Motor Fault Frequency Extraction Under Varying Load and Speed
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Solution Overview
Problem
Existing motor current signature analysis (MCSA) methods struggle to effectively extract fault signatures under varying load and speed conditions due to weak fault signatures being submerged in background noise and interference, especially from power electronic device harmonics, and are sensitive to noise and load fluctuations.
Innovation Solution
A minimum variance beam-forming method is applied to segment time-domain current measurements into overlapped sequences, treating them as a linear sensor array to generate a current spectrum with robust performance under varying load operations, minimizing noise variance and enhancing fault detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If Fourier transform is used for spectral analysis, then the method is simple and works well at steady status, but it is not satisfactory for varying-load operations
Solution Approach 1:
The patent segments the time-domain current signal into multiple overlapping sequences, treating each sequence as an independent measurement from a virtual sensor array element. This segmentation enables the application of beam-forming techniques while maintaining computational feasibility, resolving the contradiction between method simplicity and effectiveness under varying loads.
Solution Approach 2:
The patent introduces minimum variance beam-forming as an intermediary processing step between signal segmentation and spectral analysis. This intermediary technique effectively suppresses noise and varying load interference while preserving fault signatures, bridging the gap between simple Fourier transform and complex adaptive filtering methods.
2Measurement precision
If multiple time sequences are measured and averaged, then the influence of noise and varying operations can be averaged down, but it requires longer time measurements and may not work effectively for extracting small fault signatures
Solution Approach 1:
The patent employs minimum variance beam-forming as an intermediary that provides superior noise suppression compared to simple averaging, achieving better measurement precision without requiring extended measurement times. The beam-forming technique adaptively weights signal components to maximize fault signature extraction while minimizing noise influence.
Solution Approach 2:
The patent changes the processing parameter from uniform averaging to adaptive weighting based on minimum variance criterion. This parameter change enables more effective noise suppression and fault signature extraction within the same measurement time, particularly for small fault signatures that would be lost in conventional averaging.
3Measurement precision
If advanced signal-processing methods such as ESPRIT, MUSIC, and compressive sensing are used, then high-resolved spectrum can be achieved, but they are either sensitive to noise or heavily relying on the signal model
Solution Approach 1:
The patent positions minimum variance beam-forming as a robust intermediary that achieves high spectrum resolution without the extreme noise sensitivity of ESPRIT/MUSIC or the heavy model dependencies of compressive sensing. The beam-forming approach provides a balanced solution with adaptive noise suppression and moderate computational requirements.
Solution Approach 2:
The patent changes the signal processing parameter from model-based spectral estimation to adaptive beam-forming weight optimization. This parameter change maintains high spectrum resolution while improving robustness to noise and reducing dependency on accurate signal models, making the method more reliable under varying operating conditions.
4Ease of operation
If motor is driven by inverter, then motor operation is controlled, but fault signature may be interfered by harmonics of the power electronic devices
Solution Approach 1:
The patent introduces minimum variance beam-forming as an intermediary filtering stage that selectively suppresses harmonic interference from power electronic devices while preserving motor fault signatures. This intermediary processing enables continued use of inverter-driven motors for controlled operation without suffering from harmonic interference degradation.
Data Source
AI summary
A fault detection system of extracting fault signature of a motor operating at varying speed or varying load conditions is provided. The fault detection system includes a sensor interface configured to acquire sensor signals from sensors arranged at predetermined positions of the induction machine, wherein the sensor signals are indicative of an eccentricity level of a rotor of the induction machine, a memory coupled with a processor. The instructions include steps a sensor interface configured to acquire operation signals of the induction machine; a memory configured to store a computer-implemented fault detection method by extracting fault signals in the frequency domain from the frequency spectrum formed by a minimum variance beam-forming method.