Self-referencing Spectrometer with Shared Aperture for Mobile Devices

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Solution Overview

Problem

Existing smartphone-based optical spectrometers require offline calibration and periodic recalibration due to temperature variations and optical configuration changes, lacking simultaneous self-referencing and real-time spectrum measurement capabilities.

Innovation Solution

A system comprising a self-referencing optical module with a calibration light source, common aperture, lens, and diffraction grating, where a mobile device's image sensor detects spatially-separated wavelength components from both the calibration and external illumination sources, enabling automatic real-time calibration and spectral measurement.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If offline calibration is performed to establish wavelength accuracy, then wavelength measurement precision is improved, but device complexity and operational time increase due to periodic recalibration requirements

Engineering Contradiction:
Improvewavelength accuracyVSAvoidcalibration procedure complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The calibration light source is pre-configured within the optical module to provide known reference wavelengths. The system performs preliminary calibration by capturing the calibration light source spectrum alongside the external light source spectrum, establishing the pixel-to-wavelength mapping relationship before actual measurement begins. This eliminates the need for separate offline calibration procedures.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system uses its own calibration light source to perform self-calibration. The image sensor simultaneously detects both the calibration light source spectrum and the external light source spectrum, allowing the system to automatically determine wavelength accuracy without requiring external calibration equipment or manual intervention. The processor automatically calculates the pixel-to-wavelength relationship from the captured calibration spectrum.

Inventive Principle:
Principle #25Self-service

2Reliability

If periodic recalibration is performed to maintain wavelength accuracy under temperature variations and optical configuration changes, then measurement reliability is improved, but loss of time and productivity decrease due to offline calibration requirements

Engineering Contradiction:
Improvewavelength reproducibilityVSAvoidcalibration time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The calibration light source remains continuously available within the optical module, allowing the system to perform calibration at any time during operation. The image sensor continuously captures spectra, and the processor continuously updates the pixel-to-wavelength mapping relationship, ensuring wavelength accuracy is maintained without interruption to the measurement process.

Inventive Principle:
Principle #20Continuity of useful action

Solution Approach 2:

The system uses the calibration light source spectrum as a reference feedback signal. The processor compares the detected calibration spectrum against known reference wavelengths and automatically adjusts the wavelength calibration parameters to maintain accuracy. This closed-loop feedback mechanism compensates for temperature variations and optical configuration changes in real-time.

Inventive Principle:
Principle #23Feedback

3Device complexity

If a shared aperture is used to simultaneously detect calibration and external light sources, then device complexity is reduced, but measurement precision may be affected by overlapping spectral patterns

Engineering Contradiction:
Improveoptical module simplicityVSAvoidspectral pattern separation
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The optical system segments the spectral patterns spatially on the image sensor. The calibration light source spectrum and external light source spectrum are dispersed by the diffraction grating and focused at different positions on the image sensor array. This spatial segmentation allows both spectra to be detected simultaneously through the shared aperture without overlapping, enabling clear distinction and separate analysis of each spectral pattern.

Inventive Principle:
Principle #1Segmentation

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

This solution allows for accurate, real-time spectral analysis with enhanced wavelength reproducibility and visual interpretation, addressing the need for a low-cost, simultaneous self-referencing and measuring capability in smartphone-based optical spectrometers.

Implementation Method 1

a lens and a diffraction grating wherein the optical output is dispersed into spatially-separated wavelength components

Methodology Applied
Scientific EffectDiffraction: Diffraction

Implementation Method 2

a mobile device includes an image sensor simultaneously detects the dispersed optical output

Methodology Applied
Scientific EffectPhotoelectric Effect: Photoelectric Effect

Data Source

PatentUS9360366B1Self-referencing spectrometer on mobile computing device
Publication Date: 2016.06.07 TRAN CHUONG VAN
  • US9360366B1 patent drawing
  • US9360366B1 patent drawing
  • US9360366B1 patent drawing

AI summary

This invention discloses a self-referencing spectrometer that simultaneously auto-calibrate and measure optical spectra of physical object utilizing shared aperture as optical inputs. The concurrent measure and self-calibrate capabilities makes it possible as an attachment spectrometer on a mobile computing device without requiring an off-line calibration with an external reference light source. Through the mobile computing device, the obtained spectral information and imagery captured can be distributed through the wireless communication networks.