A maintenance method and system for a liquid hydrogen refueling station

Abstract

The present invention provides a maintenance method and system for a liquid hydrogen refueling station. The method includes: obtaining pressure sensor data of the pressure vessel and pipeline system of the liquid hydrogen refueling station, inputting the pressure sensor data into a deep analysis model, and obtaining a pressure anomaly value; if the pressure anomaly value is lower than a first threshold, obtaining historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station, and predicting several maintenance time periods based on the historical hydrogenation data and the historical hydrogen replenishment data; wherein the remaining amount of liquid hydrogen in the pressure vessel in each maintenance time period is lower than a second threshold; outputting each maintenance time period to the maintenance personnel, so that the maintenance personnel can select any maintenance time period to maintain the pressure vessel and pipeline system. The present invention predicts the maintenance time period with the least remaining amount of liquid hydrogen, which can effectively reduce the maintenance cost of the liquid hydrogen refueling station.

Description

Technical Field

[0001] The present invention relates to the technical field of liquid hydrogen safety management, and in particular to a maintenance method, system, electronic equipment and computer storage medium for a liquid hydrogen refueling station. Background Art

[0002] Liquid hydrogen refueling is an efficient way to utilize hydrogen energy. It has the characteristics of high energy density and low storage temperature, and is an important direction for the future development of hydrogen energy. Liquid hydrogen refueling stations are equipped with pressure vessels and pipeline systems designed specifically for hydrogen. Various monitoring sensors and pressure control systems are also installed to monitor the pressure in the pressure vessels and pipeline systems, and strictly control the pressure not to exceed the maximum allowable working pressure of the equipment and pipelines.

[0003] However, when abnormal pressure occurs in the pressure vessel and pipeline system of the liquid hydrogen refueling station, it is necessary to stop the operation for maintenance. For example, when a pressure vessel fails, it is sometimes necessary to drain the liquid hydrogen in the pressure vessel so that the inside of the pressure vessel can be carefully inspected manually or by an automatic robot. This requires transferring the remaining liquid hydrogen to other liquid hydrogen containers, and draining the liquid hydrogen takes a long time, which causes the liquid hydrogen refueling station to suspend operations for a long time, resulting in greater economic losses.

[0004] It can be seen that how to determine the appropriate maintenance strategy to reduce the maintenance cost of liquid hydrogen refueling stations is a technical problem that needs to be solved urgently. Summary of the invention

[0005] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a maintenance method, system, electronic equipment, computer storage medium and computer program product of a liquid hydrogen refueling station.

[0006] The present invention provides a maintenance method for a liquid hydrogen refueling station, the method comprising the following steps:

[0007] Obtaining pressure sensor data of a pressure vessel and a pipeline system of a liquid hydrogen refueling station, inputting the pressure sensor data into a deep analysis model, and obtaining a pressure anomaly value;

[0008] If the pressure abnormality value is lower than the first threshold, historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station are obtained, and a number of maintenance periods are predicted based on the historical hydrogenation data and the historical hydrogen replenishment data; wherein the remaining amount of liquid hydrogen in the pressure vessel in each of the maintenance periods is lower than the second threshold;

[0009] The maintenance time periods are output to the maintenance personnel so that the maintenance personnel can select any maintenance time period to perform maintenance on the pressure vessel and the pipeline system.

[0010] Preferably, the step of obtaining pressure sensing data of a pressure vessel and a pipeline system of a liquid hydrogen refueling station includes:

[0011] Obtain pressure sensing data of a pressure vessel and a pipeline system of a liquid hydrogen refueling station, and obtain flow rate data of an air inlet and an air outlet of the pressure vessel and the pipeline system, and add a static tag or a dynamic tag to the pressure sensing data according to the flow rate data.

[0012] Preferably, the step of inputting the pressure sensing data into a depth analysis model to obtain a pressure anomaly value includes:

[0013] If the label of the pressure sensing data is a static label, inputting the pressure sensing data into a first depth analysis model to obtain a first pressure anomaly value;

[0014] If the label of the pressure sensing data is a dynamic label, the pressure sensing data is input into the first depth analysis model and the second depth analysis model respectively, and the depth analysis results of the first depth analysis model and the second depth analysis model are fused to obtain a second pressure anomaly value.

[0015] Preferably, fusing the depth analysis results of the first depth analysis model and the second depth analysis model to obtain a second pressure anomaly value includes:

[0016] Determine the flow velocity magnitude of the flow velocity data, determine a first weight of the first depth analysis model according to the flow velocity magnitude, and determine a second weight of the second depth analysis model according to the first weight;

[0017] The second pressure abnormality value is obtained by weightedly averaging the pressure abnormality values ​​of the first depth analysis model and the second depth analysis model based on the first weight and the second weight.

[0018] Preferably, the predicting of several maintenance periods based on the historical hydrogenation data and the historical hydrogen replenishment data includes:

[0019] Liquid hydrogen consumption law data is obtained by fitting the historical hydrogenation data, and liquid hydrogen replenishment law data is obtained by fitting the historical hydrogen replenishment data; wherein both the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data correspond to the date attribute of the current date;

[0020] According to the current remaining amount of liquid hydrogen, the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data, a number of time periods in which the remaining amount of liquid hydrogen is lower than the second threshold are calculated, namely, a number of the maintenance time periods.

[0021] Preferably, the acquiring of historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station includes:

[0022] Obtain the number of liquid hydrogen refueling stations within the geographical range where the liquid hydrogen refueling station is located, and determine the duration coefficient according to the number of liquid hydrogen refueling stations according to a forward function;

[0023] Use the duration coefficient to multiply the first acquisition duration and the second acquisition duration respectively to obtain a third acquisition duration and a fourth acquisition duration;

[0024] The historical hydrogenation data related to the liquid hydrogen refueling station is acquired according to the third acquisition time, and the historical hydrogen replenishment data related to the liquid hydrogen refueling station is acquired according to the fourth acquisition time.

[0025] The present invention also provides a maintenance system for a liquid hydrogen refueling station, the system comprising an acquisition module, a prediction module, and a prompt module;

[0026] The acquisition module is used to acquire pressure sensor data of the pressure vessel and pipeline system of the liquid hydrogen refueling station, input the pressure sensor data into the deep analysis model, and obtain the pressure anomaly value;

[0027] The prediction module is used for obtaining historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station if the pressure abnormality value is lower than the first threshold, and predicting a number of maintenance periods according to the historical hydrogenation data and the historical hydrogen replenishment data; wherein the remaining amount of liquid hydrogen in the pressure vessel in each of the maintenance periods is lower than the second threshold;

[0028] The prompt module is used to output each maintenance period to the maintenance personnel, so that the maintenance personnel can select any maintenance period to perform maintenance on the pressure vessel and the pipeline system.

[0029] The present invention also provides an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute any of the methods described above.

[0030] The present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, any of the above methods is executed.

[0031] The present invention also provides a computer program product, wherein a computer program is stored in the computer program product, and when the computer program is executed, any of the above methods is implemented.

[0032] The beneficial effects of the present invention are:

[0033] 1. The design of the present invention predicts several maintenance periods based on the historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station. The maintenance period refers to the period when the remaining amount of liquid hydrogen in the pressure vessel is lower than a threshold value. When maintenance personnel perform maintenance on the pressure vessel and the pipeline system during such a maintenance period, the time used to empty the remaining liquid hydrogen can be reduced, the business suspension time caused by maintenance can be shortened, and the maintenance loss of the liquid hydrogen refueling station can be effectively reduced.

[0034] 2. The present invention also uses a pre-built deep analysis model to evaluate and analyze the pressure sensor data of the pressure vessel and pipeline system of the liquid hydrogen refueling station, and obtains the pressure anomaly value of the pressure vessel and pipeline system. When the pressure anomaly value is lower than the threshold, it means that there is an anomaly but the degree of anomaly is relatively mild. At this time, maintenance can be temporarily not performed, but a suitable maintenance opportunity can be found in the subsequent period. With this setting, the maintenance opportunity can be reasonably arranged, further reducing the maintenance loss of the liquid hydrogen refueling station. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 It is a flow chart of a maintenance method of a liquid hydrogen refueling station disclosed in an embodiment of the present invention.

[0037] Figure 2 It is a schematic diagram of a process for obtaining historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station disclosed in an embodiment of the present invention.

[0038] Figure 3 It is a structural schematic diagram of a maintenance system for a liquid hydrogen refueling station disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0040] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. 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.

[0041] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0042] In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. appear to indicate an orientation or position relationship, they are based on the orientation or position relationship shown in the accompanying drawings, or are the orientation or position relationship in which the product of the invention is usually placed when used. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0043] In addition, the terms “first”, “second”, etc., if used, are merely used to distinguish between the descriptions and should not be understood as indicating or implying relative importance.

[0044] It should be noted that, in the absence of conflict, the features in the embodiments of the present invention may be combined with each other.

[0045] like Figure 1 As shown, an embodiment of the present invention discloses a maintenance method for a liquid hydrogen refueling station, the method comprising the following steps:

[0046] Obtaining pressure sensor data of a pressure vessel and a pipeline system of a liquid hydrogen refueling station, inputting the pressure sensor data into a deep analysis model, and obtaining a pressure anomaly value;

[0047] If the pressure abnormality value is lower than the first threshold, historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station are obtained, and a number of maintenance periods are predicted based on the historical hydrogenation data and the historical hydrogen replenishment data; wherein the remaining amount of liquid hydrogen in the pressure vessel in each of the maintenance periods is lower than the second threshold;

[0048] The maintenance time periods are output to the maintenance personnel so that the maintenance personnel can select any maintenance time period to perform maintenance on the pressure vessel and the pipeline system.

[0049] In order to solve the problem that existing liquid hydrogen refueling stations need to suspend business to carry out maintenance on pressure vessels and pipeline systems, the present invention is designed to predict several maintenance periods based on historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station. The maintenance period refers to the period when the remaining amount of liquid hydrogen in the pressure vessel is lower than a threshold value. When maintenance personnel perform maintenance on the pressure vessel and the pipeline system during such a maintenance period, the time used to empty the remaining liquid hydrogen can be reduced, the business suspension time caused by maintenance can be shortened, and the maintenance loss of the liquid hydrogen refueling station can be effectively reduced.

[0050] At the same time, the present invention also uses a pre-built deep analysis model to evaluate and analyze the pressure sensor data of the pressure vessel and pipeline system of the liquid hydrogen refueling station, and obtains the pressure anomaly value of the pressure vessel and pipeline system. When the pressure anomaly value is lower than the threshold, it means that there is an abnormality but the degree of abnormality is relatively mild. At this time, maintenance can be temporarily not performed, but a suitable maintenance opportunity can be found in the subsequent period. With such a setting, the maintenance time can be reasonably arranged to further reduce the maintenance loss of the liquid hydrogen refueling station. Of course, when the pressure anomaly value is higher than the first threshold, it means that the degree of abnormality of the pressure vessel and pipeline system is relatively serious, and maintenance needs to be performed as soon as possible to avoid serious problems.

[0051] The Transformer model abandons the traditional recurrent neural network (RNN) structure and uses a self-attention mechanism to process sequence data. This mechanism allows the model to focus on all positions in the sequence simultaneously during encoding and decoding, thereby capturing long-distance dependencies. Therefore, the present invention preferably uses the Transformer model to construct a deep analysis model, so that the deep analysis model can identify slight anomalies in pressure vessels and pipeline systems, that is, obtain more accurate pressure anomaly values.

[0052] Preferably, the step of obtaining pressure sensing data of a pressure vessel and a pipeline system of a liquid hydrogen refueling station includes:

[0053] Obtain pressure sensing data of a pressure vessel and a pipeline system of a liquid hydrogen refueling station, and obtain flow rate data of an air inlet and an air outlet of the pressure vessel and the pipeline system, and add a static tag or a dynamic tag to the pressure sensing data according to the flow rate data.

[0054] In an embodiment of the present invention, the arranged sensors can monitor various points of the pressure vessel and pipeline system of the liquid hydrogen refueling station to obtain pressure sensing data. At the same time, the pressure sensing data may be obtained in a static state or a dynamic state. Specifically, the static state or the dynamic state can be determined according to the flow rate data of the air inlet and the air outlet of the pressure vessel and the pipeline system. When any flow rate data of the air inlet and the air outlet is greater than the flow rate threshold, it means that there is external hydrogenation and internal hydrogen replenishment operation, and this is the dynamic state. On the contrary, when any flow rate data is less than the flow rate threshold (for example, 0.002kg / min), it means that neither external hydrogenation nor internal hydrogen replenishment operation exists, and this is the static state. Correspondingly, a dynamic label or a static label is added to the obtained pressure sensing data. For the pressure sensing data in the dynamic state or the static state, the present invention adopts different depth analysis methods.

[0055] Preferably, the step of inputting the pressure sensing data into a depth analysis model to obtain a pressure anomaly value includes:

[0056] If the label of the pressure sensing data is a static label, inputting the pressure sensing data into a first depth analysis model to obtain a first pressure anomaly value;

[0057] If the label of the pressure sensing data is a dynamic label, the pressure sensing data is input into the first depth analysis model and the second depth analysis model respectively, and the depth analysis results of the first depth analysis model and the second depth analysis model are fused to obtain a second pressure anomaly value.

[0058] In an embodiment of the present invention, the depth analysis model of the present invention includes two models, namely, a first depth analysis model and a second depth analysis model. Among them, the first depth analysis model is obtained by training based on a training data set composed of pressure sensor data in a static state, and the second depth analysis model is obtained by training based on a training data set composed of pressure sensor data in a dynamic state. When it is determined that the label of the pressure sensor data monitored by the above method is a static label, the first depth analysis model can be directly used to perform an in-depth analysis on the pressure sensor data, so as to obtain the first pressure abnormality value corresponding to the pressure vessel and the pipeline system; and when it is determined that the label of the pressure sensor data monitored by the above method is a dynamic label, the first depth analysis model and the second depth analysis model are used at the same time to perform an in-depth analysis on the pressure sensor data, and then the analysis results of the two models are fused to obtain the second pressure abnormality value. Therefore, for the latter, the present invention uses both static and dynamic models to conduct a comprehensive analysis of the pressure sensor data, which is conducive to analyzing and obtaining a more accurate pressure abnormality value when the pressure abnormality value is low, that is, the abnormality degree of the pressure sensor data is low.

[0059] Preferably, fusing the depth analysis results of the first depth analysis model and the second depth analysis model to obtain a second pressure anomaly value includes:

[0060] Determine the flow velocity magnitude of the flow velocity data, determine a first weight of the first depth analysis model according to the flow velocity magnitude, and determine a second weight of the second depth analysis model according to the first weight;

[0061] The second pressure abnormality value is obtained by weightedly averaging the pressure abnormality values ​​of the first depth analysis model and the second depth analysis model based on the first weight and the second weight.

[0062] In an embodiment of the present invention, when the aforementioned determined flow rate is smaller, it means that the flow rate data of the air inlet and outlet of the current pressure vessel and pipeline system are closer to the static state. At this time, the first weight of the first depth analysis model corresponding to the static state is set to be larger, for example, 0.6, and the corresponding second weight of the second depth analysis model is 0.4; and when the aforementioned determined flow rate is larger, it means that the flow rate data of the air inlet and outlet of the current pressure vessel and pipeline system are approximately close to the dynamic state. At this time, the first weight of the first depth analysis model corresponding to the static state is set to be smaller, for example, 0.55, and the corresponding second weight of the second depth analysis model is 0.45. Finally, based on the obtained first weight and second weight, the pressure anomaly values ​​of the first depth analysis model and the second depth analysis model are weighted and averaged to obtain a more accurate second pressure anomaly value.

[0063] Preferably, the predicting of several maintenance periods based on the historical hydrogenation data and the historical hydrogen replenishment data includes:

[0064] Liquid hydrogen consumption law data is obtained by fitting the historical hydrogenation data, and liquid hydrogen replenishment law data is obtained by fitting the historical hydrogen replenishment data; wherein both the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data correspond to the date attribute of the current date;

[0065] According to the current remaining amount of liquid hydrogen, the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data, a number of time periods in which the remaining amount of liquid hydrogen is lower than the second threshold are calculated, namely, a number of the maintenance time periods.

[0066] In an embodiment of the present invention, historical hydrogenation data and historical hydrogen replenishment data can be obtained through big data capture and statistical analysis technology. The historical hydrogenation data reflects the law of hydrogen vehicles coming to the liquid hydrogen refueling station to refuel, that is, the daily liquid hydrogen consumption law of the liquid hydrogen refueling station, while the historical hydrogen replenishment data reflects the law of hydrogen tank trucks replenishing liquid hydrogen to the liquid hydrogen refueling station. By analyzing the law of liquid hydrogen consumption and replenishment, and based on the current remaining amount of liquid hydrogen in the liquid hydrogen refueling station, it is possible to calculate a number of time periods when the remaining amount of liquid hydrogen is lower than the second threshold, and these time periods are the best maintenance time periods. When maintenance personnel perform maintenance operations during these maintenance time periods, due to the small amount of liquid hydrogen remaining in the tank, the time taken to empty the remaining liquid hydrogen is the shortest, and the corresponding overall maintenance operation duration is also shorter, and the duration of suspension of business due to maintenance is also shorter, thereby reducing the maintenance cost of the liquid hydrogen refueling station.

[0067] Among them, the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data both correspond to the date attributes of the current date. For example, the above laws for working days and non-working days are counted separately, and also include holidays, etc., which will not be elaborated in detail.

[0068] Preferably, if Figure 2 As shown, the acquisition of historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station includes:

[0069] Obtain the number of liquid hydrogen refueling stations within the geographical range where the liquid hydrogen refueling station is located, and determine the duration coefficient according to the number of liquid hydrogen refueling stations according to a forward function;

[0070] Use the duration coefficient to multiply the first acquisition duration and the second acquisition duration respectively to obtain a third acquisition duration and a fourth acquisition duration;

[0071] The historical hydrogenation data related to the liquid hydrogen refueling station is acquired according to the third acquisition time, and the historical hydrogen replenishment data related to the liquid hydrogen refueling station is acquired according to the fourth acquisition time.

[0072] In an embodiment of the present invention, the historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station need to reach a certain amount of data to ensure the accuracy of the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data. To this end, the present invention first determines the duration coefficient based on the number of liquid hydrogen refueling stations within the geographical range of the liquid hydrogen refueling station and the corresponding positive function (i.e., a function that characterizes the positive correlation between the duration coefficient and the number of liquid hydrogen refueling stations, such as y=15x+100). At the same time, the first acquisition duration and the second acquisition duration for obtaining the historical hydrogenation data and the historical hydrogen replenishment data can be determined through historical experience. The first acquisition duration and the second acquisition duration are determined based on the laws of many liquid hydrogen refueling stations, that is, obtaining the historical hydrogenation data and the historical hydrogen replenishment data according to the first acquisition duration and the second acquisition duration can ensure the accuracy of the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data. The present invention is further improved by using the above-mentioned duration coefficient to adjust the first acquisition duration and the second acquisition duration respectively to obtain a third acquisition duration and a fourth acquisition duration, that is, obtaining historical hydrogenation data according to the third acquisition duration, and obtaining historical hydrogen replenishment data according to the fourth acquisition duration, thereby taking into account the actual situation of the liquid hydrogen refueling station.

[0073] It should be noted that the number of other liquid hydrogen refueling stations around the liquid hydrogen refueling station (especially the number of newly built liquid hydrogen refueling stations) will affect the liquid hydrogen consumption law and liquid hydrogen replenishment law, because the hydrogen refueling law of hydrogen vehicles for the liquid hydrogen refueling station will fluctuate to a certain extent, and correspondingly, the law of hydrogen refueling tank trucks for hydrogen refueling time points will also fluctuate to a certain extent. Therefore, the present invention appropriately increases the amount of historical hydrogenation data and historical hydrogen refueling data based on the above time coefficient (a value greater than 1), which can reduce the impact of the above two fluctuation factors.

[0074] The size of the geographical range of the above-mentioned liquid hydrogen refueling station can be preset, for example, 5km or 10km.

[0075] like Figure 3 As shown, an embodiment of the present invention further discloses a maintenance system for a liquid hydrogen refueling station, the system comprising an acquisition module, a prediction module, and a prompt module;

[0076] The acquisition module is used to acquire pressure sensor data of the pressure vessel and pipeline system of the liquid hydrogen refueling station, input the pressure sensor data into the deep analysis model, and obtain the pressure anomaly value;

[0077] The prediction module is used for obtaining historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station if the pressure abnormality value is lower than the first threshold, and predicting a number of maintenance periods according to the historical hydrogenation data and the historical hydrogen replenishment data; wherein the remaining amount of liquid hydrogen in the pressure vessel in each of the maintenance periods is lower than the second threshold;

[0078] The prompt module is used to output each maintenance period to the maintenance personnel, so that the maintenance personnel can select any maintenance period to perform maintenance on the pressure vessel and the pipeline system.

[0079] An embodiment of the present invention further discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the method described in the first embodiment.

[0080] The processor may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of processors include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor executes the various methods and processes described above, such as the maintenance method of a liquid hydrogen refueling station.

[0081] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0082] The embodiment of the present invention further discloses a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in the first embodiment is executed.

[0083] Computer storage media can be tangible media that can contain or store programs for use by or in conjunction with an instruction execution system, device, or equipment. Computer storage media can be machine-readable signal media or machine-readable storage media. Computer storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0084] An embodiment of the present invention further discloses a computer program product, wherein a computer program is stored in the computer program product, and when the computer program is executed, any of the above methods is implemented.

[0085] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0086] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A maintenance method for a liquid hydrogen refueling station, characterized in that: The method comprises the following steps: Obtaining pressure sensor data of a pressure vessel and a pipeline system of a liquid hydrogen refueling station, inputting the pressure sensor data into a deep analysis model, and obtaining a pressure anomaly value; If the pressure abnormality value is lower than the first threshold, historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station are obtained, and a number of maintenance periods are predicted based on the historical hydrogenation data and the historical hydrogen replenishment data; wherein the remaining amount of liquid hydrogen in the pressure vessel in each of the maintenance periods is lower than the second threshold; Outputting each of the maintenance time periods to the maintenance personnel so that the maintenance personnel can select any of the maintenance time periods to perform maintenance on the pressure vessel and the piping system; The method of obtaining pressure sensing data of pressure vessels and pipeline systems of liquid hydrogen refueling stations includes: obtaining pressure sensing data of pressure vessels and pipeline systems of liquid hydrogen refueling stations, and obtaining flow rate data of air inlets and air outlets of pressure vessels and pipeline systems, and adding static tags or dynamic tags to the pressure sensing data according to the flow rate data.

2. A maintenance method for a liquid hydrogen refueling station according to claim 1, characterized in that: The step of inputting the pressure sensing data into a depth analysis model to obtain a pressure anomaly value includes: If the label of the pressure sensing data is a static label, inputting the pressure sensing data into a first depth analysis model to obtain a first pressure anomaly value; If the label of the pressure sensing data is a dynamic label, the pressure sensing data is input into the first depth analysis model and the second depth analysis model respectively, and the depth analysis results of the first depth analysis model and the second depth analysis model are fused to obtain a second pressure anomaly value.

3. A maintenance method for a liquid hydrogen refueling station according to claim 2, characterized in that: The depth analysis results of the first depth analysis model and the second depth analysis model are integrated to obtain a second pressure anomaly value, including: Determine the flow velocity magnitude of the flow velocity data, determine a first weight of the first depth analysis model according to the flow velocity magnitude, and determine a second weight of the second depth analysis model according to the first weight; The second pressure abnormality value is obtained by weightedly averaging the pressure abnormality values ​​of the first depth analysis model and the second depth analysis model based on the first weight and the second weight.

4. A maintenance method for a liquid hydrogen refueling station according to claim 3, characterized in that: The predicting of a number of maintenance periods based on the historical hydrogenation data and the historical hydrogen replenishment data includes: Liquid hydrogen consumption law data is obtained by fitting the historical hydrogenation data, and liquid hydrogen replenishment law data is obtained by fitting the historical hydrogen replenishment data; wherein both the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data correspond to the date attribute of the current date; According to the current remaining amount of liquid hydrogen, the liquid hydrogen consumption law data and the liquid hydrogen replenishment law data, a number of time periods in which the remaining amount of liquid hydrogen is lower than the second threshold are calculated, namely, a number of the maintenance time periods.

5. A maintenance method for a liquid hydrogen refueling station according to claim 4, characterized in that: The obtaining of historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station includes: Obtain the number of liquid hydrogen refueling stations within the geographical range where the liquid hydrogen refueling station is located, and determine the duration coefficient according to the number of liquid hydrogen refueling stations according to a forward function; Use the duration coefficient to multiply the first acquisition duration and the second acquisition duration respectively to obtain a third acquisition duration and a fourth acquisition duration; The historical hydrogenation data related to the liquid hydrogen refueling station is acquired according to the third acquisition time, and the historical hydrogen replenishment data related to the liquid hydrogen refueling station is acquired according to the fourth acquisition time.

6. A maintenance system for a liquid hydrogen refueling station for executing the method according to any one of claims 1 to 5, characterized in that: The system includes an acquisition module, a prediction module, and a prompt module; The acquisition module is used to acquire pressure sensor data of the pressure vessel and pipeline system of the liquid hydrogen refueling station, input the pressure sensor data into the deep analysis model, and obtain the pressure anomaly value; The prediction module is used for obtaining historical hydrogenation data and historical hydrogen replenishment data related to the liquid hydrogen refueling station if the pressure abnormality value is lower than the first threshold, and predicting a number of maintenance periods according to the historical hydrogenation data and the historical hydrogen replenishment data; wherein the remaining amount of liquid hydrogen in the pressure vessel in each of the maintenance periods is lower than the second threshold; The prompt module is used to output each maintenance period to the maintenance personnel, so that the maintenance personnel can select any maintenance period to perform maintenance on the pressure vessel and the pipeline system.

7. An electronic device, comprising: A memory storing executable program code; A processor coupled to the memory; characterized in that: the processor calls the executable program code stored in the memory to execute the method according to any one of claims 1-5.

8. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is executed.

9. A computer program product, characterized in that: The computer program product stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 5 is implemented.

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