Measuring device and its control method, and program

Abstract

To improve the accuracy of measuring physical quantity distributions. [Solution] The measuring device comprises a first light generation unit that generates a first light, a second light generation unit that generates a second light having a different frequency from the first light, a light receiving unit that converts a third light, which is scattered light generated by incidenting the first light onto the first end of the optical fiber to be measured and the second light onto the second end of the optical fiber, into an electrical signal, and a processor. The processor determines the peak frequency for each of the multiple waveforms of the third light converted into an electrical signal, calculates the average value of the determined peak frequencies to calculate the frequency shift of the third light, and outputs the calculated frequency shift of the third light.

Description

Technical Field

[0001] The present disclosure relates to a measuring device, a control method thereof, and a program.

Background Art

[0002] Devices for measuring the distribution of physical quantities such as temperature and strain by measuring the spectrum of Brillouin scattered light from an optical fiber of a measurement target are known. For example, Patent Document 1 describes a technique related to the measurement of Brillouin frequency shift distribution in Brillouin optical fiber time domain analysis (BOTDA).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the conventional configuration has room for improvement in the measurement accuracy of the physical quantity distribution.

[0005] An object of the present disclosure is to improve the measurement accuracy of the physical quantity distribution.

Means for Solving the Problems

[0006] The measuring device according to some embodiments includes: (1) a first light generation unit that generates first light; a second light generation unit that generates second light having a different frequency from the first light; a light receiving unit that converts third light, which is scattered light generated by incident the first light on a first end of an optical fiber of a measurement target and incident the second light on a second end of the optical fiber, into an electrical signal; a processor; and includes. The aforementioned processor, The peak frequency of each of the multiple waveforms of the third light converted into an electrical signal is determined, and the average value of the determined peak frequencies is calculated to calculate the frequency shift of the third light. The calculated frequency shift of the third light is output.

[0007] In one embodiment, (2) In the measuring device of (1), The light receiving unit may convert Brillouin scattered light as the third light into an electrical signal.

[0008] In one embodiment, (3) In the measuring device of (1) or (2), It is possible to perform a first averaging method which calculates an averaged waveform by averaging multiple waveforms of the third light converted into electrical signals, calculates the peak frequency of the averaged waveform, and calculates the frequency shift of the third light; and a second averaging method which determines the peak frequency for each of the multiple waveforms of the third light converted into electrical signals, calculates the average value of the determined peak frequencies, and calculates the frequency shift of the third light. The aforementioned processor, The frequency shift of the third light is calculated using either the first averaging method or the second averaging method. The calculated frequency shift of the third light may be output.

[0009] (4)(3) In the measuring device, The aforementioned processor, The user selects either the first averaging method or the second averaging method. The frequency shift of the third light is calculated using the method selected by the user from among the first averaging method and the second averaging method. The frequency shift of the third light, calculated by the method selected by the user, may be output.

[0010] In one embodiment, In the measuring device of (5)(3), The processor acquires noise information indicating the magnitude of the noise included in the third light converted into an electrical signal, determines a recommended averaging method based on the noise information, calculates the frequency shift of the third light by the determined recommended averaging method, and may output the frequency shift of the third light calculated by the recommended averaging method.

[0011] In one embodiment, In the measuring device of (6)(5), The processor may determine, as the recommended averaging method, an averaging method with a smaller variation in the frequency shift of the third light by referring to the relationship between the magnitude of the noise acquired in advance and the variation in the frequency shift of the third light.

[0012] In one embodiment, In the measuring device of (7)(5), The processor inputs the measurement conditions at the time of measurement including the noise information to a prediction model previously obtained for each averaging method by machine learning using the measurement conditions of the frequency shift of the third light as explanatory variables and the variation in the frequency shift of the third light as the objective variable, predicts the measurement accuracy of the frequency shift of the third light, and may determine, as the recommended averaging method, an averaging method with a higher measurement accuracy of the frequency shift of the third light.

[0013] In one embodiment, In the measuring device of any one of (8)(1) to (7), The processor determines the peak frequency for each of a plurality of waveforms of the third light sequentially acquired in accordance with the passage of time, calculates the moving average of the determined peak frequencies as the average value, and calculates the frequency shift of the third light, The calculated frequency shift of the third light may be output.

[0014] In one embodiment, (9) In any one of the measuring devices (1) to (7), the processor determines the peak frequency for each of a plurality of waveforms of the third light sequentially acquired according to the passage of time, and calculates the weighted average calculated by multiplying a greater weight to the more recently acquired peak frequency with respect to the determined peak frequency as the average value, and calculates the frequency shift of the third light, The calculated frequency shift of the third light may be output.

[0015] A control method for a measuring device according to some embodiments, (10) a first light generation unit that generates first light, a second light generation unit that generates second light having a different frequency from the first light, a light receiving unit that converts the third light, which is scattered light generated by incident the first light on a first end of an optical fiber to be measured and the second light on a second end of the optical fiber, into an electrical signal, a processor, A control method for a measuring device including: where the processor determines the peak frequency for each of a plurality of waveforms of the third light converted into an electrical signal, calculates the average value of the determined peak frequencies, and calculates the frequency shift of the third light, outputs the calculated frequency shift of the third light, and includes.

[0016] A program according to some embodiments, (11) a first light generation unit that generates first light, a second light generation unit that generates second light having a different frequency from the first light, a light receiving unit that converts the third light, which is scattered light generated by incident the first light on a first end of an optical fiber to be measured and the second light on a second end of the optical fiber, into an electrical signal, Processor and A program for controlling the operation of a measuring device equipped with the following: The aforementioned processor, A procedure for determining the peak frequency of each of the multiple waveforms of the third light converted into an electrical signal, and calculating the average value of the determined peak frequencies to calculate the frequency shift of the third light, A procedure for outputting the calculated frequency shift of the third light, Make it run. [Effects of the Invention]

[0017] According to one embodiment of this disclosure, the measurement accuracy of the physical quantity distribution can be improved. [Brief explanation of the drawing]

[0018] [Figure 1] This figure shows an example of the configuration of a measuring device according to one embodiment. [Figure 2] This flowchart shows an example of how the measuring device works. [Figure 3] This is an overview diagram showing an example of the process for calculating the average BFS using the first averaging method. [Figure 4] This flowchart shows an example of how the measuring device works. [Figure 5] This is an overview diagram showing an example of the process for calculating the average BFS using the second averaging method. [Figure 6] This scatter plot shows an example of the distribution of average BFS for each averaging method. [Figure 7] This scatter plot shows an example of the distribution of average BFS for each averaging method. [Figure 8] This scatter plot shows an example of the distribution of average BFS for each averaging method. [Figure 9] This scatter plot shows an example of the distribution of average BFS for each averaging method. [Figure 10] This histogram shows an example of the distribution of mean BFS calculated using the first averaging method. [Figure 11]This histogram shows an example of the distribution of mean BFS calculated using the second averaging method. [Figure 12] This graph shows the relationship between the noise level and the standard deviation of the mean BFS. [Figure 13] This flowchart shows an example of how the measuring device works. [Modes for carrying out the invention]

[0019] <Embodiment> Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. In each drawing, parts having the same configuration or function are denoted by the same reference numerals. In the description of this embodiment, redundant descriptions of the same parts may be omitted or simplified as appropriate.

[0020] (Example of the configuration of measuring device 1) First, an example of the configuration of the measuring device 1 will be described. Figure 1 is a diagram showing an example of the configuration of the measuring device 1 according to one embodiment. The measuring device 1 is an optical fiber sensing device that measures the spectrum of Brillouin scattered light from the FUT (Fiber Under Test) 50, which is an optical fiber to be measured, and measures the distribution of physical quantities such as temperature and strain in the FUT 50. By attaching or embedding the FUT 50 in a structure or the like and measuring the changes in the physical quantities of the FUT 50, the measuring device 1 can determine the soundness (health condition) of the structure.

[0021] Measurement device 1 measures the characteristics of FUT50 using the Brillouin Optical Correlation Domain Analysis (BOCDA) method. Measurement device 1 measures the characteristics of FUT50 by injecting frequency-modulated probe light from one end of FUT50 and frequency-modulated pump light from the other end. Here, at the correlation peak position, which is the position where the optical frequency difference between the probe light and the pump light is constant, the probe light gains due to stimulated Brillouin scattering.

[0022] The spectrum of Brillouin scattered light is called the BGS (Brillouin Gain Spectrum). The peak frequency of the BGS is called the BFS (Brillouin frequency shift). The BFS is known to have a linear relationship with temperature and strain. Therefore, the measuring device 1 can measure the temperature and strain of FUT50 by determining the BFS from the observed BGS. By changing the measurement position along the longitudinal direction of FUT50, the measuring device 1 can measure the temperature and strain distribution at various positions on FUT50.

[0023] Specifically, the frequency difference ν between the pump light and the probe light. B Sweep the frequency difference ν B When the level of the probe light relative to the BFS is measured as the gain, a spectrum with the shape of a Lorentz function centered on the BFS is obtained. The measuring device 1 can measure the relative strain or temperature at the measurement position by moving the correlation peak to the desired measurement position in the FUT50 and measuring the BFS. By repeating this process, the measuring device 1 can measure the strain distribution or temperature distribution along the longitudinal direction of the FUT50.

[0024] As shown in Figure 1, the measuring device 1 comprises a control processing unit 10, a light source unit 20, a light receiving unit 30, and a light circulator 40.

[0025] The light source unit 20 generates probe light as the first light source and pump light as the second light source. The light source unit 20 emits the probe light to one end (first end) of the FUT 50 and emits the pump light to the optical circulator 40 connected to the other end (second end) of the FUT 50. The light source unit 20 includes a probe light generation unit 21 as the first light generation unit and a pump light generation unit 22 as the second light generation unit.

[0026] Both probe light and pump light are generated by frequency modulating and amplifying laser light output from a semiconductor laser. For example, the probe light generation unit 21 and the pump light generation unit 22 may generate probe light and pump light based on frequency modulated laser light output from a common semiconductor laser. Probe light is light with a different frequency and amplitude from pump light. The probe light generation unit 21 may generate probe light by shifting the frequency of frequency modulated laser light and amplifying its amplitude, and output the generated probe light to one end of the FUT 50. The probe light generation unit 21 may be able to adjust the amount of shift when shifting the frequency of frequency modulated laser light. The pump light generation unit 22 may generate pump light by amplifying the frequency of frequency modulated laser light, and output the generated pump light to the optical circulator 40.

[0027] The light source unit 20 may include at least one of the following: a semiconductor laser, a temperature control circuit, a drive circuit, an optical pulse generation circuit, a frequency modulation circuit, a signal generator, a directional coupler (optical coupler), etc.

[0028] Furthermore, the probe light generation unit 21 may include, for example, an optical frequency shifter and an optical amplifier. The optical frequency shifter shifts the frequency of the frequency-modulated laser light. The optical frequency shifter may be, for example, an SSB (Single Side Band) modulator. The optical amplifier amplifies the amplitude of the frequency-modulated laser light. The probe light generation unit 21 may further include at least one of a polarization controller, an optical switch, an optical isolator, an optical attenuator, a signal generator, a peak adjustment unit, etc.

[0029] Furthermore, the pump light generation unit 22 may include at least one of a polarization controller, an optical switch, an optical isolator, an optical amplifier, an optical frequency shifter, an optical attenuator, a signal generator, and the like. The optical frequency shifter may be configured using an SSB modulator or the like.

[0030] The configuration of the light source unit 20 described above is just one example, and the light source unit 20 may have any configuration capable of generating probe light and pump light.

[0031] The optical circulator 40 emits scattered light, which is incident from the FUT 50 as third light, to the light receiving unit 30. The optical circulator 40 may be equipped with a directional coupler (optical coupler).

[0032] The light receiving unit 30 receives light incident from the light circulator 40 and converts it into an electrical signal that can be processed by the control processing unit 10. The light receiving unit 30 includes a photodetector 31 and a light receiving circuit 32.

[0033] The photodetector 31 converts the light incident from the light circulator 40 into an electrical signal and outputs it to the light receiving circuit 32. The photodetector 31 may include a photodiode for converting the incident light into an electrical signal. The photodiode may have any configuration, such as an avalanche photodiode, a PIN type photodiode, or a differential balanced photodiode incorporating two photodiodes with matched characteristics. The photodetector 31 may further include an optical attenuator, a trans-impedance amplifier circuit, etc. Such a configuration is just an example, and the photodetector 31 may have any configuration for converting the incident light into an electrical signal.

[0034] The light receiving circuit 32 processes the electrical signal input from the photodetector 31, such as amplification and filtering, to convert it into an electrical signal that can be processed by the control processing unit 10. The light receiving circuit 32 outputs the converted electrical signal to the control processing unit 10. The light receiving circuit 32 may have any configuration, such as an A / D (Analog-to-Digital) converter, an amplification circuit, or a filtering circuit. Such a configuration is just an example, and the light receiving circuit 32 may have any configuration that converts the input signal into an electrical signal that can be processed by the control processing unit 10.

[0035] The control processing unit 10 controls the operation of the light source unit 20 and the light receiving unit 30, analyzes the BGS returned from the FUT 50 based on the electrical signal received from the light receiving unit 30 to calculate the BFS, and converts the BFS into physical quantities such as temperature and strain. The control processing unit 10 is composed of any general-purpose computer, such as a PC (Personal Computer), but may also be other dedicated electronic equipment. The control processing unit 10 may be one computer or multiple computers that can communicate with each other. For example, the control processing unit 10 may be equipped with a spectrum analyzer, oscilloscope, voltmeter, etc., and spectral analysis may be performed using these instruments.

[0036] The control processing unit 10 comprises a processor 11, a storage unit 12, an input unit 13, and an output unit 14.

[0037] The processor 11 controls the operation of the entire control processing unit 10. The processor 11 includes at least one controller, at least one arithmetic unit, at least one dedicated circuit, or a combination thereof. The processor 11 may be a general-purpose processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), or a dedicated processor specialized for a specific process. The dedicated circuit may be, for example, an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). At least some of the functions of the processor 11 may be implemented by any arithmetic entity that can communicate via a network.

[0038] The storage unit 12 includes, for example, any storage module such as an HDD (Hard Disk Drive), SSD (Solid State Drive), ROM (Read-Only Memory), and RAM (Random Access Memory). The storage unit 12 may function as, for example, main memory, auxiliary memory, or cache memory. The storage unit 12 stores any information used in the operation of the control processing unit 10. For example, the storage unit 12 may store system programs, application programs, and various information received by the light receiving unit 30. For example, the storage unit 12 may store BGS and BFS. The storage unit 12 is not limited to one built into the control processing unit 10, but may be an external database or an external storage module.

[0039] The input unit 13 includes one or more input interfaces that receive user input operations and acquire input information based on user operations. For example, the input unit 13 may be, but is not limited to, physical keys, capacitive keys, a pointing device, a touchscreen integrated with the display of the output unit 14, or a microphone that accepts voice input.

[0040] The output unit 14 includes one or more output interfaces that output information to the user and notify the user. For example, the output unit 14 is a display that outputs information as an image, or a speaker that outputs information as sound, but is not limited to these. Such a display may be, for example, a liquid crystal panel display or an organic EL (Electro Luminescence) display. At least one of the above-mentioned input unit 13 and output unit 14 may be configured integrally with the control processing unit 10, or may be provided as a separate unit.

[0041] The functions of the control processing unit 10 can be realized by executing a computer program (program) according to this embodiment on the processor 11. In other words, the functions of the control processing unit 10 can be realized by software. The computer program causes the computer to execute the processing of the steps included in the operation of the control processing unit 10, thereby realizing the functions corresponding to the processing of each step on the computer. In other words, the computer program is a program that causes the computer to function as the control processing unit 10 according to this embodiment. The computer program may be recorded on a recording medium that can be read by the computer. The program includes information used for processing by an electronic computer that is equivalent to a program. For example, data that is not a direct instruction to the computer but has the nature of defining the processing of the computer falls under the category of "information equivalent to a program".

[0042] Some or all of the functions of the control processing unit 10 may be implemented by dedicated circuits included in the processor 11. In other words, some or all of the functions of the control processing unit 10 may be implemented by hardware. Furthermore, the control processing unit 10 may be implemented by a single computer or by the cooperation of multiple computers.

[0043] (Example of operation of measuring device 1) Next, an example of the operation of the measuring device 1 will be described. First, laser light emitted from both the probe light generation unit 21 and the pump light generation unit 22 included in the light source unit 20 is incident on the FUT 50 from both ends in both directions.

[0044] Within the FUT50, Brillouin scattering occurs due to the interaction of probe light and pump light. The generated Brillouin scattered light travels through the FUT50 and reaches the optical circulator 40. The optical circulator 40 is an element that selects the direction of light propagation. The optical circulator 40 guides the light received from the pump light generation unit 22 towards the FUT50. The optical circulator 40 also guides the light received from the direction of the FUT50 towards the photodetector 31.

[0045] Brillouin scattered light from the direction of FUT50 is incident on the photodetector 31 and converted into an electrical signal. The converted electrical signal is input to the light receiving circuit 32, where it is amplified, A / D converted, and filtered before being input to the control processing unit 10.

[0046] The control processing unit 10 acquires the BGS based on the signal input from the light receiving circuit 32. Subsequently, the control processing unit 10 calculates the BFS from the obtained BGS. Here, the BGS obtained by the control processing unit 10 is a waveform with superimposed noise due to the influence of disturbances and noise latent in electrical circuits, etc. Therefore, in order to improve measurement accuracy, the control processing unit 10 calculates the BFS by averaging using multiple BGSs. However, the control processing unit 10 does not have to perform averaging.

[0047] The measuring device 1 according to this embodiment measures BFS with higher accuracy by using a more appropriate averaging process based on the noise conditions in the FUT 50 and electrical circuits, etc. Therefore, the measuring device 1 can measure the distribution of physical quantities such as temperature and strain with higher accuracy.

[0048] The BFS calculation process using the first averaging method of the measuring device 1 will be explained with reference to Figures 2 and 3. Figure 2 is a flowchart showing an example of the operation of the measuring device 1. Figure 3 is a schematic diagram showing an example of the process for calculating the average BFS using the first averaging method. The first averaging method is a procedure in which multiple acquired BGSs are first averaged before calculating the BFS. That is, the first averaging method is a method in which multiple BGSs are first averaged to calculate the averaged BGS, and the average BFS is obtained from the averaged BGS.

[0049] The operation of the measuring device 1, as described with reference to Figure 2, may correspond to one of the control methods for the measuring device 1. The operation of each step in Figure 2 may be performed based on control by the processor 11 of the measuring device 1.

[0050] In step S1, the processor 11 acquires N BGS waveforms 61 (see Figure 3), where N is any integer greater than or equal to 2. In Figure 3, the horizontal axis of the BGS waveform 61 represents frequency, and the vertical axis represents signal strength.

[0051] In step S2, the processor 11 calculates an averaged BGS 62 (see Figure 3) by adding up the points of the N BGS waveforms 61. Specifically, the processor 11 calculates the sum of the signal strengths of the N BGS waveforms 61 for each frequency, and calculates the average BGS value for that frequency by dividing that sum by N. The processor 11 calculates the averaged BGS 62 by performing such calculations over the entire frequency range.

[0052] In step S3, the processor 11 detects the peak of the generated averaged BGS62 and calculates the frequency of that peak as the averaged BFS63. Specifically, the processor 11 may approximate the waveform in a certain range around the peak of the averaged BGS62 (for example, around 0.1 of the bandwidth) with a multidimensional curve (for example, a two-dimensional curve), and calculate the frequency corresponding to the peak of that multidimensional curve as the averaged BFS63. As shown in the graph of averaged BGS62 in Figure 3, if the averaged BGS62 contains noise, detecting the maximum value of the signal strength as the peak may result in an inability to calculate the averaged BFS63 with sufficient accuracy. By regressing the area around the peak of the averaged BGS62 with a multidimensional curve to determine the peak, the processor 11 can cancel out the noise and calculate the averaged BFS63 with high accuracy, even if the averaged BGS62 contains noise.

[0053] In step S4, the processor 11 outputs the average BFS63 obtained in step S3. The processor 11 may, for example, output the average BFS63 to the memory unit 12 for storage, or display the average BFS63 on the display unit 14. After completing the processing in step S4, the processor 11 terminates the processing shown in the flowchart in Figure 2.

[0054] The control processing unit 10 may convert the acquired average BFS 63 into physical quantities such as temperature and strain and display them on the display unit of the output unit 14.

[0055] The BFS calculation process using the second averaging method of the measuring device 1 will be explained with reference to Figures 4 and 5. Figure 4 is a flowchart showing an example of the operation of the measuring device 1. Figure 5 is a schematic diagram showing an example of the process for calculating the average BFS using the second averaging method. The second averaging method is a method in which a process is performed to acquire BFS for each of multiple BGSs, and the acquired BFSs are averaged to obtain the average BFS.

[0056] The operation of the measuring device 1, as described with reference to Figure 4, may correspond to one of the control methods for the measuring device 1. The operation of each step in Figure 4 may be performed based on control by the processor 11 of the measuring device 1.

[0057] In step S11, the processor 11 acquires one BGS waveform 71 (see Figure 5).

[0058] In step S12, the processor 11 detects the peak of the BGS waveform 71 acquired in step S11 and calculates the BFS 72 (see Figure 5). The processor 11 may also calculate the BFS 72 based on a regression curve near the peak of the BGS waveform 71, similar to step S3 in Figure 2.

[0059] The processor 11 performs the processing in steps S11 and S12 for each of the N BGSs.

[0060] In step S13, the processor 11 determines whether or not N BFS72s have been obtained through the processing up to step S12. If N BFS72s have been obtained (YES in step S13), the processor 11 proceeds to step S14; otherwise (NO in step S13), it returns to step S11 and repeats the processing for the other BGS waveforms 71.

[0061] In this way, once the processor 11 acquires one BGS, it immediately detects the peak of the BGS and calculates the BFS72. The processor 11 repeats this N times to acquire N BFS72s.

[0062] In step S14, the processor 11 calculates the average BFS73 by adding up the N BFS72 values.

[0063] In step S15, the processor 11 outputs the average BFS73 obtained in step S14. The processing in step S15 is performed in the same way as in step S4 in Figure 2. After completing the processing in step S15, the processor 11 terminates the processing shown in the flowchart in Figure 4.

[0064] The control processing unit 10 may convert the acquired average BFS 73 into physical quantities such as temperature and strain and display them on the display unit of the output unit 14.

[0065] The first averaging method and the second averaging method differ in terms of memory usage, measurement speed, and measurement accuracy.

[0066] Regarding memory usage and measurement speed, the measured BGS is a one-dimensional array of data representing the signal level for each frequency. The number of elements in the one-dimensional array representing the BGS is determined by the frequency measurement range and frequency resolution. For example, if the measurement range is 1 GHz (10.5 GHz to 11.5 GHz) and the frequency resolution is 200 kHz, the number of elements will be 5001. For example, let's assume the number of averaging iterations N is 1000.

[0067] In this case, the first averaging method requires memory for 5,001 points × 1,000 times = 5,001,000 points per measurement. This requires allocating a very large amount of memory, which can affect other processes. Therefore, this method may slow down the overall processing speed of the software and reduce the measurement speed.

[0068] On the other hand, in the second averaging method, under the same conditions (5001 BGS points, N averaging cycles), the BFS is calculated from the BGS waveform first, so memory is released once the BFS is calculated. Therefore, the memory required to calculate one averaged BFS is only 1000 points' worth to store 1000 (=N) BFSs, saving 5,000,000 points' worth of memory. This is expected to improve the software's operating speed, thus improving the measurement speed per point.

[0069] In the second averaging method, if the control processing unit 10 receives the next BGS waveform while calculating the BFS from a given BGS waveform, it may store the next BGS waveform in the storage unit 12. In other words, the control processing unit 10 may perform the process of calculating the BFS from each BGS waveform and the process of acquiring BGS waveforms in parallel. In this case, the amount of memory required in the second averaging method will be larger.

[0070] Regarding measurement speed, it was found that the measurement accuracy of BFS differs between the first averaging method and the second averaging method depending on conditions such as noise in FUT50 and electrical circuits. The measurement accuracy of BFS in the first averaging method and the second averaging method will be explained with reference to Figures 6 to 12.

[0071] Figures 6 to 9 are scatter plots showing examples of the distribution of average BFS for each averaging method. Figures 6 to 9 all show experimental results from experiments where average BFS was obtained using a real optical fiber as FUT50. In each of Figures 6 to 9, the horizontal axis represents the number of trials (1st, 2nd, ...) in which the average BFS was calculated. The vertical axis represents the average BFS value. Plot 81 shows the average BFS measured using the first averaging method. Plot 82 shows the average BFS measured using the second averaging method.

[0072] Figure 6 shows the distribution of average BFS measured under the conditions that the noise level in FUT50 and electrical circuits is A1, and the number of BGS samples used to calculate one average BFS is N1. Figure 7 shows the distribution of average BFS measured under the conditions that the noise level is A1, and the number of samples used to calculate one average BFS is N2. Figure 8 shows the distribution of average BFS measured under the conditions that the noise level is A2, and the number of samples used to calculate one average BFS is N1. Figure 9 shows the distribution of average BFS measured under the conditions that the noise level is A2, and the number of samples used to calculate one average BFS is N2. Here, N1 <N2、A1<A2である。

[0073] Figure 10 is a histogram showing an example of the distribution of mean BFS calculated using the first averaging method. Figure 11 is a histogram showing an example of the distribution of mean BFS calculated using the second averaging method. Both Figures 10 and 11 show the frequency distribution of mean BFS shown in Figure 9 for each frequency. In Figures 10 and 11, the horizontal axis represents frequency, and the vertical axis represents frequency. Graph 91 in Figure 10 shows the frequency of mean BFS obtained using the first averaging method. Graph 92 in Figure 11 shows the frequency of mean BFS obtained using the second averaging method.

[0074] Thus, in all cases from Figures 6 to 9, the variability (standard deviation) of the mean BFS obtained by the second averaging method was smaller than that of the mean BFS obtained by the first averaging method. As shown in Figures 10 and 11, when the BGS noise is small, the distribution of the mean BFS obtained by the first averaging method shows a shape that deviates from a normal distribution. Based on these findings, it appears that averaging by the second averaging method can obtain the mean BFS with higher accuracy.

[0075] On the other hand, when the noise in FUT50 and the electrical circuit was varied, simulation results were obtained suggesting that, depending on the noise level, the first averaging method could obtain the average BFS with higher accuracy than the second averaging method. Figure 12 shows the relationship between the noise level and the standard deviation of the average BFS.

[0076] In Figure 12, the horizontal axis represents the additional noise level, and the vertical axis represents the variability (standard deviation σ) of the average BFS. Graph 101 shows the relationship between the variability of the average BFS calculated by the first averaging method and the noise. Graph 102 shows the relationship between the variability of the average BFS calculated by the second averaging method and the noise. As shown in Figure 12, in the range where the noise level is less than A0, the variability of the average BFS obtained by the second averaging method is smaller and more accurate than that of the first averaging method. In the range where the noise level is greater than A0, the average BFS obtained by the first averaging method is more accurate than that obtained by the second averaging method.

[0077] As described above, the measurement accuracy of the first averaging method and the second averaging method varies depending on the characteristics of the noise in FUT50 and the electrical circuit, etc. Therefore, the measuring device 1 may actually measure the noise in FUT50 and the electrical circuit, etc., and determine the averaging method according to the measurement results. This operation will be explained with reference to Figure 13.

[0078] Figure 13 is a flowchart illustrating an example of the operation of the measuring device 1. The operation of the measuring device 1 described with reference to Figure 13 may correspond to one of the control methods for the measuring device 1. The operation of each step in Figure 13 may be performed based on control by the processor 11 of the measuring device 1.

[0079] In step S21, the processor 11 acquires noise information from the FUT 50 and electrical circuits, etc. Specifically, the measuring device 1 may emit probe light or pump light to the FUT 50, analyze the signal waveform detected by the light receiving unit 30 accordingly, calculate the magnitude of the noise, and acquire noise information.

[0080] In step S22, the processor 11 determines a recommended averaging method based on the noise information acquired in step S21. For example, the measuring device 1 may pre-store the relationship between the noise information and the measurement accuracy (e.g., the standard deviation of the mean BFS) as described with reference to Figures 6 to 12 for each averaging method, and by referring to such relationships, determine the averaging method with higher measurement accuracy as the recommended averaging method.

[0081] Alternatively, for example, the measuring device 1 may predict the measurement accuracy of the average BFS by inputting the measurement conditions at the time of measurement into a prediction model that has been acquired in advance for each averaging method by machine learning, with the measurement conditions of the average BFS as the explanatory variable and the standard deviation of the average BFS as the dependent variable. Such measurement conditions of the average BFS may include, for example, noise information, the frequencies of the probe light and pump light in the light source unit 20, the sampling frequency and quantization level in the light receiving unit 30, and the type of FUT 50. The processor 11 may use such a prediction model to predict the measurement accuracy of the average BFS for each averaging method and determine the averaging method with higher measurement accuracy as the recommended averaging method.

[0082] In step S23, the processor 11 displays the recommended averaging method determined in step S22 on a display unit such as the output unit 14. Then, the processor 11 accepts the user's selection of one of several averaging methods (first averaging method, second averaging method). When accepting the selection of an averaging method, the processor 11 may also display the predicted value of the measurement accuracy of the average BFS calculated in step S22 for each averaging method. This allows the user to select an averaging method while considering the predicted value of the measurement accuracy of the average BFS.

[0083] In step S24, the processor 11 calculates the average BFS using the averaging method selected in step S23. For example, if the first averaging method is selected, the processor 11 may calculate the average BFS by executing the processes in steps S1 to S3 of Figure 2. If the second averaging method is selected, the processor 11 may calculate the average BFS by executing the processes in steps S11 to S14 of Figure 4.

[0084] In step S25, the processor 11 outputs the average BFS calculated in step S15. The processing in step S25 is performed in the same way as in step S4 in Figure 2. After completing the processing in step S25, the processor 11 terminates the processing shown in the flowchart in Figure 13.

[0085] The control processing unit 10 may convert the acquired average BFS into physical quantities such as temperature and strain and display them on the display unit of the output unit 14.

[0086] As described above, the measuring device 1 comprises a probe light generation unit 21, a pump light generation unit 22, a light receiving unit 30, and a processor 11. The probe light generation unit 21 generates probe light as the first light. The pump light generation unit 22 generates pump light as the second light, which has a different frequency from the probe light. The light receiving unit 30 directs the probe light into the first end of the optical fiber FUT 50, which is the optical fiber to be measured, and the pump light is directed into the second end of the FUT 50, generating scattered light, which is the third light, and converts it into an electrical signal. The processor 11 determines the peak frequency for each of the multiple waveforms of the third light converted into an electrical signal, calculates the average value of the determined peak frequencies, and calculates the frequency shift of the third light. The processor 11 outputs the calculated frequency shift of the third light.

[0087] Thus, instead of first averaging the waveforms of the third light, the measuring device 1 first determines the peak frequency of each of the multiple waveforms of the third light converted into electrical signals, and then calculates the frequency shift of the third light by averaging the determined peak frequencies. Therefore, the frequency shift of the third light can be measured with high accuracy. Thus, the measuring device 1 can improve the measurement accuracy of the physical quantity distribution.

[0088] Furthermore, the light receiving unit 30 may convert the scattered light, specifically the Brillouin scattered light, into an electrical signal as a third light. Therefore, the measuring device 1 can achieve high-precision measurement of physical quantities based on Brillouin scattered light.

[0089] Furthermore, the measuring device 1 may be capable of executing both the first averaging method and the second averaging method. The first averaging method calculates an averaged waveform by averaging multiple waveforms of the third light converted into electrical signals, and calculates the frequency shift of the third light by calculating the peak frequency of the averaged waveform. The second averaging method determines the peak frequency for each of the multiple waveforms of the third light converted into electrical signals, calculates the average value of the determined peak frequencies, and calculates the frequency shift of the third light. The processor 11 may calculate the frequency shift of the third light using either the first averaging method or the second averaging method and output the calculated frequency shift of the third light. In this way, since the measuring device 1 calculates and outputs the frequency shift of the third light using any of the multiple averaging methods, it is possible to calculate the frequency shift of the third light calculated using the appropriate averaging method depending on the situation.

[0090] Furthermore, the processor 11 may accept a selection from the user for either the first averaging method or the second averaging method. The processor 11 may calculate the frequency shift of the third light using the method selected by the user from the first averaging method and the second averaging method. The processor 11 may output the frequency shift of the third light calculated using the method selected by the user. In this way, since the measuring device 1 calculates the frequency shift of the third light using the averaging method selected by the user, the user can measure the frequency shift of the third light with high accuracy using the desired averaging method.

[0091] Furthermore, the processor 11 may acquire noise information indicating the magnitude of noise contained in the third light converted into an electrical signal. Based on the noise information, the processor 11 may determine a recommended averaging method. The processor 11 may calculate the frequency shift of the third light using the determined recommended averaging method. The processor 11 may output the frequency shift of the third light calculated using the recommended averaging method. In this way, the measuring device 1 determines a recommended averaging method based on the noise information and calculates the frequency shift of the third light using that averaging method, so it can measure the frequency shift of the third light with high accuracy depending on the noise conditions.

[0092] The processor 11 may, after presenting the user with a recommended averaging method determined based on noise information, accept the user's selection of either the first averaging method or the second averaging method. The processor 11 may also calculate and output the frequency shift of the third light using the method selected by the user from the first averaging method and the second averaging method.

[0093] Furthermore, the processor 11 may refer to the relationship between the previously acquired noise magnitude and the variation in the frequency shift of the third light, and determine the averaging method that results in a smaller variation in the frequency shift of the third light as the recommended averaging method. Therefore, the measuring device 1 can determine a more appropriate averaging method based on the noise information.

[0094] Furthermore, the processor 11 may predict the measurement accuracy of the frequency shift of the third light by inputting the measurement conditions during measurement, including noise information, into a prediction model that has been acquired in advance for each averaging method using machine learning, with the measurement conditions of the frequency shift of the third light as the explanatory variable and the standard deviation of the frequency shift of the third light as the dependent variable. The processor 11 may also determine the averaging method that yields higher measurement accuracy of the frequency shift of the third light as the recommended averaging method. In this way, the measuring device 1 can determine an even more appropriate averaging method by predicting the measurement accuracy for each averaging method using a prediction model that has been machine-learned based on various measurement conditions, not just noise information.

[0095] Furthermore, the processor 11 may determine the peak frequency for each of the multiple waveforms of the third light acquired sequentially over time, and calculate the frequency shift of the third light by calculating the moving average of the determined peak frequencies as the average value. The processor 11 may also output the calculated frequency shift of the third light. In this way, the measuring device 1 can accurately measure the frequency shift of the third light that reflects the most recent state of FUT50 by calculating the moving average of the peak frequencies as the average value.

[0096] Furthermore, the processor 11 may determine the peak frequency for each of the multiple waveforms of the third light acquired sequentially over time, and calculate the frequency shift of the third light by calculating a weighted average of the determined peak frequencies, multiplying the most recently acquired peak frequencies by a larger weight, and using this weighted average as the average value. The processor 11 may also output the calculated frequency shift of the third light. In this way, the measuring device 1 can measure an averaged frequency shift of the third light that better reflects the most recently acquired measurements by calculating a weighted average of the most recently acquired peak frequencies as the average value.

[0097] This disclosure is not limited to the embodiments described above. For example, multiple blocks shown in a block diagram may be combined, or one block may be divided. Multiple steps shown in a flowchart may be performed in parallel or in a different order, depending on the processing capacity of the device performing each step, or as necessary, instead of being performed in chronological order as described. Other modifications are possible without departing from the spirit of this disclosure. [Explanation of symbols]

[0098] 1: Measuring device 10: Control Processing Unit 11: Processor 12: Storage part 13: Input section 14: Output section 20: Light source part 21: Probe light generation unit 22: Pump light generating unit 30: Light receiving part 31: Photodetector 32: Light receiving circuit 32 40: Light Circulator 50:FUT

Claims

1. A first light generation unit that generates the first light, A second light generation unit that generates a second light with a different frequency from the first light, A light receiving unit that receives the first light by incident on the first end of the optical fiber to be measured, and the third light which is scattered light generated by incident on the second end of the optical fiber by incident on the second end of the optical fiber, and converts this into an electrical signal, Processor and Equipped with, The aforementioned processor, The peak frequency of each of the multiple waveforms of the third light converted into an electrical signal is determined, and the average value of the determined peak frequencies is calculated to calculate the frequency shift of the third light. Output the calculated frequency shift of the third light. Measuring device.

2. The measuring device according to claim 1, wherein the light receiving unit converts Brillouin scattered light as the scattered light into an electrical signal as the third light.

3. It is possible to perform a first averaging method which calculates an averaged waveform by averaging multiple waveforms of the third light converted into electrical signals, calculates the peak frequency of the averaged waveform, and calculates the frequency shift of the third light; and a second averaging method which calculates the frequency shift of the third light by determining the peak frequency for each of the multiple waveforms of the third light converted into electrical signals, and calculating the average value of the determined peak frequencies. The aforementioned processor, The frequency shift of the third light is calculated using either the first averaging method or the second averaging method. Output the calculated frequency shift of the third light. The measuring device according to claim 1 or 2.

4. The aforementioned processor, The user selects either the first averaging method or the second averaging method. The frequency shift of the third light is calculated using the method selected by the user from among the first averaging method and the second averaging method. Outputs the frequency shift of the third light calculated by the method selected by the user. The measuring device according to claim 3.

5. The aforementioned processor, Noise information indicating the magnitude of noise contained in the third light converted into an electrical signal is obtained, Based on the aforementioned noise information, a recommended averaging method is determined. The frequency shift of the third light is calculated using the determined recommended averaging method. Outputting the frequency shift of the third light calculated by the recommended averaging method, The measuring device according to claim 3.

6. The aforementioned processor, By referring to the relationship between the previously acquired noise magnitude and the variation in the frequency shift of the third light, an averaging method that results in a smaller variation in the frequency shift of the third light is determined as the recommended averaging method. The measuring device according to claim 5.

7. The aforementioned processor, The measurement conditions during measurement, including the noise information, are input to a prediction model obtained in advance for each averaging method using machine learning, with the measurement conditions of the frequency shift of the third light as the explanatory variable and the variability of the frequency shift of the third light as the dependent variable, in order to predict the measurement accuracy of the frequency shift of the third light. The averaging method that provides higher measurement accuracy for the frequency shift of the third optical element is determined as the recommended averaging method. The measuring device according to claim 5.

8. The aforementioned processor, The peak frequency of each of the multiple waveforms of the third light acquired sequentially over time is determined, and the moving average of the determined peak frequencies is calculated as the average value to calculate the frequency shift of the third light. Output the calculated frequency shift of the third light. The measuring device according to claim 1.

9. The aforementioned processor, The peak frequency of each of the multiple waveforms of the third light acquired sequentially over time is determined, and the frequency shift of the third light is calculated by multiplying the determined peak frequencies by a larger weight for the most recently acquired peak frequencies and calculating a weighted average as the average value. Output the calculated frequency shift of the third light. The measuring device according to claim 1.

10. A first light generation unit that generates the first light, A second light generation unit that generates a second light with a different frequency from the first light, A light receiving unit that receives the first light by incident on the first end of the optical fiber to be measured, and the third light which is scattered light generated by incident on the second end of the optical fiber by incident on the second end of the optical fiber, and converts this into an electrical signal, Processor and A control method for a measuring device comprising, The aforementioned processor, The frequency shift of the third light is calculated by determining the peak frequency of each of the multiple waveforms of the third light converted into an electrical signal, and calculating the average value of the determined peak frequencies. Output the calculated frequency shift of the third light, A control method for a measuring device, including the control method for a measuring device.

11. A first light generation unit that generates the first light, A second light generation unit that generates a second light with a different frequency from the first light, A light receiving unit that receives the first light by incident on the first end of the optical fiber to be measured, and the third light which is scattered light generated by incident on the second end of the optical fiber by incident on the second end of the optical fiber, and converts this into an electrical signal, Processor and A program for controlling the operation of a measuring device equipped with the following: The aforementioned processor, A procedure for determining the peak frequency of each of the multiple waveforms of the third light converted into an electrical signal, and calculating the average value of the determined peak frequencies to calculate the frequency shift of the third light, A procedure for outputting the calculated frequency shift of the third light, A program that executes the command.

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