US20110313702A1 - Spectral measurement device - Google Patents

Spectral measurement device Download PDF

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Publication number
US20110313702A1
US20110313702A1 US13/112,401 US201113112401A US2011313702A1 US 20110313702 A1 US20110313702 A1 US 20110313702A1 US 201113112401 A US201113112401 A US 201113112401A US 2011313702 A1 US2011313702 A1 US 2011313702A1
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band
spectral
correction
wavelength
pass filter
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Tatsuaki Funamoto
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Seiko Epson Corp
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Seiko Epson Corp
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Publication of US20110313702A1 publication Critical patent/US20110313702A1/en
Priority to US13/948,753 priority Critical patent/US8711360B2/en
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02—Details
    • G01J3/027—Control of working procedures of a spectrometer; Failure detection; Bandwidth calculation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/12—Generating the spectrum; Monochromators
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/12—Generating the spectrum; Monochromators
    • G01J3/26—Generating the spectrum; Monochromators using multiple reflection, e.g. Fabry-Perot interferometer, variable interference filters
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/30—Measuring the intensity of spectral lines directly on the spectrum itself
    • G01J3/32—Investigating bands of a spectrum in sequence by a single detector
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/30—Measuring the intensity of spectral lines directly on the spectrum itself
    • G01J3/36—Investigating two or more bands of a spectrum by separate detectors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/42—Absorption spectrometry; Double beam spectrometry; Flicker spectrometry; Reflection spectrometry
    • G01J3/433—Modulation spectrometry; Derivative spectrometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/55—Specular reflectivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/59—Transmissivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/12—Generating the spectrum; Monochromators
    • G01J2003/1213—Filters in general, e.g. dichroic, band

Definitions

  • the present invention relates to spectral measurement devices and the like.
  • Examples of a spectral measurement device include a colorimeter, a spectroscopic analyzer, and a spectrum analyzer.
  • JP-A-2002-277326 discloses a spectral measurement device that uses a transmission wavelength-variable filter.
  • JP-A-5-248952 discloses an optical spectrum analyzer that uses an etalon spectrometer (Fabry-Perot etalon filter) as a spectrometer capable of variably controlling transmission wavelengths.
  • Fabry-Perot etalon filter Fabry-Perot etalon filter
  • the reception signal intensities of the respective spectral bands can be calculated by integrating (summing) the reception light intensity for each wavelength included in the respective spectral bands. For example, by using the integrated value (summed value) as the reception light intensity corresponding to the central wavelengths of the respective spectral bands, it is possible to obtain spectral reception light intensity data for each spectral band.
  • the measurement error increases.
  • the spectrometer for example, the optical band-pass filter
  • the spectrometer becomes too large, and it is necessary to use an expensive spectrometer. Therefore, for example, when reduction of the costs and size of the spectral measurement device is prioritized, it is difficult to use the high-performance optical band-pass filters.
  • An advantage of some aspects of the invention is that it provides a spectral measurement device capable of improving measurement accuracy without using an expensive optical band-pass filter, for example.
  • a spectral measurement device including: an optical band-pass filter section that has first to n-th wavelengths (n is an integer of 2 or more) having a predetermined wavelength width as a spectral band thereof; a light receiving section that receives light from the optical band-pass filter section; a correction operation section that performs an operation to correct a reception signal obtained from the light receiving section; and a signal processing section that executes predetermined signal processing based on the reception signal corrected by the correction operation section, wherein the correction operation section corrects the reception signal based on a change in a spectral distribution of the reception signal.
  • a characteristic line which may be a straight line or a curve, and is sometimes referred to as a spectral distribution curve
  • an optical spectrum a reception light intensity distribution for each wavelength
  • the correction operation section corrects the reception signal (reception data) based on a change in the spectral distribution of the reception signal. In this way, measurement errors (measurement errors resulting from the change in the spectral distribution: integration errors) are suppressed.
  • the reception signal can be corrected by superimposing (adding or subtracting) a correction value on the reception signal.
  • the reception signal can be also corrected by multiplying the reception signal by the correction value (correction coefficient).
  • the measurement error is reduced by the correction operation. Therefore, it is possible to perform high-accuracy spectral measurement, for example, by using an optical filter (variable wavelength filter and the like) which has good usability and is relatively cheap and small.
  • the correction operation section calculates a second derivative of a spectral distribution curve representing the spectral distribution of the reception signal, decreases the value of the reception signal through the correction when the second derivative is positive, and increases the value of the reception signal through the correction when the second derivative is negative.
  • the correction operation section generates a correction value based on the second derivative of the spectral distribution curve and corrects the reception signal (reception data or reception light intensity data) using the generated correction value.
  • the spectral distribution curve is a downwardly convex curve.
  • an integrated value of the spectral intensities for each wavelength of one spectral band tends to be larger than the actual reception light intensity at the central wavelength of the spectral band. Therefore, when the second derivative is positive, the value of the reception signal (reception data) is decreased by correction so as to suppress errors.
  • the polarity of the second derivative is negative, the spectral distribution curve is an upwardly convex curve.
  • a predetermined fixed value may be used as the correction value, and a correction value (variable correction value) of which the value changes in accordance with the degree of the change in the spectral distribution curve may be used.
  • a variable correction value a method in which the value of the correction value is continuously changed in accordance with the degree of the change in the spectral distribution may be used.
  • a method in which the degree of the change in the spectral distribution may be divided into a plurality of steps using a threshold or the like, and the value of the correction value is changed (switched) gradually in accordance with the respective steps may be used.
  • the second derivative can be calculated by a simple operation which uses the measurement data of three adjacent wavelength bands, for example.
  • a plane curve (approximated curve) may be estimated based on the actual measurement values (discrete values), and the second derivative of the plane curve may be calculated.
  • the correction operation section controls a correction value used for the correction variably based on the magnitude of an absolute value of the second derivative.
  • the measurement error decreases when the change in the curvature of the spectral distribution curve is smooth and increases when the change is abrupt. That is, the measurement error correlates with the curvature of the spectral distribution curve.
  • the degree of the change in the curvature of the spectral distribution curve can be determined based on the magnitude of the absolute value of the second derivative. Therefore, in this aspect of the invention, the correction operation section controls the correction value variably based on the magnitude of the absolute value of the second derivative. For example, when the curvature of the spectral distribution curve changes abruptly, the value of the correction value is adjusted variably so that the amount of correction of the reception signal by the correction value is larger than that when the change is smooth. In this way, the correction accuracy is improved further.
  • the second derivative is calculated by a simple operation using the actual measurement data p 1 , p 2 , and p 3 (3-point data) for each of three adjacent spectral bands (first to third spectral bands). Moreover, the second derivative is used for generation of the correction value.
  • the spectral distribution curve is a downwardly convex curve.
  • the spectral distribution curve is an upwardly convex curve.
  • the second derivative Q 1 is 0, the spectral distribution changes in a straight line.
  • the curvature of the spectral distribution curve is large (the change in the spectral intensity is abrupt)
  • the actual measurement data p 3 increases.
  • the absolute value of the second derivative Q 1 increases.
  • the second derivative Q 1 (positive or negative) serves as information on the shape of the spectral distribution curve (information on whether the curve is upwardly convex or downwardly convex) and information on the abruptness of the change in the curvature of the spectral distribution.
  • the correction coefficient k 1 is basically a positive real number excluding 0, k 1 may exceptionally be set to 0 (for example, when no correction is executed). According to this method, the correction value of which the magnitude is variably controlled can be generated quickly (for example, real-time) by a simple method (simple configuration).
  • the optical band-pass filter section functions as an m-th band-pass filter corresponding to the m-th wavelength band and also functions as a k-th band-pass filter corresponding to the k-th wavelength band
  • the correction operation section further includes a noise estimation section that estimates the amount of the noise component for each wavelength band of the k-th wavelength band included in an interest reception signal obtained by the light receiving section receiving transmission light or reflection light of the m-th band-pass filter corresponding to the m-th wavelength band, and a noise removal and correction section that performs correction of subtracting the sum of the estimated noise component for each wavelength band from the interest
  • the optical band-pass filter section used as a spectrometer functions as a m-th band-pass filter corresponding to an m-th wavelength band (1 ⁇ m ⁇ n) which is an interest wavelength band and a k-th band-pass filter corresponding to a k-th wavelength band (k ⁇ m and 1 ⁇ k ⁇ n) which is a non-interest wavelength band.
  • a component of wavelengths other than a desired wavelength band is mixed, and the reception signal level increases by an amount corresponding to the component. Thus, a base floating error occurs.
  • a correction operation (base floating correction) is executed in which the sum of the noise component for each wavelength band included in all of the reception signals (that is, interest reception signals) obtained by receiving light from the m-th band-pass filter, and the calculated sum of noise components is subtracted from all of the reception signals to thereby suppress the effect of noise.
  • This base floating correction is preferably executed prior to the integration error correction. That is, noise is removed from the spectroscopic data of the respective spectral bands (spectral wavelength bands) through the base floating correction, and the integration error correction is executed based on the spectroscopic data in which the noise is removed.
  • the correction accuracy can be further improved.
  • a noise estimation section and a noise removal and correction section are provided as a configuration for the base floating correction.
  • the noise estimation section estimates the amount of the noise component for each wavelength band of the k-th wavelength band included in an interest reception signal obtained by the light receiving section receiving transmission light or reflection light of the m-th band-pass filter corresponding to the m-th wavelength band.
  • the noise removal and correction section performs correction of subtracting the sum of the estimated noise component for each wavelength band from the interest reception signal to thereby calculate a corrected reception signal.
  • an etalon filter can be used, for example, and as a reflection-type optical band-pass filter, a dichroic mirror can be used, for example.
  • the first to n-th optical band-pass filters corresponding to the respective wavelength bands may be realized using a variable wavelength filter and may be realized by juxtaposing a plurality (n) of fixed wavelength filters having different wavelength bands.
  • the noise estimation section estimates the amount of the noise component for each wavelength band in the non-interest wavelength band through the operation based on Formula (1).
  • the noise removal and correction section calculates the sum of the estimated noise components for each wavelength band and calculates the corrected interest reception signal (that is, corrected reception signal) through the operation based on Formula (2).
  • Sk is the non-interest reception signals obtained by the light receiving section receiving the transmission light or the reflection light of the k-th band-pass filter.
  • the non-interest reception signals are all of the reception signals which are the entire output of the photodiodes and are known since they are actually measured.
  • it is ideal to use only the value of a reception signal corresponding to light of the k-th wavelength band among the non-interest reception signals since it is not possible to separate only the reception component corresponding to the light of the k-th wavelength band, all of the reception signals of the k-th band-pass filter are used as a substitute.
  • P(m,k) is the transmittance or the reflectance in the k-th wavelength band of the m-th band-pass filter.
  • the notation P(m,k) represents the transmittance (or the reflectance) P in the “k”-th wavelength band which is the non-interest wavelength band, of the “m”-th band-pass filter (an optical filter associated with the “m”-th wavelength band which is the interest wavelength).
  • the spectral properties (relative spectral intensities of the respective wavelengths) in the all of the wavelength bands of the m-th band-pass filter are known.
  • P(m,k) can be calculated by integrating the transmittance (reflectance) of the respective wavelengths included in the k-th wavelength band (that is, by calculating all of the area of the k-th wavelength band in a graph showing the relationship between wavelengths and transmittance (reflectance)). Therefore, P(m,k) is known.
  • P(k,k) is the transmittance or the reflectance in the k-th wavelength band of the k-th band-pass filter.
  • the notation P(k,k) represents the transmittance (or the reflectance) P in the “k”-th wavelength band which is the non-interest wavelength band, of the “k”-th band-pass filter (an optical filter associated with the “k”-th wavelength band which is the non-interest wavelength).
  • the k-th band-pass filter is a filter associated with the k-th wavelength band, the transmittance in the k-th wavelength band is known.
  • the interest reception signal Sm is calculated using these known values. That is, the noise components for each wavelength band of the k-th wavelength band included in all of the reception signals obtained by the light receiving section receiving light from the m-th band-pass filter which is a filter associated with the interest wavelength band are calculated.
  • the use of the expression “noise components N(m,k) for each wavelength band of the k-th wavelength band” is based on the following reason. As described above, the first to n-th wavelength bands are wavelength bands each having a predetermined wavelength width, and if n ⁇ 3, there will be two or more k-th wavelength bands which are the non-interest wavelength bands. Considering this, the expression expresses a case in which when there is a plurality of wavelength bands as the non-interest wavelength bands, the noise components for each wavelength band are calculated.
  • the reception signal Sk corresponding to the transmittance (reflectance) P(k,k) in the k-th wavelength band of the k-th band-pass filter it is possible to obtain the reception signal Sk corresponding to the transmittance (reflectance) P(k,k) in the k-th wavelength band of the k-th band-pass filter. That is, all of the reception signals can be taken to be a substitute by regarding them as the reception signal corresponding to the k-th wavelength band. If P(k,k) is changed to P(m,k), since the amount of reception signals changes in accordance with the ratio between P(k,k) and P(m,k), the amount of reception signals will be changed to Sk ⁇ P(m,k)/P(k,k) ⁇ . This amount of reception signal is regarded as the noise components N(m,k) for each wavelength band of the k-th wavelength band included in the interest reception signal Sm. Formula (1) above expresses this.
  • the noise removal and correction section calculates the sum ⁇ N(m,k) of the estimated noise components N(m,k) for each wavelength band.
  • the notation ⁇ N(m,k) represents the entire signal components (that is, all of the noise components ⁇ N) of the “k”-th wavelength band which is the non-interest wavelength band, included in all of the reception signals obtained by the light receiving section receiving light from the “m”-th band-pass filter which is a filter associated with the interest wavelength band.
  • the corrected reception signal Smc is obtained by removing noise therefrom and can be regarded as substantially the reception signal corresponding to light of the interest wavelength band.
  • the measurement accuracy of the optical spectrum data is improved.
  • noise components are calculated based on a way of thinking in which “if P(k,k) is changed to P(m,k), since the amount of reception signals changes in accordance with the ratio between P(k,k) and P(m,k), the amount of reception signals will be changed to Sk ⁇ P(m,k)/P(k,k) ⁇ ”.
  • an optical filter being used is switched from the k-th band-pass filter to the m-th band-pass filter, there is a difference in the total amount (total light intensity) of light entering the light receiving section after passing through the respective filters due to the different properties (for example, relative transmittance distribution or relative reflectance distribution) of the respective filters.
  • Sk used in Formula (1) above represents all of the reception signals of the light receiving section when the k-th band-pass filter is used.
  • the noise components that are to be calculated are noise components included in all of the reception signals of the light receiving section when the m-th band-pass filter is used. That is, the noise components included in all of the reception signals when the m-th band-pass filter is used are estimated using actual measurement values when the k-th band-pass filter (a filter different from the m-th band-pass filter associated with correction) is used.
  • the noise components included in all of the reception signals when the m-th band-pass filter is used are estimated using actual measurement values when the k-th band-pass filter (a filter different from the m-th band-pass filter associated with correction) is used.
  • there is a difference in the total amount (total light intensity) of light entering the light receiving section after passing through the respective filters due to the different properties (for example, relative transmittance distribution or relative reflectance distribution) of the respective filters. Therefore, by adding signal processing for compens
  • the operational formula of Formula (1) above is multiplied by the correction coefficient R for correcting the difference in the transmittance property or the reflectance property between filters (that is, the operation based on Formula (3) above is executed).
  • the sum of the transmittance or the reflectance of all of the wavelength bands of the m-th band-pass filter is denoted as ⁇ Qm(1 ⁇ n)
  • the sum of the transmittance or the reflectance of all of the wavelength bands of the k-th band-pass filter is denoted as ⁇ Qk(1 ⁇ n).
  • the ratio ( ⁇ Qm(1 ⁇ n)/ ⁇ Qk(1 ⁇ n)) of the sum of transmittance properties and reflectance properties between the respective filters will be referred to as the correction coefficient R for correcting (compensating for) the difference in the transmittance properties or the reflectance properties between the respective filters.
  • the correction coefficient R By multiplying the operational formula of Formula (1) above by the correction coefficient R, the difference in the transmittance properties or the reflectance properties between the respective filters is compensated. Accordingly, the measurement accuracy of the optical spectrum data is improved further.
  • the optical band-pass filter section is a variable gap etalon filter.
  • variable wavelength filter is one type of filter device and is a high-performance optical filter capable of realizing a plurality of filter properties. Since the variable wavelength filter can cover a plurality of wavelength bands using the same filter, it is effective for miniaturization and cost reduction of an optical filter and has excellent usability. Although the variable wavelength filter generally does not have excellent wavelength separation properties, as described above, the measurement accuracy can be improved through correction of the reception data. Therefore, it is possible to realize a spectral measurement device which is small, light, and cheap, and has high measurement accuracy, for example, by using variable wavelength filters having high performance.
  • the signal processing section measures a spectrophotometric distribution of a measurement target sample based on the reception signal corrected by the correction value.
  • FIG. 1 is a diagram showing an example of a configuration of a spectral measurement device.
  • FIGS. 2A and 2B are diagrams showing a configuration example of a variable-gap etalon and an example of band-pass filter properties, respectively.
  • FIG. 3 is a diagram showing an example of a configuration of a rotary band-pass filter used as an optical band-pass filter.
  • FIG. 4 is a diagram showing, for the purpose of comparison, a spectral distribution curve (in this example, spectral reflectance distribution curve) generated based on 16-point data before correction, actually measured by the spectral measurement device of FIG. 1 and an actual spectral distribution (spectral reflectance distribution) of a sample.
  • a spectral distribution curve in this example, spectral reflectance distribution curve
  • FIGS. 5A and 5B are diagrams illustrating the cause of an error (integration error) resulting from a change in the spectral reflectance of a sample.
  • FIG. 6 is a diagram showing a change in the first and second derivatives of a spectral distribution curve obtained through computer simulation.
  • FIGS. 7A and 7B are diagrams showing examination results based on computer simulation on how a reception light intensity distribution (spectral light intensity distribution) obtained by a photodiode receiving light having passed through an optical band-pass filter will change in accordance with the shape of a characteristic line representing a spectral reflectance of a sample.
  • FIG. 8 is a diagram illustrating a configuration example of a correction operation section provided in the spectral measurement device and an outline of a correction operation.
  • FIGS. 9A to 9C are diagrams illustrating examples of a calculation method of a second derivative.
  • FIG. 10 is a diagram showing, for the purpose of comparison, a spectral distribution curve (in this example, a spectral reflectance distribution curve) generated based on 16-point data after integration error correction and an actual spectral distribution (in this example, a spectral reflectance distribution) of a sample.
  • a spectral distribution curve in this example, a spectral reflectance distribution curve
  • FIG. 11 is a diagram illustrating a configuration example of a correction operation section and an outline of a correction operation according to a second embodiment.
  • FIGS. 12A and 12B are diagrams illustrating the effect of base floating correction.
  • FIGS. 13A and 13B are diagrams showing the distribution of reception signal intensities (relative reception signal intensities) of respective photodiodes and showing the extracted optical spectra of a reception signal in a third wavelength band (a wavelength band having a central wavelength of 440 nm) in an enlarged scale, respectively.
  • FIGS. 14A and 14B are diagrams illustrating an outline of an estimation method of noise components in a 13-th wavelength band, which are included in the light of a third wavelength band passed through a third band-pass filter.
  • FIGS. 15A to 15D are diagrams showing a first specific example (correction using Operational Formula (1)) of a method of estimating the amount of the noise components.
  • FIGS. 16A to 16C are diagrams showing a second specific example (correction using Operational Formula (3)) of a method of estimating the amount of the noise components.
  • FIGS. 17A to 17C are diagrams illustrating the content of noise removal and correction by a noise removal and correction section.
  • FIGS. 18A to 18C are diagrams showing an example of a method of calculating the sum of the noise components.
  • FIGS. 19A and 19B are diagrams showing a difference in the band-pass filter properties depending on the presence of correction processing.
  • a spectral measurement device for example, a colorimeter, a spectroscopic analyzer, and an optical spectrum analyzer
  • FIG. 1 is a diagram showing an example of a configuration of a spectral measurement device.
  • a spectral measurement device include a colorimeter, a spectroscopic analyzer, and an optical spectrum analyzer.
  • a light source 100 is used when performing color measurement of a sample 200
  • a light source 100 ′ is used when performing spectroscopic analysis of the sample 200 .
  • the spectral measurement device includes the light source 100 (or 100 ′), an optical band-pass filter section (BPF) 300 , a light receiving section (PD) 400 using photodiodes and the like, a correction operation section 500 that performs a correction operation (correction processing) for correcting a reception signal (light intensity data) obtained from the light receiving section 400 , and a signal processing section 600 that calculates a spectrophotometric distribution and the like based on the light intensity data (reception data) after correction.
  • the light source 100 ( 100 ′) an incandescent bulb, a fluorescent bulb, a discharge tube, a light source (a solid-state lighting source) using a solid-state light emitting element such as an LED, and the like can be used.
  • an m-th wavelength band (1 ⁇ m ⁇ n) is sometimes referred to as an interest wavelength band
  • a k-th wavelength band (k ⁇ m and 1 ⁇ k ⁇ n) other than the m-th wavelength band is sometimes referred to as a non-interest wavelength band.
  • the optical band-pass filter section (BPF) 300 functions as an m-th band-pass filter corresponding to the m-th wavelength band and also functions as a k-th band-pass filter corresponding to the k-th wavelength band.
  • the optical band-pass filter section 300 may be a transmission-type optical band-pass filter and may be a reflection-type optical band-pass filter.
  • a transmission-type optical band-pass filter a variable-gap etalon filter can be used, for example.
  • a dichroic mirror or a dichroic prism
  • the dichroic mirror is one type of mirror formed of a special optical material, and is an optical filter having a property such that it reflects light of a specific wavelength and transmits light of other wavelengths.
  • 16 band-pass filters corresponding to the respective 16 spectral bands are illustrated. These 16 band-pass filters are illustrated as the first band-pass filter BPF( 1 ) to the 16th band-pass filter BPF( 16 ).
  • the respective band-pass filters BPF( 1 ) to BPF( 16 ) have a property such that they transmit (or reflect) at least light of a specific wavelength.
  • the first to 16th optical band-pass filters BPF( 1 ) to BPF( 16 ) corresponding to the respective wavelength bands may be realized using one or plural variable wavelength filters and may be realized by arranging (juxtaposing) 16 fixed wavelength filters having different wavelength bands.
  • the central wavelengths of the spectral bands associated with the first to 16th band-pass filters BPF( 1 ) to BPF( 16 ) are ⁇ 1 to ⁇ 16 .
  • the light receiving section (PD) 400 that receives light from the optical band-pass filter section 300 includes 16 photodiodes. That is, these 16 photodiodes are illustrated as the first photodiode PD( 1 ) to the 16th photodiode PD( 16 ).
  • the respective photodiodes PD( 1 ) to PD( 16 ) have reception sensitivity to the above-mentioned respective wavelength bands.
  • optical sensors having a broad wavelength band to which they have reception sensitivity, one or plural optical sensors may be used.
  • the correction operation section 500 generates a correction value based on the polarity of a second derivative of the spectral distribution (sometimes referred to as a spectral distribution curve) of a reception signal and corrects the reception signal using the correction value.
  • a second derivative of the spectral distribution sometimes referred to as a spectral distribution curve
  • the curvature (the degree of curvedness) of a spectral distribution curve representing an optical spectrum changes abruptly, particularly, a difference between an integrated value of reception light intensity for each wavelength of the spectral band and an actual reception light intensity at the central wavelength of the spectral band increases. Therefore, the reception signals (reception data) are corrected through signal processing so as to suppress a measurement error (integration error).
  • the polarity of error is different depending on whether a curve representing the optical spectrum is an upwardly convex curve or a downwardly convex curve. That is, when a reception light intensity value obtained through integration is larger than an actual reception light intensity value, the error has a positive polarity. When the former value is smaller than the latter value, the error has a negative polarity. Thus, it is necessary to change the polarity (positive/negative) of the correction value so as to correspond to the polarity (positive/negative) of the error. Whether the spectral distribution curve is an upwardly convex curve or a downwardly convex curve can be determined by the polarity of a second derivative of the spectral distribution of the reception signal.
  • the correction operation section 500 generates the correction value based on the polarity of the second derivative of the spectral distribution of the reception signal and corrects the reception signal (reception data, reception light intensity data) using the correction value. As described above, this correction is sometimes referred to as integration error correction.
  • the reception signal can also be corrected by multiplying the reception signal by the correction value (correction coefficient).
  • the measurement error is reduced by the correction operation. Therefore, it is possible to perform high-accuracy spectral measurement, for example, by using an optical filter (variable wavelength filter and the like) which has good usability and is relatively cheap and small.
  • the correction operation section 500 can execute base floating correction in addition to the integration error correction. An example of executing the base floating correction together will be described in the second embodiment.
  • FIGS. 2A and 2B are diagrams showing a configuration example of a variable-gap etalon and an example of band-pass filter properties, respectively.
  • a variable-gap etalon filter includes a first substrate 11 and a second substrate 12 disposed to face each other, a first reflection film 13 formed on the principal surface (front surface) of the first substrate 11 , a second reflection film 14 formed on the principal surface (front surface) of the second substrate 12 , and a first actuator (for example, a piezoelectric element or the like) 15 a and a second actuator 15 b which are interposed between the respective substrates so as to adjust a gap (distance) between the respective substrates.
  • a first actuator for example, a piezoelectric element or the like
  • the first and second actuators 15 a and 15 b are driven by a first drive circuit 16 a and a second drive circuit 16 b , respectively. Moreover, the operation of the first and second drive circuits 16 a and 16 b is controlled by a gap control circuit 17 .
  • Light Lin incident from the outside at a predetermined angle ⁇ passes through the first reflection film 13 substantially being seldom scattered.
  • the reflection of light occurs repeatedly between the first reflection film 13 formed on the first substrate 11 and the second reflection film 14 formed on the second substrate 12 .
  • interference of light occurs, part of the incident light passes through the second reflection film 14 on the second substrate 12 , and output light Lout reaches the light receiving section 400 (the photodiode PD).
  • Which wavelength of light will be strengthened by the interference depends on the gap d between the first substrate 11 and the second substrate 12 . Therefore, it is possible to change the wavelength band (spectral band) of light passing through the second reflection film 14 by controlling the gap d variably. For example, 16 spectral bands can be realized by controlling the gap d so as to be changed from d 1 to d 16 .
  • FIG. 2B shows a spectral property of the variable-gap etalon filter (specifically, a relative spectral intensity for each of 16 wavelength bands each having a width of 20 nm).
  • a variable-gap etalon filter is used as the optical band-pass filter section (optical filter section) 300 , since a plurality of transmission wavelength bands can be realized using one filter, it is possible to obtain a spectrometer section which is simple, small, and cheap.
  • FIG. 3 is a diagram showing an example of a configuration of a rotary band-pass filter used as an optical band-pass filter.
  • a rotary band-pass filter includes an optical system (lens) 87 and a rotatable disk 85 in which a plurality of band-pass filters 85 a to 85 f having different transmission wavelength bands is incorporated.
  • One of the band-pass filters 85 a to 85 f is selected in accordance with a measurement target wavelength band and measurement is executed.
  • FIG. 4 is a diagram showing, for the purpose of comparison, a spectral distribution curve (in this example, spectral reflectance distribution curve) generated based on 16-point data before correction, actually measured by the spectral measurement device of FIG. 1 and an actual spectral distribution (spectral reflectance distribution) of a sample.
  • the spectral reflectance distribution curve is generated, for example, by the following procedure.
  • the surface color of a sample being used is red.
  • the spectral measurement device shown in FIG. 1 is used as a colorimeter (color measurement device), and light reflected from a sample is received by the light receiving section 400 to obtain reception data of 16 points. Then, a spectral reflectance distribution curve is generated based on the reception data.
  • a spectral distribution curve in this example, spectral reflectance distribution curve
  • the horizontal axis represents a wavelength
  • the vertical axis represents a relative reception light intensity.
  • the 16-point data before correction are indicated by black squares
  • the actual spectral distribution (spectral reflectance distribution) of the sample is indicated by a solid line.
  • the first is a phenomenon in which the actual measurement value is higher than the actual reception light intensity in a wavelength band (wavelength band A 1 ) corresponding to the wavelengths 580 nm and 600 nm.
  • the second is a phenomenon in which the actual measurement value is lower than the actual reception light intensity conversely in a wavelength band (wavelength band A 2 ) of 640 nm to 700 nm.
  • the actual measurement data in the wavelength of 620 nm corresponds to an inflection point (a point where the second derivative is zero) of the spectral distribution curve, and thus, substantially no error occurs.
  • the error (integration error) resulting from the change in the spectral reflectance of the sample in the wavelength bands A 1 and A 2 is corrected using the correction value, thus making it possible to generate more accurate spectral reflectance. This will be described in detail below.
  • FIGS. 5A and 5B are diagrams illustrating the cause of an error (integration error) resulting from a change in the spectral reflectance of a sample.
  • the spectral distribution curve shown in FIG. 5A is a curve (downwardly convex curve) in which the second derivative is positive.
  • the spectral distribution curve shown in FIG. 5B is a curve (upwardly convex curve) in which the second derivative is negative.
  • a bold solid line represents a spectral reflectance curve representing the actual spectral reflectance of the sample 200 .
  • This spectral reflectance curve is a downwardly convex curve (second derivative: positive).
  • the points A, B, and C indicated by black circles represent reception light intensities (ideal reception light intensities) with no error at the respective central wavelengths (560 nm, 580 nm, and 600 nm) of three spectral wavelength bands (550 nm to 570 nm, 570 nm to 590 nm, and 590 nm to 610 nm) having a width of 20 nm.
  • the points A′, B′, and C′ represent the actual measurement values with errors (namely, the integrated values of the reception light intensities in the respective wavelength bands having the width of 20 nm).
  • the integrated values (smoothed areas) of the respective wavelength bands are indicated by hatching.
  • a wavelength band of 570 nm to 590 nm will be focused on, for example.
  • the reception light intensity of this spectral wavelength band can be obtained by integrating (smoothing) the reception light intensities (spectral intensities) corresponding to the respective wavelengths of 570 nm to 590 nm.
  • the integrated value of the reception light intensities will be used as a reception light intensity corresponding to the central wavelength 580 nm of this spectral wavelength band.
  • regions a and b will be focused on.
  • a reception light intensity level B′ after integration is identical to an ideal reception light intensity B.
  • the curve (spectral distribution curve) representing the spectral distribution of the wavelength band of 570 nm to 590 nm is a downwardly convex curve, and the curvature of the spectral distribution curve changes abruptly, the area of the region a is larger than the area of the region b.
  • an error corresponding to the difference in the area occurs, and the level B′ of the integrated value is higher than the ideal reception light intensity B.
  • an integration error an error resulting from the change in the spectral reflectance of the sample
  • the spectral distribution curve representing the spectral reflectance of the sample 200 is illustrated as a curve (upwardly convex curve) in which the second derivative is negative.
  • the points D, E, and F represent the ideal reception light intensities at the central wavelengths of the respective wavelength bands.
  • the points D′, E′, and F′ represent the actual measurement values with errors.
  • a wavelength band of 570 nm to 590 nm will be focused on. Regarding the respective areas of the regions a and b in this wavelength band, a relation of a>b is satisfied. Therefore, an error corresponding to the difference between the areas occurs, and the level E′ of the actual integrated value is lower than the ideal reception light intensity E. In this way, an integration error (an error resulting from the change in the spectral reflectance of the sample) occurs.
  • the level of the point E′ is lower than the level of the point E.
  • the level of the point F′ is lower than the level of the point F.
  • the level of the actual measurement value will be higher or lower than the ideal level depends on the shape of the spectral distribution curve (that is, whether the second derivative of the spectral distribution curve is positive or negative). Therefore, when calculating the correction value, it is preferable to change the polarity (positive/negative) of the correction value so as to correspond to the polarity (positive/negative) of the second derivative of the spectral distribution curve. Moreover, since the degree of error (the amount of error) increases when the spectral distribution changes abruptly, it is preferable to change the magnitude of the correction value variably in accordance with the degree of the change in the spectral distribution to execute correction on a case by case basis.
  • FIG. 6 is a diagram showing a change in the first and second derivatives of a spectral distribution curve obtained through computer simulation.
  • the solid line represents the spectral distribution curve (spectral reception light intensity curve) representing the spectral reflectance of the sample 200
  • the one-dot chain line represents the change in the first derivative
  • the bold dotted line represents the change in the second derivative.
  • the second derivative changes abruptly in the wavelength band of 570 nm to 590 nm. Therefore, as described in FIG. 5A , the integration error (an error resulting from the change in the spectral reflectance of the sample) becomes most obvious in the wavelength band of 570 nm to 590 nm.
  • FIGS. 7A and 7B are diagrams showing examination results based on computer simulation on how a reception light intensity distribution (spectral light intensity distribution) obtained by a photodiode receiving light having passed through an optical band-pass filter will change in accordance with the shape of a characteristic line representing a spectral reflectance of a sample.
  • the spectral property (spectral transmittance property) of the optical band-pass filter is indicated by a bold solid line.
  • characteristic lines representing the spectral reflectance of four samples are used.
  • FIG. 7B shows the reception light intensity distributions (spectral light intensity distributions) corresponding to the respective samples.
  • the spectral reception light intensity obtained by the photodiode receiving light having passed through the optical band-pass filter can be calculated by multiplying the spectral reflectance of the sample by the spectral transmittance of the optical band-pass filter.
  • the spectral reception light intensity property indicated by a dotted line corresponds to the sample in which the spectral reflectance is constant.
  • the shape of the curve representing the spectral reception light intensity property indicated by the dotted line is identical to the shape of the spectral transmittance curve of the optical band-pass filter.
  • the curves representing the spectral reception light intensity properties corresponding to the other three samples since the spectral reflectance of the samples increases towards the high-wavelength band, the curves representing the spectral reception light intensity properties also shift towards the high-wavelength band (right side).
  • the sparsely dotted curve corresponds to the sample indicated by the curve having the positive curvature (>0); the solid line corresponds to the sample in which the spectral reception light intensity is indicated by a monotonically increasing straight line; and the one-dot chain line corresponds to the sample indicated by the curve having the negative curvature ( ⁇ 0).
  • the correction operation section 500 ( FIG. 1 ) generates a correction value based on the polarity of the second derivative of the spectral distribution (spectral distribution curve) of the reception signal and corrects the reception signal using the correction value.
  • the correction operation section 500 decreases the value of the reception signal (reception data) through correction using the correction value.
  • the correction operation section 500 increases the value of the reception signal (reception data) through correction using the correction value.
  • the spectral measurement device of the present embodiment is provided with the correction operation section 500 having a configuration as shown in FIG. 8 .
  • FIG. 8 is a diagram illustrating a configuration example of a correction operation section provided in the spectral measurement device and an outline of a correction operation.
  • dispersed light components w( 1 ) to w( 16 ) are output from the first to 16th band-pass filters BPF( 1 ) to BPF( 16 ) included in the optical band-pass filter section 300 .
  • the first to 16th photodiodes PD( 1 ) to PD( 16 ) included in the light receiving section 400 receive the dispersed light components w( 1 ) to w( 16 ) and output electric signals (analog reception signals) S 1 a to S 16 a (the ending characteristics a indicate that they are analog signals) corresponding to reception light intensities through photoelectric conversion.
  • the correction operation section 500 includes, for example, an initial-stage amplifier 502 that amplifies the reception signal output from the light receiving section 400 , an A/D converter 504 that converts the output signal (analog signal) of the initial-stage amplifier 502 into a digital signal, a memory 506 that can be used for storing various types of data, and an integration error correction section 521 .
  • the integration error correction section 521 includes a readout circuit 523 that reads out the reception data from the memory 506 , a second derivative calculation section 525 that calculates a second derivative of a spectral light intensity distribution (a broad-sense spectral distribution or a spectral distribution curve) based on the reception data, a multiplication section 527 of a correction coefficient (k 1 : a real number), and a correction value superimposition section (correction value addition/subtraction section) 529 that superimposes (adds or subtracts) the correction value output from the multiplication section 527 on the readout reception data (reception signal).
  • a readout circuit 523 that reads out the reception data from the memory 506
  • a second derivative calculation section 525 that calculates a second derivative of a spectral light intensity distribution (a broad-sense spectral distribution or a spectral distribution curve) based on the reception data
  • the memory 506 temporarily stores the reception data (or reception light intensity data) S 1 to S 16 output from the A/D converter 504 .
  • the readout circuit 523 reads out the reception data S 1 to S 16 from the memory 506 .
  • the second derivative calculation section 525 calculates the second derivative Q 1 of the spectral distribution (spectral distribution curve) based on the readout reception data S 1 to S 16 . A calculation method will be described later with reference to FIGS. 9A to 9C .
  • the correction coefficient multiplication section 527 multiplies the calculated second derivative Q 1 by a correction coefficient k 1 .
  • the correction coefficient k 1 may be a fixed value and may be adaptively generated on a case by case basis.
  • a correction value Cx for a correction target spectral band is calculated through an operation based on the second derivative and the correction coefficient k 1 .
  • the second derivative Q 1 serves as information on the shape of the spectral distribution curve (information on whether the curve is upwardly convex or downwardly convex) and information on the abruptness of the change in the spectral distribution (information on whether or not the change is abrupt or smooth).
  • the second derivative Q 1 is used as the basic data for calculation of the correction value. That is, as described above, the correction value Cx for a correction target spectral band is calculated through an operation (specifically, multiplication of the second derivative Q 1 by the correction coefficient k 1 ) based on the calculated second derivative Q 1 and the correction coefficient k 1 (k 1 is a real number).
  • the correction value Cx has a property such that it has a polarity (positive/negative) corresponding to the upward/downward convex shape of the spectral distribution curve and the magnitude of the absolute value thereof increases in proportion to the abruptness of the change in the spectral distribution curve. Therefore, the correction value Cx which has an appropriate value corresponding to the shape of the spectral distribution curve and the abruptness thereof is obtained by a simple method.
  • the second derivative Q 1 is used as the correction value as it is.
  • the correction coefficient k 1 is basically a positive real number excluding 0, k 1 may exceptionally be set to 0 (for example, when no correction is executed). According to this method, the correction value of which the magnitude is variably controlled can be generated quickly (for example, real-time) by a simple method (simple configuration).
  • the correction value superimposition section 529 the correction value Cx output from the multiplication section 527 is superimposed (added or subtracted) on the reception data (reception signal) read out by the readout circuit 523 (specifically, the correction value Cx is subtracted from the reception data (reception signal), for example).
  • the signal processing section 600 includes a calculation section 602 for calculating a spectral reflectance curve or a spectral absorptance curve.
  • the signal processing section 600 executes predetermined signal processing based on the corrected reception signal (corrected reception data) corrected by the correction operation section 500 to calculate a spectrophotometric distribution, for example.
  • the signal processing section 600 outputs a signal (that is, spectrophotometric distribution information) Sout representing the calculated spectral intensities for each wavelength.
  • the reception data are corrected by superimposing (adding or subtracting) the correction value on the reception data
  • the reception data may be corrected by multiplying the reception data by the correction value (correction coefficient).
  • a predetermined fixed value may be used as the correction value
  • a correction value (variable correction value) of which the value changes in accordance with the degree of the change in the spectral distribution curve may be used.
  • a variable correction value a method in which the value of the correction value is continuously changed in accordance with the degree of the change in the spectral distribution may be used.
  • a method in which the degree of the change in the spectral distribution may be divided into a plurality of steps using a threshold or the like, and the value of the correction value is changed (switched) gradually in accordance with the respective steps may be used.
  • FIGS. 9A to 9C are diagrams illustrating examples of a calculation method of the second derivative.
  • FIG. 9A shows an example where the second derivative is 0
  • FIG. 9B shows an example where the second derivative is positive (>0)
  • FIG. 9C shows an example where the second derivative is negative ( ⁇ 0).
  • the spectral distribution changes (increases) in a straight line.
  • the reception light intensity of the first spectral band is p 1
  • the reception light intensity of the second spectral band adjacent to the first spectral band is p 2
  • the reception light intensity of the third spectral band adjacent to the second spectral band is p 3
  • Q 1 0 (the second derivative is zero). In this case, since no integration error occurs, the integration error correction is not necessary.
  • the second derivative may be calculated by other methods.
  • the second derivative is calculated by a simple operation which uses the measurement data of three adjacent wavelength bands.
  • a method in which a plane curve (approximated curve) is estimated based on the actual measurement values (discrete values), and the second derivative of the plane curve is calculated may be used.
  • FIG. 10 is a diagram showing, for the purpose of comparison, a spectral distribution curve (in this example, a spectral reflectance distribution curve) generated based on 16-point data after integration error correction and an actual spectral distribution (in this example, a spectral reflectance distribution) of a sample.
  • the spectral reflectance distribution curve is generated, for example, by the following procedure.
  • the surface color of a sample being used is red.
  • the spectral measurement device shown in FIG. 1 is used as a colorimeter (color measurement device), and light reflected from a sample is received by the light receiving section 400 to obtain reception data of 16 points.
  • the above-described integration error correction is executed on the reception data, and a spectral reflectance distribution curve is generated based on the reception signal (reception data) after correction.
  • the spectral reflectance values based on the measurement data (16-point data) after correction are indicated by white circles.
  • the corrected spectral property based on the corrected measurement data is indicated by a dotted line.
  • the spectral reflectance value based on the actual measurement data in a wavelength band in the vicinity of the wavelengths 580 nm to 700 nm is substantially identical to the actual spectral reflectance value of the sample.
  • the spectral property after correction shown in FIG. 10 is compared with the spectral property before correction shown in FIG. 4 . From the comparison, it can be understood that in the spectral property after correction shown in FIG. 10 , the error (integration error) in the spectral reflectance changing region is sufficiently suppressed.
  • a base floating error remains in the wavelength band of 400 nm to 560 nm. If it is possible to reduce the base floating error, it is possible to further improve the measurement accuracy of the spectral measurement device. Therefore, in the present embodiment, base floating error correction is executed in addition to the integration error correction.
  • the base floating error occurs, for example, when the half bandwidth of the optical band-pass filter 300 is broad (the wavelength separation property is not high). That is, although an optical band-pass filter associated with a desired wavelength band ideally transmits only light of the wavelength band, light of wavelengths other than the desired wavelength band is also mixed into the transmission light. Therefore, a noise component (reception component corresponding to wavelengths other than the desired wavelength band) is superimposed on the reception signals of the respective wavelength bands, and the reception signal level increases by an amount corresponding to the noise component. Thus, a base floating error occurs.
  • a correction operation (base floating correction) is executed in which the sum of the noise component for each wavelength band included in all of the reception signals (that is, interest reception signals) obtained by receiving light from the m-th band-pass filter, and the calculated sum of noise components is subtracted from all of the reception signals to thereby suppress the effect of noise.
  • This base floating correction is preferably executed prior to the integration error correction. That is, noise is removed from the spectroscopic data of the respective spectral bands (spectral wavelength bands) through the base floating correction, and the integration error correction is executed based on the spectroscopic data in which the noise is removed.
  • correction accuracy can be further improved.
  • FIG. 11 is a diagram illustrating a configuration example of a correction operation section and an outline of a correction operation according to a second embodiment.
  • the readout circuit 523 in the configuration shown in FIG. 8 is removed, and a noise estimation section 508 and a noise removal and correction section 510 are provided.
  • the noise estimation section 508 and the noise removal and correction section 510 executes a correction operation (base floating error correction) for reducing the base floating error (noise that causes the base floating).
  • the noise estimation section 508 reads out the reception data S 1 to S 16 stored in the memory 506 and estimates a noise component (component having the wavelengths of a wavelength band w (#m)) included in an interest reception signal (interest reception data) Sm based on the reception data S 1 to S 16 .
  • the noise removal and correction section 510 subtracts the sum of the noise components for each wavelength band from the interest reception signal (interest reception data) Sm to calculate a corrected reception signal (corrected reception data or corrected reception light intensity data).
  • the signal processing section 600 executes predetermined signal processing based on the corrected reception signal (corrected reception data) corrected by the correction operation section 500 to calculate a spectrophotometric distribution, for example.
  • the signal processing section 600 outputs a signal (that is, spectrophotometric distribution information) Sout representing the calculated spectral intensities for each wavelength.
  • the m-th wavelength band (1 ⁇ m ⁇ n) will be referred to as an interest wavelength band.
  • the interest wavelength band is a wavelength band that is being focused on in the correction processing of the reception data.
  • the k-th wavelength band (k ⁇ m and 1 ⁇ k ⁇ n) other than the m-th wavelength band will be referred to as a non-interest wavelength band.
  • the light receiving section 400 shown in FIG. 11 receives the transmission light or the reflection light of the m-th band-pass filter PDm and outputs an interest reception signal Sm (any one of S 1 a to S 16 a ). Similarly, the light receiving section 400 receives the transmission light or reflection light of the k-th band-pass filter and outputs non-interest reception signals Sk (signals excluding the interest reception signal Sm from S 1 a to S 16 a ).
  • the transmittance or the reflectance in the k-th wavelength band of the m-th band-pass filter will be denoted as P(m,k)
  • the transmittance or the reflectance in the k-th wavelength band of the k-th band-pass filter will be denoted as P(k,k)
  • the noise component for each wavelength band of the k-th wavelength band included in the interest reception signal Sm will be denoted as N(m,k).
  • the noise estimation section 508 performs an operation based on Formula (1) below to estimate the amount of the noise components for each wavelength band of the k-th wavelength band included in the interest reception signal Sm.
  • N ( m,k ) Sk ⁇ P ( m,k )/ P ( k,k ) ⁇ (1)
  • the noise removal and correction section 510 calculates the sum ⁇ N(m,k) of the estimated amount of noise components N(m,k) for each wavelength band. Moreover, the noise removal and correction section 510 performs an operation based on Formula (2) below to obtain a corrected reception signal (corrected reception data) Smc.
  • Sk is the non-interest reception signals obtained by the light receiving section receiving the transmission light or the reflection light of the k-th band-pass filter.
  • the non-interest reception signals are all of the reception signals which are the entire output of the photodiodes and are known since they are actually measured.
  • it is ideal to use only the value of a reception signal corresponding to light of the k-th wavelength band among the non-interest reception signals since it is not possible to separate only the reception component corresponding to the light of the k-th wavelength band, all of the reception signals of the k-th band-pass filter are used as a substitute.
  • P(m,k) is the transmittance or the reflectance in the k-th wavelength band of the m-th band-pass filter.
  • the notation P(m,k) represents the transmittance (or the reflectance) P in the “k”-th wavelength band which is the non-interest wavelength band, of the “m”-th band-pass filter (an optical filter associated with the “m”-th wavelength band which is the interest wavelength).
  • the spectral properties (relative spectral intensities of the respective wavelengths) in the all of the wavelength bands of the m-th band-pass filter are known.
  • P(m,k) can be calculated by integrating the transmittance (reflectance) of the respective wavelengths included in the k-th wavelength band (that is, by calculating the entire area of the k-th wavelength band in a graph showing the relationship between wavelengths and transmittance (reflectance)). Therefore, P(m,k) is known.
  • P(k,k) is the transmittance or the reflectance in the k-th wavelength band of the k-th band-pass filter.
  • the notation P(k,k) represents the transmittance (or the reflectance) P in the “k”-th wavelength band which is the non-interest wavelength band, of the “k”-th band-pass filter (an optical filter associated with the “k”-th wavelength band which is the non-interest wavelength).
  • the k-th band-pass filter is a filter associated with the k-th wavelength band, the transmittance in the k-th wavelength band is known.
  • the interest reception signal Sm is calculated using these known values. That is, the noise components N(m,k) for each wavelength band of the k-th wavelength band included in all of the reception signals obtained by the light receiving section receiving light from the m-th band-pass filter which is a filter associated with the interest wavelength band are calculated.
  • the use of the expression “noise components N(m,k) for each wavelength band of the k-th wavelength band” is based on the following reason. As described above, the first to n-th wavelength bands are wavelength bands each having a predetermined wavelength width, and if n ⁇ 3, there will be two or more k-th wavelength bands which are the non-interest wavelength bands. Considering this, the expression expresses a case in which when there is a plurality of wavelength bands as the non-interest wavelength bands, the noise components for each wavelength band are calculated.
  • the reception signal Sk corresponding to the transmittance (reflectance) P(k,k) in the k-th wavelength band of the k-th band-pass filter it is possible to obtain the reception signal Sk corresponding to the transmittance (reflectance) P(k,k) in the k-th wavelength band of the k-th band-pass filter. That is, all of the reception signals can be taken to be a substitute by regarding them as the reception signal corresponding to the k-th wavelength band. If P(k,k) is changed to P(m,k), since the amount of reception signals changes in accordance with the ratio between P(k,k) and P(m,k), the amount of reception signals will be changed to Sk ⁇ P(m,k)/P(k,k) ⁇ . This amount of reception signal is regarded as the noise components N(m,k) for each wavelength band of the k-th wavelength band included in the interest reception signal Sm. Formula (1) above expresses this.
  • the noise removal and correction section 510 calculates the sum ⁇ N(m,k) of the estimated noise components N(m,k) for each wavelength band.
  • the notation ⁇ N(m,k) represents the entire signal components (that is, all of the noise components ⁇ N) of the “k”-th wavelength band which is the non-interest wavelength band, included in all of the reception signals obtained by the light receiving section receiving light from the “m”-th band-pass filter which is a filter associated with the interest wavelength band.
  • the corrected reception signal Smc is obtained by removing noise therefrom and can be regarded as substantially the reception signal (reception data) corresponding to light of the interest wavelength band.
  • the measurement accuracy of the optical spectrum data is improved.
  • the noise estimation section 508 performs an operation based on Formula (3) below to estimate the amount of the noise components for each wavelength bands of the k-th wavelength band included in the interest reception signal Sm.
  • N ( m,k ) Sk ⁇ P ( m,k )/ P ( k,k ) ⁇ R (3)
  • ⁇ Qm(1 ⁇ n) is the sum of the transmittance or the reflectance of the all of the wavelength bands of the m-th band-pass filter
  • ⁇ Qk(1 ⁇ n) is the sum of the transmittance or the reflectance of all of the wavelength bands of the k-th band-pass filter
  • noise components are calculated based on a way of thinking in which “if P(k,k) is changed to P(m,k), since the amount of reception signals changes in accordance with the ratio between P(k,k) and P(m,k), the amount of reception signals will be changed to Sk ⁇ P(m,k)/P(k,k) ⁇ ”.
  • an optical filter being used is switched from the k-th band-pass filter to the m-th band-pass filter, there is a difference in the total amount (total light intensity) of light entering the light receiving section after passing through the respective filters due to the different properties (for example, relative transmittance distribution or relative reflectance distribution) of the respective filters.
  • Sk used in Formula (1) above represents all of the reception signals of the light receiving section when the k-th band-pass filter is used.
  • the noise components that are to be calculated are noise components included in all of the reception signals of the light receiving section when the m-th band-pass filter is used. That is, the noise components included in all of the reception signals when the m-th band-pass filter is used are estimated using actual measurement values when the k-th band-pass filter (a filter different from the m-th band-pass filter associated with correction) is used.
  • the noise components included in all of the reception signals when the m-th band-pass filter is used are estimated using actual measurement values when the k-th band-pass filter (a filter different from the m-th band-pass filter associated with correction) is used.
  • there is a difference in the total amount (total light intensity) of light entering the light receiving section after passing through the respective filters due to the different properties (for example, relative transmittance distribution or relative reflectance distribution) of the respective filters. Therefore, by adding signal processing for compens
  • the operational formula of Formula (1) is multiplied by the correction coefficient R for correcting the difference in the transmittance property or the reflectance property between the filters.
  • the sum of the transmittance or the reflectance of all of the wavelength bands of the m-th band-pass filter is denoted as ⁇ Qm(1 ⁇ n)
  • the sum of the transmittance or the reflectance of all of the wavelength bands of the k-th band-pass filter is denoted as ⁇ Qk(1 ⁇ n).
  • the ratio ( ⁇ Qm(1 ⁇ n)/EQk (1 ⁇ n)) of the sum of transmittance properties and reflectance properties between the respective filters will be referred to as the correction coefficient R for correcting (compensating for) the difference in the transmittance properties or the reflectance properties between the respective filters.
  • the correction coefficient R By multiplying the operational formula of Formula (1) above by the correction coefficient R, the difference in the transmittance properties or the reflectance properties between the respective filters is compensated. Accordingly, the measurement accuracy of the optical spectrum data is improved further.
  • FIG. 11 A specific example of estimation of noise components is illustrated on the lower side of FIG. 11 .
  • a transmission-type optical band-pass filter is used as the optical band-pass filter section 300 .
  • reception data S 3 obtained by converting an analog reception signal S 3 a output from the third photodiode PD( 3 ) into a digital value is used as an interest reception signal (interest reception data).
  • interest reception data In the reception data S 3 , noise components are superimposed for each wavelength band of w( 1 ), w( 2 ), and w( 4 ) to w( 16 ) which are non-interest wavelength bands.
  • the amount of the noise components in the 13th wavelength band (w( 13 )) is first estimated in accordance with Formula (3) described above.
  • the noise components in the 13th wavelength band (w( 13 )) included in the interest reception signal (interest reception data) S 3 can be obtained by multiplying the non-interest reception signal (non-interest reception data) S 13 by the transmittance (total light intensity) correction coefficient R between the third band-pass filter BPF( 3 ) and the 13th band-pass filter BPF( 13 ) and multiplying the same by the ratio (P(3,13)/P(13,13)) of the transmittances of the 13th wavelength band (w( 13 )) in the respective filters.
  • reception light intensity data Since components (noise components) of unnecessary wavelength bands, which are superimposed on the reception data (reception light intensity data) are removed by such a correction operation, the accuracy of the reception data (reception light intensity data) is improved. Therefore, it is possible to improve the measurement accuracy of a spectral measurement device without using an optical band-pass filter which is expensive and large.
  • the corrected reception data in which the base floating error is reduced are stored in the memory 506 .
  • FIGS. 12A and 12B are diagrams illustrating the effect of base floating correction.
  • FIG. 12A shows spectral distribution properties when only the base floating error correction is executed
  • FIG. 12B shows spectral properties when both the base floating error correction and the integration error correction (correction of errors in the reflectance changing region) are used.
  • FIGS. 12A and 12B show the spectral distribution curve and the spectral distribution (in this example, a spectral reflectance distribution) of the sample which are generated based on the corrected 16-point data (the surface color of the sample being used is red).
  • the spectral reflectance obtained based on the corrected measurement data (16-point data) is indicated by white circles.
  • the actual spectral reflectance distribution of the sample (red) is indicated by a solid line.
  • the measurement data in the wavelength band of 400 nm to 560 nm are substantially identical to the actual spectral reflectance distribution of the sample (red).
  • an error occurs in a spectral reflectance changing region in the vicinity of the wavelengths 580 nm to 700 nm.
  • the integration error correction is also executed in addition to the base floating error correction, the measured spectral reflectance values in the vicinity of the wavelengths 580 nm to 700 nm are substantially identical to the actual spectral reflectance values of the sample (red). In this way, according to the present embodiment, since both the base floating error and the integration error are reduced, higher accuracy spectral measurement is possible.
  • FIGS. 13A and 13B are diagrams showing the distribution of reception signal intensities (relative reception signal intensities) of respective photodiodes of the light receiving section and showing the extracted optical spectra of a reception signal in a third wavelength band (a wavelength band having a central wavelength of 440 nm) in an enlarged scale, respectively.
  • the reception signals of each of the first to 16th photodiodes PD( 1 ) to PD( 16 ) are denoted as 1′, 2′, . . . , and 16′. Since the surface color of the sample is red, the reception signal intensities in the first to 10th wavelength bands are not higher than the reception signal intensities in the 11th to 16th wavelength bands. Therefore, large noise components are superimposed on the first to 10th wavelength bands to cause base floating. Thus, the S/N ratio of the reception signals in these respective wavelength bands decreases greatly.
  • FIG. 13B shows the extracted optical spectra of the reception signal 3 ′ in the third wavelength band in an enlarged scale. Since the half bandwidth of the third band-pass filter BPF( 3 ) is broad, the components of the respective first, second, and fourth to 16th wavelength bands in addition to the wavelength components of the third wavelength band which is the original wavelength band are superimposed on the reception signal 3 ′. Since the material color (surface color) of the sample 200 is red, large noise components (unnecessary components) appear in the vicinity of a wavelength band of 600 nm to 720 nm.
  • base floating error correction is executed. In this way, most of the noise components superimposed on the reception signal 3 ′ in the third wavelength band are removed, and the accuracy of the measurement signals in the third wavelength band is improved.
  • the same correction processing is executed on the other wavelength bands (particularly, a wavelength band of 600 nm or lower in which base floating is likely to occur).
  • FIGS. 14A and 14B are diagrams illustrating an outline of an estimation method of noise components in a 13-th wavelength band, which are included in the light of a third wavelength band passed through a third band-pass filter.
  • the third band-pass filter BPF( 3 ) is an optical filter associated with a wavelength band having a width of 20 nm and a central wavelength of 440 nm, as described above, since the actual reception signal of the third photodiode (third photoreceiver) PD( 3 ) includes the components (noise components) of the other wavelength bands (the first, second, and fourth to 16th wavelength bands). In order to correct the reception data, it is necessary to estimate the signal amount of the noise components in the respective wavelength bands.
  • a wavelength band having a central wavelength of 440 nm indicated by a reticular pattern is the original wavelength associated with the third band-pass filter BPF( 3 ).
  • BPF( 3 ) the third band-pass filter
  • some basic data are required.
  • the basic data the reception data obtained by the 13th photodiode PD( 13 ) receiving light having passed through the 13th band-pass filter BPF( 13 ) are used. It may be ideal to use only the reception data of the 13th wavelength band indicated by a dotted pattern in FIG. 14B as the basic data.
  • all of the reception signals obtained from the 13th photodiode PD( 3 ) are used (substituted) in place of the reception data of the 13th wavelength band.
  • the reception signal intensity of the 13th wavelength band corresponding to the third photodiode PD( 3 ) shown in FIG. 14A is lower than the reception signal intensity of the 13th wavelength band corresponding to the 13th photodiode PD( 13 ) shown in FIG. 14B .
  • this is because the transmittance of the third band-pass filter BPF( 3 ) in the 13th wavelength band is different from the transmittance of the 13th band-pass filter BPF( 13 ) in the 13th wavelength band.
  • the difference in the transmittance between the respective filters is known, by multiplying the reception signal intensity (substituted by entire reception data) of the 13th wavelength band corresponding to the 13th photodiode PD( 13 ) by the ratio of transmittance between the respective filters in the 13th wavelength band, it is possible to estimate the amount of the noise components (the reception signal intensity of the 13th wavelength band corresponding to the third photodiode PD( 3 )).
  • FIGS. 15A to 15D are diagrams showing a first specific example (correction using Operational Formula (1)) of a method of estimating the amount of the noise components.
  • signal components indicated by a dotted pattern are reception signal components (unclear) in the 640 nm band (the 13th wavelength band w( 13 )) of the 13th band-pass filter BPF( 13 ) (a band-pass filter associated with the 640 nm band).
  • BPF( 13 ) a band-pass filter associated with the 640 nm band.
  • signal components indicated by hatching are noise components which are to be estimated.
  • the noise components are reception signal components (unknown) in the 440 nm band (the 13th wavelength band w( 13 )) of the third band-pass filter BPF( 3 ) (a band-pass filter associated with the 440 nm band).
  • the noise components are denoted as c1x1(440,640). This notation represents the noise components c1x1 in the 640 nm band of a band-pass filter associated with the 440 nm band.
  • FIG. 15D shows the specific content of the correction operational formula (Formula (1)) described above. That is, specifically, Formula (1) can be expressed as follows.
  • FIGS. 16A to 16C are diagrams showing a second specific example (correction using Operational Formula (3)) of a method of estimating the amount of the noise components.
  • the difference in transmittance (difference in total light intensity) between the filters is not taken into consideration. Therefore, in the example shown in FIGS. 16A to 16C , the basic data serving as the basis of noise estimation are corrected using the correction coefficient (transmittance correction coefficient) R for correcting the difference in transmittance (difference in total light intensity) between the filters.
  • R transmittance correction coefficient
  • This is the content of Formula (3) shown in FIG. 16C .
  • Formula (3) since the basic data are corrected considering the difference in optical properties (transmittance or reflectance) between the filters, the measurement accuracy is further improved.
  • the amounts of the noise components in the respective first, second, fourth to 12th, and 14th to 16th wavelength bands included in the reception signal (third reception data) obtained from the third photodiode PD( 3 ) are estimated by the same method (correction operation based on Formula (1) or (3)).
  • the estimated noise data of the respective wavelength bands are temporarily stored in the memory 506 .
  • FIGS. 17A to 17C are diagrams illustrating the content of noise removal and correction by a noise removal and correction section 510 .
  • the noise removal and correction section 510 calculates the third reception data corresponding to the third band-pass filter BPF( 3 ). That is, the noise removal and correction section 510 calculates the sum (c1x1(440)) of noise components included in the reception data obtained from the third photodiode PD( 3 ).
  • the notation c1x1(440) represents all of the noise components c1x1 included in the reception data of the 440 nm band.
  • FIGS. 18A to 18C are diagrams showing an example of a method of calculating the sum of the noise components.
  • three methods shown in FIGS. 18A to 18C can be considered as a method of calculating the sum of the noise components included in the m-th reception data which are the interest reception data (here, the sum corresponds to the sum of the noise components in the k-th wavelength band (k ⁇ m and 1 ⁇ k ⁇ n) which is the non-interest wavelength).
  • the first wavelength band is the interest wavelength band
  • the 16th wavelength band is the interest wavelength band
  • FIGS. 19A and 19B are diagrams showing a difference in the band-pass filter properties depending on the presence of a correction process.
  • the actual spectral property Ftr of the optical band-pass filter section 300 has a property such that it has broad skirts.
  • the spectral property Ftc of the optical band-pass filter section 300 is changed to a steep band-pass property as shown in FIG. 19A . Therefore, it is possible to improve the measurement accuracy of the spectral measurement device while allowing the use of various optical filters. For example, high-accuracy spectral measurement can be performed using a simple and cheap wavelength band-pass filter such as a variable-gap etalon.
  • the invention can be broadly applied to spectral measurement devices such as a colorimeter, a spectroscopic analyzer, and an optical spectrum analyzer.

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CN117405622A (zh) * 2023-12-14 2024-01-16 广东伊茗药业有限公司 一种燕窝中亚硝酸盐含量智能检测方法

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