Robot Subassembly Fault Diagnosis During Continuous Operation
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Solution Overview
Problem
Current robot diagnosis methods are inadequate as they fail to identify failure sources at the subassembly level and require robots to stop operating, disrupting production and causing economic losses by relying on specific motion cycles for data comparison.
Innovation Solution
A method and device that obtain and analyze motion signals from rotating components during operation to determine frequency amplitudes based on physical characteristics and speed, allowing for real-time failure detection by comparing these amplitudes with threshold values, enabling accurate subassembly-level diagnosis without interrupting normal production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robot diagnosis is performed using system level abnormality detection, then diagnosis coverage is achieved, but failure source identification accuracy deteriorates
Solution Approach 1:
The patent segments the robot system into multiple rotating components (motors, gearboxes, etc.) and further divides them into sub-components (bearings, gears, shafts). By analyzing vibration signals at this granular level, the system achieves both comprehensive coverage and precise failure source identification, resolving the contradiction between diagnosis coverage and accuracy.
Solution Approach 2:
The patent transitions from system-level diagnosis to component-level diagnosis by introducing a new dimension of analysis - the rotating component dimension. This dimensional shift enables precise localization of failure sources while maintaining comprehensive diagnosis coverage through spectrum analysis of multiple components simultaneously.
2Measurement precision
If robot stops working for data measurement under specific motion cycle, then failure source identification becomes possible, but production efficiency deteriorates
Solution Approach 1:
The patent enables continuous vibration signal acquisition during normal robot operation without requiring shutdowns or specific motion cycles. The spectrum analysis is performed on data collected continuously during production, maintaining both diagnostic capability and production efficiency simultaneously.
Solution Approach 2:
The system performs preliminary spectrum analysis on vibration signals during normal operation to identify potential failures before they cause downtime. This preliminary detection allows for planned maintenance rather than emergency shutdowns, preserving production efficiency while enabling accurate failure identification.
3Measurement precision
If diagnosis requires specific motion cycle, then failure detection accuracy improves, but time loss increases
Solution Approach 1:
The patent eliminates the requirement for specific motion cycles by performing continuous spectrum analysis on vibration signals during normal robot operation. This approach achieves accurate failure detection without any production interruption, resolving the time loss issue while maintaining detection accuracy.
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
Enables early detection of failures on subassembly level, reducing downtime and economic losses by allowing for continuous operation and precise identification of faulty components, thus extending the life of robots.
Implementation Method 1
obtaining a spectrum of a motion signal generated by a rotating component of the robot during operation of the robot; determining a frequency amplitude of a sub-component of the rotating component from the spectrum
Data Source
AI summary
Methods and devices for diagnosing a robot. A method includes obtaining a spectrum of a motion signal generated by a rotating component of the robot during operation of the robot. A frequency amplitude of a sub-component of the rotating component is determined from the spectrum, based on a physical characteristic and a speed of the sub-component. A failure of the sub-component is detected by comparing the frequency amplitude with a threshold amplitude.