Energy Waveform Angle Analysis for Predictive Equipment Maintenance
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Solution Overview
Problem
Current predictive maintenance methods are inadequate in preventing significant losses due to apparatus breakdowns in large-scale manufacturing facilities, as they fail to accurately detect abnormalities in energy waveforms, leading to unexpected downtime and substantial economic losses.
Innovation Solution
A method for predictive maintenance that extracts start, peak, and end points from energy waveforms, calculates critical angles for connection lines with a horizontal line, and issues warnings when abnormal conditions are met, allowing for timely maintenance and replacement to prevent apparatus failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional preventive maintenance methods are used, then maintenance activities are performed periodically, but they fail to accurately detect abnormalities leading to unexpected breakdowns
Solution Approach 1:
The patent transforms the energy waveform data into angular parameters (α1, α2, β1, β2) by connecting characteristic points (start point, peak point, end point) with reference lines. This parameter transformation enables more sensitive detection of abnormal changes in the energy waveform shape, allowing for precise identification of apparatus abnormalities before they cause breakdowns.
Solution Approach 2:
The patent replaces traditional mechanical or periodic maintenance approaches with a data-driven method using energy waveform analysis. By substituting physical inspection with electronic signal processing and angular parameter comparison, the system achieves continuous monitoring and precise abnormality detection without interrupting apparatus operation.
2Measurement precision
If continuous monitoring of energy waveforms is implemented, then abnormality detection capability is improved, but system complexity increases
Solution Approach 1:
The patent extracts only the essential characteristic points (start point, peak point, end point) from the continuous energy waveform and focuses analysis on the angular relationships between these points and reference lines. This extraction approach reduces the complexity of processing entire waveforms while maintaining high abnormality detection precision.
Solution Approach 2:
The patent segments the energy waveform into three key portions by identifying characteristic points, then analyzes each segment's angular relationship with reference lines. This segmentation simplifies the monitoring system by breaking down complex waveform analysis into manageable angular measurements, reducing computational requirements while improving detection accuracy.
Data Source
AI summary
Provided is a method for predictive maintenance for an apparatus, which allows inducing maintenance at an appropriate time, based on an energy waveform indicating changes over time in the energy for an operation of the apparatus in drive, by extracting a start point, an end point, and a peak point, respectively, indicating the beginning and the end of the energy waveform, and the highest energy value; detecting angles of a start point connection line and an end point connection line, each connecting the extracted points, as to a horizontal line; determining critical angles for the detected angles; comparing, with the relevant critical angles, the angles of the start point connection line and the end point connection line regarding the start, end, and the peak points, extracted from the energy waveform in real time, as to the horizontal line; and issuing a warning when abnormal symptoms in the apparatus are detected.