Feeding device for balance shaft machining

Abstract

The invention relates to the technical field of feeding devices, in particular to a feeding device for balance shaft machining. The feeding device comprises a belt conveyor, a guide hopper is arranged at one end of the belt conveyor, a plurality of bases are fixedly connected to the outer portion of the belt conveyor, connecting rods are fixedly connected to the bases, and a supporting plate is fixedly connected to the tops of the connecting rods; a clamping assembly used for clamping the balance shaft is arranged on the supporting plate, a pushing assembly is arranged on one side of the outer portion of the belt conveyor, and the pushing assembly pushes the clamping assembly. The balance shaft is placed on the supporting plate and can be conveyed through the belt conveyor, then the balance shaft is automatically transferred to other places through the transferring assembly, and therefore the manual operation time and the feeding period are greatly shortened. Compared with traditional manual feeding, the feeding efficiency can be improved, and the productivity of a balance shaft machining production line is remarkably improved.

Description

Technical Field

[0001] The invention relates to the technical field of feeding devices, in particular to a feeding device for processing a balancing shaft. Background Art

[0002] In the balance shaft processing industry, the traditional loading method often relies on manual handling of the balance shafts one by one to the loading position of the processing equipment. This manual loading method has many disadvantages. First, manual operation is inefficient and difficult to meet the needs of large-scale production. As the scale of production expands, labor costs will also rise sharply. Second, the accuracy of manual loading is limited. During the process of carrying and placing the balance shaft, position deviation is prone to occur, which affects the subsequent processing accuracy and leads to unstable product quality. Summary of the invention

[0003] In view of the technical problems raised in the background technology, the present invention provides a feeding device for processing a balance shaft.

[0004] The technical solution adopted by the present invention is: a feeding device for balancing shaft processing, comprising a belt conveyor, a guide bucket is provided at one end of the belt conveyor, a plurality of groups of bases are fixedly connected to the outside of the belt conveyor, a connecting rod is fixedly connected to the base, a support plate is fixedly connected to the top of the connecting rod, a clamping assembly for clamping the balancing shaft is provided on the support plate, a pushing assembly is provided on one side of the outside of the belt conveyor, after the pushing assembly pushes the clamping assembly, the balancing shaft on the support plate is pushed out to the guide bucket, and a transfer assembly is also provided on one side of the outside of the belt conveyor.

[0005] In one of the embodiments, a proximity sensor is fixedly embedded inside the guide bucket.

[0006] In one of the embodiments, through holes are provided on all four sides of the top of the support plate, and the clamping assembly includes a clamping plate rotatably connected in the through hole, a guide frame fixedly connected to the base, and a sliding seat slidably connected to both sides of the guide frame, the outside of the clamping plate is fixedly connected to a pull rod, the inside of the guide frame is fixedly connected to a limit rod, the limit rod passes through the sliding seat, the outside of the sliding seat is hinged with a first connecting rod, the first connecting rod is rotatably connected to the pull rod, the outside of the sliding seat is also fixedly connected to a sliding rod, the outside of the sliding rod is fixedly connected to an inclined plate, the support plate is also fixedly connected to a guide rod, the outside of the guide rod is penetrated by a slider, the outside of the slider is fixedly connected to a fixed plate, and the top of the slider is rotatably connected to a resistance wheel.

[0007] In one embodiment, the outer sleeve of the limiting rod is provided with a second spring, and the outer sleeve of the guiding rod is provided with a first spring.

[0008] In one embodiment, the pushing assembly includes a fixed frame fixedly connected to the outside of the belt conveyor and a motor rotatably connected to the fixed frame, the output end of the motor is fixedly connected to the threaded rod, the external thread of the threaded rod is connected to a push plate, the outside of the belt conveyor is fixedly connected to a guide plate, the outside of the push plate is fixedly connected to a first push rod, the first push rod penetrates the guide plate, the outside of the first push rod is fixedly connected to a synchronization plate, and the outside of the synchronization plate is fixedly connected to a second push rod.

[0009] In one embodiment, the transfer assembly includes a six-axis robotic arm and a support platform fixedly connected to the bottom of the six-axis robotic arm, and an output end of the six-axis robotic arm is fixedly connected to an electric gripper.

[0010] In one of the embodiments, a control system is further included, and the control system includes a visual sensing module and a control module.

[0011] In one embodiment, the visual sensing module is a plurality of sets of high-definition industrial cameras fixedly connected above the guide bucket.

[0012] In one embodiment, the control module processes the image captured by the visual sensor module based on a deep learning target detection algorithm, and the specific steps are as follows:

[0013] Firstly, a large number of image samples of the balance shaft are trained to enable the algorithm to recognize the features of the balance shaft. For the positioning of the balance shaft, a method combining feature point matching and geometric calculation is adopted.

[0014] By identifying the centers of the two ends of the balancing shaft as feature points, their coordinates in the image coordinate system are calculated, and then combined with the calibration parameters of the high-definition industrial camera, the image coordinates are converted into actual space coordinates;

[0015] Assume that the coordinates of the center of one end of the balance axis in the image are (x1, y1), the intrinsic parameter matrix of the camera is K, and the extrinsic parameter matrix is ​​[R|T]. Then the coordinates of the balance axis in the actual space (X1, Y1, Z1) can be calculated by the following formula:

[0016]

[0017] In one embodiment, the control module further includes controlling the speed of the six-axis robot arm, and the movement speed v of the six-axis robot arm is m The fuzzy control rules are:

[0018]

[0019] Among them, T1, T2, T3, etc. are the input fuzzy variables, namely the weight of the balancing shaft, surface roughness, and urgency of the production task, and C1, C2, etc. are the corresponding fuzzy control output values, namely the movement speed of the six-axis robot arm;

[0020] Among them, according to the balance axis position and posture information determined by the visual recognition system, the control module determines the grasping strategy. During the grasping process, the motion trajectory planning of the six-axis robot arm adopts the method combining the A algorithm with the spline curve interpolation;

[0021] The A algorithm is used to determine the path from the initial position of the six-axis robot to the grasping position of the balance axis, and the spline curve interpolation is used to smooth the path;

[0022] Assume that the joint angle vector of the six-axis robot is θ(t) = [θ1(t), θ2(t), …, θ6(t)], and the spline curve interpolation formula is:

[0023]

[0024] Among them, N i,k (t) is the k-order B-spline basis function, P i is the control point of the joint angle, and n is the number of control points. By adjusting the position of the control point and the number of spline curves, smooth motion trajectories with different requirements can be obtained.

[0025] Wherein, the control module also includes thrust control of the second push rod, and the thrust F of the second push rod and the input current I of the motor satisfy a linear relationship F=k1I (where k1 is the thrust coefficient);

[0026] During the ejection process, the PID control algorithm is used to accurately control the movement of the second push rod to ensure a stable ejection speed and accurate position. The formula of the PID control algorithm is:

[0027]

[0028] Where, u(t) is the control signal of the motor (related to the input current), K P is the proportionality coefficient, K I is the integration coefficient, K D is the differential coefficient, and e(t) is the error signal between the set position and the actual position.

[0029] The beneficial effects of the present invention are:

[0030] 1. Compared with the prior art, in the present invention, by placing the balancing shaft on the support plate, the balancing shaft can be transported by a belt conveyor, and then the balancing shaft is automatically transported to other ends by the transfer component, thereby greatly reducing the manual operation time and loading cycle. Compared with traditional manual loading, the loading efficiency can be improved, so that the production capacity of the balancing shaft processing production line is significantly improved.

[0031] 2. Compared with the prior art, the present invention can accurately identify the position, shape and size of the balance shaft through a high-precision visual sensor module and a six-axis robotic arm, and achieve precise grasping and placement. Compared with the traditional feeding method, the feeding accuracy is effectively improved, providing a good foundation for subsequent processing. The deep learning image recognition algorithm enables the system to adapt to balance shafts of different specifications and shapes, without the need for complex parameter adjustments for each type of balance shaft, thereby automatically realizing an intelligent feeding system. In summary, this embodiment integrates advanced visual recognition, intelligent control, robotics technology, etc., and realizes a fully automated intelligent process from material temporary storage, identification and grasping to conveyor belt transportation. The overall intelligence level of the equipment has been improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the structure of the present invention;

[0033] Figure 2 It is a schematic diagram of the axonometric structure of the present invention;

[0034] Figure 3 yes Figure 1 Schematic diagram of the enlarged structure of the A area in the middle;

[0035] Figure 4 yes Figure 2 Schematic diagram of the enlarged structure of the middle B area;

[0036] Figure 5 It is a structural schematic diagram of the belt conveyor in the present invention;

[0037] Figure 6 It is a structural schematic diagram of the base in the present invention;

[0038] Figure 7 It is a structural schematic diagram of the base and the clamping plate in the present invention;

[0039] Figure 8 It is a structural schematic diagram of the slider in the present invention.

[0040] The markings in the figure are:

[0041] 100. Belt conveyor; 1001. Guide bucket; 1002. Proximity sensor;

[0042] 200, six-axis robotic arm; 2001, support platform;

[0043] 300, base; 3001, support plate; 3002, through hole; 3003, connecting rod; 3004, guide rod; 3005, slider; 3006, fixing plate; 3007, first spring; 3008, guide frame; 3009, sliding seat; 30010, limit rod; 30011, second spring; 30012, first connecting rod; 30013, pull rod; 30014, slide rod; 30015, inclined plate; 30016, abutment wheel; 30017, clamping plate;

[0044] 400, fixed frame; 4001, motor; 4002, threaded rod; 4003, push plate; 4004, first push rod; 4005, synchronous plate; 4006, guide plate; 4007, second push rod. DETAILED DESCRIPTION

[0045] In the description of the present invention, it should be noted that the orientations or positional relationships indicated by terms such as “front”, “up”, “down”, “left”, “right”, “vertical” and “horizontal” are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0046] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0047] The following is combined with Figure 1-8 The present invention is further described.

[0048] Embodiment 1:

[0049] In order to solve the problems existing in the background technology, the present application proposes the following technical solutions: a feeding device for balancing shaft processing, comprising a belt conveyor 100, a guide bucket 1001 is provided at one end of the belt conveyor 100, and multiple groups of bases 300 are fixedly connected to the outside of the belt conveyor 100, and a connecting rod 3003 is fixedly connected to the base 300, and a support plate 3001 is fixedly connected to the top of the connecting rod 3003. The support plate 3001 is a V-shaped structure, and the support plate 3001 is used to place the balancing shaft.

[0050] In this embodiment, a clamping assembly for clamping the balancing shaft is further provided on the support plate 3001 .

[0051] In a specific design, a proximity sensor 1002 is fixedly embedded inside the guide bucket 1001 , and the proximity sensor 1002 is used to detect whether the balance shaft falls on the guide bucket 1001 .

[0052] In a further design, through holes 3002 are provided around the top of the support plate 3001, and the clamping assembly includes a clamping plate 30017 rotatably connected to the through hole 3002, a guide frame 3008 fixedly connected to the base 300, and a sliding seat 3009 slidably connected to both sides of the guide frame 3008. The outside of the clamping plate 30017 is fixedly connected to a pull rod 30013, and the guide frame 3008 is fixedly connected to a limit rod 30010, which passes through the sliding seat 3009. The outside of the sliding seat 3009 is hinged with a first link, and the first link 30012 is rotatably connected to the pull rod 30013. The outside of the sliding seat 3009 is also A sliding rod 30014 is fixedly connected, and an inclined plate 30015 is fixedly connected to the outside of the sliding rod 30014. A guide rod 3004 is also fixedly connected to the support plate 3001. A slider 3005 is penetrated through the outside of the guide rod 3004. A fixed plate 3006 is fixedly connected to the outside of the slider 3005. A resistance wheel 30016 is rotatably connected to the top of the slider 3005. A second spring 30011 is sleeved on the outside of the limit rod 30010, and a first spring 3007 is sleeved on the outside of the guide rod 3004. Both the first spring 3007 and the second spring 30011 play a resetting role, allowing the sliding seat 3009 and the slider 3005 to reset to their initial positions.

[0053] The above technical solution is explained as follows: the balance shaft is placed on the support plate 3001, clamped and fixed by the clamping plate 30017, and transported by the belt conveyor 100. After being transported to the side close to the guide bucket 1001, the fixed plate 3006 is resisted by the pushing component, and the fixed plate 3006 drives the slider 3005 to slide, and the slider 3005 drives the resistance wheel 30016 to resist the inclined plate 30015, so that the two sliding bars 30014 on the two support plates 3001 can slide back to back, and the sliding bar 30014 drives the sliding seat 3009 to slide, so that by pulling the pull rod 30013, the clamping plate 30017 can be rotated outward, and the balance shaft is no longer clamped and fixed.

[0054] In this embodiment, a pushing component is provided on the outer side of the belt conveyor 100. After the pushing component pushes the clamping component, it pushes the balancing shaft on the support plate 3001 onto the guide bucket 1001. A transfer component is also provided on the outer side of the belt conveyor 100.

[0055] The pushing assembly includes a fixing frame 400 fixedly connected to the outside of the belt conveyor 100 and a motor 4001 rotatably connected to the fixing frame 400, the output end of the motor 4001 is fixedly connected to the threaded rod 4002, the external thread of the threaded rod 4002 is connected to the push plate 4003, the external of the belt conveyor 100 is fixedly connected to the guide plate 4006, the external of the push plate 4003 is fixedly connected to the first push rod 4004, the first push rod 4004 penetrates the guide plate 4006, and the first push rod 4004 004 is fixedly connected to the outside with a synchronization plate 4005, and the synchronization plate 4005 is fixedly connected to the outside with a second push rod 4007. The motor 4001 drives the threaded rod 4002 to move, so that the push plate 4003 moves outside the threaded rod 4002 until the first push rod 4004 contacts the fixed plate 3006, thereby achieving pushing, and the first push rod 4004 drives the second push rod 4007 to slide, so that the balance shaft can be pushed into the guide bucket 1001 through the push of the second push rod 4007.

[0056] In this embodiment, the transfer assembly includes a six-axis robot arm 200 and a support platform 2001 fixedly connected to the bottom of the six-axis robot arm 200. The output end of the six-axis robot arm 200 is fixedly connected to an electric clamp, which is used to clamp and transfer the balance shaft.

[0057] In order for those skilled in the art to fully understand the technical solution, the method of using this embodiment is as follows:

[0058] The balancing shaft is placed on the support plate 3001, clamped and fixed by the clamping plate 30017, and transported by the belt conveyor 100. After being transported to the side close to the guide bucket 1001, the motor 4001 drives the threaded rod 4002 to move, so that the push plate 4003 moves outside the threaded rod 4002 until the first push rod 4004 contacts the fixed plate 3006, and the fixed plate 3006 drives the slider 3005 to slide, and the slider 3005 drives the contact wheel 30016 to contact the inclined plate 30015, so that the two slide bars 30014 on the two support plates 3001 can slide back to back, and the slide bars 30014 drive the sliding seat 3009 to slide, so that the clamping plate 30017 can be rotated outward by pulling the pull rod 30013, and no longer clamp and fix the balancing shaft;

[0059] At this time, the first push rod 4004 drives the second push rod 4007 to slide, so that the balance shaft can be pushed into the guide bucket 1001 through the push of the second push rod 4007, and then the balance shaft can be clamped and transported by the six-axis robot arm 200.

[0060] Embodiment 2:

[0061] The present embodiment is different from the first embodiment in that the present embodiment further includes a control system, and the control system includes a visual sensor module and a control module.

[0062] Among them, the visual sensing module is a group of high-definition industrial cameras fixedly connected above the guide bucket.

[0063] Among them, the control module processes the images taken by the visual sensor module based on the target detection algorithm of deep learning. The specific steps are as follows:

[0064] Firstly, a large number of image samples of the balance shaft are trained to enable the algorithm to recognize the features of the balance shaft. For the positioning of the balance shaft, a method combining feature point matching and geometric calculation is adopted.

[0065] By identifying the centers of the two ends of the balancing shaft as feature points, their coordinates in the image coordinate system are calculated, and then combined with the calibration parameters of the high-definition industrial camera, the image coordinates are converted into actual space coordinates;

[0066] Assume that the coordinates of the center of one end of the balance axis in the image are (x1, y1), the intrinsic parameter matrix of the camera is K, and the extrinsic parameter matrix is ​​[R|T]. Then the coordinates of the balance axis in the actual space (X1, Y1, Z1) can be calculated by the following formula:

[0067]

[0068] The above technical solution is explained as follows: In this implementation, multiple groups of high-definition industrial cameras are used as visual sensing modules, which can obtain high-precision image data and lay the foundation for subsequent precise detection. Secondly, the control module is based on a target detection algorithm based on deep learning. By training a large number of balance shaft image samples, it can accurately identify the characteristics of the balance shaft with high positioning accuracy. This method combines feature point matching and geometric calculation. By identifying the center of the circle at both ends of the balance shaft as feature points, and combining the calibration parameters of the camera, the image coordinates are converted into actual space coordinates. The calculation process is scientific and reasonable, ensuring the accuracy of coordinate conversion. This system can effectively improve the efficiency and quality of balance shaft detection in industrial production, reduce the errors of manual detection, and thus improve the reliability and stability of the entire production process.

[0069] The control module also includes speed control for the six-axis robot arm 200. The movement speed v of the six-axis robot arm 200 is m The fuzzy control rules are:

[0070]

[0071] Among them, T1, T2, T3, etc. are input fuzzy variables, namely, the weight of the balancing shaft, the surface roughness, and the urgency of the production task, and C1, C2, etc. are corresponding fuzzy control output values, namely, the movement speed of the six-axis robot arm 200;

[0072] Among them, according to the balance axis position and posture information determined by the visual recognition system, the control module determines the grasping strategy. During the grasping process, the motion trajectory planning of the six-axis robot arm 200 adopts a method combining the A algorithm with the spline curve interpolation;

[0073] The A algorithm is used to determine the path from the initial position of the six-axis robot 200 to the grasping position of the balance axis, and the spline curve interpolation is used to smooth the path;

[0074] Assume that the joint angle vector of the six-axis robot arm 200 is θ(t) = [θ1(t), θ2(t), …, θ6(t)], and the spline curve interpolation formula is:

[0075]

[0076] Among them, N i,k (t) is the k-order B-spline basis function, P i is the control point of the joint angle, and n is the number of control points. By adjusting the position of the control point and the number of spline curves, smooth motion trajectories with different requirements can be obtained.

[0077] The control module further includes thrust control of the second push rod, and the thrust F of the second push rod and the input current I of the motor satisfy a linear relationship F=k1I (where k1 is the thrust coefficient);

[0078] During the ejection process, the PID control algorithm is used to accurately control the movement of the second push rod to ensure a stable ejection speed and accurate position. The formula of the PID control algorithm is:

[0079]

[0080] Where, u(t) is the control signal of the motor (related to the input current), K P is the proportionality coefficient, K I is the integration coefficient, K D is the differential coefficient, and e(t) is the error signal between the set position and the actual position.

[0081] In summary, the position and posture information of the balance axis are determined by the visual recognition system, which provides an accurate data basis for the motion trajectory planning of the six-axis robot 200. The method of combining the A algorithm with the spline curve interpolation is adopted. The A algorithm can efficiently determine the path from the initial position of the six-axis robot 200 to the grasping position of the balance axis, and the spline curve interpolation can smooth the path, making the movement of the six-axis robot 200 smoother and more accurate. Secondly, a specific formula is used for the spline curve interpolation of the joint angle vector of the six-axis robot 200. By adjusting the position of the control point and the number of spline curves, a smooth motion trajectory that meets different requirements can be obtained, which greatly improves the adaptability of the six-axis robot 200 in complex operations. In addition, a linear relationship is used for the thrust control of the second push rod, and a PID control algorithm is used during the push-out process to ensure the precise control of the movement of the second push rod, which can ensure a stable push-out speed and accurate position, reduce operating errors, and improve overall work efficiency and quality.

[0082] The above technical solution is explained as follows:

[0083] Through the high-precision visual sensing module and the six-axis robot arm 200, the position, shape and size of the balance shaft can be accurately identified, and precise grasping and placement can be achieved. Compared with the traditional feeding method, the feeding accuracy is effectively improved, providing a good foundation for subsequent processing. The deep learning image recognition algorithm enables the system to adapt to balance shafts of different specifications and shapes, without the need for complex parameter adjustments for each type of balance shaft, so that the automatic intelligent feeding system greatly reduces manual operation time and feeding cycle. Compared with traditional manual feeding, the feeding efficiency can be improved, and the production capacity of the balance shaft processing production line can be significantly improved. In summary, this embodiment integrates advanced visual recognition, intelligent control, robotics technology, etc., and realizes a fully automated intelligent process from material temporary storage, identification and grasping to conveyor belt transportation. Improve the overall intelligence level of the equipment.

[0084] The standard parts used in the present invention can all be purchased from the market, and special-shaped parts can be customized according to the description in the specification and the drawings. The specific connection methods of each part adopt conventional means such as mature bolts, rivets, welding, etc. in the prior art. Machinery, parts and equipment all adopt conventional models in the prior art, and the circuit connection adopts the conventional connection method in the prior art, which will not be described in detail here. The content not described in detail in this specification belongs to the prior art known to professional and technical personnel in this field.

[0085] While the embodiments of the present invention have been shown and described, it will be apparent to those skilled in the art that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A feeding device for processing a balancing shaft, comprising a belt conveyor (100), characterized in that: A guide bucket (1001) is provided at one end of the belt conveyor (100), and a plurality of bases (300) are fixedly connected to the outside of the belt conveyor (100), and a connecting rod (3003) is fixedly connected to the base (300), and a support plate (3001) is fixedly connected to the top of the connecting rod (3003), and a clamping assembly for clamping a balancing shaft is provided on the support plate (3001), and a pushing assembly is provided on one side of the outside of the belt conveyor (100), and after the pushing assembly pushes the clamping assembly, the balancing shaft on the support plate (3001) is pushed out onto the guide bucket (1001), and a transfer assembly is also provided on one side of the outside of the belt conveyor (100).

2. A feeding device for processing a balancing shaft according to claim 1, characterized in that: A proximity sensor (1002) is fixedly embedded inside the guide bucket (1001).

3. A feeding device for processing a balance shaft according to claim 1, characterized in that: The top of the support plate (3001) is provided with through holes (3002) on all sides, and the clamping assembly includes a clamping plate (30017) rotatably connected to the through hole (3002), a guide frame (3008) fixedly connected to the base (300), and a sliding seat (3009) slidably connected to both sides of the guide frame (3008), the clamping plate (30017) is fixedly connected to the outside with a pull rod (30013), the guide frame (3008) is fixedly connected to a limit rod (30010), the limit rod (30010) passes through the sliding seat (3009), and the sliding seat (3009) is fixedly connected to the outside with a pull rod (30013), and the guide frame (3008) is fixedly connected to the inside with a limit rod (30010), and the limit rod (30010) passes through the sliding seat (3009). A first connecting rod (30012) is hinged on the outside, and the first connecting rod (30012) is rotatably connected to the pull rod (30013). The outside of the sliding seat (3009) is also fixedly connected to a sliding rod (30014), and the outside of the sliding rod (30014) is fixedly connected to an inclined plate (30015). The support plate (3001) is also fixedly connected to a guide rod (3004), and a slider (3005) is provided on the outside of the guide rod (3004). The outside of the slider (3005) is fixedly connected to a fixed plate (3006), and the top of the slider (3005) is rotatably connected to a contact wheel (30016).

4. A feeding device for processing a balancing shaft according to claim 3, characterized in that: The outer sleeve of the limiting rod (30010) is provided with a second spring (30011), and the outer sleeve of the guiding rod (3004) is provided with a first spring (3007).

5. A feeding device for processing a balance shaft according to claim 4, characterized in that: The pushing assembly comprises a fixing frame (400) fixedly connected to the outside of the belt conveyor (100) and a motor (4001) rotatably connected to the fixing frame (400), the output end of the motor (4001) being fixedly connected to a threaded rod (4002), the external thread of the threaded rod (4002) being connected to a push plate (4003), the external of the belt conveyor (100) being fixedly connected to a guide plate (4006), the external of the push plate (4003) being fixedly connected to a first push rod (4004), the first push rod (4004) passing through the guide plate (4006), the external of the first push rod (4004) being fixedly connected to a synchronization plate (4005), the external of the synchronization plate (4005) being fixedly connected to a second push rod (4007).

6. A feeding device for processing a balance shaft according to claim 5, characterized in that: The transfer assembly comprises a six-axis robotic arm (200) and a support platform (2001) fixedly connected to the bottom of the six-axis robotic arm (200), and an electric gripper is fixedly connected to the output end of the six-axis robotic arm (200).

7. A feeding device for processing a balance shaft according to claim 6, characterized in that: It also includes a control system, which includes a visual sensor module and a control module.

8. The feeding device for processing a balance shaft according to claim 7, characterized in that: The visual sensing module is a plurality of groups of high-definition industrial cameras fixedly connected above the guide bucket (1001).

9. A feeding device for processing a balance shaft according to claim 8, characterized in that: The control module processes the image captured by the visual sensor module based on the target detection algorithm of deep learning. The specific steps are as follows: Firstly, a large number of image samples of the balance shaft are trained to enable the algorithm to recognize the features of the balance shaft. For the positioning of the balance shaft, a method combining feature point matching and geometric calculation is adopted. By identifying the centers of the two ends of the balancing shaft as feature points, their coordinates in the image coordinate system are calculated, and then combined with the calibration parameters of the high-definition industrial camera, the image coordinates are converted into actual space coordinates; let the coordinates of the center of one end of the balancing shaft in the image be ( x1,y 1) , the camera's internal parameter matrix is ​​K, and the external parameter matrix is [ R|T ] , then the coordinates of the equilibrium axis in real space are ( X1, Y1, Z1) can be calculated by the following formula:

10. A feeding device for processing a balancing shaft according to claim 9, characterized in that: The control module further comprises a step of controlling the speed of the six-axis robot arm (200), wherein the movement speed v of the six-axis robot arm (200) is m The fuzzy control rules are: Among them, T1, T2, T3, etc. are the input fuzzy variables, namely the weight of the balancing shaft, surface roughness, and urgency of the production task, and C1, C2, etc. are the corresponding fuzzy control output values, namely the movement speed of the six-axis robot arm; According to the balance axis position and posture information determined by the visual recognition system, the control module determines the grasping strategy, and during the grasping process, the motion trajectory planning of the six-axis robot arm (200) adopts a method combining the A algorithm with the spline curve interpolation; Algorithm A is used to determine a path from an initial position of the six-axis robot arm (200) to a grasping position of the balancing axis, and spline curve interpolation is used to smooth the path; Assuming that the joint angle vector of the six-axis robot arm (200) is θ(t)=[θ1(t),θ2(t),…,θ6(t)], the spline curve interpolation formula is: Among them, N i , k(t) is the k-order B-spline basis function, P i is the control point of the joint angle, and n is the number of control points. By adjusting the position of the control point and the number of spline curves, smooth motion trajectories with different requirements can be obtained. The control module further includes thrust control of the second push rod (4007), and the thrust F of the second push rod (4007) and the input current I of the motor (4001) satisfy a linear relationship F=k1I (where k1 is the thrust coefficient); During the ejection process, the PID control algorithm is used to accurately control the movement of the second push rod (4007) to ensure a stable ejection speed and accurate position. The formula of the PID control algorithm is: Wherein, u(t) is the control signal of the motor (4001) (related to the input current), K P is the proportionality coefficient, K I is the integration coefficient, K D is the differential coefficient, and e(t) is the error signal between the set position and the actual position.

Images