Noise Replica Generator for Mains Interference Reduction
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Solution Overview
Problem
Electrophysiology data acquisition systems face challenges in effectively isolating low-level electrical signals from electromagnetic interference (EMI) generated by mains power sources, which can distort signals and result in lost data or irrecoverable losses during critical measurement windows.
Innovation Solution
A data acquisition system incorporating a test probe, zero crossing detector, analog-to-digital converter, noise replica generator, and noise removal module, which generates noise replicas at a lower rate than sampling rate and subtracts them from corresponding data samples to remove noise, synchronized with the mains power frequency to minimize EMI impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise cancellation is performed at the full sampling rate, then noise removal accuracy is improved, but processing complexity and memory requirements increase significantly
Solution Approach 1:
The patent divides the noise cancellation process into two distinct stages: (1) noise replica generation at a reduced rate (e.g., 1/4 or 1/8 of sampling rate) to capture periodic noise characteristics, and (2) interpolation to expand the reduced-rate replicas to full sampling rate. This segmentation allows accurate noise removal while reducing processing complexity by performing heavy computations at lower rates.
Solution Approach 2:
The patent exploits the periodic nature of mains power interference (50/60 Hz) by generating noise replicas at rates synchronized with the power line frequency. By capturing noise characteristics periodically and interpolating between periods, the system achieves accurate noise cancellation without processing every sample at full rate, thus reducing computational burden while maintaining precision.
2Measurement precision
If noise replicas are generated at full sampling rate, then noise estimation accuracy is improved, but memory requirements and processing load increase
Solution Approach 1:
The patent applies partial action by generating noise replicas at a reduced rate (e.g., one replica per 4 or 8 samples) rather than at full sampling rate. This partial generation is sufficient because the noise is periodic and can be accurately represented at lower rates, then interpolated to fill in the intermediate values. This reduces memory requirements significantly while maintaining adequate noise estimation accuracy.
3Object-affected harmful factors
If traditional noise isolation methods (Faraday cages, ground loop avoidance) are used, then environmental noise protection is improved, but system complexity and setup difficulty increase
Solution Approach 1:
The patent extracts the noise cancellation function from the physical isolation infrastructure (Faraday cages, ground loop prevention) and implements it digitally through software-based noise replica generation and subtraction. This extracts the noise mitigation capability from complex physical setup requirements and relocates it to a simpler computational process, reducing system complexity while maintaining noise protection.
Solution Approach 2:
The patent replaces mechanical/physical noise isolation methods (Faraday cages, shielded cables, ground loop avoidance) with a digital signal processing approach. Instead of using physical barriers and careful wiring practices, the system uses computational methods to generate noise replicas and subtract them from the signal, substituting mechanical complexity with algorithmic simplicity.
Data Source
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AI summary
A data acquisition system and a method of operating the data acquisition system are disclosed. A zero crossing detector generates a mains cycle start signal in accordance with a power line frequency of a mains power source. An analog-to-digital converter samples a signal provided by a test probe and generates data samples at a sampling rate. A noise replica generator generates noise replicas from the data samples at a replica generation rate, and noise estimates from the noise replicas at the sampling rate, wherein the noise replica generation rate is less than the sampling frequency. A noise removal module removes each noise estimate from a corresponding data sample.