Motor Abnormality Detection Using Frequency-Aligned Averaged Spectra
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing abnormality detection systems struggle to accurately differentiate between motor noise components and constant peaks when motor drive frequency fluctuates, leading to inaccurate diagnosis results.
Innovation Solution
An abnormality detector apparatus that performs frequency analysis on motor current or voltage data in different time intervals, adjusts the frequency axis to align peak values, and calculates an averaged spectrum to detect abnormal peaks exceeding a threshold, thereby improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If frequency analysis is performed on motor current data to detect abnormal noise components, then abnormality detection capability is improved, but measurement precision deteriorates when drive frequency fluctuates during measurement
Solution Approach 1:
The measurement period is divided into multiple sub-periods, and frequency analysis is performed separately for each sub-period. This segmentation allows the system to capture frequency fluctuations over time while maintaining precise frequency measurement within each sub-period, thereby resolving the contradiction between detecting abnormal noise and maintaining measurement precision under variable drive frequency conditions.
Solution Approach 2:
The system performs frequency analysis on multiple sub-periods before making a final abnormality determination. By preliminarily analyzing frequency characteristics across different time segments and identifying consistent abnormal peaks, the system ensures accurate detection even when the overall drive frequency varies during the complete measurement period.
2Reliability
If the measurement period is extended to improve detection accuracy, then abnormality detection reliability is improved, but the system becomes sensitive to drive frequency fluctuations, worsening measurement precision
Solution Approach 1:
Instead of performing a single frequency analysis over the entire measurement period, the system segments the period into multiple sub-periods and performs frequency analysis on each segment. This approach maintains high frequency measurement precision within each short sub-period while still providing comprehensive coverage of the measurement period through multiple segments, thus resolving the contradiction between detection accuracy and frequency separation precision.
Solution Approach 2:
The system dynamically adapts to drive frequency fluctuations by performing frequency analysis on multiple sub-periods and comparing results across segments. This dynamic approach allows the system to maintain accurate frequency separation even when the drive frequency changes during the measurement period, as each sub-period analysis captures the local frequency characteristics.
Data Source
AI summary
In an abnormality detector apparatus, a signal processor unit performs frequency analysis on data of a current or a voltage in different first and second time intervals to retrieve a first drive frequency corresponding to a maximum peak value of a spectrum in the first time interval and a second drive frequency corresponding to a maximum peak value of a spectrum in the second time interval; adjusts a frequency axis of one spectrum such that the maximum peak values coincide with each other, and calculates an averaged spectrum relating to the adjusted and unadjusted spectra; and retrieve an abnormal peak value equal to or more than a predetermined threshold value at a frequency different from the drive frequency having the maximum peak value based on the averaged spectrum; and determine an abnormal state of the motor depending on presence or absence of the abnormal peak value.