Rotating Machine Diagnostic Device for Overlapping Frequency Separation
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Solution Overview
Problem
Existing diagnostic methods for rotating machines face challenges in accurately distinguishing between different types of deterioration, as characteristic frequencies often overlap, leading to erroneous diagnoses.
Innovation Solution
A diagnostic device and method that utilize current frequency mode analysis, state mode models, and activity level calculations to separate overlapping deterioration characteristic frequencies and determine the specific deterioration factors in rotating machine systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Fourier transform is used to extract characteristic frequency components for diagnosis, then diagnostic capability is improved, but measurement precision deteriorates when frequencies overlap
Solution Approach 1:
The patent segments the current waveform into multiple frequency components using Fast Fourier Transform (FFT), and further segments overlapping frequency components by identifying and separating characteristic frequencies associated with different deterioration types (brush, commutator, bearing, gear). This segmentation allows individual analysis of each frequency component to resolve the overlap problem.
Solution Approach 2:
The patent transitions from analyzing only frequency magnitude to analyzing both frequency magnitude and phase information. By incorporating phase data alongside amplitude, the system creates an additional dimension for distinguishing between overlapping frequency components from different deterioration sources, improving diagnostic precision.
2Reliability
If characteristic frequency analysis is performed to identify deterioration, then diagnostic capability is improved, but reliability deteriorates due to frequency overlap causing erroneous diagnosis
Solution Approach 1:
The patent implements a feedback mechanism where the diagnosed deterioration type and level are used to adjust and refine the frequency analysis parameters. The system continuously monitors frequency components and updates the diagnostic model based on observed patterns, improving reliability by learning from actual deterioration cases and reducing erroneous diagnoses.
Solution Approach 2:
The patent changes the analysis parameters by considering not only frequency magnitude but also phase information, frequency shift, and spectral broadening. By monitoring multiple parameters simultaneously, the system can distinguish between overlapping frequencies from different deterioration sources, thereby improving diagnosis reliability.
3Device complexity
If simple frequency amplitude analysis is used, then device complexity is reduced, but measurement precision deteriorates due to inability to separate overlapping frequencies
Solution Approach 1:
The patent introduces an intermediary processing layer that acts on the frequency spectrum data. This intermediary layer applies signal processing techniques such as spectral subtraction, wavelet transform, or pattern recognition algorithms to separate overlapping frequency components before final diagnosis, achieving high precision without requiring complex hardware modifications.
Solution Approach 2:
The patent replaces simple mechanical frequency counting with advanced signal processing methods including Fast Fourier Transform (FFT), spectral analysis, and pattern recognition. This substitution of analytical methods enables precise separation of overlapping frequencies while maintaining computational efficiency, avoiding the need for physically complex diagnostic equipment.
Data Source
AI summary
The invention provides a diagnostic device including: an input/output unit that receives an input of a current value indicating a value of a current of an electric motor measured by a sensor; a frequency analysis unit that converts the current value measured by the sensor into a frequency intensity; a deterioration mode decomposition unit that uses a state mode model indicating a change situation of a frequency intensity in a part constituting the electric motor to calculate an activity level indicating a time series change of a deterioration intensity for each state mode model from the frequency intensity; and an abnormality determination unit that determines a deterioration and an abnormality of each part using the activity level.