JP6579059B2 - Data processing method, data processing apparatus, and data processing program - Google Patents

Description

  The present invention relates to a data processing method, a data processing apparatus, and a data processing program for generating particle size distribution data by processing light intensity distribution data obtained by receiving diffracted and scattered light from a sample with a plurality of light receiving elements. Is.

  Conventionally, a particle size distribution measuring device has been used to measure the particle size distribution of a group of particles in a sample. In a general particle size distribution measuring apparatus, a sample to be measured is irradiated with a laser beam, and light diffracted or scattered by the sample is received by a plurality of light receiving elements, so that the light receiving intensity in each light receiving element is increased. Based on this, the particle size distribution of the particle group in the sample can be measured.

  In this type of particle size distribution measuring apparatus, light diffracted or scattered by a sample is received by a plurality of light receiving elements, whereby light intensity distribution data representing the received light intensity in each light receiving element is obtained. Then, calculation using the refractive index is performed on the obtained light intensity distribution data, whereby particle size distribution data representing the amount of particles at each particle size is calculated.

  The parameters representing the refractive index as described above are set, for example, when an operator inputs in advance (see, for example, Patent Document 1 below). That is, the particle contained in the sample is one kind of particle having a specific refractive index, and a parameter representing the refractive index of the particle is input, and calculation is performed using the parameter.

JP 2011-220918 A

  Thus, conventionally, only the particle size distribution of a sample containing one kind of particles having a specific refractive index could be measured. There are cases where plural types of particles having different refractive indexes are mixed in the sample, but even in such a case, only calculation using the refractive index corresponding to any one type of particles can be performed. There is a problem that the particle size distribution cannot be measured with high accuracy.

  The present invention has been made in view of the above circumstances, and is a data processing method, data processing apparatus, and data processing capable of accurately measuring the particle size distribution of a sample in which a plurality of types of particles having different refractive indexes are mixed. The purpose is to provide a program.

(1) The data processing method according to the present invention includes a data input reception step, a coefficient matrix generation step, and a particle size distribution data generation step. In the data input receiving step, input of light intensity distribution data obtained by receiving diffraction scattered light from a sample mixed with a plurality of types of particles having different refractive indexes by a plurality of light receiving elements is received. In the coefficient matrix generation step, a coefficient matrix is generated by combining optical models obtained for each refractive index. In the particle size distribution data generation step, calculation is performed based on the light intensity distribution data and the coefficient matrix, thereby generating particle size distribution data for a plurality of types of particles having different refractive indexes.

  According to such a configuration, particle size distribution data for a plurality of types of particles having different refractive indexes is generated at a time by performing an operation using a coefficient matrix in which optical models obtained for each refractive index are combined. be able to. Thereby, even for a sample in which a plurality of types of particles having different refractive indexes are mixed, the particle size distribution for each of the plurality of types of particles can be measured with high accuracy.

(2) In the coefficient matrix generation step, the coefficient matrix in which each column is linearly independent may be generated.

  According to such a configuration, since each column of the coefficient matrix is linearly independent, the particle size distribution data for a plurality of types of particles having different refractive indexes can be reliably distinguished. Therefore, the particle size distribution for each of a plurality of types of particles can be measured with higher accuracy.

(3) The data processing method further includes a data correction step for performing correction so that the particle size ranges of the particle size distribution data for the plurality of types of particles generated by the particle size distribution data generation step are the same. May be.

  According to such a configuration, it is possible to easily compare the particle size distribution data with each other by setting the particle size ranges of the particle size distribution data for a plurality of types of particles to be the same. Therefore, the particle size distribution for each of the plurality of types of particles can be easily analyzed for a sample in which a plurality of types of particles having different refractive indexes are mixed.

(4) The data processing method may further include a display processing step of displaying the particle size distribution data for each of a plurality of types of particles corrected in the data correction step in the same display area.

  According to such a configuration, the particle size distribution data for each of a plurality of types of particles are displayed in the same display area, so that it is easy to compare the particle size distribution data. In particular, since the particle size ranges of the particle size distribution data for a plurality of types of particles are corrected to be the same, the amount of particles in each particle size range can be easily compared.

  The data processing apparatus according to the present invention includes a data input receiving unit, a storage unit, and a particle size distribution data generating unit. The data input receiving unit receives input of light intensity distribution data obtained by receiving diffraction scattered light from a sample in which a plurality of types of particles having different refractive indexes are mixed with a plurality of light receiving elements. The storage unit stores a coefficient matrix in which optical models obtained for each refractive index are combined. The particle size distribution data generation unit generates particle size distribution data for each of a plurality of types of particles having different refractive indexes by performing calculations based on the light intensity distribution data and the coefficient matrix.

  The data processing program according to the present invention causes a computer to function as a data input receiving unit and a particle size distribution data generating unit. The data input receiving unit receives input of light intensity distribution data obtained by receiving diffraction scattered light from a sample in which a plurality of types of particles having different refractive indexes are mixed with a plurality of light receiving elements. The particle size distribution data generation unit performs an operation based on the light intensity distribution data and a coefficient matrix in which an optical model obtained for each refractive index is combined, thereby obtaining a plurality of types of particles having different refractive indexes. Generate particle size distribution data.

  According to the present invention, even for a sample in which a plurality of types of particles having different refractive indices are mixed, the particle size distribution for each of the plurality of types of particles is accurately measured including information on the relative magnitude of the amount of particles. be able to.

It is the schematic which showed the structural example of the particle diameter distribution measuring apparatus provided with the data processor which concerns on one Embodiment of this invention. It is a block diagram for demonstrating the specific structure of the data processor of FIG. It is the figure which showed an example of the display mode of the particle diameter distribution data with respect to a display part. It is the figure which showed the other example of the display mode of the particle diameter distribution data with respect to a display part. It is the flowchart which showed the flow at the time of measuring the particle diameter distribution of the sample with which multiple types of particle | grains from which refractive index differs were mixed.

  FIG. 1 is a schematic diagram illustrating a configuration example of a particle size distribution measuring apparatus including a data processing apparatus 5 according to an embodiment of the present invention. This particle size distribution measuring device is for generating particle size distribution data by measuring the relationship between the particle size and the amount of particles contained in a sample, and is used for measuring a sample. A mechanism 1 is provided.

  The measurement mechanism 1 includes a light source 11, a condensing lens 12, a spatial filter 13, a collimator lens 14, a flow cell 15, a condensing lens 16, a detector 17, and the like. A sample to be measured is supplied to the flow cell 15 from a supply source such as a circulation sampler 2 in which an ultrasonic transducer is incorporated.

  The light source 11 is composed of, for example, a laser light source, and light (measurement light) emitted from the light source 11 passes through the condenser lens 12, the spatial filter 13, and the collimator lens 14 to become parallel light. The measurement light thus converted into parallel light is irradiated onto the flow cell 15 to which the sample is supplied, and light diffracted or scattered by the particle group included in the sample in the flow cell 15 (diffraction scattered light) is collected. The light is received by the detector 17 through the optical lens 16. However, not only the flow cell 15 but also a configuration in which a measurement is performed by storing a sample in the batch cell for each measurement.

  The detector 17 is for detecting light from the sample, and is composed of, for example, a photodiode array. The detector 17 includes, for example, a plurality of (for example, 64) light receiving elements 171 formed with ring-shaped or semi-ring-shaped detection surfaces having different radii, concentrically around the optical axis of the condenser lens 16. The light from the sample diffracted or scattered in the direction of the angle corresponding to each position is incident on each light receiving element 171. Therefore, the detection signal of each light receiving element 171 of the detector 17 represents the intensity of light corresponding to the incident angle.

  In the example of FIG. 1, the detector 17 is shown only in front of the flow cell 15 (on the side opposite to the light source 11). However, a detector having a light receiving element for receiving light diffracted or scattered by the sample is also provided behind (on the light source 11 side) and on the side (in a plane perpendicular to the light incident direction) of the flow cell 15, respectively. It may be provided.

  The detection signal of each light receiving element 171 of the detector 17 is converted from an analog signal to a digital signal by the A / D converter 3 and then input to the data processing device 5 via the communication unit 4. . Thereby, light intensity distribution data in which the element number of each light receiving element 171 of the detector 17 is associated with the detected intensity in each light receiving element 171 is input to the data processing device 5.

  The data processing device 5 processes data when measuring the particle size distribution of the sample. The data processing device 5 is configured by a computer, for example, and includes a control unit 51, an operation unit 52, a display unit 53, a storage unit 54, and the like. The control unit 51 includes, for example, a CPU (Central Processing Unit), and each unit such as an operation unit 52, a display unit 53, and a storage unit 54 is electrically connected.

  The operation unit 52 includes, for example, a keyboard and a mouse, and the user can perform input work and the like by operating the operation unit 52. The display unit 53 is configured by a liquid crystal display, for example, and various types of information such as measurement results in the measurement mechanism 1 are displayed on the display unit 53. The storage unit 54 includes, for example, a RAM (Random Access Memory) and a hard disk.

  FIG. 2 is a block diagram for explaining a specific configuration of the data processing device 5 of FIG. The control unit 51 in the present embodiment functions as a data input receiving unit 511, a particle size distribution data generation unit 512, a data correction unit 513, a display processing unit 514, and the like when the CPU executes a program.

  A light intensity distribution data storage unit 541, a particle size distribution data storage unit 542, a coefficient matrix storage unit 543, and the like are allocated to the storage unit 54. The light intensity distribution data storage unit 541 stores light intensity distribution data based on input signals from the light receiving elements 171 of the detector 17. The control unit 51 generates particle size distribution data based on the light intensity distribution data stored in the light intensity distribution data storage unit 541 and stores the particle size distribution data in the particle size distribution data storage unit 542. When the control unit 51 generates the particle size distribution data, the coefficient matrix stored in the coefficient matrix storage unit 543 is used.

  In the particle size distribution measuring apparatus according to this embodiment, the particle size distribution of a sample in which a plurality of types of particles having different refractive indexes are mixed can be measured. Such a sample is measured by the measurement mechanism 1, and diffracted and scattered light from each particle (a plurality of types of particles having different refractive indexes) in the sample is received by a plurality of light receiving elements 171 to obtain light intensity distribution data. It is done. The obtained light intensity distribution data is stored in the light intensity distribution data storage unit 541.

  The data input receiving unit 511 receives input of light intensity distribution data stored in the light intensity distribution data storage unit 541 when generating particle size distribution data. The particle size distribution data generation unit 512 performs calculation using the refractive index on the light intensity distribution data input from the light intensity distribution data storage unit 541, thereby obtaining the particle size distribution data corresponding to the refractive index. Generate. In this embodiment, since the refractive index is different for each of a plurality of types of particles included in the sample, the particle size distribution data generation unit 512 performs matrix calculation using one coefficient matrix generated based on each refractive index. By doing so, particle size distribution data for each of a plurality of types of particles can be generated. Each generated particle size distribution data is stored in the particle size distribution data storage unit 542.

When calculating the particle size distribution data, the relationship of the following formula (1) can be used.

Here, s, q, and A are represented by the following formulas (2) to (4).

The vector s is light intensity distribution data. Each element s _u (u = 1, 2,..., K) in the vector s is a light receiving element 171 of the detector 17 and a light receiving element provided behind or on the side of the flow cell 15 (both shown in FIG. (Not shown).

The vector q is particle size distribution data expressed as a frequency distribution%. In this example, a vector q in the case where two types of particles (particle a and particle b) having different refractive indexes are included in the sample is shown, and each element q _ai (i = 1, 2,..., N) is shown. ) Represents the particle amount of the particle a, and each element q _bj (j = 1, 2,..., M) represents the particle amount of the particle b. That is, the entire particle including the particle a and the particle b is represented as a vector q having n + m elements.

More specifically, each element q _ai (i = 1, 2,..., N) divides the particle diameter measurement target range (maximum particle diameter is x ₁ , minimum particle diameter is x _{n + 1} ) into n parts. When the respective particle diameter ranges are [x _i , x _{i + 1} ], the amounts of particles a corresponding to the respective particle diameter ranges [x _i , x _{i + 1} ] are shown. On the other hand, each element q _bj (j = 1, 2,..., M) divides the particle diameter measurement target range (the maximum particle diameter is y ₁ and the minimum particle diameter is y _{m + 1} ) into m parts. When the diameter range is [y _j , y _{j + 1} ], the amount of particles b corresponding to each particle diameter range [y _j , y _{j + 1} ] is shown. Thus, the particle size range of the particle size distribution data differs for each of a plurality of types of particles (particle a and particle b). Of course, it is possible to set n and m to the same value with n = m.

The amount of particles is calculated on a volume basis and is normalized so that the total amount of all particles is 100% when displayed. That is, it is displayed so as to satisfy the following formula (5). As the display, display the sum of the elements _q a1 _{to q an,} for the particles a is 100%, i.e. the display and satisfying the equation (6), the sum of each element _q b1 _{to q bm} of the particle b A display that is 100%, that is, a display that satisfies Expression (7) may be adopted.

The matrix A is a coefficient matrix in which coefficients for converting the particle size distribution data q into the light intensity distribution data s are arranged in a matrix. The matrix A is generated by combining optical models (theoretical light intensity) obtained for each of the refractive indexes of a plurality of types of particles. In this example, optical models A1 and A2 for two types of particles (particle a and particle b) having different refractive indexes are combined. Each element a _{u, i} (u = 1, 2,..., K, i = 1, 2,..., N) in the optical model A1 belongs to each particle diameter range [x _i , x _{i + 1} ]. This is the received light intensity of diffracted and scattered light in the u-th light receiving element 171 when the unit volume of particles a is irradiated with unit intensity measurement light. Each element a _{u, j} (u = 1, 2,..., K, j = 1, 2,..., M) in the optical model A2 belongs to each particle diameter range [y _j , y _{j + 1} ]. This is the received light intensity of diffracted scattered light in the u-th light receiving element 171 when the unit b of particle b is irradiated with unit intensity measurement light.

The value of each element a _{u, i} , a _{u, j} in each optical model A1, A2 can be theoretically calculated in advance using the refractive index of the particles a, b as one of the parameters. For example, when the particle diameter is sufficiently larger than the wavelength of the measurement light from the light source 11 (for example, 10 times or more), it can be calculated using Fraunhofer diffraction theory. On the other hand, when the particle diameter is about the same as or smaller than the wavelength of the measurement light from the light source 11, it can be calculated using Mie scattering theory. The optical models A1 and A2 for the particles a and b thus obtained have the same number of rows k, and are arranged side by side so as to form different columns, thereby generating a matrix A. The As a result, the matrix A is a matrix having elements of k rows and (n + m) columns.

When generating the matrix A _, the values of the elements a _{u, i} , a _{u, j} are selected so that the columns of the matrix A are linearly independent. That is, the value obtained by multiplying each column vector of the matrix A by the coefficient and adding up is 0 only when the coefficients are all 0. Whether or not each column of the matrix A is linearly independent can be confirmed by calculating the rank (rank) of the matrix A. If the rank is smaller than the number of columns (n + m) of the matrix A, the matrix A Can be determined not to be primary independent. In this case, if the particle size range of the particle size distribution data is adjusted for each of a plurality of types of particles, a matrix A in which each column is linearly independent can be generated.

In the matrix calculation by the particle size distribution data generation unit 512, the vector q is obtained by the following equation (8) based on the above equation (1). Where ^AT is a transposed matrix of A. In this case, the obtained vector q becomes the particle size distribution data, each element q _ai (i = 1, 2,..., N) is the particle amount of the particle a, and each element q _bj (j = 1, 2, .., M) are calculated as the amount of particles b.

  As described above, in the present embodiment, the calculation is performed using the coefficient matrix (matrix A) in which the optical models A1 and A2 obtained for each refractive index are combined, whereby a plurality of types of particles a and b having different refractive indexes are obtained. Each particle size distribution data can be generated at once. As a result, even in a sample in which a plurality of types of particles a and b having different refractive indexes are mixed, the particle size distribution for each of the plurality of types of particles a and b is represented by the relative amount of particles a and b. It is possible to measure accurately including large and small information.

  In particular, in this embodiment, since each column of the coefficient matrix (matrix A) is linearly independent, the particle size distribution data for each of a plurality of types of particles a and b having different refractive indexes can be reliably distinguished. Therefore, the particle size distribution for each of the plurality of types of particles a and b can be measured with higher accuracy.

The data correction unit 513 corrects the particle size distribution data for each of the plurality of types of particles a and b generated as described above. Specifically, correction is performed so that the particle size ranges of the particle size distribution data for a plurality of types of particles are the same. That is, the particle diameter range [x _i , x _{i + 1} ] for the particle a and the particle diameter range [y _j , y _{j + 1} ] for the particle b are corrected to be the same. Such correction can be performed by using a known interpolation method.

  The display processing unit 514 performs processing for causing the display unit 53 to display the particle size distribution data. In the present embodiment, the particle size distribution data for each of a plurality of types of particles a and b corrected by the data correction unit 513 is displayed in the same display area in the display unit 53.

  FIG. 3A is a diagram showing an example of a display mode of particle size distribution data on the display unit 53. In this example, a line graph G11 representing the particle size distribution data of the particles a and a line graph G12 representing the particle size distribution data of the particles b are simultaneously displayed in the same display area D. Each line graph G11, G12 shows the amount of particles a and b in each particle size range in association with the same particle size range.

  FIG. 3B is a diagram showing another example of a display mode of particle size distribution data on the display unit 53. In this example, a bar graph G21 representing the particle size distribution data of the particles a and a bar graph G22 representing the particle size distribution data of the particles b are simultaneously displayed in the same display area D. Each bar graph G21, G22 indicates the amount of particles a and b in each particle size range in association with the same particle size range. In this example, the bar graphs G21 and G22 are stacked (accumulated) in each particle size range and displayed, thereby confirming the integrated value of the total amount of particles a and b in each particle size range. Can be done.

  As illustrated in FIGS. 3A and 3B, in this embodiment, the particle size distribution data for each of a plurality of types of particles a and b are made the same, and the particle size distribution data can be easily compared with each other. Can do. Therefore, the particle size distribution for each of the plurality of types of particles a and b can be easily analyzed for a sample in which a plurality of types of particles a and b having different refractive indexes are mixed.

  Moreover, since the particle size distribution data for each of the plurality of types of particles a and b are displayed in the same display area D, it is easy to compare the particle size distribution data. In particular, since the particle size ranges of the particle size distribution data for a plurality of types of particles a and b are corrected to be the same, the amount of particles in each particle size range can be easily compared.

  FIG. 4 is a flowchart showing a flow when measuring a particle size distribution of a sample in which a plurality of types of particles having different refractive indexes are mixed. When a plurality of types of particles having different refractive indexes are included in the sample, a coefficient matrix (matrix A) is generated in advance based on the refractive indexes and stored in the coefficient matrix storage unit 543 (step S101: coefficient). Matrix generation step). At this time, the coefficient matrix may be generated by the operator operating the operation unit 52, or a coefficient matrix generated in advance may be input to the data processing device 5 from the outside.

  Thereafter, when the sample is measured in the measurement mechanism 1, the light intensity distribution data is generated by receiving the diffraction scattered light from the sample by each light receiving element 171 of the detector 17, and the data input is accepted. The input of the light intensity distribution data is received by the unit 511 (step S102: data input receiving step). However, the light intensity distribution data is not limited to the configuration that is directly input from the measurement mechanism 1, and the light intensity distribution data obtained by measuring the sample in advance may be input to the data processing device 5 from the outside. .

  When the light intensity distribution data is input, the coefficient matrix (matrix A) is read from the coefficient matrix storage unit 543, and the particle diameter distribution data generation unit 512 uses the above equation (8) based on the light intensity distribution data and the coefficient matrix. ) Is performed. Thereby, particle size distribution data for each of a plurality of types of particles is generated (step S103: particle size distribution data generation step), and the generated particle size distribution data is stored in the particle size distribution data storage unit 542.

  If only the particle size distribution is measured, the processing up to step S103 is completed. However, when displaying the measured particle size distribution on the display unit 53, the processing of steps S104 and S105 is further performed. Specifically, first, the data correction unit 513 corrects each particle size distribution data so that the particle size ranges of the particle size distribution data for each of the plurality of types of particles generated in step S103 are the same ( Step S104: Data correction step).

  Thereafter, each corrected particle size distribution data is displayed on the same display area D of the display unit 53 by the display processing unit 514 (step S105: display processing step). Thereby, the measurement result of the particle size distribution for each of the plurality of types of particles is displayed on the display unit 53 in an easy-to-understand manner for a sample in which a plurality of types of particles having different refractive indexes are mixed.

  In the above embodiment, the case where two types of particles a and b having different refractive indexes are included in the sample has been described. However, three or more types of particles having different refractive indexes may be included in the sample. In this case, a coefficient matrix (matrix A) may be generated by combining three or more optical models for each particle side by side.

  The mode of displaying the particle size distribution data on the display unit 53 is not limited to the line graphs G11 and G12 and the bar graphs G21 and G22. That is, as long as the particle size distribution data for each of a plurality of types of particles can be displayed in the same display region D, the particle size distribution data is displayed in another graph or a display mode other than the graph. Also good.

  In the above embodiment, the configuration in which the data processing device 5 for calculating the particle size distribution data is provided in the particle size distribution measuring device has been described. However, the configuration is not limited to such a configuration, and a configuration in which the data processing device 5 is provided separately from the particle size distribution measuring device may be used. In this case, the light intensity distribution data output from the measurement mechanism 1 of the particle size distribution measuring device may be configured to be input to the data processing device 5 via wired communication or wireless communication. The configuration may be such that the data is once stored in (not shown) and then input to the data processing device 5 from the storage medium.

  The data processing device 5 is not limited to a configuration in which the light intensity distribution data input from the measurement mechanism 1 is temporarily stored in the light intensity distribution data storage unit 541 and then used for calculation, but the light intensity distribution input from the outside. The particle size distribution data may be calculated from the data as it is.

  Moreover, not only can the data processing device 5 for processing data based on the light intensity distribution data be provided as in the data processing device 5 according to the above-described embodiment, but also the computer functions as the data processing device 5. It is also possible to provide a program (data processing program) for this purpose. In this case, the program may be configured to be provided in a state stored in a storage medium, or may be configured to provide the program itself via wired communication or wireless communication. .

DESCRIPTION OF SYMBOLS 1 Measurement mechanism 2 Circulating sampler 3 A / D converter 4 Communication part 5 Data processing apparatus 11 Light source 12 Condensing lens 13 Spatial filter 14 Collimator lens 15 Flow cell 16 Condensing lens 17 Detector 51 Control part 52 Operation part 53 Display part 54 Storage Unit 171 Light Receiving Element 511 Data Input Accepting Unit 512 Particle Size Distribution Data Generation Unit 513 Data Correction Unit 514 Display Processing Unit 541 Light Intensity Distribution Data Storage Unit 542 Particle Diameter Distribution Data Storage Unit 543 Coefficient Matrix Storage Unit

Claims (6)

A data input receiving step for receiving input of light intensity distribution data obtained by receiving diffraction scattered light from a sample in which a plurality of types of particles having different refractive indexes are mixed with a plurality of light receiving elements;
A coefficient matrix generating step for generating a coefficient matrix in which optical models obtained for each refractive index are combined;
A particle size distribution data generating step for generating particle size distribution data for each of a plurality of types of particles having different refractive indexes by performing calculations based on the light intensity distribution data and the coefficient matrix. Processing method.   The data processing method according to claim 1, wherein in the coefficient matrix generation step, the coefficient matrix in which each column is linearly independent is generated.   3. A data correction step for correcting the particle size distribution data for each of a plurality of types of particles generated by the particle size distribution data generation step so that the particle size ranges are the same. The data processing method described in 1.   The data processing method according to claim 3, further comprising a display processing step of displaying the particle size distribution data for each of the plurality of types of particles corrected in the data correction step in the same display area. A data input receiving unit that receives input of light intensity distribution data obtained by receiving diffraction scattered light from a sample in which a plurality of types of particles having different refractive indexes are mixed with a plurality of light receiving elements;
A storage unit for storing a coefficient matrix combined with an optical model obtained for each refractive index;
Data comprising: a particle size distribution data generation unit that generates particle size distribution data for each of a plurality of types of particles having different refractive indexes by performing calculations based on the light intensity distribution data and the coefficient matrix. Processing equipment. A data input receiving unit that receives input of light intensity distribution data obtained by receiving diffraction scattered light from a sample in which a plurality of types of particles having different refractive indexes are mixed with a plurality of light receiving elements;
A particle size that generates particle size distribution data for a plurality of types of particles having different refractive indexes by performing calculations based on the light intensity distribution data and a coefficient matrix in which optical models obtained for each refractive index are combined. A data processing program for causing a computer to function as a distribution data generation unit.

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