Steam turbine vibration monitoring system and method
By designing a turbine vibration monitoring system, real-time collection and processing of vibration data, and performing fault detection and early warning, the problem of real-time monitoring and early warning of turbine fault diagnosis in the existing technology is solved, and the operation reliability and safety of the equipment are improved.
Patent Information
- Application Number
- CN202411851757.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-16
- Publication Date
- 2025-03-11
AI Technical Summary
In the prior art, steam turbine fault diagnosis mainly relies on manual experience and regular maintenance, and real-time monitoring and early warning cannot be achieved, which poses great safety hazards.
A steam turbine vibration monitoring system is designed, including a data acquisition module, a data processing module and a fault diagnosis module, which can collect and process the vibration data of the steam turbine in real time, and perform fault detection and early warning through the fault diagnosis module.
Real-time monitoring and fault warning of the operating status of the turbine are realized, which significantly improves the operating reliability and safety of the equipment, and reduces maintenance costs and downtime risks.
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Abstract
Description
Technical Field
[0001] The present application relates to the technical field of mechanical fault diagnosis, and in particular to a steam turbine vibration monitoring system and method. Background Art
[0002] With the improvement of industrial automation level, the stable operation of large rotating mechanical equipment such as steam turbines is crucial to power production. However, the fault diagnosis of steam turbines in the existing technology mainly relies on manual experience and regular maintenance, and cannot achieve real-time monitoring and early warning, which poses a great safety hazard. Summary of the invention
[0003] The technical problem to be solved by this application is to provide a steam turbine vibration monitoring system and method, which can monitor the operating status of the steam turbine in real time. The specific scheme is as follows:
[0004] A steam turbine vibration monitoring system, comprising:
[0005] Data acquisition module, data processing module and fault diagnosis module;
[0006] The data acquisition module is used to collect status monitoring data of the steam turbine during operation;
[0007] The data processing module is used to preprocess the state monitoring data, obtain the preprocessed target state monitoring data, and store the target state monitoring data in a preset storage space;
[0008] The fault diagnosis module is used to perform fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain a fault detection result of the steam turbine;
[0009] The simulation module is used to determine the simulation time corresponding to the simulation instruction when receiving the simulation instruction, obtain the target state monitoring data corresponding to the simulation time in the storage space, and simulate the operating state of the turbine at the simulation time according to the target state monitoring data corresponding to the simulation time.
[0010] In the above system, optionally, the fault diagnosis module is used to:
[0011] Generate vibration trend data of the preset time period according to vibration data in the target state monitoring data within the preset time period stored in the storage space, determine whether the steam turbine has a first type of fault according to the vibration trend data, and obtain a first diagnosis result;
[0012] Converting vibration data in the target state monitoring data stored in the storage space from the time domain to the frequency domain to obtain frequency domain vibration data, and detecting whether the steam turbine has a second type of fault according to the frequency domain vibration data to obtain a second diagnosis result;
[0013] The first vibration data in the target state monitoring data stored in the storage space is used to detect whether the steam turbine has a third type of fault to obtain a third diagnostic result, wherein the first vibration data is vibration data generated by the steam turbine during start-up and shutdown or load change.
[0014] In the above system, optionally, the data processing module is used to:
[0015] When the diagnosis result indicates that the steam turbine is faulty, fault alarm information of the steam turbine is output.
[0016] In the above system, optionally, the data processing module is used to:
[0017] removing outliers in the condition monitoring data and filling missing values in the condition monitoring data;
[0018] Filtering or wavelet transform technology is used to remove high-frequency noise and interference signals in the state monitoring data after filling the missing values, so as to obtain target state monitoring data.
[0019] In the above system, optionally, the data processing module is further used for:
[0020] When a data query instruction of the target system is received, the target state monitoring data corresponding to the data query instruction is obtained in the storage space, and the target state monitoring data corresponding to the query instruction is sent to the target system.
[0021] A steam turbine vibration monitoring method is applied to a steam turbine vibration monitoring system, wherein the steam turbine vibration monitoring system comprises a data acquisition module, a data processing module, a fault diagnosis module and a simulation module, and the method comprises:
[0022] The data acquisition module acquires status monitoring data of the steam turbine during operation; the status monitoring data at least includes vibration data;
[0023] The data processing module preprocesses the state monitoring data to obtain preprocessed target state monitoring data, and stores the target state monitoring data in a preset storage space;
[0024] The fault diagnosis module performs fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain a fault detection result of the steam turbine;
[0025] When receiving a simulation instruction, the simulation module determines the simulation time corresponding to the simulation instruction, obtains the target state monitoring data corresponding to the simulation time in the storage space, and simulates the operating state of the turbine at the simulation time based on the target state monitoring data corresponding to the simulation time.
[0026] In the above method, optionally, the fault diagnosis module performs fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain the fault detection result of the steam turbine, including:
[0027] The fault diagnosis module generates vibration trend data for a preset time period according to vibration data in the target state monitoring data within a preset time period stored in the storage space, determines whether the steam turbine has a first type of fault according to the vibration trend data, and obtains a first diagnosis result;
[0028] The fault diagnosis module converts the vibration data in the target state monitoring data stored in the storage space from the time domain to the frequency domain to obtain frequency domain vibration data, and detects whether the steam turbine has a second type of fault according to the frequency domain vibration data to obtain a second diagnosis result;
[0029] The fault diagnosis module uses the first vibration data in the target state monitoring data stored in the storage space to detect whether the steam turbine has a third type of fault and obtain a third diagnostic result. The first vibration data is the vibration data generated by the steam turbine during start-up and shutdown or load change.
[0030] The above method, optionally, after obtaining the fault detection result of the steam turbine, further comprises:
[0031] The fault diagnosis module outputs fault alarm information of the steam turbine when the diagnosis result indicates that the steam turbine has a fault.
[0032] In the above method, optionally, the data processing module preprocesses the state monitoring data to obtain the preprocessed target state monitoring data, including:
[0033] The data processing module removes abnormal values in the condition monitoring data and fills in missing values in the condition monitoring data;
[0034] The data processing module uses filtering or wavelet transform technology to remove high-frequency noise and interference signals in the state monitoring data after filling the missing values, so as to obtain target state monitoring data.
[0035] The above method, optionally, after storing the target state monitoring data in a preset storage space, further comprises:
[0036] When receiving a data query instruction from a target system, the data processing module obtains target status monitoring data corresponding to the data query instruction in the storage space, and sends the target status monitoring data corresponding to the query instruction to the target system.
[0037] The present application provides a steam turbine vibration monitoring system and method, which includes: a data acquisition module, a data processing module and a fault diagnosis module; the data acquisition module is used to collect status monitoring data of the steam turbine during operation; the status monitoring data at least includes vibration data, and the vibration data includes at least one of amplitude, frequency and phase; the data processing module is used to preprocess the status monitoring data, obtain preprocessed target status monitoring data, and store the target status monitoring data in a preset storage space; the fault diagnosis module is used to perform fault detection on the steam turbine according to the target status monitoring data stored in the storage space, and obtain the fault detection result of the steam turbine; the simulation module is used to determine the simulation time corresponding to the simulation instruction when receiving the simulation instruction, obtain the target status monitoring data corresponding to the simulation time in the storage space, and simulate the operating state of the steam turbine at the simulation time according to the target status monitoring data corresponding to the simulation time. The method provided in the embodiment of the present application can not only monitor the operating status of the steam turbine in real time and detect potential faults in advance, but also simulate the operating status of the steam turbine, significantly improving the operating reliability and safety of the equipment and reducing maintenance costs and downtime risks. BRIEF DESCRIPTION OF THE DRAWINGS
[0038] 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 embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.
[0039] Figure 1 A schematic diagram of the structure of a steam turbine vibration monitoring system provided in this application;
[0040] Figure 2 A structural schematic diagram of another steam turbine vibration monitoring system provided in this application;
[0041] Figure 3 A method flow chart of a steam turbine vibration monitoring method provided in this application;
[0042] Figure 4A flowchart of a process for obtaining pre-processed target state monitoring data provided by the present application;
[0043] Figure 5 This is an example diagram of an implementation scenario provided for this application. DETAILED DESCRIPTION
[0044] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions 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. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0045] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.
[0046] The present application embodiment provides a steam turbine vibration monitoring system. The structural diagram of the system is as follows: Figure 1 As shown, specifically including:
[0047] Data acquisition module 101, data processing module 102, fault diagnosis module 103 and simulation module 104;
[0048] The data acquisition module 101 is used to collect state monitoring data of the steam turbine during operation; the state monitoring data at least includes vibration data. In this embodiment, the vibration data can be time domain signal data, which can include acceleration, displacement, velocity and other information; the data acquisition module can include a highly sensitive vibration sensor deployed on the target component of the steam turbine, which can collect vibration data of the target component of the steam turbine in real time, and the target component can include bearings, rotors, gear boxes and the like.
[0049] In some embodiments, the state monitoring data may also include temperature data, pressure data, etc.
[0050] The data processing module 102 is used to preprocess the state monitoring data, obtain the preprocessed target state monitoring data, and store the target state monitoring data in a preset storage space; in this embodiment, the process of preprocessing the state monitoring data can be data cleaning and data denoising of the state monitoring data, specifically, it can be to check and remove abnormal data points caused by sensor failure, data transmission error, etc.; for missing data caused by equipment shutdown, sensor failure, etc., interpolation method (such as linear interpolation, neighboring value filling, etc.) is used to fill; digital filters (such as low-pass filters, high-pass filters, band-pass filters, etc.) are used to remove high-frequency noise and interference signals in the data; using wavelet transform technology, the signal is decomposed into wavelet coefficients of different frequency components, and then the noise component is removed or weakened, and finally the signal is reconstructed to obtain the target state monitoring data.
[0051] Optionally, the storage space may be a scalable high-speed data buffer pool pre-established in memory, into which real-time dynamic and static data flows at high speed and is “first in, first out” and rolled over in the buffer pool; in some embodiments, the storage space may also be a database.
[0052] In some embodiments, the data processing module can be used to generate real-time historical data such as start-up and shutdown, cranking, alarm, machine tripping, vibration trend fluctuations, spectrum fluctuations, sudden changes, conventional high density, and conventional low density.
[0053] In some embodiments, the data processing module integrates a variety of signal processing algorithms, such as FFT, wavelet transform, Hilbert-Huang transform, etc.
[0054] The fault diagnosis module 103 is used to perform fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain the fault detection result of the steam turbine. In this embodiment, the fault diagnosis module can provide a fault diagnosis conclusion for the alarm event and can also provide real-time diagnosis information for real-time data in a dynamic manner.
[0055] The simulation module 104 is used to determine the simulation time corresponding to the simulation instruction when receiving the simulation instruction, obtain the target state monitoring data corresponding to the simulation time in the storage space, and simulate the operating state of the steam turbine at the simulation time according to the target state monitoring data corresponding to the simulation time. In this embodiment, the simulation instruction can be an instruction triggered when an alarm event occurs, or it can be an instruction triggered by a user clicking a preset button or virtual control.
[0056] In some embodiments, when a fault occurs, the simulation module automatically records the vibration data within a relevant time period and stores it in a distributed database; generates a three-dimensional model of the steam turbine based on the structural data of the steam turbine; maps the stored vibration data to the three-dimensional model to simulate the vibration conditions during actual operation; provides a variety of viewing options, and users can choose different viewing angles to observe the process of the fault, including top view, side view, stereo view, etc.; can dynamically replay the process of the fault in chronological order, and users can pause, fast forward, and rewind to analyze the vibration conditions of each time node in detail.
[0057] In some embodiments, when the simulation module simulates the operating state of the steam turbine at the simulation time, the fault diagnosis module can continuously provide dynamic diagnosis information for different stages of events generated by the steam turbine during the simulation time.
[0058] The method provided in the embodiment of the present application can not only monitor the operating status of the steam turbine in real time and detect potential faults in advance, but also simulate the operating status of the steam turbine, significantly improving the operating reliability and safety of the equipment and reducing maintenance costs and downtime risks.
[0059] In an embodiment provided in the present application, based on the above solution, optionally, the fault diagnosis module 103 is used to:
[0060] Generate vibration trend data of the preset time period according to vibration data in the target state monitoring data within the preset time period stored in the storage space, determine whether the steam turbine has a first type of fault according to the vibration trend data, and obtain a first diagnosis result;
[0061] Converting vibration data in the target state monitoring data stored in the storage space from the time domain to the frequency domain to obtain frequency domain vibration data, and detecting whether the steam turbine has a second type of fault according to the frequency domain vibration data to obtain a second diagnosis result;
[0062] The first vibration data in the target state monitoring data stored in the storage space is used to detect whether the steam turbine has a third type of fault to obtain a third diagnostic result, wherein the first vibration data is vibration data generated by the steam turbine during start-up and shutdown or load change.
[0063] In this embodiment, the first type of fault may be at least one of turbine imbalance, eccentricity and bearing wear; the second type of fault may be at least one of misalignment, looseness and oil film oscillation; the third type of fault may be at least one of steam flow excitation, rotor thermal deformation and the like.
[0064] In an embodiment provided in the present application, based on the above solution, optionally, the data processing module is used to:
[0065] When the diagnosis result indicates that the steam turbine is faulty, fault alarm information of the steam turbine is output.
[0066] In an embodiment provided in the present application, based on the above solution, optionally, the data processing module is used to:
[0067] removing outliers in the condition monitoring data and filling missing values in the condition monitoring data;
[0068] Filtering or wavelet transform technology is used to remove high-frequency noise and interference signals in the state monitoring data after filling the missing values, so as to obtain target state monitoring data.
[0069] In an embodiment provided in the present application, based on the above solution, optionally, the data processing module is further used to:
[0070] When a data query instruction of the target system is received, the target state monitoring data corresponding to the data query instruction is obtained in the storage space, and the target state monitoring data corresponding to the query instruction is sent to the target system.
[0071] In this embodiment, the target system may be a third-party system such as a remote diagnosis system.
[0072] Optionally, a balance adjustment suggestion fed back by the target system may be received and the balance adjustment suggestion may be output.
[0073] In an embodiment provided in the present application, based on the above solution, optionally, Figure 2 As shown, the steam turbine vibration monitoring system further includes a display module 206;
[0074] The display module 206 can be used to display the simulation results obtained by the simulation module on the operation status of the steam turbine during the simulation time; it can also display the fault diagnosis results, conclusions and dynamic diagnosis information obtained by the fault diagnosis module during the simulation process.
[0075] In some embodiments, the steam turbine vibration monitoring system further includes a data interface unit, which complies with various industrial protocol standards such as OPC UA, Modbus, MQTT, etc., and provides an API interface.
[0076] and Figure 1 Corresponding to the method, the embodiment of the present application further provides a steam turbine vibration monitoring method, which is applied to the above-mentioned steam turbine vibration monitoring system. The method flow chart of the method is as follows: Figure 3 As shown, specifically including:
[0077] S301: The data acquisition module acquires status monitoring data of the steam turbine during operation.
[0078] S302: The data processing module preprocesses the state monitoring data to obtain preprocessed target state monitoring data, and stores the target state monitoring data in a preset storage space.
[0079] S303: The fault diagnosis module performs fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain a fault detection result of the steam turbine.
[0080] S304: When receiving a simulation instruction, the simulation module determines the simulation time corresponding to the simulation instruction, obtains the target state monitoring data corresponding to the simulation time in the storage space, and simulates the operating state of the steam turbine at the simulation time according to the target state monitoring data corresponding to the simulation time.
[0081] In an embodiment provided by the present application, based on the above solution, optionally, the fault diagnosis module performs fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain the fault detection result of the steam turbine, including:
[0082] The fault diagnosis module generates vibration trend data for a preset time period according to vibration data in the target state monitoring data within a preset time period stored in the storage space, determines whether the steam turbine has a first type of fault according to the vibration trend data, and obtains a first diagnosis result;
[0083] The fault diagnosis module converts the vibration data in the target state monitoring data stored in the storage space from the time domain to the frequency domain to obtain frequency domain vibration data, and detects whether the steam turbine has a second type of fault according to the frequency domain vibration data to obtain a second diagnosis result;
[0084] The fault diagnosis module uses the first vibration data in the target state monitoring data stored in the storage space to detect whether the steam turbine has a third type of fault and obtain a third diagnostic result. The first vibration data is the vibration data generated by the steam turbine during start-up and shutdown or load change.
[0085] In an embodiment provided in the present application, based on the above solution, optionally, after obtaining the fault detection result of the steam turbine, the method further includes:
[0086] The fault diagnosis module outputs fault alarm information of the steam turbine when the diagnosis result indicates that the steam turbine has a fault.
[0087] In an embodiment provided in the present application, based on the above solution, optionally, the data processing module preprocesses the state monitoring data to obtain the preprocessed target state monitoring data, such as Figure 4 As shown, including:
[0088] S401: The data processing module removes abnormal values in the condition monitoring data and fills in missing values in the condition monitoring data.
[0089] S402: The data processing module uses filtering or wavelet transform technology to remove high-frequency noise and interference signals in the state monitoring data after filling the missing values, so as to obtain target state monitoring data.
[0090] In an embodiment provided by the present application, based on the above solution, optionally, after storing the target state monitoring data in a preset storage space, the method further includes:
[0091] When receiving a data query instruction from a target system, the data processing module obtains target status monitoring data corresponding to the data query instruction in the storage space, and sends the target status monitoring data corresponding to the query instruction to the target system.
[0092] See also Figure 5 , is an example diagram of an implementation scenario provided by the present application, showing an implementation scenario including a steam turbine, a routing device, a server device and a client device, wherein the server device can be used to collect status monitoring data of the steam turbine during operation. The status monitoring data is preprocessed to obtain preprocessed target status monitoring data, and the target status monitoring data is stored in a preset storage space. According to the target status monitoring data stored in the storage space, fault detection is performed on the steam turbine to obtain a fault detection result of the steam turbine. When a simulation instruction is received, the simulation time corresponding to the simulation instruction is determined, the target status monitoring data corresponding to the simulation time is obtained in the storage space, and according to the target status monitoring data corresponding to the simulation time, the operating state of the steam turbine at the simulation time is simulated.
[0093] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.
[0094] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.
[0095] For the convenience of description, the above device is described in terms of functions and is described separately in various units. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.
[0096] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.
[0097] The above is a detailed introduction to a turbine vibration monitoring system provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.
Claims
1. A steam turbine vibration monitoring system, characterized in that: include: Data acquisition module, data processing module, fault diagnosis module and simulation module; The data acquisition module is used to collect status monitoring data of the steam turbine during operation; The condition monitoring data includes at least vibration data; The data processing module is used to preprocess the state monitoring data, obtain the preprocessed target state monitoring data, and store the target state monitoring data in a preset storage space; The fault diagnosis module is used to perform fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain a fault detection result of the steam turbine; The simulation module is used to determine the simulation time corresponding to the simulation instruction when receiving the simulation instruction, obtain the target state monitoring data corresponding to the simulation time in the storage space, and simulate the operating state of the turbine at the simulation time according to the target state monitoring data corresponding to the simulation time.
2. The system according to claim 1, characterized in that The fault diagnosis module is used for: Generate vibration trend data of the preset time period according to vibration data in the target state monitoring data within the preset time period stored in the storage space, determine whether the steam turbine has a first type of fault according to the vibration trend data, and obtain a first diagnosis result; Converting vibration data in the target state monitoring data stored in the storage space from the time domain to the frequency domain to obtain frequency domain vibration data, and detecting whether the steam turbine has a second type of fault according to the frequency domain vibration data to obtain a second diagnosis result; The first vibration data in the target state monitoring data stored in the storage space is used to detect whether the steam turbine has a third type of fault to obtain a third diagnostic result, wherein the first vibration data is vibration data generated by the steam turbine during start-up and shutdown or load change.
3. The system according to claim 1, characterized in that The data processing module is used to: When the diagnosis result indicates that the steam turbine is faulty, fault alarm information of the steam turbine is output.
4. The system according to claim 1, characterized in that The data processing module is used to: removing outliers in the condition monitoring data and filling missing values in the condition monitoring data; Filtering or wavelet transform technology is used to remove high-frequency noise and interference signals in the state monitoring data after filling the missing values, so as to obtain target state monitoring data.
5. The system according to claim 1, characterized in that The data processing module is also used for: When a data query instruction of the target system is received, the target state monitoring data corresponding to the data query instruction is obtained in the storage space, and the target state monitoring data corresponding to the query instruction is sent to the target system.
6. A method for monitoring vibration of a steam turbine, characterized in that: Applied to a steam turbine vibration monitoring system, the steam turbine vibration monitoring system includes a data acquisition module, a data processing module, a fault diagnosis module and a simulation module, and the method includes: The data acquisition module acquires status monitoring data of the steam turbine during operation; the status monitoring data at least includes vibration data; The data processing module preprocesses the state monitoring data to obtain preprocessed target state monitoring data, and stores the target state monitoring data in a preset storage space; The fault diagnosis module performs fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain a fault detection result of the steam turbine; When receiving a simulation instruction, the simulation module determines the simulation time corresponding to the simulation instruction, obtains the target state monitoring data corresponding to the simulation time in the storage space, and simulates the operating state of the turbine at the simulation time based on the target state monitoring data corresponding to the simulation time.
7. The method according to claim 6, characterized in that The fault diagnosis module performs fault detection on the steam turbine according to the target state monitoring data stored in the storage space to obtain a fault detection result of the steam turbine, including: The fault diagnosis module generates vibration trend data for a preset time period according to vibration data in the target state monitoring data within a preset time period stored in the storage space, determines whether the steam turbine has a first type of fault according to the vibration trend data, and obtains a first diagnosis result; The fault diagnosis module converts the vibration data in the target state monitoring data stored in the storage space from the time domain to the frequency domain to obtain frequency domain vibration data, and detects whether the steam turbine has a second type of fault according to the frequency domain vibration data to obtain a second diagnosis result; The fault diagnosis module uses the first vibration data in the target state monitoring data stored in the storage space to detect whether the steam turbine has a third type of fault and obtain a third diagnostic result. The first vibration data is the vibration data generated by the steam turbine during start-up and shutdown or load change.
8. The method according to claim 6, characterized in that After obtaining the fault detection result of the steam turbine, the method further includes: The fault diagnosis module outputs fault alarm information of the steam turbine when the diagnosis result indicates that the steam turbine has a fault.
9. The method according to claim 6, characterized in that The data processing module preprocesses the state monitoring data to obtain preprocessed target state monitoring data, including: The data processing module removes abnormal values in the condition monitoring data and fills in missing values in the condition monitoring data; The data processing module uses filtering or wavelet transform technology to remove high-frequency noise and interference signals in the state monitoring data after filling the missing values, so as to obtain target state monitoring data.
10. The method according to claim 6, characterized in that After storing the target state monitoring data in a preset storage space, the method further includes: When receiving a data query instruction from a target system, the data processing module obtains target status monitoring data corresponding to the data query instruction in the storage space, and sends the target status monitoring data corresponding to the query instruction to the target system.