Waveform Analysis Using DFT Weighting for Machinery Impulse Detection
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Solution Overview
Problem
Existing machinery condition monitoring methods require advance registration of various deterioration sounds and are inefficient in capturing impulse waveforms, leading to potential machinery failures and accidents due to reliance on specific frequency settings and manual adjustments.
Innovation Solution
A waveform analysis device using discrete Fourier transform and weighting techniques to decompose impulse waveforms into multiple frequencies, limiting amplitude values to reduce the effect of natural vibrations and detect anomalies without prior knowledge of frequency ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If impulse waveforms are captured to detect machinery defects without advance registration of deterioration sounds, then detection efficiency is improved and time for research and registration is reduced, but it becomes difficult to distinguish impulse waveforms from natural vibrations generated by the measurement object itself
Solution Approach 1:
The patent segments the analysis process into two distinct stages: first performing discrete Fourier transform to decompose the impulse waveform into frequency components, then performing amplitude accumulation specifically on the impulse waveform data. This segmentation allows the system to process and analyze impulse characteristics separately from natural vibrations, enabling accurate defect detection without requiring advance registration of deterioration sounds.
Solution Approach 2:
The patent transforms the impulse waveform analysis from the time domain to the frequency domain through discrete Fourier transform, then performs amplitude accumulation in the frequency domain. This dimensional transformation enables the system to identify impulse characteristics that are not apparent in the time domain, distinguishing them from natural vibrations and improving detection accuracy without sacrificing productivity.
2Measurement precision
If Fourier transform is performed on detection signals to analyze impulse waveforms, then frequency analysis capability is improved, but impulse waveforms at relatively low frequencies are buried in the frequency of the measurement object itself and cannot be clearly observed
Solution Approach 1:
The patent merges the discrete Fourier transform analysis with amplitude accumulation processing specifically applied to impulse waveform data. By combining these two processing steps and performing amplitude accumulation on the transformed frequency data, the system enhances the visibility of impulse signals across all frequency ranges, including low frequencies that would otherwise be buried in the measurement object's natural vibration spectrum.
3Measurement precision
If manual setting of frequency bands is performed to avoid frequencies generated by the measurement object, then impulse waveform detection is improved, but the system becomes dependent on the specific machinery being detected and requires operator expertise
Solution Approach 1:
The patent implements a self-service approach where the system automatically performs discrete Fourier transform and amplitude accumulation processing on the detected waveforms without requiring manual frequency band selection. The amplitude accumulation step automatically enhances impulse characteristics regardless of the measurement object's natural vibration frequencies, making the system adaptable to different machinery types without requiring operator expertise in setting frequency bands.
Solution Approach 2:
The patent creates a universal analysis method that can be applied to any machinery type without requiring machinery-specific frequency band settings. The combination of discrete Fourier transform and amplitude accumulation on impulse waveforms provides a general-purpose solution that automatically adapts to different measurement objects, eliminating the need for operator-dependent frequency selection and enhancing the system's versatility.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately analyzes impulse waveforms independent of machinery-specific frequencies, enabling timely detection of mechanical anomalies and preventing failures by setting upper-limit values for amplitude, thus facilitating efficient maintenance.
Implementation Method 1
a sensor unit (physical sensor) that detects physical phenomena such as vibration, sound, and electromagnetic waves emitted during operation of machinery
Implementation Method 2
a sensor unit (physical sensor) that detects physical phenomena such as vibration, sound, and electromagnetic waves emitted during operation of machinery
Implementation Method 3
when evaluating Fourier transform data obtained through experiments, an increase in signal level due to the impulse waveform could not be clearly observed
Data Source
Figure 1
Figure 2A~2C
Figure 3A~3D
AI summary
The present invention prevents stoppage or a disruptive accident during operation due to a breakdown in machinery. A waveform analysis device 200 comprises: a sensor unit 300 for detecting a physical phenomenon; a discrete Fourier transform unit 208 for performing a discrete Fourier transform of a detection signal transmitted from the sensor unit 203; a later-stage weighting unit 209 for setting amplitude values at each frequency generated by the discrete Fourier transform unit 208 that exceed a prescribed upper-limit value to said prescribed upper-limit value; and an accumulation unit 210 for adding the amplitude values at each frequency weighted by the later-stage weighting unit 209. An operator console 100 sets the prescribed upper-limit value in the waveform analysis device 200.