Robot Vibration Threshold Adjustment for Failure Prediction Timing
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Solution Overview
Problem
Existing abnormality detection methods in robots fail to accurately predict failure at high work speeds, as they detect abnormalities too early or too late, depending on the work speed and time, leading to inefficient maintenance.
Innovation Solution
An abnormality detecting device that adjusts the threshold for vibration data comparison based on the work time and pause time, allowing for precise determination of apparatus failure by using a criterion dependent on the length of work time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed threshold is used for abnormality detection, then the detection method is simple, but the detection accuracy varies with work speed leading to premature or delayed failure prediction
Solution Approach 1:
The patent applies dynamics by making the threshold variable rather than fixed. The threshold is dynamically adjusted based on work speed and work time parameters, allowing the abnormality detection criterion to adapt to different operating conditions. This resolves the contradiction by enabling accurate detection across varying work speeds without requiring multiple fixed thresholds for different speed ranges.
Solution Approach 2:
The patent changes the threshold parameter based on work speed and work time. By establishing a relationship between the threshold and these operational parameters, the system achieves accurate abnormality detection across different work conditions. This parameter change approach allows a single adaptive threshold to replace multiple fixed thresholds, balancing accuracy with system simplicity.
2Reliability
If early failure prediction is implemented for high work speed, then maintenance can be performed timely, but abnormality may be detected too early for low work speed
Solution Approach 1:
The patent uses dynamics to adjust the detection criterion based on work time, which itself varies with work speed. For high work speeds, the system detects abnormalities earlier because the same degradation level represents a shorter remaining life. For low work speeds, detection occurs later as the system allows more operational time. This dynamic adjustment optimizes reliability without causing premature maintenance.
Solution Approach 2:
The patent changes the detection threshold as a function of work time and work speed parameters. This allows the system to predict failure at appropriate times for different operating conditions - earlier for high-speed operations where failure occurs quickly, and later for low-speed operations where components last longer. The parameter-based threshold adjustment eliminates both premature and delayed detection.
3Reliability
If vibration data is continuously monitored, then failure can be predicted, but the system complexity and data processing load increase
Solution Approach 1:
The patent simplifies data processing by changing the approach from analyzing raw vibration waveforms to comparing extracted vibration parameters against work-speed-adjusted thresholds. This parameter-based comparison method maintains reliable failure prediction while significantly reducing processing complexity. The system extracts key vibration parameters and compares them to dynamically set thresholds rather than performing complex continuous waveform analysis.
Data Source
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AI summary
An abnormality detecting device (1) determines an abnormality in an apparatus (2) by comparing data on vibration detected in the apparatus with a predetermined threshold. Moreover, the abnormality detecting device changes the threshold depending on a length of work time required for the apparatus to perform a certain work.