CN110705609A - Method and device for diagnosing operation state of induced draft fan, electronic equipment and storage medium - Google Patents
Method and device for diagnosing operation state of induced draft fan, electronic equipment and storage medium Download PDFInfo
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- CN110705609A CN110705609A CN201910871697.2A CN201910871697A CN110705609A CN 110705609 A CN110705609 A CN 110705609A CN 201910871697 A CN201910871697 A CN 201910871697A CN 110705609 A CN110705609 A CN 110705609A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
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- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/24323—Tree-organised classifiers
Abstract
The application discloses a method and a device for diagnosing the running state of an induced draft fan, electronic equipment and a storage medium, and relates to the technical field of machine learning. The diagnosis result is generated according to the obtained multiple operation state parameters, the pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result, so that before the induced draft fan fails, the induced draft fan is subjected to fault early warning through the mutual action among the multiple operation state parameters, the fault early warning accuracy is high, a reference basis is provided for maintenance personnel to adjust the operation state of the induced draft fan, the induced draft fan is prevented from failing, and the working efficiency is improved.
Description
Technical Field
The application relates to the technical field of machine learning, in particular to a method and a device for diagnosing the running state of an induced draft fan, electronic equipment and a storage medium.
Background
The induced draft fan is the key auxiliary machinery equipment of the thermal power plant, and has an important effect on the safe operation of the boiler. The induced draft fan runs in the environment of boiler flue gas and alternating pressure, can receive the wearing and tearing of flue gas, corruption, heating's influence, and the fault rate is higher. The failure of the induced draft fan easily causes the reduction of output of the generator set or unplanned shutdown, so how to monitor the failure of the induced draft fan and give an alarm in time is the guarantee of normal operation of the induced draft fan.
In the prior art, the common fault monitoring mode for the induced draft fan is as follows: and collecting the running state parameters of the induced draft fan in real time. For example, the operation state parameters include indexes such as induced draft fan bearing temperature, induced draft fan bearing vibration, induced draft fan motor stator temperature, and when one of the indexes is not within a preset range, a fault alarm is performed on the induced draft fan, but the fault alarm is inaccurate and cannot achieve advance warning.
Disclosure of Invention
In a first aspect, an embodiment of the present application provides a method for diagnosing an operation state of an induced draft fan, including:
acquiring various running state parameters of the draught fan during running;
and generating a diagnosis result according to the obtained various operation state parameters, a pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result.
In a second aspect, an embodiment of the present application further provides a method for diagnosing an operation state of an induced draft fan, including:
the parameter obtaining unit is configured to obtain various operation state parameters when the induced draft fan operates;
and the running state diagnosis unit is configured to generate a diagnosis result according to the obtained various running state parameters, a pre-trained random forest algorithm diagnosis model and a historical running state parameter for determining a historical diagnosis result and a correlation condition between the historical running state parameters.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
a memory having a computer program stored thereon;
a processor configured to execute the computer program in the memory to implement the steps of the method provided in the first aspect provided in the embodiments of the present application.
In a fourth aspect, this application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is used to implement, when executed by a processor, the steps of the method provided in the first aspect provided by this application.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects: the diagnosis result is generated according to the obtained multiple operation state parameters, the pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result, so that before the induced draft fan fails, the induced draft fan is subjected to fault early warning through the mutual action among the multiple operation state parameters, the fault early warning accuracy is high, a reference basis is provided for maintenance personnel to adjust the operation state of the induced draft fan, the induced draft fan is prevented from failing, and the working efficiency is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic diagram of interaction between a server and a display terminal and interaction between the server and a plurality of different types of sensors, respectively, according to an embodiment of the present disclosure;
fig. 2 is a flowchart of an embodiment of a method for diagnosing an operation state of an induced draft fan according to the embodiment of the present application;
fig. 3 is a flowchart of an embodiment of a method for diagnosing an operation state of an induced draft fan according to the embodiment of the present application;
fig. 4 is a flowchart of an embodiment of a method for diagnosing an operation state of an induced draft fan according to the embodiment of the present application;
fig. 5 is a functional block diagram of an induced draft fan operation state diagnosis device provided in the embodiment of the present application;
fig. 6 is a functional block diagram of an induced draft fan operation state diagnosis device provided in the embodiment of the present application;
fig. 7 is a circuit connection block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
The embodiment of the application provides a method for diagnosing the running state of an induced draft fan, which is applied to an electronic device 101, wherein the electronic device 101 can be a server, and the server is respectively in communication connection with a display terminal 103 and a plurality of sensors 102 of different types installed on the induced draft fan so as to realize data interaction. As shown in fig. 1, the plurality of sensors 102 of different types include a vibration sensor, a temperature sensor, a rotation speed sensor, and the like, which are not limited herein. As shown in fig. 2, the method includes:
s21: and obtaining various running state parameters of the induced draft fan during running.
Specifically, various operating state parameters of the induced draft fan during operation can be obtained directly by receiving data transmitted by various different types of sensors 102. It will be appreciated that each sensor 102 may periodically collect data based on the sampling time, and that certain sampled data may be missing due to force-inefficacy. Thus, S21 may include: the method comprises the steps of periodically collecting various running state parameters of the draught fan during running, and obtaining the average value of various historical running state parameters before the current moment if the collected data at the current sampling moment is missing.
The plurality of operating condition parameters may include, for example only, a rotational speed, a motor current, a smoke pressure, a shaft vibration, a surge, a motor vibration frequency, a motor cooling water temperature, a flow rate of a lubricating oil flowing through the motor, an oil temperature, and the like.
S22: and generating a diagnosis result according to the obtained various operation state parameters, a pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result.
Specifically, after the diagnosis result is generated, the diagnosis result is sent to the display terminal 103 to be displayed, so as to remind a worker that the current induced draft fan may have a fault and the current operation state of the induced draft fan needs to be adjusted.
According to the method for diagnosing the operation state of the induced draft fan, the diagnosis result is generated according to the obtained multiple operation state parameters, the pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result, therefore, before the induced draft fan breaks down, fault early warning is carried out on the induced draft fan through the mutual effect among the multiple operation state parameters, the fault early warning accuracy is high, a reference basis is provided for maintenance personnel to adjust the operation state of the induced draft fan, the induced draft fan is prevented from breaking down, and the working efficiency is improved.
Alternatively, as shown in fig. 3, S22 includes:
s31: and judging whether the obtained association condition among the multiple operation state parameters is the same as the association condition among the multiple historical operation state parameters of the same type, and whether the probability of the fault hidden danger is larger than a preset threshold value according to the historical diagnosis result corresponding to the association condition among the multiple historical operation state parameters of the same type, if so, executing S32, and if not, generating S33.
S32: and generating a diagnosis result representing the hidden trouble of the induced draft fan.
For example, the various operating state parameters may include a temperature of a free end of a motor of the induced draft fan, a temperature of a driving end, and a temperature of lubricating oil flowing through the driving end, and the associated conditions may be that a vibration direction of the motor of the induced draft fan is inconsistent with a preset vibration direction, the temperature of the free end is increased, the temperature of the driving end is unchanged, and the temperature of the lubricating oil flowing through the driving end is increased. If historically the vibration direction of the motor of the induced draft fan is inconsistent with the preset vibration direction, the temperature of the free end rises, the temperature of the driving end is unchanged, and the probability of the fault caused by the temperature rise of the lubricating oil flowing through the driving end is larger than a preset threshold (such as 60 percent), a diagnosis result representing the fault hidden trouble of the induced draft fan is generated.
S33: and generating a diagnosis result representing the normal operation of the induced draft fan.
Based on the above, if historically the motor vibration direction of the induced draft fan is inconsistent with the preset vibration direction, the temperature of the free end is increased, the temperature of the drive end is unchanged, and the probability of the fault occurrence caused by the temperature increase of the lubricating oil flowing through the drive end is greater than the preset threshold (for example, 60%), a diagnosis result representing the fault hidden danger of the induced draft fan is generated. If the current conditions associated with the various operation state parameters are that the vibration direction of the motor of the induced draft fan is inconsistent with the preset vibration direction, the temperature of the free end is unchanged, the temperature of the drive end is unchanged, and the temperature of the lubricating oil flowing through the drive end is increased, a diagnosis result representing the normal operation of the induced draft fan is generated. Furthermore, if historically the vibration direction of the motor of the induced draft fan is inconsistent with the preset vibration direction, the temperature of the free end is increased, the temperature of the driving end is unchanged, and the probability of the temperature rise of the lubricating oil flowing through the driving end being in fault is smaller than a preset threshold value (such as 60 percent), a diagnosis result representing the normal operation of the induced draft fan is generated.
Optionally, as shown in fig. 4, the method further includes:
s23: and generating a diagnosis result representing the fault hidden danger of the induced draft fan, and simultaneously generating the fault severity according to the first weight coefficient of each operation state parameter and the second weight coefficient of the threshold range in which each operation state parameter is positioned.
For example, the weight coefficient of the free end temperature of the motor of the induced draft fan may be set to 0.3, the weight coefficient in the temperature zone a may be 1.1, the weight coefficient in the temperature zone B may be 1.2, and the weight coefficient in the temperature zone C may be 1.3. The drive end temperature was set to 0.3, the weight coefficient in temperature interval a was 1.1, the weight coefficient in temperature interval B was 1.2, and the weight coefficient in temperature interval C was 1.3. The temperature of the lubricating oil flowing through the drive end was set to 0.4, the weight coefficient in the temperature interval a was 1.1, the weight coefficient in the temperature interval B was 1.2, the weight coefficient in the temperature interval C was 1.3,
when the multiple operation state parameters include the temperature of the free end of the motor of the induced draft fan and the temperature of the free end of the motor of the induced draft fan is in a temperature range A, the temperature of the driving end of the motor of the induced draft fan is in a temperature range B, and the temperature of the lubricating oil flowing through the driving end of the induced draft fan is in a temperature range C, the severity of the generated fault is 0.3X1.1+0.3X1.2+0.4X 1.3-1.11.
Optionally, the random forest algorithm diagnosis model is formed by training in advance according to historical operating state parameters, historical fault diagnosis results and association conditions between the historical operating state parameters for determining the historical fault diagnosis results, wherein the association conditions are taken as training samples.
The basic construction process of the random forest can be expressed as the following mode:
selecting n samples from an original training set by using a self-service sampling method, wherein the n samples are randomly replaced, and performing m times to generate m training sets; respectively training m newly generated training sets to obtain m decision tree classification models, namely m trees; for a single tree, selecting an optimal splitting mode to split according to information gain or information gain ratio or a kini index when a new node is split each time; each tree is split according to the step 3) until the training samples are correctly classified at a certain node or the maximum depth of the tree is reached; and (4) forming a random forest classifier by the generated decision trees, and determining a final classification result in a voting mode. Due to the randomness of sampling of each tree corresponding to the training set and the mode of selecting partial characteristics when new nodes are split, the random forest basically does not have the overfitting phenomenon without pruning, and has good tolerance to noise and abnormal values, high stability and strong generalization capability. In addition, the random forest is suitable for parallel computation, has higher training speed even for large samples and high-latitude data, and realizes efficient operation.
Referring to fig. 5, an induced draft fan operation state diagnosis device 500 is further provided in the embodiment of the present application, and is applied to the electronic device 101, where the electronic device 101 may be a server. It should be noted that the basic principle and the generated technical effects of the induced draft fan operation state diagnosis device 500 provided in the embodiment of the present application are the same as those of the above embodiment, and for the sake of brief description, no part of the embodiment may refer to the corresponding contents in the above embodiment. The device 500 comprises a parameter obtaining unit 501 and an operation state diagnosing unit 502. Wherein the content of the first and second substances,
the parameter obtaining unit 501 is configured to obtain various operation state parameters when the induced draft fan operates.
The operation state diagnosing unit 502 is configured to generate a diagnosis result according to the obtained various operation state parameters, a pre-trained random forest algorithm diagnosis model, and a historical operation state parameter and a correlation condition between the historical operation state parameters for determining the historical diagnosis result.
The random forest algorithm diagnosis model is formed by pre-training a training sample according to historical operating state parameters, historical fault diagnosis results and correlation conditions among the historical operating state parameters for determining the historical fault diagnosis results.
When the induced draft fan operation state diagnosis device 500 provided by the embodiment of the application is executed, the following functions can be realized: the diagnosis result is generated according to the obtained multiple operation state parameters, the pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result, so that before the induced draft fan fails, the induced draft fan is subjected to fault early warning through the mutual action among the multiple operation state parameters, the fault early warning accuracy is high, a reference basis is provided for maintenance personnel to adjust the operation state of the induced draft fan, the induced draft fan is prevented from failing, and the working efficiency is improved.
Optionally, the parameter obtaining unit 501 may be specifically configured to periodically collect multiple kinds of operation state parameters of the induced draft fan during operation, and if the collected data at the current sampling time is missing, obtain an average value of multiple kinds of historical operation state parameters before the current sampling time.
Optionally, the operation state diagnosing unit 502 may be specifically configured to generate a diagnosis result representing that the induced draft fan has the hidden fault trouble if the obtained association condition between the multiple operation state parameters is the same as the association condition between the multiple historical operation state parameters of the same type, and the historical diagnosis result corresponding to the association condition between the multiple historical operation state parameters of the same type is that the probability of the hidden fault trouble occurring is greater than a preset threshold.
Optionally, as shown in fig. 6, the apparatus 500 further includes: the fault severity generation unit 503 is configured to generate a fault severity according to the first weight coefficient of each operation state parameter and the second weight coefficient of the threshold range in which each operation state parameter is located, while generating a diagnosis result representing that the induced draft fan has a fault hidden danger.
When the diagnosis result is a diagnosis result representing that the induced draft fan has the fault hidden danger, the multiple operation state parameters comprise the temperature of the free end of a motor of the induced draft fan, the temperature of a driving end and the temperature of lubricating oil flowing through the driving end, and the related conditions are that the vibration direction of the motor of the induced draft fan is inconsistent with the preset vibration direction, the temperature of the free end is increased, the temperature of the driving end is unchanged, and the temperature of the lubricating oil flowing through the driving end is increased.
It should be noted that the execution subjects of the steps of the method provided in embodiment 1 may be the same device, or different devices may be used as the execution subjects of the method. For example, the execution subject of steps 21 and 22 may be device 1, and the execution subject of step 23 may be device 2; for another example, the execution subject of step 21 may be device 1, and the execution subjects of steps 22 and 23 may be device 2; and so on.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 7, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 7, but this does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
And the processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the fan running state diagnosis device on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring various running state parameters of the draught fan during running;
and generating a diagnosis result according to the obtained various operation state parameters, a pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result.
The method executed by the fan operation state diagnosis device according to the embodiment shown in fig. 5 of the present application may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the method in fig. 2, and implement the functions of the fan operation state diagnosis apparatus in the embodiments shown in fig. 2, fig. 3, and fig. 4, which are not described herein again in this embodiment of the present application.
Of course, besides the software implementation, the electronic device of the present application does not exclude other implementations, such as a logic device or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or a logic device.
Embodiments of the present application also propose a computer-readable storage medium storing one or more programs, the one or more programs including instructions, which when executed by a portable electronic device including a plurality of application programs, enable the portable electronic device to perform the method of the embodiments shown in fig. 2, 3, and 4, and are specifically configured to:
acquiring various running state parameters of the draught fan during running;
and generating a diagnosis result according to the obtained various operation state parameters, a pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result.
In short, the above description is only a preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Claims (10)
1. An induced draft fan operation state diagnosis method is characterized by comprising the following steps:
acquiring various running state parameters of the draught fan during running;
and generating a diagnosis result according to the obtained various operation state parameters, a pre-trained random forest algorithm diagnosis model and the correlation condition between the historical operation state parameters and the historical operation state parameters for determining the historical diagnosis result.
2. The method of claim 1, wherein generating the diagnostic result according to the obtained plurality of operating state parameters, a pre-trained random forest algorithm diagnostic model and the historical operating state parameters for determining the historical diagnostic result and the correlation condition between the historical operating state parameters comprises:
and if the obtained association condition among the multiple operation state parameters is the same as the association condition among the multiple historical operation state parameters of the same type, and the probability that the hidden trouble occurs in the historical diagnosis result corresponding to the association condition among the multiple historical operation state parameters of the same type is larger than a preset threshold value, generating a diagnosis result representing the hidden trouble of the induced draft fan.
3. The method of claim 2, further comprising: and generating a diagnosis result representing the fault hidden danger of the induced draft fan, and simultaneously generating the fault severity according to the first weight coefficient of each operation state parameter and the second weight coefficient of the threshold range in which each operation state parameter is positioned.
4. The method according to claim 2, wherein the plurality of operating state parameters comprise a free end temperature, a drive end temperature and a temperature of the lubricating oil flowing through the drive end of the motor of the induced draft fan, and the correlation condition is that a vibration direction of the motor of the induced draft fan is inconsistent with a preset vibration direction, the temperature of the free end is increased, the temperature of the drive end is unchanged and the temperature of the lubricating oil flowing through the drive end is increased.
5. The method as claimed in claim 1, wherein the random forest algorithm diagnosis model is trained in advance by using correlation conditions between historical operating state parameters, historical fault diagnosis results and historical operating state parameters for determining the historical fault diagnosis results as training samples.
6. The method of claim 1, wherein the collecting of the plurality of operation state parameters of the induced draft fan during operation comprises:
the method comprises the steps of periodically collecting various running state parameters of the draught fan during running, and obtaining the average value of various historical running state parameters before the current moment if the collected data at the current sampling moment is missing.
7. An operation state diagnostic device for an induced draft fan, comprising:
the parameter obtaining unit is configured to obtain various operation state parameters when the induced draft fan operates;
and the running state diagnosis unit is configured to generate a diagnosis result according to the obtained various running state parameters, a pre-trained random forest algorithm diagnosis model and a historical running state parameter for determining a historical diagnosis result and a correlation condition between the historical running state parameters.
8. The device according to claim 7, wherein the operating state diagnosing unit is specifically configured to generate a diagnosis result representing the potential fault of the induced draft fan if the obtained association condition between the plurality of operating state parameters is the same as the association condition between the plurality of historical operating state parameters of the same type, and the probability that the potential fault is generated according to the historical diagnosis result corresponding to the association condition between the plurality of historical operating state parameters of the same type is greater than a preset threshold value.
9. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 6.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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| CN113715796A (en) * | 2021-07-23 | 2021-11-30 | 东风汽车集团股份有限公司 | Vehicle control method, vehicle control device, hybrid vehicle, and storage medium for hybrid vehicle |
| CN113837264A (en) * | 2021-09-18 | 2021-12-24 | 深圳市裕展精密科技有限公司 | Training method, electronic equipment, equipment health diagnosis method and device |
| CN116095305A (en) * | 2023-04-12 | 2023-05-09 | 长鑫存储技术有限公司 | Method, device and medium for monitoring image acquisition system |
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