A signal first arrival time picking method, system, electronic device and storage medium

Abstract

The application discloses a signal first arrival time picking method and system, electronic equipment and a storage medium. The method comprises the following steps: obtaining a target signal by collecting and preprocessing to-be-processed data; performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval containing a first arrival time; picking an improved Akaike information criterion minimum value point in the target interval as the first arrival time; and completing a geophysical data processing process according to the first arrival time. The embodiment of the application can improve the picking efficiency and the signal picking accuracy under the condition of low signal-to-noise ratio, and can be widely applied to the near-surface engineering geophysical technology field.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of near-surface engineering geophysical prospecting technology, and in particular to a signal first arrival time picking method and system, an electronic device and a storage medium. BACKGROUND

[0002] Near-surface exploration uses geophysical methods to obtain the structure and target location of underground media. These geophysical prospecting methods include ground penetrating radar, cross-hole radar, shallow seismic and ultrasonic detection, etc. The first arrival time is a very important parameter in the data processing process of geophysical prospecting, and whether the first arrival time can be quickly and accurately picked is crucial to data processing, velocity model construction and tomographic imaging. With the wide application of three-dimensional geophysical prospecting technology, the amount of data has increased geometrically, and the workload of picking the first arrival time has also increased significantly. At present, the picking of the first arrival time is mainly carried out manually, but it depends on the professional knowledge of the operator and the picking efficiency is low. In addition, in a low signal-to-noise ratio environment, the first arrival time of the signal is difficult to pick accurately.

[0003] In the prior art, the energy-based analysis method and the autoregressive (AR) analysis method are still the most commonly used. The energy-based picking method is simple and has high computational efficiency, but the picking accuracy of the short-term average / long-term average (STA / LTA) method is affected by the length of the long-term and short-term windows and the threshold setting, and the picking accuracy is poor in a low signal-to-noise ratio environment. The picking method based on AR analysis has high accuracy, and the AR-AIC method is one of the most commonly used methods. However, the AR-AIC method requires a preliminary determination of the approximate arrival time window, and the picking effect of low signal-to-noise ratio signals is unstable. Therefore, there is an urgent need for an automatic picking method with high picking accuracy, good stability and strong noise resistance to solve the problems of low picking efficiency of manual picking and poor signal picking accuracy in a low signal-to-noise ratio environment. SUMMARY

[0004] The main purpose of the embodiments of the present application is to provide a signal first arrival time picking method, system, electronic device and storage medium, which can improve the picking efficiency and improve the signal picking accuracy in a low signal-to-noise ratio environment.

[0005] To achieve the above-mentioned purpose, one aspect of the embodiments of the present application provides a signal first arrival time picking method, comprising the following steps:

[0006] Collecting and preprocessing the data to be processed to obtain a target signal;

[0007] Performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval containing the first arrival time;

[0008] Picking the improved Akaike information criterion minimum value point in the target interval as the first arrival time;

[0009] The first arrival time is used to complete a geophysical data processing procedure.

[0010] In some embodiments, the collected data to be processed is pre-processed to obtain a target signal, including the following steps:

[0011] Two drill holes are arranged in the underground karst area to be detected, wherein the receiving antenna and the transmitting antenna of the radar are respectively arranged in different drill holes, and both of them move along the depth direction of the drill hole with a fixed sampling point interval, and the sampling point interval is smaller than the half wavelength of the main frequency of the cross-hole radar, and the depth of the measuring line is determined according to the site condition.

[0012] The collected data to be processed is subjected to zero-time correction, band-pass filtering, amplitude normalization and down-sampling processing.

[0013] In the method, the original radar data is subjected to down-sampling to reduce the calculation cost, so that the number of sampling points N is kept at 1500-2000, and meanwhile, it is ensured that the down-sampling process satisfies the Nyquist sampling theorem.

[0014] In some embodiments, the amplitude-aware permutation entropy of the target signal is calculated to determine a target interval containing the first arrival time, including the following steps:

[0015] Given a sliding time window with a moving step of 1, the amplitude-aware permutation entropy value of each sliding time window with a length of W is calculated, and the time sequence of the original signal is converted into an entropy sequence.

[0016] The sampling point corresponding to the first minimum amplitude-aware permutation entropy value in the entropy sequence is picked up, and the sampling point corresponding to the last minimum entropy value is taken as an approximate peak value point, since the amplitude-aware permutation entropy value remains minimum after the sampling point.

[0017] The range between the time starting point and the approximate peak value point is taken as the interval L containing the first arrival time.

[0018] In some embodiments, given a sliding time window with a moving step of 1, the amplitude-aware permutation entropy value of each sliding time window with a length of W is calculated, and the time sequence of the original signal is converted into an entropy sequence, including the following steps:

[0019] For any time sequence W={x1,x2,...,x N}, the m-dimensional reconstruction vector of the delay time d at a specific time point i is defined as:

[0020]

[0021] The relative probability of the reconstruction vector is: ​​

[0022]

[0023] The calculation formula of the amplitude-aware permutation entropy is as follows:

[0024]

[0025] wherein, x(i) represents a symbol sequence; A represents an adjustment coefficient; m represents an embedding dimension; d represents a delay time; and g represents an m! permutation number.

[0026] In some embodiments, the picking up of the minimum value point of the improved Akaike information criterion in the target interval as the first arrival time comprises the following steps:

[0027] The original time sequence x(i) is replaced by a characteristic function CF(i) composed of slopes in a sliding time window w;

[0028] The minimum value of the time sequence in the local window range is picked up by using the improved Akaike information criterion algorithm, and the time sampling point corresponding to the minimum value is taken as the accurately picked first arrival time.

[0029] In some embodiments, the expression of the process of replacing the original time sequence x(i) by the characteristic function CF(i) composed of slopes in a sliding time window w is as follows:

[0030]

[0031] wherein, w represents a sliding time window size;

[0032] The calculation formula of the improved Akaike information criterion algorithm is as follows:

[0033] AIC(i)=i×log[var(CF(1,i))]+(L-i-1)×log[var(CF(i+1,L))],

[0034] wherein, L is an interval containing the first arrival time; i is a time sampling point sequence number; var(·) is a variance of the characteristic function CF; and AIC(i) is an improved Akaike information criterion value of radar data at the i-th point.

[0035] Another aspect of the embodiment of the application further provides a signal first arrival time picking system, comprising:

[0036] A first module is configured to collect and pre-process data to be processed to obtain a target signal;

[0037] A second module is configured to perform amplitude-aware permutation entropy calculation on the target signal to determine a target interval containing the first arrival time.

[0038] ​a third module configured to pick up a minimum value point of the improved Akaike information criterion in the target interval as the first arrival time;

[0039] a fourth module configured to complete a geophysical data processing procedure according to the first arrival time.

[0040] To achieve the above object, another aspect of the embodiment of the present application provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the above method when executing the computer program.

[0041] To achieve the above object, another aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above method.

[0042] The embodiment of the present application also discloses a computer program product or a computer program, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device can read the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to make the computer device execute the above method.

[0043] The embodiment of the present application at least has the following beneficial effects: the present application provides a signal first arrival time picking method, system, electronic device and storage medium, the scheme acquires and pre-processes data to be processed to obtain a target signal, performs amplitude-aware permutation entropy calculation on the target signal to determine a target interval containing the first arrival time, picks up a minimum value point of the improved Akaike information criterion in the target interval as the first arrival time, and completes a geophysical data processing procedure according to the first arrival time. The embodiment of the present application can improve picking efficiency and improve signal picking accuracy under a low signal-to-noise ratio condition. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 is an implementation environment schematic diagram provided by the embodiment of the present application;

[0045] Figure 2 is a flowchart of the overall steps provided by the embodiment of the present application;

[0046] Figure 3 is a flowchart of the specific implementation steps provided by the embodiment of the present application;

[0047] Figure 4 is a signal first arrival time picking method schematic diagram based on amplitude-aware permutation entropy and improved Akaike information criterion provided by the embodiment of the present application;

[0048] Figure 5 (a), Figure 5(b) the first arrival time picking results of the radar signal by the picking method and the conventional energy ratio method, respectively;

[0049] Figure 6 Fig. 1 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. When the following description refers to the accompanying drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application, and they are only examples of devices and methods consistent with some aspects of the embodiments of the present application as described in the appended claims.

[0051] It can be understood that the terms "first", "second", and the like used in the present application can be used herein to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information, without departing from the scope of the embodiments of the present application. Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon" or "in response to determining".

[0052] The terms "at least one", "multiple", "each", "any", and the like used in the present application include one, two or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0054] The signal first arrival time picking method, system, electronic device and storage medium provided by the embodiment of the present application relate to the near-surface engineering geophysical prospecting technical field. The signal first arrival time picking method provided by the embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in the terminal or the server. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a vehicle-mounted terminal and the like, but is not limited thereto; the server end can be configured as a stand-alone physical server, can also be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN and big data and artificial intelligence platform, and the server can also be a node server in a blockchain network; the software can be an application for implementing the signal first arrival time picking method, and the like, but is not limited to the above forms.

[0055] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as a program module. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in a distributed computing environment, in which tasks are performed by remote processing devices connected by a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0056] As shown in Figure 1 , it is an implementation environment schematic diagram provided by the embodiment of the present application. Referring to Figure 1 , the implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected by wireless or wired means for network connection to complete data transmission and exchange.

[0057] Server 101 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), as well as big data and artificial intelligence platforms.

[0058] In addition, server 101 can also be a node server in a blockchain network. Blockchain is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithm.

[0059] Terminal 102 may be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc. Terminal 102 may also be a vehicle-mounted terminal of the various device types described above, but is not limited thereto. Terminal 102 and server 101 may be connected directly or indirectly via wired or wireless communication, which is not limited in this embodiment of the present invention.

[0060] Based on the example Figure 1 In the implementation environment shown, an embodiment of the present invention provides a signal first arrival time picking method. The following is explained using the example of the signal first arrival time picking method applied to the server 101. It can be understood that the method can also be applied to the terminal 102.

[0061] Reference Figure 2 , Figure 2 The flowchart of the method for picking the first arrival time of a signal applied to a server provided by an embodiment of the present invention, the execution subject of the method can be any of the aforementioned computer devices (including servers or terminals). Figure 2 , the method may include the following steps:

[0062] Collect the data to be processed and perform preprocessing to obtain the target signal;

[0063] Performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval including the first arrival time;

[0064] Picking the minimum value point of the improved Akaike Information Criterion within the target interval as the first arrival time;

[0065] The geophysical data processing process is completed according to the first arrival time.

[0066] In some embodiments, collecting the data to be processed and performing preprocessing to obtain the target signal includes the following steps:

[0067] Two boreholes are laid out in the underground karst area to be detected. The radar's receiving antenna and transmitting antenna are located in different boreholes. Both antennas move along the borehole depth direction with a fixed measurement point spacing. The measurement point spacing is less than half the wavelength of the main frequency of the cross-hole radar. The depth of the survey line is determined according to the site conditions.

[0068] Performing zero-time correction, band-pass filtering, amplitude normalization and downsampling processing on the collected data to be processed;

[0069] Among them, each channel of original radar data is downsampled to reduce the computational cost, so that the number of sampling points N is maintained between 1500 and 2000, while ensuring that the downsampling process satisfies the Nyquist sampling theorem.

[0070] In some embodiments, performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval including a first arrival time comprises the following steps:

[0071] Given a sliding time window with a moving step of 1, the amplitude-aware permutation entropy value of each sliding time window with a length of W is calculated to convert the time series of the original signal into an entropy sequence;

[0072] Pick up the sampling point corresponding to the first minimum amplitude perception permutation entropy value in the entropy sequence. After this sampling point, the amplitude perception permutation entropy value still maintains the minimum value, and the sampling point corresponding to the last minimum entropy value is used as the approximate peak point.

[0073] The range between the time starting point and the approximate peak point is taken as the interval L including the first arrival time.

[0074] In some embodiments, given a sliding time window with a moving step length of 1, calculating the amplitude-aware permutation entropy value of each sliding time window with a length of W, and converting the time series of the original signal into an entropy sequence includes the following steps:

[0075] For any time series W = {x1, x2, ..., x N}, at a specific time point i, the m-dimensional reconstruction vector with a delay time d Defined as:

[0076]

[0077] Reconstruction vector The relative probability for:

[0078]

[0079] The calculation formula of amplitude-aware permutation entropy is:

[0080] in, A represents an adjustment coefficient; m represents an embedding dimension; d represents a delay time; and g represents a number of m! permutations.

[0081] In some embodiments, the picking up of the minimum value point of the improved Akaike information criterion in the target interval as the first arrival time comprises the following steps:

[0082] replacing the original time sequence x(i) with a characteristic function CF(i) composed of slopes in a sliding time window w;

[0083] by using the improved Akaike information criterion algorithm to pick up the minimum value of the time sequence in the local window range, the time sampling point corresponding to the minimum value is taken as the accurately picked first arrival time.

[0084] In some embodiments, the expression of the process of replacing the original time sequence x(i) with a characteristic function CF(i) composed of slopes in a sliding time window w is:

[0085]

[0086] where w represents the size of the sliding time window;

[0087] The calculation formula of the improved Akaike information criterion algorithm is:

[0088] AIC(i) = i x log[var(CF(i, i))] + (L-i-1) x log[var(CF(i+1, L))],

[0089] where L is an interval containing the first arrival time; i is the serial number of the time sampling point; var(·) is the variance of the characteristic function CF; and AIC(i) is the improved Akaike information criterion value of the radar data at the i-th point.

[0090] The implementation process of the application in a specific application scenario will be described in detail below with reference to the accompanying drawings of the specification:

[0091] In view of the problems existing in the prior art, the purpose of the application is to provide a signal first arrival time picking method based on amplitude perception permutation entropy and improved Akaike information criterion, so as to solve the problems of low efficiency of manual picking and poor signal picking accuracy in the low signal-to-noise ratio condition in the above background.

[0092] Reference Figure 3 , Figure 4 and Figure 5 The method of the application comprises the following steps:

[0093] Step S1: using system acquisition data X(n), where n = 1, 2, …, N; N is the number of sampling points of the signal;

[0094] Step S2: pre-processing the collected signal;

[0095] The pre-processing operation in step S2 includes zero time correction, band-pass filtering, amplitude normalization and down-sampling, etc.

[0096] Step 3: calculating the amplitude-aware permutation entropy of the pre-processed signal to determine the interval L containing the first arrival time;

[0097] Step 3 specifically includes the following steps:

[0098] 3.1 Given a sliding time window with a moving step of 1, calculate the amplitude-aware permutation entropy value of each sliding time window with a length of W according to formula (3), and convert the time series of the original signal into an entropy sequence;

[0099] For any time series W = {x1, x2,..., x N}, at a specific time point i, the m-dimensional reconstructed vector of the delay time d is defined as:

[0100]

[0101] The relative probability of the reconstructed vector is:

[0102]

[0103] In formula (2), A is an adjustment coefficient. For peak detection of a signal, A is usually taken as <<0.5.

[0104] The calculation formula of the amplitude-aware permutation entropy is:

[0105]

[0106] Wherein, represents a symbol sequence; A represents an adjustment coefficient; m represents an embedding dimension; d represents a delay time; and g represents the number of m! permutations.

[0107] 3.2 Pick up the sampling point corresponding to the first minimum amplitude-aware permutation entropy value in the entropy sequence. After the sampling point, the amplitude-aware permutation entropy value still remains the minimum value. Then, the sampling point corresponding to the last minimum entropy value is taken as an approximate peak point.

[0108] 3.3 The range between the time starting point and the approximate peak point is taken as the interval L containing the first arrival time.

[0109] Step 4: pick up the minimum value point of the improved Akaike information criterion in the interval L as the first arrival time.

[0110] A feature function CF(i) composed of the slopes within a sliding time window w is proposed to replace the original time series x(i) and its calculation formula is as follows:

[0111]

[0112] The calculation formula of the improved Akaike information criterion is as follows:

[0113] AIC(i) = i x log[var(CF(1, i))] + (L-i-1) x log[var(CF(i+1, L))] (5)

[0114] In formula (5), L is an interval containing a first arrival time; i is a time sampling point serial number; var(·) is a variance of the feature function CF; and AIC(i) is an improved Akaike information criterion value of the i-th point.

[0115] The minimum value of the time series in a local window range is picked up by using the improved Akaike information criterion algorithm, and the time sampling point corresponding to the minimum value is taken as the accurately picked first arrival time.

[0116] Wherein, Figure 4 The flow of picking up the first arrival time by the whole algorithm is as follows: Figure 4 (a) is a time series of original data; Figure 4 (b) is an entropy sequence; Figure 4 (c) is a feature function CF; Figure 4 (d) is an original data time series and an improved AIC curve.

[0117] Figure 5 (a) and Figure 5 (b) are respectively the picking up results of the algorithm and the energy ratio method, and it can be clearly seen that the picking up effect of the algorithm is better than that of the energy ratio method, and no false first arrival time is picked up.

[0118] In summary, the application solves the problem of false picking up of a local minimum Akaike information criterion value by a traditional Akaike information criterion algorithm under a low signal-to-noise ratio signal. The signal first arrival time picking up method based on amplitude-aware permutation entropy and improved Akaike information criterion can accurately pick up the first arrival time, reduce the workload of practitioners in data processing, and has lower algorithm complexity, and has strong practicability and innovation in practice.

[0119] Compared with the prior art, the application has the following beneficial effects:

[0120] (1) The amplitude-aware permutation entropy algorithm is used to pick up an approximate peak point of a signal, so as to determine a time window range of the improved Akaike information criterion, and this measure can avoid the problem of false picking up of a local minimum Akaike information criterion value;

[0121] (2), the application identifies the time window range first, and then picks accurate first arrival time by using the improved Akaike information criterion algorithm, so that the processing pressure of a large amount of data is reduced, misjudgment caused by noise interference is avoided, and accuracy is ensured;

[0122] (3), the application has high calculation efficiency and low algorithm complexity, and has strong practicability and innovation in practice.

[0123] Another aspect of the embodiment of the application also provides a signal first arrival time picking system, comprising:

[0124] A first module is configured to collect and pre-process the data to be processed to obtain a target signal;

[0125] A second module is configured to calculate the amplitude-aware permutation entropy of the target signal to determine a target interval containing the first arrival time;

[0126] A third module is configured to pick the minimum value point of the improved Akaike information criterion in the target interval as the first arrival time;

[0127] A fourth module is configured to complete the geophysical data processing process according to the first arrival time.

[0128] It can be understood that the contents in the above method embodiments are all applicable to the present system embodiment, the present system embodiment specifically realizes the same functions as the above method embodiments, and achieves the same beneficial effects as the above method embodiments.

[0129] The embodiment of the application also provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor realizes the above signal first arrival time picking method when executing the computer program.

[0130] It can be understood that the contents in the above method embodiments are all applicable to the present device embodiment, the present device embodiment specifically realizes the same functions as the above method embodiments, and achieves the same beneficial effects as the above method embodiments.

[0131] Please refer to Figure 6 , Figure 6 The hardware structure of the electronic device of another embodiment is illustrated, and the electronic device comprises:

[0132] The processor 601 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, and is configured to execute related programs to implement the technical solutions provided by the embodiments of the present application.

[0133] The memory 602 can be implemented by a ROM (Read Only Memory), a static storage device, a dynamic storage device, or a RAM (Random Access Memory), and the like. The memory 602 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present application are implemented by software or firmware, the related program codes are stored in the memory 602 and are called and executed by the processor 601 to implement the signal first arrival time picking method of the embodiments of the present application.

[0134] The input / output interface 603 is configured to implement information input and output.

[0135] The communication interface 604 is configured to implement the communication interaction between the device and other devices. The communication can be realized by a wired manner (for example, a USB, a network cable, or the like) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, or the like).

[0136] The bus 605 is configured to transmit information between various components (for example, the processor 601, the memory 602, the input / output interface 603, and the communication interface 604) of the device.

[0137] The processor 601, the memory 602, the input / output interface 603, and the communication interface 604 are connected to each other through the bus 605 to realize the communication connection between the device.

[0138] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program. The computer program is executed by the processor to implement the above-mentioned signal first arrival time picking method.

[0139] It can be understood that the contents of the above-mentioned method embodiments are applicable to the present storage medium embodiments. The present storage medium embodiments specifically implement the functions of the above-mentioned method embodiments, and achieve the same beneficial effects as the above-mentioned method embodiments.

[0140] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory and can also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include memory that is remotely arranged with respect to the processor, and these remote memories can be connected to the processor through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0141] It should be noted that in various specific embodiments of the present application, when it is necessary to perform relevant processing according to user information, user behavior data, user history data, and user location information and other data related to the identity or characteristics of the user, the user's permission or consent will be obtained first, and the collection, use and processing of these data will comply with relevant laws, regulations and standards. In addition, when the embodiments of the present application need to obtain sensitive personal information of the user, the separate permission or separate consent of the user will be obtained through a pop-up window or by jumping to a confirmation page, and after obtaining the separate permission or separate consent of the user, the necessary user-related data for enabling the embodiments of the present application to normally operate will be obtained.

[0142] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0143] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than those shown in the figures, or combine certain steps or different steps.

[0144] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, i.e., can be located in one place or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0145] Those skilled in the art can understand that all or some of the steps in the above disclosed method, the functions of the modules / units in the system and the device can be implemented as software, firmware, hardware and appropriate combinations thereof.

[0146] The terms "first", "second", "third", "fourth", and the like in the description and in the claims of this application, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of the terms so termed is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of orderly or chronological mundane operation, reverse order operation, based on completion of some desired or other convenient events, or based on other modification that can be wished to those with average skill in the art. Additionally, the terms "comprising", "having", "including", and "containing" are to be construed as open-ended terms (i.e., meaning "including, but not limited to", "comprising, but not limited to", "having, but not limited to", or "including, but not limited to") unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein and each separate value is incorporated into the specification as if it were individually recited herein. The use of any of the following terms "coupled", "connected", or "communicatively coupled", means the elements so connected are electrically or physically connected in some way and do not necessarily mean a direct electrical, physical or communicative connection unless otherwise indicated herein.

[0147] It should be understood that, in the application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the relationship between associated objects, which means that there can be three relationships, for example, "A and / or B" can mean that there are three cases: only A, only B, and A and B at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can mean a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0148] In several embodiments provided by the application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the above-mentioned units is only a logical functional division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed objects can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0149] The units described above as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0150] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0151] If the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods in each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0152] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modification, equivalent replacement and improvement made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A method for picking up the first arrival time of a signal, characterized in that: The following steps are involved: Collect the data to be processed and perform preprocessing to obtain the target signal; Performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval including the first arrival time; Picking the minimum value point of the improved Akaike Information Criterion within the target interval as the first arrival time; completing a geophysical data processing process according to the first arrival time; The step of performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval including the first arrival time comprises the following steps: Given a sliding time window with a moving step of 1, the amplitude-aware permutation entropy value of each sliding time window with a length of W is calculated to convert the time series of the original signal into an entropy sequence; Pick up the sampling point corresponding to the first minimum amplitude perception permutation entropy value in the entropy sequence. After this sampling point, the amplitude perception permutation entropy value still maintains the minimum value, and the sampling point corresponding to the last minimum entropy value is used as the approximate peak point. The range between the time starting point and the approximate peak point is taken as the target interval L including the first arrival time; Given a sliding time window with a moving step of 1, calculating the amplitude-aware permutation entropy value of each sliding time window with a length of W, and converting the time series of the original signal into an entropy sequence, the method includes the following steps: For any time series W={x1,x2,…,x N }, at a specific time point i, the m-dimensional reconstruction vector with a delay time d Defined as: Reconstruction vector The relative probability for: The calculation formula of amplitude-aware permutation entropy is: in, represents the symbol sequence; A represents the adjustment coefficient; m represents the embedding dimension; d represents the delay time; g represents the number of permutations; Picking the minimum point of the improved Akaike Information Criterion within the target interval as the first arrival time comprises the following steps: The original time series x(i) is replaced by a characteristic function CF(i) consisting of the slope within the sliding time window w of the target interval; By using the improved Akaike Information Criterion algorithm to pick the minimum value of the time series within the local window range, the time sampling point corresponding to the minimum value is used as the accurately picked first arrival time; The expression for the process of replacing the original time series x(i) with the characteristic function CF(i) composed of the slope within the sliding time window w of the target interval is: Where w represents the sliding time window size of the target interval; The calculation formula of the improved Akaike information criterion algorithm is: AIC(i)=i×log[var(CF(1,i))]+(Li-1)×log[var(CF(i+1,L))], where L is the target interval including the first arrival time; i is a specific time point; var(·) is the variance of the characteristic function CF; and AIC(i) is the improved Akaike information criterion value of the radar data at the i-th point.

2. A method for picking up the first arrival time of a signal according to claim 1, characterized in that: The method of collecting the data to be processed and performing preprocessing to obtain the target signal includes the following steps: Two boreholes are laid out in the underground karst area to be detected. The radar's receiving antenna and transmitting antenna are located in different boreholes. Both antennas move along the borehole depth direction with a fixed measurement point spacing. The measurement point spacing is less than half the wavelength of the main frequency of the cross-hole radar. The depth of the survey line is determined according to the site conditions. Performing zero-time correction, band-pass filtering, amplitude normalization and downsampling processing on the collected data to be processed; Among them, each channel of original radar data is downsampled to reduce the computational cost, so that the number of sampling points N is maintained between 1500 and 2000, while ensuring that the downsampling process satisfies the Nyquist sampling theorem.

3. A system for implementing the signal first arrival time picking method according to claim 1 or 2, characterized in that: include: The first module is used to collect and pre-process the data to obtain the target signal; The second module is used to perform amplitude perception permutation entropy calculation on the target signal to determine the target interval including the first arrival time; The third module is used to pick the minimum value point of the improved Akaike Information Criterion within the target interval as the first arrival time; The fourth module is used to complete the geophysical data processing process according to the first arrival time.

4. An electronic device, characterized in that: including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method according to any one of claims 1 or 2.

5. A computer-readable storage medium, characterized in that The storage medium stores a program, and the program is executed by a processor to implement the method according to any one of claims 1 or 2.

6. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to claim 1 or 2 is implemented.

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