Seabed subsurface buoy in-situ multi-source data edge processing and fusion method

Abstract

The invention provides a seabed subsurface buoy in-situ multi-source data edge processing and fusion method, which comprises the following steps of: 1, acquiring multi-source data through an upper computer in a seabed subsurface buoy system, and storing the multi-source data in a local SDXC card; 2, performing multi-source data extraction on the multi-source data through the upper computer according to a group of preset timestamps; step 3, performing data compression on the extracted multi-source data in the upper computer to obtain compressed multi-source data; and step 4, writing the compressed multi-source data into a binary file in a fusion format through the upper computer, and storing the binary file in the local SDXC card. Through data compression and format conversion, the size of the data volume is remarkably reduced, the data transmission efficiency is optimized, multi-source data is extracted, compressed and fused through edge calculation, the data volume in a specific format is generated, subsequent comprehensive analysis is facilitated, and the utilization rate and the analysis capacity of the data are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of marine geophysical exploration, and in particular to a method for edge processing and fusion of in-situ multi-source data of seabed buoys. Background Art

[0002] With the development of deep-sea monitoring technology, submarine buoys have become an important tool for marine environmental monitoring and scientific research. Submarine buoys can work stably for a long time and collect various data in the marine environment, such as four-component seismic sensor data, methane sensor data, temperature sensor data, etc. used in deep-sea hydrate leakage monitoring.

[0003] In the existing technology, deep-sea submersibles usually store the collected data in situ, and analyze the data after the submersibles are retrieved in a cycle of several months to several years, which is not conducive to the real-time feedback of marine environmental information. In order to achieve real-time transmission of monitoring data, underwater acoustic communication is the first choice for long-distance underwater data transmission, but underwater acoustic communication has a small bandwidth and high bit error rate, and has strict requirements for the transmitted data.

[0004] In summary, due to the particularity of deep sea areas, the existing methods for collecting and storing multi-source data from submarine buoys have the following problems:

[0005] (1) The data volume is large and does not meet the bandwidth requirements for acoustic communication data transmission;

[0006] (2) The data are of many types and are independent of each other, which is not conducive to comprehensive analysis;

[0007] (3) The data format is not suitable for acoustic transmission. Summary of the invention

[0008] In view of this, the present invention provides an edge processing and fusion method for in-situ multi-source data of seabed buoys, aiming to solve the problem that in the existing deep-sea seabed buoy monitoring process, there are many types of multi-source data, large data volume, and real-time or quasi-real-time transmission cannot be achieved.

[0009] The present invention provides an edge processing and fusion method for in-situ multi-source data of a submarine buoy, comprising: step 1, collecting multi-source data through a host computer in a submarine buoy system, and storing the multi-source data in a local SDXC card; step 2, extracting multi-source data from the multi-source data through the host computer according to a preset set of timestamps; step 3, compressing the extracted multi-source data through the host computer to obtain compressed multi-source data; step 4, writing the compressed multi-source data into a binary file in a fusion format through the host computer, and storing the binary file in the local SDXC card.

[0010] In one implementation, the seabed buoy system in step 1 includes a host computer, a PPB crystal array, a four-component seismic sensor, a methane sensor, a temperature sensor and a power supply, wherein the four-component seismic sensor includes H-component seismic data, X-component seismic data, Y-component seismic data, and Z-component seismic data components, and the data sampling rate is 800 Hz. The methane sensor samples once per minute, and the temperature sensor samples once per minute.

[0011] In another implementation, the multi-source data includes four-component seismic data, methane data and temperature transmission data, and the local SDXC card is used for data storage and has a capacity of 512G.

[0012] In another implementation, the preset set of timestamps in step 2 is a UNIX timestamp accurate to milliseconds, and the multi-source data extraction is performed on the multi-source data by the host computer based on the preset set of timestamps, including: according to the UNIX timestamp accurate to milliseconds, the multi-source data corresponding to each timestamp is extracted by the host computer; wherein, for the four-component seismic data, the data extracted is 1 second after each timestamp, and for the methane data and the temperature data, the data extracted is the data collected closest to each timestamp.

[0013] In another implementation, the step 3 of compressing the extracted multi-source data by the host computer includes: converting the four-component seismic data in the extracted multi-source data into a signed two-byte integer format; converting the methane data and the temperature data in the extracted multi-source data into a half-precision floating point format.

[0014] In another implementation, the fusion format in step 4 refers to the little-endian storage format of the compressed multi-source data in the binary file, specifically, each line starts with an 8-byte timestamp in a preset set of timestamps, followed by a two-byte character SH and compressed H component seismic data, followed by a two-byte character SZ and compressed Z component seismic data, followed by a two-byte character SX and compressed X component seismic data, followed by a two-byte character SY and compressed Y component seismic data, followed by a two-byte character ME and compressed two-byte methane data, followed by a two-byte character TM and compressed two-byte temperature data.

[0015] In summary, the present invention significantly reduces the size of the data body through data compression and format conversion, so that the compressed data format is suitable for the bandwidth and bit error rate requirements of long-distance transmission of underwater acoustic communication, and optimizes the data transmission efficiency. Through edge computing, multi-source data is extracted, compressed and fused to generate a data body in a specific format, which is convenient for subsequent comprehensive analysis and improves data utilization and analysis capabilities. The edge computing method and data fusion technology proposed in the present invention have wide applicability, can adapt to different seabed monitoring environments and various sensor data types, and have stronger adaptability and flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flowchart of the steps of the method for edge processing and fusion of multi-source data of seabed buoy in situ according to an embodiment of the present invention.

[0017] Figure 2 It is a schematic diagram of the fusion format of the edge processing and fusion method of the seabed buoy in-situ multi-source data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 A method for edge processing and fusion of multi-source data of submarine buoy in-situ according to an embodiment of the present invention includes:

[0020] Step 1, collecting multi-source data through a host computer in a submarine buoy system, and storing the multi-source data in a local SDXC card;

[0021] Step 2, extracting multi-source data from the multi-source data through the host computer according to a preset set of timestamps;

[0022] Step 3, compressing the extracted multi-source data in the host computer to obtain compressed multi-source data;

[0023] Step 4: Write the compressed multi-source data into a binary file in a fusion format through the host computer, and store the binary file in the local SDXC card.

[0024] The present invention provides an edge processing and fusion method for in-situ multi-source data of a seafloor buoy. Through the edge processing method, the extraction and fusion of multi-source data (four-component seismic sensor data, methane sensor data, and temperature sensor data) are realized in-situ on the seafloor, and the data volume is compressed. The specific data body format is suitable for the bandwidth and bit error rate requirements of long-distance data transmission in deep-sea acoustic communication, thereby providing a data basis for realizing or quasi-real-time acoustic communication transmission.

[0025] Optionally, the seabed buoy system in step 1 includes a host computer, a PPB crystal array, a four-component seismic sensor, a methane sensor, a temperature sensor and a power supply, wherein the four-component seismic sensor includes H-component seismic data, X-component seismic data, Y-component seismic data, and Z-component seismic data components, and the data sampling rate is 800 Hz. The methane sensor samples once per minute, and the temperature sensor samples once per minute.

[0026] It should be understood that the function of the host computer is to collect and process multi-source data, and the PPB crystal array is a PPB (parts per billion) level crystal array.

[0027] Optionally, the multi-source data includes four-component seismic data, methane data and temperature transmission data, and the local SDXC card is used for data storage and has a capacity of 512G.

[0028] Optionally, the preset set of timestamps in step 2 is a UNIX timestamp accurate to milliseconds, and the multi-source data extraction is performed on the multi-source data by the host computer based on the preset set of timestamps, including: according to the UNIX timestamp accurate to milliseconds, extracting the multi-source data corresponding to each timestamp by the host computer; wherein, for the four-component seismic data, the data extracted is 1 second after each timestamp, and for the methane data and the temperature data, the data extracted is the data collected closest to each timestamp.

[0029] Optionally, the step 3 of compressing the extracted multi-source data by the host computer includes: converting the four-component seismic data in the extracted multi-source data into a signed two-byte integer format; converting the methane data and the temperature data in the extracted multi-source data into a half-precision floating point format.

[0030] It should be understood that data compression in step 3 refers to significantly reducing the size of the data body through data format conversion. The specific method is to convert the four-component seismic data extracted in step 2 into a signed two-byte integer format, and take 32767 for values ​​greater than 32767 and -32767 for values ​​less than -32767; convert the extracted methane data and temperature data into half-precision floating point format.

[0031] Optionally, the fusion format in step 4 refers to the little-endian storage format of the compressed multi-source data in the binary file, specifically, each line starts with an 8-byte timestamp in a preset set of timestamps, followed by a two-byte character SH and compressed H component seismic data, followed by a two-byte character SZ and compressed Z component seismic data, followed by a two-byte character SX and compressed X component seismic data, followed by a two-byte character SY and compressed Y component seismic data, followed by a two-byte character ME and compressed two-byte methane data, followed by a two-byte character TM and compressed two-byte temperature data.

[0032] For example, see Figure 2 This is a schematic diagram of the fusion format of the method for edge processing and fusion of multi-source data of submarine buoy in-situ according to an embodiment of the present invention, and the symbols therein are explained as follows:

[0033] X - one byte, 1-8 byte timestamp, 2- two-byte character "SH" and the H component seismic data compressed in step 3, 3- two-byte character "SZ" and the Z component seismic data compressed in step 3, 4- two-byte character "SX" and the X component seismic data compressed in step 3, 5- two-byte character "SY" and the Y component seismic data compressed in step 3, 6- two-byte character "ME" and the two-byte methane data compressed in step 3, 7- two-byte character "TM" and the two-byte temperature data compressed in step 3.

[0034] That is, each line starts with the 8-byte timestamp in step 2, followed by the two-byte character "SH" and the H component seismic data compressed in step 3, followed by the two-byte character "SZ" and the Z component seismic data compressed in step 3, followed by the two-byte character "SX" and the X component seismic data compressed in step 3, followed by the two-byte character "SY" and the Y component seismic data compressed in step 3, followed by the two-byte character "ME" and the two-byte methane data compressed in step 3, followed by the two-byte character "TM" and the two-byte temperature data compressed in step 3.

[0035] In summary, the present invention significantly reduces the size of the data body through data compression and format conversion, so that the compressed data format is suitable for the bandwidth and bit error rate requirements of long-distance transmission of underwater acoustic communication, and optimizes the data transmission efficiency. Through edge computing, multi-source data is extracted, compressed and fused to generate a data body in a specific format, which is convenient for subsequent comprehensive analysis and improves data utilization and analysis capabilities. The edge computing method and data fusion technology proposed in the present invention have wide applicability, can adapt to different seabed monitoring environments and various sensor data types, and have stronger adaptability and flexibility.

[0036] It should be noted that the present invention may be a method, a system, an apparatus and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0037] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0038] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0039] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, Python, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present invention.

[0040] Various aspects of the present invention are described herein with reference to the flow charts and / or block diagrams of the methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each box of the flow chart and / or block diagram and the combination of each box in the flow chart and / or block diagram can be implemented by computer-readable program instructions.

[0041] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0042] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0043] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a part of a module, a program segment or an instruction, and a part of the module, a program segment or an instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that it is equivalent to implement it by hardware, implement it by software, and implement it by combining software and hardware.

[0044] Embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the marketplace, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A method for edge processing and fusion of multi-source data of submarine buoy in situ, characterized in that: include: Step 1, collecting multi-source data through a host computer in a submarine buoy system, and storing the multi-source data in a local SDXC card; Step 2, extracting multi-source data from the multi-source data through the host computer according to a preset set of timestamps; Step 3, compressing the extracted multi-source data in the host computer to obtain compressed multi-source data; Step 4: Write the compressed multi-source data into a binary file in a fusion format through the host computer, and store the binary file in the local SDXC card.

2. The method according to claim 1, characterized in that The seabed buoy system described in step 1 includes a host computer, a PPB crystal array, a four-component seismic sensor, a methane sensor, a temperature sensor and a power supply, wherein the four-component seismic sensor includes H-component seismic data, X-component seismic data, Y-component seismic data, and Z-component seismic data components, and the data sampling rate is 800 Hz. The methane sensor samples once per minute, and the temperature sensor samples once per minute.

3. The method according to claim 2, characterized in that The multi-source data includes four-component seismic data, methane data and temperature data. The local SDXC card is used for data storage and has a capacity of 512G.

4. The method according to claim 3, characterized in that The preset set of timestamps in step 2 is a UNIX timestamp accurate to milliseconds. The multi-source data extraction is performed on the multi-source data by the host computer according to the preset set of timestamps, including: According to the UNIX timestamp accurate to milliseconds, extracting multi-source data corresponding to each timestamp through the host computer; Among them, for the four-component seismic data, the data extracted is 1 second after each time stamp, and for the methane data and the temperature data, the data extracted is the data collected closest to each time stamp.

5. The method according to claim 3, characterized in that: The step 3 of compressing the extracted multi-source data in the host computer includes: Convert the four-component seismic data in the extracted multi-source data into a signed two-byte integer format; The methane data and the temperature data in the extracted multi-source data are converted into a half-precision floating point format.

6. The method according to claim 5, characterized in that The fusion format described in step 4 refers to the little-endian storage format of the compressed multi-source data in the binary file, specifically, each line starts with an 8-byte timestamp in a preset set of timestamps, followed by a two-byte character SH and compressed H component seismic data, followed by a two-byte character SZ and compressed Z component seismic data, followed by a two-byte character SX and compressed X component seismic data, followed by a two-byte character SY and compressed Y component seismic data, followed by a two-byte character ME and compressed two-byte methane data, followed by a two-byte character TM and compressed two-byte temperature data.

Images