Intelligent billiard training system

Abstract

The invention discloses an intelligent billiard training system, which relates to the technical field of image processing, and is characterized in that a three-dimensional model of a billiard table and a billiard body is accurately constructed through a multi-sensor fusion technology of a depth camera, a laser radar, a high-speed camera and the like, so that the training environment is more real; the path simulation module can automatically calculate the optimal ball hitting angle and the optimal ball hitting force F to help the trainee to find the optimal attack path, and the trial and error cost is reduced. The tablecloth friction coefficient can be measured in real time, track correction is carried out based on different materials rubbed by the tablecloth, it is ensured that the calculated cue ball speed is matched with the actual situation, and track deviation is avoided. If the ball hitting angle or force of the trainee deviates from the optimal calculated value, the system can perform automatic correction and provide optimization suggestions. The system can also monitor the station posture, rod holding and body balance conditions and quantitatively evaluate the posture stability; and the trainer can correct bad postures in a short time.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and particularly to an intelligent billiards training system. Background Art

[0002] Billiards training is a sport with extremely high precision requirements. Its training effect is affected by various factors, including the hitting force of the trainer, the hitting angle, the collision trajectory between the cue ball and the object ball, the friction coefficient of the tablecloth, etc. During traditional billiards training, trainers often rely on personal experience for practice and lack quantitative indicators to evaluate the accuracy of hitting. Since trainers cannot accurately master the appropriate hitting force and angle, it often leads to low training efficiency and difficulty in achieving accurate hitting. In addition, traditional training methods mainly rely on visual judgment and repeated attempts, lacking scientific error analysis and path optimization, making it difficult for trainers to systematically improve their technical level.

[0003] Although some existing billiards auxiliary training devices can provide a certain degree of trajectory analysis or video playback functions, there are still many deficiencies. For example, most devices cannot accurately measure the hitting force of the trainer and also lack the function of dynamically adjusting the friction coefficient of the tablecloth, resulting in a deviation between the simulated movement trajectory of the cue ball and the actual situation. The friction coefficient of the tablecloth may vary slightly due to different materials, and ignoring these details will lead to errors between the simulation results and the actual hitting situation, affecting the judgment of the trainer and further reducing the accuracy and effectiveness of training.

[0004] In addition, during the process of simulating the hitting trajectory, if the friction coefficient of the tablecloth is not accurately considered, the movement trajectory of the cue ball may deviate significantly from the actual situation, causing the trainer to adjust based on inaccurate data, thereby exacerbating the training error. For example, in a high-friction area, the speed of the cue ball decays rapidly, while in a low-friction area, the cue ball may move farther. If the training system fails to accurately simulate these details, the trainer may mistakenly think it is their own technical problem rather than a venue factor, and thus wrongly adjust the hitting force or angle, affecting the training effect. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides an intelligent billiards training system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: An intelligent billiards training system, comprising: A three-dimensional billiards scene modeling module, used to obtain image data and three-dimensional data of the billiards table and the balls by using a depth camera and a lidar, construct a three-dimensional model of the billiards table, and project the trajectories of the cue ball and the object ball hit by the trainer each time onto the three-dimensional model; A path simulation module, which is used to simulate and analyze to obtain the best hitting angle of the cue ball by calculating during the training process when the trainer sets the target ball. And the initial velocity of the first cue ball ; And collect the friction coefficient of the tablecloth , correct and convert the initial velocity of the first cue ball To obtain the initial velocity of the second cue ball And the hitting force F; An error analysis module, which is used to collect the hitting force of the trainer during training And the hitting angle during training , and compare and calculate with the best hitting angle of the cue ball And the hitting force F to obtain the hitting force error And the hitting angle error : When ≠0, then send out the first warning signal to remind the trainer that the hitting force is unqualified; when ≠0, then send out the second warning signal to remind the trainer that the hitting angle is unqualified; A trajectory intelligent monitoring module, which is used to establish a trajectory motion data set for the actual motion trajectory and the expected motion trajectory after each swing of the trainer; analyze according to the trajectory motion data set to obtain: the cue ball trajectory deviation coefficient , the target ball motion deviation factor And the cue ball abnormal out-of-bounds factor , and comprehensively calculate the hitting trajectory accuracy coefficient , set a preset qualified threshold X, if Is lower than , then trigger the third warning signal.

[0007] Preferably, the path simulation module includes an image acquisition unit and a simulation calculation unit; The image acquisition unit is used to collect the coordinates of the i-th pocket on the billiard table, marked as , collect the current cue ball coordinates , the coordinates of the target ball And the radius R of the target ball: Collect the current rotation state and motion state of the cue ball, and the rotation state includes spin, topspin and backspin states; The motion state includes: stationary, rolling and sliding states; The simulation calculation unit is used to project into a three-dimensional model when setting the target ball during the training process of the trainer, and calculate and obtain the best hitting angle of the cue ball , the initial velocity of the first cue ball , the initial velocity of the second cue ball And the hitting force F; Optimal hitting angle of the cue ball is obtained as follows: S11. When the connection line of the moving directions of the target ball and the i-th pocket is the same, calculate the vector of the target ball entering the pocket : ; In the formula, represents the x-axis coordinate of the i-th pocket along the long side of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the i-th pocket along the short side of the billiard table in the Cartesian coordinate system; represents the x-axis coordinate of the target ball along the long side of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the target ball along the long side of the billiard table in the Cartesian coordinate system; S12. And calculate the i-th pocket entry direction angle of the target ball: ; S13. The cue ball needs to receive the contact point of the target ball to make the target ball move along the i-th pocket direction. First, calculate the collision point coordinates of the target ball: ; ; S14. Calculate the hitting direction of the cue ball: ; S15. Calculate the optimal hitting angle of the cue ball to ensure correct collision with the target ball: ; In the formula, represents the x-axis coordinate of the cue ball along the long side of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the cue ball along the long side of the billiard table in the Cartesian coordinate system.

[0008] Preferably, the acquisition methods of the initial velocity of the first cue ball and the initial velocity of the second cue ball are as follows: S21. To make the target ball smoothly enter the pocket, it is necessary to calculate the hitting force F of the cue ball. The hitting force F of the cue ball is affected by the friction coefficient of the tablecloth. First, according to the law of conservation of momentum, collect the mass of the cue ball and the mass of the target ball. When they are equal, calculate the initial velocity , the initial velocity of the first cue ball shall satisfy the following formula: ; In the formula, is the velocity of the object ball; when the mass of the cue ball and the mass of the object ball are equal, that is, the initial velocity of the cue ball should be equal to the final velocity of the object ball, the cue ball stops completely after hitting the object ball, and the object ball moves along the collision direction; When the mass of the cue ball ≠ the mass of the object ball , the initial velocity of the first cue ball shall satisfy the following formula: ; ; In the formula, represents the velocity of the cue ball after collision; S22, the velocity of the object ball will be attenuated by the friction coefficient of the tablecloth and the moving distance. The velocity of the object ball is corrected through the following formula to obtain the corrected velocity of the object ball : ; In the formula, represents the friction coefficient of the tablecloth, including: when it is a nylon blend material ; a tournament-grade tablecloth containing 85 - 90% wool ; American eight-ball coarse wool, with a wool content between 50% - 80% ; 91% - 100% fine wool ; a wool tablecloth for nine-ball pool ; is the distance from the object ball to the i-th pocket opening, represents the velocity attenuation factor, and the farther the distance, the greater the velocity loss; S23, based on the corrected velocity of the object ball , the initial velocity of the first cue ball is synchronously corrected, and the initial velocity of the second cue ball is calculated through the following formula. When the mass of the cue ball and the object ball are equal, the initial velocity of the second cue ball satisfies the following formula: ; When the mass of the cue ball ≠ the mass of the object ball , the initial velocity of the second cue ball satisfies the following formula: .

[0009] Preferably, the hitting force F is obtained as follows: Based on the initial velocity of the second cue ball , according to the impulse-momentum theorem and Newton's second law, it is converted into the hitting force F through the following formula: ; In the formula, t represents the contact time between the club head and the cue ball, with the unit of s, and is set to 0.001s - 0.005s.

[0010] Preferably, the error analysis module is used to install an angle sensor and a force sensor on the club, and when collecting the training hitting force of the trainer and the training hitting angle , and comparing them with the optimal hitting angle of the cue ball and the hitting force F, so as to calculate and obtain the hitting force error and the hitting angle error through the following formula: ; ; When ≠0, a first warning signal is issued to remind the trainer that the hitting force is unqualified; when >0, it means that the trainer hits too hard, and the trainer is prompted to reduce the hitting force; when <0, it means that the trainer hits too lightly, and the trainer is prompted to increase the hitting force; When ≠0, a second warning signal is issued to remind the trainer that the hitting angle is unqualified; when >0, it is prompted that the hitting club head angle of the trainer deviates to the left; when <0, it is prompted that the club head angle of the trainer deviates to the right.

[0011] Preferably, the trajectory intelligent monitoring module includes a second acquisition unit and a second calculation unit; The second acquisition unit is used to collect the actual movement trajectory and the expected movement trajectory after each swing of the trainer, and establish a trajectory movement data set; The second calculation unit is used to deeply calculate and analyze based on the trajectory movement data set, so as to calculate and obtain the cue ball trajectory deviation coefficient , the target ball movement deviation factor and the cue ball abnormal out-of-bounds factor through the following formula: ; In the formula, represents the difference value of the cue ball trajectory deviation angle, represents the lateral displacement generated during the linear movement of the cue ball, Indicates the deviation between the actual speed of the cue ball and the theoretically calculated speed, Indicates the deviation value of the topspin or backspin state of the cue ball; Is expressed as a weight coefficient; ; In the formula, Indicates the angle between the actual running direction of the object ball and the expected direction, Indicates the distance error between the final stopping position of the object ball and the target point, Indicates the error between the actual speed of the object ball and the expected speed, Indicates the deviation between the rotation direction of the object ball and the rotation direction of the object ball in the expected movement trajectory; Is expressed as a weight coefficient; ; In the formula, Indicates the closest distance between the cue ball and the table boundary, Indicates the jumping height of the cue ball, Indicates the deviation value of the spin state of the cue ball Is shown as a weight coefficient.

[0012] Preferably, the trajectory intelligent monitoring module further includes a first correlation unit and a first warning unit; The first correlation unit is used to dimensionless process the cue ball trajectory deviation coefficient , the object ball motion deviation factor and the cue ball abnormal out-of-bounds factor , and calculate and obtain the hitting trajectory accuracy coefficient through the following correlation formula : ; In the formula, Are respectively the weight coefficients of the cue ball trajectory deviation coefficient , the object ball motion deviation factor and the cue ball abnormal out-of-bounds factor ; The first warning unit is used to preset a qualified threshold X, and compare the hitting trajectory accuracy coefficient with the preset qualified threshold X. If the hitting trajectory accuracy coefficient < the qualified threshold X, it means that the trainee's billiards training is unqualified, trigger the third warning signal, and generate a first strategy, including: adjusting the current training plan, increasing the stick head angle training task by 10%-20%, and the stick head angle training task includes: low shot training, high shot training and side spin training; If the hitting trajectory accuracy coefficient ≥ the qualified threshold X, it means that the trainee's billiards training is qualified, and continue with the current training plan.

[0013] Preferably, the posture correction module is used to analyze the trainer's standing posture, grip method and body center of gravity distribution to analyze and calculate the standing posture stability factor , Grip stability factor and body balance factors ; The posture correction module includes a pressure acquisition unit, a grip acquisition unit and an inertia acquisition unit; The pressure collection unit is used to install a pressure sensor on the ground mat to detect the pressure of the trainer's left foot. and right foot pressure ; The grip collection unit is used to install a grip pressure sensor at the club grip position to detect and obtain the actual grip pressure ; Inertial acquisition unit, used to install a posture sensor on the trainer's waist to acquire the center of gravity position , front and rear tilt angle , and install an acceleration sensor on the trainee to monitor the body shaking speed in real time .

[0014] Preferably, the posture correction module further includes a first analysis unit, a second analysis unit and a third analysis unit; The first analysis unit is used to extract the center of gravity position , the trainer's left foot pressure and right foot pressure , after dimensionless processing, the standing stability factor is calculated by the following formula : ; In the formula, The total force on the body. , Indicates the maximum allowable offset distance of the center of gravity in standing position; ; Indicates the horizontal coordinate of the trainer's current center of gravity. Shows the coordinates of the trainee’s current center of gravity in the front and back directions; Indicates the horizontal coordinates of the center of gravity in the standard standing posture; Indicates the front-to-back coordinates of the center of gravity in a standard standing posture; like , indicating that the trainee's center of gravity is biased to the right; like , indicating that the trainee's center of gravity is biased to the left; like , indicating that the trainee's current center of gravity is biased forward, causing forward leaning; like , indicating that the trainee's current center of gravity is biased to the rear, causing backward leaning; The second analysis unit is used to extract the actual grip pressure , and calculate and obtain the grip stability factor through the following formula : ; In the formula, is the actual grip pressure, represents the optimal grip pressure, represents the maximum allowable grip pressure, represents the deviation value of the shaft angle during gripping, represents the maximum allowable deviation value of the grip angle; The third analysis unit is used to extract the forward and backward tilt angles and the body sway speed . After dimensionless processing, calculate and obtain the body balance factor through the following formula : ; In the formula, represents the maximum allowable tilt angle, represents the allowable maximum sway speed.

[0015] Preferably, the posture correction module further includes a second correlation unit and a second warning unit; The second correlation unit is used to extract the standing posture stability factor , the grip stability factor and the body balance factor . After dimensionless processing, obtain the posture standard index through the following correlation formula : ; In the formula, are the weight coefficients of the standing posture stability factor , the grip stability factor and the body balance factor respectively;

[0016] The second warning unit is used to preset the posture standardization threshold Z, and compare the posture standard index with the posture standardization threshold Z to determine whether the trainer's posture is qualified, including: If the posture standard index < the posture standardization threshold Z, it means that the trainer's posture during billiards training is unqualified, trigger the fourth warning signal, and generate a second strategy, including: adjusting the current training plan, adjusting the standing posture, and adding 30s of standing posture balance training before each training. The standing posture balance training includes: single-leg standing training and core muscle group training; adjusting the standing position, and distributing the center of gravity according to and getting closer, and increasing the grip strength stability training by 5%; If the posture standard index ≥ the posture standardization threshold Z, it indicates that the trainer's posture is qualified during billiards training, and the current training plan continues to be carried out.

[0017] The present invention provides an intelligent billiards training system. It has the following beneficial effects: (1) For this intelligent billiards training system, through multi-sensor fusion technologies such as depth cameras, lidar, and high-speed cameras, a three-dimensional model of the billiard table and the ball is accurately constructed, making the training environment more realistic; the path simulation module can automatically calculate the best hitting angle and the best hitting force F, helping the trainer find the best offensive route and reducing the trial-and-error cost. It can measure the coefficient of friction of the tablecloth in real time and correct the trajectory based on different materials of the tablecloth friction to ensure that the calculated speed of the cue ball matches the actual situation and avoid trajectory deviation. If the hitting angle or force of the trainer deviates from the best calculated value, the system can automatically correct it and provide optimization suggestions.

[0018] (2) For this intelligent billiards training system, the system integrates a high-frame-rate motion capture device to collect the actual motion trajectory and the expected motion trajectory of the trainer after each swing, and establishes a trajectory motion data set for subsequent calculation and analysis. Based on the trajectory motion data set, the cue ball trajectory deviation coefficient, the target ball motion deviation factor, and the cue ball abnormal out-of-bounds factor are deeply calculated, and the flight trajectory is analyzed in real time to identify abnormal situations such as flying balls and jump balls. The system can automatically match the optimal hitting trajectory, provide adjustment suggestions, effectively reduce mistakes caused by angle, speed, or rotation errors, enable the player to more accurately control the landing point of the ball, and improve the game performance.

[0019] (3) Through the pressure acquisition unit, the grip acquisition unit, and the inertia acquisition unit, combined with the multi-factor calculation model, the accurate quantification and real-time feedback of the trainer's standing posture stability, grip stability, and body balance are realized. By detecting the pressure of the trainer's left foot and right foot through the pressure acquisition unit and combining the center of gravity position, the standing posture stability factor is calculated , and the center of gravity deviation of the trainer is analyzed; when the standing posture stability is insufficient, the system automatically provides posture optimization suggestions, such as adjusting the foot placement and performing core stability training, to help the trainer maintain the best standing position.

[0020] (4) For this intelligent billiards training system, the actual grip pressure of the trainer is obtained through the grip acquisition unit, and the grip stability factor is calculated , and whether the grip force and the shaft angle meet the best standards are analyzed in real time; if the grip stability factor is too small or too large, it indicates that the grip force or the shaft angle deviation is relatively large, which may affect the hitting trajectory, and targeted training (such as increasing the grip force adjustment practice) is required.

[0021] (5) The intelligent billiards training system monitors the forward and backward tilt angles and the body sway speed of the trainer through the inertial acquisition unit, and calculates the body balance factor. , and evaluates the stability of the trainer during the hitting process in real time; the system calculates the weighted values of the stance stability factor , the grip stability factor and the body balance factor to obtain the posture standard index , which is used to comprehensively evaluate the qualification of the trainer's posture: if Z < the preset threshold Z, the system triggers the fourth warning signal and generates the second training strategy to correct the trainer's posture. Compared with the traditional training mode, it promotes the accurate monitoring of the stance, grip and body balance, and quantitatively evaluates the posture stability; the trainer can correct the bad posture in a short time and improve the hitting stability; it avoids the posture deviation caused by different observation angles of the coach or the insufficient self-perception of the trainer. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 FIG. is a schematic flow chart of an intelligent billiards training system according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0024] Embodiment 1 Please refer to Figure 1 , the present invention provides an intelligent billiards training system. Please refer to Figure 1 , including: A three-dimensional billiards scene modeling module, which is used to obtain the image data and three-dimensional data of the billiards table and the balls by using a depth camera and a lidar, construct a three-dimensional model of the billiards table, and project the trajectories of the cue ball and the target ball hit by the trainer each time onto the three-dimensional model; The spatial coordinate information of the billiards table and the surrounding environment is obtained in real time through the depth camera to form point cloud data; Combined with RGB information, the point cloud data is converted into a color 3D model to make the training environment more intuitive; Optimize edge detection using an adaptive deep learning algorithm to improve 3D modeling accuracy; use a high-precision lidar to perform detailed scanning on the surface of the billiard table; combine an optical recognition algorithm to detect the edge of the billiard table, the position of the pockets, and the distribution of the balls in real time, providing more accurate data support for subsequent trajectory simulation; use a high-frame-rate (above 1000fps) camera to record the movement trajectories of the cue ball and the object balls in real time to ensure accurate data capture at the moment of hitting the ball; through the trajectories of the cue ball and the object balls hit by the trainer each time, combine vision recognition technology and image processing technology to restore their movement paths in the 3D model in real time; use spatial point cloud reconstruction technology to generate a high-precision billiard table model to ensure that the movement paths of all the balls are based on a virtual environment with real proportions; A path simulation module, which is used to simulate and analyze to obtain the best hitting angle of the cue ball during the training process of the trainer when setting the object ball. And the initial velocity of the first cue ball ; and collect the friction coefficient of the tablecloth , correct and convert the initial velocity of the first cue ball to obtain the initial velocity of the second cue ball and the hitting force F; An error analysis module, which is used to collect the hitting force of the trainer during training and the hitting angle during training , and compare and calculate with the best hitting angle of the cue ball and the hitting force F to obtain the hitting force error and the hitting angle error : when , then issue a first warning signal to remind the trainer that the hitting force is unqualified; when , then issue a second warning signal to remind the trainer that the hitting angle is unqualified; A trajectory intelligent monitoring module, which is used to establish a trajectory movement data set for the actual movement trajectory and the expected movement trajectory after each swing of the trainer; analyze according to the trajectory movement data set to obtain: the cue ball trajectory deviation coefficient , the object ball movement deviation factor and the cue ball abnormal out-of-bounds factor , and comprehensively calculate the hitting trajectory accuracy coefficient , set a preset qualified threshold X, if is lower than , then trigger a third warning signal.

[0025] In this embodiment, through multi-sensor fusion technologies such as depth cameras, lidar, and high-speed cameras, a three-dimensional model of the billiard table and the balls is accurately constructed, making the training environment more realistic; the path simulation module can automatically calculate the optimal hitting angle and the initial hitting speed, helping the trainer find the best offensive route and reducing the trial-and-error cost. It can measure the coefficient of friction of the tablecloth in real time and correct the trajectory based on different regions of the tablecloth friction to ensure that the calculated speed of the cue ball matches the actual situation and avoid trajectory deviation. If the hitting angle or force of the trainer deviates from the optimal calculated value, the system can automatically correct it and provide optimization suggestions.

[0026] The system can detect the actual hitting force and angle of the trainer, compare them with the calculated optimal hitting force F and the optimal hitting angle, and calculate the error: If the hitting force error ≠ 0, trigger the first warning signal to remind the trainer to adjust the force.

[0027] If the hitting angle error ≠ 0, trigger the second warning signal to remind the trainer to adjust the angle.

[0028] Through the trajectory intelligent monitoring module, a trajectory motion data set is established, covering: The cue ball trajectory deviation coefficient (detect whether the cue ball moves along the expected path); The object ball motion deviation factor (calculate whether the object ball rolls in the expected direction); The cue ball abnormal out-of-bounds factor (detect whether the cue ball goes out of bounds abnormally); Calculate the hitting trajectory accuracy coefficient. If it is lower than the set threshold X, trigger the third warning signal to remind the trainer to adjust the hitting method. This module can accumulate training data for a long time, analyze the technical stability of the trainer, and provide targeted improvement suggestions.

[0029] The system can record the historical hitting data of the trainer and support slow playback and key frame analysis to help the trainer review the training details; provide a personalized training plan for its weaknesses. For example, if the trainer often has a large hitting force error, the system can recommend a precise force control training mode. If the trainer's angle control is unstable, it recommends hitting angle optimization training.

[0030] Embodiment 2 This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically, the path simulation module includes an image acquisition unit and a simulation calculation unit; The image acquisition unit is used to collect the coordinates of the i-th pocket on the billiard table, marked as , collect the current cue ball coordinates , the coordinates of the object ball and the radius R of the object ball: Collect the current spin state and motion state of the cue ball. The spin state includes the topspin, backspin, and sidespin states. The motion state includes: stationary, rolling, and sliding states. A simulation calculation unit, which is used to project the target ball into the 3D model during the training process of the trainer and calculate the best hitting angle of the cue ball through the collision physics algorithm 、the initial velocity of the first cue ball 、the initial velocity of the second cue ball and the hitting force F. The best hitting angle of the cue ball is obtained as follows: S11. When the direction connection line between the target ball and the i-th pocket is the same, calculate the target ball pocketing vector : ; In the formula, represents the x-axis coordinate of the i-th pocket along the long side of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the i-th pocket along the short side of the billiard table in the Cartesian coordinate system; represents the x-axis coordinate of the target ball along the long side of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the target ball along the long side of the billiard table in the Cartesian coordinate system; The target ball pocketing vector represents the target ball pocketing direction pointing to the i-th pocket; S12. And calculate the i-th pocketing direction angle of the target ball : ; The i-th pocketing direction angle describes how the target ball should move to correctly enter the pocket.

[0031] S13. The cue ball needs to receive the contact point of the target ball to make the target ball move along the i-th pocket direction. First, calculate the collision point coordinates of the target ball : ; ; The collision point coordinates of the target ball represent the specific position where the cue ball must hit the target ball.

[0032] S14. Calculate the hitting direction of the cue ball : ; The hitting direction of the cue ball It describes how the cue ball should move to accurately strike the best contact point of the object ball; S15. Calculate the best hitting angle of the cue ball , to ensure a correct collision with the object ball. The expression is as follows: ; In the formula, represents the x-axis coordinate of the cue ball along the long side direction of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the cue ball along the long side direction of the billiard table in the Cartesian coordinate system.

[0033] In this embodiment, for the best hitting angle of the cue ball , how should the trainer aim at the cue ball so that the object ball enters the pocket along the correct trajectory? The simulation calculation of the best hitting angle of the cue ball is based on a real physical model to calculate the best hitting angle of the cue ball, avoiding the error of traditional empirical judgment. Reduce unnecessary trial and error, and improve the success rate of the trainer in complex hitting scenarios. The system can automatically adapt to different object balls and pocket positions, improving the training applicability. Combined with real-time trajectory feedback, adjust the training strategy to enable the trainer to master the hitting skills faster.

[0034] Embodiment 3 This embodiment is an explanatory description carried out in Embodiment 1. Please refer to Figure 1 , specifically, the acquisition method of the initial velocity of the first cue ball and the initial velocity of the second cue ball is as follows: S21. In order to allow the object ball to enter the pocket smoothly, it is necessary to calculate the hitting force F of the cue ball. The hitting force F of the cue ball is affected by the friction coefficient of the tablecloth. First, according to the law of conservation of momentum, collect the mass of the cue ball and the mass of the object ball. When they are equal, calculate the initial velocity of the first cue ball. The initial velocity of the first cue ball should satisfy the following formula: ; In the formula, is the velocity of the object ball; when the mass of the cue ball and the mass of the object ball are equal, that is, the initial velocity of the cue ball should be equal to the final velocity of the object ball. The cue ball stops completely after hitting the object ball, and the object ball moves along the collision direction; When the mass of the cue ball ≠ the mass of the object ball, the initial velocity of the first cue ball should satisfy the following formula: ; ; In the formula, represents the velocity of the cue ball after collision; when the mass of the cue ball is greater than that of the object ball, the initial velocity of the cue ball will be slightly higher than the final velocity of the object ball to compensate for the momentum loss. At this time, the velocities of the cue ball and the object ball are averaged to conform to the principle of conservation of momentum. If the mass of the object ball is larger, the cue ball may rebound faster.

[0035] S22. Velocity of the object ball will be attenuated by the friction coefficient of the tablecloth and the moving distance. The velocity of the object ball is corrected through the following formula to obtain the corrected velocity of the object ball : ; In the formula, represents the friction coefficient of the tablecloth, including: when it is made of nylon blend ; tournament-grade tablecloth containing 85 - 90% wool ; American eight-ball rough wool with a wool content between 50% - 80% ; 91% - 100% fine wool tablecloth ; nine-ball wool tablecloth ; is the distance from the object ball to the i-th pocket opening, represents the velocity attenuation factor, and the farther the distance, the greater the velocity loss; The following is the friction coefficient of the tablecloth Example shown in the figure:

[0036] When using a tablecloth with a high wool content (such as 91% - 100% fine wool), the friction is lower and the object ball rolls farther; When using a coarser wool tablecloth (such as 50% - 80% American eight-ball tablecloth), the friction is greater and the object ball rolls with faster attenuation.

[0037] During the actual ball hitting process, the velocity of the object ball will be affected by the friction of the tablecloth and attenuate as the moving distance increases. The corrected velocity of the object ball can improve the calculation accuracy and prevent the object ball from not being able to enter the pocket due to too fast deceleration caused by friction.

[0038] S23. According to the corrected velocity of the object ball , the initial velocity of the first cue ball is synchronously corrected, and the initial velocity of the second cue ball is calculated and obtained through the following formula to satisfy the following formula: ; When the mass of the cue ball ≠Target ball mass When the second cue ball initial velocity satisfies the following formula: .

[0039] In this embodiment, in the billiards training system, in order to ensure that the target ball smoothly enters the pocket, it is necessary to accurately calculate the hitting force F and the initial velocity of the cue ball, and consider the influence of the tablecloth friction to correct the velocity of the target ball. Based on the law of conservation of momentum and the influence of friction, this system optimizes the movement trajectory of the cue ball and improves the hitting accuracy. Based on the conservation of momentum, ensure that the hitting force F of the cue ball is just right, avoiding too strong or too weak hitting. Correct the velocity of the target ball to make it more conform to the real environment, ensuring that the calculation results are consistent with the actual hitting trajectory. The calculation formula can be automatically adjusted according to different tablecloth materials to improve applicability. Help the trainer find the most suitable hitting force and improve the success rate of hitting the ball into the pocket. Calculating the velocity of the cue ball after impact helps to formulate a continuous offensive strategy and realize advanced billiards tactical training.

[0040] Embodiment 4 This embodiment is an explanatory description carried out in Embodiment 1. Please refer to Figure 1 , specifically, the acquisition method of the hitting force F is: According to the second cue ball initial velocity , according to the impulse-momentum theorem and Newton's second law, it is converted into the hitting force F through the following formula: ; In the formula, t represents the contact time between the tip of the cue and the cue ball, with the unit of S, and is set to 0.001s - 0.005s.

[0041] The mass of the cue ball of standard billiards is about 0.17kg - 0.18kg (slightly different for American 8-ball, snooker, nine-ball, etc.).

[0042] Depending on the hitting target and tactical requirements, for example: Hitting that requires a strong force (such as hitting a long-distance target ball with great force).

[0043] Hitting that requires controlling the force (such as gently pushing for a small-angle position).

[0044] Short contact time (0.001s - 0.002s): Generates a stronger hitting force, suitable for strong attacks, kissing balls, and long-distance shots.

[0045] Long contact time (0.003s - 0.005s): The hitting force is smaller, suitable for gentle positioning, bank shots, etc.

[0046] In this embodiment, the initial velocity of the cue ball is converted into the force exerted by the cue tip to help the trainer master the optimal force. The hitting force F can be combined with a camera tracking system or a table sensor to measure the hitting force in real time and compare it with the theoretically calculated value to improve the training accuracy.

[0047] Embodiment 5 This embodiment is an explanatory description based on Embodiment 4. Please refer to Figure 1 , specifically, the error analysis module is used to install an angle sensor and a force sensor on the cue. When collecting the training hitting force and the training hitting angle , and compare them with the optimal hitting angle of the cue ball and the hitting force F, so as to calculate and obtain the hitting force error and the hitting angle error through the following formula: ; ; When ≠0, a first warning signal is sent to remind the trainer that the hitting force is unqualified; when F>0, it means that the trainer hits too hard, and the trainer is prompted to reduce the hitting force; when F<0, it means that the trainer hits too lightly, and the trainer is prompted to increase the hitting force; When ≠0, a second warning signal is sent to remind the trainer that the hitting angle is unqualified; when >0, it is prompted that the hitting cue tip angle of the trainer deviates to the left; when <0, it is prompted that the cue tip angle of the trainer deviates to the right.

[0048] In this embodiment, the system adopts an error analysis module. Through the angle sensor and force sensor installed on the cue, the hitting force and training hitting angle of the trainer are collected in real time, and compared with the optimal hitting angle and hitting force F of the cue ball calculated theoretically, so as to calculate the hitting force error and hitting angle error, and provide targeted feedback and adjustment. Through real-time data comparison, the trainer can intuitively perceive the hitting error, gradually adjust the hitting force and angle, and improve the accuracy. Through the first warning signal and the second warning signal, the trainer can correct the error immediately and avoid the long-term wrong posture from affecting the game level. The system can record the historical hitting error data of the trainer, analyze its common problems (such as excessive force, angle deviation), and provide personalized training suggestions.

[0049] Embodiment 6 If the initial velocity of the cue ball is too high, it may cause abnormal rebound after hitting the cushion, or even fly out of the table. If the cue tip is tilted too much, it may cause the cue ball to jump excessively, increasing the risk of flying out. This is usually regarded as a serious mistake in billiards training.

[0050] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically, the trajectory intelligent monitoring module includes a second acquisition unit and a second calculation unit; The second acquisition unit is used to acquire the actual movement trajectory and the expected movement trajectory of the trainer after each swing, and establish a trajectory movement data set; The second calculation unit is used to deeply calculate and analyze based on the trajectory movement data set, so as to calculate and obtain the cue ball trajectory deviation coefficient , the object ball movement deviation factor and the cue ball abnormal out-of-bounds factor : ; In the formula, represents the difference value of the cue ball trajectory deviation angle, represents the lateral displacement generated by the cue ball during linear movement, represents the deviation between the actual speed and the theoretically calculated speed of the cue ball, represents the deviation value of the topspin or backspin state of the cue ball; represents the weight coefficient, and the sum of the weights is 1; ; In the formula, represents the included angle between the actual running direction and the expected direction of the object ball, represents the distance error between the final stopping position of the object ball and the target point, represents the error between the actual speed and the expected speed of the object ball, represents the deviation between the rotation direction of the object ball and the rotation direction of the object ball in the expected movement trajectory; represents the weight coefficient, and the sum of the weights is 1; ; In the formula, represents the closest distance between the cue ball and the table boundary, represents the jumping height of the cue ball, represents the deviation value of the spin state of the cue ball; represents the weight coefficient, and the sum of the weights is 1.

[0051] The cue ball trajectory deviation coefficient represents the degree of deviation of the cue ball trajectory; The object ball movement deviation factor represents the accuracy of the object ball movement trajectory; The cue ball abnormal out-of-bounds factor represents whether the cue ball abnormally jumps out of the boundary.

[0052] In this embodiment, the actual motion trajectory and expected motion trajectory of the trainee after each swing are collected, and a trajectory motion data set is established for subsequent calculation and analysis. Based on the trajectory motion data set, the cue ball trajectory deviation coefficient, target ball motion deviation factor and cue ball abnormal out-of-bounds factor are calculated in depth to evaluate the quality and accuracy of the shot.

[0053] Example 7 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically, the trajectory intelligent monitoring module also includes a first association unit and a first warning unit; The first associated unit is used to offset the cue ball trajectory coefficient , target ball motion deviation factor and the cue ball out of bounds factor After dimensionless processing, the accuracy coefficient of the hitting trajectory is calculated by the following related formula: : ; In the formula, They are the cue ball trajectory deviation coefficients , target ball motion deviation factor and the cue ball out of bounds factor The weight coefficient of , and the weight sum is 1; The first warning unit is used to preset the qualified threshold X and the hitting trajectory accuracy coefficient Compared with the preset qualified threshold X, if the hitting trajectory accuracy coefficient < qualified threshold value X, indicating that the trainee's billiards training is unqualified, triggering the third warning signal, and generating the first strategy, including: adjusting the current training plan, adding 10%-20% club head angle training tasks, and the club head angle training tasks include: low club training, high club training and side spin training; If the hitting trajectory accuracy coefficient ≥Qualified threshold value X, indicating that the trainee has passed the billiards training and continues the current training plan.

[0054] In this embodiment, by calculating the cue ball trajectory deviation coefficient, the target ball motion deviation factor, and the cue ball abnormal out-of-bounds factor, the trainee's shot trajectory deviation can be comprehensively measured and the shot quality can be accurately analyzed. The trainee can intuitively understand the deviation between the actual cue ball trajectory and the ideal trajectory, optimize the shot strategy in a targeted manner, and improve the shot accuracy. The dimensionless processing method is used to standardize multiple deviation data, eliminate the influence between different physical quantities, and improve the scientific nature of data analysis.

[0055] By calculating the accuracy coefficient of the striking trajectory and establishing quantifiable evaluation standards, the training process can be made more objective and accurate.

[0056] Set a warning threshold X. When the hitting trajectory accuracy coefficient is lower than the threshold, the system automatically triggers the third warning signal to remind the trainee to adjust the hitting method to prevent the formation of wrong habits.

[0057] Trainers can get targeted training suggestions in time to reduce bad hitting habits caused by long-term incorrect training; After the third warning signal is triggered, the system will automatically adjust the training plan, adding 10%-20% of club head angle training tasks, including special training such as low club, high club, and side spin, to specifically optimize the trainee's batting control ability.

[0058] Example 8 In billiards training, the correct standing posture, grip and body center of gravity control are crucial to the accuracy and stability of the shot. However, under traditional training methods, it is often difficult for trainees to intuitively perceive their own posture deviations, leading to the following problems: the trainees may lose balance due to uneven distribution of the center of gravity of their feet, thus affecting the stability of the shot. Gripping the club too tightly will limit the ability to control the club head, while gripping the club too loosely will easily cause the club head to deviate, affecting the trajectory and rotation control of the shot. When aiming or hitting the ball, the trainee's body may shake, causing the cue ball trajectory to deviate, especially when performing high-spin, low-spin or side-spin shots, affecting accuracy. Traditional training mainly relies on the coach's observation or the trainee's subjective feelings, lacks data support, and is difficult to accurately identify posture errors, and it is impossible to develop targeted corrective training plans.

[0059] This embodiment is explained in Example 1, please refer to Figure 1 Specifically, it also includes a posture correction module, which is used to analyze the trainer's standing posture, grip method and body center of gravity distribution, so as to analyze and calculate the standing posture stability factor. , Grip stability factor and body balance factors ; The posture correction module includes a pressure acquisition unit, a grip acquisition unit and an inertia acquisition unit; The pressure collection unit is used to install a pressure sensor on the ground mat to detect the pressure of the trainer's left foot. and right foot pressure ; The grip collection unit is used to install a grip pressure sensor at the club grip position to detect and obtain the actual grip pressure ; Inertial acquisition unit, used to install a posture sensor on the trainer's waist to acquire the center of gravity position , front and rear tilt angle , and install an acceleration sensor on the trainee to monitor the body shaking speed in real time .

[0060] The posture correction module further includes a first analysis unit, a second analysis unit and a third analysis unit; The first analysis unit is used to extract the center of gravity position , the pressure on the left foot of the trainer and the pressure on the right foot . After dimensionless processing, the standing posture stability factor is calculated through the following formula : ; In the formula, represents the total body force, , represents the maximum allowable offset distance of the center of gravity in the standing posture; , The closer it is to 1, the more stable the standing posture is; represents the horizontal coordinate of the current center of gravity of the trainer, represents the coordinate of the current center of gravity of the trainer in the front-back direction; represents the horizontal coordinate of the center of gravity in the standard standing posture; represents the coordinate of the center of gravity in the front-back direction in the standard standing posture; If , it means that the center of gravity of the trainer is biased to the right; If , it means that the center of gravity of the trainer is biased to the left; If , it means that the current center of gravity of the trainer is biased forward, resulting in forward tilt; If , it means that the current center of gravity of the trainer is biased backward, resulting in backward tilt; The second analysis unit is used to extract the actual grip pressure , and calculate the grip stability factor through the following formula : ; In the formula, is the actual grip pressure, represents the optimal grip pressure, represents the maximum allowable grip pressure, represents the deviation value of the shaft angle during gripping, represents the maximum allowable deviation value of the grip angle; The closer it is to 1, the more stable the trainer's grip is; The third analysis unit is used to extract the front-back tilt angle and the body swaying speed . After dimensionless processing, the body balance factor is calculated through the following formula : ; In the formula, Represents the maximum allowable tilt angle, Represents the maximum allowable wobbling speed, The closer it is to 1, the better the body balance of the trainer.

[0061] The posture correction module further includes a second correlation unit and a second warning unit; The second correlation unit is used to extract the standing posture stability factor , the club-holding stability factor and the body balance factor , after dimensionless processing, the posture standard index is obtained through the following correlation formula : ; In the formula, are respectively the standing posture stability factor , the club-holding stability factor and the body balance factor weight coefficients, and the sum of the weights is 1; The second warning unit is used to preset the posture standardization threshold Z, and compare the posture standard index with the posture standardization threshold Z to determine whether the trainer's posture is qualified, including: If the posture standard index < the posture standardization threshold Z, it means that the trainer's posture during billiards training is unqualified, triggering the fourth warning signal and generating a second strategy, including: adjusting the current training plan, adjusting the standing posture, and adding 30s of standing posture balance training before each training. The standing posture balance training includes: single-leg standing training and core muscle group training; adjusting the standing position, and distributing the center of gravity according to and getting closer, increasing the club-holding force stability training by 5%; If the posture standard index ≥ the posture standardization threshold Z, it means that the trainer's posture during billiards training is qualified, and the current training plan continues.

[0062] In this embodiment, through the pressure acquisition unit, the club-holding acquisition unit and the inertial acquisition unit, combined with the multi-factor calculation model, the accurate quantification and real-time feedback of the trainer's standing posture stability, club-holding stability and body balance are realized. By detecting the pressure of the trainer's left foot and right foot through the pressure acquisition unit and combining the center of gravity position, the standing posture stability factor is calculated to analyze the center of gravity deviation of the trainer; when the standing posture stability is insufficient, the system automatically provides posture optimization suggestions, such as adjusting the foot placement and performing core stability training, to help the trainer maintain the best standing position.

[0063] The actual club-holding pressure of the trainer is obtained through the club-holding acquisition unit, and the club-holding stability factor , analyze in real time whether the grip strength and the shaft angle meet the best standards; grip stability factor Too small or too large indicates a large deviation in grip strength or shaft angle, which may affect the hitting trajectory and targeted training is required (such as increasing grip strength adjustment exercises).

[0064] Monitor the forward and backward tilt angles and body sway speed of the trainer through the inertial acquisition unit, and calculate the body balance factor , and evaluate the stability of the trainer during the hitting process in real time; Through the second associated unit, the system will use the stance stability factor , grip stability factor and body balance factor to perform weighted calculations to obtain the posture standard index , which is used to comprehensively evaluate the qualification of the trainer's posture: If Z < the preset threshold Z, the system triggers the fourth warning signal and generates the second training strategy, including: Increase the 30s stance balance training (single-leg standing training, core muscle group training); Adjust the stance to ensure a more balanced center of gravity distribution; Increase the 5% grip strength stability training to enhance the shaft control ability.

[0065] Through the posture correction scheme of the above embodiments, compared with the traditional training mode, it promotes the accurate monitoring of the stance, grip and body balance, and quantitatively evaluates the posture stability; the trainer can correct the bad posture in a short time, improve the hitting stability; avoid the posture deviation caused by different observation angles of the coach or the insufficient self-perception of the trainer.

[0066] The setting of the size of the threshold is for the convenience of comparison. Regarding the size of the threshold, it depends on the amount of sample data and the number of base numbers set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values.

[0067] The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The coefficients in the formula are set by those skilled in the art according to the actual situation. As described above, only the preferred specific embodiments of the present invention are described, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. An intelligent billiards training system, characterized in that, Including: A three-dimensional billiards scene modeling module, which is used to obtain image data and three-dimensional data of the billiard table and the balls by using a depth camera and a lidar, construct a three-dimensional model of the billiard table, and project the trajectories of the cue ball and the target ball hit by the trainer each time onto the three-dimensional model; A path simulation module, which is used to simulate and analyze to obtain the best hitting angle of the cue ball through image processing technology when setting the target ball during the training process of the trainer and the initial speed of the first cue ball ; and collect the friction coefficient of the tablecloth , correct and convert the initial velocity of the first cue ball to obtain the initial velocity of the second cue ball and the hitting force F; An error analysis module for collecting the hitting force of the trainer during training and the hitting angle during training , and comparing and calculating with the optimal hitting angle of the cue ball and the hitting force F to obtain the hitting force error and the hitting angle error : When , a first warning signal is issued to remind the trainer that the hitting force is unqualified; when , a second warning signal is issued to remind the trainer that the hitting angle is unqualified; The trajectory intelligent monitoring module is used to establish a trajectory motion data set for the actual motion trajectory and the expected motion trajectory after each swing of the trainer; analyze according to the trajectory motion data set to obtain: the cue ball trajectory deviation coefficient , the target ball motion deviation factor and the cue ball abnormal out-of-bounds factor , and comprehensively calculate the hitting trajectory accuracy coefficient . Set a preset qualified threshold X. If is lower than , then trigger the third warning signal.

2. The intelligent billiards training system according to claim 1, characterized in that, The path simulation module includes an image acquisition unit and a simulation calculation unit; The image acquisition unit is used to collect the coordinates of the i-th pocket on the billiard table, marked as , and collect the coordinates of the current cue ball , the coordinates of the target ball and the radius R of the target ball: Collect the current rotation state and motion state of the cue ball, and the rotation state includes spin, topspin and backspin states; The motion states include: stationary, rolling and sliding states; The simulation calculation unit is used to project the target ball into the three-dimensional model during the training process of the trainer, and calculate the best hitting angle of the cue ball through the collision physics algorithm , the initial velocity of the first cue ball , the initial velocity of the second cue ball and the hitting force F; The best hitting angle of the cue ball is obtained as follows: S11. When the connection line of the moving directions of the target ball and the i-th pocket opening is the same, calculate the vector of the target ball entering the pocket : ; wherein, represents the x-axis coordinate of the i-th pocket in the direction of the long side of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the i-th pocket in the Cartesian coordinate system along the short side direction of the billiard table; represents the x-axis coordinate of the target ball along the long side direction of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the target ball along the long side direction of the billiard table in the Cartesian coordinate system; S12. Calculate the i-th pocketing direction angle of the target ball : ; S13. The cue ball needs to receive the contact point of the object ball in order to make the object ball move along the direction of the i-th pocket. First, calculate the collision point coordinates of the object ball : ； ； S14. Calculate the hitting direction of the cue ball : ; S15. Calculate the best hitting angle of the cue ball , to ensure a correct collision with the object ball: ; In the formula, represents the x-axis coordinate of the cue ball along the long side direction of the billiard table in the Cartesian coordinate system; represents the y-axis coordinate of the cue ball along the long side direction of the billiard table in the Cartesian coordinate system.

3. An intelligent billiards training system according to claim 2, characterized in that, The initial velocity of the first cue ball and the initial velocity of the second cue ball are obtained as follows: S21. To make the target ball fall into the pocket smoothly, it is necessary to calculate the hitting force F of the cue ball. The hitting force F of the cue ball is affected by the friction coefficient of the tablecloth. First, according to the law of conservation of momentum, collect the mass of the cue ball and the mass of the target ball . When the mass of the cue ball is equal to the mass of the target ball , calculate the initial velocity of the first cue ball. The initial velocity of the first cue ball should satisfy the following formula: ; In the formula, is the velocity of the target ball; when the mass of the cue ball is equal to the mass of the target ball , that is, the initial velocity of the cue ball should be equal to the final velocity of the target ball, the cue ball stops completely after hitting the target ball, and the target ball moves along the collision direction; When the mass of the cue ball ≠ the mass of the object ball the initial velocity of the first cue ball should satisfy the following formula: ； ； Wherein, represents the velocity after the cue ball collision; S22, Target ball speed will be attenuated by the friction coefficient of the tablecloth and the moving distance. The target ball speed is corrected through the following formula to obtain the corrected target ball speed : ； Wherein, represents the friction coefficient of the tablecloth, including: when it is made of nylon blended material ; competition-level tablecloth containing 85-90% wool ; American eight-ball rough wool, with the wool content between 50%-80% ; 91%-100% fine wool ; wool tablecloth for nine-ball pool ; is the distance from the target ball to the i-th pocket opening, represents the speed decay factor, and the greater the distance, the greater the speed loss; S23. According to the corrected target ball speed , synchronously correct the initial speed of the first cue ball . Obtain the initial speed of the second cue ball through the following formula . When the masses of the cue ball and the target ball are equal, the initial speed of the second cue ball satisfies the following formula: ; When the mass of the cue ball ≠ the mass of the object ball the initial velocity of the second cue ball satisfies the following formula: .

4. An intelligent billiards training system according to claim 3, characterized in that, The acquisition method of the hitting force F is: According to the initial velocity of the second cue ball , according to the impulse-momentum theorem and Newton's second law, it is converted into the hitting force F through the following formula: ; In the formula, t represents the contact time between the cue tip and the cue ball, the unit is s, and it is set to 0.001s - 0.005s.

5. An intelligent billiards training system according to claim 4, characterized in that, The error analysis module is used to install an angle sensor and a force sensor on the cue, and collect the hitting force of the trainee during training and the hitting angle during training , and compare them with the optimal hitting angle of the cue ball and the hitting force F, so as to calculate and obtain the hitting force error and the hitting angle error : ； ； When , a first warning signal is issued to remind the trainer that the hitting force is unqualified; when , it means that the trainer hits the ball too hard, and the trainer is prompted to reduce the hitting force; when , it means that the trainer hits the ball too lightly, and the trainer is prompted to increase the hitting force; When , a second warning signal is issued to remind the trainer that the hitting angle is unqualified; when , it indicates that the hitting clubhead angle of the trainer deviates to the left; when , it indicates that the clubhead angle of the trainer deviates to the right.

6. An intelligent billiards training system according to claim 1, characterized in that The trajectory intelligent monitoring module includes a second acquisition unit and a second calculation unit; The second acquisition unit is used to collect the actual motion trajectory and the expected motion trajectory after the trainer swings the cue each time, and establish a trajectory motion data set; The second calculation unit is configured to perform in-depth calculation and analysis based on the trajectory motion data set, so as to calculate and obtain the cue ball trajectory deviation coefficient through the following formula , the target ball motion deviation factor and the cue ball abnormal out-of-bounds factor : ; In the formula, represents the difference value of the offset angle of the cue ball trajectory, represents the lateral displacement generated during the linear motion of the cue ball, represents the deviation between the actual speed and the theoretically calculated speed of the cue ball, represents the deviation value of the forward or backward spin state of the cue ball; represents the weighting coefficient: ; In the formula, represents the angle between the actual running direction of the target ball and the expected direction, represents the distance error between the final stopping position of the target ball and the target point, represents the error between the actual speed of the target ball and the expected speed, represents the deviation between the rotation direction of the target ball and the rotation direction of the target ball in the expected motion trajectory; represents the weight coefficient; ; In the formula, represents the closest distance between the cue ball and the boundary of the table, represents the jumping height of the cue ball, represents the deviation value of the spin state of the cue ball; represents the weight coefficient.

7. An intelligent billiards training system according to claim 6, characterized in that, The trajectory intelligent monitoring module further includes a first correlation unit and a first warning unit; The first associated unit is used to dimensionless process the cue ball trajectory deviation coefficient , the object ball motion deviation factor and the cue ball abnormal out-of-bounds factor , and then calculate and obtain the hitting trajectory accuracy coefficient through the following associated formula : ; In the formula, are respectively the offset coefficients of the cue ball trajectory , the motion deviation factors of the object ball and the abnormal out-of-bounds factors of the cue ball weight coefficients; The first warning unit is configured to preset a qualified threshold X and compare the accuracy coefficient of the hitting trajectory with the preset qualified threshold X. If the accuracy coefficient of the hitting trajectory < the qualified threshold X, it indicates that the trainee's billiards training is unqualified, triggers a third warning signal, and generates a first strategy, including: adjusting the current training plan, increasing the head angle training task by 10%-20%, and the head angle training task includes: low shot training, high shot training, and side spin training; If the accuracy coefficient of the hitting trajectory ≥ the qualified threshold X, it indicates that the trainee's billiards training is qualified, and the current training plan continues.

8. An intelligent billiards training system according to claim 1, wherein, Also including: A posture correction module, configured to analyze the trainer's standing posture, grip style, and body center of gravity distribution, so as to analyze and calculate to obtain a standing posture stability factor , a grip stability factor , and a body balance factor ; The posture correction module includes a pressure acquisition unit, a grip acquisition unit and an inertia acquisition unit; The pressure acquisition unit is used to install pressure sensors on the ground mat to detect the pressure of the trainer's left foot and the pressure of the right foot ; The grip acquisition unit is used to install a grip pressure sensor at the grip position of the club to detect and obtain the actual grip pressure ; The inertial acquisition unit is used to install a posture sensor on the trainer's waist to acquire the center of gravity position. , front and rear tilt angle , and install an acceleration sensor on the trainee to monitor the body shaking speed in real time .

9. An intelligent billiards training system according to claim 8, characterized in that, The posture correction module further includes a first analysis unit, a second analysis unit and a third analysis unit; The first analysis unit is used to extract the centroid position , the pressure on the left foot of the trainer and the pressure on the right foot . After dimensionless processing, the stance stability factor is calculated through the following formula : ; In the formula, represents the total force on the body, , represents the maximum allowable offset distance of the center of gravity in the standing posture; represents the horizontal coordinate of the current center of gravity of the trainer, represents the coordinate of the current center of gravity of the trainer in the front-back direction; represents the horizontal coordinate of the center of gravity in the standard standing posture; represents the coordinate of the center of gravity in the front-back direction in the standard standing posture; If , it indicates that the center of gravity of the trainer is biased towards the right side; If , it means that the center of gravity of the trainer is biased towards the left; If , it indicates that the current center of gravity of the trainer is biased forward, resulting in a forward lean; If , it indicates that the current center of gravity of the trainer is biased backward, resulting in a backward tilt; The second analysis unit is configured to extract the actual grip pressure and calculate and obtain a grip stability factor through the following formula : ; In the formula, is the actual grip pressure, represents the optimal grip pressure, represents the maximum allowable grip pressure, represents the deviation value of the shaft angle during gripping, represents the maximum allowable deviation value of the grip angle; The closer it is to 1, the more stable the trainee's grip is. The third analysis unit is used to extract the forward and backward tilt angles and the body swaying speed , after dimensionless processing, the body balance factor is calculated and obtained through the following formula : ; In the formula, represents the maximum allowable tilt angle, represents the maximum allowable swaying speed.

10. An intelligent billiards training system according to claim 9, characterized in that, The posture correction module further includes a second correlation unit and a second warning unit; The second associated unit is used to extract the standing posture stability factor , the club-holding stability factor and the body balance factor . After dimensionless processing, the posture standard index is obtained through the following associated formula : ; In the formula, are respectively the weight coefficients of the standing posture stability factor, grip stability factor and body balance factor. The second warning unit is used to preset a postural standardization threshold Z and compare the postural standard index with the postural standardization threshold Z to determine whether the posture of the trainer is qualified, including: If the posture standard index <The posture standardization threshold Z indicates that the posture of the trainee during billiards training is unqualified, triggering the fourth warning signal and generating the second strategy, including: adjusting the current training plan, adjusting the standing posture, and adding 30s of standing posture balance training before each training. The standing posture balance training includes: single-leg standing training and core muscle group training; adjusting the standing position, and the center of gravity distribution is according to and getting closer, increasing the grip strength stability training by 5%; If the posture standard index ≥ the posture standardization threshold Z, it indicates that the posture of the trainer during billiards training is in a qualified state, and the current training plan continues to be carried out.

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