Spectrum Signal Extraction Using Dual Moving Averages
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Solution Overview
Problem
Existing signal processing devices for generating spectra from analysis data, such as TOF-MS, face challenges in effectively removing noise due to varying noise characteristics with ion charge and mass, requiring cumbersome pre-analysis and filter coefficient setting.
Innovation Solution
A signal processing device that calculates first and second moving averages and determines data points as signals or noise based on a threshold difference, generating spectra without the need for sample-specific filter design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If filter design is conducted for each sample based on pre-analysis, then noise removal effectiveness is improved, but operation complexity and time consumption increase
Solution Approach 1:
The system performs automatic filter coefficient determination through pre-analysis of the input signal characteristics. The apparatus self-adjusts the filter parameters based on the detected noise characteristics without requiring manual intervention, thereby maintaining effective noise removal while simplifying operation.
Solution Approach 2:
The filter coefficients are determined in advance through pre_analysis before the actual signal processing. This preliminary action involves analyzing the noise characteristics of the input signal and setting appropriate filter parameters, which are then applied during the main measurement process to remove noise effectively.
2Measurement precision
If filter coefficients are determined through pre_analysis, then noise removal effectiveness is improved, but processing time increases
Solution Approach 1:
The pre_analysis process focuses on determining only the essential filter coefficients needed for noise removal, rather than performing comprehensive signal processing. By applying partial action only where necessary (coefficient determination), the system achieves effective noise removal while minimizing additional processing time.
Data Source
AI summary
The signal processing device applies signal-processing to one or more analysis data that are obtained through an analysis apparatus to generate a spectrum. The signal processing device comprises a memory that stores the one or more analysis data and a processor that applies signal-processing to the one or more analysis data. Each analysis data includes a plurality of data points. For each data point, the signal processing device calculates a first moving average of a first number of data points, calculates a second moving average of a second number of data points, the second number being larger than the first number, calculates a difference between the second and first moving averages, and determines the data point to be a signal if the difference is larger than a threshold value. The signal processing device generates for each analysis data a first spectrum including the data point determined to be the signal.