera and a laser sensor are installed side by side at the bottom of the vertical slide block and facing the target at the top of the vibrating screen.
2. The vibration amplitude detection device for a vibrating screen as described in claim 1, characterized in that: The vertical telescopic adjustment rod includes a lower rod body and an upper rod body that telescopically cooperates with the lower rod body. The lower rod body is connected to a telescopic rod support leg, and the mounting arm is installed at the top of the upper rod body.
3. The vibration amplitude detection device for a vibrating screen as described in claim 2, characterized in that, The top of the upper rod section is provided with a vertically arranged mounting hole. The mounting cantilever is provided with a mounting post that rotates and engages with the mounting hole. The mounting post is a hollow structure. A bolt is provided between the mounting cantilever and the upper rod section for fixing the mounting cantilever after rotational adjustment. The bolt includes a threaded rod that passes through the inner hole of the mounting post and a bolt head located at the lower end of the threaded rod. A washer is provided between the bolt head and the lower edge of the mounting hole. The upper end of the threaded rod protrudes from the upper side of the mounting cantilever. A nut is threaded onto the threaded rod and connected to the upper side of the mounting cantilever.
4. The vibration amplitude detection device for a vibrating screen as described in claim 3, characterized in that: The mounting cantilever includes a cantilever body and a telescopic cantilever that telescopically engages with the cantilever body along the length of the mounting cantilever. The telescopic cantilever is threaded with a tightening screw for fixing the position of the telescopic cantilever after telescopic adjustment.