Adaptive Signal Enhancer for Weak Blind Signal Extraction
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Solution Overview
Problem
Existing detection techniques for high-speed railway wheel-rail systems face challenges in real-time defect detection due to high noise levels and spectral overlap between noise and defect signals, making it difficult to extract weak and blind target signals effectively.
Innovation Solution
A signal enhancer system incorporating a delay module, adaptive filter, convergent criterion, and irregular criterion based on the Hurst exponent is used to denoise and extract weak and blind target signals, allowing for real-time parameter adjustment and optimal filtering without prior information about the target signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If simple filtering processing is used to remove noise, then noise reduction is achieved, but the defect signal cannot be extracted because the noise amplitude is far higher than the target signal and their spectrums overlap
Solution Approach 1:
The patent employs an adaptive filter with dynamically adjustable parameters instead of fixed filtering characteristics. The filter adapts its impulse response in real-time to match the statistical properties of the input signal, enabling it to distinguish between noise and defect signals even when their spectrums overlap. This dynamic adaptation allows the system to maintain high signal extraction accuracy while effectively reducing noise.
Solution Approach 2:
The patent changes the parameters of the filtering process by using an adaptive algorithm that continuously adjusts the filter coefficients based on the input signal characteristics. By modifying the filter parameters dynamically rather than using fixed values, the system can adapt to varying noise conditions and extract defect signals effectively, resolving the contradiction between noise reduction and signal extraction accuracy.
2Object-affected harmful factors
If adaptive filter is used to remove noises, then noise cancellation is achieved, but irregularities of the output signal cannot be compensated
Solution Approach 1:
The patent incorporates a feedback mechanism where the output of the adaptive filter is analyzed and fed back to adjust the filter parameters. This feedback loop enables the system to detect signal irregularities and compensate for them by modifying the filter's impulse response. The feedback ensures that noise cancellation is achieved while maintaining signal stability and compensating for any introduced irregularities.
Solution Approach 2:
The adaptive filter performs self-adjustment by automatically modifying its own parameters based on the statistical properties of the input signal. This self-service capability allows the filter to compensate for its own output irregularities without external intervention, maintaining signal stability while effectively canceling noise.
3Object-affected harmful factors
If existing signal enhancer with adaptive filter is used, then noise removal is achieved, but it cannot extract weak and blind signals when noise amplitude is far higher than target signal
Solution Approach 1:
The patent uses a dynamic adaptive filtering approach where the filter characteristics continuously adapt to the input signal statistics. This dynamic behavior enables the system to detect weak and blind signals even when noise amplitude is far higher, as the filter learns to distinguish signal patterns from noise patterns over time, improving measurement precision without sacrificing noise removal capability.
Data Source
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AI summary
The disclosure relates to a signal enhancer, including a delay module, an adaptive filter (FIR), for outputting the target signal (g(n)), and a parameter adjustment module for adjusting parameters of the adaptive filter by a convergent criterion and an irregular criterion in real-time. A method based on the signal enhancer includes steps of: inputting a signal (d(n), h(n)) into an adaptive filter (FIR) through a delay module; adjusting parameters of the adaptive filter in real-time by means of the convergent criterion and the irregular criterion; and outputting a target signal (g(n)) by the adaptive filter with the adjusted parameters after optimization. A signal detection system includes the signal enhancer. In advantage, the disclosure is suitable for the extracting and denoising of the weak target signal whose spectrum has an overlap with the one of the strong noise, suitable for the extracting of the unknown and blind target signal, and able to extract the time domain waveform and all frequency components of the target signal.