CN110865538A - Unit working condition optimization method and device and electronic equipment - Google Patents
Unit working condition optimization method and device and electronic equipment Download PDFInfo
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Abstract
The application discloses a unit working condition optimization method and device and electronic equipment, and relates to the technical field of equipment control. The unit working condition optimization method comprises the following steps: preprocessing the current state parameters of the unit; determining a target operation parameter corresponding to the current optimal technological index of the unit based on a pre-established SVM classification model and the preprocessed current state parameter, wherein the SVM classification model is established according to the historical optimal technological index of the unit and the corresponding historical state parameter and historical operation parameter; if the target operation parameters meet the execution conditions, performing optimization control on the unit according to the target operation parameters; otherwise, reconstructing the SVM classification model. The method and the device for optimizing the working condition of the unit and the electronic equipment can enable the working condition of the unit in the operation process to be close to the optimal working condition, and reduce the energy consumption of the unit.
Description
Technical Field
The application relates to the technical field of equipment control, in particular to a method and a device for optimizing unit working conditions and electronic equipment.
Background
Data of a unit of a thermal power plant in an operation process often presents the characteristic of being complex, mainly reflects that the data volume is huge, noise and incompleteness exist, great difficulty is caused to data processing, and a plurality of potential operation rules and knowledge are accumulated in the data.
Currently, the control of the thermal power plant unit is mostly controlled in real time based on a mechanism model and related feedback. However, since the real environment is often complex and changeable, the operation rule and the optimized parameters of the unit are also continuously evolved at any time along with the change of the fire coal and the change of the environment, and when the control is performed based on the mechanism model and the related feedback, the actual working condition is often far from the optimal working condition.
Therefore, how to provide an effective scheme to optimize the working condition of the unit and make the working condition of the unit close to the optimal working condition which can be achieved by the unit is an urgent problem to be solved in the prior art.
Disclosure of Invention
The embodiment of the application provides a method for optimizing the working condition of a unit, which aims to solve the problem that the working condition of the unit is far from the optimal working condition in the prior art.
The embodiment of the application also provides a unit working condition optimizing device, so as to solve the problem that the working condition of the unit is far from the optimal working condition in the prior art.
The embodiment of the application also provides the electronic equipment.
The embodiment of the application adopts the following technical scheme:
a method for optimizing the working condition of a unit comprises the following steps:
preprocessing the current state parameters of the unit;
determining a target operation parameter corresponding to the current optimal process index of the unit based on a pre-established SVM classification model and the preprocessed current state parameter, wherein the SVM classification model is established according to the historical optimal process index of the unit and the corresponding historical state parameter and historical operation parameter;
if the target operation parameters meet execution conditions, performing optimization control on the unit according to the target operation parameters;
otherwise, reconstructing the SVM classification model.
The utility model provides a unit operating mode optimizing apparatus, unit operating mode optimizing apparatus includes:
the first preprocessing module is configured to preprocess the current state parameters of the unit;
the determining module is configured to determine a target operation parameter corresponding to a current optimal process index of the unit based on a pre-established SVM classification model and the preprocessed current state parameter, wherein the SVM classification model is established according to a historical optimal process index of the unit and a historical state parameter and a historical operation parameter corresponding to the historical optimal process index;
a determination module configured to determine whether the target operating parameter meets an execution condition;
the optimization control module is configured to perform optimization control on the unit according to the target operation parameters if the target operation parameters meet execution conditions;
a reconstruction module configured to reconstruct the SVM classification model.
An electronic device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the bus;
a memory for storing a computer program;
the processor is used for executing the program stored in the memory and realizing the following processes:
preprocessing the current state parameters of the unit;
determining a target operation parameter corresponding to the optimal process index of the unit by taking the preprocessed current state parameter as input based on a pre-established SVM classification model, wherein the SVM classification model is established according to the historical optimal process index of the unit and the corresponding historical state parameter and historical operation parameter;
if the target operation parameters meet execution conditions, performing optimization control on the unit according to the target operation parameters;
otherwise, reconstructing the SVM classification model.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects:
because the SVM classification model is established in advance according to the historical optimal process index of the unit and the corresponding historical state parameter and historical operation parameter, when the unit is controlled, the target operation parameter corresponding to the current optimal process index of the unit can be determined according to the pre-established SVM classification model and the preprocessed current state parameter, when the target operation parameter meets the execution condition, the unit is optimally controlled according to the target parameter, otherwise, the SVM classification model is reestablished. Therefore, the working condition of the unit in the operation process can be close to the optimal working condition, the energy consumption of the unit is reduced, and the economical efficiency is good.
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 flowchart of a unit working condition optimization method provided in an embodiment of the present application.
Fig. 2 is a flowchart of reconstructing an SVM classification model according to an embodiment of the present application.
Fig. 3 is a flowchart of another unit operating condition optimization method provided in the embodiment of the present application.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of the unit working condition optimization device provided in the 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.
In order to enable the working condition of a unit of a thermal power plant in the operation process to be close to the optimal working condition, the embodiment of the application provides a method and a device for optimizing the working condition of the unit and electronic equipment. The method, the device and the electronic equipment for optimizing the working condition of the unit can determine a target operation parameter corresponding to the current optimal technological index of the unit according to a pre-established SVM classification model and the current state parameter, and optimally control the unit according to the target operation parameter when the target operation parameter meets the execution condition.
The execution subject of the method may be a server or a user terminal, and the execution subject does not constitute a limitation of the present application.
For convenience of description, unless otherwise specified, in the embodiments of the present application, an execution subject is exemplified as a server.
Please refer to fig. 1, which is a flowchart of a method for optimizing a unit operating condition according to an embodiment of the present application, including the following steps:
step S101, the historical state parameters and the historical operation parameters are preprocessed.
In the embodiment of the present application, the state parameter refers to data reflecting a unit production operation state of a thermal power plant, and the state parameter includes, but is not limited to, parameters such as a unit operation mode, an exhaust gas temperature, a condenser vacuum, a main steam flow, a furnace negative pressure, and the like.
The operation parameters are parameter data which can be adjusted and controlled in the running process of the unit, and include, but are not limited to, steam temperature, temperature-reducing water quantity, coal supply quantity and the like.
The unit is provided with sensing equipment for detecting various state parameters of the unit, and the unit and the various set sensing equipment upload historical operating parameters and historical state parameters of the unit to the server in the operation process of the unit. For example, the exhaust gas temperature may be detected by a temperature sensor. And for the negative pressure of the hearth, a pressure sensor can be adopted for detection. For the unit operation mode, the unit can directly upload the operation mode to the server.
The historical state parameters and the historical operation parameters are preprocessed, and the denoising and conversion can be performed on the historical state parameters and the historical operation parameters, so that unified data, namely data with unified dimension and unified format, is obtained, and operation processing can be performed subsequently.
And denoising the historical state parameters and the historical operating parameters, which can be removing noise data in the historical state parameters and the historical operating parameters, and interpolating and filling missing data. For example, when a data value in a certain historical state parameter or a certain historical operation parameter changes abruptly in a short time so that the difference between the data value and an adjacent data value is extremely large, the abruptly changed data value is considered as noise data, and the abruptly changed data value is removed and the missing data value is filled up by data interpolation. In a certain historical state parameter or a certain historical operating parameter, if a data value at a certain moment is missing, the missing data value can also be filled in by means of data interpolation.
In one or more embodiments of the present application, if one or more of the historical state parameters or the historical operating parameters have little influence on the operating condition of the unit or do not have any influence on the operating condition of the unit, the historical state parameters or the historical operating parameters may be subjected to dimensionality reduction, that is, the influence on the operating condition of the unit is removed or no influence parameter is generated on the operating condition of the unit, so as to reduce the data computation.
And step S103, establishing an SVM classification model.
The optimal process index is the target required to be achieved in the production process, and for the unit of the thermal power plant, the process index mainly aims at the power supply coal consumption, so the optimal process index can be the lowest coal consumption under different loads.
Before the working condition of the unit is optimally controlled, the lowest coal consumption under different loads and the corresponding historical state parameters and historical operation parameters thereof, namely the historical optimal process indexes and the corresponding historical state parameters and historical operation parameters thereof, can be counted from a large amount of historical operation data of the unit in a manual counting mode.
After the historical state parameters and the historical operation parameters are preprocessed, the preprocessed historical state parameters and the historical optimal process indexes can be used as input, the preprocessed historical operation parameters are used as output, and an SVM classification model is established.
In the embodiment of the application, a gaussian kernel function can be adopted to participate in the calculation of the SVM classification model.
And step S105, preprocessing the current state parameters of the unit.
When the working condition of the unit is optimally controlled, the unit and various set sensing devices upload the current operating parameters of the unit to a server. And preprocessing the current state parameters of the unit at the server side.
The preprocessing of the current state parameters of the unit may include, but is not limited to, denoising and converting the current state parameters, which is specifically consistent with the denoising and converting manner in step S101, and is not described herein again.
Similarly, according to the historical operating parameters when the SVM classification model is established, the dimension reduction processing can be carried out on the current state parameters.
And S107, determining a target operation parameter corresponding to the current optimal process index of the unit based on a pre-established SVM classification model.
After the current state parameters of the unit are preprocessed, the preprocessed current state parameters and the current optimal technological indexes of the unit can be used as the input of the established SVM classification model for operation, and the target operation parameters corresponding to the current optimal technological indexes of the unit are calculated. The current optimal process index can be determined according to the historical optimal process index (for example, if the current unit is required to have the lowest coal consumption under 80% of load, the lowest coal consumption of the unit under 80% of load can be found according to the historical record), and therefore the target operation parameter corresponding to the current optimal process index can be calculated.
Step S109, judging whether the target operation parameter accords with the execution condition, if so, executing step S111; if not, step S113 is performed.
In the process of controlling the unit, some operating parameters may be associated with each other, so that after one or more operating parameters reach the required values, the associated one or more operating parameters cannot reach the required values. For example, assuming the operating parameters include the ratio of the damper opening to the mixture entering the combustion chamber, the mixture entering the combustion chamber may not reach the normally required ratio when the damper opening is too low.
Therefore, after the target operation parameter corresponding to the current optimal process index of the unit is determined, the target operation parameter needs to be judged, and whether the target operation parameter meets the execution condition is judged, that is, whether each operation parameter of the unit can simultaneously reach the required value in the target operation parameter is judged. If yes, the target operation parameter is satisfied with the execution condition, and S111 is executed. If not, the target operation parameter is not satisfied with the execution condition, and step S113 is executed.
For example, in the target operating parameters, the damper opening degree is 40%, and the content of gas a in the mixed gas is 15%. However, in the actual case, when the damper opening degree is 40%, the content of the gas a in the mixed gas cannot reach 15%, and the target operation parameter is judged not to be in compliance with the execution condition.
It should be noted that the above relation between the opening degree of the damper and the ratio of the mixture gas in the combustion chamber is merely an example for facilitating understanding of the present application, and is not a limitation of the present application.
And step S111, performing optimization control on the unit according to the target operation parameters.
If the target operation parameters meet the execution conditions, the unit can be optimally controlled according to the target operation parameters, so that the numerical values of all parameters of the unit reach the numerical values of all parameters recorded in the target operation parameters. At this time, the coal consumption of the unit under the current load can be close to the minimum coal consumption which can be achieved by the unit, namely close to the optimal working condition of the unit.
And step S113, reconstructing the SVM classification model.
And if the target operation parameters meet the execution conditions, reconstructing the SVM classification model.
Referring to fig. 2, in the embodiment of the present application, reconstructing the SVM classification model includes the following steps.
In step S201, the historical state parameters and the historical operating parameters are adjusted.
In the embodiment of the present application, adjusting the historical state parameters and the historical operation parameters means increasing or decreasing data dimensions of the historical state parameters and the historical operation parameters, or exchanging some parameters of the historical state parameters and exchanging some parameters of the historical operation parameters.
For example, when the SVM classification model is constructed last time, the parameters A, B, C, D, E are included in the historical state parameters, and the parameters a, b, c, d, e are included in the historical operation parameters. And if the parameter A in the historical state parameters and the parameter a in the historical operating parameters have relatively small influence on the working condition of the unit. Then parameter a in the historical state parameters and parameter a in the historical operating parameters may be removed when adjusting the historical state parameters and the historical operating parameters. Or replacing the parameter A in the historical state parameters with the historical parameter F of the production running state of the reactor set, and replacing the parameter a in the historical operating parameters with the historical parameter F which can be regulated and controlled.
Step S203, the adjusted historical state parameters and the adjusted historical operation parameters are preprocessed.
Similarly, the adjusted historical state parameters are preprocessed, including but not limited to denoising and converting the adjusted historical state parameters.
The adjusted historical operating parameters are preprocessed, including but not limited to denoising and converting the adjusted historical operating parameters.
And S205, taking the adjusted preprocessing result of the historical state parameters and the historical optimal process indexes as input, taking the adjusted preprocessing result of the historical operation parameters as output, and reestablishing the SVM classification model.
Please refer to fig. 3, which is a flowchart of another method for optimizing the operating condition of the unit according to the embodiment of the present application, including the following steps:
and S301, preprocessing the current state parameters of the unit.
Step S303, determining a target operation parameter corresponding to the current optimal process index of the unit based on a pre-established SVM classification model.
Step S305, judging whether the target operation parameter meets the execution condition, if so, executing step S307; if not, step S309 is performed.
And step S307, performing optimization control on the unit according to the target operation parameters.
Step S309, reconstructing the SVM classification model.
In summary, the method for optimizing the unit operating condition provided in the embodiment of the present application may pre-establish an SVM classification model according to the historical optimal process index of the unit, the historical state parameter and the historical operating parameter corresponding to the historical optimal process index, determine the target operating parameter corresponding to the current optimal process index of the unit according to the pre-established SVM classification model and the preprocessed current state parameter when controlling the unit, and perform optimal control on the unit according to the target operating parameter when the target operating parameter meets the execution condition. Therefore, the working condition of the unit in the operation process can be close to the optimal working condition, the energy consumption of the unit is reduced, and the economical efficiency is good. Meanwhile, when the target operation parameters do not accord with the execution conditions, the SVM classification model is reconstructed, so that the interaction and the action among the parameters can be considered, the phenomenon that the interaction and the action among the operation parameters cause the operation is considered is avoided, and more accurate guidance can be provided for the operation guidance of the unit. In addition, the unit working condition optimization method provided by the embodiment of the application can reduce the decision difficulty of the operation personnel for optimizing the operation parameters, and is favorable for the execution effect and the acceptability of the unit working condition optimization.
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. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 4, 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. 4, but that 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 to the memory and then runs the computer program to form the unit working condition optimizing device on a logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
preprocessing the current state parameters of the unit;
determining a target operation parameter corresponding to the current optimal process index of the unit based on a pre-established SVM classification model and the preprocessed current state parameter, wherein the SVM classification model is established according to the historical optimal process index of the unit and the corresponding historical state parameter and historical operation parameter;
if the target operation parameters meet execution conditions, performing optimization control on the unit according to the target operation parameters;
otherwise, reconstructing the SVM classification model.
The method executed by the unit condition optimizing device disclosed in the embodiments of fig. 1-3 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 may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware component. 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 also execute the method shown in fig. 1-3, and implement the functions of the unit working condition optimization apparatus in the embodiments shown in fig. 1-3, which are not described herein again in this 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 provide a computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a portable electronic device comprising a plurality of application programs, enable the portable electronic device to perform the method of the embodiments shown in fig. 1-3, and are specifically configured to:
preprocessing the current state parameters of the unit;
determining a target operation parameter corresponding to the current optimal process index of the unit based on a pre-established SVM classification model and the preprocessed current state parameter, wherein the SVM classification model is established according to the historical optimal process index of the unit and the corresponding historical state parameter and historical operation parameter;
if the target operation parameters meet execution conditions, performing optimization control on the unit according to the target operation parameters;
otherwise, reconstructing the SVM classification model.
Fig. 5 is a schematic structural diagram of a unit operating condition optimizing device 500 according to an embodiment of the present application. Referring to fig. 5, in a software implementation, the crew condition optimizing device 500 may include:
the first preprocessing module 501 is configured to preprocess the current state parameters of the unit.
Specifically, the first preprocessing module 501 is configured to denoise and convert the current state parameter, so as to obtain data of a unified standard.
The determining module 503 is configured to determine a target operation parameter corresponding to a current optimal process indicator of the unit based on a pre-established SVM classification model and the pre-processed current state parameter, where the SVM classification model is established according to a historical optimal process indicator of the unit and a historical state parameter and a historical operation parameter corresponding to the historical optimal process indicator.
A determining module 505 configured to determine whether the target operating parameter meets an execution condition.
An optimization control module 507 configured to perform optimization control on the unit according to the target operation parameter if the target operation parameter meets an execution condition.
A reconstruction module 509 configured to reconstruct the SVM classification model.
Specifically, the reconstruction module 509 is configured to adjust the historical state parameters and the historical operating parameters, and pre-process the adjusted historical state parameters and the adjusted historical operating parameters; and taking the adjusted preprocessing result of the historical state parameters and the historical optimal process indexes as input, taking the adjusted preprocessing result of the historical operation parameters as output, and reestablishing the SVM classification model.
In this embodiment, the unit condition optimizing apparatus 500 may further include:
a second pre-processing module 511 configured to pre-process the historical state parameters and the historical operating parameters.
A building module 513 configured to build the SVM classification model with the preprocessed historical state parameters and the historical optimal process indicators as inputs and the preprocessed historical operating parameters as outputs.
To sum up, the unit operating condition optimizing device 500 provided in this embodiment of the present application may previously establish an SVM classification model according to the historical optimal process index of the unit, the historical state parameter and the historical operating parameter corresponding to the historical optimal process index, determine the target operating parameter corresponding to the current optimal process index of the unit according to the SVM classification model established in advance and the preprocessed current state parameter when controlling the unit, and perform optimal control on the unit according to the target operating parameter when the target operating parameter meets the execution condition. Therefore, the working condition of the unit in the operation process can be close to the optimal working condition, the energy consumption of the unit is reduced, and the economical efficiency is good. Meanwhile, when the target operation parameters do not accord with the execution conditions, the SVM classification model is reconstructed, so that the interaction and the action among the parameters can be considered, the phenomenon that the interaction and the action among the operation parameters cause the operation is considered is avoided, and more accurate guidance can be provided for the operation guidance of the unit. In addition, the unit working condition optimization device 500 provided by the embodiment of the application can reduce the decision difficulty of the operation personnel in optimizing the operation parameters, and is beneficial to the execution effect and the acceptability of the unit working condition optimization.
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. A method for optimizing the working condition of a unit is characterized by comprising the following steps:
preprocessing the current state parameters of the unit;
determining a target operation parameter corresponding to the current optimal process index of the unit based on a pre-established SVM classification model and the preprocessed current state parameter, wherein the SVM classification model is established according to the historical optimal process index of the unit and the corresponding historical state parameter and historical operation parameter;
if the target operation parameters meet execution conditions, performing optimization control on the unit according to the target operation parameters;
otherwise, reconstructing the SVM classification model.
2. The method of claim 1, wherein prior to the pre-processing of the current state parameters of the crew, the method further comprises:
preprocessing the historical state parameters and the historical operation parameters;
and establishing the SVM classification model by taking the preprocessed historical state parameters and the historical optimal process indexes as input and the preprocessed historical operation parameters as output.
3. The method of claim 2, wherein said reconstructing the SVM classification model comprises:
adjusting the historical state parameters and the historical operating parameters;
preprocessing the adjusted historical state parameters and the adjusted historical operation parameters;
and reestablishing the SVM classification model by taking the adjusted preprocessing result of the historical state parameters and the historical optimal process indexes as input and the adjusted preprocessing result of the historical operation parameters as output.
4. The method according to claim 1, wherein the preprocessing of the current state parameters of the crew comprises:
and denoising and converting the current state parameters to obtain unified data.
5. The method of claim 4, wherein denoising the current state parameter comprises:
and removing noise data in the current state parameters and interpolating and filling missing data.
6. The utility model provides a unit operating mode optimizing device which characterized in that unit operating mode optimizing device includes:
the first preprocessing module is configured to preprocess the current state parameters of the unit;
the determining module is configured to determine a target operation parameter corresponding to a current optimal process index of the unit based on a pre-established SVM classification model and the preprocessed current state parameter, wherein the SVM classification model is established according to a historical optimal process index of the unit and a historical state parameter and a historical operation parameter corresponding to the historical optimal process index;
a determination module configured to determine whether the target operating parameter meets an execution condition;
the optimization control module is configured to perform optimization control on the unit according to the target operation parameters if the target operation parameters meet execution conditions;
a reconstruction module configured to reconstruct the SVM classification model.
7. The unit operating condition optimizing device according to claim 6, further comprising:
a second pre-processing module configured to pre-process the historical state parameters and the historical operating parameters;
the establishing module is configured to establish the SVM classification model by taking the preprocessed historical state parameters and the historical optimal process indexes as input and the preprocessed historical operation parameters as output.
8. The unit operating condition optimization device according to claim 7, wherein the reconstruction module is configured to adjust the historical state parameters and the historical operating parameters;
preprocessing the adjusted historical state parameters and the adjusted historical operation parameters; and
and reestablishing the SVM classification model by taking the adjusted preprocessing result of the historical state parameters and the historical optimal process indexes as input and the adjusted preprocessing result of the historical operation parameters as output.
9. The unit operating condition optimizing device according to claim 6, wherein the first preprocessing module is configured to denoise and convert the current state parameters to obtain unified data.
10. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing the communication between the processor and the memory through the bus;
a memory for storing a computer program;
the processor is used for executing the program stored in the memory and realizing the following processes:
preprocessing the current state parameters of the unit;
determining a target operation parameter corresponding to the optimal process index of the unit by taking the preprocessed current state parameter as input based on a pre-established SVM classification model, wherein the SVM classification model is established according to the historical optimal process index of the unit and the corresponding historical state parameter and historical operation parameter;
if the target operation parameters meet execution conditions, performing optimization control on the unit according to the target operation parameters;
otherwise, reconstructing the SVM classification model.
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