JP6953142B2 - Measuring device, measuring method and control program of measuring device - Google Patents

Description

The present invention relates to a measuring device, a measuring method, and a control program of the measuring device for measuring the state of an object such as concrete.

Conventionally, an apparatus for measuring a deteriorated state of, for example, concrete, which is an object, has been proposed (for example, Patent Document 1).
Such a measuring device cuts out a test piece directly from an object, detects the salt concentration and the like, and diagnoses the deterioration state of concrete.

Japanese Unexamined Patent Publication No. 2008-14779

However, conventionally, since the test piece is cut out directly from the concrete or the like which is the object, there is a problem that the concrete is damaged and it is difficult to measure repeatedly.
On the other hand, it is also conceivable to irradiate the object with near infrared rays or the like without cutting out the test piece and receive the reflected light to perform the analysis.
However, when analyzing the received reflected light, there is a problem that an error or the like is generated due to the influence of noise or the like, and as a result, the accuracy of the measurement result is lowered.

Therefore, the present invention is a measuring device and a measuring method capable of obtaining highly accurate analysis results by irradiating an object with irradiation light and analyzing the reflected light without directly cutting out a test piece or the like from the object. And to provide a control program for the measuring device.

According to the present invention, the object is related to the spectral spectrum generated by the reflected light of the irradiation light applied to the test pieces without deforming a plurality of test pieces whose evaluation information of the substance to be measured is known. A spectral spectrum-related information storage unit that stores information and a PLS regression coefficient information storage unit that stores PLS regression coefficient information for calculating the spectral spectrum-related information by PLS (Partial Least Squares) regression analysis. Based on the spectral spectrum-related information, the PLS regression coefficient absolute value information storage unit for each wavelength, which stores the PLS regression coefficient absolute value information for each wavelength of the plurality of test pieces processed in the PLS regression analysis, and the wavelength. A candidate window function information storage unit that stores a plurality of candidate window function information generated based on another PLS regression coefficient absolute value information and candidate PLS regression coefficient threshold information, which is threshold information of a plurality of candidates, and the candidate window function information. Candidate PLS regression coefficient information storage that stores a plurality of candidate PLS regression coefficient information obtained by processing the window function spectral spectrum-related information generated based on the spectral spectrum-related information of the test piece by the PLS regression analysis. Execution PLS regression coefficient information which is the PLS regression coefficient information in which the PLS regression coefficient information having a relatively small error among the plurality of candidate PLS regression coefficient information is used for the measurement object. Regression that stores the spectral reflectance spectrum information after the regression coefficient multiplier obtained by processing in the PLS regression analysis using the executed PLS regression coefficient information based on the spectral spectrum-related information of the object. achieve a spectral reflectance spectrum information storage unit after the coefficient multiplier, and a display unit for displaying the evaluation information of the object on the basis of the regression coefficient multiplier after spectral reflectance spectrum information, the measuring device characterized that you have a To be done.

According to the above configuration, spectral spectrum-related information is generated by the reflected light of the irradiation light irradiating the object without deforming the object such as a concrete piece.
Then, based on the spectral spectrum-related information, the chemometric method calculation basic information (for example, the executed PLS regression coefficient) is used, and the chemometric method such as PLS (Partial Last Squares (partial least squares regression)) regression analysis is performed. Generates chemometric result information (eg, spectral reflectance spectrum after regression coefficient multiplication) obtained by processing.
Further, evaluation information such as deterioration index information of the object is displayed on a display unit such as a display based on the result information of the chemometric method.

Therefore, in the above configuration, the object can be evaluated by irradiating the test piece directly from the object such as concrete without cutting out the test piece and receiving the reflected light, so that the object is not damaged. , Can be repeatedly measured.
Further, since the chemometric method result information can be processed into information that is not easily affected by noise or the like, it is possible to improve the analysis accuracy of the salt concentration or the like that affects the evaluation information such as the deterioration index information.
It is also possible to obtain such a highly accurate analysis result and display it on the display unit.
Further, according to the above configuration, among the candidate chemometric method calculation basic information, the information having a relatively small error is used as the chemometric method calculation basic information.
Therefore, since it is possible to process information that is less susceptible to noise and the like, it is possible to further improve the analysis accuracy of degree information such as salinity that affects evaluation information such as deterioration information.

Preferably, the spectral spectrum information of the measuring device generates a wavelength-specific measurement spectral spectrum for each wavelength of the test piece from the light receiving intensity for each wavelength based on the spectral data, and corresponds to a specific measurement distance. Using the reference spectral spectrum information which is the change information of the reference spectral spectrum, the wavelength-specific measurement spectral spectrum of each test piece is corrected to generate a wavelength-specific spectral reflectance spectrum, and the wavelength-specific spectrum of each test piece is generated. It is characterized in that the spectral spectrum related information is generated based on the reflectance spectrum.

Preferably, the measuring device is characterized in that the PLS regression coefficient information having a relatively small error is obtained by an RMSP (Root Means Square Error Reader) method.

Preferably, the spectral spectrum-related information is high-pass filtered spectral spectrum information obtained by processing the spectral spectrum information generated by the reflected light of the irradiation light irradiating the object with the high-pass filter coefficient information. ..

According to the above configuration, the spectral spectrum-related information is the high-pass filter-processed spectroscopy obtained by processing the spectral spectrum information such as the spectral reflectance spectrum for each wavelength generated by the reflected light of the irradiation light irradiating the object with the high-pass filter coefficient information. Since it is spectral information, the influence of noise and the like can be further removed, and the analysis accuracy of the salt concentration and the like, which affects the evaluation information such as the deterioration index information, can be further improved.
The measuring device according to any one of claims 1 to 4, wherein the measurement object of the measuring device is concrete, and the evaluation information is deterioration index information.

According to the present invention, the object is related to a spectral spectrum generated by the reflected light of the irradiation light applied to the test piece without deforming a plurality of test pieces whose evaluation information of the substance of the measurement object is known. PLS regression coefficient information for generating information and calculating the spectral spectrum-related information by PLS (Partial Least Squares) regression analysis is generated, and the PLS regression analysis is performed based on the spectral spectrum-related information. The PLS regression coefficient absolute value information for each wavelength of the plurality of test pieces processed in is generated, and a plurality of PLS regression coefficient absolute value information for each wavelength and the candidate PLS regression coefficient threshold information which is the threshold information for the plurality of candidates are used. Candidate window function information is generated, and the window function spectral spectrum-related information generated based on the candidate window function information and the spectral spectrum-related information of the test piece is processed by the PLS regression analysis to perform a plurality of candidates. The PLS regression coefficient information is generated, and among the plurality of candidate PLS regression coefficient information, the PLS regression coefficient information having a relatively small error is used for the measurement object. The executed PLS regression coefficient is the PLS regression coefficient information. Stored as information, based on the spectral spectrum-related information of the object, the executed PLS regression coefficient information is used to process in the PLS regression analysis to generate spectral reflectance spectrum information after the regression coefficient multiplier, and the above-mentioned It is achieved by a measurement method characterized by displaying the evaluation information of an object generated based on the spectral reflectance spectrum information after the regression coefficient multiplier on the display unit.

According to the present invention, the object is generated by the reflected light of the irradiation light irradiating the test piece without deforming a plurality of test pieces whose evaluation information of the substance to be measured is known in the measuring device. A step of generating the spectral spectrum-related information, a step of generating PLS regression coefficient information for calculating the spectral spectrum-related information by PLS (Partial Least Squares) regression analysis , and the spectral spectrum-related information. Based on the information, the step of generating the PLS regression coefficient absolute value information for each wavelength of the plurality of test pieces processed by the PLS regression analysis, the PLS regression coefficient absolute value information for each wavelength, and the threshold information of a plurality of candidates. The step of generating a plurality of candidate window function information based on a certain candidate PLS regression coefficient threshold information, and the window function spectral spectrum-related information generated based on the candidate window function information and the spectral spectrum-related information of the test piece are described. A step of generating a plurality of candidate PLS regression coefficient information by processing by PLS regression analysis, and the PLS regression coefficient information having a relatively small error among the plurality of candidate PLS regression coefficient information is obtained with respect to the measurement target. Based on the step of storing as the executed PLS regression coefficient information which is the PLS regression coefficient information to be used and the spectral spectrum related information of the object, the executed PLS regression coefficient information is used and processed in the PLS regression analysis. And the process of generating spectral reflectance spectral information after the regression coefficient multiplier,
A control program of a measuring device for executing a step of displaying evaluation information of an object generated based on the spectral reflectance spectral information after the regression coefficient multiplier on a display unit.

The present invention is a measuring device capable of obtaining highly accurate analysis results by irradiating an object with irradiation light and analyzing the reflected light without directly cutting out a test piece or the like from the object. There is an advantage that a measuring method and a control program of a measuring device can be provided.

It is a schematic diagram which shows the state which the measuring apparatus which concerns on this invention is measuring the deterioration information, for example, which is the evaluation information of concrete such as Portland cement which is an object. It is a schematic explanatory drawing which shows the main structure of the spectroscope which the measuring apparatus of FIG. 1 has. It is a schematic block diagram which shows the main structure of the measuring apparatus of FIG. It is a schematic block diagram which shows the main structure of the 1st various information storage part. It is a schematic block diagram which shows the main structure of the 2nd various information storage part. It is a schematic block diagram which shows the main structure of the 3rd various information storage part. It is a schematic block diagram which shows the main structure of the 4th various information storage part. It is a schematic block diagram which shows the main structure of the 5th various information storage part. A chemometric method used to generate deterioration information from the reflected light of the concrete shown in FIG. 1, for example, the optimal chemometric method in the PLS regression analysis method. Basic information for calculation, for example, "execution PLS regression coefficient". It is a schematic flowchart which shows the process of selecting and storing. A chemometric method used to generate deterioration information from the reflected light of the concrete shown in FIG. 1, for example, the optimal chemometric method in the PLS regression analysis method. Basic information for calculation, for example, "execution PLS regression coefficient". It is another schematic flowchart which shows the process of selecting and memorizing. It is a schematic flowchart which shows the process of displaying the deterioration information of concrete on a display using "execution PLS regression coefficient information". It is another schematic flowchart which shows the process of displaying the deterioration information of concrete on a display using "execution PLS regression coefficient information". It is a schematic diagram which shows an example of "HPF processed spectral reflectance spectrum by wavelength". It is a schematic diagram which shows an example of "PLS regression coefficient absolute value information by wavelength". It is the schematic which shows the "threshold window function" of a specific threshold. It is a schematic diagram which shows an example of "window function multiplication spectroscopic reflectance spectrum". It is a schematic explanatory diagram which shows the relationship between the RMSEP value of each concrete piece and "PLS regression coefficient threshold value".

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings and the like.
Since the embodiments described below are suitable specific examples of the present invention, various technically preferable limitations are attached, but the scope of the present invention particularly limits the present invention in the following description. Unless otherwise stated, the present invention is not limited to these aspects.

FIG. 1 is a schematic view showing a state in which the measuring device 1 according to the present invention is measuring, for example, deterioration index information, which is evaluation information of concrete 100 such as Portland cement, which is an object.
Since the concrete 100 such as Portland cement used in buildings and the like deteriorates due to the salt content and the depth of neutralization, the measuring device 1 of FIG. 1 can accurately measure and display this deterioration index information. It is a device that can be used.
Further, as will be described later, the measuring device 1 has a configuration capable of measuring the deterioration index information of the concrete 100 of a building or the like without taking out a test piece from the building.

FIG. 2 is a schematic explanatory view showing a main configuration of the spectrometer 10 included in the measuring device 1 of FIG.
As shown in FIG. 2, the spectrometer 10 includes a halogen lamp 11 that irradiates irradiation light including near infrared rays, a relay lens 12, a mirror 13, and an objective lens 14.
Therefore, the irradiation light including the near infrared rays emitted from the halogen lamp 11 is applied to the concrete 100 via the relay lens 12, the mirror 13 and the objective lens 14 as shown in FIG.
Therefore, the halogen lamp 11, the relay lens 12, the mirror 13, and the objective lens 14 are arranged on the light projection axis 16.

Further, as shown in FIG. 2, the spectroscope 10 includes an imaging lens 17, a light receiving fiber 19, a condenser 18, a spectroscope 20, and a light receiving element 21.
Therefore, the reflected light reflected by the concrete 100 of FIG. 2 is guided to the objective lens 14, the mirror 13, the imaging lens 17, the light receiving fiber 19, and the condenser 18.
The reflected light is converted into a parallel light flux by the condenser 18, and is incident on the spectroscopic plate 20. The spectrum reflected by the spectroscopic plate 20 is received by the light receiving element 21.
Therefore, the imaging lens 17, the light receiving fiber 19, the condenser 18, and the like are arranged on the light receiving optical axis 22.

Based on the spectroscopy received by the light receiving element 21 in this way, the measuring device 1 of FIG. 1 is analyzed and the like as described later, and the deterioration index information of the concrete 100 of FIG. 2 is generated and displayed.

Further, the measuring device 1 of FIG. 1 has a computer, and the computer has a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and the like (not shown), and these are buses and the like. It is connected via.

FIG. 3 is a schematic block diagram showing a main configuration of the measuring device 1 of FIG.
As shown in FIG. 3, the measuring device 1 has a “measuring device control unit 31”, and the measuring device control unit 31 is a spectroscope 10 shown in FIG. 2, a display unit for displaying various information, for example, a display. It controls 32 and an input device 33 for inputting various information.

Further, the measuring device control unit 31 includes "first various information storage units 40", "second various information storage units 50", "third various information storage units 60", and "fourth various information storage units 60" shown in FIG. The "various information storage units 70" and the "fifth various information storage units 80" are also controlled.
4 to 8 show "first various information storage units 40", "second various information storage units 50", "third various information storage units 60", and "fourth various information storage units 70", respectively. It is a schematic block diagram which shows the main structure of "fifth various information storage part 80". The contents of each of these storage units 40 and the like will be described later.

9 and 10 are chemometric methods used to generate deterioration index information from the reflected light of the concrete 100 shown in FIG. 1, for example, PLS regression analysis method ((Partial Least Squares) (partial least squares method). )), It is a schematic flow chart showing a process of selecting and storing, for example, "execution PLS regression coefficient" which is the optimum basic information of cheometric method calculation.

11 and 12 are schematic flowcharts showing a process of displaying deterioration information of the concrete 100 on the display 32 by using the above-mentioned "execution PLS regression coefficient information".

First, a schematic flowchart showing a process of selecting and storing the optimum "execution PLS regression coefficient" used in the PLS regression analysis when generating deterioration index information from the reflected light of the concrete 100 of FIGS. 9 and 10 will be described. ..
In this step, as will be described later, "window function information" is used, and this "window function information" is a function that becomes "0" except for a certain finite interval, and is used for a certain function or signal (data). When the window function is multiplied, the outside of the interval becomes "0", and only the inside of the finite interval remains, so that the numerical analysis becomes easy.
Therefore, in the present embodiment, this window function is used to accurately analyze the reflected light from the concrete 100.

Hereinafter, a detailed description will be given according to the flowcharts of FIGS. 9 and 10.
First, in this step, for example, a plurality of concrete test pieces, which are objects for testing whose concentration (additional salt content) of a target substance, for example, salt or the like is known, are prepared.
For example, six concrete test pieces having a salt input amount of 0 kg, 4 kg, 8 kg, 12 kg, 16 kg, and 20 kg are prepared.

Then, the process proceeds to step 1 of FIG. 9 (hereinafter referred to as “ST”) 1. In ST1, the spectroscope 10 of FIG. 2 irradiates the six concrete pieces that are the objects with the irradiation light, disperses the reflected light with the spectroscope 20, and generates a data set of “spectroscopic data”. It is stored in the "spectral data storage unit 41" of the above.

Then, the process proceeds to ST2. In ST2, the "first measurement spectral spectrum information generation processing unit (program) 42" of FIG. 4 operates, and based on the "spectral data" of each concrete piece, the light receiving intensity for each wavelength is determined for each wavelength of each concrete piece. A "wavelength-specific measurement spectrum" is generated and stored in the "wavelength-specific measurement spectrum storage unit 43".

Then, the process proceeds to ST3. In ST3, the “wavelength-specific spectral reflectance spectrum generation processing unit (program) 44” of FIG. 4 operates, and the “reference spectral spectrum information storage unit 45” of FIG. 4 is referred to.
The "reference spectroscopic spectrum storage unit 45" stores "reference spectroscopic spectrum information", that is, information on changes in the reference spectroscopic spectrum corresponding to a specific measurement distance.
In the measuring device 1 of the present embodiment, since the measurement is performed at a distance close to each object such as a concrete piece, the measuring distance is set to be extremely short.

Then, the “wavelength-specific spectral reflectance spectrum generation processing unit (program) 44” converts the “wavelength-specific measurement spectral spectrum” of each concrete piece of the “wavelength-specific measurement spectral spectrum storage unit 43” of FIG. 4 into the above-mentioned “reference spectrum”. Correction or the like is performed based on "spectral information".
Then, a "spectral reflectance spectrum by wavelength" of each concrete piece is generated and stored in the "spectral reflectance spectrum storage unit 46 by wavelength" in FIG.

That is, in this step, the reflected light from the concrete piece is stored as spectral data of its reflectance.
This "spectral reflectance spectrum by wavelength" information is an example of spectral spectral information.

Then, the process proceeds to ST4. In ST4, the “HPF (high-pass filter) processing unit (program) 47” operates, and the “HPF (high-pass filter) coefficient storage unit 48” in FIG. 4 is referred to.
The "HPF coefficient storage unit 48" stores, for example, a specific "HPF (high-pass filter) coefficient" which is "high-pass filter coefficient information".
In this step, using this specific "HPF (high pass filter) coefficient", the "spectral reflectance spectrum information by wavelength" of each concrete piece is processed by "HPF (high pass filter)", and the "HPF treatment" of each concrete piece is performed. The “spectral reflectance spectrum for each wavelength completed” is generated and stored in the “HPF-processed spectral reflectance spectrum storage unit 49 for each wavelength” in FIG.

FIG. 13 is a schematic view showing an example of “HPF-processed spectral reflectance spectrum by wavelength”. As shown in FIG. 13, the “reflection spectrum after HPF” is shown for each “wavelength”, and at that time, the data is easy to analyze by removing noise and the like.

As described above, in the present embodiment, the "spectral reflectance spectrum information by wavelength" is processed by the "HPF (high-pass filter)" to make the data easy to analyze.
The "reflection spectrum after HPF" is an example of "spectral spectrum-related information" and "high-pass filtered spectral spectrum information".

Then, the process proceeds to ST5. In ST5, the “PLS regression coefficient absolute value generation processing unit (program) 51 for each wavelength” in FIG. 5 operates, and the “PLS regression equation storage unit 52” in FIG. 5 is referred to.
The "PLS regression equation storage unit 52" stores a "PLS regression equation" used in, for example, a PLS regression analysis method, which is a chemometric method.

PLS regression analysis is an example of chemometric regression analysis, and PLS regression of PLS regression analysis (Partial Least Squares) does not use the data as it is, and scores (also called latent variables and components). Is calculated and regression to its score (fitting the model between the dependent variable (objective variable) and the independent variable (explanatory variable) of the continuous scale).
The weights when calculating the score are sequentially calculated so that the covariance between the score and the dependent variable is the highest and the scores are uncorrelated with each other, and for a part of the obtained scores. It is a method of estimating the coefficient by the least squares method.

Then, the “PLS regression coefficient absolute value generation processing unit (program) 51 by wavelength” uses the PLS regression equation of the “PLS regression equation storage unit 52” of FIG. 5, and “HFP-processed spectral reflectance by wavelength” of FIG. 4 is used. The "HPF-processed wavelength-specific spectral reflectance spectrum data" of each concrete piece of the rate spectrum storage unit 49 "is processed.
Then, the "PLS regression coefficient absolute value information for each wavelength" of each concrete piece is obtained and stored in the "PLS regression coefficient absolute value storage unit 53 for each wavelength" in FIG.

FIG. 14 is a schematic view showing an example of “PLS regression coefficient absolute value information for each wavelength”.
As shown in FIG. 14, the “PLS regression coefficient absolute value” is shown for each “wavelength”, and at that time, weighting processing is performed to provide data that facilitates analysis of the salinity of the concrete piece.

The "PLS regression coefficient absolute value information by wavelength" is an example of "chemometric method absolute value information", and the "PLS regression coefficient absolute value storage unit 53 by wavelength" is "chemometric method absolute value information". It is an example of "memory unit".

Then, the process proceeds to ST6. In ST6, the “first window function generation processing unit (program) 54” of FIG. 5 operates, and the “PLS regression coefficient threshold storage unit 55” of FIG. 5 is referred to.
In this "PLS regression coefficient threshold storage unit 55", a plurality of threshold information (candidate threshold information), for example, PLS regression coefficient threshold information, for example, 0, 32, 34, 36, 37, 38, 39, 40, A value of 42 is stored.

Therefore, the "first window function generation processing unit (program) 54" selects the "PLS regression coefficient threshold" of any one of the "PLS regression coefficient threshold storage units 55", for example, "0", and uses the threshold value. The threshold information that sets the weight of the wavelength with low correlation to "0" and the weight of the wavelength with high correlation to "1" is the "PLS regression by wavelength" of the "PLS regression coefficient absolute value storage unit 53 by wavelength" of each concrete piece. Applies to "coefficient absolute value information".

Then, a "window function having a threshold value of" 0 "" (an example of candidate window function information) is created and stored in the "first window function information storage unit 56" of FIG.
That is, the "window function of the threshold value" 0 "for each of the" absolute value information of the PLS regression coefficient by wavelength "of the six concrete test pieces having the above-mentioned input salt content of 0 kg, 4 kg, 8 kg, 12 kg, 16 kg, and 20 kg". Is created and stored in the "first window function information storage unit 56" of FIG.

FIG. 15 is a schematic diagram showing a particular threshold, eg, 40 “threshold window functions”.
As shown in FIG. 15, a “threshold value, eg, a weighting function of 40” is applied to the “PLS regression coefficient absolute value” of FIG. 14, and the function is shown for each “wavelength”.
Therefore, the window function information is a function that becomes "0" except for a certain finite interval, and when a certain function or signal (data) is multiplied by a window function, the outside of the interval becomes "0". , Since it remains only within a finite interval, numerical analysis becomes easy.

Further, the "window function having a threshold value of" 0 "" is an example of "candidate window function information", and the "first window function information storage unit 56" is an example of "candidate window function information storage unit".

Then, the process proceeds to ST7. In ST7, the “first window function multiplication processing unit (program) 61” of FIG. 6 operates, and each concrete piece (additional salt content) of the “HPF-processed wavelength-specific spectral reflectance spectrum storage unit 49” of FIG. 4 is determined. Multiply the "window function of threshold" 0 "of the" first window function information storage unit 56 "of FIG. 5 corresponding to 6 concrete test pieces of 0 kg, 4 kg, 8 kg, 12 kg, 16 kg, and 20 kg).
Then, the "threshold" 0 "window function multiplying spectral reflectance spectrum" information of each concrete piece is generated and stored in the "window function multiplying spectral reflectance spectrum storage unit 62" of FIG.

This "threshold" 0 "window function multiplication spectroscopic reflectance spectrum" information is an example of "window function spectroscopic spectrum related information".

FIG. 16 is a schematic view showing an example of “window function multiplication spectroscopic reflectance spectrum”.
In FIG. 16, for example, the “HPF-processed wavelength-specific spectral reflectance spectrum” as shown in FIG. 13 is multiplied by, for example, the window function of the threshold 40 to obtain the “threshold 40 window function multiplied spectral reflectance” of the concrete piece. The rate spectrum ”is shown.
In FIG. 16, the “spectrum after multiplication by the weight function (window function)” is shown for each “wavelength”, and the influence of noise and the like is removed, so that the accuracy of numerical analysis such as salinity is remarkably improved.

Then, the process proceeds to ST8. In ST8, the used “PLS regression coefficient threshold value”, for example, “0” is stored in the “used threshold value storage unit 63” of FIG.
By storing in this way, it is possible to grasp the already processed "PLS regression coefficient threshold value", for example, "0".

Then, the process proceeds to ST9. In ST9, the “RMSEP and PLS regression coefficient calculation unit (program) 65” of FIG. 6 operates, and the “PLS regression equation” of the “PLS regression equation storage unit 52” of FIG. Perform "PLS regression analysis" on the "window function multiplication spectral reflectance spectrum" of the spectrum storage unit 62, and obtain "RMSEP (Root Means Square Error) value" and "PLS regression coefficient". Ask.
Then, the obtained "RMSEP value" and "PLS regression coefficient" are stored in the "RMSEP value storage unit 67" and the "PLS regression coefficient storage unit 68" of FIG. 6, respectively.

Here, "RMSEP" is an analysis method indicating the degree of error, and the smaller the value, the smaller the error. The "PLS regression coefficient" is a coefficient used for PLS regression analysis.

The "PLS regression coefficient" obtained in ST9 is an example of "candidate chemometric method calculation basic information", and the "RMSEP value storage unit 67" is an example of "candidate lightweight chemical method calculation basic information storage unit". be.

Then, the process proceeds to ST10. In ST10, the “unprocessed information determination processing unit (program) 64” of FIG. 6 operates, and the “PLS regression coefficient threshold storage unit 55” and the “used threshold storage unit 63” of FIG. 5 are referred to and unprocessed. Determine if the "PLS regression coefficient threshold" exists.

Next, in ST11, the unprocessed "PLS regression coefficient threshold", for example, in the above example, "0" has already been processed, so "32", "34", "36", "37", "38", and "39". "40" and "42" are unprocessed.
In ST10, when there is an unprocessed “PLS regression coefficient threshold”, the steps of ST7 to ST10 are repeatedly executed.

On the other hand, in ST11, there is no unprocessed "PLS regression coefficient threshold", that is, all of "0", "32", "34", "36", "37", "38", "39", "40" and "42". The "window function multiplication spectral reflectance spectrum" information is generated, the "PLS regression analysis" of ST9 is performed, and the obtained "RMSEP value" and "PLS regression coefficient" are each of those in FIG. When it is stored in the "RMSEP value storage unit 67" and the "PLS regression coefficient storage unit 68", the process proceeds to ST12.

FIG. 17 is a schematic explanatory view showing the relationship between the RMSPI value of each concrete piece and the “PLS regression coefficient threshold value (0.32, 34, 36, 37, 38, 39, 40, 42)”.
FIG. 17 shows which “PLS regression coefficient threshold” has the smallest RMSEP value, that is, which has the smallest error and is close to the true value (0 kg, 4 kg, 8 kg, 12 kg, 16 kg, 20 kg).

Then, the process proceeds to ST12. In ST12, the “PLS reflectance coefficient threshold value specifying processing unit (program) 71” of FIG. 7 operates, and with reference to the “RMSEP value storage unit 67” of FIG. 6, the “RMSEP value” is the lowest or the lowest for each concrete piece. Select the "PLS regression coefficient threshold (0.32, 34, 36, 37, 38, 39, 40, 42)" of the "window function multiplication spectral reflectance spectrum" judged to be low.
Then, referring to the “PLS regression coefficient storage unit 68”, the “PLS regression coefficient” corresponding to the lowest value “RMSEP value” is set as the “execution PLS regression coefficient”, and the “execution PLS regression coefficient storage unit 72” in FIG. Remember.
This "execution PLS regression coefficient storage unit 72" is an example of the "chemometric method calculation basic information storage unit".

In the present embodiment, as shown in FIG. 17, for example, the threshold (PLS regression coefficient threshold) “38” has the smallest RMSEP value, so the “PLS regression coefficient” corresponding to the threshold “38” is shown in FIG. It is stored in the "execution PLS regression coefficient storage unit 72" of.

As described above, in the present embodiment, among the plurality of PLS regression coefficients of the “PLS regression coefficient storage unit 68” of FIG. 6, the “PLS regression coefficient” having a relatively small error in the RMSPI value should be used for “execution”. PLS regression coefficient ”.
Therefore, since it is possible to process information that is less susceptible to noise and the like, it is possible to further improve the analysis accuracy of the salt concentration and the like that affect the evaluation information such as the deterioration index information.

In this way, the optimum "PLS regression coefficient" used in the inspection of the salt concentration of the concrete piece and the like is stored in the "execution PLS regression coefficient storage unit 72".
Therefore, in the following, the process of generating deterioration index information from the salt concentration and the like of concrete 100 such as Portland cement to be actually measured and displaying it on the display 32 will be described in detail according to the flowcharts of FIGS. 11 and 12. Explain to.

First, in ST21 of FIG. 11, similarly to ST1 of FIG. 9 described above, the spectrometer 10 of FIG. 2 irradiates the target object, for example, the concrete 100 to be measured, and the reflected light is emitted by the spectroscope 20. The spectroscopic light is generated, and the data of "spectroscopic data" is generated and stored in the "spectroscopic data storage unit 41" of FIG.

Then, the process proceeds to ST22. In ST22, the “second measurement spectral spectrum information generation processing unit (program) 73” of FIG. 7 operates, and based on the “spectral data” of the measurement target concrete 100, the measurement target concrete 100 is based on the light receiving intensity for each wavelength. A "measurement spectroscopic spectrum by wavelength" for each wavelength is generated and stored in the "measurement spectroscopic spectrum storage unit 43 by wavelength" in FIG.

Then, the process proceeds to ST23. In ST23, the “second wavelength-specific spectral reflectance spectrum generation processing unit (program) 74” of FIG. 7 operates, and the “wavelength-specific measurement spectral storage unit 43” of FIG. The “measured spectral spectrum” is corrected based on the “reference spectral spectrum information” of the “reference spectral spectrum storage unit 45” of FIG.
Then, a "spectral reflectance spectrum by wavelength" of the concrete 100 to be measured is generated and stored in the "spectral reflectance spectrum storage unit 46 by wavelength" in FIG.

Then, the process proceeds to ST24. In ST24, the “second HPF processing unit (program) 75” of FIG. 7 operates, the “HPF coefficient” of the “HPF coefficient storage unit 48” of FIG. 4 is acquired, and the “spectral reflection by wavelength” of the concrete 100 to be measured is obtained. "Rate spectrum information" is processed by "HPF".
Then, for example, "HPF-processed wavelength-specific spectral reflectance spectrum" which is "spectral spectrum-related information" of the concrete 100 to be measured is generated, and for example, "HPF" which is the "spectral spectrum-related information storage unit" of FIG. It is stored in the processed wavelength-specific spectral reflectance spectrum storage unit 49 ”.

An example of the information of the “HPF-processed spectral reflectance spectrum for each wavelength” at this time is the data example shown in FIG. 13 described above. By performing the high-pass filter processing in this way, noise and the like can be effectively removed.

Then, the process proceeds to ST25. In ST25, the “regression coefficient multiplication processing unit (program) 83” of FIG. 8 operates, and the “HPF-processed wavelength” of the concrete 100 to be measured by the “HPF-processed wavelength-specific spectral reflectance spectrum storage unit 49” of FIG. 4 operates. The "different spectral reflectance spectrum" information (for example, data as shown in FIG. 13) is multiplied by the "execution PLS regression coefficient" of the "execution PLS regression coefficient storage unit 72" of FIG.

Then, for the concrete 100 to be measured, the "spectral reflectance spectrum after multiplication of the regression coefficient" for each weighted wavelength is obtained and stored in the "spectral reflectance spectrum storage unit 84 after multiplication of the regression coefficient" in FIG.
That is, the "spectral reflectance spectrum after multiplication by the regression coefficient" information for each weighted wavelength is stored.

This "spectral reflectance spectrum after multiplication of the regression coefficient" is an example of "chemometric method result information", and the "spectral reflectance spectrum storage unit 84 after multiplication of the regression coefficient" is the "chemometric method result information storage unit". Is an example.

Then, the process proceeds to ST26. In ST26, the “deterioration index determination processing unit (program) 85” of FIG. 8 operates, and the “spectral reflectance spectrum after multiplication of the regression coefficient” information of the “spectral reflectance spectrum storage unit 84 after multiplication of the regression coefficient” of FIG. 8 operates. To get.

Then, all the "spectral reflectance spectrum after multiplication of the regression coefficient" information is added up to obtain "deterioration index information". The larger the value of this "deterioration index information", the more the deterioration is progressing.
This "deterioration index information" is stored in the "deterioration degree information storage unit 87" of FIG.

Then, the process proceeds to ST27. In ST27, the deterioration index information of the “deterioration degree information storage unit 87” of FIG. 8 is displayed on the display 32.
As a result, information on salt damage and neutralization of the concrete 100 to be measured, for example, information such as salt concentration and pH can be displayed with high accuracy.

Further, in the present embodiment, the object can be evaluated by irradiating light and receiving the reflected light without cutting out the test piece directly from the object such as concrete 100, so that the object is damaged or the like. It is possible to carry out repeated measurements without doing so.

The present invention is not limited to the above-described embodiment.

1 ... Measuring device, 10 ... Spectrometer, 11 ... Halogen lamp, 12 ... Relay lens, 13 ... Mirror, 14 ... Objective lens, 16 ... Floodlight axis, 17 ... imaging lens, 18 ... condenser, 19 ... light receiving fiber, 20 ... spectroscopic plate, 21 ... light receiving element, 22 ... light receiving optical axis, 31 ... measurement Device control unit, 32 ... display, 33 ... input device, 40 ... first various information storage units, 41 ... spectral data storage unit, 42 ... first measurement spectral spectrum information generation processing Unit (program), 43 ... measurement spectroscopic spectrum storage unit by wavelength, 44 ... spectral reflectance spectrum generation processing unit (program) by wavelength, 45 ... reference spectroscopic spectrum information storage unit, 46 ... wavelength Separate spectral reflectance spectrum storage unit, 47 ... HPF (high pass filter) processing unit (program), 48 ... HPF (high pass filter) coefficient storage unit, 49 ... HPF processed spectral reflectance spectrum storage by wavelength Units, 50 ... 2nd various information storage units, 51 ... frequency-specific PLS regression coefficient absolute value generation processing unit (program), 52 ... PLS regression type storage unit, 53 ... wavelength-specific PLS regression Absolute coefficient value storage unit, 54 ... 1st window function generation processing unit (program), 55 ... PLS regression coefficient threshold storage unit, 56 ... 1st window function information storage unit, 60 ... 3rd Various information storage units, 61 ... 1st window function multiplication processing unit (program), 62 ... window function multiplication spectral reflectance spectrum storage unit, 63 ... used threshold storage unit, 64 ... not yet Processing information judgment processing unit (program), 65 ... RMSEP and PLS regression coefficient calculation unit (program), 67 ... RMSEP value storage unit, 68 ... PLS regression coefficient storage unit, 70 ... 4th Various information storage units, 71 ... PLS regression coefficient threshold specification processing unit (program), 72 ... execution PLS regression coefficient threshold value storage unit, 73 ... second measurement spectroscopic spectrum information generation processing unit (program), 74 ... Second wavelength-specific spectral reflectance spectrum generation processing unit (program), 75 ... Second HPF processing unit (program), 80 ... Fifth various information storage units, 83 ... Regression coefficient multiplication processing Part (program), 84 ... Spectral reflectance after multiplication by regression coefficient Spectral storage unit, 85 ... Deterioration index judgment processing unit (program), 87 ... Deterioration degree information storage unit, 100 ... Concrete

Claims (7)

A spectroscopic spectrum-related information storage unit that stores spectroscopic spectrum-related information generated by the reflected light of the irradiation light applied to the test pieces without deforming a plurality of test pieces whose evaluation information of the substance to be measured is known. When,
A PLS regression coefficient information storage unit that stores PLS regression coefficient information for calculating the spectral spectrum-related information by PLS (Partial Least Squares) regression analysis.
Based on the spectroscopic spectrum-related information, a wavelength-specific PLS regression coefficient absolute value information storage unit that stores wavelength-specific PLS regression coefficient absolute value information of each of the plurality of test pieces processed in the PLS regression analysis, and a wavelength-specific PLS regression coefficient absolute value information storage unit.
A candidate window function information storage unit that stores a plurality of candidate window function information generated based on the candidate PLS regression coefficient threshold information, which is the wavelength-specific PLS regression coefficient absolute value information and the threshold information of a plurality of candidates.
By processing the window function spectral spectrum-related information generated based on the candidate window function information and the spectral spectrum-related information of the test piece in the PLS regression analysis, a plurality of candidate PLS regression coefficient information obtained can be stored. It has a candidate PLS regression coefficient information storage unit and
Of the plurality of candidate PLS regression coefficient information, the PLS regression coefficient information having a relatively small error is stored as the executed PLS regression coefficient information which is the PLS regression coefficient information used for the measurement object.
Wherein based on said spectrum-related information of the object, using said execution PLS regression coefficient information, the PLS regression analysis by the process stores the spectral reflectance spectrum information after the regression coefficient multiplier obtained regression coefficient multiplier after spectral Reflectivity spectrum information storage unit and
Measuring device characterized that you have a, a display unit for displaying the evaluation information of the object on the basis of the regression coefficient multiplier after spectral reflectance spectrum information. Based on the spectroscopic data, the spectroscopic spectrum information generates a wavelength-specific measurement spectroscopic spectrum for each wavelength of each of the test pieces from the light receiving intensity for each wavelength.
Using the reference spectroscopic spectrum information which is the change information of the reference spectral spectrum corresponding to a specific measurement distance, the wavelength-specific measurement spectral spectrum of each test piece is corrected to generate a wavelength-specific spectral reflectance spectrum.
The measuring apparatus according to claim 1 , wherein the spectral spectrum-related information is generated based on the spectral reflectance spectrum for each wavelength of each test piece. Measuring device according to claim 1 or claim 2, characterized in Rukoto determined by mean square error) method of a relatively small error of the candidate PLS regression coefficient information RMSEP (Root Means Square Error Prediction (prediction. Claim wherein the spectrum-related information, characterized a high-pass filtered spectral information der Rukoto treated the spectrum information generated by the reflected light of irradiation light irradiated on the object with high-pass filter coefficient information 1 to the measurement apparatus according to any one of claims 3. The measuring device according to any one of claims 1 to 4, wherein the measurement object is concrete and the evaluation information is deterioration index information. Without deforming a plurality of test pieces whose evaluation information of the substance to be measured is known, the spectroscopic spectrum-related information generated by the reflected light of the irradiation light applied to the test pieces is generated.
PLS regression coefficient information for calculating the spectral spectrum-related information by PLS (Partial Least Squares) regression analysis is generated.
Based on the spectroscopic spectrum-related information, PLS regression coefficient absolute value information for each wavelength of the plurality of test pieces processed in the PLS regression analysis is generated.
A plurality of candidate window function information is generated based on the PLS regression coefficient absolute value information for each wavelength and the candidate PLS regression coefficient threshold information which is the threshold information of a plurality of candidates.
By processing the window function spectroscopic spectrum-related information generated based on the candidate window function information and the spectroscopic spectrum-related information of the test piece in the PLS regression analysis, a plurality of candidate PLS regression coefficient information is generated.
Among the plurality of candidate PLS regression coefficient information, the PLS regression coefficient information having a relatively small error is stored as the executed PLS regression coefficient information which is the PLS regression coefficient information used for the measurement object.
Based on the spectral spectrum-related information of the object, the executed PLS regression coefficient information is used to process in the PLS regression analysis to generate spectral reflectance spectrum information after the regression coefficient multiplier.
A measurement method characterized in that evaluation information of an object generated based on the spectral reflectance spectral information after the regression coefficient multiplier is displayed on a display unit. For measuring equipment
A step of generating spectroscopic spectrum-related information generated by the reflected light of the irradiation light applied to the test piece without deforming a plurality of test pieces whose evaluation information of the substance to be measured is known.
A step of generating PLS regression coefficient information for calculating the spectral spectrum-related information by PLS (Partial Least Squares) regression analysis, and
Based on the spectral spectrum-related information, a step of generating PLS regression coefficient absolute value information for each wavelength of the plurality of test pieces processed in the PLS regression analysis, and a step of generating the absolute value information of the PLS regression coefficient for each wavelength.
A step of generating a plurality of candidate window function information based on the PLS regression coefficient absolute value information for each wavelength and the candidate PLS regression coefficient threshold information which is the threshold information of a plurality of candidates.
A step of generating a plurality of candidate PLS regression coefficient information by processing the window function spectroscopic spectrum-related information generated based on the candidate window function information and the spectroscopic spectrum-related information of the test piece in the PLS regression analysis. ,
A step of storing the PLS regression coefficient information having a relatively small error among the plurality of candidate PLS regression coefficient information as the executed PLS regression coefficient information which is the PLS regression coefficient information used for the measurement object.
A step of generating spectral reflectance spectrum information after multiplication of the regression coefficient by processing in the PLS regression analysis using the executed PLS regression coefficient information based on the spectral spectrum-related information of the object.
A control program of a measuring device for executing a step of displaying evaluation information of an object generated based on the spectral reflectance spectral information after the regression coefficient multiplier on a display unit.

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