A natural gas CO2 removal self-diagnosis method, system, equipment and medium

Abstract

The present application discloses a natural gas de-CO2 self-diagnosis method, system, equipment and medium, which relates to the field of natural gas purification technology. The method includes: obtaining the CO2 content and monitoring parameter data in the purified gas; when the CO2 content in the purified gas is greater than a preset threshold, calling the device abnormality database; traversing the device abnormality database, searching for data in the monitoring parameter data that exceeds the parameter variation range of the corresponding influencing factors, obtaining the corresponding influencing reasons and fault codes, and generating an abnormal data set; generating a first warning message based on the abnormal data set. The present application searches the device abnormality database for data that exceeds the corresponding parameter variation range of the monitoring parameter data, generates an abnormal data set based on the influencing reasons and fault codes corresponding to the data, and then generates a first warning message to prompt the staff to repair, without stopping the machine for manual troubleshooting operations, quickly locate the abnormal position, and improve the decarbonization efficiency.

Description

Technical Field

[0001] The present application generally relates to the field of natural gas purification technology, and specifically to a natural gas CO2 removal self-diagnosis method, system, equipment and medium. Background Art

[0002] As a hydrocarbon gas mixture, natural gas contains more than 90% methane, as well as a small amount of carbon 2, carbon 3 and carbon 4 alkanes and acid gases such as CO2 and H2S. The hazards of CO2 in natural gas are mainly the following three points: 1. It seriously affects the calorific value and transportation performance of natural gas; 2. It causes pipeline blockage; 3. It causes pipeline corrosion. At present, the commonly used decarbonization methods at home and abroad include low-temperature separation, membrane separation, adsorption separation, solvent absorption, and the combined separation method of the above methods.

[0003] However, in the actual decarbonization process, the CO2 concentration in the final purified gas may be abnormal, but the staff cannot quickly know the cause of the abnormality or the location of the fault. They need to shut down the entire system for testing and inspection one by one. This method is not only time-consuming and labor-intensive, but also affects the decarbonization efficiency. Therefore, we propose a natural gas deCO2 self-diagnosis method, system, equipment and medium to solve the above problems. Summary of the invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a natural gas CO2 removal self-diagnosis method, system, equipment and medium that can quickly locate abnormal positions and improve decarbonization efficiency and quality.

[0005] In the first aspect, the present application provides a natural gas CO2 removal self-diagnosis method, which is applied to a natural gas CO2 removal device, wherein the natural gas CO2 removal device at least comprises: an absorption tower, wherein the absorption tower has a feed port and a discharge port; the feed port is connected to a feed unit, and the feed unit is used to transport natural gas and decarbonization slurry into the absorption tower; a control unit is also provided between the feed unit and the feed port, which is used to control the on-off of the feed unit and the feed port; the discharge port is used to discharge purified gas; the method comprises the following steps:

[0006] Obtaining the CO2 content and monitoring parameter data in the purified gas; the monitoring parameter data include: the pressure, displacement, differential pressure of the natural gas and the decarbonized slurry at the feed inlet, and the temperature, pressure, and displacement of the purified gas at the discharge port;

[0007] When the CO2 content in the purified gas is greater than a preset threshold, the device abnormality database is called; the device abnormality database at least includes: multiple influencing factors and parameter variation ranges, influencing causes, and fault codes corresponding to each of the influencing factors;

[0008] Traversing the device abnormality database, searching for data in the monitoring parameter data that exceeds the parameter variation range of the corresponding influencing factor, and obtaining the corresponding influencing cause and fault code, and generating an abnormal data set; the abnormal data set includes: at least one abnormal parameter data and the corresponding abnormal cause and abnormal code;

[0009] A first warning message is generated based on the abnormal data set; the first warning message is used to prompt the staff to perform maintenance.

[0010] According to the technical solution provided by this application, the following steps are also included:

[0011] Acquire a fault processing database; the fault processing database at least includes: multiple fault codes and corresponding processing measures;

[0012] Traversing the fault processing database, searching for fault codes in the fault processing database and corresponding to the abnormal codes in the abnormal data set, and obtaining corresponding processing measures;

[0013] First processing information is generated according to the abnormal code and the corresponding processing measures; the first processing information is used to guide the staff to perform corresponding maintenance operations.

[0014] According to the technical solution provided by the present application, generating first processing information according to the abnormal code and the corresponding processing measure specifically includes the following steps:

[0015] Obtain the influence ratios of the influencing factors corresponding to all the abnormal codes, and divide the abnormal codes into queues of different levels according to the priorities of the influence ratios to obtain queue information; the queue information at least includes: a first-level queue and a second-level queue arranged in descending order of priority;

[0016] When there are at least two abnormal codes in the same level queue, the abnormal codes are sorted in descending order according to the corresponding impact proportions to obtain an abnormal sequence;

[0017] First processing information is generated according to the queue information and the exception sequence.

[0018] According to the technical solution provided by the present application, the abnormal codes are divided into queues of different levels according to the priority of the impact ratio, which specifically includes the following steps:

[0019] When the impact ratio is greater than or equal to the preset ratio, the abnormal code corresponding to the impact ratio is classified into the first-level queue;

[0020] When the impact ratio is less than the preset ratio, the abnormal code corresponding to the impact ratio is classified into the second-level queue.

[0021] According to the technical solution provided in this application, obtaining the CO2 content and monitoring parameter data in the purified gas specifically includes the following steps:

[0022] Acquire the status information of the natural gas CO2 removal device; the status information at least includes: compressor status information, slurry pump status information, lean liquid cooler status information, cooling fan status information;

[0023] When the status information of the natural gas CO2 removal device meets the preset conditions, a first prompt information is generated, and the CO2 content and monitoring parameter data in the purified gas are obtained.

[0024] In a second aspect, the present application provides a natural gas CO2 removal self-diagnosis system, which can implement the above-mentioned natural gas CO2 removal self-diagnosis method, and the system includes:

[0025] A data acquisition unit, the data acquisition unit is configured to obtain the CO2 content in the purified gas and monitoring parameter data; the monitoring parameter data includes: the pressure, displacement, differential pressure of the natural gas and the decarbonized slurry at the feed inlet and the temperature, pressure, displacement of the purified gas at the discharge port;

[0026] A data processing unit, wherein the data processing unit is configured to call a device abnormality database when the CO2 content in the purified gas is greater than a preset threshold; the device abnormality database at least includes: multiple influencing factors and parameter change ranges, influencing causes, and fault codes corresponding to each of the influencing factors; traverse the device abnormality database, search for data in the monitoring parameter data that exceeds the parameter change range of the corresponding influencing factor, and obtain the corresponding influencing causes and fault codes, and generate an abnormal data set; the abnormal data set includes: at least one abnormal parameter data and the corresponding abnormal cause and abnormal code; generate a first warning message based on the abnormal data set; the first warning message is used to prompt the staff to repair.

[0027] The technical solution provided by this application also includes:

[0028] A display module, wherein the display module is configured to display the first warning information in real time.

[0029] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned natural gas CO2 removal self-diagnosis method when executing the computer program.

[0030] In a fourth aspect, the present application 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 steps of the natural gas CO2 removal self-diagnosis method as described above are implemented.

[0031] It can be seen from the above technical solution that the present application has at least the following beneficial effects:

[0032] The present application discloses a natural gas CO2 removal self-diagnosis method, which includes: obtaining the CO2 content and monitoring parameter data in the purified gas, wherein the monitoring parameter data includes the pressure, displacement, differential pressure of the natural gas and the decarbonized slurry at the feed port of the natural gas CO2 removal device and the temperature, pressure, and displacement of the purified gas at the discharge port of the natural gas CO2 removal device; when the CO2 content in the purified gas is greater than a preset threshold, calling the device abnormality database, wherein the device abnormality database includes at least a plurality of influencing factors and a parameter variation range, an influencing cause, and a fault code corresponding to each influencing factor; further, traversing the device abnormality database, searching for data that exceeds the parameter variation range of the corresponding influencing factor in the monitoring parameter data summary, and obtaining the corresponding influencing cause and fault code, and generating an abnormal data set, wherein the abnormal data set includes: at least one abnormal parameter data and a corresponding abnormal cause and abnormal code; generating a first warning message based on the abnormal data set, using the first warning message to quickly locate the abnormal position, and prompting the staff to perform maintenance.

[0033] The method quickly locates the abnormal position of the natural gas CO2 removal device through the above steps. Compared with the traditional method of shutting down to test and inspect each component one by one, the present application obtains the CO2 content in the purified gas in real time. When the CO2 content in the purified gas is greater than a preset threshold, the device abnormality database is searched for data whose monitoring parameter data exceeds the corresponding parameter variation range, and an abnormal data set is generated based on the influencing cause and fault code corresponding to the data, that is, the abnormal position is quickly located, and then a first warning message is generated based on this abnormal data set to prompt the staff to perform maintenance. There is no need to shut down for manual troubleshooting operations, the abnormal position is quickly located, and the decarbonization efficiency is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Other features, objects and advantages of the present application will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings.

[0035] Figure 1 This is a flow chart of the self-diagnosis method for removing CO2 from natural gas.

[0036] Figure 2 A flowchart to guide staff in performing maintenance operations.

[0037] Figure 3A schematic diagram of a flow chart for generating first processing information.

[0038] Figure 4 This is a schematic diagram of the structure of the natural gas CO2 removal system.

[0039] Figure 5 A schematic diagram of the structure of an electronic device.

[0040] Numbers in the figure: 1, data acquisition unit; 2, data processing unit; 3, display module; 20, data transmission module; 21, data analysis module; 22, control module;

[0041] 500. Electronic device; 501. CPU; 502. ROM; 503. RAM; 504. Bus; 505. I / O interface; 506. Input part; 507. Output part; 508. Storage part; 509. Communication part; 510. Drive; 511. Removable media. DETAILED DESCRIPTION

[0042] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0043] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0044] A natural gas CO2 removal self-diagnosis method provided in the present application is applied to a natural gas CO2 removal device, which at least includes: an absorption tower, the absorption tower has a feed port and a discharge port; the feed port is connected to a feed unit, the feed unit is used to transport natural gas and decarbonization slurry into the absorption tower; a control unit is also provided between the feed unit and the feed port, which is used to control the on and off of the feed unit and the feed port; the discharge port is used to discharge purified gas.

[0045] In order to make the technical solution of the present application clearer and easier to understand, the natural gas CO2 removal self-diagnosis method provided by the embodiment of the present application is introduced below in conjunction with the accompanying drawings. Figure 1 As shown, this figure is a schematic diagram of the process of the natural gas CO2 removal self-diagnosis method provided in an embodiment of the present application, and the method includes the following steps:

[0046] S100, obtaining the CO2 content in the purified gas and monitoring parameter data; the monitoring parameter data include: the pressure, displacement, differential pressure of the natural gas and the decarbonized slurry at the feed inlet, and the temperature, pressure, and displacement of the purified gas at the discharge port.

[0047] The process of obtaining the CO2 content and monitoring parameter data in the purified gas specifically includes the following steps:

[0048] Obtaining status information of the natural gas CO2 removal device; the status information at least includes: compressor status information, slurry pump status information, lean liquid cooler status information, and cooling fan status information;

[0049] When the status information of the natural gas CO2 removal device meets the preset conditions, the first prompt information is generated, and the CO2 content and monitoring parameter data in the purified gas are obtained.

[0050] It should be noted that the preset condition means that the compressor is in the on state, the slurry pump is in the on state, the lean liquid cooler is in the on state, and the cooling fan is in the on state. When the compressor, slurry pump, lean liquid cooler and cooling fan of the natural gas CO2 removal device are all in the on state, the CO2 content and monitoring parameter data in the purified gas can be obtained, and the first prompt information is generated. This first prompt information is used to indicate that the current natural gas CO2 removal device is in a normal operating environment, and the device can be monitored to find out whether the device has a fault.

[0051] Here, decarbonization slurry refers to a slurry used to capture CO2, such as Metal-Organic Frameworks (MOFS) slurry. The CO2 content in the purified gas can be obtained using a CO2 analyzer; the pressure of the natural gas and the decarbonization slurry at the feed port, as well as the pressure of the purified gas at the discharge port can be collected using a pressure sensor; the displacement of the natural gas and the decarbonization slurry at the feed port, as well as the displacement of the purified gas at the discharge port can be collected using a flow sensor; the temperature of the purified gas at the discharge port can be collected using a temperature sensor. The differential pressure refers to the difference between the pressure of the raw gas at the feed port and the pressure at the top of the absorption tower.

[0052] S200. When the CO2 content in the purified gas is greater than a preset threshold, the device abnormality database is called; the device abnormality database at least includes: multiple influencing factors and the parameter variation range, influencing cause, and fault code corresponding to each influencing factor.

[0053] It should be noted that the preset threshold refers to the ratio of the volume fraction of CO 2 at the outlet of the absorption tower to the total amount of purified gas at the outlet, for example, 3%.

[0054] Among them, the device abnormality database is shown in Table 1.

[0055] Table 1 Device abnormality database

[0056]

[0057] Furthermore, the meaning of each fault code is shown in Table 2.

[0058] Table 2 Meaning of fault codes

[0059] serial number Fault Codes Fault Description grade #1 P0105 Raw gas pressure sensor failure CLASS3 #2 P0106 Adsorption tower temperature sensor failure CLASS3 #3 P0107 Lean liquid cooler failure CLASS3 #4 P0108 Air cooler unit 1#-6# fault CLASS3 #5 P0109 Air-cooled unit RTD sensor abnormality CLASS3 #6 P0110 Lean liquid heat exchanger RTD sensor abnormality CLASS3 #7 P0111 Lean liquid heat exchanger device failure CLASS3 #8 P0112 The tower body RTD temperature sensor is abnormal CLASS3 #9 P0113 Slurry pump failure CLASS3 #10 P0114 Slurry pump inverter failure CLASS3 #11 P0115 Pipeline freezing CLASS2

[0060] It should be noted that one influencing factor can correspond to multiple fault codes, that is, the cause of the change of an influencing factor can be caused by the failure of different components, while one fault code only indicates one component failure. Here, the level in Table 2 refers to the priority level of the processing order of these fault locations when there are multiple faults, CLASS3>CLASS2. Among them, there is no corresponding fault code for the CO2 concentration meter fault in Table 2, because the CO2 concentration meter is not a component of the natural gas de-CO2 device. "RTD" in Table 2 is the abbreviation of Resistance Temperature Detector, which refers to a resistance temperature detector, or RTD for short.

[0061] In addition, when the CO2 content in the purified gas is less than or equal to the preset threshold, it indicates that there is no abnormality in the current natural gas deCO2 device and the decarbonization operation can be performed normally.

[0062] S300, traverse the device abnormality database, search for data in the monitoring parameter data that exceeds the parameter change range of the corresponding influencing factor, and obtain the corresponding influencing cause and fault code, and generate an abnormal data set; the abnormal data set includes: at least one abnormal parameter data and the corresponding abnormal cause and abnormal code.

[0063] Specifically, the device abnormality database in Table 1 is traversed, and the data in the monitoring parameter data that exceeds the parameter change range of the corresponding influencing factor is searched in Table 1, and the corresponding influencing cause and fault code are obtained, and an abnormal data set is constructed. For example, the displacement of the decarbonization slurry at the feed inlet is greater than 7 cubic meters / hour, which exceeds the parameter change range recorded in Table 1. The corresponding influencing cause is the slurry pump failure, and the corresponding fault code is P0113, P0114, P0115; accordingly, the abnormal data set is: (displacement of the decarbonization slurry at the feed inlet, slurry pump failure, P0113, P0114, P0115).

[0064] S400. Generate a first warning message based on the abnormal data set; the first warning message is used to prompt the staff to perform maintenance.

[0065] Here, the first warning information can be displayed on the display screen to allow the staff to obtain the cause of the fault and the fault code. According to the fault code and the information in Table 2, the fault location can be quickly located, eliminating the need for shutdown and troubleshooting operations, while improving the decarbonization efficiency.

[0066] Furthermore, if Figure 2 As shown, the method further comprises the following steps:

[0067] S500, obtaining a fault processing database; the fault processing database at least includes: a plurality of fault codes and corresponding processing measures.

[0068] Among them, the fault processing database is shown in Table 3.

[0069] Table 3 Fault handling database

[0070] Fault Codes Treatment measures P0105 Replace the raw gas pressure sensor P0106 Replace the adsorption tower temperature sensor P0107 Switch to standby air cooler P0108 Repair air cooler units 1#-6# P0109 Replace the RTD sensor of the air-cooled unit P0110 Replace the lean liquid heat exchanger RTD sensor P0111 Repair of lean liquid heat exchanger P0112 Replace the tower RTD temperature sensor P0113 Repair slurry pump P0114 Replace the slurry pump inverter P0115 Cleaning the pipes

[0071] S600 , traverse the fault processing database, search for the fault code corresponding to the abnormal code in the fault processing database and the abnormal data set, and obtain the corresponding processing measures.

[0072] Specifically, the fault handling database in Table 3 is traversed to find the fault code corresponding to the abnormal code in Table 3 and the abnormal data set, and the corresponding treatment measures are obtained. For example, the abnormal codes are P0113, P0114, and P0115, and the corresponding treatment measures are to repair the slurry pump, replace the slurry pump inverter, and clean the pipeline.

[0073] S700. Generate first processing information according to the abnormality code and the corresponding processing measures; the first processing information is used to guide the staff to perform corresponding maintenance operations.

[0074] Specifically, Figure 3 As shown, generating first processing information according to the abnormal code and the corresponding processing measures specifically includes the following steps:

[0075] S701. Obtain the influence ratios of the influencing factors corresponding to all the abnormal codes, and classify the abnormal codes into queues of different levels according to the priorities of the influence ratios to obtain queue information; the queue information at least includes: a first-level queue and a second-level queue arranged from high to low priority.

[0076] Among them, the impact ratio can be obtained by statistics and calculation based on the actual number of adjustments during the actual operation on site. For example, the impact of the natural gas discharge at the feed inlet accounts for 13%, the impact of the pressure of the natural gas and decarbonization slurry at the feed inlet accounts for 24%, the impact of the temperature of the purified gas at the discharge port accounts for 18%, the impact of the decarbonization slurry discharge at the feed inlet accounts for 22%, the impact of the carbon dioxide concentration of the raw gas accounts for 21%, and the impact of the differential pressure level accounts for 4%.

[0077] Among them, the exception codes are divided into queues of different levels according to the priority of the impact ratio, which specifically includes the following steps:

[0078] When the impact ratio is greater than or equal to the preset ratio, the exception code corresponding to the impact ratio is divided into the first-level queue;

[0079] When the impact ratio is less than the preset ratio, the abnormal code corresponding to the impact ratio is divided into the second-level queue.

[0080] Here, the preset proportion is, for example, 10%, which can be adjusted according to actual needs. The level of the first-level queue is higher than the level of the second-level queue. When the two queues appear at the same time, the fault in the first-level queue is processed first.

[0081] S702: When there are at least two exception codes in the same-level queue, the exception codes are sorted in descending order according to their corresponding impact proportions to obtain an exception sequence.

[0082] Among them, the staff can repair the device according to the order of the abnormal sequence in the same level queue, giving priority to handling faults with greater impact.

[0083] S703: Generate first processing information according to the queue information and the exception sequence.

[0084] The first processing information is used to guide the staff to repair the device, which speeds up the maintenance efficiency and can also improve the decarbonization efficiency to a certain extent.

[0085] like Figure 4 As shown, the present application provides a natural gas CO2 removal self-diagnosis system, which can implement the above-mentioned natural gas CO2 removal self-diagnosis method, and the system includes:

[0086] Data acquisition unit 1, data acquisition unit 1 is configured to obtain CO2 content and monitoring parameter data in the purified gas; the monitoring parameter data include: pressure, displacement, differential pressure of natural gas and decarbonized slurry at the feed inlet, and temperature, pressure, displacement of purified gas at the discharge port;

[0087] Data processing unit 2, data processing unit 2 is configured to call the device abnormality database when the CO2 content in the purified gas is greater than a preset threshold; the device abnormality database includes at least: multiple influencing factors and the parameter change range, influencing cause, and fault code corresponding to each influencing factor; traverse the device abnormality database, find the data in the monitoring parameter data that exceeds the parameter change range of the corresponding influencing factor, and obtain the corresponding influencing cause and fault code, and generate an abnormal data set; the abnormal data set includes: at least one abnormal parameter data and the corresponding abnormal cause and abnormal code; generate a first warning message based on the abnormal data set; the first warning message is used to prompt the staff to repair.

[0088] Among them, the data processing unit 2 includes: a data transmission module 20, a data analysis module 21 and a control module 22. The data transmission module 20 is used to receive the CO2 content and monitoring parameter data in the purified gas; the data analysis module 21 is used to call the device abnormality database when the CO2 content in the purified gas is greater than a preset threshold; traverse the device abnormality database, search for data in the monitoring parameter data that exceeds the parameter change range of the corresponding influencing factor, and obtain the corresponding influencing cause and fault code, and generate an abnormal data set; based on the abnormal data set, generate a first warning message; the control module 22 is used to send the first warning message to the display module 3.

[0089] Furthermore, the system also includes: a display module 3, and the display module 3 is configured to display the first warning information in real time.

[0090] The present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of a natural gas CO2 removal self-diagnosis method as described in the above embodiment are implemented.

[0091] Among them, Figure 5 As shown, electronic device 500 includes CPU 501, which can perform various appropriate actions and processes according to the program stored in ROM 502 or the program loaded from the storage part into RAM 503. Various programs and data required for system operation are also stored in RAM 503. CPU 501, ROM 502 and RAM 503 are connected to each other through bus 504. I / O interface 505 is also connected to bus 504.

[0092] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage section 508 as needed.

[0093] In particular, according to the embodiments of the present application, the above reference process Figure 1The described process can be implemented as a computer software program. For example, the present application includes a computer program product, which includes a computer program carried on a computer readable medium, and the computer program contains program code for executing the method shown in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium. When the computer program is executed by CPU501, the above-mentioned functions defined in the system of the present application are executed.

[0094] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-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 of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a RAM (random access memory), a ROM (read-only memory), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0095] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that 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 boxes represented in succession 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 or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0096] The units involved in the embodiments described in the present application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not constitute limitations on the units themselves under certain circumstances. The units or modules described may also be set in a processor.

[0097] The present application also provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements a natural gas CO2 removal self-diagnosis method as described in the above embodiment.

[0098] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the present application.

Claims

1. A natural gas CO2 removal self-diagnosis method, applied to a natural gas CO2 removal device, the natural gas CO2 removal device at least comprising: An absorption tower, the absorption tower is provided with a feed port and a discharge port; the feed port is connected to a feed unit, the feed unit is used to transport natural gas and decarbonized slurry into the absorption tower; a control unit is also provided between the feed unit and the feed port, which is used to control the on-off of the feed unit and the feed port; the discharge port is used to discharge the purified gas; characterized in that the method comprises the following steps: Obtaining the CO2 content and monitoring parameter data in the purified gas; the monitoring parameter data include: the pressure, displacement, differential pressure of the natural gas and the decarbonized slurry at the feed inlet, and the temperature, pressure, and displacement of the purified gas at the discharge port; When the CO2 content in the purified gas is greater than a preset threshold, the device abnormality database is called; the device abnormality database at least includes: multiple influencing factors and parameter variation ranges, influencing causes, and fault codes corresponding to each of the influencing factors; Traversing the device abnormality database, searching for data in the monitoring parameter data that exceeds the parameter variation range of the corresponding influencing factor, and obtaining the corresponding influencing cause and fault code, and generating an abnormal data set; the abnormal data set includes: at least one abnormal parameter data and the corresponding abnormal cause and abnormal code; Generate a first warning message according to the abnormal data set; the first warning message is used to prompt the staff to repair; The following steps are also included: Acquire a fault processing database; the fault processing database at least includes: multiple fault codes and corresponding processing measures; Traversing the fault processing database, searching for fault codes in the fault processing database and corresponding to the abnormal codes in the abnormal data set, and obtaining corresponding processing measures; Generate first processing information according to the abnormality code and the corresponding processing measure; the first processing information is used to guide the staff to perform corresponding maintenance operations; Generating first processing information according to the abnormal code and the corresponding processing measure specifically includes the following steps: Obtain the influence ratios of the influencing factors corresponding to all the abnormal codes, and divide the abnormal codes into queues of different levels according to the priorities of the influence ratios to obtain queue information; the queue information at least includes: a first-level queue and a second-level queue arranged in descending order of priority; When there are at least two abnormal codes in the same level queue, the abnormal codes are sorted in descending order according to the corresponding impact proportions to obtain an abnormal sequence; Generate first processing information according to the queue information and the exception sequence; The abnormal codes are divided into queues of different levels according to the priority of the impact ratio, specifically including the following steps: When the impact ratio is greater than or equal to the preset ratio, the abnormal code corresponding to the impact ratio is classified into the first-level queue; When the impact ratio is less than the preset ratio, the abnormal code corresponding to the impact ratio is classified into the second-level queue.

2. A natural gas CO2 removal self-diagnosis method according to claim 1, characterized in that: Obtaining the CO2 content and monitoring parameter data in the purified gas includes the following steps: Acquire the status information of the natural gas CO2 removal device; the status information at least includes: compressor status information, slurry pump status information, lean liquid cooler status information, cooling fan status information; When the status information of the natural gas CO2 removal device meets the preset conditions, a first prompt information is generated, and the CO2 content and monitoring parameter data in the purified gas are obtained.

3. A natural gas CO2 removal self-diagnosis system, capable of implementing the natural gas CO2 removal self-diagnosis method according to claim 1 or 2, characterized in that: The system comprises: A data acquisition unit, the data acquisition unit is configured to obtain the CO2 content in the purified gas and monitoring parameter data; the monitoring parameter data includes: the pressure, displacement, differential pressure of the natural gas and the decarbonized slurry at the feed inlet and the temperature, pressure, displacement of the purified gas at the discharge port; A data processing unit, wherein the data processing unit is configured to call a device abnormality database when the CO2 content in the purified gas is greater than a preset threshold; the device abnormality database at least includes: multiple influencing factors and parameter change ranges, influencing causes, and fault codes corresponding to each of the influencing factors; traverse the device abnormality database, search for data in the monitoring parameter data that exceeds the parameter change range of the corresponding influencing factor, and obtain the corresponding influencing causes and fault codes, and generate an abnormal data set; the abnormal data set includes: at least one abnormal parameter data and the corresponding abnormal cause and abnormal code; generate a first warning message based on the abnormal data set; the first warning message is used to prompt the staff to repair.

4. A natural gas CO2 removal self-diagnosis system according to claim 3, characterized in that: Also includes: A display module, wherein the display module is configured to display the first warning information in real time.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the natural gas CO2 removal self-diagnosis method as claimed in claim 1 or 2 are implemented.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the natural gas CO2 removal self-diagnosis method as claimed in claim 1 or 2 are implemented.

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