Non-contact Alcohol Concentration Measurement Device At NIR Spectrum

Team Member

Lim Gin Joe, Sun Weijia, Yan Chengrui, Zhu Junyi

Background

Alcohol (ethanol) is a widely used organic compound in medicine, chemical industry, food, and beverages. Rapid and accurate measurement of alcohol concentration is crucial in various industries, including food and beverage manufacturing, medical disinfection, and industrial synthesis. Existing measurement methods typically have limitations such as complexity, high equipment costs, and large measurement errors. Therefore, developing an efficient, cost-effective, and non-contact measurement method is essential.

Objective

This research proposes a non-contact alcohol concentration measurement method and infrared spectroscopy. This method measures changes in infrared light intensity transmitted through alcohol solutions, using photoelectric sensors and data fitting techniques to achieve high precision measurements.

Schematic Diagram of the Experiment

Advantages of Infrared-Based Alcohol Detection

• Non-contact measurement, reducing contamination.
• High accuracy, based on alcohol-specific infrared absorption characteristics.
• Low cost, with simple photodetection devices.

Equipment Required

• Oband Light Source: A broadband light source capable of emitting light across a spectrum of wavelengths.
• Photodetector: A device to measure the intensity of light that has passed through the sample solution.
• Alcohol Samples: Different alcohol solutions with known concentrations (e.g., ethanol, isopropanol).
• Cuvette: A transparent container to hold the alcohol solution for light transmission.
• Spectrometer: For recording and analyzing the intensity of transmitted light.
• Power Supply: To power the Oband light source.

Methodology

1. Experiment Procedures

• Preparation of alcohol solutions at concentrations of 25%, 50%, and 75%.

Ethanol Sample Preparation

Ethanol Sample

• Measurement of absorption using spectrometer.

Spectrometer

• Use Origin software for spectral normalization and baseline correction, and process the alcohol spectra at three different concentrations.

(Due to very small differences in spectral data, it is challenging for non-experts to visually distinguish spectra from the three alcohol concentrations. Therefore, apply machine learning-based Principal Component Analysis (PCA) for spectral classification, thus enabling alcohol concentration measurement.)

Data Analysis

1. Beer-Lambert Law: The relationship between absorbance and concentration is governed by the Beer-Lambert Law, which states:

  $A=ϵ\cdot c\cdot l$
  Where:
  * $A$ is the absorbance,
  * $ϵ$ is the molar absorptivity (a constant for the alcohol),
  * $c$ is the concentration of the alcohol,
  * $l$ is the path length of light through the sample.

References

• Beer-Lambert Law for Spectrophotometry
• Applications of Optical Sensing for Chemical Analysis
• Practical Guide to Spectrometer Calibration