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CN-122007057-A - Automatic change and cut and detect branch cave balance device system

CN122007057ACN 122007057 ACN122007057 ACN 122007057ACN-122007057-A

Abstract

The invention relates to the technical field of cutting detection hole-separating swabs, in particular to an automatic cutting detection hole-separating swabs equipment system, which comprises a discharging module, a mold cavity number detection module, a cutting module, a visual detection module, a code printing module, a code scanning module, a swabs sorting module and a control module; the automatic feeding device comprises a discharging module, a die cavity number detection module, a cutting module, a visual detection module, a code printing module, a code scanning module, a tray sorting module, a control module and an intelligent algorithm, wherein the discharging module is used for automatically feeding a material, the die cavity number detection module is used for identifying a product die cavity number, the cutting module is used for cutting a product PIN foot, the visual detection module is used for detecting and positioning the quality of the PIN foot, the code printing module is used for marking a product, the code scanning module is used for reading and verifying code information, the tray sorting module is used for sorting the product according to the die cavity number, the control module is used for coordinating the working flow of each module and integrating the intelligent algorithm to optimize production parameters, full-flow automation is realized, manual intervention is greatly reduced, the production beat is improved, and the automatic feeding device is suitable for large-scale continuous production, and production efficiency and automation level are improved.

Inventors

  • LI WENYAO

Assignees

  • 坲尔德智能科技(苏州)有限公司

Dates

Publication Date
20260512
Application Date
20251225

Claims (10)

  1. 1. The automatic cutting, detecting and hole-dividing tray arranging equipment system is characterized by comprising a discharging module, a die cavity number detecting module, a cutting module, a visual detecting module, a code printing module, a code scanning module, a tray arranging and sorting module and a control module, wherein the discharging module is used for automatically supplying a feeding belt, the die cavity number detecting module is used for identifying a product die cavity number, the cutting module is used for cutting a product PIN foot, the visual detecting module is used for detecting and positioning the quality of the PIN foot, the code printing module is used for marking a product, the code scanning module is used for reading and verifying code information, the tray arranging and sorting module is used for sorting the product according to the die cavity number, and the control module is used for coordinating the work flow of each module and integrating intelligent algorithms to optimize production parameters.
  2. 2. The automated cavity-detecting and cavity-dividing wobble plate equipment system according to claim 1, wherein the control module comprises a cavity number identification and sorting optimization algorithm and a cutting parameter self-adaptive adjustment algorithm, wherein the cavity number identification and sorting optimization algorithm classifies cavity images in real time based on a deep learning model, and the cutting parameter self-adaptive adjustment algorithm dynamically adjusts cutting force and path according to PIN foot detection results.
  3. 3. The automated cavity detection and sorting wobble plate equipment system according to claim 2, wherein the step of the cavity number identification and sorting optimization algorithm comprises the steps of collecting cavity images and preprocessing, extracting features by using a convolutional neural network, continuously optimizing a model by combining historical sorting data, and outputting sorting instructions to a wobble plate sorting module.
  4. 4. The automated hole-dividing and cutting-detecting wobble plate equipment system according to claim 1, wherein the visual detection module comprises a multi-camera cooperative detection system and a triangular prism-based optical path refraction imaging system, forward and lateral PIN synchronous detection is achieved, and detection results are fed back to the cutting module and the coding module in real time to form closed-loop control.
  5. 5. The automated cut-and-detect split-cavity wobble plate equipment system of claim 1, further comprising a quality prediction and maintenance pre-warning subsystem and a real-time production billboard, wherein the quality prediction and maintenance pre-warning subsystem predicts equipment faults and maintenance periods through a machine learning algorithm based on production data and equipment state data, and the real-time production billboard displays indexes including production efficiency, yield and equipment state.
  6. 6. The automated hole-separating and cutting tray arranging equipment system according to claim 1, wherein the tray arranging and sorting module comprises an intelligent path planning algorithm and a self-adaptive suction nozzle pressure control system, wherein the intelligent path planning algorithm optimizes a carrying path according to the current tray arranging state and the next tray target, and the self-adaptive suction nozzle pressure control system dynamically adjusts the suction force according to the material and the weight of a product.
  7. 7. The automatic cutting detection hole-dividing pendulum disc equipment system of claim 1, wherein the system is characterized by supporting the docking with an MES system, realizing the automatic issuing of production orders, the uploading of real-time production data, the quality tracing and the report generation.
  8. 8. The automatic cutting, detecting and hole-dividing wobble plate equipment system according to claim 1 is characterized in that the control method comprises the steps of receiving a mold cavity number detection result, distributing the mold cavity number detection result to a corresponding wobble plate station according to a preset sorting rule, adjusting cutting and coding parameters according to a visual detection result, carrying out product identity verification and classification based on a code scanning result, optimizing equipment operation rhythm and energy consumption through an intelligent algorithm, monitoring equipment states in real time and early warning potential faults.
  9. 9. The automated cut-test split-cavity wobble plate system of claim 8, wherein the control method further comprises continuously optimizing the device operating parameters using a reinforcement learning algorithm.
  10. 10. The automated cut-test drop tray system of claim 8, wherein the control method further comprises adjusting the device operating strategy in conjunction with the environmental data.

Description

Automatic change and cut and detect branch cave balance device system Technical Field The invention relates to the technical field of cutting detection hole-separating wobble plates, in particular to an automatic cutting detection hole-separating wobble plate equipment system. Background The cutting, detecting and hole-separating tray arranging equipment is an integrated automatic system, and integrates key procedures of cutting, detecting, hole-separating, tray arranging and the like into an intelligent production line. The core function of the equipment is to realize full-link automation from raw material input to finished product finishing. The automatic material receiving and sorting machine is generally completed by a plurality of functional modules in a coordinated mode, wherein the cutting module is responsible for accurately cutting continuous materials, the detection module utilizes a vision system or a sensor to screen the quality of a workpiece and automatically identify good products and defective products, and the hole-separating tray module accurately distributes qualified products to corresponding material holes through a mechanical arm or a conveying mechanism to complete material receiving. However, the traditional cutting and detecting swinging disc flow is dependent on manual operation, has low efficiency and is easy to make mistakes, the traditional visual detection system has limited identification capability on products with different die cavity numbers, is easy to generate sorting errors, has insufficient detection precision and sorting accuracy, is fixed in technological parameters, cannot be dynamically adjusted according to PIN foot states, is easy to cause poor cutting, is unstable in cutting quality, depends on manual experience, is lack of intelligent maintenance mechanism in traditional equipment, has sudden failure to influence production continuity, is lack of early warning in equipment maintenance, is frequent in failure shutdown, is single in path fixing and absorbing force, is easy to cause product damage or inaccurate in arrangement, is difficult to realize seamless connection between a carrying path and an upper layer system such as an MES (manufacturing execution system), cannot upload and analyze production data in real time, is disjointed with a management system, cannot be dynamically adjusted according to production states, causes energy waste, and is high in energy consumption and is not optimized in operation rhythm. In view of the above, we propose an automatic cutting detection hole-separating wobble plate equipment system to solve the existing problems. Disclosure of Invention The invention aims to provide an automatic cutting detection hole-dividing pendulum disc equipment system so as to solve the problems in the background technology. The automatic cutting detection hole-dividing wobble plate equipment system comprises a discharging module, a mold cavity number detection module, a cutting module, a visual detection module, a code printing module, a code scanning module, a wobble plate sorting module and a control module, wherein the discharging module is used for automatically supplying a feeding belt, the mold cavity number detection module is used for identifying a product mold cavity number, the cutting module is used for cutting a product PIN foot, the visual detection module is used for detecting and positioning the quality of the PIN foot, the code printing module is used for marking a product, the code scanning module is used for reading and verifying code information, the wobble plate sorting module is used for sorting the product according to the mold cavity number, and the control module is used for coordinating the work flow of each module and integrating intelligent algorithms to optimize production parameters. The control module further comprises a die cavity number identification and sorting optimization algorithm and a cutting parameter self-adaptive adjustment algorithm, wherein the die cavity number identification and sorting optimization algorithm classifies die cavity images in real time based on the deep learning model, and the cutting parameter self-adaptive adjustment algorithm dynamically adjusts cutting force and path according to the PIN foot detection result. Further, the mold cavity number identification and sorting optimization algorithm comprises the steps of collecting mold cavity images, preprocessing, extracting features by using a convolutional neural network, continuously optimizing a model by combining historical sorting data, and outputting a sorting instruction to a wobble plate sorting module. Further, the visual detection module comprises a multi-camera cooperative detection system and a light path refraction imaging system based on a triangular prism, forward and lateral PIN synchronous detection is achieved, and detection results are fed back to the cutting module and the coding module in real time to form closed-loop