A near-infrared sugar detection device and method based on a filter rotating wheel

Abstract

This invention discloses a near-infrared sugar detection device and method based on a filter wheel, belonging to the field of sugar component detection equipment. The device includes: a broadband near-infrared light source, a filter switching mechanism, a sample cell, a photoelectric detection unit, a signal processing unit, a control and calculation unit, and a display module. The filter switching mechanism includes a filter wheel and a driving mechanism. The filter wheel is equipped with a narrow-band filter, a baseline filter, and a filterless window. During detection, light source drift correction is first performed through the filterless window, followed by empty cell calibration using air as the medium to obtain reference light intensities for each wavelength. After adding the sugar solution to be tested, the background absorption of water is measured through the baseline filter, and the water absorption ratio is used for conversion and subtraction. Finally, characteristic wavelength signals are acquired through the narrow-band filter, and a system of simultaneous equations is solved to obtain the concentration of each sugar. This invention is low-cost, small in size, and can achieve rapid differentiation and concentration detection of multiple sugars.

Description

Technical Field

[0001] This invention relates to the field of sugar component detection equipment, specifically to a near-infrared sugar detection device and method based on a filter wheel, which is suitable for rapid identification and quantitative detection of various sugars. Background Technology

[0002] Near-infrared spectroscopy is widely used in the detection of sugar components due to its non-destructive and rapid characteristics. Existing near-infrared sugar detection devices mostly use spectrometers as the core dispersive component. While these devices offer high detection accuracy, the high cost and large integrated size of spectrometers make it difficult to meet the demands of low-cost, miniaturized, and civilian applications. Furthermore, the dense and highly overlapping near-infrared absorption peaks of sugars make it difficult for conventional, simple detection devices to effectively distinguish polysaccharides and accurately detect their concentrations under low-cost architectures. Some devices also lack dedicated visualization modules for detection results, impacting operational efficiency. Summary of the Invention

[0003] This invention provides a near-infrared sugar detection device and method based on a filter wheel, which can achieve low-cost, miniaturized polysaccharide identification and quantitative concentration detection, and the detection results can be visualized.

[0004] This invention provides a near-infrared sugar detection device and method based on a filter wheel, comprising: a broadband near-infrared light source, a filter switching mechanism, a sample cell, a photoelectric detection unit, a signal processing unit, a control and calculation unit, and a display module; the broadband near-infrared light source, the filter switching mechanism, the sample cell, and the photoelectric detection unit are sequentially arranged on the same detection optical path; the filter switching mechanism includes a filter wheel and a driving mechanism, the filter wheel is provided with several narrowband filters corresponding to the near-infrared characteristic absorption peaks of sugars and a baseline filter, the baseline filter is used to collect baseline signals from water background absorption, optical path substrate, and environmental scattering interference, and a filterless window is reserved for collecting the original light intensity to correct for light source attenuation and intensity drift; the photoelectric detection unit is used to receive the light signal transmitted through the sample cell and convert it into an electrical signal; the signal processing unit is connected to the photoelectric detection unit and is used to process the micro-signal output by the photoelectric detection unit. The weak electrical signal is amplified, filtered, and converted from analog to digital. The control and calculation unit is connected to the drive mechanism, signal processing unit, and display module, respectively. It is used to control the wavelength switching sequence of the filter wheel, collect and store the transmitted light intensity at each wavelength, calibrate the empty sample cell with air as the medium to obtain the reference light intensity at each characteristic wavelength and the reference light intensity of the reference channel, calculate the water absorption at the reference wavelength using the baseline signal collected by the baseline filter, and convert the water absorption at the reference wavelength into the water background absorption contribution at each characteristic wavelength through a pre-calibrated water absorption ratio coefficient. The net absorbance of the sugar component is obtained by subtracting the water background absorption contribution of the corresponding wavelength from the total absorbance of each characteristic wavelength. According to the Lambert-Beer law, a system of simultaneous equations is constructed using the difference in the absorbance coefficient of different sugars at each wavelength to solve for the concentration of each sugar component in the mixed sugar solution, realizing the differentiation of sugar types and the detection of corresponding concentrations, and outputting the detection results to the display module.

[0005] Furthermore, the broadband near-infrared light source is a broadband near-infrared LED.

[0006] Furthermore, the filter wheel is provided with a number of narrowband filters, the wavelength of which covers the near-infrared characteristic absorption band of sugars, and includes at least one baseline filter.

[0007] Furthermore, the driving mechanism is a servo motor, used to drive the filter wheel to achieve precise wavelength positioning.

[0008] Furthermore, the photoelectric detection unit is a photodetector.

[0009] Furthermore, the signal processing unit includes an operational amplifier and an ADC acquisition unit.

[0010] Furthermore, the control and computing unit adopts a microcontroller.

[0011] Furthermore, the display module is a liquid crystal display module.

[0012] The beneficial effects of this invention are as follows: It employs a spectroscopic structure combining a filter wheel and a single-channel photoelectric detector, replacing traditional high-cost spectrometers, significantly reducing the overall cost of the device. The structure is simple, compact, and easily miniaturized. Through time-division multi-wavelength signal acquisition, it achieves effective differentiation and accurate concentration detection of various sugars under a low-cost architecture, exhibiting good channel consistency and strong anti-interference capabilities. The use of filterless window pre-illumination, double calibration with an empty cell, and multiple averaging acquisitions effectively solves errors caused by uneven voltage in the near-infrared light source unit, light source drift, and environmental interference, significantly improving detection stability and consistency. A dedicated result display module is added, enabling real-time visual reading of detection results and facilitating operation. The modular design of each module simplifies connections, reducing the difficulty of later maintenance, debugging, and mass production, making it highly practical. Attached Figure Description

[0013] Figure 1 is a schematic diagram of the overall structure of the device of the present invention; Figure 2 is a schematic diagram of the filter wheel structure of the present invention; Figure 3 is a flowchart of the system workflow of the present invention.

[0014] In the diagram: 1. Broadband near-infrared light source; 2. Filter switching mechanism; 21. Filter wheel; 211. Narrowband filter; 212. Baseline filter; 213. Filterless window; 22. Drive mechanism; 3. Sample cell; 4. Photodetector unit; 5. Signal processing unit; 51. Operational amplifier; 52. ADC acquisition unit; 6. Control and calculation unit; 7. Display module. Detailed Implementation

[0015] As shown in Figure 1, the near-infrared sugar detection device based on a filter wheel of the present invention includes a broadband near-infrared light source, a filter switching mechanism, a sample cell, a photoelectric detection unit, a signal processing unit, a control and calculation unit, and a display module.

[0016] The broadband near-infrared light source uses a broadband near-infrared LED to emit continuous light covering the near-infrared sensitive band of sugars. It has low energy consumption, small size, and is suitable for portable design.

[0017] The filter wheel is equipped with four narrow-band filters, one of which is an 850nm baseline filter, and the other three are 910nm, 980nm, and 1050nm component characteristic detection filters, corresponding to the near-infrared characteristic absorption peaks of glucose, fructose, and sucrose, respectively. This enables effective differentiation of multiple sugars and simultaneous quantitative detection of multiple components. The drive mechanism uses a servo motor to drive the filter wheel to complete precise switching of multiple wavelengths in time.

[0018] The photoelectric detection unit converts transmitted light signals of different wavelengths into electrical signals and outputs them to the signal processing unit. The signal processing unit includes an operational amplifier and an ADC acquisition unit, which amplifies the weak electrical signals and converts them into digital signals, which are then sent to the control and calculation unit.

[0019] The control and calculation unit employs a microcontroller as its core control and data processing component. It performs filter wheel timing control, light intensity signal acquisition, empty cell calibration, absorbance calculation, sugar type identification, and concentration quantification, outputting the results to the display module. The display module uses an LCD display to clearly show the sugar type and concentration values ​​in real time, facilitating quick and easy reading by the user.

[0020] The specific method for light source drift correction is as follows: When the device is started, the broadband near-infrared light source is turned on and kept running stably until all detections are completed. The light intensity is continuously collected three times through an unfiltered window, and the average value is recorded as I_source. At the beginning of each detection batch (i.e., before empty cell calibration and sample detection), the current light intensity I_window is collected again through the unfiltered window, and the correction factor α = I_source / I_window is calculated. The original transmitted light intensity I_raw measured by all filter channels (including baseline and feature filters) within the detection batch is directly multiplied by α to obtain the corrected light intensity I_corrected = I_raw × α. Subsequent absorbance calculations all use the corrected light intensity value.

[0021] Because water absorbs differently at different near-infrared wavelengths, this device is pre-calibrated to determine the water absorption ratio coefficient k(λ) for each characteristic wavelength relative to the baseline wavelength. The specific calibration method is as follows: using pure water as the sample, the absorbance is measured at the baseline wavelength λ_ref (850 nm) and each characteristic wavelength λ_i (910 nm, 980 nm, 1050 nm), and k(λ_i) = A_water(λ_i) / A_water(λ_ref). k(λ_i) is a fixed constant determined by the near-infrared absorption spectrum of water and is used long-term after a single calibration.

[0022] The complete calculation process for deducting water background absorption by this device is as follows: (1) Empty cell calibration: Using air as the medium, measure the reference light intensity I0(λ) at each characteristic wavelength and the reference light intensity I_ref0 of the baseline channel. Collect the transmitted light intensity three times at each wavelength position and take the average value. (2) Baseline measurement: Measure the transmitted light intensity of the sample through an 850nm baseline filter, collect three times consecutively and take the average value as I_ref, and calculate the water absorption at the baseline wavelength: A_water (850) = -log (I_ref / I_ref0). (3) Wavelength conversion: Use the water absorption ratio coefficient k (λ) to calculate the water background absorption at each characteristic wavelength: A_water (910) = k (910) × A_water (850), A_water (980) = k (980) × A_water (850), A_water (1050) = k (1050) × A_water (850). (4) Calculation of total absorbance: The transmitted light intensity of the sample is measured through each characteristic filter. The sample is collected three times for each characteristic wavelength and the average value is taken as I(λ). The total absorbance is calculated as: A_total(λ) = -log(I(λ) / I0(λ)). (5) Subtraction of water background: The water background absorption at the corresponding wavelength is subtracted from the total absorbance to obtain the net absorbance of the sugar component: A_sugar(λ) = A_total(λ) - A_water(λ). (6) Concentration solution: The net absorbance is substituted into the system of simultaneous equations constructed by Lambert-Beer's law. Specifically, the form of the system of simultaneous equations is as follows: A_sugar (910) = ε_G (910)・c_G・L + ε_F (910)・c_F・L + ε_S (910)・c_S・L A_sugar (980) = ε_G (980)・c_G・L + ε_F (980)・c_F・L + ε_S (980)・c_S・L A_sugar (1050) = ε_G (1050)・c_G・L + ε_F (1050)・c_F・L + ε_S (1050)・c_S・L Where ε_G, ε_F, and ε_S are the absorbance coefficients of glucose, fructose, and sucrose, respectively, and are pre-calibrated known constants; c_G, c_F, and c_S are the concentrations of glucose, fructose, and sucrose to be determined; and L is the optical path length. Solving the above system of equations yields the concentration of each carbohydrate component.

[0023] The working process of this device is as follows: After the device is started, the broadband near-infrared light source is turned on and remains stable until all detections are completed. First, light source drift correction is performed: the light intensity is continuously collected three times through an empty window without filters and the average value is taken as I_source, and the correction factor α is calculated. Then, empty cell reference calibration is performed: using air as the medium, the filter wheel is controlled to switch the narrowband filters and the baseline filter in sequence, and the transmitted light intensity is continuously collected three times at each wavelength position and the average value is taken to obtain the reference light intensity I0(λ) at each characteristic wavelength (910nm, 980nm, 1050nm) and the reference light intensity I_ref0 of the baseline channel (850nm). Next, the sugar solution to be tested is added to the sample cell, and the transmitted light intensity of the sample is collected through the baseline filter. The average value is taken as I_ref and the water absorption at the baseline wavelength A_water (850) = -log (I_ref / I_ref0) is calculated. Using a pre-calibrated water absorption ratio k(λ), A_water(850) was converted into water background absorption contributions A_water(910), A_water(980), and A_water(1050) at each characteristic wavelength. Then, the transmitted light intensity of the sample was collected through each characteristic filter. Three consecutive acquisitions were performed at each characteristic wavelength, and the average value was taken as I(λ). The total absorbance A_total(λ) = -log(I(λ) / I0(λ)) at each characteristic wavelength was calculated, and the water background absorption contribution at the corresponding wavelength was subtracted to obtain the net absorbance A_sugar(λ) of the sugar component. Finally, using the differences in the absorbance coefficients of glucose, fructose, and sucrose at 910nm, 980nm, and 1050nm, a system of simultaneous equations was constructed. Specifically, the form of the system of simultaneous equations is as follows: A_sugar (910) = ε_G (910)・c_G・L + ε_F (910)・c_F・L + ε_S (910)・c_S・L A_sugar (980) = ε_G (980)・c_G・L + ε_F (980)・c_F・L + ε_S (980)・c_S・L A_sugar (1050) = ε_G (1050)・c_G・L + ε_F (1050)・c_F・L + ε_S (1050)・c_S・L Where ε_G, ε_F, and ε_S are the absorbance coefficients of glucose, fructose, and sucrose, respectively, and are pre-calibrated known constants; c_G, c_F, and c_S are the concentrations of glucose, fructose, and sucrose to be determined, respectively; and L is the optical path length. Substituting the net absorbance into the equation system, the concentrations of each sugar component in the mixed sugar solution are obtained, and the detection results are output in real time through the display module.

[0024] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A near-infrared sugar detection device based on a filter rotor, characterized in that, include: The system comprises a broadband near-infrared light source, a filter switching mechanism, a sample cell, a photodetector unit, a signal processing unit, a control and computing unit, and a display module. The broadband near-infrared light source, filter switching mechanism, sample cell, and photodetector unit are sequentially arranged on the same detection optical path. The filter switching mechanism includes a filter wheel and a driving mechanism. The filter wheel is equipped with several narrowband filters corresponding to the near-infrared characteristic absorption peaks of sugars and a baseline filter. The baseline filter is used to collect baseline signals from water background absorption, optical path substrate, and environmental scattering interference, and a filterless window is reserved for collecting the original light intensity to correct for light source attenuation and intensity drift. The photodetector unit receives the light signal transmitted through the sample cell and converts it into an electrical signal. The signal processing unit, connected to the photodetector unit, amplifies, filters, and performs analog-to-digital conversion on the weak electrical signal output by the photodetector unit. The control and calculation unit is connected to the drive mechanism, signal processing unit, and display module, respectively. It is used to control the wavelength switching sequence of the filter wheel, collect and store the transmitted light intensity at each wavelength, calibrate the empty sample cell with air as the medium to obtain the reference light intensity at each characteristic wavelength and the reference light intensity of the reference channel, calculate the water absorption at the reference wavelength using the baseline signal collected by the baseline filter, and convert the water absorption at the reference wavelength into the water background absorption contribution at each characteristic wavelength through a pre-calibrated water absorption ratio coefficient. The net absorbance of the sugar component is obtained by subtracting the water background absorption contribution of the corresponding wavelength from the total absorbance of each characteristic wavelength. Based on the Lambert-Beer law, a system of simultaneous equations is constructed using the difference in the absorbance coefficient of different sugars at each wavelength to solve for the concentration of each sugar component in the mixed sugar solution, thereby realizing the differentiation of sugar types and the detection of corresponding concentrations, and outputting the detection results to the display module.

2. The near-infrared sugar detection device according to claim 1, characterized in that, The broadband near-infrared light source is a broadband near-infrared LED.

3. The near-infrared sugar detection device according to claim 1, characterized in that, The filter wheel is provided with a number of narrowband filters, the wavelength of which covers the near-infrared characteristic absorption band of sugars, and includes at least one baseline filter.

4. The near-infrared sugar detection device according to claim 1, characterized in that, The driving mechanism is a servo motor, used to drive the filter wheel to achieve precise wavelength positioning.

5. The near-infrared sugar detection device according to claim 1, characterized in that, The photoelectric detection unit is a photoelectric detector.

6. The near-infrared sugar detection device according to claim 1, characterized in that, The signal processing unit includes an operational amplifier and an ADC acquisition unit.

7. The near-infrared sugar detection device according to claim 1, characterized in that, The control and computing unit uses a microcontroller.

8. The near-infrared sugar detection device according to claim 1, characterized in that, The display module is a liquid crystal display module.

9. A near-infrared sugar detection method based on a filter rotor, applied to the apparatus described in any one of claims 1 to 8, characterized in that, Includes the following steps: Step 1: After the device is started, turn on the broadband near-infrared light source and keep it working continuously and stably until all detections are completed; pre-illuminate the light source through the filterless window, continuously collect the original light intensity three times and take the average value as the reference light intensity I_source; multiply the original transmitted light intensity measured by each channel by the correction factor a=I_source / I_window for normalization correction, where I_window is the light intensity of the window measured in the same batch of detections, in order to eliminate the influence of light source attenuation and light intensity drift on the detection results; Step 2: Use air as a medium to calibrate the empty sample cell, control the filter wheel to switch the narrowband filter and baseline filter in sequence, continuously collect the transmitted light intensity three times at each wavelength position and take the average value, and obtain the reference light intensity I0(λ) and the reference light intensity I_ref0 of the reference channel at each characteristic wavelength. Step 3: Add the sugar solution to be tested to the sample cell, collect the transmitted light intensity of the sample through the baseline filter, collect three times in a row and take the average value as I_ref, and calculate the water absorption at the reference wavelength A_water(λ_ref)=-log(I_ref / I_ref0); Step 4: Using the pre-calibrated water absorption ratio coefficient k(λ), convert the water absorption at the reference wavelength into the water background absorption contribution at each characteristic wavelength A_water(λ) = k(λ) × A_water(λ_ref); Step 5: Collect the transmitted light intensity of the sample through each characteristic filter, collect the light intensity three times for each characteristic wavelength and take the average value as I(λ), and calculate the total absorbance A_total(λ) = -log( I(λ) / I0(λ) ); Step 6: Subtract the water background absorption contribution at the corresponding wavelength from the total absorbance at each characteristic wavelength to obtain the net absorbance of the sugar component A_sugar(λ) = A_total(λ) - A_water(λ); Step 7: Construct a system of simultaneous equations by utilizing the differences in the absorbance coefficients of different sugars at various wavelengths. Substitute the net absorbance of each sugar component into the system of equations to solve for the concentration of each sugar component in the mixed sugar solution, and output the detection results to the display module.

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