A method for cutting meat into a predetermined weight and shape

Abstract

The present application belongs to the technical field of food processing, and particularly relates to a meat weight setting and shape setting cutting method. The method collects meat contour data through a 3D camera, calculates the total weight in combination with a preset average density; converts 3D point cloud data into a 2D projection image, determines a maximum inscribed rectangle through a rotation matrix iteration of a rotation angle; adjusts the size of a cutting frame according to a preset specification, calculates the weight after cutting in combination with height, length and step length, and optimizes according to a duty cycle dynamic frame shrinking; and finally, a motion controller drives a cutting head to complete automatic cutting in combination with a conveyor belt encoder position. The present application realizes precise and efficient cutting of meat weight setting and shape setting, improves raw material utilization and automation, and is suitable for diversified product specification requirements.

Description

Technical Field

[0001] This invention belongs to the field of food processing technology, and in particular relates to a method for cutting meat to a fixed weight and shape. Background Technology

[0002] In the meat and poultry food processing industry, weight- and shape-based cutting is a crucial step in ensuring product standardization and improving production efficiency. Traditional cutting methods rely heavily on manual operation or semi-automated equipment, which has the following significant drawbacks: First, the cutting accuracy is low, making it difficult to simultaneously meet the dual specifications of finished product weight and shape (length, width, diameter, etc.), resulting in poor product consistency; second, the raw material utilization rate is low, and manual judgment of the cutting path easily generates excessive waste, increasing production costs; third, the degree of automation is insufficient, relying on manual adjustment of cutting parameters, resulting in poor flexibility when adapting to different product specifications, and limiting production efficiency. Summary of the Invention

[0003] In view of the technical problems existing in the background art, the present invention proposes a method for fixed-weight and fixed-shape cutting of meat.

[0004] To achieve the above objectives, the technical solution adopted by the present invention includes the following steps:

[0005] S1. First, the outline data of meat products is collected using a 3D camera;

[0006] S2. Calculate the total weight of the collected meat products based on the predicted average density;

[0007] S3. Preset product specifications, including finished product weight, length, width, and diameter;

[0008] S4. Process the acquired 3D scanned images and convert the 3D point cloud data into 2D image data using an algorithm;

[0009] S5. Calculate the cutting parameters for the obtained 2D image data, including determining the maximum inscribed rectangle, determining the cutting frame size, calculating the weight after cutting, and adjusting the cutting frame.

[0010] Determine the maximum inscribed rectangle: Used to find the maximum rectangular range of the product to fit on a 2D projected image by matrix rotation;

[0011] Determine the dimensions of the cutting frame: Based on the preset specifications, determine the length, width, and vertex position of the cutting frame through coordinate adjustment to meet the shape requirements;

[0012] Calculate the weight after cutting: This is used to combine the height, length, and step length to calculate the weight of the finished product after cutting, ensuring that it meets the weight specifications.

[0013] Adjust the cutting frame: This is used to reduce the blank area by shrinking the frame according to the duty cycle, thereby improving the utilization rate of raw materials while meeting the requirements.

[0014] S6. After receiving the cutting parameters, the motion controller calculates the starting and ending coordinates of the cutting head by combining the encoder position of the conveyor belt, and completes the automatic cutting.

[0015] Preferably, in step S4, the 3D scanned image is processed and the 3D point cloud data is converted into 2D image data by an algorithm. This is achieved by first projecting the 3D scanned image from 3D to 2D, and then projecting the 3D point cloud data onto a two-dimensional plane to form a 2D projected image.

[0016] Preferably, the determination of the maximum inscribed rectangle in step S5 is achieved by converting the 3D image projection into a 2D image, and then determining the maximum inscribed rectangle on the projected image based on matrix relationships through image rotation. The rotation process uses the rotation matrix HomMat2DRotat and the identity matrix HomMat2D, specifically as follows:

[0017] First, rotate the 2D projected image to a suitable angle using a rotation matrix. The maximum inscribed rectangle at that angle is determined, and then the material is rotated back to its original orientation using the identity matrix HomMat2D. The cutting frame rotates synchronously with the material to maintain consistent relative positions. The rotation matrix HomMat2DRotat is calculated as follows: ,in It is a two-dimensional rotation transformation matrix.

[0018] Preferably, the rotation angle The traversal interval is and with rotation angle step size Perform a traversal and calculate the area of ​​the largest inscribed rectangle.

[0019] Preferably, in step S5, the dimensions of the cutting frame are determined by adjusting the coordinates according to preset specifications to determine the length, width, and vertex position of the cutting frame, thereby satisfying the shape requirements.

[0020] First, set the scaling step, then calculate the coordinates of the cut box vertices after adjustment: , ; , ; Length of the cutting frame ,width ;in, These are the coordinates of the original bounding box vertices.

[0021] Next, calculate the coordinates of the four vertices of the cutting box:

[0022] Vertex 1 is ,

[0023] ;

[0024] Vertex 2 is ,

[0025] ;

[0026] Vertex 3 is ,

[0027] ;

[0028] Vertex 4 is ,

[0029] ;in, Center point of the cutting frame coordinate, Center point of the cutting frame coordinate.

[0030] Preferably, the method for calculating the weight after cutting in step S5 is as follows: ,in, For height, For length.

[0031] Preferably, in step S5, adjusting the cutting frame involves, after determining the size of the cutting frame, detecting whether there is any blank area within the cutting frame. If blank area exists and the duty cycle is greater than a set threshold, then frame reduction processing will be performed. The duty cycle is calculated as follows: ,in Expressed as duty cycle, The area of ​​the blank region. The area of ​​the entire rectangular region must satisfy the duty cycle within the weight limit. It is the minimum value.

[0032] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0033] 1. By traversing the rotation angle through a rotation matrix to determine the maximum inscribed rectangle, and combining it with 2D projection processing, the cutting area is accurately located, improving the adaptability of irregular meat pieces.

[0034] 2. The cutting frame is dynamically adjusted based on the duty cycle, and the blank area is reduced by shrinking the frame, which significantly improves the utilization rate of raw materials and reduces the waste rate. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 A schematic diagram of the structural process of a method for cutting meat to a fixed weight and shape. Detailed Implementation

[0037] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0038] Numerous specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways than those described herein, and therefore the invention is not limited to the specific embodiments disclosed in the following specification.

[0039] In the meat and poultry food processing industry, fixed-weight and fixed-shape cutting is a key step in ensuring product standardization and improving production efficiency. Traditional cutting methods rely heavily on manual operation or semi-automated equipment, resulting in insufficient precision and low raw material utilization. To address these issues, this invention proposes a fixed-weight and fixed-shape cutting method for meat, the specific implementation process of which is as follows: Figure 1 As shown, to accurately measure the volume of the raw materials and thus accurately estimate their weight, the product's contour data is collected by a 3D camera on a conveyor belt. Then, the total weight of the collected meat product is calculated using the measured average density. Specifically, the cut meat sample is placed on a specially designed conveyor belt, and a high-precision 3D structured light camera mounted above the conveyor belt scans the sample from multiple angles. The camera continuously collects point cloud data on the sample surface along a preset trajectory, generating a set of millions of 3D coordinate points. Subsequently, the point cloud is filtered, registered, and the closed surface is reconstructed within the computing unit to build an accurate mesh model and calculate the total volume. Based on the pre-calibrated average density, the total weight of the sample is obtained by multiplying the average density by the total volume.

[0040] The product specifications are preset, including finished product weight, length, width, and diameter. Then, the acquired 3D scanned images are processed, converting the 3D point cloud data into 2D image data using an algorithm. This conversion involves first projecting the 3D scanned images from 3D to 2D onto a two-dimensional plane to form a 2D projected image. Specifically, when processing the acquired 3D scanned images, the original point cloud data is first preprocessed, including noise filtering and point cloud registration, to ensure data integrity and continuity. Then, a projection plane is selected, and the 3D point set is mapped to a two-dimensional coordinate system according to perspective or orthogonal projection, generating the pixel coordinates of each point. Next, the pixel plane is meshed, and the projected points are projected into the pixel grid at a predetermined resolution and assigned grayscale or binarization processing, ultimately obtaining a 2D projected image that accurately reflects the material's outline. This projection method preserves the geometric features of the 3D structure and transforms subsequent image-based cutting parameter calculations into efficient two-dimensional matrix operations, laying the foundation for maximum inscribed rectangle detection and cutting box optimization.

[0041] The obtained 2D image data is used to calculate cutting parameters, including determining the maximum inscribed rectangle, determining the cutting frame size, calculating the weight after cutting, and adjusting the cutting frame.

[0042] The determination of the maximum inscribed rectangle is used to find the maximum rectangular range suitable for the product on the 2D projected image through matrix rotation. Specifically, after converting the 3D image projection into a 2D image, the maximum inscribed rectangle is determined on the projected image by rotating the image based on matrix relationships. The rotation process uses the rotation matrix HomMat2DRotat and the identity matrix HomMat2D. Specifically, the 2D projected image is first rotated to a suitable angle using the rotation matrix. The maximum inscribed rectangle at that angle is determined, and then the material is rotated back to its original orientation using the identity matrix HomMat2D. The cutting frame rotates synchronously with the material to maintain consistent relative positions. The rotation matrix HomMat2DRotat is calculated as follows: ,in This is a two-dimensional rotation transformation matrix. Where the rotation angle is... The traversal interval is and with rotation angle step size The process involves iterating through the image to find the area of ​​the largest inscribed rectangle. After each rotation, the minimum bounding rectangle algorithm is used to quickly calculate the current bounding rectangle. After traversing all angles, the rectangle with the largest area is selected, and its vertex coordinates are restored to the original image coordinate system through a reverse rotation. This rectangle is the largest inscribed rectangle, which completely contains the outline and closely matches the material orientation, providing an initial framework for subsequent cutting box optimization. This method balances computational efficiency and accuracy; by adjusting the step size, the traversal can be completed in a short time, ensuring consistency between the optimal rectangle orientation and the maximum utilized area.

[0043] Determining the cutting frame size involves adjusting the coordinates of the cutting frame according to preset specifications to meet shape requirements. Specifically, based on the obtained maximum inscribed rectangle, the next step is to adjust the cutting frame size according to the target dimensions. First, a scaling step is set, and the adjusted vertex coordinates of the cutting frame are calculated. , ; , ; Length of the cutting frame ,width ;in, Given the original frame vertex coordinates, calculate the coordinates of the four vertices of the cut frame: Vertex 1 is... , Vertex 2 is , Vertex 3 is , Vertex 4 is , ;in, Center point of the cutting frame coordinate, Center point of the cutting frame coordinate.

[0044] Next, the weight after cutting is calculated. This calculation, taking into account height, length, and step length, yields the final weight of the finished product, ensuring it meets weight specifications. Specifically, the method for calculating the weight after cutting is as follows: ,in, For height, For length.

[0045] Considering that while ensuring weight and shape specifications are met, frame reduction is also necessary to maximize material utilization and reduce blank waste, the cutting frame is adjusted to reduce blank area based on the duty cycle, thereby improving material utilization while meeting requirements. Specifically, after determining the cutting frame size, the presence of blank area within the cutting frame is detected. If blank area exists and the duty cycle is greater than a set threshold, frame reduction is performed. The duty cycle is calculated as follows: ,in Expressed as duty cycle, The area of ​​the blank region. The area of ​​the entire rectangular region, within the limits of weight and shape specifications, must also satisfy the duty cycle. It is the minimum value.

[0046] Based on the calculated cutting parameters, the motion controller receives the parameters and, in conjunction with the encoder position of the conveyor belt, calculates the starting and ending coordinates of the cutting head to complete the automatic cutting. Specifically, after receiving the calculated cutting parameters, the motion controller first maps the vertex coordinates of the cutting frame from the image coordinate system to the actual physical coordinate system through a preset coordinate transformation relationship, determining the relative position of the cutting path in space. Simultaneously, the motion controller reads the pulse signals fed back by the conveyor belt encoder in real time, calculates the real-time displacement of the conveyor belt based on the encoder's pulse equivalent (the distance the conveyor belt moves per pulse), and thus obtains the current physical position of the meat piece on the conveyor line. By matching the relative position of the cutting path with the real-time physical position of the meat piece, the motion controller accurately calculates the starting and ending coordinates of the cutting head. When the meat piece moves with the conveyor belt to the starting cutting position, the motion controller drives the cutting head to move along the calculated path, synchronously compensating for the conveyor belt's running speed to ensure that the cutting head and the meat piece remain relatively stationary during the cutting process. After completing the cutting, the cutting head resets, awaiting the next cutting command.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for cutting meat to a fixed weight and shape, characterized in that, Includes the following steps: S1. First, the outline data of meat products is collected using a 3D camera; S2. Calculate the total weight of the collected meat products based on the preset average density; S3. Preset product specifications, including finished product weight, length, width and diameter; S4. Process the acquired 3D scanned images and convert the 3D point cloud data into 2D image data using an algorithm; S5. Calculate the cutting parameters for the obtained 2D image data, including determining the maximum inscribed rectangle, determining the cutting frame size, calculating the weight after cutting, and adjusting the cutting frame. Determine the maximum inscribed rectangle: Used to find the maximum rectangular range of the product to fit on a 2D projected image by matrix rotation; Determine the dimensions of the cutting frame: Based on the preset specifications, determine the length, width, and vertex position of the cutting frame through coordinate adjustment to meet the shape requirements; Calculate the weight after cutting: This is used to combine the height, length, and step length to calculate the weight of the finished product after cutting, ensuring that it meets the weight specifications. Adjust the cutting frame: This is used to reduce the blank area by shrinking the frame according to the duty cycle, thereby improving the utilization rate of raw materials while meeting the requirements. S6. After receiving the cutting parameters, the motion controller calculates the starting and ending coordinates of the cutting head by combining the encoder position of the conveyor belt, and completes the automatic cutting. The determination of the maximum inscribed rectangle in step S5 is achieved by converting the 3D image projection into a 2D image, and then determining the maximum inscribed rectangle on the projected image based on matrix relationships through image rotation. The rotation process uses the rotation matrix HomMat2DRotat and the identity matrix HomMat2D, specifically as follows: First, rotate the 2D projected image to a suitable angle using a rotation matrix. The maximum inscribed rectangle at that angle is determined, and then the material is rotated back to its original orientation using the identity matrix HomMat2D. The cutting frame rotates synchronously with the material to maintain consistent relative positions. The rotation matrix HomMat2DRotat is calculated as follows: ,in It is a two-dimensional rotation transformation matrix; In step S5, the dimensions of the cutting frame are determined. Based on preset specifications, the length, width, and vertex positions of the cutting frame are determined through coordinate adjustment to meet the shape requirements. The specific implementation is as follows: First, set the scaling step, then calculate the coordinates of the cut box vertices after adjustment: , ; , ; Length of the cutting frame ,width ;in, These are the coordinates of the original bounding box vertices. Next, calculate the coordinates of the four vertices of the cutting box: Vertex 1 is , ； Vertex 2 is , ； Vertex 3 is , ； Vertex 4 is , ;in, Center point of the cutting frame coordinate, Center point of the cutting frame coordinate.

2. The method for fixed-weight and fixed-shape cutting of meat according to claim 1, characterized in that, In step S4, the acquired 3D scanned image is processed. The algorithm converts the 3D point cloud data into 2D image data by first projecting the 3D scanned image from 3D to 2D, and then projecting the 3D point cloud data onto a two-dimensional plane to form a 2D projected image.

3. The method for fixed-weight and fixed-shape cutting of meat according to claim 1, characterized in that, The angle The traversal interval is and in angular step size Perform a traversal and calculate the area of ​​the largest inscribed rectangle.

4. The method for fixed-weight and fixed-shape cutting of meat according to claim 1, characterized in that, The method for calculating the weight after cutting in step S5 is as follows: ,in, For height, For length.

5. A method for fixed-weight and fixed-shape cutting of meat according to claim 1, characterized in that, In step S5, adjusting the cutting frame involves, after determining the size of the cutting frame, detecting whether there is any blank area within the cutting frame. If blank area exists and the duty cycle is greater than a set threshold, frame reduction processing will be performed. The duty cycle is calculated as follows: ,in Expressed as duty cycle, The area of ​​the blank region. The area of ​​the entire rectangular region must satisfy the duty cycle within the weight limit. It is the minimum value.

Images