Method, device, equipment, storage medium and computer program for converting das data

Abstract

The present disclosure relates to a distributed optical fiber sensing data conversion method and device, and a computer device, computer readable storage medium and computer program product, the conversion method comprising: obtaining original data of distributed optical fiber sensing; performing first transformation processing on the original data to transform it from phase response to strain response to obtain first data; performing second transformation processing on the first data to transform it from strain response to displacement response to obtain second data; performing third transformation processing on the second data to transform it from displacement response to velocity response to obtain third data; and outputting the third data. The present disclosure gradually transforms the distributed optical fiber sensing data from phase response to velocity response to finally obtain physically corresponding data, thereby realizing effective conversion of DAS data response. Moreover, the converted physically corresponding data is free of direct current noise, and the effect of the converted data is highly consistent with the actual response.

Description

Technical Field

[0001] This disclosure pertains to the application field of fiber optic sensing technology, and specifically relates to a method, device, equipment, storage medium, and computer program for converting distributed fiber optic sensing (DAS) data. Background Technology

[0002] As an emerging and transformative technology, distributed fiber optic sensing technology has developed rapidly in fields such as oil and gas exploration and development, and engineering monitoring, but there are still some problems that urgently need to be solved.

[0003] Due to the differences in fiber demodulation and response mechanisms, DAS records the phase delay between the difference frequency signals formed by scattering points in the fiber before and after strain caused by vibration. This phase delay is equivalent to the strain response. Electronic geophones record the velocity of particles caused by vibration. Strain and velocity can be converted to each other. Studying the conversion relationship between the two, and converting the DAS signal into the velocity or acceleration signal of the electronic geophone, is a prerequisite for subsequent applications of seismic data.

[0004] Currently, the common method for converting this physical response is to directly perform time-differential conversion on the DAS data. However, this is not a true conversion, and the converted data will introduce some DC noise, resulting in a difference between the actual response and the actual response. Summary of the Invention

[0005] Based on the above, the purpose of this disclosure is to propose a method and device for converting distributed optical fiber sensing data, so as to solve the problems that the converted data will introduce certain DC noise and that the effect of the converted data is different from the actual response.

[0006] In a first aspect, this disclosure provides a method for converting distributed optical fiber sensing data, including:

[0007] S1. Acquire raw data from distributed fiber optic sensing;

[0008] S2. Perform a first transformation process on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data;

[0009] S3. Perform a second transformation process on the first data to transform it from strain response to displacement response, and obtain the second data;

[0010] S4. Perform a third transformation process on the second data to transform it from a displacement response to a velocity response, and obtain the third data.

[0011] S5. Output the third data.

[0012] In some embodiments, the first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant inherent to the performance of the demodulation device based on distributed fiber optic sensing data, and is typically available from the device vendor.

[0013] In some embodiments, the second transformation process includes:

[0014] S31. For the first data, at a sampling time t1, select a sampling channel c1, and superimpose the sample values ​​of sampling channel c1 and all the sampling channels before it at sampling time t1 as the value at sample point (t1, c1); wherein, the sampling channels are ordered in order according to their positions in the distributed optical fiber, and here, the sampling channel with a sequence number smaller than c1 is the preceding sampling channel, and the sampling channel with a sequence number larger than c1 is the following sampling channel;

[0015] S32. Following step S31, traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1.

[0016] S33. Following steps S31 and S32, traverse all sampling points at all sampling times on all sampling channels in the sampling channel direction, and calculate the value of each sampling channel at all sampling times.

[0017] S34. On the sample points calculated in step S33, at a sampling time t2, select a sampling channel c2, take the sample point (t2,c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and use the value of the midpoint (t2,c2) minus the calculated median value of the sample points to obtain the new value at the position of the midpoint (t2,c2).

[0018] S35. Following step S34, traverse all sampling channels in the channel direction and calculate the value of the sample point (or midpoint) of each sampling channel at sampling time t2.

[0019] S36. Following steps S34 and S35, iterate through the sample points of each sampling channel at all sampling times and calculate the value of each sampling channel at all sampling times.

[0020] In some embodiments, in step S34, the time window refers to the number of sample points within the time window. The time window is an odd number that is greater than or equal to 10 and less than or equal to 100. The value of the time window can be determined by the experimental results.

[0021] In some embodiments, in step S34, the median value of the sample points within the time window refers to the median value selected after sorting the sample point values ​​within the time window according to their size.

[0022] In some embodiments, the third transformation process includes:

[0023] S41. For the second data, on a sampling channel c3, select a sampling time t3, and use the original value of the sample point (t3,c3) minus the original value of the sample point (t3-1,c3) to obtain the first new value of the sample point (t3,c3), where the value of the sample point (t3=0,c3) is equal to its own original value.

[0024] S42. Following step S41, traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time.

[0025] S43. Following steps S41 and S42, traverse all channels in the channel direction and calculate the first new value of each sampling channel at all sampling times.

[0026] S44. For the sample points calculated in step S43, select a sampling channel c4, and perform a forward Fourier transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where... P = atan(I / R);

[0027] S45. Subtract π from each element of the phase angle sequence P obtained in step S44 to obtain a new phase angle sequence P'.

[0028] S46. Using the new phase angle sequence P' from step S45, calculate the new real part sequence R' and the new imaginary part sequence I', where I' = AcosP' and R' = Asin(P');

[0029] S47. Using the new real part sequence R' and the new imaginary part sequence I' obtained in step S46, perform an inverse Fourier transform to obtain the second new value of all sample points on sampling channel c4;

[0030] S48. Following steps S44 to S47, traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

[0031] Secondly, this disclosure provides a distributed optical fiber sensing data conversion device for implementing the aforementioned distributed optical fiber sensing data conversion method, comprising:

[0032] The acquisition module is used to acquire raw data from distributed fiber optic sensing.

[0033] The first transformation processing module is used to perform a first transformation processing on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data.

[0034] The second transformation processing module is used to perform a second transformation processing on the first data to transform it from a strain response into a displacement response, thereby obtaining the second data.

[0035] The third transformation processing module is used to perform a third transformation processing on the second data to transform it from a displacement response to a velocity response, thereby obtaining the third data.

[0036] The output module is used to output the third data.

[0037] In some embodiments, the first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant determined by the inherent performance of the demodulation device based on distributed fiber optic sensing data, and is typically available from the device vendor.

[0038] In some embodiments, the second transformation process includes:

[0039] S31. For the first data, at a sampling time t1, select a sampling channel c1, and superimpose the sample values ​​of sampling channel c1 and all the preceding channels at sampling time t1 as the value at sample point (t1, c1); wherein, the sampling channels are ordered in sequence according to their positions in the distributed optical fiber, and the sampling channels with a sequence number smaller than c1 are the preceding sampling channels, and the sampling channels with a sequence number larger than c1 are the following sampling channels;

[0040] S32. Following step S31, traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1.

[0041] S33. Following steps S31 and S32, traverse all sample points in the channel direction at all sampling times and calculate the value of each sample point in the channel at all sampling times.

[0042] S34. On the sample points calculated in step S33, at a sampling time t2, select a sampling channel c2, take the sample point (t2,c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and use the value of the midpoint (t2,c2) minus the calculated median value of the sample points to obtain the new value at the position of the midpoint (t2,c2).

[0043] S35. Following step S34, traverse all sampling channels in the channel direction and calculate the value of the sample point for each sampling channel at sampling time t2.

[0044] S36. Following steps S34 and S35, iterate through all sampling points at all sampling times for each sampling channel and calculate the value of each sampling channel at all sampling times.

[0045] In some embodiments, in step S34, the time window refers to the number of sample points within the time window. The time window is an odd number that is greater than or equal to 10 and less than or equal to 100. The value of the time window can be determined by the experimental results.

[0046] In some embodiments, in step S34, the median value of the sample points within the time window refers to the median value selected after sorting the sample point values ​​within the time window according to their size.

[0047] In some embodiments, the third transformation process includes:

[0048] S41. For the second data, on a sampling channel c3, select a sampling time t3, and use the original value of the sample point (t3,c3) minus the original value of the sample point (t3-1,c3) to obtain the first new value of the sample point (t3,c3), where the value of the sample point (t3=0,c3) is equal to its own original value.

[0049] S42. Following step S41, traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time.

[0050] S43. Following steps S41 and S42, traverse all channels in the channel direction and calculate the first new value of each sampling channel at all sampling times.

[0051] S44. For the sample points calculated in step S43, select a sampling channel c4, and perform a forward Fourier transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where... P = atan(I / R);

[0052] S45. Subtract π from each element of the phase angle sequence P obtained in step S44 to obtain a new phase angle sequence P'.

[0053] S46. Using the new phase angle sequence P' from step S45, calculate the new real part sequence R' and the new imaginary part sequence I', where I' = AcosP' and R' = Asin(P');

[0054] S47. Using the new real part sequence R' and the new imaginary part sequence I' obtained in step S46, perform an inverse Fourier transform to obtain the second new value of all sample points on sampling channel c4;

[0055] S48. Following steps S44 to S47, traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

[0056] Thirdly, this disclosure provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method.

[0057] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0058] Fifthly, this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0059] The beneficial effects of this disclosure are as follows:

[0060] Compared with the prior art, the embodiments of this disclosure achieve effective conversion of DAS data response by progressively transforming distributed fiber optic sensing data from phase response to strain response, then to displacement response, and finally to velocity response to obtain the physical response data. Furthermore, the converted physical response data is free of DC noise, and the effect of the converted data highly matches the actual response. Attached Figure Description

[0061] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0062] Figure 1 This is a schematic diagram of an application scenario of the distributed optical fiber sensing data transformation method provided in the embodiments of this disclosure.

[0063] Figure 2 This is a flowchart of a second embodiment of the method for transforming distributed optical fiber sensing data according to the present disclosure.

[0064] Figure 3 A composite image showing the comparison between raw DAS data and electronic detector data.

[0065] Figure 4 This is a comparison chart showing the original DAS data after conversion according to Example 2 and the electronic detector data.

[0066] Figure 5 The image shows a comparison of the waveforms of the DAS raw data before and after conversion according to Example 2, and the waveforms of the electronic detector data.

[0067] Figure 6 This is a simplified structural diagram of a distributed optical fiber sensing data conversion device provided according to an embodiment of the present disclosure.

[0068] Figure 7 This is a schematic diagram of an electronic device provided according to an embodiment of the present disclosure.

[0069] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0070] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0071] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0072] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0073] Example 1

[0074] Figure 1 This is a schematic diagram illustrating an application scenario of an embodiment of this disclosure. The application scenario may include server 4, network 5, and terminal devices.

[0075] The terminal device can be either hardware or software. When the terminal device is hardware, it can be various electronic devices with an LED display screen that support communication with the server 4, including but not limited to smartphones 1, tablets 3, laptops 2, and desktop computers; when the terminal device is software, it can be installed in the aforementioned electronic devices. The terminal device can be implemented as multiple software programs or software modules, or as a single software program or software module; this disclosure does not limit this. Furthermore, various applications can be installed on the terminal device, such as data processing applications, instant messaging tools, social platform software, search applications, shopping applications, etc.

[0076] Server 4 can be a server that provides various services, such as a backend server that receives requests sent by terminal devices with which it has established communication connections. This backend server can receive and analyze the requests sent by the terminal devices and generate processing results. Server 4 can be a single server, a server cluster consisting of several servers, or a cloud computing service center. This disclosure embodiment does not limit this.

[0077] It should be noted that server 4 can be either hardware or software. When server 4 is hardware, it can be any electronic device that provides various services to the terminal device. When server 4 is software, it can implement multiple software programs or software modules that provide various services to the terminal device, or it can implement a single software program or software module that provides various services to the terminal device. This disclosure does not impose any limitations on this aspect.

[0078] Network 5 can be a wired network using coaxial cable, twisted pair, and fiber optic connection, or it can be a wireless network that enables interconnection of various communication devices without wiring, such as Bluetooth, Near Field Communication (NFC), and Infrared. This disclosure does not limit the scope of the embodiments.

[0079] Users can establish a communication connection with server 4 via network 5 through terminal devices to receive or send information, etc.

[0080] Specifically, firstly, server 4 can acquire the raw data from the distributed fiber optic sensing. Secondly, server 4 can perform a first transformation process, converting the raw data from a phase response into a strain response to obtain first data. Thirdly, server 4 can perform a second transformation process, converting the first data from a strain response into a displacement response to obtain second data. Fourthly, server 4 can perform a third transformation process, converting the second data from a displacement response into a velocity response to obtain third data. Finally, server 4 can output the third data.

[0081] It should be noted that the specific types, quantities, and combinations of server 4, network 5, and terminal devices can be adjusted according to the actual needs of the application scenario, and this disclosed embodiment does not impose any restrictions on this.

[0082] Example 2

[0083] Continue to refer to Figure 2 , Figure 2 A flowchart illustrating a method for converting distributed optical fiber sensing data according to an embodiment of this disclosure is shown. This method can be... Figure 1 It is executed by electronic devices within the system. For example... Figure 2 As shown, the method for converting distributed fiber optic sensing data includes:

[0084] S1. Acquire raw data from distributed fiber optic sensing;

[0085] S2. Perform a first transformation process on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data;

[0086] S3. Perform a second transformation process on the first data to transform it from strain response to displacement response, and obtain the second data;

[0087] S4. Perform a third transformation process on the second data to transform it from a displacement response to a velocity response, and obtain the third data.

[0088] S5. Output the third data.

[0089] In some embodiments, the entity performing the conversion method (such as...) Figure 1 The electronic device shown can connect to the target device via a wired or wireless connection, and then acquire the raw data from the distributed fiber optic sensing. The raw data from the distributed fiber optic sensing can refer to the unprocessed data collected by the distributed fiber optic sensing, such as... Figure 2 The data on the left side of the table.

[0090] It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future wireless connection methods.

[0091] In some embodiments, the first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, the strain-phase conversion coefficient being a constant of the inherent performance of the demodulation device based on distributed fiber optic sensing data.

[0092] In some embodiments, the second transformation process includes:

[0093] S31. For the first data, at a sampling time t1, select a sampling channel c1, and superimpose the sample values ​​of sampling channel c1 and all the preceding channels at sampling time t1 as the value at sample point (t1, c1); wherein, the sampling channels are ordered in sequence according to their positions in the distributed optical fiber, and the sampling channels with a sequence number smaller than c1 are the preceding sampling channels, and the sampling channels with a sequence number larger than c1 are the following sampling channels;

[0094] S32. Following step S31, traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1.

[0095] S33. Following steps S31 and S32, traverse all sampling points at all sampling times on all sampling channels in the sampling channel direction, and calculate the value of each sampling channel at all sampling times.

[0096] S34. On the sample points calculated in step S33, at a sampling time t2, select a channel c2, take the sample point (t2, c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and subtract the calculated median value of the sample points from the value of the midpoint (t2, c2) to obtain the new value at the position of the midpoint (t2, c2). The time window refers to the number of sample points within the time window. The time window is an odd number greater than or equal to 10 and less than or equal to 100. The value of the time window can be determined through experimental results.

[0097] S35. Following step S34, traverse all sampling channels in the channel direction and calculate the value of the sample point for each sampling channel at sampling time t2.

[0098] S36. Following steps S34 and S35, iterate through the sample points of each sampling channel at all sampling times and calculate the value of each sampling channel at all sampling times.

[0099] In some embodiments, the third transformation process includes:

[0100] S41. For the second data, on a channel c3, select a sampling time t3, and use the original value of sample point (t3,c3) minus the original value of sample point (t3-1,c3) to obtain the first new value of sample point (t3,c3), where the value of sample point (t3=0,c3) is equal to its own original value.

[0101] S42. Following step S41, traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time.

[0102] S43. Following steps S41 and S42, traverse all first channels in the direction of the first channel and calculate the first new value of each first channel at all sampling times.

[0103] S44. For the sample points calculated in step S43, select a sampling channel c4, and perform a forward Fourier transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where... P = atan(I / R);

[0104] S45. Subtract π from each element of the phase angle sequence P obtained in step S44 to obtain a new phase angle sequence P'.

[0105] S46. Using the new phase angle sequence P' from step S45, calculate the new real part sequence R' and the new imaginary part sequence I', where I' = AcosP' and R' = Asin(P');

[0106] S47. Using the new real part sequence R' and the new imaginary part sequence I' obtained in step S46, perform an inverse Fourier transform to obtain the second new value of all sample points on sampling channel c4;

[0107] S48. Following steps S44 to S47, traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

[0108] The beneficial effects of one of the embodiments described above in this disclosure include at least the following: by progressively transforming the distributed optical fiber sensing data from phase response to strain response, then to displacement response, and finally to velocity response to obtain the physical response data, effective conversion of DAS data response is achieved. Furthermore, the converted physical response data is free of DC noise, and the effect of the converted data highly matches the actual response.

[0109] The present disclosure is illustrated below through a specific embodiment:

[0110] Figure 3 The data on the left side represents the raw DAS data from a particular acquisition. To compare the experimental results, an electronic detector was also used for simultaneous acquisition. The raw data acquired by the electronic detector is shown below. Figure 3 The right side. From Figure 3 As can be seen, since the physical response of the data acquired by the electronic detector is velocity, while the physical response of the data acquired by the DAS is phase, there is a significant difference in polarity between the two at the data splicing point (the part indicated by the arrow).

[0111] Figure 4 The data on the left side is Figure 3The input raw DAS data is processed Figure 2 The third data output after the first, second, and third transformations. Compare this to the previous data. Figure 4 The polarity of the original data from the electronic detector on the right and the polarity of the output DAS data are consistent with those of the electronic detector data, indicating that the physical response of the DAS after transformation is consistent with the physical response of the detector data.

[0112] Figure 5 Is to take Figure 3 and Figure 4 The waveform comparison diagrams of the DAS data before and after conversion and the electronic detector data at the same channel position show that the waveforms of the original DAS data and the electronic detector data have polarity reversal and amplitude differences. After conversion, the waveform and amplitude of the DAS data are basically consistent with the electronic detector data. This further illustrates that after the processing in this embodiment, the purpose of converting DAS data from phase response to velocity response is fully achieved.

[0113] Example 3

[0114] This embodiment describes another implementation of the distributed fiber optic sensor data conversion method according to this disclosure. The distributed fiber optic sensor data conversion method includes:

[0115] S100: Acquire raw data from distributed fiber optic sensing;

[0116] S200. Perform a first transformation process on the original data to transform it from a phase response to a strain response, and obtain first data, including: multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant of the inherent performance of the demodulation device based on distributed optical fiber sensing data;

[0117] S300. Perform a second transformation process on the first data to transform it from a strain response to a displacement response, obtaining second data, including:

[0118] S310. For the first data, at a sampling time t1, select a sampling channel c1, and superimpose the sample values ​​of sampling channel c1 and all the preceding channels at sampling time t1 as the value at sample point (t1, c1); wherein, the sampling channels are ordered in sequence according to their positions in the distributed optical fiber, and here, the sampling channel with a sequence number smaller than c1 is the preceding sampling channel, and the sampling channel with a sequence number larger than c1 is the following sampling channel;

[0119] S320. Following step S310, traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1.

[0120] S330. Following steps S310 and S320, traverse all sampling points on all sampling channels in the sampling channel direction at all sampling times, and calculate the value of each sampling channel at all sampling points at all sampling times.

[0121] S340. On the sample points calculated in step S330, at a sampling time t2, select a sampling channel c2, take the sample point (t2, c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and subtract the calculated median value of the sample points from the value of the midpoint (t2, c2) to obtain the new value at the position of the midpoint (t2, c2); where, the time window refers to the number of sample points within the time window, and the time window is an odd number greater than or equal to 10 and less than or equal to 100. The value of the time window can be determined through experimental results;

[0122] S350. Following step S340, traverse all sampling channels in the channel direction and calculate the value of the sample point for each sampling channel at sampling time t2.

[0123] S360. Following steps S340 and S350, iterate through the sample points of each sampling channel at all sampling times and calculate the value of each sampling channel at all sampling times.

[0124] S400. Perform a third transformation process on the second data to transform it from a displacement response to a velocity response, obtaining third data, including:

[0125] S410. For the second data, on a sampling channel c3, select a sampling time t3, and use the original value of the sample point (t3,c3) minus the original value of the sample point (t3-1,c3) to obtain the first new value of the sample point (t3,c3), where the value of the sample point (t3=0,c3) is equal to its own original value.

[0126] S420. Following step S410, traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time.

[0127] S430. Following steps S410 and S420, traverse all sampling channels in the sampling channel direction and calculate the first new value of each sampling channel at all sampling times.

[0128] S440. For the sample points calculated in step S430, select a sampling channel c4, and perform a forward Fourier transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where... P = atan(I / R);

[0129] S450. Subtract π from each element of the phase angle sequence P obtained in step S440 to obtain a new phase angle sequence P'.

[0130] S460. Calculate the new real part sequence R' and the new imaginary part sequence I' using the new phase angle sequence P' from step S450, where I' = AcosP' and R' = Asin(P');

[0131] S470. Using the new real part sequence R' and the new imaginary part sequence I' obtained in step S460, perform an inverse Fourier transform to obtain the second new values ​​of all samples on channel c4;

[0132] S480. Following steps S440 to S470, traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

[0133] S500, Output the third data.

[0134] In some embodiments, the specific implementation of steps S100 to S500 and the resulting technical effects can be referred to Figure 2 The steps in the corresponding embodiments will not be repeated here.

[0135] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0136] Example 4

[0137] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0138] Further reference Figure 6 As an implementation of the methods described in the above figures, this disclosure provides some embodiments of a distributed optical fiber sensing data conversion device, which are similar to... Figure 2 The above-described method embodiments correspond to these.

[0139] like Figure 6 As shown, the distributed optical fiber sensor data conversion device 11 in some embodiments includes:

[0140] Acquisition module 6 is used to acquire raw data from distributed fiber optic sensing;

[0141] The first transformation processing module 7 is used to perform a first transformation processing on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data.

[0142] The second transformation processing module 8 is used to perform a second transformation processing on the first data to transform it from strain response to displacement response, thereby obtaining the second data.

[0143] The third transformation processing module 9 is used to perform a third transformation processing on the second data to transform it from a displacement response to a velocity response, thereby obtaining the third data.

[0144] Output module 10 is used to output the third data.

[0145] In some embodiments, the first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant determined by the inherent performance of the demodulation device based on distributed fiber optic sensing data.

[0146] In some embodiments, the second transformation process includes:

[0147] (2-1) For the first data, at a sampling time t1, a sampling channel c1 is selected, and the sample values ​​of sampling channel c1 and all the sampling channels before it at sampling time t1 are superimposed as the value at sample point (t1, c1); wherein, the sampling channels are ordered in order according to their positions in the distributed optical fiber, and the sampling channels with a sequence number smaller than c1 are the preceding sampling channels, and the sampling channels with a sequence number larger than c1 are the following sampling channels;

[0148] (2-2) Following step (2-1), traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1;

[0149] (2-3) Following steps (2-1) and (2-2), traverse all sampling points at all sampling times along all sampling channels in the sampling channel direction, and calculate the value of each sampling channel at all sampling times.

[0150] (2-4) On the sample points calculated in step (2-3), at a sampling time t2, select a sampling channel c2, take the sample point (t2,c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and use the value of the midpoint (t2,c2) minus the calculated median value of the sample points to obtain the new value at the position of the midpoint (t2,c2);

[0151] (2-5) Following step (2-4), traverse all sampling channels in the sampling channel direction and calculate the value of the sample point at sampling time t2 for each sampling channel;

[0152] (2-6) Following steps (2-4) and (2-5), iterate through all the sample points at all sampling times for each sampling channel and calculate the value of each sampling channel at all sampling times.

[0153] In some embodiments, in steps (2-4), the time window refers to the number of sample points within the time window. The time window is an odd number greater than or equal to 10 and less than or equal to 100. The value of the time window can be determined by the experimental results.

[0154] In some embodiments, in steps (2-4), the median value of the sample points within the time window refers to the median value selected after sorting the sample point values ​​within the time window according to their size.

[0155] In some embodiments, the third transformation process includes:

[0156] (3-1) For the second data, on a sampling channel c3, select a sampling time t3, and use the original value of the sample point (t3,c3) minus the original value of the sample point (t3-1,c3) to obtain the first new value of the sample point (t3,c3), where the value of the sample point (t3=0,c3) is equal to its own original value.

[0157] (3-2) Following step (3-1), traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time;

[0158] (3-3) Following steps (3-1) and (3-2), traverse all channels in the channel direction and calculate the first new value of each sampling channel at all sampling times;

[0159] (3-4) For the sample points calculated in step (3-3), select a sampling channel c4, and perform a Fourier forward transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where P = atan(I / R);

[0160] (3-5) Subtract π from each element of the phase angle sequence P obtained in step (3-4) to obtain a new phase angle sequence P';

[0161] (3-6) Calculate the new real part sequence R' and the new imaginary part sequence I' using the new phase angle sequence P' from step (3-5), where I' = AcosP' and R' = Asin(P');

[0162] (3-7) Using the new real part sequence R' and the new imaginary part sequence I' obtained in step (3-6), perform an inverse Fourier transform to obtain the second new value of all sample points on sampling channel c4;

[0163] (3-8) Following steps (3-4) to (3-7), traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

[0164] It is understandable that the modules described in the distributed fiber optic sensor data conversion device 11 are similar to those in the reference. Figure 2 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the conversion device 11 and the modules contained therein, and will not be repeated here.

[0165] Example 5

[0166] like Figure 7 As shown, the electronic device 12 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 12-1, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 12-2 or a program loaded from a storage device 12-8 into a random access memory (RAM) 12-3. The RAM 12-3 also stores various programs and data required for the operation of the electronic device 12. The processing unit 12-1, ROM 12-2, and RAM 12-3 are interconnected via a bus 12-4. An input / output (I / O) interface 12-5 is also connected to the bus 12-4.

[0167] Typically, the following devices can be connected to I / O interface 12-5: input devices 12-6 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 12-7 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 12-8 including, for example, magnetic tapes, hard disks, etc.; and communication devices 12-9. Communication device 12-9 allows electronic device 12 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 An electronic device 12 with various devices is shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have instead. Figure 7 Each box shown can represent a device or multiple devices as needed.

[0168] Specifically, according to this embodiment, the process described in the above-referenced flowchart can be implemented as a computer software program. For example, this embodiment includes a computer program product comprising a computer program or instructions carried on a computer-readable medium, the computer program or instructions containing program code for performing the methods shown in the flowchart. In this embodiment, the computer program can be downloaded and installed from a network via communication device 12-9, or installed from storage device 12-8, or installed from ROM 12-2. When the computer program is executed by processing device 12-1, the following steps can be performed:

[0169] In some embodiments, the method for converting distributed optical fiber sensing data includes:

[0170] S1. Acquire raw data from distributed fiber optic sensing;

[0171] S2. Perform a first transformation process on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data;

[0172] S3. Perform a second transformation process on the first data to transform it from strain response to displacement response, and obtain the second data;

[0173] S4. Perform a third transformation process on the second data to transform it from a displacement response to a velocity response, and obtain the third data.

[0174] S5. Output the third data.

[0175] In some embodiments, the first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant of the inherent performance of the demodulation device based on distributed fiber optic sensing data.

[0176] In some embodiments, the second transformation process includes:

[0177] S31. For the first data, at a sampling time t1, select a sampling channel c1, and superimpose the sample values ​​of sampling channel c1 and all the sampling channels before it at sampling time t1 as the value at sample point (t1, c1); wherein, the sampling channels are ordered in order according to their positions in the distributed optical fiber, and here, the sampling channel with a sequence number smaller than c1 is the preceding sampling channel, and the sampling channel with a sequence number larger than c1 is the following sampling channel;

[0178] S32. Following step S31, traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1.

[0179] S33. Following steps S31 and S32, traverse all sampling points at all sampling times on all sampling channels in the sampling channel direction, and calculate the value of each sampling channel at all sampling times.

[0180] S34. On the sample points calculated in step S33, at a sampling time t2, take a sampling channel c2, take the sample point (t2, c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and subtract the calculated median value of the sample points from the value of the midpoint (t2, c2) to get the new value at the position of the midpoint (t2, c2). The time window refers to the number of sample points within the time window. The time window is an odd number greater than or equal to 10 and less than or equal to 100. The value of the time window can be determined through experimental results.

[0181] S35. Following step S34, traverse all sampling channels in the sampling channel direction and calculate the value of the sample point for each sampling channel at sampling time t2.

[0182] S36. Following steps S34 and S35, iterate through all sampling points at all sampling times for each sampling channel and calculate the value of each sampling channel at all sampling times.

[0183] In some embodiments, the third transformation process includes:

[0184] S41. For the second data, on a sampling channel c3, select a sampling time t3, and use the original value of the sample point (t3,c3) minus the original value of the sample point (t3-1,c3) to obtain the first new value of the sample point (t3,c3), where the value of the sample point (t3=0,c3) is equal to its own original value.

[0185] S42. Following step S41, traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time.

[0186] S43. Following steps S41 and S42, traverse all sampling channels in the sampling channel direction and calculate the first new value for each sampling channel and the sample points at all sampling times.

[0187] S44. For the sample points calculated in step S43, select a sampling channel c4, and perform a forward Fourier transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where... P = atan(I / R);

[0188] S45. Subtract π from each element of the phase angle sequence P obtained in step S44 to obtain a new phase angle sequence P'.

[0189] S46. Using the new phase angle sequence P' from step S45, calculate the new real part sequence R' and the new imaginary part sequence I', where I' = AcosP' and R' = Asin(P');

[0190] S47. Using the new real part sequence R' and the new imaginary part sequence I' obtained in step S46, perform an inverse Fourier transform to obtain the second new value of all sample points on sampling channel c4;

[0191] S48. Following steps S44 to S47, traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

[0192] It should be noted that the computer-readable medium described above in this embodiment can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this embodiment, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this embodiment, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0193] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0194] The aforementioned computer-readable medium may be included in the aforementioned device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to perform the following steps:

[0195] In some embodiments, the method for converting distributed optical fiber sensing data includes:

[0196] S1. Acquire raw data from distributed fiber optic sensing;

[0197] S2. Perform a first transformation process on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data;

[0198] S3. Perform a second transformation process on the first data to transform it from strain response to displacement response, and obtain the second data;

[0199] S4. Perform a third transformation process on the second data to transform it from a displacement response to a velocity response, and obtain the third data.

[0200] S5. Output the third data.

[0201] In some embodiments, the first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant of the inherent performance of the demodulation device based on distributed fiber optic sensing data.

[0202] In some embodiments, the second transformation process includes:

[0203] S31. For the first data, at a sampling time t1, select a sampling channel c1, and superimpose the sample values ​​of sampling channel c1 and all the sampling channels before it at sampling time t1 as the value at sample point (t1, c1); wherein, the sampling channels are ordered in order according to their positions in the distributed optical fiber, and here, the sampling channel with a sequence number smaller than c1 is the preceding sampling channel, and the sampling channel with a sequence number larger than c1 is the following sampling channel;

[0204] S32. Following step S31, traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1.

[0205] S33. Following steps S31 and S32, traverse all sampling points at all sampling times on all sampling channels in the sampling channel direction, and calculate the value of each sampling channel at all sampling times.

[0206] S34. On the sample points calculated in step S33, at a sampling time t2, take a sampling channel c2, take the sample point (t2, c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and subtract the calculated median value of the sample points from the value of the midpoint (t2, c2) to get the new value at the position of the midpoint (t2, c2). The time window refers to the number of sample points within the time window. The time window is an odd number greater than or equal to 10 and less than or equal to 100. The value of the time window can be determined through experimental results.

[0207] S35. Following step S34, traverse all sampling channels in the sampling channel direction and calculate the value of the sample point for each sampling channel at sampling time t2.

[0208] S36. Following steps S34 and S35, iterate through all sampling points at all sampling times for each sampling channel and calculate the value of each sampling channel at all sampling times.

[0209] In some embodiments, the third transformation process includes:

[0210] S41. For the second data, on a sampling channel c3, select a sampling time t3, and use the original value of the sample point (t3,c3) minus the original value of the sample point (t3-1,c3) to obtain the first new value of the sample point (t3,c3), where the value of the sample point (t3=0,c3) is equal to its own original value.

[0211] S42. Following step S41, traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time.

[0212] S43. Following steps S41 and S42, traverse all sampling channels in the sampling channel direction and calculate the first new value for each sampling channel and the sample points at all sampling times.

[0213] S44. For the sample points calculated in step S43, select a sampling channel c4, and perform a forward Fourier transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where... P = atan(I / R);

[0214] S45. Subtract π from each element of the phase angle sequence P obtained in step S44 to obtain a new phase angle sequence P'.

[0215] S46. Using the new phase angle sequence P' from step S45, calculate the new real part sequence R' and the new imaginary part sequence I', where I' = AcosP' and R' = Asin(P');

[0216] S47. Using the new real part sequence R' and the new imaginary part sequence I' obtained in step S46, perform an inverse Fourier transform to obtain the second new value of all sample points on sampling channel c4;

[0217] S48. Following steps S44 to S47, traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

[0218] Computer program code for performing the operations of this embodiment can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0219] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0220] The modules described in this embodiment can be implemented in software or hardware. The described modules can also be located in a processor; for example, they can be described as:

[0221] The module comprises an acquisition module, a generation module, and a calculation module. For example, the acquisition module can also be described as "a module for acquiring seismic wave data collected by distributed optical fibers for a target area."

[0222] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0223] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for converting distributed optical fiber sensor data, characterized in that, include: S1. Acquire raw data from distributed fiber optic sensing; S2. Perform a first transformation process on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data; S3. Perform a second transformation process on the first data to transform it from strain response to displacement response, and obtain the second data; S4. Perform a third transformation process on the second data to transform it from a displacement response to a velocity response, and obtain the third data. S5. Output the third data.

2. The conversion method according to claim 1, characterized in that, The first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant of the inherent performance of the demodulation device based on distributed optical fiber sensing data.

3. The conversion method according to claim 1, characterized in that, The second transformation process includes: S31. For the first data, at a sampling time t1, select a sampling channel c1, and superimpose the sample values ​​of sampling channel c1 and all the sampling channels before it at the sampling time t1 as the value at the sample point (t1, c1). S32. Following step S31, traverse all sampling channels in the sampling channel direction and calculate the value of each sampling channel at the sample point at sampling time t1. S33. Following steps S31 and S32, traverse all sampling points at all sampling times on all sampling channels in the sampling channel direction, and calculate the value of each sampling channel at all sampling times. S34. On the sample points calculated in step S33, at a sampling time t2, select a sampling channel c2, take the sample point (t2,c2) as the midpoint, take a time window, calculate the median value of the sample points within the time window, and use the value of the midpoint (t2,c2) minus the calculated median value of the sample points to obtain the new value at the position of the midpoint (t2,c2). S35. Following step S34, traverse all sampling channels in the channel direction and calculate the value of the sample point for each sampling channel at sampling time t2. S36. Following steps S34 and S35, iterate through all sampling points at all sampling times for each sampling channel and calculate the value of each sampling channel at all sampling times.

4. The conversion method according to claim 3, characterized in that, In step S34, the time window is an odd number that is greater than or equal to 10 and less than or equal to 100.

5. The conversion method according to any one of claims 1-4, characterized in that, The third transformation process includes: S41. For the second data, on a sampling channel c3, select a sampling time t3, and use the original value of the sample point (t3,c3) minus the original value of the sample point (t3-1,c3) to obtain the first new value of the sample point (t3,c3), where the value of the sample point (t3=0,c3) is equal to its own original value. S42. Following step S41, traverse all sample points at all sampling times and calculate the first new value at each sample point at each sampling time. S43. Following steps S41 and S42, traverse all channels in the channel direction and calculate the first new value of each sampling channel at all sampling times. S44. For the sample points calculated in step S43, select a sampling channel c4, and perform a forward Fourier transform on the first new values ​​of all sample points on sampling channel c4 to obtain the real part sequence R and the imaginary part sequence I; use the imaginary part sequence I and the real part sequence R to calculate the corresponding amplitude sequence A and phase sequence P, where... P = atan(I / R); S45. Subtract π from each element of the phase angle sequence P obtained in step S44 to obtain a new phase angle sequence P'. S46. Using the new phase angle sequence P' from step S45, calculate the new real part sequence R' and the new imaginary part sequence I', where I' = AcosP' and R' = Asin(P'); S47. Using the new real part sequence R' and the new imaginary part sequence I' obtained in step S46, perform an inverse Fourier transform to obtain the second new value of all sample points on sampling channel c4; S48. Following steps S44 to S47, traverse all sampling channels in the sampling channel direction to obtain the second new value of all sample points on each sampling channel.

6. A distributed optical fiber sensor data conversion device, used to implement the distributed optical fiber sensor data conversion method according to any one of claims 1-5, characterized in that, include: The acquisition module is used to acquire raw data from distributed fiber optic sensing. The first transformation processing module is used to perform a first transformation processing on the raw data to transform it from a phase response to a strain response, thereby obtaining the first data. The second transformation processing module is used to perform a second transformation processing on the first data to transform it from a strain response into a displacement response, thereby obtaining the second data. The third transformation processing module is used to perform a third transformation processing on the second data to transform it from a displacement response to a velocity response, thereby obtaining the third data. The output module is used to output the third data.

7. The conversion device according to claim 6, characterized in that, The first transformation process includes multiplying each sample point in the original data by a strain-phase conversion coefficient, wherein the strain-phase conversion coefficient is a constant determined by the inherent performance of the demodulation device based on distributed optical fiber sensing data.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 5.

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