Intelligent diagnosis system and intelligent question and answer system for fuel cell

Abstract

The invention provides an intelligent diagnosis system and an intelligent question and answer system for a fuel cell, and relates to the technical field of fuel cell diagnosis. The intelligent diagnosis system for the fuel cell comprises a multi-modal data acquisition module, a multi-modal data fusion and feature extraction module, an intelligent reasoning and fault diagnosis module and a control and feedback module. The multi-modal data acquisition module is used for acquiring operation data, image data and text data of the fuel cell in real time; the multi-modal data fusion and feature extraction module is used for performing feature extraction on the operation data, the image data and the text data and generating fusion data; the intelligent reasoning and fault diagnosis module is used for generating a fault diagnosis result; and the control and feedback module is used for generating a regulation and control instruction and sending the regulation and control instruction to the fuel cell system. According to the intelligent diagnosis system for the fuel cell, the accuracy and precision of fault diagnosis can be effectively improved, and the real-time performance of fault diagnosis can be effectively improved.

Description

Technical Field

[0001] The present application relates to the technical field of fuel cell diagnosis, and in particular to an intelligent diagnosis system and an intelligent question-answering system for fuel cells. Background Art

[0002] Fuel cells have important applications in efficient energy conversion and storage, but their complex working principles and sensitivity to the external environment make equipment fault diagnosis difficult.

[0003] At present, the existing fault diagnosis methods usually rely on a single data source and are highly dependent on human experience. Not only are there problems with low accuracy and precision of fault diagnosis, but there are also problems such as poor real-time performance of fault diagnosis and unclear troubleshooting paths. Summary of the invention

[0004] In order to solve the technical problems in the related art, the present application provides an intelligent diagnosis system and an intelligent question-and-answer system for a fuel cell.

[0005] In order to achieve the above objectives, the technical solutions adopted in this application include:

[0006] According to a first aspect of the present application, there is provided an intelligent diagnostic system for a fuel cell, comprising:

[0007] A multimodal data acquisition module, used to acquire the operation data, image data and text data of the fuel cell in real time; wherein the operation data includes the temperature, pressure, current, voltage and gas concentration during the operation of the fuel cell, the image data includes the images during the operation of the fuel cell, and the text data includes the historical faults and maintenance records of the fuel cell;

[0008] Multimodal data fusion and feature extraction module, used to extract features from operating data, image data and text data, and generate fused data;

[0009] Intelligent reasoning and fault diagnosis module, used to perform fault analysis based on fused data to generate fault diagnosis results;

[0010] A control and feedback module generates a control instruction according to the fault diagnosis result, and is used to send the control instruction to the fuel cell system to adjust the fuel cell operating parameters or implement safety measures;

[0011] The operation method of the intelligent diagnosis system for fuel cells includes the following steps:

[0012] Step S1: The multimodal data acquisition module acquires the operation data, image data and text data of the fuel cell in real time;

[0013] Step S2-1: The multimodal data fusion and feature extraction module performs feature extraction on the operation data, image data and text data respectively;

[0014] Step S2-2: The multimodal data fusion and feature extraction module integrates the data features from different data sources into a shared feature space and establishes the same data set to generate fused data;

[0015] Step S3: The intelligent reasoning and fault diagnosis module performs fault cause reasoning and diagnosis through a reasoning engine based on the fused data to perform fault analysis and generate fault diagnosis results;

[0016] Step S4: Generate a control instruction based on the fault diagnosis result, and send the control instruction to the fuel cell to adjust the fuel cell operating parameters or implement safety measures.

[0017] Optionally, the multimodal data acquisition module includes an image acquisition device and a plurality of sensors;

[0018] The image acquisition device is used to acquire images during the operation of the fuel cell, and the image acquisition device includes a camera and an infrared thermal imager. The camera is used to acquire external images during the operation of the fuel cell, and the infrared thermal imager is used to acquire thermal distribution images during the operation of the fuel cell.

[0019] Several sensors are used to collect temperature, pressure, current, voltage and gas concentration during the operation of the fuel cell.

[0020] Optionally, the process of processing data by the multimodal data fusion and feature extraction module specifically includes:

[0021] For the operation data, each operation data is analyzed separately through the time series analysis model to extract the change trend of each operation data;

[0022] For image data, the image data is processed through a computer vision model to identify physical damage and abnormal thermal distribution of the fuel cell;

[0023] For text data, natural language processing technology is used to perform semantic analysis on the text data to extract historical failure modes and corresponding solutions.

[0024] According to the second aspect of the present application, there is also provided an intelligent question-answering system for a fuel cell, comprising the intelligent diagnosis system for a fuel cell as described in any one of the technical solutions in the first aspect of the present application, and an intelligent question-answering system module;

[0025] The intelligent question-answering system module is used to generate an answer text based on the question text input by the user, combined with the intelligent reasoning and fault diagnosis modules, and the answer text includes the fault diagnosis results and maintenance suggestions;

[0026] The intelligent question-answering system for fuel cells further comprises the following operating steps:

[0027] Step S5: Obtain the question text input by the user in natural language, combine the intelligent reasoning with the fault diagnosis result of the fault diagnosis module, and generate the answer text.

[0028] Optionally, the intelligent question answering system module includes a data preprocessing part, a knowledge graph part, a question text acquisition part, a natural language large model part, a knowledge base part and an answer output part;

[0029] Among them, the data preprocessing part is used to perform entity recognition, relationship extraction and attribute extraction on text data, that is, to use text data for knowledge fusion to generate a knowledge graph; the knowledge base part includes fault manuals, experience documents and user feedback texts; the natural language large model part is used to generate answer text based on the question text obtained by the question text acquisition part, the knowledge base and the output of the knowledge graph.

[0030] Optionally, the intelligent diagnosis system for fuel cells also includes an adaptive optimization and learning module, which is used to optimize the intelligent reasoning and fault diagnosis module and the intelligent question and answer system module according to manual feedback on the answer text, and update the knowledge base.

[0031] According to the third aspect of the present application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it can implement the operating method of the intelligent diagnostic system for fuel cells described in the first aspect of the present application or the operating steps of the intelligent question and answer system for fuel cells described in the second aspect of the present application.

[0032] According to the fourth aspect of the present application, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, it can implement the operating method of the intelligent diagnostic system for fuel cells described in the first aspect of the present application or the operating steps of the intelligent question and answer system for fuel cells described in the second aspect of the present application.

[0033] Beneficial effects:

[0034] 1. Through the above technical solution, first, the multimodal data acquisition module of the present application collects the operating data, image data and text data of the fuel cell in real time, which can provide more sources and more comprehensive data for fault diagnosis, and can avoid the limitations of the single data source in the existing related technology, thereby effectively improving the accuracy and precision of fault diagnosis. At the same time, since the entire diagnostic process is carried out in combination with real-time collected data, the real-time nature of fault diagnosis can also be effectively improved.

[0035] Second, during the fault diagnosis process, the intelligent diagnosis system for fuel cells provided in the present application first uses a multimodal data fusion and feature extraction module to extract features from operating data, image data, and text data, and generates fused data; and then uses an intelligent reasoning and fault diagnosis module to perform fault analysis on the fused data. In this way, the efficiency of fault diagnosis can be effectively improved and the clarity of the troubleshooting path can be ensured, so that relevant personnel can quickly and accurately troubleshoot the fault.

[0036] Third, the control and feedback module of the present application can generate corresponding control instructions based on the fault diagnosis results, so that the operating parameters of the fuel cell can be adjusted or corresponding safety measures can be implemented in real time, which can not only effectively ensure the operating safety and production efficiency of the fuel cell, but also effectively improve the safety of the fuel cell during operation.

[0037] Fourthly, the intelligent reasoning and fault diagnosis module of the present application has multi-level fault pattern recognition, that is, it combines the outputs of different data sources to identify the root cause of the fault layer by layer and provide more accurate diagnosis results.

[0038] 2. Other beneficial effects or advantages of the present application will be described in detail in the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative labor.

[0040] in:

[0041] Figure 1 is a schematic diagram of the arrangement of an intelligent diagnosis system and an intelligent question-and-answer system for a fuel cell provided by an exemplary embodiment of the present application;

[0042] Figure 2 is a schematic flow chart of the operation steps of an intelligent diagnostic system for a fuel cell provided by an exemplary embodiment of the present application;

[0043] Figure 3 It is a schematic diagram of a partial arrangement of an intelligent diagnostic system for a fuel cell provided in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0045] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0046] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes other steps or units that are not listed, or optionally includes other steps or units that are inherent to these processes, methods, products or devices. Among them, it should also be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design solutions. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0047] The technical solution of the present application is described in detail below with reference to the accompanying drawings.

[0048] Example 1

[0049] like Figures 1 to 3 As shown, according to the first aspect of the present application, this embodiment provides an intelligent diagnosis system for a fuel cell, including a multimodal data acquisition module, a multimodal data fusion and feature extraction module, an intelligent reasoning and fault diagnosis module, and a control and feedback module.

[0050] The multimodal data acquisition module is used to acquire the operating data, image data and text data of the fuel cell in real time; wherein the operating data includes the temperature, pressure, current, voltage and gas concentration during the operation of the fuel cell, the image data includes the images during the operation of the fuel cell, and the text data includes the historical failure and maintenance records of the fuel cell.

[0051] The multimodal data fusion and feature extraction module is used to extract features from operating data, image data and text data, and generate fused data. The intelligent reasoning and fault diagnosis module is used to perform fault analysis based on the fused data to generate fault diagnosis results; the control and feedback module generates control instructions based on the fault diagnosis results, and is used to send the control instructions to the fuel cell system to adjust the fuel cell operating parameters or implement safety measures.

[0052] Among them, see Figure 2 The operation method of the intelligent diagnosis system for fuel cells comprises the following steps:

[0053] Step S1: The multimodal data acquisition module acquires the operation data, image data and text data of the fuel cell in real time;

[0054] Step S2-1: The multimodal data fusion and feature extraction module performs feature extraction on the operation data, image data and text data respectively;

[0055] Step S2-2: The multimodal data fusion and feature extraction module integrates the data features from different data sources into a shared feature space and establishes the same data set to generate fused data;

[0056] Step S3: The intelligent reasoning and fault diagnosis module performs fault cause reasoning and diagnosis based on the fused data through a reasoning engine (e.g., a deep neural network, a graph neural network, etc.) to perform fault analysis and generate fault diagnosis results;

[0057] Step S4: Generate a control instruction based on the fault diagnosis result, and send the control instruction to the fuel cell to adjust the fuel cell operating parameters or implement safety measures.

[0058] Through the above technical solution, first, the multimodal data acquisition module of the present application collects the operating data, image data and text data of the fuel cell in real time, which can provide more sources and more comprehensive data for fault diagnosis, and can avoid the limitations of the single data source in the existing related technology, thereby effectively improving the accuracy and precision of fault diagnosis. At the same time, since the entire diagnostic process is carried out in combination with real-time collected data, the real-time nature of fault diagnosis can also be effectively improved.

[0059] Second, during the fault diagnosis process, the intelligent diagnosis system for fuel cells provided in the present application first uses a multimodal data fusion and feature extraction module to extract features from operating data, image data, and text data, and generates fused data; and then uses an intelligent reasoning and fault diagnosis module to perform fault analysis on the fused data. In this way, the efficiency of fault diagnosis can be effectively improved and the clarity of the troubleshooting path can be ensured, so that relevant personnel can quickly and accurately troubleshoot the fault.

[0060] Third, the control and feedback module of the present application can generate corresponding control instructions based on the fault diagnosis results, so that the operating parameters of the fuel cell can be adjusted or corresponding safety measures can be implemented in real time, which can not only effectively ensure the operating safety and production efficiency of the fuel cell, but also effectively improve the safety of the fuel cell during operation.

[0061] Fourthly, the intelligent reasoning and fault diagnosis module of the present application has multi-level fault pattern recognition, that is, it combines the outputs of different data sources to identify the root cause of the fault layer by layer and provide more accurate diagnosis results.

[0062] In one embodiment of the present application, the multimodal data acquisition module of the present application may include an image acquisition device and several sensors; wherein the image acquisition device is used to acquire images during the operation of the fuel cell, the image acquisition device includes a camera and an infrared thermal imager, the camera is used to acquire external images during the operation of the fuel cell, and the infrared thermal imager is used to acquire thermal distribution images during the operation of the fuel cell; the several sensors are respectively used to acquire temperature, pressure, current, voltage and gas concentration during the operation of the fuel cell.

[0063] In this embodiment, the temperature, pressure, current, voltage, gas concentration and other operating data of the fuel cell can be collected in real time by a number of sensors. The external image or on-site video monitoring of the fuel cell can be carried out by a camera or an infrared thermal imager to assist in the physical damage detection of the equipment. In this way, the timeliness and accuracy of the operation data collection can be effectively guaranteed, and at the same time, it is also conducive to real-time monitoring of the operating status of the fuel cell.

[0064] In one embodiment of the present application, the process of processing data by the multimodal data fusion and feature extraction module of the present application may specifically include:

[0065] For the operation data, each operation data is analyzed separately through the time series analysis model to extract the change trend of each operation data;

[0066] For image data, the image data is processed through a computer vision model to identify physical damage and abnormal thermal distribution of the fuel cell;

[0067] For text data, natural language processing technology is used to perform semantic analysis on the text data to extract historical failure modes and corresponding solutions.

[0068] In this embodiment, it can be understood that, first, the timing analysis model can use analysis models such as LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit), and the present application does not make specific limitations on this.

[0069] Second, the computer vision model can use models such as CNN (Convolutional Neural Networks), RNN (Recurrent Neural Network), etc., and this application does not make specific limitations on this.

[0070] Third, natural language processing technology can use models such as BERT (Bidirectional Encoder Representations from Transformers, a pre-trained natural language processing model) and GPT (Generative Pre-trained Transformer, a generative pre-trained language model), and this application does not make specific limitations on this.

[0071] According to the second aspect of the present application, there is also provided an intelligent question-answering system for a fuel cell, comprising the intelligent diagnosis system for a fuel cell according to any one of the technical solutions in the first aspect of the present application, and an intelligent question-answering system module; the intelligent question-answering system module is used to generate an answer text according to the question text input by the user, in combination with the intelligent reasoning and fault diagnosis module, and the answer text includes a fault diagnosis result and a maintenance suggestion;

[0072] The intelligent question-answering system for fuel cells also includes the following operating steps:

[0073] Step S5: Obtain the question text input by the user in natural language, combine the intelligent reasoning with the fault diagnosis result of the fault diagnosis module, and generate the answer text.

[0074] Through the above technical solution, the intelligent question and answer system for fuel cells of the present application is based on the intelligent diagnosis system for fuel cells, combined with the intelligent question and answer system module, and can be well adapted to the needs of inexperienced users. It can generate corresponding answer texts based on the questions raised by users, combined with the data collected by the intelligent reasoning and fault diagnosis module and the fault diagnosis results.

[0075] In one embodiment of the present application, Figure 3 As shown, the intelligent question-answering system module of the present application may include a data preprocessing part, a knowledge graph part, a question text acquisition part, a natural language large model part, a knowledge base part and an answer output part; wherein the data preprocessing part is used to perform entity recognition, relationship extraction and attribute extraction on text data, that is, to use text data for knowledge fusion to generate a knowledge graph; the knowledge base part includes fault manuals, experience documents and user feedback texts; the natural language large model part is used to generate an answer text based on the question text acquired by the question text acquisition part, the knowledge base and the output of the knowledge graph.

[0076] In this way, based on the questions raised by the user, the intelligent question-answering system module can convert the question text into a structured question, and generate a more accurate answer text through the natural language large model part in combination with the reasoning engine and the knowledge base part. At the same time, combined with the natural language large model part, the intelligent diagnosis system and intelligent answering system for fuel cells of this application can understand the user's natural language input, and provide personalized fault diagnosis reports and maintenance suggestions to improve the user experience.

[0077] Taking an exemplary implementation as an example, the operation process of the intelligent diagnosis system and intelligent answering system for fuel cells of the present application may be:

[0078] Assuming that a fuel cell system has abnormal temperature during operation, the specific steps of the system operation are as follows:

[0079] Data collection: The sensor detected that the temperature continued to rise, the camera captured burn marks on the outside of the device, and the operator input "Why is the device overheating?"

[0080] Data processing: The sensor data is denoised and a trend graph is generated, the image is enhanced to clearly show the burn area, and the text data is segmented and parsed.

[0081] Data fusion: Integrate sensor data, image features, and operator input into a unified data framework.

[0082] Fault reasoning: The system combines data and historical cases to determine that the cause of equipment overheating may be a failure of the heat dissipation device.

[0083] Smart Q&A: The system answers "The device may overheat due to a failure of the cooling fan. It is recommended to check the fan's operating status or replace the fan assembly."

[0084] Report Generation: The system generates a detailed report including sensor temperature profile, burn image and recommended repair steps.

[0085] In one embodiment of the present application, the intelligent diagnosis system for fuel cells of the present application also includes an adaptive optimization and learning module, which is used to optimize the intelligent reasoning and fault diagnosis module and the intelligent question and answer system module according to manual feedback on the answer text, and update the knowledge base.

[0086] In this way, through the adaptive optimization and learning module set up in this way, the intelligent diagnosis system for fuel cells of the present application can continuously optimize the reasoning model and question-answering system through the feedback learning mechanism, thereby continuously improving the accuracy and efficiency of fault diagnosis.

[0087] In addition, the intelligent diagnosis system and intelligent question-and-answer system for fuel cells of the present application are based on historical data and real-time collected data (including operation data, image data and text data). In this way, the intelligent diagnosis system and intelligent question-and-answer system for fuel cells of the present application can not only meet the needs of fault diagnosis, but also effectively predict potential faults, provide preventive maintenance suggestions, and extend the service life of the equipment.

[0088] According to the third aspect of the present application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it can implement the operating method of the intelligent diagnostic system for fuel cells described in the first aspect of the present application or the operating steps of the intelligent question and answer system for fuel cells described in the second aspect of the present application.

[0089] It is understood that in this embodiment, the memory may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a read-only memory, a flash memory, a hard disk or a solid state drive; in addition, the memory may also include a combination of the above-mentioned types of memory. This application does not specifically limit this.

[0090] Similarly, the processor may be a processor that implements or executes various exemplary logic steps described in conjunction with the disclosure of the present application. The processor may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. It may implement or execute various exemplary logic steps described in conjunction with the disclosure of the present application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0091] According to the fourth aspect of the present application, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, it can implement the operating method of the intelligent diagnostic system for fuel cells described in the first aspect of the present application or the operating steps of the intelligent question and answer system for fuel cells described in the second aspect of the present application.

[0092] In this embodiment, 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 thereof. More specific examples (non-exhaustive list) of computer readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, 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, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and can write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may be located in an application-specific integrated circuit (ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0093] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent diagnostic system for a fuel cell, characterized in that: include: A multimodal data acquisition module, used to acquire the operation data, image data and text data of the fuel cell in real time; wherein the operation data includes the temperature, pressure, current, voltage and gas concentration during the operation of the fuel cell, the image data includes the images during the operation of the fuel cell, and the text data includes the historical faults and maintenance records of the fuel cell; Multimodal data fusion and feature extraction module, used to extract features from operating data, image data and text data, and generate fused data; Intelligent reasoning and fault diagnosis module, used to perform fault analysis based on fused data to generate fault diagnosis results; A control and feedback module generates a control instruction according to the fault diagnosis result, and is used to send the control instruction to the fuel cell system to adjust the fuel cell operating parameters or implement safety measures; The operation method of the intelligent diagnosis system for fuel cells includes the following steps: Step S1: The multimodal data acquisition module acquires the operation data, image data and text data of the fuel cell in real time; Step S2-1: The multimodal data fusion and feature extraction module performs feature extraction on the operation data, image data and text data respectively; Step S2-2: The multimodal data fusion and feature extraction module integrates the data features from different data sources into a shared feature space and establishes the same data set to generate fused data; Step S3: The intelligent reasoning and fault diagnosis module performs fault cause reasoning and diagnosis through a reasoning engine based on the fused data to perform fault analysis and generate fault diagnosis results; Step S4: Generate a control instruction based on the fault diagnosis result, and send the control instruction to the fuel cell to adjust the fuel cell operating parameters or implement safety measures.

2. The intelligent diagnostic system for fuel cells according to claim 1, characterized in that: The multimodal data acquisition module includes an image acquisition device and a plurality of sensors; The image acquisition device is used to acquire images during the operation of the fuel cell, and the image acquisition device includes a camera and an infrared thermal imager. The camera is used to acquire external images during the operation of the fuel cell, and the infrared thermal imager is used to acquire thermal distribution images during the operation of the fuel cell. Several sensors are used to collect temperature, pressure, current, voltage and gas concentration during the operation of the fuel cell.

3. The intelligent diagnostic system for fuel cells according to claim 1, characterized in that: The process of processing data by the multimodal data fusion and feature extraction module specifically includes: For the operation data, each operation data is analyzed separately through the time series analysis model to extract the change trend of each operation data; For image data, the image data is processed through a computer vision model to identify physical damage and abnormal thermal distribution of the fuel cell; For text data, natural language processing technology is used to perform semantic analysis on the text data to extract historical failure modes and corresponding solutions.

4. An intelligent question-answering system for fuel cells, characterized in that: An intelligent diagnostic system for a fuel cell as claimed in any one of claims 1 to 3, and an intelligent question-answering system module; The intelligent question-answering system module is used to generate an answer text based on the question text input by the user, combined with the intelligent reasoning and fault diagnosis modules, and the answer text includes the fault diagnosis results and maintenance suggestions; The intelligent question-answering system for fuel cells further comprises the following operating steps: Step S5: Obtain the question text input by the user in natural language, combine the intelligent reasoning with the fault diagnosis result of the fault diagnosis module, and generate the answer text.

5. The intelligent diagnostic system for fuel cells according to claim 4, characterized in that: The intelligent question answering system module includes a data preprocessing part, a knowledge graph part, a question text acquisition part, a natural language large model part, a knowledge base part and an answer output part; Among them, the data preprocessing part is used to perform entity recognition, relationship extraction and attribute extraction on text data, that is, to use text data for knowledge fusion to generate a knowledge graph; the knowledge base part includes fault manuals, experience documents and user feedback texts; the natural language large model part is used to generate answer text based on the question text obtained by the question text acquisition part, the knowledge base and the output of the knowledge graph.

6. The intelligent diagnostic system for fuel cells according to claim 5, characterized in that: The intelligent diagnosis system for fuel cells also includes an adaptive optimization and learning module, which is used to optimize the intelligent reasoning and fault diagnosis module and the intelligent question-answering system module and update the knowledge base based on manual feedback on the answer text.

7. A computer 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, it can implement the operating method of the intelligent diagnosis system for fuel cells described in claim 1 or the operating steps of the intelligent question-and-answer system for fuel cells described in claim 4.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it can implement the operating method of the intelligent diagnosis system for fuel cells described in claim 1 or the operating steps of the intelligent question-and-answer system for fuel cells described in claim 4.

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