Information processing device, information processing method, and program

Abstract

Provided is an information processing device comprising: an acquisition unit that acquires information indicating a waveform observed by an optical fiber sensor; a determination unit that determines a threshold value for the amplitude of the waveform; and an output unit that outputs warning information when the amplitude of the waveform is equal to or greater than the threshold value determined by the determination unit.

Description

Information processing device, information processing method, and program

[0001] The present disclosure relates to an information processing device, an information processing method, and a program.

[0002] Japanese Patent Application Laid-Open No. 2003-144999 discloses a technique for setting a threshold value that follows fluctuations in the input level caused by environmental changes or the like in a detection switch that discriminates the input level.

[0003] Japanese Patent Application Publication No. 09-284117

[0004] However, the technology described in Patent Document 1 does not consider, for example, the case where an abnormality alarm is issued based on an optical fiber sensor.

[0005] In view of the above-mentioned problems, an object of the present disclosure is to provide a technology that can appropriately issue an abnormality warning based on an optical fiber sensor.

[0006] In a first aspect of the present disclosure, an information processing device is provided that has an acquisition unit that acquires information indicating a waveform observed by an optical fiber sensor, a determination unit that determines a threshold value for the amplitude of the waveform, and an output unit that outputs warning information when the amplitude of the waveform is equal to or greater than the threshold value determined by the determination unit.

[0007] In addition, a second aspect of the present disclosure provides an information processing method that acquires information indicating a waveform observed by an optical fiber sensor, determines a threshold value for the amplitude of the waveform, and outputs warning information if the amplitude of the waveform is equal to or greater than the determined threshold value.

[0008] In addition, a third aspect of the present disclosure provides a program for causing a computer to execute a process of acquiring information indicating a waveform observed by an optical fiber sensor, determining a threshold value for the amplitude of the waveform, and outputting warning information if the amplitude of the waveform is equal to or greater than the determined threshold value.

[0009] According to one aspect, an abnormality alarm can be issued appropriately based on an optical fiber sensor.

[0010] 1 is a diagram illustrating an example of the configuration of an information processing device according to an embodiment; FIG. 2 is a diagram illustrating an example of the configuration of a detection system according to an embodiment; FIG. 3 is a diagram illustrating an example of the hardware configuration of an information processing device according to an embodiment; FIG. 4 is a flowchart illustrating an example of processing of an information processing device according to an embodiment; FIG. 5 is a diagram illustrating an example of the amplitude of a waveform observed by an optical fiber sensor according to an embodiment; FIG. 6 is a diagram illustrating an example of the value of α(z) for each value of z according to an embodiment; FIG. 7 is a diagram illustrating an example of each periodic wave for explaining a DMD according to an embodiment; FIG. 8 is a diagram illustrating an example of a wave obtained by combining each periodic wave for explaining a DMD according to an embodiment; FIG. 9 is a diagram illustrating an example of each eigenvalue of a DMD according to an embodiment; and FIG. 10 is a diagram illustrating an example of time evolution of each eigenvalue of a DMD according to an embodiment.

[0011] The principles of the present disclosure will be described with reference to some exemplary embodiments. It should be understood that these embodiments are set forth for illustrative purposes only, to aid those skilled in the art in understanding and practicing the present disclosure, without implying any limitation on the scope of the disclosure. The disclosure described herein may be implemented in various ways other than those described below.

[0012] In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0013] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that each drawing is merely an example for describing one or more embodiments. Each drawing is not related to only one particular embodiment, but may also be related to one or more other embodiments. As will be understood by those skilled in the art, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings to create, for example, an embodiment not explicitly shown or described. Not all features or steps shown in any one drawing are necessarily required to describe an exemplary embodiment, and some features or steps may be omitted. The order of steps described in any drawing may be changed as appropriate.

[0014] (First Embodiment) <Configuration> The configuration of an information processing device 10 according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of the information processing device 10 according to an embodiment. The information processing device 10 has an acquisition unit 11, a determination unit 12, and an output unit 13. Each of these units may be realized by cooperation between one or more programs installed in the information processing device 10 and hardware such as a processor 101 and a memory 102 of the information processing device 10.

[0015] The acquisition unit 11 acquires information indicating a waveform observed by the optical fiber sensor. The determination unit 12 determines a threshold value for the amplitude of the waveform observed by the optical fiber sensor. The output unit 13 outputs warning information when the amplitude of the waveform observed by the optical fiber sensor is equal to or greater than the threshold value determined by the determination unit 12.

[0016] (Embodiment 2) Next, the configuration of a detection system 1 according to an embodiment will be described with reference to Fig. 2. <System Configuration> Fig. 2 is a diagram showing an example configuration of a detection system 1 according to an embodiment. In the example of Fig. 2, the detection system 1 has an information processing device 10 and an optical fiber sensor 20. Note that the number of information processing devices 10 and optical fiber sensors 20 is not limited to the example of Fig. 2. Note that the technology disclosed herein can be used for monitoring various facilities such as substations, plants, factories, offices, and logistics warehouses, for example.

[0017] 2, the information processing device 10 and the optical fiber sensor 20 are connected to each other so as to be able to communicate with each other via a network N. Examples of the network N include the Internet, a mobile communication system, a wireless local area network (LAN), a short-range wireless communication such as BLE, a LAN, and a bus. Examples of the mobile communication system include a fifth-generation mobile communication system (5G), a fourth-generation mobile communication system (4G), a third-generation mobile communication system (3G), and the like.

[0018] The information processing device 10 may be, for example, a server, a cloud, a personal computer, a smartphone, or the like. The information processing device 10 provides, for example, detection of an intruder climbing over a fence and entering a facility, and detection of abnormalities in various pieces of equipment installed in the facility.

[0019] In the example of Fig. 2, the optical fiber cable of the optical fiber sensor 20 is laid on the surface of a fence that is installed along the perimeter of the site of the facility. Note that the laying position of the optical fiber cable of the optical fiber sensor 20 is not limited to the example of Fig. 2.

[0020] The optical fiber sensor 20 has an optical fiber cable 21, which is an information transmission medium. The optical fiber sensor 20 also has a sensing device 22 connected to one end of the optical fiber cable 21, and a termination device 23 connected to the other end of the optical fiber cable 21. The termination device 23 is a device that performs termination processing to suppress reflection of the sensing signal output from the sensing device 22.

[0021] The sensing device 22 outputs a pulse wave sensing signal to the optical fiber cable 21. The sensing device 22 then measures, in time series, reflected signals (returned light) in response to the sensing signal from all positions on the optical fiber cable 21. Note that when vibration or sound is applied to the optical fiber cable 21, or when the temperature changes, the intensity and phase of the returned light change. The sensing device 22 calculates the position in the optical fiber cable 21 where the vibration or sound was applied, based on the round-trip time from when the sensing signal is output until the returned light with changed intensity and phase is observed.

[0022] The sensing device 22 simultaneously measures the vibration and sound applied at multiple points spaced apart by a predetermined distance (e.g., 1 m). Furthermore, by outputting a sensing signal at a time interval such that the return light from the farthest end of the optical fiber cable 21 and the light of the next sensing signal to be output are no longer mixed, it is possible to measure the change over time (time transition) of the vibration and sound applied at each point. Furthermore, the optical fiber cable 21 may be installed at different heights at each point. This allows the three-dimensional location of the abnormality to be estimated.

[0023] By using the optical fiber sensor 20, installation work is easier than when using, for example, multiple microphones or multiple vibration sensors. Furthermore, if an optical fiber cable 21 for communication has already been installed, the optical fiber cable 21 can be used for both communication and facility maintenance, eliminating the need for new installation work. Furthermore, because no electricity flows through the optical fiber cable 21, it can be used in facilities where flammable gases may be present.

[0024] <Hardware Configuration> Fig. 3 is a diagram showing an example of the hardware configuration of the information processing device 10 according to the embodiment. In the example of Fig. 3, the information processing device 10 (computer 100) includes a processor 101, a memory 102, and a communication interface 103. These components may be connected via a bus or the like. The memory 102 stores at least a part of a program 104. The communication interface 103 includes an interface required for communication with other network elements.

[0025] When the program 104 is executed by the processor 101, memory 102, and other components in cooperation with each other, the computer 100 performs at least some of the processing of the embodiments of the present disclosure. The memory 102 may be of any type suitable for a local technology network. The memory 102 may be, by way of non-limiting example, a non-transitory computer-readable storage medium. The memory 102 may also be implemented using any suitable data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and removable memory. While only one memory 102 is shown in the computer 100, several physically distinct memory modules may be present in the computer 100. The processor 101 may be of any type. The processor 101 may include one or more of a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), and, by way of non-limiting example, a processor based on a multi-core processor architecture. The computer 100 may have multiple processors, such as application-specific integrated circuit chips time-slaved to a clock that synchronizes the main processor.

[0026] Embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, logic, or any combination thereof. Some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software that may be executed by a controller, microprocessor, or other computing device.

[0027] The present disclosure also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, that execute on a target real or virtual processor or device to perform the processes or methods of the present disclosure. Program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or divided among program modules as desired in various embodiments. The machine-executable instructions of the program modules may be executed in local or distributed devices. In a distributed device, the program modules may be located in both local and remote storage media.

[0028] The program code for executing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus. When the program code is executed by the processor or controller, the functions / acts in the flowcharts and / or implementing block diagrams are performed. The program code may be executed entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine, or entirely on a remote machine or server.

[0029] The program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The program may be stored on a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable media or tangible storage media include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disc (DVD), Blu-ray disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals.

[0030] <Processing> Next, an example of processing of the information processing device 10 according to the embodiment will be described with reference to FIGS. 4 to 10 . FIG. 4 is a flowchart illustrating an example of processing of the information processing device 10 according to the embodiment. FIG. 5 is a diagram illustrating an example of the amplitude of a waveform observed by the optical fiber sensor 20 according to the embodiment. FIG. 6 is a diagram illustrating an example of the value of α(z) for each value of z according to the embodiment. FIG. 7 is a diagram illustrating an example of each periodic wave for explaining the DMD according to the embodiment. FIG. 8 is a diagram illustrating an example of a wave obtained by combining each periodic wave for explaining the DMD according to the embodiment. FIG. 9 is a diagram illustrating an example of each eigenvalue of the DMD according to the embodiment. FIG. 10 is a diagram illustrating an example of the time evolution of each eigenvalue of the DMD according to the embodiment. Note that the processing of FIG. 4 may be executed, for example, periodically.

[0031] In step S101, the acquiring unit 11 acquires information indicating a waveform observed by the optical fiber sensor 20. Here, the acquiring unit 11 may acquire the amplitude of the waveform observed by the optical fiber sensor 20 at each time point i (i is an integer from 1 to n) measured at a specific sampling interval. Hereinafter, the value of the amplitude of the waveform observed by the optical fiber sensor 20 at each time point i measured at a specific sampling interval will also be referred to as a vector y, as appropriate.

[0032] 5 shows an example of the amplitude 501 of a waveform observed by the optical fiber sensor 20 according to the embodiment. Note that the example of FIG. 5 shows that the amplitude 501 exceeds the specific value TH during a period when, for example, a strong wind is blowing.

[0033] Next, the determination unit 12 determines a threshold value for the amplitude of the waveform observed by the optical fiber sensor 20 (step S102).

[0034] (Example of determining threshold value based on moving averages of multiple intervals) The determination unit 12 may determine a threshold value based on moving averages of multiple intervals. In this case, the determination unit 12 may determine the threshold value Th by, for example, the following formulas (1) and (2). Here, TH is a set value related to the threshold value. The value of TH may be registered in advance in the information processing device 10 by, for example, an operator. Th=α(z)×TH (1) α(z)=1 / (1+e －ｚ ) + 1 / 2 ... (2)

[0035] 6 shows an example of the value 601 of α(z) for each value of z according to the embodiment. According to equation (2), when z=0, Th=TH, and as z increases, Th also increases.

[0036] The determiner 12 may determine the threshold value based on the deviation (variation) of the moving averages of the waveforms observed by the optical fiber sensor 20 over multiple intervals. As a result, the threshold value can be determined to be larger as the deviation increases based on equations (1) to (3). In this case, the determiner 12 may calculate z using the following equation (3):

[0037] where wi is the i-th component of vector w, and w is the average value of all components of vector w. ｊ is the time from the current time to the time observed by the optical fiber sensor 20 ｊ The coefficient c may be set to a larger value as the time length becomes shorter. This allows, for example, observation data closer to the current time to be given more importance. In this case, the determination unit 12 sets the coefficient c to １ ≦c ２ ≦・・・≦c ｎ The determination unit 12 may calculate the vector w using the following equation (4).

[0038] The superscript t indicates transposition. Vector y is the amplitude of the waveform observed by the optical fiber sensor 20 at each time point i (i is an integer from 1 to n) measured at a specific sampling interval. X is expressed by the following equation (5).

[0039] Vector x ｊ (j is an integer between 1 and m) is the moving average of each of the intervals of vector y. For example, vector x １ is the one-minute moving average (the change in the average value every minute), and the vector x ２ is the 10-minute moving average, vector x ３ may be a 30-minute moving average.

[0040] Equation (4) expresses a vector y, which is the amplitude of the waveform observed by the optical fiber sensor 20 at each time point i, as a moving average of each time interval of the vector y, as a vector x ｊ (j is an integer from 1 to m), W shown in the following equation (6) is minimized.

[0041] When the optical fiber cable of the optical fiber sensor 20 is laid on the surface of a fence, the tension of the fence may weaken due to aging or other factors. In this case, the amplitude of the waveform observed by the optical fiber sensor 20 will be sensitive to vibrations caused by external factors such as intermittent wind. Therefore, if an abnormality is determined based on the same threshold as when the fence tension is relatively high, false alarms are likely to occur. On the other hand, the above-mentioned method makes it possible to appropriately determine the threshold for abnormality determination even when the magnitude of the components of vector w varies due to, for example, relatively weak fence tension.

[0042] (Example of determining a threshold based on the waveform of the longest-term (longest period) vibration in dynamic mode decomposition (DMD)) The determination unit 12 may determine a threshold at time t based on the time evolution of the longest-term (longest vibration period) vibration analyzed by DMD.

[0043] In this case, the determiner 12 may determine the threshold value Th using, for example, the following formula (7), (8), or (9). According to formula (7), the threshold value at each time point is determined based on the value at each time point of the time evolution of the longest vibration in the dynamic mode decomposition. According to formula (8), the threshold value is determined based on the value at each time point of the time evolution of the longest vibration in the dynamic mode decomposition and a weighting coefficient for each time point.

[0044] Here, vector m is the time evolution of the longest-term vibration (mode 0) of the DMD of the amplitude of the waveform observed by the optical fiber sensor 20, having components m0, m1, ... mt as shown in the following equation (10). TH is a set value related to the threshold, as described above.

[0045] Th = (m ｔ +β)×TH...(7)

[0046] In addition, the coefficient C ｋ may be calculated by, for example, regression analysis or the like, and may be set in advance in the information processing device 10 by an operator or the like.

[0047] Here, NN(x) represents, for example, inputting an explanatory variable x into a trained model based on machine learning such as deep learning to estimate appropriate coefficients. In this case, the machine learning may be supervised learning using, as training data, data that is a combination of a vector m calculated for each measured waveform and a threshold value set for each waveform by an operator or the like.

[0048] A method for analyzing a mode using a DMD will be described below. Each component of the vector y is expressed as S ０ , S １ , ...S Ｎ The determination unit 12 generates a matrix X expressed by the following equation (10) and a matrix Y expressed by the following equation (11). ...(10) ...(11)

[0049] Assuming that matrix X and matrix Y can be expressed by a linear model of Y = AX, predicting one period ahead (the value at the next sampling point) is |AX - Y| ２ It is known that this is an optimization problem to minimize

[0050] The determination unit 12 determines X=UΣ ｔ When X is subjected to singular value decomposition as in V, the matrix Σ is a matrix in which the eigenvalues ​​of the matrix X are arranged diagonally in descending order of magnitude. The determination unit 12 then determines the effective dimension r from the contribution rate of the diagonal elements of the matrix Σ. Here, the determination unit 12 may extract a specific number r (e.g., 5) of diagonal elements of the matrix Σ in descending order of magnitude, for example.

[0051] Then, the determination unit 12 calculates tilde A according to the following equation (12). ...(12) Here, U ｒ is the matrix obtained by extracting columns 1 to r of matrix U, U ｒ ＊ is U ｒ represents the adjoint matrix of V. ｒ is the matrix obtained by extracting columns 1 to r of matrix V, V ｒ ＊ is V ｒFurthermore, let Σr be the r × r matrix obtained by extracting the 1st to rth rows and the 1st to rth columns of the matrix Σ. Since the matrix V and the matrix Σ are both orthogonal matrices, the following equation (13) holds. ...(13)

[0052] When the eigenvalue matrix of tilde A is Λ and the eigenvector matrix of tilde A is W, the following equation (14) holds. ...(14)

[0053] Here, the eigenvalue matrix Λ is expressed as in the following equation (15). ...(15) And, φ = U ｒ If W is used, then from the above equation (14), Aφ=φΛ. Therefore, φ=ΦΛ ―１ Then, since Aφ=φΛ, AΦΛ ―１ =ΦΛ ―１ Λ=Φ. Therefore, AΦ=ΦA. In other words, are the eigenvectors of A.

[0054] Let the first column of matrix X be X(0), Let's say.

[0055] In this case, time t ｉ = i × Δt, then mode j (eigenvalue λ ｊ The time evolution of the equation (corresponding to ... (16) Furthermore, is.

[0056] Using the time evolution of equation (16), time t ｉ , the k-th time series data in mode j is reconstructed by the following equation (17). ...(17)

[0057] 7 shows an example of each periodic wave for explaining the DMD according to the embodiment. In the example of FIG. 7, examples of the longest-term (longest period) vibration waveform Trend, the second longest-term waveform Periodic#1, the third longest-term waveform Periodic#2, and the noise waveform Noise are shown. The horizontal axis of FIG. 7 represents time, and the vertical axis represents amplitude.

[0058] Fig. 8 shows an example of a wave obtained by combining periodic waves to explain the DMD according to the embodiment. The example of Fig. 8 shows a waveform "Toy data" obtained by combining (adding) the waveforms "Trend," "Periodic#1," "Periodic#2," and "Noise" shown in Fig. 7. The horizontal axis of Fig. 8 represents time, and the vertical axis represents amplitude.

[0059] Fig. 9 shows an example of each eigenvalue of the DMD according to the embodiment. In the example of Fig. 9, each eigenvalue (DMD mode) mode 0 to 4 calculated by the above-mentioned equation (14) for the waveform Toy data of Fig. 8 is shown on a complex plane. Note that the horizontal axis of Fig. 9 represents the real axis, and the vertical axis represents the imaginary axis.

[0060] FIG. 10 shows an example of the time evolution of each eigenvalue of the DMD according to the embodiment. The example of FIG. 10 shows an example of each waveform obtained by evolving the eigenvalues ​​(DMD modes) mode 0 to 4 of FIG. 9 over time using the above-described equation (17). It can be seen that the waveform of mode 0 in FIG. 10 roughly matches the waveform Trend of the longest-term vibration in FIG. 7. It can also be seen that combining the waveforms in FIG. 10 roughly reproduces the waveform Toy data in FIG. 8. By determining a threshold based on the waveform of the longest-term vibration in dynamic mode decomposition, it is possible to determine a threshold for detecting vibrations caused by an intruder or the like, while excluding periodic vibrations (swaying) caused by intermittent strong winds, for example.

[0061] The above-described methods can be used in combination as appropriate. In this case, the determiner 12 may determine, as the threshold, the average value of a threshold based on each moving average over multiple intervals and a threshold based on the waveform of the longest-term vibration (the waveform corresponding to the real eigenvalue) in dynamic mode decomposition.

[0062] Next, the output unit 13 outputs warning information if the amplitude of the waveform observed by the optical fiber sensor 20 is equal to or greater than the threshold determined by the determination unit 12 (step S103). This makes it possible to notify a security center or the like of an abnormality such as an intrusion, for example, based on the shaking of the fence caused by an intruder climbing up the fence.

[0063] <Modifications> The information processing device 10 may be a device contained in a single housing, but the information processing device 10 of the present disclosure is not limited to this. Each unit of the information processing device 10 may be realized, for example, by cloud computing configured with one or more computers. Furthermore, the information processing device 10 and at least a portion of the optical fiber sensor 20 may be housed in the same housing and configured as an integrated information processing device. Such information processing devices 10 are also included in examples of the "information processing device" of the present disclosure.

[0064] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0065] Some or all of the above embodiments may also be described as, but are not limited to, the following supplementary notes. Note that some or all of the elements (e.g., configurations and functions) described in each supplementary note dependent on supplementary note 1 may also be dependent on independent supplementary notes in other categories in a similar dependency relationship. Some or all of the elements described in any supplementary note may be applied to various hardware, software, and recording means, systems, and methods for recording software. (Supplementary note 1) An information processing device comprising: an acquisition unit that acquires information indicating a waveform observed by an optical fiber sensor; a determination unit that determines a threshold for the amplitude of the waveform; and an output unit that outputs warning information when the amplitude of the waveform is equal to or greater than the threshold determined by the determination unit. (Supplementary note 2) The information processing device described in supplementary note 1, wherein the determination unit determines the threshold based on at least one of a moving average of each of a plurality of intervals of the waveform and a waveform of the longest-term vibration in dynamic mode decomposition (DMD). (Supplementary Note 3) The information processing device according to Supplementary Note 2, wherein the determination unit determines the threshold based on a degree of deviation between a moving average of a first interval of the waveform and a moving average of a second interval of the waveform. (Supplementary Note 4) The information processing device according to Supplementary Note 3, wherein the determination unit determines the threshold to a larger value as the degree of deviation increases. (Supplementary Note 5) The information processing device according to Supplementary Note 2, wherein the determination unit determines the threshold based on a time evolution of a longest vibration in the dynamic mode decomposition. (Supplementary Note 6) The information processing device according to Supplementary Note 2, wherein the determination unit determines the threshold at each time point based on a value at each time point of the time evolution of the longest vibration in the dynamic mode decomposition. (Supplementary Note 7) The information processing device according to Supplementary Note 2, wherein the determination unit determines the threshold based on a value at each time point of the time evolution of the longest vibration in the dynamic mode decomposition and a weighting coefficient for each time point. (Supplementary Note 8) The information processing device according to Supplementary Note 2, wherein the determination unit determines the threshold value based on values ​​at each point in time of the time evolution of the longest-term oscillation in the dynamic mode decomposition and a trained model obtained by machine learning.(Supplementary Note 9) An information processing method comprising: acquiring information indicating a waveform observed by an optical fiber sensor; determining a threshold value for the amplitude of the waveform; and outputting warning information if the amplitude of the waveform is equal to or greater than the determined threshold value. (Supplementary Note 10) A program causing a computer to execute the following processes: acquiring information indicating a waveform observed by an optical fiber sensor; determining a threshold value for the amplitude of the waveform; and outputting warning information if the amplitude of the waveform is equal to or greater than the determined threshold value.

[0066] This application claims priority based on Japanese Patent Application No. 2024-016823, filed February 7, 2024, the disclosure of which is incorporated herein in its entirety by reference.

[0067] REFERENCE SIGNS LIST 1 detection system 10 information processing device 11 acquisition unit 12 determination unit 13 output unit 20 optical fiber sensor

Claims

1. An information processing device having: an acquisition unit that acquires information indicating a waveform observed by an optical fiber sensor; a determination unit that determines a threshold value for the amplitude of the waveform; and an output unit that outputs warning information when the amplitude of the waveform is equal to or greater than the threshold value determined by the determination unit.

2. The information processing device according to claim 1, wherein the determination unit determines the threshold value based on at least one of a moving average of each of a plurality of intervals of the waveform and a waveform of the longest-term vibration in dynamic mode decomposition (DMD).

3. The information processing device according to claim 2, wherein the determination unit determines the threshold value based on a degree of deviation between a moving average of a first interval of the waveform and a moving average of a second interval of the waveform.

4. The information processing device according to claim 3, wherein the determination unit determines the threshold to be a larger value as the degree of deviation increases.

5. The information processing device according to claim 2, wherein the determination unit determines the threshold value based on the time evolution of the longest-term oscillation in the dynamic mode decomposition.

6. The information processing device according to claim 2, wherein the determination unit determines the threshold at each time point based on a value at each time point of the time evolution of the longest-term oscillation in the dynamic mode decomposition.

7. The information processing device according to claim 2, wherein the determination unit determines the threshold value based on a value at each point in time of the time evolution of the longest-term oscillation in the dynamic mode decomposition and a weighting coefficient for the value at each point in time.

8. The information processing device according to claim 2, wherein the determination unit determines the threshold value based on values at each point in time of the longest-term time evolution of the oscillation in the dynamic mode decomposition and a trained model obtained by machine learning.

9. An information processing method comprising: acquiring information indicating a waveform observed by an optical fiber sensor; determining a threshold value for the amplitude of the waveform; and outputting warning information if the amplitude of the waveform is equal to or greater than the determined threshold value.

10. A program that causes a computer to execute the following process: acquiring information indicating a waveform observed by an optical fiber sensor; determining a threshold value for the amplitude of the waveform; and outputting warning information if the amplitude of the waveform is equal to or greater than the determined threshold value.

Images