Mass Spectral Data Frequency-Domain Noise Filtering

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Solution Overview

Problem

Mass spectral data from Time of Flight (ToF) mass spectrometers often suffer from peak skirting and baseline rising due to ion collisions with residual gas, which existing noise filtering techniques, such as manual peak elimination, are unable to effectively address.

Innovation Solution

Transforming mass spectral data into frequency-domain data, attenuating or removing noise-associated frequency ranges, and then transforming it back to improve data quality by reducing peak skirting and baseline rising effects.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual peak elimination is used to remove noise, then periodic chemical background noise peaks can be removed, but peak skirting and baseline rising effects cannot be addressed

Engineering Contradiction:

Improvenoise removal effectivenessVSAvoidability to address peak skirting

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent replaces manual peak elimination with a Fourier transform-based signal processing approach. By transforming the mass spectral data into the frequency domain, the system can automatically identify and remove peak skirting artifacts through spectral filtering, eliminating the need for manual intervention while addressing both periodic noise and peak skirting effects simultaneously.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent changes the domain of the data from the time/mass domain to the frequency domain using Fourier transform. This parameter transformation allows the system to view and manipulate the data in a different representation where peak skirting artifacts appear as distinct frequency components that can be selectively removed through filtering operations.

Inventive Principle:

Principle #35Parameter changes

2Manufacturing precision

If frequency-domain transformation is applied, then peak skirting and baseline rising can be removed, but processing complexity increases

Engineering Contradiction:

Improvedata qualityVSAvoidprocessing complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent replaces complex manual data processing with automated Fourier transform algorithms. The transformation to frequency domain and subsequent filtering operations are performed computationally, which automates what would otherwise be complex manual analysis and provides consistent, reproducible results without requiring expert intervention.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates a frequency-domain copy or representation of the original mass spectral data. This copied representation in the frequency domain allows for filtering and manipulation without directly altering the original data, enabling non-destructive processing and preserving the ability to revert to or reprocess the original data if needed.

Inventive Principle:

Principle #26Copying

3Reliability

If existing noise filtering techniques are used, then periodic noise can be removed, but data resolution and accuracy are not improved for peak skirting

Engineering Contradiction:

Improvenoise filtering capabilityVSAvoiddata resolution

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The patent transforms the data from the time/mass domain to the frequency domain, fundamentally changing the parameter space in which filtering occurs. This allows the system to target and remove peak skirting artifacts that appear as specific frequency components, thereby improving data resolution and accuracy in a way that time-domain filtering cannot achieve.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces inadequate time-domain filtering methods with frequency-domain signal processing. The Fourier transform approach provides a more powerful and versatile framework for noise removal that can selectively target different types of artifacts (periodic noise, peak skirting, baseline rising) while preserving the integrity of the actual spectral peaks.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The method effectively removes non-repeating peak skirting and baseline rising artifacts, enhancing the quality of mass spectral data by selectively attenuating frequencies associated with peak noise, thereby improving data resolution and accuracy.

Implementation Method 1

transforming mass spectral data to produce frequency-domain mass spectral data

Methodology Applied

Scientific EffectFourier transform:

Implementation Method 2

transforming the modified frequency-domain mass spectral data to produce modified mass spectral data

Methodology Applied

Scientific EffectInverse Fourier transform:

Data Source

PatentUS10269547B2Processing mass spectral data

Publication Date: 2019.04.23 MICROMASS UK LTD

AI summary

A method of mass spectrometry is disclosed that includes transforming mass spectral data to produce frequency-domain mass spectral data, modifying the frequency-domain mass spectral data to produce modified frequency-domain mass spectral data by attenuating and/or removing one or more ranges of the frequency-domain mass spectral data that relate to noise associated with peaks of interest in the mass spectral data, and transforming the modified frequency-domain mass spectral data to produce modified mass spectral data.