Gripper-Based Rotation Classification for Resonance-Safe Workpiece Sorting
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Solution Overview
Problem
Despite advancements in manufacturing techniques, workpieces made of materials like plastics often exhibit varying rotation parameters, leading to resonance phenomena and increased material stress in rotary applications, which can be mitigated by grouping workpieces with similar measurement values for uniform rotation.
Innovation Solution
A computer-controlled gripping system that uses optical recognition to grip workpieces via predetermined reference points, performs reference movements, and records rotation data to determine and classify workpieces based on rotation parameters, enabling automated sorting and placement in designated positions for uniform processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If workpieces are used without rotation classification, then productivity is maintained, but resonance phenomena occur causing increased material stress and reduced reliability
Solution Approach 1:
The system performs preliminary measurement of rotation parameters and classification of workpieces before they are used in production. By determining the rotation characteristics in advance and grouping workpieces with similar parameters, the system prevents resonance phenomena from occurring during actual operation, thereby improving reliability without reducing productivity
Solution Approach 2:
The system uses sensors to measure rotation parameters of workpieces and provides feedback to the control unit. Based on this feedback, workpieces are automatically classified and sorted into different groups. This closed-loop feedback mechanism ensures that only workpieces with appropriate rotation characteristics are selected for specific applications, eliminating resonance issues while maintaining efficient production flow
2Measurement precision
If rotation parameters are measured and classification is performed, then workpiece sorting accuracy is improved, but device complexity increases
Solution Approach 1:
The gripper arm serves multiple functions: it performs reference movements for measurement, acts as a positioning device, and functions as part of the classification system. The sensor system is integrated into the existing robotic gripper structure, allowing the same hardware to perform both gripping and measurement tasks, thereby reducing overall system complexity while maintaining high measurement precision
Solution Approach 2:
The control unit acts as an intermediary that processes sensor data and coordinates the classification process. It receives rotation parameter data from sensors, compares measurements against predefined criteria, and automatically directs workpieces to appropriate sorting locations. This centralized control approach simplifies the system architecture by consolidating intelligence in a single unit rather than distributing complexity across multiple components
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system allows for reliable classification and sorting of workpieces based on reproducible dynamic properties, reducing resonance issues and enabling precise processing, particularly beneficial in the production of wind turbines where uniform rotation parameters minimize vibrations.
Implementation Method 1
grip the workpiece based on an optical detection of the workpiece via at least two predetermined reference receiving points
Implementation Method 2
record and output rotation data during execution of the reference movements via a gripping sensor system integrated in the computer-controlled gripper arm
Data Source
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AI summary
A gripping system (100) for sorting a plurality of workpieces (105), comprising a computer-controlled gripper arm (110) and a control unit (130). The gripper arm is configured to grasp the workpiece based on optical recognition of the workpiece via at least two predetermined reference gripping points (112, 113), and to perform a plurality of predetermined reference movements (118) with the grasped workpiece. During execution, rotation data (122) is acquired and output via gripper sensors (120) integrated into the gripper arm. The control unit is configured to control movements of the computer-controlled gripper arm, to determine a plurality of rotation parameters (132) of the workpiece based on the output rotation data, and based on this, to assign a rotation classification (134) to the workpiece and to control the sorting of the gripped workpiece based on the rotation classification.