Noise Detection Apparatus Using Cepstral Analysis
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Solution Overview
Problem
Conventional detection methods face challenges in accurately detecting noise signals with minute differences in peak intensities, leading to degradation in detection accuracy, especially when multiple noise signals are present, and struggle to effectively identify periodic noises with varying frequency components.
Innovation Solution
A detection apparatus that acquires data with superimposed signal groups of different base frequencies, calculates these base frequencies using Fourier transforms and cepstral operations, and detects noise signals based on the calculated frequencies, enhancing accuracy by separating and identifying periodic noises.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional Fourier transform method with threshold comparison is used to detect noise signals, then the detection process is simple, but the detection accuracy degrades when peak intensity differences between noise signals and other signals are minute
Solution Approach 1:
The patent segments the complex spectrum into multiple signal groups based on base frequency identification. By using cepstral analysis to separate signals with different base frequencies, the system can individually analyze each group, improving detection accuracy for signals with minute intensity differences without requiring overly complex global processing
Solution Approach 2:
The patent introduces cepstral analysis as an intermediary step between the Fourier transform and threshold comparison. The cepstrum acts as a mediator that separates mixed signals by their base frequencies, allowing subsequent detection to operate on separated signal groups rather than the original mixed spectrum, thereby improving accuracy while maintaining manageable complexity
2Reliability
If threshold comparison method is used for signal detection, then the processing speed is fast, but the reliability of detection decreases when multiple noise signals with varying frequencies are present
Solution Approach 1:
The patent performs preliminary cepstral analysis to identify and separate signal groups by their base frequencies before the actual detection process. This preliminary action organizes the spectrum into structured groups, making subsequent detection more reliable without requiring excessive processing time during the main detection phase
Solution Approach 2:
The patent dynamically adapts the detection process by identifying the actual base frequencies present in the signal and organizing detection around these dynamic characteristics rather than using fixed thresholds. This allows the system to reliably detect multiple noise signals with varying frequencies by adjusting the detection strategy to match the actual signal structure
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
The solution improves the accuracy of noise detection by calculating and utilizing base frequencies to differentiate and remove periodic noises, even when multiple noise signals are present, thereby enhancing signal quality and reducing errors in detection.
Implementation Method 1
the calculation unit configured to calculate, based upon a frequency spectrum of the data acquired by the acquisition unit, the base frequencies of the respective signal groups
Data Source
AI summary
A detection apparatus according to an embodiment includes an acquisition unit, a calculation unit, and a detection unit. The acquisition unit acquires, via an antenna positioned on a movable body, data on which signal groups with different base frequencies are superimposed. The calculation unit calculates, based upon a frequency spectrum of the data acquired by the acquisition unit, the base frequencies of the respective signal groups. The detection unit detects signals in the respective signal groups based upon the base frequencies calculated by the calculation unit.