Robot Condition Detection via Work Cycle Data Synchronization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for monitoring the health condition of industrial robot manipulators are largely manual and lack a systematic way to synchronize data from different production cycles, making it difficult to compare and analyze changes in motion data for predictive maintenance.
Innovation Solution
An algorithmic method for synchronizing and comparing work cycle data from different occasions by selecting a reference signal, logging it at two occasions, identifying identical batches, and analyzing deviations in the time and frequency domains to detect condition changes in robot systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual methods are used to indicate health condition of robot manipulator, then service engineer can interpret signals, but the method is not automatic and requires skilled personnel
Solution Approach 1:
The robot system performs self-diagnosis by automatically collecting and analyzing its own operational data. The system monitors its own health condition through automated comparison of work cycle data, eliminating the need for manual inspection by service engineers while maintaining detection capability.
Solution Approach 2:
The patent replaces manual mechanical inspection methods with automated electronic data analysis. By substituting the engineer's auditory and interpretive skills with automated signal processing and statistical analysis algorithms, the system achieves automatic health indication without requiring skilled personnel.
2Measurement precision
If data from different production cycles are compared without synchronization, then production continues without interruption, but the data cannot be directly compared due to timing differences
Solution Approach 1:
The patent introduces a reference signal as an intermediary element that mediates the comparison between different work cycle data sets. This reference signal serves as a common temporal framework that enables synchronization and direct comparison of otherwise incompatible data from different production cycles.
Solution Approach 2:
The system transforms the temporal parameters of work cycle data by aligning them to a reference signal. By changing the time reference frame of the collected data through synchronization algorithms, the patent enables meaningful comparison while maintaining continuous production operation.
3Reliability
If traditional six-axis manipulator is used, then sufficient movability and high accuracy are achieved, but maintenance requires breakdown or scheduled stops
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors robot health indicators and provides information about deteriorating conditions. This feedback loop enables predictive maintenance by alerting operators to potential failures before they occur, allowing maintenance to be scheduled at optimal times rather than waiting for breakdowns.
Solution Approach 2:
The system performs preliminary detection of health condition changes by analyzing work cycle data patterns. By identifying early signs of deterioration through automated comparison and statistical analysis, the patent enables preventive action to be taken before actual failures occur, reducing unplanned downtime.
Data Source
Figure 1A~1B
Figure 2
Figure 3
AI summary
A method for detecting condition changes in a robot system, wherein said method comprises a logging of work cycle representative signals at a first and at a second occasion, synchronizing said representative signals, and comparing said synchronized signals to determine if any condition changes have occurred between said first and second occasions.