CN115306339A - Subsea tree device - Google Patents

Abstract

The present disclosure relates to an ocean deep-water Christmas tree device, comprising: a signal acquisition module for acquiring a communication signal sent by an underwater control module; a signal transformation module for performing Fourier transform processing on the communication signal to obtain a signal spectrum, comprising: Phase spectrum and amplitude spectrum; the signal processing module is used to input the phase spectrum into the first model to obtain the noise phase characteristic information, and input the amplitude spectrum into the second model to obtain the noise amplitude characteristic information, based on the noise phase characteristic information and the noise amplitude The characteristic information removes the noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and performs inverse Fourier transform processing on the target signal spectrum to obtain the target signal; the first model is based on the phase spectrum of the sample communication signal and the extracted phase spectrum of the sample communication signal The noise feature in the neural network is trained, and the second model is obtained by training the neural network based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal.

Description

Offshore submerged Christmas tree device

technical field

Embodiments of the present disclosure relate to the technical field of offshore oil and gas exploitation equipment, and in particular, to an offshore underwater Christmas tree device.

Background technique

Subsea trees are often used in the underwater oil and gas exploitation of offshore oil and gas fields to control and regulate the underwater exploitation process. At present, the underwater Christmas tree equipment is the key high-end equipment for oil and gas exploitation such as marine underwater oil and natural gas. Compared with Christmas trees on land, subsea trees are generally located in deep water environments, and the application environment of Christmas tree equipment is more harsh. The process usually contains a lot of noise signals, how to better remove these noise signals in this scenario has become an urgent problem to be solved.

Contents of the invention

In order to solve the above technical problems or at least partly solve the above technical problems, an embodiment of the present disclosure provides a marine subsea Christmas tree device.

In a first aspect, an embodiment of the present disclosure provides a marine subsea oil tree device, including a subsea control module, and further comprising:

A signal acquisition module, configured to acquire the communication signal sent by the underwater control module;

A signal conversion module, configured to perform Fourier transform processing on the communication signal to obtain a signal spectrum, the signal spectrum includes a phase spectrum and an amplitude spectrum;

A signal processing module, configured to input the phase spectrum into the first model to obtain noise phase feature information, and simultaneously input the amplitude spectrum into the second model to obtain noise amplitude feature information, based on the noise phase feature information and noise The amplitude feature information removes the noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and performs inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein the first model is based on a sample communication signal The phase spectrum and the noise features in the extracted phase spectrum of the sample communication signal are obtained by training the neural network, and the second model is based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal obtained by training the neural network.

In one embodiment, the noise phase feature information includes position information of abnormal peaks and/or valleys in the phase spectrum.

In one embodiment, the noise amplitude feature information includes position information of abnormal amplitude points in the amplitude spectrum.

In one embodiment, the removing the noise signal spectrum in the signal spectrum based on the noise phase feature information and the noise amplitude feature information to obtain a target signal spectrum includes:

determining a phase spectrum of a noise signal in the phase spectrum based on location information of abnormal peaks and/or troughs in the phase spectrum;

determining the noise signal amplitude spectrum in the amplitude spectrum based on the abnormal amplitude point position information in the amplitude spectrum;

determining a noise signal spectrum based on the noise signal phase spectrum and the noise signal amplitude spectrum;

removing the noise signal spectrum from the signal spectrum to obtain the target signal spectrum.

In one embodiment, also includes:

An information acquisition module, configured to acquire marine environment information in the operating area of the underwater tree device;

The information processing module is used to determine the safety risk level in the marine environment based on the marine environment information, and when the safety risk level is greater than the preset risk level, generate an alarm message and send it to the Christmas tree operation monitoring platform.

In one embodiment, the marine environment information includes at least the temperature of seawater at different depths in the operating area of the underwater tree device and the concentration of combustible gases in the operating area of the underwater tree device.

In one embodiment, the communication signal comprises an acoustic communication signal.

In one embodiment, the signal acquisition module, the signal conversion module and the signal processing module are integrated on the same control circuit board, and the control circuit board is located in the water part of the subsea tree device.

In a second aspect, an embodiment of the present disclosure provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

Obtaining a communication signal sent by a subsea control module of the subsea tree device;

performing Fourier transform processing on the communication signal to obtain a signal spectrum, where the signal spectrum includes a phase spectrum and an amplitude spectrum;

inputting the phase spectrum into the first model to obtain noise phase characteristic information, and simultaneously inputting the amplitude spectrum into the second model to obtain noise magnitude characteristic information, and removing all The noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and perform inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein, the first model is based on the phase spectrum of the sample communication signal and the extracted samples The noise feature in the phase spectrum of the communication signal is obtained by training the neural network, and the second model is obtained by training the neural network based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal .

In a third aspect, an embodiment of the present disclosure provides an electronic device, including:

processor; and

memory for storing computer programs;

Wherein, the processor is configured to perform the following steps by executing the computer program:

Obtaining a communication signal sent by a subsea control module of the subsea tree device;

performing Fourier transform processing on the communication signal to obtain a signal spectrum, where the signal spectrum includes a phase spectrum and an amplitude spectrum;

inputting the phase spectrum into the first model to obtain noise phase characteristic information, and simultaneously inputting the amplitude spectrum into the second model to obtain noise magnitude characteristic information, and removing all The noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and perform inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein, the first model is based on the phase spectrum of the sample communication signal and the extracted samples The noise feature in the phase spectrum of the communication signal is obtained by training the neural network, and the second model is obtained by training the neural network based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal .

Compared with the prior art, the technical solutions provided by the embodiments of the present disclosure have the following advantages:

In the marine underwater Christmas tree device provided by the embodiment of the present disclosure, the signal acquisition module acquires the communication signal sent by the underwater control module; the signal conversion module performs Fourier transform processing on the communication signal to obtain a signal spectrum, and the signal spectrum includes phase spectrum and amplitude spectrum; the signal processing module inputs the phase spectrum into the first model to obtain noise phase feature information, and simultaneously inputs the amplitude spectrum into the second model to obtain noise amplitude feature information, based on the noise phase The feature information and the noise amplitude feature information remove the noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and perform inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein the first model is based on The phase spectrum of the sample communication signal and the noise features in the extracted phase spectrum of the sample communication signal are obtained by training the neural network, and the second model is based on the amplitude spectrum of the sample communication signal and the extracted amplitude spectrum of the sample communication signal The noise features in are obtained by training the neural network. In this way, the communication signal sent by the subsea control module of the subsea tree, that is, the control system module, is used for noise signal recognition to remove the noise signal through the pre-trained first and second models, so that the noise of the subsea tree can be better removed. The communication signal sent by the underwater control module contains a lot of noise signals in the process of reaching the water, and the removal effect is better, which is conducive to the subsequent accurate analysis of the communication signal to control the operation, and the operation safety is improved.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure.

In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, In other words, other drawings can also be obtained from these drawings without paying creative labor.

FIG. 1 is a schematic diagram of a marine submerged Christmas tree device according to an embodiment of the present disclosure;

Fig. 2 is a schematic diagram of a marine submerged Christmas tree device according to another embodiment of the present disclosure;

3 is a schematic diagram of a phase spectrum of a communication signal in an embodiment of the present disclosure;

FIG. 4 is a flow chart of a method for controlling an offshore submerged Christmas tree according to an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of an electronic device according to an embodiment of the disclosure.

Detailed ways

In order to more clearly understand the above objects, features and advantages of the present disclosure, the solutions of the present disclosure will be further described below. It should be noted that, in the case of no conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other.

In the following description, many specific details are set forth in order to fully understand the present disclosure, but the present disclosure can also be implemented in other ways than described here; obviously, the embodiments in the description are only some of the embodiments of the present disclosure, and Not all examples.

It should be understood that hereinafter, "at least one (item)" means one or more, and "multiple" means two or more. "And/or" is used to describe the association relationship of associated objects, which means that there can be three kinds of relationships, for example, "A and/or B" can mean: only A exists, only B exists, and A and B exist at the same time. Among them, A and B can be singular or plural. The character "/" generally indicates that the contextual objects are an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one item (piece) 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, c can be single or multiple.

Fig. 1 is a schematic diagram of an offshore submerged Christmas tree device provided by an embodiment of the present disclosure, including an underwater control module, a signal acquisition module located above the water, a signal conversion module and a signal processing module;

Among them, the underwater control module is used as the underwater control system of the offshore subsea tree device, and is used to control the opening and closing of respective hydraulic valves, etc. These can be understood with reference to the prior art, and will not be repeated here. Generally, the subsea control module has a communication function to transmit some communication signals to the surface. These communication signals may be communication signals carrying collected subsea environmental information and/or working status of the Christmas tree device, etc., but are not limited thereto.

The signal acquisition module communicates with the underwater control module, for example, it may be a wired or wireless communication connection. The above-water signal acquisition module is used to acquire the communication signal sent by the underwater control module, that is, to receive the communication signal sent by the underwater control module.

The signal conversion module receives the communication signal from the signal acquisition module, and then performs Fourier transform processing on the communication signal to obtain a signal spectrum, and the signal spectrum includes a phase spectrum and an amplitude spectrum.

The signal processing module inputs the phase spectrum into the first model to obtain noise phase characteristic information, and at the same time inputs the amplitude spectrum into the second model to obtain noise magnitude characteristic information, based on the noise phase characteristic information and noise magnitude characteristic The information removes the noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and performs Fourier inverse transform processing on the target signal spectrum to obtain the target signal.

Wherein, the first model is obtained by training the neural network based on the phase spectrum of the sample communication signal and the extracted noise features in the phase spectrum of the sample communication signal, and the second model is based on the amplitude spectrum of the sample communication signal and The noise features in the amplitude spectrum of the extracted sample communication signal are obtained by training the neural network.

Specifically, the specific training process of the neural network can be understood with reference to the prior art, and will not be repeated here. In this embodiment, two neural networks are used to prepare two training sample data for training to obtain two models, namely the first and second models, wherein the training sample data is the amplitude spectrum of the sample communication signal and the extracted sample communication signal. The noise features in the amplitude spectrum, the phase spectrum of the sample communication signal and the noise feature in the extracted phase spectrum of the sample communication signal. The sample communication signal can be collected when the Christmas tree is working, and then transformed to obtain two sets of training sample data. In this way, two models that can accurately identify different features of noise signals, such as amplitude features and phase features, can be trained. After the training is finished, the input of the first model is the phase spectrum corresponding to the communication signal collected in the actual application, and the output is the noise phase feature information, that is, the phase feature information of the noise signal in the communication signal. The input of the second model is the amplitude spectrum corresponding to the communication signal collected in actual application, and the output is the noise amplitude feature information, that is, the amplitude feature information of the noise signal in the communication signal.

In this embodiment, through the first and second pre-trained models, noise signal recognition is performed on the communication signal sent by the subsea control module of the subsea tree, that is, the control system module, so as to remove the noise signal, and different characteristic information of the noise signal is obtained by respectively identifying , and then remove the noise signal, which can better remove a lot of noise signals contained in the communication signal sent by the subsea control module of the subsea tree to reach the water, and the removal effect is better, which is conducive to the subsequent accurate analysis of the communication signal to control operation, and the safety of operation is improved.

In one embodiment, the noise phase feature information includes position information of abnormal peaks and/or valleys in the phase spectrum. As shown in Figure 3, the peaks and troughs of the phase Q in the phase spectrum of the collected communication signal change regularly, which is the target signal, that is, the actual communication signal, and the peaks and troughs in the phase spectrum of the collected communication signal are abnormal as before. High or low irregular changes, it is the phase P of the included noise signal, and the position information of these abnormal peaks and troughs can be recorded, such as the relative position point coordinates in the entire phase spectrum.

In one embodiment, the noise amplitude feature information includes position information of abnormal amplitude points in the amplitude spectrum. Exemplarily, the amplitude in the amplitude spectrum of the collected communication signal changes regularly, which is the target signal, that is, the actual communication signal, and the abnormal amplitude point in the amplitude spectrum of the collected communication signal is such as the amplitude is too high Or too low irregular changes, it is the amplitude of the included noise signal, and the position information of these abnormal amplitude points can be recorded, such as the relative position point coordinates in the entire amplitude spectrum.

Further, as an example, in one embodiment, the signal processing module removes the noise signal spectrum in the signal spectrum based on the noise phase feature information and the noise amplitude feature information to obtain a target signal spectrum, which may specifically include: Determining the noise signal phase spectrum in the phase spectrum based on the abnormal peak and/or valley position information in the phase spectrum; determining the noise in the amplitude spectrum based on the abnormal amplitude point position information in the amplitude spectrum signal amplitude spectrum; determining a noise signal spectrum based on the noise signal phase spectrum and noise signal amplitude spectrum; removing the noise signal spectrum from the signal spectrum to obtain the target signal spectrum.

That is to say, the phase spectrum and the amplitude of the noise signal in the collected communication signal can be respectively determined through the position information of the abnormal peak and/or trough in the phase spectrum and the position information of the abnormal amplitude point in the amplitude spectrum. , then the noise signal spectrum of the noise signal in the collected communication signal can be determined, and then the noise signal spectrum can be removed from the signal spectrum of the collected communication signal to obtain the target signal spectrum, that is, the signal spectrum of the actually required communication signal, Finally, inverse Fourier transform processing is performed to obtain the target signal spectrum, that is, the actual required communication signal. In this way, many noise signals included in the process of the communication signal sent by the subsea control module of the subsea tree reaching the water can be better removed, and the removal effect is better.

In one embodiment, as shown in FIG. 2 , the device further includes: an information acquisition module, configured to acquire marine environment information in the operating area of the underwater tree device; an information processing module, configured to obtain information based on the marine environment information , determine the safety risk level in the marine environment, and when the safety risk level is greater than the preset risk level, generate an alarm message and send it to the Christmas tree operation monitoring platform.

Exemplarily, the preset risk level can be set as required, without limitation. In one embodiment, the marine environment information may at least include but not limited to the temperature of seawater at different depths in the operating area of the underwater tree device and the concentration of combustible gases such as methane in the operating area of the underwater tree device gas concentration. Through the monitoring of seawater temperature and combustible gas concentration, the existing safety risk level such as explosion risk level can be determined, and the safety of Christmas tree operation can be improved and accidents can be avoided through monitoring and early warning prompts.

In one embodiment, the communication signal comprises an acoustic communication signal, such as an ultrasonic signal. Sound waves such as ultrasonic waves can propagate relatively well in seawater, so communication signals in the form of sound waves such as ultrasonic waves can transmit communication signals more accurately, and can reduce other forms of communication signals that are difficult to identify due to the enhancement of noise signals caused by the attenuation of seawater The situation of obtaining the target signal further improves the recognition accuracy of the target signal in the above solution of this embodiment.

In one embodiment, the signal acquisition module, the signal transformation module and the signal processing module are integrated on the same control circuit board, such as a PCB, and the control circuit board is located in the water part of the subsea tree device. This can improve integration and reduce space occupation.

It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. Actually, according to the embodiment of the present disclosure, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided to be embodied by a plurality of modules or units. Components shown as modules or units may or may not be physical units, may be located in one place, or may be distributed over multiple network elements. Part or all of the modules can be selected according to actual needs to realize the purpose of the disclosed scheme. It can be understood and implemented by those skilled in the art without creative effort.

An embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored. Referring to FIG. 4 , the computer program is executed by a processor to implement the following steps:

Step S401: Obtain the communication signal sent by the underwater control module;

Step S402: performing Fourier transform processing on the communication signal to obtain a signal spectrum, the signal spectrum includes a phase spectrum and an amplitude spectrum;

Step S403: Input the phase spectrum into the first model to obtain noise phase feature information, and at the same time input the amplitude spectrum into the second model to obtain noise amplitude feature information, based on the noise phase feature information and noise amplitude feature The information removes the noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and performs inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein the first model is based on the phase spectrum of the sample communication signal and The noise feature in the phase spectrum of the extracted sample communication signal is trained on the neural network, and the second model is based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal. obtained by training.

In one embodiment, the noise phase feature information includes position information of abnormal peaks and/or valleys in the phase spectrum.

In one embodiment, the noise amplitude feature information includes position information of abnormal amplitude points in the amplitude spectrum.

In one embodiment, the removing the noise signal spectrum in the signal spectrum based on the noise phase feature information and the noise amplitude feature information to obtain a target signal spectrum includes:

determining a phase spectrum of a noise signal in the phase spectrum based on location information of abnormal peaks and/or troughs in the phase spectrum;

determining the noise signal amplitude spectrum in the amplitude spectrum based on the abnormal amplitude point position information in the amplitude spectrum;

determining a noise signal spectrum based on the noise signal phase spectrum and the noise signal amplitude spectrum;

removing the noise signal spectrum from the signal spectrum to obtain the target signal spectrum.

Exemplarily, the readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: electrical connection with one or more conductors, portable disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

The computer readable storage medium may include a data signal carrying readable program code in baseband or as part of a carrier wave traveling as a data signal. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium other than a readable storage medium that can send, propagate or transport a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the readable storage medium may be transmitted by any suitable medium, including but not limited to wireless, cable, optical cable, RF, etc., or any suitable combination of the above.

An embodiment of the present disclosure also provides an electronic device, including a processor and a memory, where the memory is used to store a computer program. Wherein, the processor is configured to perform the following steps by executing the computer program:

Obtain the communication signal sent by the underwater control module;

performing Fourier transform processing on the communication signal to obtain a signal spectrum, where the signal spectrum includes a phase spectrum and an amplitude spectrum;

inputting the phase spectrum into the first model to obtain noise phase characteristic information, and simultaneously inputting the amplitude spectrum into the second model to obtain noise magnitude characteristic information, and removing all The noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and perform inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein, the first model is based on the phase spectrum of the sample communication signal and the extracted samples The noise feature in the phase spectrum of the communication signal is obtained by training the neural network, and the second model is obtained by training the neural network based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal .

In one embodiment, the noise phase feature information includes position information of abnormal peaks and/or valleys in the phase spectrum.

In one embodiment, the noise amplitude feature information includes position information of abnormal amplitude points in the amplitude spectrum.

In one embodiment, the removing the noise signal spectrum in the signal spectrum based on the noise phase feature information and the noise amplitude feature information to obtain a target signal spectrum includes:

determining a phase spectrum of a noise signal in the phase spectrum based on location information of abnormal peaks and/or troughs in the phase spectrum;

determining the noise signal amplitude spectrum in the amplitude spectrum based on the abnormal amplitude point position information in the amplitude spectrum;

determining a noise signal spectrum based on the noise signal phase spectrum and the noise signal amplitude spectrum;

removing the noise signal spectrum from the signal spectrum to obtain the target signal spectrum.

It should be noted that although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that these steps must be performed in this specific order, or that all shown steps must be performed to achieve achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution, etc. In addition, it is easy to understand that these steps may be executed synchronously or asynchronously in multiple modules/processes/threads, for example.

An electronic device 600 according to this embodiment of the present invention is described below with reference to FIG. 5 . The electronic device may be a water control device on the Christmas tree, and the electronic device 600 shown in FIG. 5 is only an example, and should not impose any limitation on the function and application scope of the embodiment of the present invention.

As shown in FIG. 5, electronic device 600 takes the form of a general-purpose computing device. Components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different system components (including the storage unit 620 and the processing unit 610), a display unit 640, and the like.

Wherein, the storage unit stores program codes, and the program codes can be executed by the processing unit 610, so that the processing unit 610 executes various exemplary implementations according to the present invention described in the above-mentioned method embodiments of this specification. A step of.

The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 6201 and/or a cache storage unit 6202 , and may further include a read-only storage unit (ROM) 6203 .

The storage unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include the implementation of the network environment.

Bus 630 may represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local area using any of a variety of bus structures. bus. Electronic device 600 may communicate with one or more external devices 700 (eg, an underwater control module).

Through the description of the above implementations, those skilled in the art can easily understand that the example implementations described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of software products, and the software products can be stored in a non-volatile storage medium (which can be CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to make a computing device (which may be a personal computer, a server, or a network device, etc.) execute the method steps according to the above-mentioned embodiments of the embodiments of the present disclosure.

It should be noted that in this article, relative terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply these No such actual relationship or order exists between entities or operations. Furthermore, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus comprising a set of elements includes not only those elements, but also includes elements not expressly listed. other elements of or also include elements inherent in such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising said element.

The above descriptions are only specific implementation manners of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A marine underwater Christmas tree device, comprising an underwater control module, is characterized in that, also includes: A signal acquisition module, configured to acquire the communication signal sent by the underwater control module; A signal conversion module, configured to perform Fourier transform processing on the communication signal to obtain a signal spectrum, the signal spectrum includes a phase spectrum and an amplitude spectrum; A signal processing module, configured to input the phase spectrum into the first model to obtain noise phase feature information, and simultaneously input the amplitude spectrum into the second model to obtain noise amplitude feature information, based on the noise phase feature information and noise The amplitude feature information removes the noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and performs inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein the first model is based on a sample communication signal The phase spectrum and the noise features in the extracted phase spectrum of the sample communication signal are obtained by training the neural network, and the second model is based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal obtained by training the neural network. 2 . The marine subsea Christmas tree device according to claim 1 , wherein the noise phase feature information includes position information of abnormal peaks and/or troughs in the phase spectrum. 3 . 3 . The marine subsea Christmas tree device according to claim 2 , wherein the noise amplitude feature information includes position information of abnormal amplitude points in the amplitude spectrum. 4 . 4. The marine underwater Christmas tree device according to claim 3, wherein the noise signal spectrum in the signal spectrum is removed based on the noise phase feature information and the noise amplitude feature information to obtain the target signal spectrum ,include: determining a phase spectrum of a noise signal in the phase spectrum based on location information of abnormal peaks and/or troughs in the phase spectrum; determining the noise signal amplitude spectrum in the amplitude spectrum based on the abnormal amplitude point position information in the amplitude spectrum; determining a noise signal spectrum based on the noise signal phase spectrum and the noise signal amplitude spectrum; removing the noise signal spectrum from the signal spectrum to obtain the target signal spectrum. 5. The marine underwater Christmas tree device according to any one of claims 1 to 4, further comprising: An information acquisition module, configured to acquire marine environment information in the operating area of the subsea tree device; The information processing module is used to determine the safety risk level in the marine environment based on the marine environment information, and when the safety risk level is greater than the preset risk level, generate an alarm message and send it to the Christmas tree operation monitoring platform. 6. The marine underwater Christmas tree device according to claim 5, wherein the marine environment information at least includes the temperature of seawater at different depths in the working area of the underwater Christmas tree device and the temperature of the underwater Christmas tree device. Combustible gas concentration in the work area. 7. The marine submerged Christmas tree device according to any one of claims 1-4, wherein the communication signal comprises an acoustic wave communication signal. 8. The marine underwater Christmas tree device according to any one of claims 1 to 4, wherein the signal acquisition module, the signal conversion module and the signal processing module are integrated on the same control circuit board, and the control circuit A plate is located above water of the subsea tree arrangement. 9. A computer-readable storage medium on which a computer program is stored, wherein the computer program is executed by a processor to implement the following steps: Obtaining a communication signal sent by a subsea control module of the subsea tree device; performing Fourier transform processing on the communication signal to obtain a signal spectrum, where the signal spectrum includes a phase spectrum and an amplitude spectrum; inputting the phase spectrum into the first model to obtain noise phase characteristic information, and simultaneously inputting the amplitude spectrum into the second model to obtain noise magnitude characteristic information, and removing all The noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and perform inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein, the first model is based on the phase spectrum of the sample communication signal and the extracted samples The noise feature in the phase spectrum of the communication signal is obtained by training the neural network, and the second model is obtained by training the neural network based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal . 10. An electronic device, characterized in that it comprises: processor; and memory for storing computer programs; Wherein, the processor is configured to perform the following steps by executing the computer program: Obtaining a communication signal sent by a subsea control module of the subsea tree device; performing Fourier transform processing on the communication signal to obtain a signal spectrum, where the signal spectrum includes a phase spectrum and an amplitude spectrum; inputting the phase spectrum into the first model to obtain noise phase characteristic information, and simultaneously inputting the amplitude spectrum into the second model to obtain noise magnitude characteristic information, and removing all The noise signal spectrum in the signal spectrum to obtain the target signal spectrum, and perform inverse Fourier transform processing on the target signal spectrum to obtain the target signal; wherein, the first model is based on the phase spectrum of the sample communication signal and the extracted samples The noise feature in the phase spectrum of the communication signal is obtained by training the neural network, and the second model is obtained by training the neural network based on the amplitude spectrum of the sample communication signal and the noise feature in the extracted amplitude spectrum of the sample communication signal .

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