A method and system for evaluating the growth condition of a pig

Abstract

The application discloses a pig growth condition evaluation method and system, first, basic detection parameters are acquired, and a standard polar coordinate system is constructed according to the basic detection parameters, then, a body surface point polar coordinate set of a pig to be evaluated and a moving speed parameter set of the pig to be evaluated are calculated, a section curve graph set of the pig to be evaluated is generated according to the body surface point polar coordinate set, the actual three-dimensional model of the pig to be evaluated is generated by fitting according to the moving speed parameter set and the section curve graph set, finally, a standard evaluation model is selected, the standard evaluation model is compared with the actual three-dimensional model, and an evaluation result of the pig to be evaluated is output; compared with the prior art, the application realizes automatic scanning measurement of the external features of the pig and automatic generation of the three-dimensional model, meanwhile, all parameters can be acquired in one detection batch, the data acquisition efficiency is effectively improved, and then the evaluation efficiency of the growth state of the pig is improved.

Description

Technical Field

[0001] This application relates to the field of feature detection technology, specifically to a method and system for evaluating the growth status of pigs. Background Technology

[0002] In pig farming, it is necessary to regularly measure the pig's body shape, with key parameters including body length, chest circumference, waist circumference, and rump circumference. These parameters are used to evaluate the pig's growth status. Currently, these parameters are generally obtained manually, with some farms using scanners. However, manual measurement is not only inaccurate but also inefficient. While scanners can quickly acquire these parameters, they are expensive, and each measurement only obtains partial data, requiring repeated repositioning to obtain all necessary parameters. Furthermore, the measurement process is affected by the pig's movement and the measurement angle, resulting in low evaluation efficiency. Summary of the Invention

[0003] The main purpose of this application is to provide a method and system for evaluating the growth status of pigs, aiming to solve the problem of low evaluation efficiency in the existing technology.

[0004] This application achieves the above objectives through the following technical solutions: A method for evaluating the growth status of pigs includes the following steps: Obtain basic detection parameters and construct a standard polar coordinate system based on the basic detection parameters; Calculate the polar coordinate set of the body surface points of the pig to be evaluated and the set of movement speed parameters of the pig to be evaluated; A set of cross-sectional curve images of the pigs to be evaluated is generated based on the polar coordinate set of the body surface points; A three-dimensional model of the pig to be evaluated is generated by fitting the set of moving speed parameters and the set of cross-sectional curves. A standard evaluation model is selected, and the standard evaluation model is compared with the actual three-dimensional model to output the evaluation results of the pigs to be evaluated.

[0005] Optionally, obtaining basic detection parameters and constructing a standard polar coordinate system based on the basic detection parameters includes the following steps: Set the sampling period T; Construct a polar coordinate system and obtain the polar coordinate set of each detection point {(r1, θ1), (r2, θ2), ..., (r... n θ n )}, where r represents the polar radius, θ represents the polar angle, and n represents the detection point number; The detection points are calibrated in the polar coordinate system based on the polar coordinate set to obtain the standard polar coordinate system.

[0006] Optionally, the polar coordinates of the body surface points of the pig to be evaluated and the set of movement speed parameters of the pig to be evaluated are collected, including the following steps: Obtain the distance parameter d of each detection point. 11 d 12 , ..., d 1m d 21 d 22 , ..., d 2m , ..., d n1 d n2 , ..., d nm Where n represents the number of each detection point, and m represents the timestamp number determined according to the sampling time; Obtain the polar coordinate set of each detection point {(r1, θ1), (r2, θ2), ..., (r... n θ n )}; Calculate the extreme diameter of each body surface point according to the formula for calculating the extreme diameter of the body surface point, where the expression of the formula for calculating the extreme diameter of the body surface point is r. nm =r n -d nm ; A set of polar coordinates for each detection point is generated based on the polar angle and the polar radius of each body surface point. 11 ,θ1), (r 12 ,θ1),...,(r 1m ,θ1), (r 21 ,θ2), (r 22 ,θ2),...,(r 2m ,θ2),...,(r n1 θ n (r) n2 θ n ), ..., (r nm θ n )}; Obtain the movement speed values ​​of the pigs to be evaluated, and generate timestamp numbers for each movement speed value based on the sampling time, thus obtaining the movement speed parameter set {v1, v2, ..., v...}. m}, where m represents the timestamp number determined based on the sampling time.

[0007] Optionally, a set of cross-sectional curve images of the pigs to be evaluated is generated based on the polar coordinate set of the body surface points, including the following steps: Obtain the polar coordinate set of points on the body surface; Based on the timestamp number, the polar coordinate set of the body surface points is converted into several computational units [(r 11 ,θ1), (r 21 ,θ2),...,(rn1 θ n )], [(r 12 ,θ1), (r 22 ,θ2),...,(r n2 θ n )], ..., [(r 1m ,θ1), (r 2m ,θ2),...,(r nm θ n )]; Obtain any computational unit and standard polar coordinate system; The calculation unit calibrates the body surface points in the standard polar coordinate system. By sequentially connecting the various body surface points through the fitted curve, and integrating the fitted curve with the origin of the standard polar coordinate system, a cross-sectional curve is generated. Repeat the steps to obtain any computational unit and standard polar coordinate system to obtain the set of cross-sectional curves {S1, S2, ..., S} of the pig to be evaluated. m}

[0008] Optionally, a three-dimensional model of the pig to be evaluated is generated by fitting the set of moving speed parameters and the set of cross-sectional curves, including the following steps: The cross-sectional thickness parameter set {t1, t2, ..., t3} is calculated based on the moving speed parameter set and the sampling period. m-1}, wherein the calculation expression for the section thickness parameter is t m =Tv m ; Based on the timestamp number, the cross-section thickness parameter set and cross-section curve set are converted into several mapping units (S1, t1), (S2, t2), ..., (S...). m-1 , t m-1 (S) m ,0); Obtain any mapping unit, and axially stretch its cross-sectional curve according to its cross-sectional thickness parameter to obtain a three-dimensional cross-sectional model with a reference axis. Repeat the steps of obtaining any mapping unit to obtain the set of 3D models of the cross section {Q1, Q2, ..., Q...} m}; Based on the timestamp number and each reference axis, the three-dimensional models of each cross section are sequentially connected to obtain the actual three-dimensional model of the pig to be evaluated.

[0009] Optionally, a standard evaluation model is selected, and the standard evaluation model is compared with the actual three-dimensional model to output the evaluation results of the pigs to be evaluated, including the following steps: A standard evaluation model is selected based on the age group of the pigs to be evaluated; Set a standard evaluation threshold A; The reference axes of the standard evaluation model and the actual three-dimensional model are overlapped; Calculate the overlap between the standard evaluation model and the actual 3D model to generate the actual overlap parameter B; If B≥A, the growth status of the pig to be evaluated is deemed acceptable; otherwise, the growth status of the pig to be evaluated is deemed unacceptable.

[0010] Optionally, a standard evaluation model may be selected based on the age group of the pigs to be evaluated, including the following steps: The basic model is selected based on the age group of the pigs to be evaluated; Set the upper and lower evaluation biases for the pigs to be evaluated; Generate an upper deviation standard evaluation model based on the upper evaluation deviation and the standard evaluation model; A lower deviation standard evaluation model is generated based on the lower evaluation deviation and the standard evaluation model; The reference axes of the overlapping upper deviation standard evaluation model and the lower deviation standard evaluation model; The portion of the upper deviation standard model that does not overlap with the lower deviation standard evaluation model is output as the standard evaluation model.

[0011] Accordingly, this application also discloses an evaluation system based on the above-mentioned pig growth status evaluation method, including a frame; A measuring ring, wherein the measuring ring is disposed on the frame; An infrared ranging module includes several infrared distance sensors arranged around the axis of the measuring ring. Each infrared distance sensor is disposed on the measuring ring, and the emission directions of each infrared distance sensor converge at the center of the measuring ring. An ultrasonic velocity sensor is mounted on the frame and is used to detect the speed at which the pig to be evaluated passes through the measuring ring. The controller is electrically connected to each of the infrared distance sensors and the ultrasonic speed sensors.

[0012] Optionally, the evaluation system also includes a trigger switch, which includes two photoelectric sensors positioned at the front and rear ends of the measuring ring along the moving direction of the pig to be evaluated.

[0013] Optionally, the controller includes a basic parameter construction module, which is used to acquire basic detection parameters and construct a standard polar coordinate system based on the basic detection parameters; The first calculation module is used to calculate the polar coordinate set of the body surface points of the pig to be evaluated and the set of movement speed parameters of the pig to be evaluated. The second calculation module is used to generate a set of cross-sectional curve images of the pig to be evaluated based on the set of polar coordinates of the body surface points. A 3D model generation module is used to fit and generate an actual 3D model of the pig to be evaluated based on the set of moving speed parameters and the set of cross-sectional curves. The comparison and evaluation module is used to select a standard evaluation model, compare the standard evaluation model with the actual three-dimensional model, and output the evaluation results of the pigs to be evaluated.

[0014] Compared with the prior art, this application has the following beneficial effects: This application first obtains basic detection parameters and constructs a standard polar coordinate system based on these parameters. Then, it calculates the set of polar coordinates of the body surface points of the pig to be evaluated and the set of parameters of the pig's movement speed. Based on the set of polar coordinates of the body surface points, it generates a set of cross-sectional curves of the pig to be evaluated. Then, it fits the set of movement speed parameters and the set of cross-sectional curves to generate an actual three-dimensional model of the pig to be evaluated. Finally, it selects a standard evaluation model, compares the standard evaluation model with the actual three-dimensional model, and outputs the evaluation results of the pig to be evaluated. This application constructs a coordinate calibration system around the entire axis of the pig to be evaluated using polar coordinates. This means that the coordinates of all body surface points of the pig to be evaluated can be collected in a single detection process. Furthermore, several cross-sectional curves of the pig to be evaluated can be generated based on the above coordinates. Finally, the actual three-dimensional model of the pig to be evaluated is obtained by stretching and splicing the pig's movement speed. The growth status of the pig can then be evaluated by comparing the three-dimensional models. Compared with the prior art, this application first realizes the automatic scanning and measurement of the physical characteristics of pigs and the automatic generation of three-dimensional models, thereby improving the detection efficiency of relevant parameters of pigs to be evaluated, and thus improving the evaluation efficiency; Compared with existing technologies that use scanning devices, this application not only has lower hardware costs, but also eliminates the need for manual scanning of pigs by hand, reducing the workload of staff. Furthermore, all parameters can be obtained in a single batch of tests, effectively improving data collection efficiency and thus enhancing the evaluation efficiency of pig growth status. Attached Figure Description

[0015] Figure 1 This is a flowchart of the pig growth status evaluation method disclosed in the embodiments of this application; Figure 2 A schematic diagram illustrating the layout of each testing point; Figure 3 A schematic diagram illustrating the principle of polar coordinate calculation for a body surface point with timestamp number e. Figure 4 Generate a schematic diagram for the cross-sectional curve plot with timestamp number e; Figure 5 Generate images for the actual 3D model; Figure 6 This is a schematic diagram of the structure of the evaluation system provided in the embodiments of this application; Figure 7 A schematic diagram of the controller provided in the embodiments of this application; Attached reference numerals: 1-Frame, 2-Measuring ring, 3-Infrared distance sensor, 4-Ultrasonic speed sensor, 5-Photoelectric sensor, 6-RFID electronic tag, 7-Reader, 8-Controller; The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0017] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0018] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0019] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions. Taking "robot coordinate system and / or m" as an example, it includes the robot coordinate system solution, the m solution, or a solution where both the robot coordinate system and m are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0020] Example 1

[0021] Reference Figure 1 This embodiment discloses a method for evaluating the growth status of pigs, including the following steps: S1. Obtain basic detection parameters and construct a standard polar coordinate system based on the basic detection parameters; S11. Set the sampling period T; Set the sampling period T according to actual needs. For example, if the sampling period is set to 1s, the preferred sampling period is 0.5-1s. S12. Construct a polar coordinate system and obtain the polar coordinate set of each detection point {(r1, θ1), (r2, θ2), ..., (r...}. n θ n )}, where r represents the polar radius, θ represents the polar angle, and n represents the detection point number; According to the aforementioned description of the evaluation device, each infrared ranging sensor is evenly arranged around the measuring ring, and a standard polar coordinate system is established with the center of the measuring ring as the origin. By combining the size parameters and installation position parameters of the infrared distance sensors, the polar coordinates of each infrared distance sensor can be obtained. It should be noted that the detection point refers to the measurement starting point of each infrared distance sensor; see the specific reference... Figure 2 As shown; S13. Based on the polar coordinate set, calibrate each detection point in the polar coordinate system to obtain the standard polar coordinate system.

[0022] Reference Figure 2 Based on the polar coordinate set of each detection point {(r1, θ1), (r2, θ2), ..., (r... n θ nPoints can be marked in the polar coordinate system. After marking, the polar coordinate system with the detection points is output as the standard polar coordinate system.

[0023] S2. Calculate the polar coordinate set of the body surface points of the pig to be evaluated and the set of movement speed parameters of the pig to be evaluated; S21. Obtain the distance parameter d of each detection point. 11 d 12 , ..., d 1m d 21 d 22 , ..., d 2m , ..., d n1 d n2 , ..., d nm Where n represents the number of each detection point, and m represents the timestamp number determined according to the sampling time; The pigs to be evaluated are driven through the measurement ring. When the pig passes the photoelectric sensor, it triggers various infrared distance sensors and ultrasonic velocity sensors. During the process of the pig passing through the detection ring, the infrared distance sensors and ultrasonic velocity sensors continuously sample according to a set sampling period, thereby obtaining the distance parameter d at each detection point. 11 d 12 , ..., d 1m d 21 d 22 , ..., d 2m , ..., d n1 d n2 , ..., d nm Where n represents the number of each detection point, and m represents the timestamp number determined according to the sampling time; At the same time, the ultrasonic velocity sensor will also acquire a series of velocity parameters; S22. Obtain the polar coordinate set of each detection point {(r1, θ1), (r2, θ2), ..., (r... n θ n )}; S23. Calculate the extreme diameter of each body surface point according to the formula for calculating the extreme diameter of the body surface point, wherein the expression of the formula for calculating the extreme diameter of the body surface point is r. nm =r n -d nm .

[0024] Reference Figure 3 Since the positions of each infrared distance sensor are fixed, their polar coordinates are relatively fixed. Furthermore, in polar coordinates, the polar angle of each body surface point is equal to the polar angle of the corresponding detection point. The formula for calculating the polar radius of the body surface point is r. nm =r n -dnm ; Therefore, the extreme diameter r of all body surface points can be calculated using the above formula. 11 r 12 ,...,r 1m r 21 r 22 ,...,r 2m ,...,r n1 r n2 ,...,r nm ; S24. Generate a set of polar coordinates for the body surface points {(r)} based on the polar angle of each detection point and the polar radius of each body surface point. 11 ,θ1), (r 12 ,θ1),...,(r 1m ,θ1), (r 21 ,θ2), (r 22 ,θ2),...,(r 2m ,θ2),...,(r n1 θ n (r) n2 θ n ), ..., (r nm θ n )}; By combining the polar radius and polar angle of the same body surface location, we can obtain the polar coordinate set of the body surface location {(r 11 ,θ1), (r 12 ,θ1),...,(r 1m ,θ1), (r 21 ,θ2), (r 22 ,θ2),...,(r 2m ,θ2),...,(r n1 θ n (r) n2 θ n ), ..., (r nm θ n )}; S25. Obtain the movement speed values ​​of the pigs to be evaluated, and generate timestamp numbers for each movement speed value according to the sampling time, thus obtaining the movement speed parameter set {v1, v2, ..., v...}. m-1}, where m represents the timestamp number determined based on the sampling time.

[0025] Obtain the movement speed values ​​acquired in step S21, and number each movement speed value according to its timestamp (numbered according to the order of sampling time). This will yield the movement speed parameter set {v1, v2, ..., v...}. m-1}, where m represents the timestamp number determined based on the sampling time.

[0026] S3. Generate a set of cross-sectional curves of the pig to be evaluated based on the set of polar coordinates of the body surface points; S31. Obtain the polar coordinate set of points on the body surface; S32. Convert the polar coordinate set of the body surface points into several computational units based on the timestamp number [(r 11 ,θ1), (r 21 ,θ2),...,(r n1 θ n )], [(r 12 ,θ1), (r 22 ,θ2),...,(r n2 θ n )], ..., [(r 1m ,θ1), (r 2m ,θ2),...,(r nm θ n )]; As the pigs being evaluated continuously move forward through the detection ring, the data obtained at different sampling times correspond to different points on the pig's body surface, and each point is arranged sequentially along the direction of the pig's movement. The data obtained at the same sampling time are located on the same vertical cross section, meaning that the various body surface points collected at the same sampling time can be calibrated in the same polar coordinate system.

[0027] Based on the above principle, the polar coordinate set of the body surface points is converted into several computational units [(r 11 ,θ1), (r 21 ,θ2),...,(r n1 θ n )], [(r 12 ,θ1), (r 22 ,θ2),...,(r n2 θ n )], ..., [(r 1m ,θ1), (r 2m ,θ2),...,(r nm θ n )]; S33. Obtain any computational unit and standard polar coordinate system; S34. The calculation unit calibrates the body surface points in the standard polar coordinate system. Reference Figure 3 The obtained calculation unit can be used to calibrate the body surface points in the standard polar coordinate system.

[0028] S35. By sequentially connecting the various body surface points through the fitted curve, the fitted curve and the origin of the standard polar coordinate system are integrated to generate a cross-sectional curve. After each body surface point is calibrated, a fitting curve is obtained by computer fitting calculation. The fitting curve connects each body surface point in a counterclockwise or clockwise direction. The origin of the standard polar coordinate system is the center of rotation of the fitting curve.

[0029] It should be noted that after generating the fitted curve, integrating it with the origin of the standard polar coordinate system will output the cross-sectional curve. See the following for details. Figure 4 ; S36. Repeat the steps to obtain any computational unit and standard polar coordinate system to obtain the cross-sectional curve set of the pig to be evaluated {S1, S2, ..., S...}. m}

[0030] Repeating steps S33-S35 will yield all cross-sectional curve plots, thus generating a cross-sectional curve plot set {S1, S2, ..., S...}. m}

[0031] S4. Based on the set of moving speed parameters and the set of cross-sectional curves, a three-dimensional model of the pig to be evaluated is generated by fitting the model. S41. Calculate the cross-sectional thickness parameter set {t1, t2, ..., t3} based on the moving speed parameter set and the sampling period. m-1}, wherein the calculation expression for the section thickness parameter is t m =Tv m .

[0032] Since the pig being evaluated is constantly moving forward, while the position of the infrared distance sensor is fixed, the various cross-sectional curves will be arranged sequentially along the pig's spine, thus achieving natural separation of the various cross-sectional curves and scanning and sampling of the entire pig. However, the pig's forward speed is constantly changing, so the traditional method of calculating using average speed will introduce a large error. To solve the above technical problems, this application eliminates the above errors by shortening the sampling cycle and continuously detecting the pig's speed. That is, regardless of the change in the pig's moving speed, as long as the sampling period is small enough, and considering factors such as the small moving speed of the pig and human intervention in the moving speed, the change in the pig's moving speed can be ignored. Therefore, the expression for calculating the section thickness parameter is t. m =Tv m .

[0033] Compared with existing technologies, the above calculation method uses differential thinking to convert and calculate the moving speed of pigs, which improves the accuracy of the calculation as much as possible, and the technical solution is simple and reliable. Secondly, by adjusting the sampling period, the calculation accuracy can also be controlled, thereby meeting different usage requirements. That is, when the computer performance and the requirements for monitoring accuracy are not high, the calculation difficulty of the data can be reduced by increasing the sampling period.

[0034] Obtain the movement speed parameter set {v1, v2, ..., v} from step S25. m-1 By combining the above calculation formulas, the set of cross-sectional thickness parameters {t1, t2, ..., t} can be calculated. m-1}

[0035] It should be noted that the section thickness parameter refers to the distance between two adjacent section curves, i.e., t1 represents the distance between section curve S1 and section curve S2. Also, since there is no corresponding section curve after the last sampling, the velocity v... m It can be discarded; S42. Based on the timestamp number, convert the cross-section thickness parameter set and cross-section curve set into several mapping units (S1, t1), (S2, t2), ..., (S...). m-1 , t m-1 (S) m ,0); Since the last cross-sectional curve is located at the end of the pig's growth cycle, and there are no cross-sectional curves behind it, its cross-sectional thickness parameter is 0.

[0036] S43. Obtain any mapping unit, and axially stretch its cross-sectional curve according to its cross-sectional thickness parameter to obtain a three-dimensional cross-sectional model with a reference axis. As can be seen from the above analysis, between any two adjacent cross-sectional thickness surfaces, this technical solution simplifies them into uniform motion by differentiation, and the moving distance is the cross-sectional thickness parameter. Therefore, the cross-sectional curve in the two-dimensional plane can be converted into a three-dimensional cross-sectional model by translation and stretching. Therefore, by obtaining any mapping unit and axially stretching it according to the expected corresponding section thickness parameter, the three-dimensional model of the section can be obtained. During the stretching process, the origin of the standard polar coordinate system in the cross-section curve diagram will be stretched along with it, and the reference axis of the three-dimensional model of the cross-section will be generated. Since different pigs have different physiological characteristics, it is impossible to specify the same reference axis based on the physiological characteristics of the pigs so as to combine the three-dimensional models of various cross sections later. Therefore, this application uses the origin of the standard polar coordinate system as the basis for generating the reference axis. That is, no matter what changes occur in the height and body shape of the pigs to be evaluated, the origin of the standard polar coordinate system remains unchanged. Therefore, generating the reference axis with its origin has uniformity. S44. Repeat the steps of obtaining any mapping unit to obtain the set of 3D models of the cross section {Q1, Q2, ..., Q...}m}; S45. Based on the timestamp number and each of the reference axes, the three-dimensional models of each cross section are sequentially connected to obtain the actual three-dimensional model of the pig to be evaluated.

[0037] During the continuous movement of the pigs to be evaluated through the detection loop, the origin of the standard polar coordinate system will generate the largest standard reference axis, and the reference axes of each cross-sectional 3D model are part of the above standard reference axes. By sequentially splicing them coaxially according to the sampling order, all reference axes can be spliced ​​into a standard reference axis. Based on the above principle, the actual three-dimensional model of the pig to be evaluated can be obtained by sequentially and coaxially stitching together the three-dimensional models of each cross-section. (See details...) Figure 5 ; Compared with existing technologies, this application ingeniously uses the reference axis generated by stretching the origin of the standard polar coordinate system as the reference for splicing, thereby realizing the accurate splicing of the three-dimensional models of each cross-section. Not only is the technical solution simple, but the accuracy and efficiency of splicing are also effectively guaranteed, thereby improving the evaluation efficiency of pigs.

[0038] Preferably, since the cross-sectional thickness parameter is averaged in the above calculation process, the actual three-dimensional model after splicing will present a stepped shape. In order to further improve the quality of the three-dimensional model, in addition to smoothing by reducing the sampling period, the entire actual three-dimensional model can also be smoothed by fitting a curved surface.

[0039] It should be noted that, due to the location settings of the photoelectric sensor, there is no tissue structure of the pig to be evaluated at the end of the actual 3D model. In this case, the above-mentioned area needs to be processed by manual deletion to improve the accuracy of the measurement.

[0040] S5. Select a standard evaluation model, compare the standard evaluation model with the actual three-dimensional model, and output the evaluation results of the pigs to be evaluated.

[0041] S51. Select a standard evaluation model based on the age group of the pigs to be evaluated; S511. Select the basic model based on the age group of the pigs to be evaluated; Since pigs grow at different ages, it is necessary to select a base model based on the actual age group of the pigs to be evaluated in order to improve the accuracy of the evaluation. It should be noted that the above basic model is a data model collected in advance; the above basic model is generated by averaging multiple actual three-dimensional models of pigs of the same age or by analyzing relevant body shape parameters; S512. Set the upper evaluation bias and lower evaluation bias of the pigs to be evaluated; The upper and lower evaluation deviations can use default values ​​or be determined based on the actual situation, such as setting the upper evaluation deviation to 5% and the lower evaluation deviation to 5%. It should be noted that when setting the above deviations, it is also necessary to set their applicable scope. That is, the growth rate of different parts of the pig is different during the growth process. For example, the abdomen of the pig is the fastest fattening area. Therefore, the upper evaluation deviation and lower evaluation deviation can be set separately for the above area, and the applicable area can be defined in the three-dimensional model. Therefore, the minimum value of the upper evaluation deviation and lower evaluation deviation is 1. The above measures can enable more refined management of pig evaluation and improve the accuracy of evaluation. S513. Generate an upper deviation standard evaluation model based on the upper evaluation deviation and the standard evaluation model; The standard evaluation model can be generated by proportionally scaling up the standard evaluation model based on the above evaluation deviation. S514. Generate a lower deviation standard evaluation model based on the lower evaluation deviation and the standard evaluation model; The lower deviation standard evaluation model can be generated by proportionally reducing the standard evaluation model according to the lower evaluation deviation. S515. Overlap the reference axes of the upper deviation standard evaluation model and the lower deviation standard evaluation model; S516. The portion of the upper deviation standard model that does not overlap with the lower deviation standard evaluation model is output as the standard evaluation model. Since the upper deviation standard evaluation model represents the upper limit of the pig's growth status and the lower deviation standard evaluation model represents the lower limit of the pig's growth status, the area between the upper deviation standard evaluation model and the lower deviation standard evaluation model is the qualified area.

[0042] That is, by subtracting the overlapping parts, the remaining parts can be used as the output of the standard evaluation model.

[0043] S52. Set the standard evaluation threshold A; Because of the significant differences among individual pigs, some areas of a pig that is in good condition may exceed the standard evaluation model. Therefore, by setting a standard evaluation threshold A, the above-mentioned misjudgments can be effectively corrected in such cases, thereby improving the objectivity of the evaluation.

[0044] The standard evaluation threshold A is the degree of overlap between the standard evaluation model and the actual 3D model. If the standard evaluation threshold A is set, it means that the actual 3D model can be judged to be qualified only when the degree of overlap between the standard evaluation model and the actual 3D model is not less than 95%. S53. Overlap the reference axes of the standard evaluation model and the actual three-dimensional model; S54. Calculate the overlap between the standard evaluation model and the actual three-dimensional model, and generate the actual overlap parameter B; After the overlap is completed, the computer automatically calculates the degree of overlap between the standard evaluation model and the actual three-dimensional model, and generates the actual overlap parameter B. S55. If B≥A, the growth status of the pig to be evaluated is deemed qualified; otherwise, the growth status of the pig to be evaluated is deemed unqualified.

[0045] If the actual overlap parameter B is 97% and the set standard evaluation threshold A is 95%, it indicates that the overlap meets the requirements and the growth status of the pig to be evaluated in terms of body shape is qualified; otherwise, it is judged as unqualified.

[0046] Compared with the prior art, this application first realizes the automatic scanning and measurement of the physical characteristics of pigs and the automatic generation of three-dimensional models, thereby improving the detection efficiency of relevant parameters of pigs to be evaluated, and thus improving the evaluation efficiency; Compared with existing technologies that use scanning devices, this application not only has lower hardware costs, but also eliminates the need for manual scanning of pigs by hand, reducing the workload of staff. Furthermore, all parameters can be obtained in a single batch of tests, effectively improving data collection efficiency and thus enhancing the evaluation efficiency of pig growth status.

[0047] Example 2

[0048] Reference Figure 6 This embodiment discloses a pig growth status evaluation system, including a frame 1, on which a moving channel is provided. Preferably, the moving channel allows only one pig to be evaluated to pass through at a time. A cutoff area is reserved in the middle of the moving channel, and a measuring ring 2 is installed in the cutoff area. The pigs to be evaluated can only pass through the measuring ring 2 during the moving channel. The measuring ring 2 is also equipped with an infrared ranging module, which includes a number of infrared distance sensors 3. Preferably, the number of infrared distance sensors 3 should not be less than 150. The infrared distance sensors 3 are evenly arranged around the axis of the measuring ring 2, and the infrared rays emitted by the infrared distance sensors 3 converge at the center of the measuring ring 2. Since the pigs to be evaluated can only pass through the measuring ring 2 during movement, the above arrangement can ensure that each infrared distance sensor 3 is arranged in a 360° circle around the pigs to be evaluated. That is, the measuring points of each infrared distance sensor 3 are arranged around the pigs to be evaluated. This not only avoids detection blind spots, but also completes the acquisition of all parameters at once, thus maximizing detection efficiency. The above objective can be achieved by cleverly arranging the positions of each infrared distance sensor 3, which helps to reduce the cost of the equipment.

[0049] Furthermore, the evaluation device also includes an ultrasonic speed sensor 4, which is arranged at the exit end of the moving channel with its probe facing the moving channel to ensure that the ultrasonic speed sensor 4 is facing the head of the pig to be evaluated, thereby improving the accuracy of speed detection.

[0050] Furthermore, the evaluation device also includes a trigger switch and an identification device. The trigger switch includes two photoelectric sensors 5. Along the direction of movement of the pig to be evaluated in the moving channel, the two photoelectric sensors 5 are respectively arranged at the front end and the rear end of the measuring ring 2. It should be noted that, in order to ensure the accuracy of the measurement, the photoelectric sensor 5 located at the rear end of the measuring ring 2 is no more than 1-3 cm away from the measuring ring 2. It is the photoelectric sensor 5 used to start the device. The photoelectric sensor located at the front end is 140-170 cm away from the measuring ring 2. It is the photoelectric sensor 5 used to turn off the device. The above settings enable timely activation of devices such as infrared distance sensor 3, and timely shutdown when the pig to be evaluated completely leaves the measuring ring 2, thereby reducing the energy consumption of the equipment. It should be noted that the distance between the photoelectric sensor 5 used to start the device and the measuring ring 2 should be minimized as much as possible to reduce or ignore the compensation value of the pig's body length. The identification device includes an RFID electronic tag 6 and a reader 7, wherein the reader 7 is located at the entrance end of the measuring ring 2; and the RFID electronic tag 6 is fixed to the pig's body by an ear loop or other device. Furthermore, the evaluation device also includes a controller 8, which is electrically connected to each of the infrared distance sensors 3, ultrasonic sensors, photoelectric sensors 5 and readers 7 via a data bus, thereby realizing the reception of data and the automatic generation of evaluation results; Preferably, the controller 8 is an industrial control computer, which has a built-in basic parameter construction module, a first calculation module, a second calculation module, a three-dimensional model generation module, and a comparison and evaluation module. The output of the parameter construction module is communicatively connected to the first calculation module, the output of the first calculation module is communicatively connected to the second communication module, the input of the three-dimensional model generation module is communicatively connected to both the first and second calculation modules, and the comparison and evaluation module is communicatively connected to the three-dimensional model generation module. The basic parameter construction module is used to obtain basic detection parameters and construct a standard polar coordinate system based on the basic detection parameters; the first calculation module is used to calculate the polar coordinate set of the body surface points of the pig to be evaluated and the set of movement speed parameters of the pig to be evaluated. The second calculation module is used to generate a set of cross-sectional curve images of the pig to be evaluated based on the set of polar coordinates of the body surface points; the three-dimensional model generation module is used to fit and generate an actual three-dimensional model of the pig to be evaluated based on the set of moving speed parameters and the set of cross-sectional curve images. The comparison and evaluation module is used to select a standard evaluation model, compare the standard evaluation model with the actual three-dimensional model, and output the evaluation results of the pigs to be evaluated.

[0051] When using the device, the pigs to be evaluated are manually driven into the moving channel. Since only one pig is allowed to pass through the moving channel at a time, the pigs will pass through one by one. In order to improve the detection accuracy, the moving distance of the pigs can also be manually controlled, and special care should be taken to prevent the pigs to be tested from walking backwards. As the pigs to be evaluated move forward, they first enter the working area of ​​the reader, thereby enabling the identification of the pigs and quickly determining their age group. The pigs to be evaluated then enter the photoelectric sensor working area, thus starting the equipment. At this time, the infrared distance sensor and the ultrasonic sensor continuously sample according to the set sampling period. When the pigs have completely passed through, the photoelectric sensor located at the front end of the measuring ring will be triggered, thus ending the detection process.

[0052] Compared with existing technologies, the above-mentioned evaluation device not only realizes one-time automatic measurement of all body surface points of pigs, but also improves the efficiency of data collection, thereby improving the evaluation efficiency of pigs. Secondly, the pigs to be evaluated can pass through the measurement ring one by one, thus achieving uninterrupted measurement of a large number of pigs. It can also automatically identify the pigs and generate an evaluation report for the measured pigs at the same time, further improving the evaluation efficiency of pigs. It is especially suitable for large-scale farms, enabling batch and accurate monitoring and evaluation of the growth status of pigs.

[0053] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for evaluating the growth status of pigs, characterized in that, Includes the following steps: Obtain basic detection parameters, and construct a standard polar coordinate system based on the basic detection parameters; wherein the standard polar coordinate system has the center of the measurement ring as the origin; Obtain the distance parameter d of each detection point. 11 d 12 , ..., d 1m d 21 d 22 , ..., d 2m , ..., d n1 d n2 , ..., d nm Where n represents the number of each detection point, and m represents the timestamp number determined according to the sampling time; Obtain the polar coordinate set of each detection point {(r1, θ1), (r2, θ2), ..., (r... n θ n )}; Calculate the extreme diameter of each body surface point according to the formula for calculating the extreme diameter of the body surface point, where the expression of the formula for calculating the extreme diameter of the body surface point is r. nm =r n -d nm ; A set of polar coordinates for each detection point is generated based on the polar angle and the polar radius of each body surface point. 11 ,θ1), (r 12 ,θ1),...,(r 1m ,θ1), (r 21 ,θ2), (r 22 ,θ2),...,(r 2m ,θ2),...,(r n1 θ n (r) n2 θ n ), ..., (r nm θ n )}; Obtain the movement speed values ​​of the pigs to be evaluated, and generate timestamp numbers for each movement speed value based on the sampling time, thus obtaining the movement speed parameter set {v1, v2, ..., v...}. m }, where m represents the timestamp number determined based on the sampling time; A set of cross-sectional curve images of the pigs to be evaluated is generated based on the polar coordinate set of the body surface points; A three-dimensional model of the pig to be evaluated is generated by fitting the set of moving speed parameters and the set of cross-sectional curves. A standard evaluation model is selected, and the standard evaluation model is compared with the actual three-dimensional model to output the evaluation results of the pigs to be evaluated.

2. The method for evaluating pig growth status according to claim 1, characterized in that, The process of obtaining basic detection parameters and constructing a standard polar coordinate system based on these parameters includes the following steps: Set the sampling period T; Construct a polar coordinate system and obtain the polar coordinate set of each detection point {(r1, θ1), (r2, θ2), ..., (r... n θ n )}, where r represents the polar radius, θ represents the polar angle, and n represents the detection point number; The detection points are calibrated in the polar coordinate system based on the polar coordinate set to obtain the standard polar coordinate system.

3. The method for evaluating pig growth status according to claim 1, characterized in that, The process of generating a set of cross-sectional curve images of the pig to be evaluated based on the set of polar coordinates of the body surface points includes the following steps: Obtain the polar coordinate set of points on the body surface; Based on the timestamp number, the polar coordinate set of the body surface points is converted into several computational units [(r 11 ,θ1), (r 21 ,θ2),...,(r n1 θ n )], [(r 12 ,θ1), (r 22 ,θ2),...,(r n2 θ n )], ..., [(r 1m ,θ1), (r 2m ,θ2),...,(r nm θ n )]; Obtain any computational unit and standard polar coordinate system; The calculation unit calibrates the body surface points in the standard polar coordinate system. By sequentially connecting the various body surface points through the fitted curve, and integrating the fitted curve with the origin of the standard polar coordinate system, a cross-sectional curve is generated. Repeat the steps to obtain any computational unit and standard polar coordinate system to obtain the set of cross-sectional curves {S1, S2, ..., S} of the pig to be evaluated. m } 4. The method for evaluating pig growth status according to claim 3, characterized in that, The process of fitting and generating an actual three-dimensional model of the pig to be evaluated based on the set of moving speed parameters and the set of cross-sectional curves includes the following steps: The cross-sectional thickness parameter set {t1, t2, ..., t3} is calculated based on the moving speed parameter set and the sampling period. m-1 }, wherein the calculation expression for the section thickness parameter is t m =Tv m ; Based on the timestamp number, the cross-section thickness parameter set and cross-section curve set are converted into several mapping units (S1, t1), (S2, t2), ..., (S...). m-1 , t m-1 (S) m ,0); Obtain any mapping unit, and axially stretch its cross-sectional curve according to its cross-sectional thickness parameter to obtain a three-dimensional cross-sectional model with a reference axis. Repeat the steps of obtaining any mapping unit to obtain the set of 3D models of the cross section {Q1, Q2, ..., Q...} m }; Based on the timestamp number and each reference axis, the three-dimensional models of each cross section are sequentially connected to obtain the actual three-dimensional model of the pig to be evaluated.

5. The method for evaluating pig growth status according to claim 4, characterized in that, The selected standard evaluation model is compared with the actual three-dimensional model to output the evaluation result of the pig to be evaluated, including the following steps: A standard evaluation model is selected based on the age group of the pigs to be evaluated; Set a standard evaluation threshold A; The reference axes of the standard evaluation model and the actual three-dimensional model are overlapped; Calculate the overlap between the standard evaluation model and the actual 3D model to generate the actual overlap parameter B; If B≥A, the growth status of the pig to be evaluated is deemed acceptable; otherwise, the growth status of the pig to be evaluated is deemed unacceptable.

6. The method for evaluating pig growth status according to claim 5, characterized in that, The selection of a standard evaluation model based on the age group of the pigs to be evaluated includes the following steps: The basic model is selected based on the age group of the pigs to be evaluated; Set the upper and lower evaluation biases for the pigs to be evaluated; Generate an upper deviation standard evaluation model based on the upper evaluation deviation and the standard evaluation model; A lower deviation standard evaluation model is generated based on the lower evaluation deviation and the standard evaluation model; The reference axes of the overlapping upper deviation standard evaluation model and the lower deviation standard evaluation model; The portion of the upper deviation standard evaluation model that does not overlap with the lower deviation standard evaluation model is output as the standard evaluation model.

7. An evaluation system based on the pig growth status evaluation method according to any one of claims 1-6, characterized in that, Including racks; A measuring ring, wherein the measuring ring is disposed on the frame; An infrared ranging module includes several infrared distance sensors arranged around the axis of the measuring ring. Each infrared distance sensor is disposed on the measuring ring, and the emission directions of each infrared distance sensor converge at the center of the measuring ring. An ultrasonic velocity sensor is mounted on the frame and is used to detect the speed at which the pig to be evaluated passes through the measuring ring. The controller is electrically connected to each of the infrared distance sensors and the ultrasonic speed sensors.

8. The evaluation system according to claim 7, characterized in that, The evaluation system also includes a trigger switch, which includes two photoelectric sensors. Along the moving direction of the pig to be evaluated, the two photoelectric sensors are respectively placed at the front end and the rear end of the measuring ring.

9. The evaluation system according to claim 7, characterized in that, The controller includes a basic parameter construction module, which is used to acquire basic detection parameters and construct a standard polar coordinate system based on the basic detection parameters. The first calculation module is used to calculate the polar coordinate set of the body surface points of the pig to be evaluated and the set of movement speed parameters of the pig to be evaluated. The second calculation module is used to generate a set of cross-sectional curve images of the pig to be evaluated based on the set of polar coordinates of the body surface points. The 3D model generation module is used to fit and generate an actual 3D model of the pig to be evaluated based on the set of moving speed parameters and the set of cross-sectional curves. The comparison and evaluation module is used to select a standard evaluation model, compare the standard evaluation model with the actual three-dimensional model, and output the evaluation results of the pigs to be evaluated.

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