Signal first arrival time pickup method and system, electronic equipment and storage medium

Abstract

The invention discloses a signal first arrival time pickup method and system, electronic equipment and a storage medium, and the method comprises the steps: collecting to-be-processed data, and carrying out the preprocessing of the to-be-processed data, and obtaining a target signal; carrying out amplitude perception permutation entropy calculation on the target signal, and determining a target interval containing first arrival time; picking up the minimum value point of the improved akaike information criterion in the target interval as first arrival time; and completing a geophysical prospecting data processing process according to the first arrival time. According to the embodiment of the invention, the pickup efficiency can be improved, the signal pickup precision under the condition of low signal-to-noise ratio is improved, and the method can be widely applied to the technical field of near-surface engineering geophysical prospecting.

Description

Technical Field

[0001] The present invention relates to the technical field of near-surface engineering geophysical exploration, and in particular to a signal first arrival time picking method, system, electronic equipment and storage medium. Background Art

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

[0003] In the prior art, energy-based analysis methods and autoregression (AR) analysis methods are still the most commonly used. The energy-based picking method is simple and computationally efficient, but the picking accuracy of the short-term average / long-term average (STA / LTA) method is affected by the length of the long and short time windows and the threshold setting, and the picking accuracy is poor under low signal-to-noise ratio. The picking method based on AR analysis has higher accuracy, among which the AR-AIC method is one of the most commonly used. However, the AR-AIC method requires the approximate arrival time window to be determined in advance, and the picking effect for 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 manual picking efficiency and poor signal picking accuracy under low signal-to-noise ratio conditions. Summary of the invention

[0004] The main purpose of the embodiments of the present invention 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 under low signal-to-noise ratio conditions.

[0005] To achieve the above object, an embodiment of the present invention provides a method for picking up the first arrival time of a signal, comprising the following steps:

[0006] Collect the data to be processed and perform preprocessing to obtain the target signal;

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

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

[0009] The geophysical data processing process is completed according to the first arrival time.

[0010] In some embodiments, the collecting of the data to be processed and preprocessing to obtain the target signal comprises the following steps:

[0011] Two boreholes are arranged in the underground karst area to be detected, wherein the receiving antenna and transmitting antenna of the radar are respectively in different boreholes, and both move along the depth direction of the borehole with a fixed measuring point spacing, and the measuring point spacing is less than half the wavelength of the main frequency of the cross-hole radar, and the depth of the survey line is determined according to the site conditions;

[0012] Performing zero-time correction, bandpass filtering, amplitude normalization and downsampling processing on the collected data to be processed;

[0013] 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.

[0014] In some embodiments, the step of performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval including a first arrival time comprises 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 to convert the time series of the original signal into an entropy sequence;

[0016] Pick up the sampling point corresponding to the first minimum amplitude-perceived permutation entropy value in the entropy sequence. After this sampling point, the amplitude-perceived 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;

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

[0018] 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 window length W, and converting the time series of the original signal into an entropy sequence, comprises the following steps:

[0019] For any time series W = {x 1 ,x 2 ,K,x N}, at a specific time point i, the m-dimensional reconstruction vector with a delay time d Defined as:

[0020] Reconstruction vector The relative probability for:

[0021]

[0022] The calculation formula of amplitude-aware permutation entropy is:

[0023] in, represents the symbol sequence; A represents the adjustment coefficient; m represents the embedding dimension; d represents the delay time; and g represents the number of permutations.

[0024] In some embodiments, the step of picking up the minimum point of the improved Akaike information criterion within the target interval as the first arrival time comprises the following steps:

[0025] The original time series x(i) is replaced by the feature function CF(i) consisting of the slope within the sliding window w;

[0026] The improved Akaike information criterion algorithm is used to pick the minimum value of the time series within the local window range, and the time sampling point corresponding to the minimum value is used as the accurately picked first arrival time.

[0027] In some embodiments, 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 window w is:

[0028] Among them, w represents the sliding window size;

[0029] The calculation formula of the improved Akaike information criterion algorithm is:

[0030] AIC(i)=i×log[var(CF(1,i))]+(Li-1)×log[var(CF(i+1,L))],

[0031] Where L is the time window length; i is the time sampling point number; var(·) is the variance of the characteristic function CF; AIC(i) is the improved Akaike information criterion value of the radar data at the i-th point.

[0032] Another aspect of the embodiment of the present invention further provides a signal first arrival time picking system, comprising:

[0033] The first module is used to collect and pre-process the data to obtain the target signal;

[0034] The second module is used to perform amplitude-aware permutation entropy calculation on the target signal to determine a target interval including the first arrival time;

[0035] The third module is used to pick up the minimum value point of the improved Akaike information criterion in the target interval as the first arrival time;

[0036] The fourth module is used to complete the geophysical data processing process according to the first arrival time.

[0037] To achieve the above objective, another aspect of an embodiment of the present invention provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above-mentioned method when executing the computer program.

[0038] To achieve the above objective, another aspect of an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method is implemented.

[0039] The embodiment of the present invention also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device can read the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the above method.

[0040] The embodiments of the present invention include at least the following beneficial effects: the present invention provides a signal first arrival time picking method, system, electronic device and storage medium, the scheme acquires the target signal by collecting the data to be processed and preprocessing it; performs amplitude perception permutation entropy calculation on the target signal to determine the target interval containing the first arrival time; picks the minimum value point of the improved Akaike information criterion in the target interval as the first arrival time; completes the geophysical data processing process according to the first arrival time. The embodiments of the present invention can improve the picking efficiency and improve the signal picking accuracy under low signal-to-noise ratio conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of an implementation environment provided by an embodiment of the present invention;

[0042] Figure 2 is a flow chart of overall steps provided by an embodiment of the present invention;

[0043] Figure 3 It is a flowchart of specific implementation steps provided by an embodiment of the present invention;

[0044] Figure 4 It is a schematic diagram of a signal first arrival time picking method based on amplitude-aware permutation entropy and improved Akaike information criterion of the present invention;

[0045] Figure 5 (a) Figure 5 (b) are the first arrival time picking result diagrams of radar signals using the picking method proposed by the present invention and the traditional energy ratio method;

[0046] Figure 6 It is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present invention. They are only examples of devices and methods consistent with some aspects of the embodiments of the present invention as detailed in the attached claims.

[0048] It is understood that the terms "first", "second", etc. used in the present invention may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present invention, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0049] The terms "at least one", "multiple", "each", "any", etc. used in the present invention, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

[0051] The signal first arrival time picking method, system, electronic device and storage medium provided in the embodiments of the present invention relate to the field of near-surface engineering geophysical exploration technology. The signal first arrival time picking method provided in the embodiments of the present invention can be applied to a terminal, can be applied to a server, or can be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a car terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, and can also be configured as 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, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application that implements the signal first arrival time picking method, etc., but is not limited to the above forms.

[0052] The present invention 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 electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present invention can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0053] like Figure 1 FIG. 1 is a schematic diagram of an implementation environment provided by an embodiment of the present invention. 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 to a network wirelessly or wired to complete data transmission and exchange.

[0054] 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.

[0055] In addition, the server 101 can also be a node server in the 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.

[0056] The terminal 102 may be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc. The terminal 102 may also be a vehicle-mounted terminal of various device types described above, but is not limited thereto. The terminal 102 and the server 101 may be directly or indirectly connected via wired or wireless communication, which is not limited in this embodiment of the present invention.

[0057] Based on the example Figure 1 In the implementation environment shown, an embodiment of the present invention provides a method for picking up the first arrival time of a signal. The following is explained using the example of applying the method for picking up the first arrival time of a signal in a server 101. It can be understood that the method can also be applied to a terminal 102.

[0058] Reference Figure 2 , Figure 2 The flowchart of the method for picking the first arrival time of a signal applied to a server provided in an embodiment of the present invention, the execution subject of the method can be any of the aforementioned computer devices (including a server or a terminal). Figure 2 , the method may include the following steps:

[0059] Collect the data to be processed and perform preprocessing to obtain the target signal;

[0060] Performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval including a first arrival time;

[0061] Picking the minimum value point of the improved Akaike information criterion within the target interval as the first arrival time;

[0062] The geophysical data processing process is completed according to the first arrival time.

[0063] In some embodiments, the collecting of the data to be processed and preprocessing to obtain the target signal comprises the following steps:

[0064] Two boreholes are arranged in the underground karst area to be detected, wherein the receiving antenna and transmitting antenna of the radar are respectively in different boreholes, and both move along the depth direction of the borehole with a fixed measuring point spacing, and the measuring point spacing is less than half the wavelength of the main frequency of the cross-hole radar, and the depth of the survey line is determined according to the site conditions;

[0065] Performing zero-time correction, bandpass filtering, amplitude normalization and downsampling processing on the collected data to be processed;

[0066] 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.

[0067] In some embodiments, the step of performing amplitude-aware permutation entropy calculation on the target signal to determine a target interval including a first arrival time comprises the following steps:

[0068] Given a sliding time window with a moving step of 1, the amplitude-aware permutation entropy value of each sliding window length W is calculated to convert the time series of the original signal into an entropy sequence;

[0069] Pick up the sampling point corresponding to the first minimum amplitude-perceived permutation entropy value in the entropy sequence. After this sampling point, the amplitude-perceived 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;

[0070] The range between the time starting point and the approximate peak point is taken as the interval L including the first arrival time.

[0071] 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, comprises the following steps:

[0072] For any time series W = {x 1 ,x 2 ,K,x N}, at a specific time point i, the m-dimensional reconstruction vector with a delay time d Defined as:

[0073] Reconstruction vector The relative probability for:

[0074]

[0075] The calculation formula of amplitude-aware permutation entropy is:

[0076] in, represents the symbol sequence; A represents the adjustment coefficient; m represents the embedding dimension; d represents the delay time; and g represents the number of permutations.

[0077] In some embodiments, the step of picking up the minimum point of the improved Akaike information criterion within the target interval as the first arrival time comprises the following steps:

[0078] The original time series x(i) is replaced by the feature function CF(i) consisting of the slope within the sliding window w;

[0079] The improved Akaike information criterion algorithm is used to pick the minimum value of the time series within the local window range, and the time sampling point corresponding to the minimum value is used as the accurately picked first arrival time.

[0080] In some embodiments, 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 window w is:

[0081] Among them, w represents the sliding window size;

[0082] The calculation formula of the improved Akaike information criterion algorithm is:

[0083] AIC(i)=i×log[var(CF(1,i))]+(Li-1)×log[var(CF(i+1,L))],

[0084] Where L is the time window length; i is the time sampling point number; var(·) is the variance of the characteristic function CF; AIC(i) is the improved Akaike information criterion value of the radar data at the i-th point.

[0085] The implementation process of the present invention in a specific application scenario is described in detail below in conjunction with the accompanying drawings of the specification:

[0086] In view of the problems existing in the prior art, the purpose of the present invention is to provide a signal first arrival time picking method based on amplitude-aware permutation entropy and improved Akaike information criterion, so as to solve the problems of low manual picking efficiency and poor signal picking accuracy under low signal-to-noise ratio conditions in the above-mentioned background.

[0087] refer to Figure 3 , Figure 4 and Figure 5 , the method of the present invention comprises the following steps:

[0088] Step S1: using the system to collect data X(n), where n=1, 2, ..., N; N is the number of sampling points of the signal;

[0089] Step S2: pre-processing the collected signal;

[0090] The preprocessing operations in step S2 include zero-time correction, bandpass filtering, amplitude normalization and downsampling;

[0091] Step 3: Calculate the amplitude-aware permutation entropy of the preprocessed signal to determine the interval L containing the first arrival time;

[0092] Step 3 specifically includes the following steps:

[0093] 3.1 Given a sliding time window with a moving step of 1, the amplitude-aware permutation entropy value of each sliding window length W is calculated according to formula (3) to convert the time series of the original signal into an entropy sequence;

[0094] For any time series W = {x 1 ,x 2 ,K,x N}, at a specific time point i, the m-dimensional reconstruction vector with a delay time d Defined as:

[0095]

[0096] Reconstruction vector The relative probability is:

[0097]

[0098] In formula (2), A is the adjustment coefficient. For peak detection of the signal, A<<0.5 is usually taken.

[0099] The calculation formula of amplitude-aware permutation entropy is:

[0100]

[0101] in; represents the symbol sequence; A represents the adjustment coefficient; m represents the embedding dimension; d represents the delay time; and g represents the number of permutations.

[0102] 3.2 Pick up the sampling point corresponding to the first minimum amplitude-perceived permutation entropy value in the entropy sequence. After this sampling point, the amplitude-perceived 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;

[0103] 3.3 The range between the time starting point and the approximate peak point is taken as the interval L including the first arrival time;

[0104] Step 4: Pick the minimum point of the improved Akaike information criterion in the interval L as the first arrival time;

[0105] The characteristic function CF(i) composed of the slope within the sliding window w is proposed to replace the original time series x(i), and its calculation formula is:

[0106]

[0107] The calculation formula of the improved Akaike information criterion is:

[0108] AIC(i)=i×log[var(CF(1,i))]+(Li-1)×log[var(CF(i+1,L))] (5)

[0109] In formula (5), L is the time window length; i is the time sampling point number; var(·) is the variance of the characteristic function CF; AIC(i) is the improved Akaike information criterion value of the i-th point.

[0110] The improved Akaike information criterion algorithm is used to pick the minimum value of the time series within the local window range, and the time sampling point corresponding to the minimum value is used as the accurately picked first arrival time.

[0111] in, Figure 4 This is the process of the entire algorithm picking up the first arrival time: Figure 4 (a) is the time series of the original data; Figure 4 (b) is the entropy sequence; Figure 4 (c) is the characteristic function CF; Figure 4 (d) is the original data time series and the improved AIC curve.

[0112] Figure 5 (a) and Figure 5 (b) are the picking results of this algorithm and the picking results of the energy ratio method. It can be clearly seen that the picking effect of this algorithm is better than that of the energy ratio method, and no wrong first arrival time is picked up.

[0113] In summary, the present invention solves the problem that the traditional Akaike information criterion algorithm mistakenly picks up the local minimum Akaike information criterion value under low signal-to-noise ratio signals. The signal first arrival time picking 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 the algorithm complexity is low, which has strong practicality and innovation in practice.

[0114] Compared with the prior art, the present invention has the following beneficial effects:

[0115] (1) The present invention uses the amplitude-aware permutation entropy algorithm to pick up the approximate peak point of the signal, thereby determining the time window range of the improved Akaike information criterion. This measure will avoid the problem of erroneously picking up the local minimum Akaike information criterion value;

[0116] (2) The present invention first identifies the time window range, and then uses the improved Akaike information criterion algorithm to pick up the accurate first arrival time, which not only reduces the processing pressure of a large amount of data, but also avoids misjudgment caused by noise interference, thereby ensuring accuracy;

[0117] (3) The present invention has high computational efficiency and low algorithm complexity, and is highly practical and innovative in practice.

[0118] Another aspect of the embodiment of the present invention further provides a signal first arrival time picking system, comprising:

[0119] The first module is used to collect and pre-process the data to obtain the target signal;

[0120] The second module is used to perform amplitude-aware permutation entropy calculation on the target signal to determine a target interval including the first arrival time;

[0121] The third module is used to pick up the minimum value point of the improved Akaike information criterion in the target interval as the first arrival time;

[0122] The fourth module is used to complete the geophysical data processing process according to the first arrival time.

[0123] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0124] The embodiment of the present invention further provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above signal first arrival time picking method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0125] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0126] See also Figure 6 , Figure 6 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0127] The processor 601 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention;

[0128] The memory 602 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 602 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 602, and the processor 601 calls and executes the signal first arrival time picking method of the embodiment of the present invention;

[0129] Input / output interface 603, used to implement information input and output;

[0130] Communication interface 604, used to realize communication interaction between the device and other devices, which can be realized by wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0131] Bus 605 , which transmits information between various components of the device (e.g., processor 601 , memory 602 , input / output interface 603 , and communication interface 604 );

[0132] The processor 601 , the memory 602 , the input / output interface 603 and the communication interface 604 are connected to each other in communication within the device via a bus 605 .

[0133] An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned signal first arrival time picking method is implemented.

[0134] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0135] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via 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.

[0136] It should be noted that in various specific embodiments of the present invention, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, 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 embodiment of the present invention needs to obtain the user's sensitive personal information, it will obtain the user's separate permission or consent through a pop-up window or jump to a confirmation page, and after clearly obtaining the user's separate permission or consent, it will obtain the necessary user-related data for the normal operation of the embodiment of the present invention.

[0137] The embodiments described in the embodiments of the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. Those skilled in the art can appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

[0138] Those skilled in the art will appreciate that the technical solutions shown in the figures do not limit the embodiments of the present invention and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0139] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0141] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0142] It should be understood that in the present invention, "at least one (item)" refers to one or more, and "plurality" refers to two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can represent: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0143] In the several embodiments provided by the present invention, 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 schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0144] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0145] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0146] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including multiple instructions for 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 of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store programs.

[0147] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the embodiments of the present invention is not limited thereby. Any modification, equivalent substitution and improvement made by those skilled in the art without departing from the scope and essence of the embodiments of the present invention shall be within the scope of the rights of the embodiments of the present invention.

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 a first arrival time; Picking the minimum value point of the improved Akaike information criterion within the target interval as the first arrival time; The geophysical data processing process is completed according to the first arrival time.

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 preprocessing it to obtain the target signal includes the following steps: Two boreholes are arranged in the underground karst area to be detected, wherein the receiving antenna and transmitting antenna of the radar are respectively in different boreholes, and both move along the depth direction of the borehole with a fixed measuring point spacing, and the measuring point spacing is less than half the wavelength of the main frequency of the cross-hole radar, and the depth of the survey line is determined according to the site conditions; Performing zero-time correction, bandpass 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. The method for picking up the first arrival time of a signal according to claim 1, characterized in that: 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 window length 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-perceived permutation entropy value in the entropy sequence. After this sampling point, the amplitude-perceived 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 interval L including the first arrival time.

4. A method for picking up the first arrival time of a signal according to claim 3, characterized in that: 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, the method includes the following steps: For any time series W = {x1,x2,K,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; and g represents the number of permutations.

5. The method for picking up the first arrival time of a signal according to claim 1, characterized in that: The step of picking up 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 the feature function CF(i) consisting of the slope within the sliding window w; The improved Akaike information criterion algorithm is used to pick the minimum value of the time series within the local window range, and the time sampling point corresponding to the minimum value is used as the accurately picked first arrival time.

6. A method for picking up the first arrival time of a signal according to claim 5, characterized in that: The expression of the process of replacing the original time series x(i) by the characteristic function CF(i) composed of the slope in the sliding window w is: Among them, w represents the sliding window size; 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 time window length; i is the time sampling point number; var(·) is the variance of the characteristic function CF; AIC(i) is the improved Akaike information criterion value of the radar data at the i-th point.

7. A signal first arrival time picking system, 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-aware permutation entropy calculation on the target signal to determine a target interval including the first arrival time; The third module is used to pick up the minimum value point of the improved Akaike information criterion in 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.

8. 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 to 6.

9. 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 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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