Load Abnormality Detection Using Multi-Threshold and Inclination Analysis
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Solution Overview
Problem
Existing load abnormality detection techniques struggle to accurately determine the cause of load imbalances in structures with multiple motors, particularly when interference occurs between rotating members driven by separate sources, leading to inaccurate control and potential system failures.
Innovation Solution
A load abnormality detection apparatus that compares drive current and torque command values between motors, using threshold values and inclination calculations to identify the cause of load imbalances, allowing for precise determination of load abnormalities and appropriate control adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single threshold value is used to detect load abnormalities, then the detection method is simple, but the accuracy of determining the cause of abnormality deteriorates when multiple motors are involved
Solution Approach 1:
The invention divides the abnormality detection into multiple segments: first threshold comparison for initial abnormality detection, second threshold comparison for cause identification, and inclination calculation for trend analysis. This segmentation allows the system to handle complex multi-motor abnormality causes while maintaining manageable detection steps.
Solution Approach 2:
The invention adds a temporal dimension by calculating the inclination (rate of change) of the second control element over time. This transforms the detection from a static single-threshold approach to a dynamic multi-dimensional analysis that considers both magnitude and rate of change, enabling accurate cause determination.
2Ease of operation
If only current value threshold comparison is used, then the detection process is simple, but the ability to distinguish between different types of load abnormalities deteriorates
Solution Approach 1:
The invention performs preliminary action by first comparing the first control element with the first threshold to detect any abnormality, then proceeds to more detailed analysis using the second threshold and inclination calculations. This staged approach maintains simplicity while enabling precise abnormality type discrimination.
Solution Approach 2:
The system uses feedback by continuously monitoring both control elements and their rates of change, then using this information to determine the specific cause of abnormality. The dual-threshold and inclination feedback mechanism enables the system to distinguish between different abnormality types such as load changes versus motor failures.
3Device complexity
If interference between rotating members is not considered, then the detection system is simpler, but the accuracy of load abnormality determination deteriorates in structures with multiple motors
Solution Approach 1:
The invention merges the analysis of multiple control elements from different motors into a unified detection framework. By combining first control element data with second control element data and their inclinations, the system can determine whether abnormalities are caused by load changes or interference between rotating members, improving reliability without excessive complexity.
Data Source
AI summary
A load abnormality detection apparatus detects a load abnormality in first and second rotational members acting on each other. An inclination calculation part calculates an inclination of a second control element. A first comparison part compares a first control element with a first threshold value and also with a second threshold value larger than the first threshold value. A second comparison part compares an inclination of change in the second control element with a third threshold value of a negative value and also with a fourth threshold value of a positive value. An abnormality detection part detects a load abnormality in a load applied to the first rotational member and the second rotational member based on results of comparison by the first comparison part and the second comparison part and identifies a cause of the detected load abnormality.