X-ray fluorescence analyzer, data processing method, and program

Abstract

To provide a technique for appropriately removing a sum peak in an analysis result of an X-ray fluorescence analyzer.SOLUTION: A method for processing the initial spectrum of a sample S obtained by processing the output of an X-ray detector 12 is provided. A CPU 30 calculates a predicted value of a count value forming a sum peak using the count value in the initial spectrum and a value of the energy of characteristic X-rays for each of one or more elements constituting the sample S. The CPU 30 subtracts the predicted value calculated for each of one or more elements constituting the sample S from the count value of the initial spectrum, thereby removing the sum peak from the initial spectrum.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a fluorescent X-ray analyzer, a data processing method, and a program.

Background Art

[0002] In the profile of the analysis result of a fluorescent X-ray analyzer, there are not only main peaks (e.g., Kα rays) but also sum peaks. The intensity of the sum peak depends on the counting rate and the time resolution of the detector. The ratio of the intensity I , , of the m-th sum peak to the intensity I (1) of the main peak is derived using the counting rate and the peaking time, as disclosed in Non-Patent Document 1 (Ryohei Tanaka, Koretaka Yuge, Jun Kawaia, Hussain Alawadhib, Artificial peaks in energy dispersive X-ray spectra: sum peaks, escape peaks, and diffraction peaks, X-RAY SPECTROMETRY, John Wiley & Sons, Ltd., 2017, 46, p5-p11).

Prior Art Documents

Non-Patent Documents

[0003]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When sum peaks were removed from the analysis result profile using conventional methods such as those disclosed in Non-Patent Document 1, situations arose where more data than necessary was removed as sum peaks, or where sum peak removal was insufficient.

[0005] This invention was conceived in view of the above circumstances, and its purpose is to provide a technique for appropriately removing sum peaks in the analysis results of an X-ray fluorescence analyzer. [Means for solving the problem]

[0006] A fluorescent X-ray analyzer according to a certain aspect of the present disclosure comprises an X-ray detector for detecting X-rays of a sample, a data processing unit for generating an initial spectrum of the sample by processing the output of the X-ray detector, and a processor for performing a removal process to remove one or more thumb peaks from the initial spectrum, the removal process including calculating a predicted value of the count that will form a thumb peak for each of the one or more elements constituting the sample, using the count value in the initial spectrum and the energy value of the characteristic X-ray, and subtracting the predicted value calculated for each of the one or more elements constituting the sample from the count value in the initial spectrum.

[0007] A data processing method according to a certain aspect of the present disclosure is a method for processing an initial spectrum of a sample obtained by processing the output of an X-ray detector, comprising the steps of: calculating a predicted value of the count that forms a sum peak for each of one or more elements constituting the sample, using the count value in the initial spectrum and the energy value of the characteristic X-ray; and subtracting the predicted value calculated for each of the one or more elements constituting the sample from the count value of the initial spectrum.

[0008] A program that conforms to certain aspects of this disclosure is executed by a computer, causing the computer to perform the data processing method described above. [Effects of the Invention]

[0009] In accordance with certain aspects of this disclosure, the sum peak is appropriately removed from the analysis results of the X-ray fluorescence analyzer. [Brief explanation of the drawing]

[0010] [Figure 1] This figure shows an example of the configuration of the X-ray analyzer 1 according to this embodiment. [Figure 2] This diagram illustrates the process of converting a differential wave to a trapezoidal wave. [Figure 3] This figure shows an example of a wave height distribution map generated by the X-ray analyzer 1 based on the count values ​​stored in the histogram memory 54. [Figure 4] This diagram illustrates the calculation of predicted values ​​for the sum peak using the count values ​​of the main peak. [Figure 5] This figure shows an example of an initial spectrum for Fe. [Figure 6] This figure shows an example of the difference between the detection results and the simulation results. [Figure 7] This figure shows an example of a spectrum after the thumb peak has been removed. [Figure 8] This is a flowchart of the process performed by X-ray analyzer 1 to set the offset value. [Figure 9] This figure shows an example of the change in the spectrum after sum peak removal using an offset value. [Figure 10] Figure 11 shows an example of configuration data used in the data processing described later. [Figure 11] This is a flowchart of the process performed in X-ray analyzer 1 to output a pulse height distribution map using the detection results of a sample. [Modes for carrying out the invention]

[0011] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and their description will not be repeated. <XX000082> <Configuration of X-ray Analyzer 1> FIG. 1 is a diagram showing a configuration example of an X-ray analyzer 1 according to this embodiment. In one implementation example, the X-ray analyzer 1 is an energy dispersive fluorescent X-ray analyzer. As shown in FIG. 1, the X-ray analyzer 1 includes an X-ray tube 10, an X-ray detector 12, a preamplifier 14, a differentiator circuit 16, an amplifier 18, an ADC (Analog to Digital Converter) 20, a CPU (Central Processing Unit) 30, a memory 31, and a signal processing device 40. The X-ray detector 12 is an energy dispersive spectrometer. The signal processing device 40 is an X-ray analysis signal processing device. <00ZZ008>

[0013] The X-ray tube 10 emits primary X-rays to the sample S. The X-ray tube 10 has, for example, a target as an anode, a filament as a cathode, and a housing that houses the target and the filament. When a high voltage is applied to the target and a low voltage is applied to the filament, thermoelectrons emitted from the filament collide with the end face of the target, and primary X-rays are generated at the end face. The primary X-rays generated at the end face of the target are emitted to the sample S. When the sample S is irradiated with the primary X-rays, fluorescent X-rays excited by the primary X-rays are emitted from the sample S and enter the X-ray detector 12.

[0014] The X-ray detector 12 detects the intensity of fluorescent X-rays in a predetermined wavelength range. The X-ray detector 12 is disposed inside the housing and has a detection element that detects the intensity of fluorescent X-rays in the above wavelength range. The detection element is, for example, a lithium-drifted Si semiconductor element.

[0015] The output signal of the X-ray detector 12 is amplified by the preamplifier 14. The output signal becomes a stepped waveform signal by the preamplifier 14. Each step of the stepped waveform signal indicates that fluorescent X-rays are being detected. The height of each step represents the wavelength λ, that is, the X-ray energy E.

[0016] The output signal amplified by the preamplifier 14 is sent to the differentiating circuit 16. The differentiating circuit 16 is composed of a capacitor C and a resistor R, and converts a staircase wave into a differentiated wave represented by the following equation (1). By converting the staircase wave into a differentiated wave, a wide dynamic range can be obtained, and as a result, high resolution can be achieved. The differentiated wave is amplified by an amplifier 18 and sent to the ADC 20.

[0017]

Number

[0018] However, τ(=RC) is the time constant, T is the sampling period, n is the number of samples, and a is (exp(-T / τ)).

[0019] The ADC 20 samples an analog differentiated wave at a predetermined sampling period and converts it into a digital signal (hereinafter referred to as a differentiated wave digital signal). The differentiated wave digital signal is input to the signal processing device 40.

[0020] The signal processing device 40 is generally composed of a logic device such as an FPGA (Field-Programmable Gate Array).

[0021] In the present embodiment, the signal processing device 40 includes an offset correction unit 44, a trapezoidal wave conversion filter 46, a baseline correction unit 48, a gain / offset adjustment unit 50, a peak detector 52, and a histogram memory 54.

[0022] The offset correction unit 44 performs offset correction on the differentiated wave digital signal given from the ADC 20, and outputs the corrected differentiated wave digital signal to the trapezoidal wave conversion filter 46.

[0023] The trapezoidal wave conversion filter 46 is a digital filter configured to convert the differentiated wave corrected by the offset correction unit 44 into a trapezoidal wave represented by the equation (2).

[0024]

number

[0025] Here, in equation (2), M corresponds to the time of the upper base of the trapezoidal wave, and N represents the rise and fall times of the trapezoidal wave.

[0026] Figure 2 is a diagram illustrating the conversion process from a differential wave to a trapezoidal wave. The differential wave shown on the left side of Figure 2 is converted by the trapezoidal wave conversion filter 46 into a trapezoidal wave with rise and fall times both being N and a top-bottom time being M, as shown on the right side of Figure 2.

[0027] The output waveform generated by the trapezoidal wave conversion filter 46 is input to the peak detector 52 after the baseline and gain are adjusted by the baseline correction unit 48 and the gain / offset adjustment unit 50.

[0028] The peak detector 52 detects peaks in the output waveform and obtains the peak height (peak top value) of each peak. The peak detector 52 increments the count value of the X-ray energy E corresponding to the peak top value for each peak and stores it in the histogram memory 54.

[0029] The memory 31 includes a program storage area 31A for storing program data and a data storage area 31B for storing data. The X-ray analyzer 1 performs various processes by having the CPU 30 execute a program stored in the program storage area 31A (or a storage device outside the X-ray analyzer 1).

[0030] The CPU 30 generates a pulse height distribution diagram (energy spectrum histogram) based on the count values ​​stored in the histogram memory 54. The pulse height distribution diagram shows the fluorescent X-ray energy E on the horizontal axis and the elemental content (intensity) on the vertical axis. In the pulse height distribution diagram, element-specific peaks appear at positions corresponding to the fluorescent X-ray energy E emitted from the elements contained in the sample S. The CPU 30 performs qualitative and quantitative analysis of the contained elements based on the location of these peaks and their X-ray intensity values.

[0031] <Sampeek> Figure 3 shows an example of a pulse height distribution diagram generated by the X-ray analyzer 1 based on the count values ​​stored in the histogram memory 54. The pulse height distribution diagram in Figure 3 is for stainless steel containing Ni (Ni-containing SUS) as the sample S. Figure 3 shows the pulse height distribution diagram G11 on the low-energy side and the pulse height distribution diagram G12 on the high-energy side. In each pulse height distribution diagram, the horizontal axis represents energy and the vertical axis represents the number of X-ray photons. In this specification, unless otherwise specified, the horizontal and vertical axes of the pulse height distribution diagrams are the same as those of the horizontal and vertical axes in Figure 3.

[0032] The pulse height distribution diagram G11 shows the so-called main peaks. The main peaks are the peaks caused by the characteristic X-rays of each element. Line L11 in the pulse height distribution diagram G11 is a spectrum containing five peaks. The five peaks, in order of increasing energy, correspond to the Kα line of Cr, the Kβ line of Cr, the Kα line of Fe, the Kβ line of Fe, and the Kα line of Ni.

[0033] Wave height distribution diagram G12 shows what is known as a "sum peak." A sum peak is a type of ghost peak observed in wave height distribution diagrams. When two X-rays enter a detector at short intervals, the detector may not be able to separate and measure the two X-rays, and may measure them as a single X-ray. As a result, the two X-rays are observed as a peak with the energy of the two X-rays added together. A peak observed in this way is a sum peak.

[0034] Line L12 in wave height distribution diagram G12 represents a spectrum that appears to contain eight peaks. The lowest energy peak is a sum peak at the point of lowest energy, attributed to the Kα line of Cr. The second lowest energy peak is a sum peak at the point of lowest energy, attributed to Cr. The third lowest energy peak is a sum peak at the point of lowest energy, attributed to Fe. The fourth lowest energy peak is a superposition of two sum peaks at the point of lowest energy, attributed to Fe. The fifth lowest energy peak is a sum peak at the point of lowest energy, attributed to Fe. The three higher energy peaks (the sixth to eighth lowest energy peaks) are each sum peaks at the point of lowest energy, attributed to Fe.

[0035] The X-ray analyzer 1 generates a wave height distribution map based on the count values ​​stored in the histogram memory 54. This generated wave height distribution map is also referred to herein as the "initial wave height distribution map." The spectrum included in the initial wave height distribution map is an example of the "initial spectrum."

[0036] The X-ray analyzer 1 generates an output pulse height distribution map by removing a thumb peak from the initial spectrum. The spectrum included in the pulse height distribution map thus generated is also referred to herein as the "final spectrum."

[0037] As will be described later with reference to Figure 4, the X-ray analyzer 1 uses the count values ​​of the main peaks of the elements that cause each sum peak to remove the sum peaks.

[0038] <Count values ​​to be removed as thumb peaks> Figure 4 illustrates the calculation of predicted values ​​for a subpeak using the count values ​​of the main peaks. Figure 4 includes pulse height distribution diagrams G21 and G22. Pulse height distribution diagram G21 corresponds to the energy ranges of five main peaks in the initial spectrum obtained for a given sample. Pulse height distribution diagram G22 schematically shows the predicted values ​​calculated using the count values ​​of the main peaks in pulse height distribution diagram G21. The calculation of the predicted values ​​shown in pulse height distribution diagram G22 will be explained in more detail below.

[0039] The X-ray analyzer 1 uses the count values ​​in a given energy range before and after the center position of the main peak P11 to calculate a predicted value of the count value of the sum peak caused by the element corresponding to the main peak P11. The given energy range before and after the center position of the peak is defined as the full width at half maximum (FMHMCoef), and will be described later with reference to Figure 10.

[0040] Figure 4 shows the predicted count values ​​from the main peak P11 within frames M11 and M12. Frame M11 shows the predicted values ​​calculated from the count values ​​near point V11, which is located on the lower energy side of the center of the main peak P11. The predicted values ​​in frame M11 range from approximately 10.7 to 13.2 keV. Frame M12 shows the predicted values ​​calculated from the count values ​​near point V12, which is located on the higher energy side of the center of the main peak P11. The predicted values ​​in frame M12 range from approximately 10.7 to 13.2 keV.

[0041] The X-ray analyzer 1 also uses the count values ​​in a given energy range before and after the center position of the main peak P21 to calculate a predicted value of the count value of the sum peak at the element corresponding to the main peak P21.

[0042] Figure 4 shows the predicted values ​​corresponding to the main peak P21 within frames M21 to M23. Frame M21 shows the predicted values ​​calculated from the count data near point V21, which is located on the lower energy side of the center of the main peak P21. The predicted values ​​in frame M21 range from approximately 11.5 to 12.9 keV. Frame M22 shows the predicted values ​​calculated from the count data near point V22, which is located on the lower energy side of the center of the main peak P21 but on the higher energy side of point V22. The predicted values ​​in frame M22 range from approximately 11.5 to 14.1 keV. Frame M23 shows the predicted values ​​calculated from the count data near point V23, which is located on the higher energy side of the center of the main peak P21. The predicted values ​​in frame M23 range from approximately 11.5 to 14.1 keV.

[0043] As explained with reference to Figure 4, the X-ray analyzer 1 calculates a predicted value for each of the one or more main peaks, which is the count value of the sum peak that is expected to be generated due to the element corresponding to that main peak. The predicted value calculated for main peak P11 is shown in frames M11 and M12. The predicted value calculated for main peak P21 is shown in frames M21 to M23.

[0044] The X-ray analyzer 1 calculates the above predicted values ​​for each of the one or more elements contained in the sample. The X-ray analyzer 1 then derives the predicted values ​​for all the sum peaks included in the initial spectrum by summing the predicted values ​​calculated for each of the one or more elements. Finally, the X-ray analyzer 1 generates the final spectrum by subtracting the predicted values ​​for all the sum peaks from the initial spectrum.

[0045] <Method for calculating predicted values> Equation (3) represents the formula used by the X-ray analyzer 1 to calculate a predicted value for the m-th sum peak of a given element.

[0046]

number

[0047] In equation (3), I (m+1) represents the count value (predicted value) of the m-th sum peak. c represents the count rate (cps), and r represents the peaking time. c and r are described in Non-Patent Literature 1 (Ryohei Tanaka, Koretaka Yuge, Jun Kawaia, Hussain Alawadhib, Artificial peaks in energy dispersive X-ray spectra: sum peaks, escape peaks, and diffraction peaks, X-RAY SPECTROMETRY, John Wiley & Sons, Ltd., 2017, 46, p5-p11). I1 represents the count value (detected value) of the main peak.

[0048] The CoefMode in equation (3) is expressed by the following equation (4).

[0049]

number

[0050] CoefA, CoefE, and Coef are all predetermined constants. e represents the energy of the characteristic X-rays of the element for which the predicted value is calculated.

[0051] CoefE may be the energy of the characteristic X-ray of the reference element in the X-ray analyzer 1. In this case, the term "CoefE-e" in equation (4) represents the difference in characteristic X-ray energy between the reference element and the element for which the predicted value is to be calculated.

[0052] For example, let's consider a case where Fe is used as the reference element. The energy of Fe's Kα characteristic X-ray is 6.398 (approximately 6.40) keV. In this example, the value of CoefE is set to 6.40.

[0053] The energy of the characteristic X-ray Kα of Cu is approximately 8.04 keV. In the above example, when calculating the sum peak due to Cu, 8.04 (keV) is used as e, so the CoefMode is derived according to the following equation (5).

[0054]

number

[0055] On the other hand, in the above example, when calculating the sum peak caused by Fe, 6.40 (keV) is used as e, so CoefMode is derived according to the following equation (6). That is, CoefMode is simply derived as Coef itself.

[0056]

number

[0057] As explained with reference to equation (6), if the energy of the characteristic X-ray of a given element is used as CoefE, the calculation of the predicted value for the sum peak attributable to that element can be simplified.

[0058] In the calculation of the predicted value as explained with reference to equations (3) to (6), CoefA can be a positive value. In this case, as the value of e increases, the value of CoefMode decreases. When the value of CoefMode decreases, I calculated according to equation (3) (m+1) The value of also becomes smaller. In other words, the predicted value of the sum peak count calculated according to equation (3) will have a coefficient (Coef) that decreases as the energy of the characteristic X-ray of the element in question increases. As a result, the data processing method for sum peak removal in this embodiment can take into account the energy dependence of the sum peak rate on the X-rays.

[0059] <Setting the offset value> Figure 5 shows an example of an initial spectrum for Fe. Figure 5 shows pulse height distribution diagrams G51 and G52. Pulse height distribution diagram G51 corresponds to the energy region containing the main peak. The line L51 shown in pulse height distribution diagram G51 represents the spectrum of the sample, which contains two peaks. One of the two peaks corresponds to the main peak of Fe's Kα. Pulse height distribution diagram G52 corresponds to the energy region containing a thumb peak. The line L52 shown in pulse height distribution diagram G52 represents the spectrum of the sample, which contains two thumb peaks.

[0060] Figure 6 shows an example of the difference between the detection result and the simulation result. In the pulse height distribution diagram G61 shown in Figure 6, line L61 represents the spectrum obtained as a simulation result, and line L62 represents the spectrum obtained as a detection result in the X-ray analyzer 1. In Figure 6, both peaks of line L62 are located on the higher energy side than the two peaks of line L61. In other words, the spectrum obtained as a detection result in the X-ray analyzer 1 contains a discrepancy with the actual energy. One possible cause of this discrepancy is the coarseness of the step width (energy width) in which data is acquired in the X-ray analyzer 1.

[0061] Figure 7 shows an example of a spectrum after the thumb peak has been removed. Line L71 in the pulse height distribution diagram G71 in Figure 7 is an example of a spectrum after the thumb peak has been removed by the X-ray analyzer 1.

[0062] Line L71 includes a region that is significantly recessed compared to the adjacent energy regions, as shown by circles C71 and C72. One possible cause of such a region is that the energy in the detection result is misaligned with the actual energy, as explained with reference to Figure 6. In other words, because the energy corresponding to the count subtracted as a sum peak is misaligned with the actual energy, it is assumed that one possible cause is that the count is subtracted from the energy in a region that is misaligned with the energy from which the count should be subtracted as a sum peak.

[0063] Therefore, the X-ray analyzer 1 may apply an offset value to the energy of the measured value used in calculating the predicted value according to equation (3). The X-ray analyzer 1 may set the offset value used in this way as a calibration.

[0064] Figure 8 is a flowchart of the process performed by the X-ray analyzer 1 to set the offset value. In one implementation example, the process in Figure 8 is realized by the CPU 30 executing a given program.

[0065] Referring to Figure 8, in step SA1, the X-ray analyzer 1 generates simulation results. In one implementation example, the X-ray analyzer 1 uses dedicated software to generate the expected fluorescence X-ray spectrum for a reference sample as a simulation result.

[0066] In step SA2, the X-ray analyzer 1 selects a given number of peaks in the simulation results. Information identifying the given number may be pre-stored in the data storage area 31B. The selected peak may be the single peak with the highest count value in the simulation results.

[0067] In step SA3, the X-ray analyzer 1 identifies the energy range to be compared for each of the selected peaks. The energy range to be compared may be the full width at half maximum of the peak.

[0068] In step SA4, the X-ray analyzer 1 calculates the difference in count values ​​between the simulation results and the detection results for the energy region identified in step SA3. The detection results are, for example, the initial spectrum of the reference sample obtained by the X-ray analyzer 1.

[0069] In step SA5, the X-ray analyzer 1 generates NA comparison profiles by shifting the detection results used in step SA4 to higher energies by a given value. The given value is, for example, 1 eV.

[0070] In step SA6, the X-ray analyzer 1 generates NA comparison profiles by shifting the detection results used in step SA4 to the lower energy side by a given value. The given value is, for example, 1 eV.

[0071] In step SA7, the X-ray analyzer 1 calculates the difference in count values ​​between the simulation results and the NA comparison profiles generated in step SA5 and step SA6, for each of the NA comparison profiles generated in step SA6, for the energy range identified in step SA3. If "20" is used as NA, 40 differences will be generated in step SA7.

[0072] In step SA8, the X-ray analyzer 1 identifies the minimum value among the differences calculated in step SA4 and the differences calculated in step S7.

[0073] In step SA9, the X-ray analyzer 1 identifies the shift value (shifted energy value) corresponding to the minimum value identified in step SA8 as the offset value and stores it in the identified offset value data storage area 31B. In one implementation example, the offset value is stored as "PosOffset" and "PosOffsetEx" as described later, with reference to Figure 10.

[0074] Subsequently, the X-ray analyzer 1 completes the process shown in Figure 8.

[0075] The X-ray analyzer 1 may use an initial spectrum with an energy shift of an offset value when calculating the predicted count value for the sum peak according to equation (3).

[0076] Figure 9 shows an example of the change in the spectrum after thumb peak removal using an offset value.

[0077] Figure 9 shows the wave height distribution diagrams G91 and G92. In wave height distribution diagram G91, line L91 represents the spectrum after thumb peak removal using equation (3) without using an offset value from the initial spectrum. In wave height distribution diagram G92, line L92 represents the spectrum after thumb peak removal using equation (3) with an offset value from the initial spectrum. The use of an offset value means that, as described above, the initial spectrum is shifted by the offset value and then used to calculate the count value for thumb peaks in equation (3).

[0078] In line L91, the area indicated by circle C91 shows excessive subtraction of the count value, while the area indicated by circle C92 shows residual count value. On the other hand, in line L92, the count value is appropriately subtracted in the energy regions corresponding to both circles C91 and C92. In other words, by utilizing offset values, sum peak removal can be achieved more effectively.

[0079] <Configuration Data> Figure 10 shows an example of configuration data used in the data processing described later, referring to Figure 11.

[0080] In Figure 10, "Enable" determines whether or not to perform thumb peak removal. If the value is "1", thumb peak removal is performed on the initial spectrum; if the value is "0", thumb peak removal is not performed on the initial spectrum.

[0081] "CoefMode" specifies how CoefMode is calculated. When the value is "2", CoefMode is calculated according to formula (4) above.

[0082] The setting data in Figure 10 includes the settings for "Coef," "CoefA," and "CoefE" used in equation (4), as well as "FMHMCoef," which is used as the full width at half maximum in the predicted value of the sum peak.

[0083] "TopNum" specifies the number of main peaks used as the source for generating the thumb peak.

[0084] "CheckNum" specifies the number of peaks to which a sum peak will be generated. The number of target peaks refers to the number of peaks included in the sum peak prediction value described above.

[0085] "MinTopLevel" defines the threshold value for the maximum count of the peak used to generate the sum peak as the main peak. In other words, peaks with a value greater than "MinTopLevel" will not be used to generate the sum peak. This helps to prevent peaks generated by detection errors in the initial spectrum from being used to generate the sum peak.

[0086] "MinCheckLevel" defines the threshold for the target peak (the ratio of the count value of the sum peak to the sum of all count values).

[0087] "EnergyL" and "EnergyH" each define the range (lower and upper limits) of peak energy used to generate the main peak.

[0088] "RecalcBG" specifies whether or not to recalculate the background during the generation of the initial spectrum.

[0089] "BGRept" specifies the number of times the background recalculation is repeated during the generation of the initial spectrum.

[0090] "BGPoint" specifies the number of energy points used when recalculating the background during the generation of the initial spectrum.

[0091] "BGMode" specifies the mode of automatic background calculation in the generation of the initial spectrum. When the value is "1", a mode is adopted in which the background value does not fall below a given value. When the value is "0", the normal mode is adopted, i.e., the mode in which the detected value is used as is.

[0092] "Interpolate" specifies whether to enable the offset of the thumb peak appearance location, that is, whether to use the aforementioned offset value to shift the initial spectrum when calculating the predicted value of the thumb peak.

[0093] "PosOffset" and "PosOffsetEx" define the decimal and integer parts of the offset value mentioned above, respectively.

[0094] <Processing flow> Figure 11 is a flowchart of the process performed in the X-ray analyzer 1 to output a pulse height distribution map using the detection results of a sample. In one implementation example, the process in Figure 11 is performed by the CPU 30 executing a given program.

[0095] In step S10, the X-ray analyzer 1 reads count values ​​from the histogram memory 54 and reads various settings from the data storage area 31B. The settings include the setting data described with reference to Figure 10.

[0096] In step S12, the X-ray analyzer 1 generates an initial wave height distribution map.

[0097] In step S14, the X-ray analyzer 1 determines whether it is configured to remove the thumb peak from the initial pulse height distribution diagram. In one implementation example, it is determined whether the value of "Enable" in the setting data in Figure 10 is "1". If the X-ray analyzer 1 determines that it is configured to remove the thumb peak (YES in step S14), it proceeds to step S16; otherwise (NO in step S14), it proceeds to step S24.

[0098] In step S16, the X-ray analyzer 1 sets the value of variable N to 1. Variable N represents the number of main peaks used to calculate the predicted value of the sum peak.

[0099] In step S18, the X-ray analyzer 1 generates data for thumb peak removal for the Nth main peak. An example of thumb peak removal data generated for the Nth main peak is the data in frames M11 and M12 generated for main peak P11 in Figure 4. Another example of thumb peak removal data is the data in frames M21 to M23 generated for main peak P21 in Figure 4. The thumb peak removal data generated for each main peak constitutes an example of a "predicted value" in thumb peak removal.

[0100] In generating data for thumb peak removal, the X-ray analyzer 1 may shift the initial spectrum by the offset value. More specifically, if the "Interpolate" value in the setting data shown in Figure 10 enables the offset, the X-ray analyzer 1 shifts the initial spectrum by the offset value and then generates data for thumb peak removal. If the "Interpolate" value in the setting data shown in Figure 10 does not enable the offset, the X-ray analyzer 1 generates data for thumb peak removal without shifting the initial spectrum.

[0101] In step S20, the X-ray analyzer 1 determines whether the value of variable N has reached a predetermined value M. Value M is the number of main peaks used to generate data for removing thumb peaks, and is stored in the data storage area 31B as "TopNum" in Figure 10. If the X-ray analyzer 1 determines that the value of variable N has reached M (YES in step S20), it proceeds to step S22; otherwise (NO in step S20), it proceeds to step S26.

[0102] In step S26, the X-ray analyzer 1 updates the value of variable N by incrementing it by 1 and returns control to step S18.

[0103] In step S22, the X-ray analyzer 1 generates a final pulse height distribution map. More specifically, the X-ray analyzer 1 generates the final spectrum by removing all the count values ​​contained in each of the M peak removal data created in step S18 from the initial spectrum included in the initial pulse height distribution map. Then, the X-ray analyzer 1 generates a final pulse height distribution map by combining the final spectrum with the vertical and horizontal axes.

[0104] For example, let's assume that X-ray analyzer 1 generates peak removal data, specifically peak removal data from the main peak P11 in Figure 4 (data shown in frames M11 and M12), and peak removal data from the main peak P21 in Figure 4 (data shown in frames M21, M22, and M23). In this case, X-ray analyzer 1 generates the final spectrum by subtracting the count values ​​of each energy in the peak removal data from the main peak P11 and the count values ​​of each energy in the peak removal data from the main peak P11 from the count values ​​of each energy in the initial spectrum.

[0105] In step S24, the X-ray analyzer 1 outputs a wave height distribution diagram. After that, the X-ray analyzer 1 completes the processing shown in Figure 11. If the X-ray analyzer 1 is set to remove the thumb peak (YES in step S14), the wave height distribution diagram output in step S24 is the final wave height distribution diagram generated in step S22. If the X-ray analyzer 1 is not set to remove the thumb peak (NO in step S14), the wave height distribution diagram output in step S24 is the initial wave height distribution diagram.

[0106] In the embodiments described above, the data for peak removal from the main peak P11 in Figure 4 (data shown in frames M11 and M12) and the data for peak removal from the main peak P21 in Figure 4 (data shown in frames M21, M22, and M23) were exemplified as predicted values ​​of the count values ​​constituting the sum peak. The predicted values ​​are calculated based on equation (3). The CoefMode in equation (3) is expressed by equation (4). Equation (4) includes the energy of the characteristic X-ray of the element for which the predicted value is to be calculated as e. That is, in this embodiment, the predicted value reflects the energy of the characteristic X-ray of the element that causes the sum peak. As a result, the predicted value reflects the energy dependence of the X-ray on the rate in which sum peaks occur.

[0107] [Pattern] Those skilled in the art will understand that the above-described exemplary embodiments are specific examples of the following embodiments.

[0108] (Section 1) A fluorescent X-ray analyzer according to one embodiment comprises an X-ray detector for detecting X-rays of a sample, a data processing unit for generating an initial spectrum of the sample by processing the output of the X-ray detector, and a processor for performing a removal process to remove one or more thumb peaks from the initial spectrum, wherein the removal process may include calculating a predicted value of the count that will form a thumb peak for each of the one or more elements constituting the sample, using the count value in the initial spectrum and the energy value of the characteristic X-ray, and subtracting the predicted value calculated for each of the one or more elements constituting the sample from the count value of the initial spectrum.

[0109] According to the X-ray fluorescence analyzer described in paragraph 1, the sum peak is appropriately removed from the analysis results.

[0110] (Paragraph 2) In the X-ray fluorescence analyzer according to Paragraph 1, the predicted value may decrease as the energy of the characteristic X-rays used increases.

[0111] According to the X-ray fluorescence analyzer described in paragraph 2, the energy dependence of the characteristic X-rays of the original element is reflected in the proportion of the sum peaks that appear.

[0112] (3) In the X-ray fluorescence analyzer according to paragraph 2, calculating the predicted value includes calculating the product of the count value in the initial spectrum, a first coefficient, and a second coefficient, wherein the second coefficient may include a term obtained by subtracting the value of the characteristic X-ray energy from a given constant.

[0113] According to the X-ray fluorescence analyzer described in Section 3, the energy dependence of the characteristic X-rays of the original element is directly reflected in the proportion of sum peaks that appear.

[0114] (Clause 4) In the X-ray fluorescence analyzer relating to paragraph 3, the given constant may be the energy value of the characteristic X-ray of a given element.

[0115] The X-ray fluorescence analyzer described in paragraph 4 facilitates the calculation of predicted values ​​for a given element.

[0116] (Clause 5) In a fluorescence X-ray analyzer relating to any one of Clauses 1 to 4, the processor may use the initial spectrum and the simulation data corresponding to the initial spectrum to identify an energy offset value, and the initial spectrum shifted by the offset value may be used to calculate the predicted value.

[0117] According to the X-ray fluorescence analyzer described in Section 5, even if an energy shift occurs in the initial spectrum, the effect of this shift is reduced in the calculation of the predicted value.

[0118] (Clause 6) In the X-ray fluorescence analyzer relating to Clause 5, the offset value may be calculated based on the difference between the initial spectrum and the simulation data corresponding to the initial spectrum.

[0119] According to the X-ray fluorescence analyzer described in Section 6, the offset value can be easily and appropriately calculated.

[0120] (Clause 7) A data processing method according to one embodiment is a method for processing an initial spectrum of a sample obtained by processing the output of an X-ray detector, comprising the steps of: calculating a predicted value of the count that forms a sum peak for each of the one or more elements constituting the sample, using the count value in the initial spectrum and the energy value of the characteristic X-ray; and subtracting the predicted value calculated for each of the one or more elements constituting the sample from the count value of the initial spectrum.

[0121] According to the data processing method described in Section 7, the sum peak is appropriately removed from the analysis results of the X-ray fluorescence analyzer.

[0122] (Clause 8) In the data processing method relating to paragraph 7, the predicted value may become smaller as the energy of the characteristic X-rays used increases.

[0123] According to the data processing method described in Section 8, the proportion of sum peaks that appear reflects the energy dependence of the characteristic X-rays of the original element.

[0124] (Clause 9) In the data processing method relating to Clause 8, the step of calculating the predicted value includes calculating the product of the count value in the initial spectrum, a first coefficient, and a second coefficient, wherein the second coefficient may include a term obtained by subtracting the value of the characteristic X-ray energy from a given constant.

[0125] According to the data processing method described in Section 9, the energy dependence of the characteristic X-rays of the original element is directly reflected in the proportion of sum peaks that appear.

[0126] (Clause 10) In the data processing method relating to paragraph 9, the given constant may be the energy value of the characteristic X-ray of a given element.

[0127] According to the data processing method described in paragraph 10, it becomes easier to calculate predicted values ​​for a given element.

[0128] (Clause 11) The data processing method relating to any one of Clauses 7 to 10 further comprises the step of identifying an energy offset value using the initial spectrum and simulation data corresponding to the initial spectrum, and the initial spectrum shifted by the offset value may be used for calculating the predicted value.

[0129] According to the data processing method described in paragraph 11, even if an energy shift occurs in the initial spectrum, the effect of that shift is reduced in the calculation of the predicted value.

[0130] (Clause 12) In the data processing method relating to paragraph 11, determining the offset value may include calculating the difference between the initial spectrum and the simulation data corresponding to the initial spectrum.

[0131] According to the data processing method described in paragraph 12, the offset value can be easily and appropriately calculated.

[0132] (Clause 13) A program according to one embodiment may be executed by a computer, causing the computer to perform the data processing method according to any one of paragraphs 7 to 12.

[0133] According to the program described in Section 13, the thumb peak is properly removed from the analysis results of the X-ray fluorescence analyzer.

[0134] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of this disclosure is indicated by the claims rather than by the description of the embodiments above, and all modifications within the meaning and scope equivalent to the claims are intended to be included. Furthermore, each technology in the embodiments is intended to be practiced individually or, as far as possible, in combination with other technologies in the embodiments. [Explanation of symbols]

[0135] 1 X-ray analyzer, 10 X-ray tubes, 30 CPUs, 40 signal processing units, S sample.

Claims

1. An X-ray detector that emits X-rays from the sample, A data processing unit that generates the initial spectrum of the sample by processing the output of the X-ray detector, The system includes a processor that performs a removal process to remove one or more sum peaks from the initial spectrum, The aforementioned removal process is For each of the one or more elements constituting the sample, the predicted count value for forming a sum peak is calculated using the count value in the initial spectrum and the energy value of the characteristic X-ray. This includes subtracting the predicted values ​​calculated for each of the one or more elements constituting the sample from the count values ​​of the initial spectrum, The count value in the initial spectrum includes the count value of the main peak in the initial spectrum. Calculating the aforementioned predicted value involves using the following formula (1): [Math 1] In the above formula (1), I(m+1) represents the predicted value of the count of the m-th sum peak, c represents the counting rate, r represents the peaking time, I1 represents the count value of the main peak in the initial spectrum, CoefMode is expressed by the following equation (2): [Math 2] In the above formula (2), CoefA, CoefE, and Coef represent predetermined constants. e represents the energy of the characteristic X-rays of the element for which the predicted value is to be calculated. X-ray fluorescence analyzer.

2. The aforementioned processor, Using the initial spectrum and the simulation data corresponding to the initial spectrum, the energy offset value is identified. The X-ray fluorescence analyzer according to claim 1, wherein the initial spectrum shifted by the offset value is used to calculate the predicted value.

3. The X-ray fluorescence analyzer according to claim 2, wherein the offset value is calculated based on the difference between the initial spectrum and the simulation data corresponding to the initial spectrum.

4. A method for processing the initial spectrum of a sample obtained by processing the output of an X-ray detector, For each of the one or more elements constituting the sample, the step of calculating a predicted value of the count that will form a sum peak using the count value in the initial spectrum and the energy value of the characteristic X-ray, The process includes the step of subtracting the predicted values ​​calculated for each of the one or more elements constituting the sample from the count values ​​of the initial spectrum, The count value in the initial spectrum includes the count value of the main peak in the initial spectrum. The step of calculating the predicted value includes using the following formula (1): [Math 3] In the above formula (1), I(m+1) represents the predicted value of the count of the m-th sum peak, c represents the counting rate, r represents the peaking time, I1 represents the count value of the main peak in the initial spectrum, CoefMode is expressed by the following equation (2): [Math 4] In the above formula (2), CoefA, CoefE, and Coef represent predetermined constants. e is a data processing method that represents the energy of the characteristic X-rays of the element for which the predicted value is to be calculated.

5. The process further comprises the step of determining an energy offset value using the initial spectrum and simulation data corresponding to the initial spectrum, The data processing method according to claim 4, wherein the initial spectrum shifted by the offset value is used to calculate the predicted value.

6. Determining the aforementioned offset value is: The data processing method according to claim 5, which includes calculating the difference between the initial spectrum and the simulation data corresponding to the initial spectrum.

7. A program that, when executed by a computer, causes the computer to perform the data processing method described in any one of claims 4 to 6.

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