Signal Processing Device for Dynamic Abnormal Noise Detection
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Solution Overview
Problem
Existing techniques struggle to detect abnormal noise from devices like vehicles and machine tools effectively, as they require pre-defined frequency bands that are difficult to set when the noise frequency varies with the type of member generating the sound.
Innovation Solution
A signal processing device that converts input signals into a time-frequency domain, estimates peaks for target and noise signals, and determines event occurrence based on the intensity ratio between these signals, allowing for dynamic detection of abnormal sounds regardless of frequency changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-defined frequency bands are used for detection, then detection simplicity is improved, but detection accuracy deteriorates when noise frequency varies
Solution Approach 1:
The patent dynamically determines frequency bands for target and noise signals based on actual signal characteristics rather than using pre-defined fixed bands. The system estimates peaks in the frequency domain and adaptively sets bands around these peaks, allowing the detection parameters to change according to the actual noise conditions, thus resolving the contradiction between operational simplicity and detection accuracy.
Solution Approach 2:
The system changes the frequency band parameters adaptively based on the detected signal characteristics. By estimating the peak frequencies of both target and noise signals and setting frequency bands relative to these peaks, the system adjusts its detection parameters to match the actual operating conditions, thereby maintaining high detection accuracy across varying noise frequencies.
2Device complexity
If fixed frequency bands are set in advance, then device complexity is reduced, but adaptability to different noise frequencies deteriorates
Solution Approach 1:
The system performs self-adjustment by automatically estimating the peak frequencies of target and noise signals and determining appropriate frequency bands without requiring external configuration or manual intervention. This self-service capability enables the system to adapt to different noise frequencies while maintaining relatively simple device architecture, as the adaptation is achieved through automated signal processing rather than complex configurable hardware.
3Measurement precision
If target sound frequency is known in advance, then detection precision is improved, but applicability to variable frequency sounds deteriorates
Solution Approach 1:
The system performs preliminary estimation of the target signal peak frequency and noise signal peak frequency before final detection. By first identifying the peak frequencies through frequency domain analysis and then setting frequency bands around these peaks, the system prepares the detection parameters in advance based on actual signal characteristics, ensuring both high precision and broad applicability to variable frequency sounds.
Data Source
AI summary
A signal processing device according to an aspect of the present disclosure includes: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: convert an input signal into a predetermined signal in a time-frequency domain; estimate a peak of a time-frequency intensity of the predetermined signal as an intensity of a target signal; estimate a band including at least a bandwidth from a frequency related to a peak to a predetermined frequency and does not include a frequency related to a peak different from the peak, as a noise band that is a frequency band of a noise signal; estimate an intensity of the noise signal based on a time-frequency intensity in the noise band; and determine whether an event has occurred based on a ratio between the intensity of the target signal to the intensity of the noise signal.