Motor Current Peak Analysis for Low-Complexity Fault Diagnosis
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Solution Overview
Problem
Existing diagnostic methods for power conversion apparatuses and motors require costly and resource-intensive spectral analysis, making it difficult to detect abnormalities at an early stage and low cost.
Innovation Solution
A diagnostic apparatus that acquires target data on current values between a power conversion apparatus and a motor, detects peak values, calculates amplitude and frequency using a frequency counting method, and diagnoses motor abnormalities based on these calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectral analysis is used for motor abnormality detection, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts only the essential feature (peak amplitude) from the complex spectral analysis process. Instead of performing full spectral analysis, the invention detects peak values in the time-series current waveform and calculates their amplitudes, thereby achieving abnormality detection with reduced computational complexity and lower cost while maintaining diagnostic effectiveness.
2Measurement precision
If spectral analysis is used for motor abnormality detection, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The invention extracts only the necessary information (peak amplitudes and their frequencies) from the current waveform, avoiding the time-consuming full spectral analysis process. By focusing on peak detection and amplitude calculation, the system achieves rapid abnormality detection that can be performed in real-time during motor operation.
Solution Approach 2:
Instead of performing complete spectral analysis, the invention applies partial action by detecting only the peak values and calculating their amplitudes. This partial analysis approach provides sufficient diagnostic information for abnormality detection while significantly reducing the computational time and resources required.
3Measurement precision
If spectral analysis is used for motor abnormality detection, then measurement precision is improved, but loss of energy increases
Solution Approach 1:
The patent extracts only the essential diagnostic feature (peak amplitude) from the current waveform, avoiding the energy-intensive full spectral analysis. By detecting peaks and calculating their amplitudes using straightforward mathematical operations, the system achieves effective abnormality detection with minimal computational energy consumption.
Data Source
AI summary
There is provided a diagnostic apparatus including: a data acquisition unit configured to acquire target data relating to a current value between a power conversion apparatus and a motor; a detection unit configured to detect a peak value in a time series waveform of the target data; a counting operation unit configured to use a frequency counting method to calculate an amplitude of the peak value and a frequency of occurrence of the amplitude; and a diagnostic unit configured to diagnose an abnormality of the motor based on the amplitude and the frequency of occurrence. The diagnostic unit diagnoses that the motor is abnormal when a statistic which is calculated from the amplitude and the frequency of occurrence of the amplitude does not satisfy a predetermined reference.