Processing device, program, and method

Abstract

This processing device acquires an absorption spectrum of a droplet to be measured and calculates the concentration to be measured on the basis of: calibration curve data indicating a relationship between the concentration and a slope when the absorption spectrum is first-order differentiated; and the slope when the acquired absorption spectrum is first-order differentiated.

Description

Processing Device, Program, and Method

[0001] The present invention relates to a processing device, a program, and a method.

[0002] As a conventional technique for optically measuring the concentration of an object, there is ATR (Attenuated Total Reflection).

[0003] Japanese Patent Application Laid-Open No. 2023-138053, Japanese Patent Application Laid-Open No. 2021-162380

[0004] However, in the conventional technique, there are cases where the concentration of the object cannot be accurately calculated, and there is room for improvement.

[0005] On one aspect, an object is to provide a processing device, a program, and a method capable of accurately calculating the concentration of an object.

[0006] The processing device according to one aspect includes a processor. The processor acquires the absorption spectrum of a droplet to be measured, and based on the calibration curve data showing the relationship between the slope when the absorption spectrum is first-order differentiated and the concentration, and the slope when the acquired absorption spectrum is first-order differentiated, calculates the concentration of the measurement target.

[0007] The program according to one aspect causes a computer to execute a process of acquiring the absorption spectrum of a droplet to be measured, and calculating the concentration of the measurement target based on the calibration curve data showing the relationship between the slope when the absorption spectrum is first-order differentiated and the concentration, and the slope when the acquired absorption spectrum is first-order differentiated.

[0008] The method according to one aspect includes a process in which a computer acquires the absorption spectrum of a droplet to be measured, and calculates the concentration of the measurement target based on the calibration curve data showing the relationship between the slope when the absorption spectrum is first-order differentiated and the concentration, and the slope when the acquired absorption spectrum is first-order differentiated.

[0009] According to one embodiment, the concentration of the object can be accurately calculated.

[0010] This is a diagram illustrating the system according to this embodiment. This is a diagram showing an example of calibration curve data. This is a flowchart illustrating the processing procedure of the apparatus according to this embodiment. This is a diagram showing the absorbance spectrum after reference correction. This is a diagram showing the absorbance spectrum after spectral normalization. This is a diagram illustrating the process of calculating the slope. This is a functional block diagram showing the configuration of the apparatus according to this embodiment. This is a diagram illustrating the processing of the generation unit. This is a diagram showing the effect of droplet adhesion rate. This is a diagram (1) when measuring the concentration of granular material. This is a diagram (2) when measuring the concentration of granular material. This is a diagram illustrating an example of hardware configuration. This is a diagram schematically showing ATR. This is a diagram illustrating the conventional technique (1) for calculating concentration from an absorbance spectrum. This is a diagram illustrating the conventional technique (2) for calculating concentration from an absorbance spectrum.

[0011] Embodiments of the processing apparatus, program, and method disclosed herein will be described in detail below with reference to the drawings. However, the present invention is not limited by these embodiments. Furthermore, the same elements are denoted by the same reference numerals, redundant descriptions are omitted as appropriate, and each embodiment can be combined as appropriate within the bounds of consistency.

[0012] (Supplement to the prior art) The above prior art will be explained in more detail. Figure 13 is a schematic diagram of ATR. In Figure 13, incident light 401 from the light source passes through the prism and undergoes total internal reflection at the surface where the prism is in contact with the object to be measured 700, and is emitted as emitted light 402. In total internal reflection, the incident light penetrates into the object to be measured 700 to a depth d, and absorption information of the object to be measured is obtained. Therefore, by measuring the emitted light 402, the absorption spectrum caused by the object to be measured can be obtained.

[0013] Figure 14 is a diagram illustrating a conventional technique (1) for calculating concentration from an absorption spectrum. In graph G1 of Figure 14, the vertical axis corresponds to absorbance, and the horizontal axis corresponds to wavelength. Curve cu1 is the absorption spectrum showing the absorbance at each wavelength. Since the Lambert-Beer law shown in equation (1) holds between absorbance and concentration, the concentration c can be determined from the maximum value D1 of curve cu1. In equation (1), ε1 is the absorption coefficient, and L is the optical path length.

[0014] D1=ε1×c×L...(1)

[0015] Figure 15 is a diagram illustrating the conventional technique (2) for calculating concentration from an absorption spectrum. In graph G2 of Figure 15, the vertical axis corresponds to the second derivative of absorbance, and the horizontal axis corresponds to the wavelength. Curve cu2 is the curve obtained by second-order differentiation of the absorption spectrum, which shows the absorbance at each wavelength. The minimum value obtained by second-order differentiation of absorbance also satisfies the Lambert-Beer law shown in equation (2) with the concentration, so the concentration c can be determined from the minimum value D2 of curve cu2. In equation (2), ε2 is the absorption coefficient and L is the optical path length.

[0016] D2=ε2×c×L...(2)

[0017] For example, while the above-mentioned conventional techniques are effective in wavelength ranges where only the absorbance of the object being measured appears, when using wavelength ranges where the absorbance of substances other than the object is mixed in, the wavelength and amplitude of each element change depending on the concentration and elemental arrangement of the object. As a result, the maximum value of the absorbance spectrum is not proportional to the concentration, making it difficult to accurately calculate the concentration.

[0018] (Embodiment) The processing of the apparatus according to this embodiment will be described below. In the following description, the apparatus according to this embodiment will be referred to as "processing apparatus 100".

[0019] (System Configuration) Figure 1 is a diagram illustrating the system according to this embodiment. As shown in Figure 1, this system includes a light source 10, a prism 11, a spectrometer 12, and a processing unit 100.

[0020] The incident light 10a from the light source 10 passes through the prism 11, undergoes total internal reflection at the surface where the droplet 11a and the prism 11 are in contact, and is emitted as emitted light 11b. The emitted light 11b is input to the spectrometer 12. The droplet 11a is sandwiched between the prism 11 and a plate (not shown) and is filled with water.

[0021] The spectrometer 12 has a wavelength range that includes the wavelength absorbed by the liquid droplet 11a, which is the object to be measured, and has a measurement speed that can track changes in concentration. For example, the spectrometer 12 measures the absorption spectrum based on the total internal reflection method and outputs the absorption spectrum data to the processing device 100.

[0022] The processing device 100 stores calibration curve data 141 that shows the relationship between the slope when the absorbance spectrum is first differentiated and the concentration. Figure 2 shows an example of calibration curve data. In Figure 2, the calibration curve data 141 is shown by the straight line L1 in graph G3. The horizontal axis of graph G3 corresponds to the concentration axis, and the vertical axis corresponds to the slope when the absorbance spectrum is first differentiated. Line segment L1 shows the relationship between concentration and slope.

[0023] The processing unit 100 calculates the concentration of the droplet to be measured based on the slope of the first derivative of the absorption spectrum obtained from the spectrometer 12 and the calibration curve data 141. The processing of the processing unit 100 will be explained using Figure 2. For example, if the slope of the first derivative of the absorption spectrum obtained from the spectrometer 12 is "-8.0E-04", the processing unit 100 calculates a concentration of "20".

[0024] As described above, the processing device 100 can accurately calculate the concentration of the droplet to be measured by calculating the concentration of the droplet based on the slope of the first derivative of the absorbance spectrum obtained from the spectrometer 12 and the calibration curve data 141.

[0025] (Processing details of the processing device) Next, the processing details of the processing device 100 will be explained in more detail. Figure 3 is a flowchart of the processing procedure of the processing device according to the embodiment. As shown in Figure 3, the processing device 100 acquires absorbance spectrum data from the spectrometer 12 (step S101).

[0026] The processing unit 100 performs a reference correction on the absorbance spectrum (step S102). Step S102 is explained in more detail below. As a reference correction, the processing unit 100 performs a process to remove noise from the absorbance spectrum. For example, the processing unit 100 performs a reference correction by performing a Discrete Fourier Transform (DFT) on the absorbance spectrum and then performing a Low Pass Filter (LPF) on the result of the DFT.

[0027] Figure 4 shows the absorbance spectrum after correction to the reference. In graph G4 shown in Figure 4, the vertical axis corresponds to absorbance, and the horizontal axis corresponds to wavelength. Curve cu3 is the absorbance spectrum after correction to the reference, with noise and other unwanted elements removed.

[0028] Returning to the explanation of Figure 3, the processing device 100 performs spectral normalization on the absorbance spectrum after reference correction (step S103). Step S103 is explained in more detail below. For example, the processing device 100 normalizes the absorbance spectrum so that the maximum value is "1".

[0029] Figure 5 shows the absorbance spectrum after spectral normalization. In graph G5 shown in Figure 5, the vertical axis corresponds to the normalized absorbance, and the horizontal axis corresponds to the wavelength. Curve cu4 shows the normalized absorbance spectrum.

[0030] Returning to the explanation of Figure 3, the processing device 100 calculates the slope by taking the first derivative of the absorbance spectrum that has undergone reference correction and spectral normalization (step S104). Step S104 will be explained in more detail below.

[0031] Figure 6 is a diagram illustrating the process of calculating the slope. In the graph G6 shown in Figure 6, the vertical axis corresponds to the absorbance obtained by the first derivative, and the horizontal axis corresponds to the wavelength. Curve cu5 is the curve obtained by the first derivative of the absorbance spectrum. Line segment L2 is a straight line representing the shape of the absorbance spectrum. The processing device 100 calculates the slope of line segment L2 as the slope in step S104.

[0032] Returning to the explanation of Figure 3, the processing device 100 calculates the concentration of the droplet to be measured based on the calculated slope and the calibration curve data 141 (step S105).

[0033] (Functional Configuration of Processing Unit 100) Next, an example of the configuration of the processing unit 100 will be described. Figure 7 is a functional block diagram showing the configuration of the processing unit according to this embodiment. As shown in Figure 7, the processing unit 100 has a communication unit 110, an input unit 120, a display unit 130, a storage unit 140, and a control unit 150.

[0034] The communication unit 110 communicates data with the spectrometer 12 and other external devices.

[0035] The input unit 120 inputs various types of information to the control unit 150. For example, the input unit 120 is an input device such as a keyboard, mouse, or touch panel.

[0036] The display unit 130 displays information output from the control unit 150. The display unit 130 is a display device such as a display or touch panel. For example, the display unit 130 displays information on the concentration of liquid droplets output from the control unit 150.

[0037] The storage unit 140 stores calibration curve data 141, etc. The storage unit 140 is implemented using memory, a hard disk, or the like.

[0038] Calibration curve data 141 provides information showing the relationship between the slope of the first derivative of the absorbance spectrum and the concentration. The explanation of calibration curve data 141 is the same as the explanation given using Figure 2.

[0039] The control unit 150 is a processing unit that controls the entire processing unit 100 and is implemented by, for example, a processor. The control unit 150 has an acquisition unit 151, a calculation unit 152, and a generation unit 153.

[0040] The acquisition unit 151 acquires absorbance spectrum data from the spectrometer 12. The acquisition unit 151 outputs the absorbance spectrum data to the calculation unit 152. If the generation unit 153 is generating calibration curve data 141, the acquisition unit 151 outputs the absorbance spectrum data to the generation unit 153.

[0041] The calculation unit 152 calculates the concentration of the droplet to be measured based on the slope when the absorption spectrum is differentiated by the first order and the calibration curve data 141. The calculation unit 152 may output the calculated concentration data to the display unit 130 for display.

[0042] The description of other processes related to the calculation unit 152 is the same as the processes of steps S102 to S105 described in FIG. 3.

[0043] The generation unit 153 generates calibration curve data 141. Hereinafter, an example of the process of the generation unit 153 will be described. First, after the user sets a droplet with a known concentration on the prism 11, the input unit 120 is operated to input the concentration of the droplet and a generation command for the calibration curve data 141 to the control unit 150.

[0044] When the generation unit 153 receives the concentration of the droplet and the generation command, it acquires the absorption spectrum data via the acquisition unit 151. When the generation unit 153 acquires the absorption spectrum, it calculates the slope by executing the processes of steps S102 to S104 described in FIG. 3 in the same manner as the calculation unit 152.

[0045] The generation unit 153 repeatedly executes the above process for droplets with different concentrations to obtain a set of "concentration of the droplet" and "slope". FIG. 8 is a diagram for explaining the process of the generation unit. The horizontal axis of the graph G7 in FIG. 8 is the axis corresponding to the concentration, and the vertical axis is the axis corresponding to the slope when differentiated by the first order. The points p1, p2, p3, p4, p5 are points showing the relationship between the slope and the concentration obtained by the generation unit 153 repeatedly executing the above process. The generation unit 153 calculates a straight line L1 that is an approximation line of the points p1 to p5. The relationship between the slope shown by the straight line L1 and the concentration is used as the calibration curve data 141.

[0046] Here, the case where the generation unit 153 generates the calibration curve data 141 has been described, but it is not limited thereto, and pre-prepared calibration curve data may be received from the input unit 120 or the like and used.

[0047] (Effect) Next, the effect of the processing device 100 according to the present embodiment will be described. The processing device 100 acquires the absorption spectrum obtained from the spectroscope 12, and calculates the concentration of the measurement target based on the slope when the absorption spectrum is differentiated by the first order and the calibration curve data 141, so that the concentration of the measurement target can be accurately calculated.

[0048] The processing device 100 executes DFT on the absorption spectrum and performs LPF processing on the execution result of the DFT, thereby removing the noise of the absorption spectrum acquired by the acquisition unit. As a result, the influence of scattering by droplets can be removed, and the calculation accuracy of the concentration of the measurement target can be further improved.

[0049] The processing device 100 normalizes the maximum value of the absorption spectrum to 1, and calculates the concentration of the measurement target based on the slope when the normalized absorption spectrum is differentiated by the first order. As a result, the influence of the amount of droplets adhering to the prism can be minimized, and the calculation accuracy of the concentration of the measurement target can be further improved. The amount of droplets adhering to the prism is expressed as the "adhesion rate".

[0050] When the time variation or environmental variation of the concentration of the measurement target is large, it may be difficult to create a calibration curve for identifying the concentration. In that case, the calibration curve data 141 is generated in a state where the prism is filled with liquid (full water), and the concentration of the measurement target is measured using the calibration curve data 141, so that accurate measurement can be achieved.

[0051] FIG. 9 is a diagram showing the influence of the droplet adhesion rate. The vertical axis of the graph G8 in FIG. 9 corresponds to the absorbance, and the horizontal axis corresponds to the wavelength. The curves cu4-1, cu4-2, cu4-3, and cu4-4 show the absorption spectra when the concentration is the same but the adhesion rate is different. In the order of the curves cu4-1, cu4-2, cu4-3, and cu4-4, the droplet adhesion rate is large. As described above, when the processing device 100 performs normalization on each of the curves cu4-1 to cu4-4, the shapes of the absorption spectra almost coincide, and the influence of the amount of droplets adhering to the prism can be eliminated.

[0052] (Regarding other concentration measurements) Measuring the concentration of granular materials is difficult because the optical path length changes depending on how the granular materials are mixed, and the amount of light decreases due to diffuse reflection. For example, methods have been proposed for measuring the concentration of granular materials, such as compounding methods like the KBr tablet method and the Noudour method, methods that measure while mechanically applying pressure, and methods that use two or more different absorption spectra. However, all of these methods are based on changing the state of the material being measured and are not suitable for in-line measurement. In contrast, the processing device 100 calculates the concentration using the processing procedure explained in Figure 3, making it possible to measure the concentration in-line without changing the state of the material being measured.

[0053] Figure 10 is a diagram (1) showing the measurement of the concentration of granular material. The example shown in Figure 10 describes transmission measurement. Incident light 20a from the light source 20 passes through the granular material and is emitted as emitted light 20b. The emitted light 20b is input to the spectrometer 21.

[0054] For example, the spectrometer 21 measures the absorption spectrum based on the emitted light 20b and outputs the absorption spectrum data to the processing unit 100. The processing unit 100 calculates the concentration of the particles 30 based on the absorption spectrum. The process by which the processing unit 100 calculates the concentration of the particles based on the absorption spectrum is the same as the process for calculating the concentration of a liquid droplet based on the absorption spectrum.

[0055] Figure 11 is a diagram (2) showing the measurement of the concentration of granular material. The example shown in Figure 11 describes the reflection measurement. The incident light 25a from the light source 25 is reflected within the granular material 31 and emitted as emitted light 20b. The emitted light 25b is input to the spectrometer 26.

[0056] For example, the spectrometer 25 measures the absorption spectrum based on the emitted light 25b and outputs the absorption spectrum data to the processing unit 100. The processing unit 100 calculates the concentration of the particles 31 based on the absorption spectrum. The process by which the processing unit 100 calculates the concentration of the particles based on the absorption spectrum is the same as the process for calculating the concentration of a liquid droplet based on the absorption spectrum.

[0057] (Hardware) Next, an example of the hardware configuration of the processing unit 100 will be described. Figure 12 is a diagram illustrating an example of the hardware configuration. As shown in Figure 12, the processing unit 100 includes a communication device 6a, an HDD (Hard Disk Drive) 6b, memory 6c, and a processor 6d. Furthermore, each of the parts shown in Figure 12 is interconnected by a bus or the like.

[0058] The communication device 6a communicates with the camera and other external devices. The HDD 6b stores programs and databases that operate the functions shown in Figure 7.

[0059] The processor 6d operates the processes that perform the functions described in Figure 7 by reading programs that perform the same processing as the processing units shown in Figure 7 from the HDD 6b or the like and loading them into memory 6c. For example, this process performs the same functions as the processing units of the processing unit 100. Specifically, the processor 6d executes processes that perform the same processing as the acquisition unit 151, calculation unit 152, generation unit 153, etc.

[0060] Thus, the processing unit 100 operates as a processing unit that performs a method of calculating concentration by reading and executing a program. Furthermore, the processing unit 100 can also achieve the same functionality as the embodiment described above by reading the program from the recording medium using a media reader and executing the read program. It should be noted that the program referred to in these other embodiments is not limited to being executed by the processing unit 100. For example, the present invention can be similarly applied when another computer or server executes the program, or when they cooperate to execute the program.

[0061] This program can be distributed via networks such as the internet. Furthermore, this program can be recorded on computer-readable storage media such as hard disks, flexible disks (floppy disks), CD-ROMs, MOs (Magneto-Optical disks), and DVDs (Digital Versatile Discs), and executed by reading the program from these media using a computer.

[0062] (Other) Some examples of combinations of disclosed technical features are listed below.

[0063] (1) The processing device comprises a processor, which performs the following actions: acquiring the absorbance spectrum of a droplet to be measured; calculating the concentration of the object to be measured based on calibration curve data showing the relationship between the slope when the absorbance spectrum is first differentiated and the concentration, and the slope when the acquired absorbance spectrum is first differentiated.

[0064] (2) The apparatus according to (1), wherein the processor further performs the following actions: remove noise from the absorbance spectrum and calculate the concentration of the object to be measured based on the slope of the first derivative of the noise-removed absorbance spectrum.

[0065] (3) The processing apparatus according to (2), wherein the processor further performs a Discrete Fourier Transform (DFT) on the absorbance spectrum and a Low Pass Filter (LPF) on the result of the DFT to remove noise from the acquired absorbance spectrum.

[0066] (4) The apparatus according to (1), (2), or (3), wherein the processor further performs the following actions: normalizing the maximum value of the absorbance spectrum to 1, and calculating the concentration of the object to be measured based on the slope of the first derivative of the normalized absorbance spectrum.

[0067] (5) The apparatus according to any one of (1) to (4), wherein the processor further generates calibration curve data based on the slope of the first derivative of absorbance spectra obtained from droplets of different concentrations.

[0068] (6) The processing apparatus according to (5), wherein the processor removes noise from the absorption spectra obtained from droplets of different concentrations, and generates the calibration curve data based on the slope of the first derivative of the noise-removed absorption spectra.

[0069] (7) The processing apparatus according to either (5) or (6), wherein the processor normalizes the maximum value of the absorbance spectra obtained from droplets of different concentrations to 1, and generates the calibration curve data based on the slope of the first derivative of the normalized absorbance spectra.

[0070] (8) The apparatus according to any one of (5) to (7), wherein the processor generates the calibration curve data based on the slope of the first derivative of the absorbance spectra obtained from droplets of water of different concentrations.

[0071] (9) The processing apparatus according to any one of (1) to (8), wherein the processor is a liquid droplet full of water and acquires the absorbance spectrum of the liquid droplet to be measured.

[0072] (10) A program that causes a computer to perform a process of obtaining the absorbance spectrum of a droplet to be measured, and calculating the concentration of the object to be measured based on calibration curve data showing the relationship between the slope when the absorbance spectrum is first differentiated and the concentration, and the slope when the absorbance spectrum is first differentiated.

[0073] (11) A method in which a computer acquires the absorbance spectrum of a droplet to be measured, and calculates the concentration of the object to be measured based on calibration curve data showing the relationship between the slope when the absorbance spectrum is first differentiated and the concentration, and the slope when the acquired absorbance spectrum is first differentiated.

[0074] 100 Processing unit 110 Communication unit 120 Input unit 130 Display unit 140 Storage unit 141 Calibration curve data 150 Control unit 151 Acquisition unit 152 Calculation unit 153 Generation unit

Claims

1. The processing apparatus comprises a processor, which performs the following actions: acquiring the absorbance spectrum of a droplet to be measured; calculating the concentration of the droplet to be measured based on calibration curve data showing the relationship between the slope when the absorbance spectrum is first differentiated and the concentration, and the slope when the acquired absorbance spectrum is first differentiated.

2. The apparatus according to claim 1, further comprising the processor removing noise from the absorption spectrum and calculating the concentration of the object to be measured based on the slope of the first derivative of the noise-removed absorption spectrum.

3. The apparatus according to claim 2, wherein the processor further performs a Discrete Fourier Transform (DFT) on the absorbance spectrum and a Low Pass Filter (LPF) on the result of the DFT to remove noise from the acquired absorbance spectrum.

4. The apparatus according to claim 1, wherein the processor further normalizes the absorbance spectrum to a maximum value of 1, and calculates the concentration of the object to be measured based on the slope obtained when the normalized absorbance spectrum is first differentiated.

5. The apparatus according to claim 1, further comprising the processor generating calibration curve data based on the slope of the first derivative of absorbance spectra obtained from droplets of different concentrations.

6. The apparatus according to claim 5, wherein the processor removes noise from absorbance spectra obtained from droplets of different concentrations, and generates calibration curve data based on the slope of the first derivative of the noise-removed absorbance spectra.

7. The apparatus according to claim 5, wherein the processor normalizes the maximum value of the absorbance spectra obtained from droplets of different concentrations to 1, and generates the calibration curve data based on the slope of the first derivative of the normalized absorbance spectra.

8. The apparatus according to claim 5, wherein the processor generates the calibration curve data based on the slope of the first derivative of the absorption spectra obtained from droplets of water at different concentrations.

9. The processing apparatus according to claim 1, wherein the processor is a liquid droplet full of water, and the apparatus acquires the absorbance spectrum of the liquid droplet to be measured.

10. A program that causes a computer to acquire the absorbance spectrum of a droplet to be measured, and to calculate the concentration of the object to be measured based on calibration curve data showing the relationship between the slope of the first derivative of the absorbance spectrum and the concentration, and the slope of the acquired absorbance spectrum when it is first differentiated.

11. A method in which a computer acquires the absorbance spectrum of a droplet to be measured, and calculates the concentration of the object to be measured based on calibration curve data showing the relationship between the slope of the first derivative of the absorbance spectrum and the concentration, and the slope of the acquired absorbance spectrum when it is first differentiated.

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