Signal Baseline Processing Device for Particle Counting
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Solution Overview
Problem
Conventional baseline recognition technologies face challenges in accurately identifying and removing fluctuating baselines from particle counting signals, leading to distorted pulse amplitudes and reduced data compression ratios, especially due to the interdependence of baseline and pulse recognition, which complicates processing and debugging.
Innovation Solution
A baseline processing device and method that utilize an analog-to-digital sampling unit, a baseline extracting unit for mid-value filtering, and a phase compensating unit to sort and subtract sample data, effectively separating baseline removal from pulse recognition, using a mid-value filtering algorithm to adapt to signal variations and ensure efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional baseline recognition technologies are used to identify and remove fluctuating baselines from particle counting signals, then baseline removal is achieved, but pulse amplitude distortion occurs and data compression ratios are reduced
Solution Approach 1:
The patent segments the signal processing into distinct phases: baseline recognition phase and pulse recognition phase. The baseline recognition unit first identifies baseline points by analyzing signal valleys, then removes the baseline to produce a baseline-corrected signal that is subsequently used for pulse detection. This segmentation prevents the interdependence problem where baseline and pulse recognition interfere with each other.
Solution Approach 2:
The patent applies preliminary baseline removal before pulse recognition. By first identifying baseline points through valley detection and interpolating baseline values, then subtracting this baseline from the original signal, the system prepares a pre-processed signal that enables more accurate subsequent pulse detection without the distortion caused by fluctuating baselines.
2Measurement precision
If conventional baseline recognition technologies are used, then baseline processing is performed, but processing complexity increases and debugging becomes difficult due to interdependence of baseline and pulse recognition
Solution Approach 1:
The patent divides the processing system into independent functional units: a baseline recognition unit that operates autonomously to identify and remove baselines, and a pulse recognition unit that processes the baseline-corrected signal. This architectural segmentation eliminates the interdependence that complicates conventional systems, making the overall processing simpler and easier to debug while maintaining high baseline recognition accuracy.
3Measurement precision
If high sampling rates are used to acquire enough pulse information, then pulse detection accuracy improves, but data volume increases and storage requirements increase
Solution Approach 1:
The patent extracts and removes unnecessary baseline components from the signal before pulse detection. By identifying baseline points at signal valleys and interpolating baseline values across the signal, then subtracting this extracted baseline from the original high-rate sampled signal, the system reduces data volume while preserving the pulse information needed for accurate detection.
Data Source
AI summary
A baseline processing device and method are provided for analyzing signals with uneven distributions of pulses and slow varying baselines. In one embodiment, the device includes an A/D sampling unit for sampling a digital counting signal to obtain sampled data, and a baseline extracting unit for sorting the N sampled data in the sampling sequence by magnitude and for outputting, among the N sample data, one sample data A with a value equal to the mid-value in the N sample data. A phase compensating unit with a width of M, to which a digital signal is input, outputs a sampled data B according to a FIFO sequence, wherein M=N/2. A first subtractor subtracts the sample data A from the sample data B and outputs the result as baseline removed data.