CN114881234A - Blast furnace condition reasoning method and device, electronic equipment and storage medium - Google Patents
Blast furnace condition reasoning method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application relates to the field of blast furnace smelting, in particular to a blast furnace condition reasoning method, a blast furnace condition reasoning device, electronic equipment and a storage medium, wherein the method comprises the steps of obtaining a furnace condition type of a blast furnace, and then obtaining a corresponding reasoning rule based on the furnace condition type; and analyzing the inference rule to obtain a parameter type, acquiring a target parameter in the blast furnace based on the parameter type, and then performing furnace condition inference based on the target parameter and the inference rule to determine the furnace condition state of the blast furnace. This application can be applicable to multiple blast furnace and carry out the reasoning of furnace condition.
Description
Technical Field
The application relates to the field of blast furnace smelting, in particular to a blast furnace condition reasoning method and device, electronic equipment and a storage medium.
Background
Blast furnace smelting as the main force of modern metal smelting process has become the object of the key research of technicians in the field, but the blast furnace is like a black box, and the running state and various intermediate parameters cannot be directly observed, so that the judgment of the operating personnel on the running state of the blast furnace is lack of basis.
At present, the rule of the furnace condition reasoning method used in the related technology in the industry is fixed, but the reality is that the rule of the furnace condition reasoning method is not suitable for the characteristic that the operation of the blast furnace is variable because the production conditions of different blast furnaces are different. The inference rules cannot be defined freely from different blast furnaces.
Disclosure of Invention
In order to be applicable to various blast furnaces for reasoning about furnace conditions, the application provides a method and a device for reasoning about the furnace conditions of the blast furnaces, electronic equipment and a storage medium.
In a first aspect, the present application provides a blast furnace condition inference method, which adopts the following technical scheme:
a method for reasoning the furnace condition of a blast furnace comprises
Acquiring the type of the furnace condition of the blast furnace;
acquiring a corresponding inference rule based on the furnace condition type;
analyzing the inference rule to obtain a parameter type;
acquiring target parameters in the blast furnace based on the parameter types;
and carrying out furnace condition reasoning based on the target parameters and the reasoning rules to determine the furnace condition state of the blast furnace.
By adopting the technical scheme, after the furnace condition type is obtained, the corresponding inference rule is obtained based on the furnace condition type, and different inference rules can be adopted to carry out inference aiming at different furnace conditions, so that each furnace condition can be inferred under a more appropriate inference rule to obtain a more accurate inference result; meanwhile, after the inference rule is analyzed, the needed target parameters are determined and obtained, the acquisition time and cost of useless parameters are reduced, the inference time and cost can be reduced, and the more accurate state in the blast furnace can be obtained conveniently.
In a possible implementation manner, the obtaining of the corresponding inference rule based on the furnace condition type includes:
acquiring a corresponding inference rule based on the furnace condition type and a preset mapping relation between the furnace condition type and the inference rule;
and acquiring an inference rule input by a user.
By adopting the technical scheme, the inference rule can be preset to improve the convenience and the efficiency in use, and meanwhile, the inference rule can be modified and input by a user to deal with the occurrence of furnace conditions under special conditions, so that the matching degree of the inference rule and the furnace conditions of the blast furnace is further improved.
In one possible implementation manner, the obtaining of the target parameter in the blast furnace based on the parameter type includes:
acquiring a current target parameter at the current moment in the blast furnace based on the parameter type;
acquiring a contrast parameter in the blast furnace based on the parameter type, wherein the contrast parameter is a target parameter of the blast furnace at a contrast moment, and the contrast moment is a moment corresponding to a preset period before the current moment;
the target parameters comprise a current target parameter and a comparison parameter.
In one possible implementation, the performing of furnace condition inference based on the target parameter and the inference rule includes:
determining a parameter variation based on the current target parameter and the comparison parameter;
and carrying out furnace condition reasoning based on the parameter variation and the reasoning rule.
In one possible implementation, the method further includes:
and determining the operation suggestions required to be executed based on the furnace condition state and the preset mapping relation between the furnace condition state and the operation suggestions.
By adopting the technical scheme, after the furnace condition state is determined, the operation suggestion is given, so that the prompt is facilitated for the user, and particularly for the personnel with insufficient experience or unfamiliar experience, the working efficiency can be improved.
In a possible implementation manner, each inference rule at least includes a preset judgment condition, and further includes:
sequencing all the furnace condition states according to the time sequence;
generating associated information by using the target parameters, the parameter variation and the inference rule corresponding to each furnace condition state, and associating the associated information with the furnace condition state;
and marking the satisfied judgment condition and the unsatisfied judgment condition in each piece of associated information in a differentiation manner.
By adopting the technical scheme, the target parameters, the parameter variation and the inference rule corresponding to the furnace condition state are used for generating the associated information, and the associated information is associated with the furnace condition state, so that the completed inference process can be conveniently analyzed subsequently, the satisfied and the non-satisfied judgment conditions can be marked in a differentiation manner, and the checking and distinguishing by a user can be conveniently realized.
In a possible implementation mode, acquiring information to be confirmed, wherein the information to be confirmed is associated information corresponding to a preset type of furnace condition state;
and sending the information to be confirmed to a preset address.
By adopting the technical scheme, for the preset type of furnace condition information, the corresponding associated information is generated into the information to be confirmed and sent to the preset address, so that the information is convenient to store and check.
In a second aspect, the present application provides a blast furnace condition inference device, which adopts the following technical solution:
an inference device of blast furnace conditions, comprising:
the furnace condition type acquisition module is used for acquiring the furnace condition type of the blast furnace;
the inference rule obtaining module is used for obtaining a corresponding inference rule based on the furnace condition type;
the analysis module is used for analyzing the inference rule to obtain a parameter type;
the target parameter acquisition module is used for acquiring target parameters in the blast furnace based on the parameter types;
and the reasoning module is used for carrying out furnace condition reasoning based on the target parameters and the reasoning rules and determining the furnace condition state of the blast furnace.
By adopting the technical scheme, after the furnace condition type is obtained, the device can obtain the corresponding inference rule based on the furnace condition type, and can infer by adopting different inference rules aiming at different furnace conditions, so that each furnace condition can be inferred under the more appropriate inference rule to obtain a more accurate inference result; meanwhile, after the inference rule is analyzed, the needed target parameters are determined and obtained, the acquisition time and cost of useless parameters are reduced, the inference time and cost can be reduced, and the more accurate state in the blast furnace can be obtained conveniently.
In a possible implementation manner, when the inference rule obtaining module obtains the corresponding inference rule based on the furnace condition type, the inference rule obtaining module is specifically configured to:
acquiring a corresponding inference rule based on the furnace condition type and a preset mapping relation between the furnace condition type and the inference rule;
and acquiring an inference rule input by a user.
In a possible implementation manner, when the target parameter obtaining module obtains the target parameter in the blast furnace based on the parameter type, the target parameter obtaining module is specifically configured to:
acquiring a current target parameter at the current moment in the blast furnace based on the parameter type;
acquiring a contrast parameter in the blast furnace based on the parameter type, wherein the contrast parameter is a target parameter of the blast furnace at a contrast moment, and the contrast moment is a moment corresponding to a preset period before the current moment;
the target parameters comprise a current target parameter and a comparison parameter.
In a possible implementation manner, when the inference module performs the furnace condition inference based on the target parameter and the inference rule, the inference module is specifically configured to:
determining a parameter variation based on the current target parameter and the comparison parameter;
and carrying out furnace condition reasoning based on the parameter variation and the reasoning rule.
In one possible implementation, the apparatus further includes:
and the operation suggestion determining module is used for determining the operation suggestions to be executed based on the furnace condition states and the preset mapping relation between the furnace condition states and the operation suggestions.
In one possible implementation, the apparatus further includes:
the sequencing module is used for sequencing all the furnace condition states according to the time sequence;
the correlation module is used for generating correlation information from the target parameters, the parameter variation and the inference rule corresponding to each furnace condition state, and correlating the correlation information with the furnace condition state;
and the marking module is used for differentially marking the satisfied judgment condition and the unsatisfied judgment condition in each piece of associated information.
In one possible implementation, the apparatus further includes:
the to-be-confirmed information acquisition module is used for acquiring to-be-confirmed information, wherein the to-be-confirmed information is associated information corresponding to a preset type of furnace condition state;
and the sending module is used for sending the information to be confirmed to a preset address.
In a third aspect, the present application provides an electronic device, which adopts the following technical solutions:
an electronic device, comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in the memory and configured to be executed by the at least one processor, the at least one application configured to: the method for reasoning the furnace condition of the blast furnace is executed.
In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:
a computer-readable storage medium, comprising: a computer program is stored which can be loaded by a processor and which implements the method of inferring the condition of a blast furnace as described above.
In summary, the present application includes at least one of the following beneficial technical effects:
after the furnace condition types are obtained, corresponding inference rules are obtained based on the furnace condition types, and different inference rules can be adopted for inference aiming at different furnace conditions, so that each furnace condition can be inferred under a more suitable inference rule to obtain a more accurate inference result; meanwhile, after the inference rule is analyzed, the needed target parameters are determined and obtained, so that the acquisition time and cost of useless parameters are reduced, the inference time and cost can be reduced, and the more accurate state in the blast furnace can be obtained conveniently;
the inference rule can be preset to improve the convenience and the efficiency in use, and meanwhile, the inference rule can be modified and input by a user to deal with the occurrence of furnace conditions under special conditions, so that the matching degree of the inference rule and the furnace conditions of the blast furnace is further improved;
and generating associated information by using the target parameters, the parameter variation and the inference rule corresponding to the furnace condition state, associating the associated information with the furnace condition state, so that the completed inference process can be conveniently analyzed subsequently, and meanwhile, the satisfied and unsatisfied judgment conditions are differentially marked, and the checking and distinguishing of a user are also convenient.
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FIG. 1 is a schematic flow chart showing a method of inferring a condition of a blast furnace in an embodiment of the present application;
FIG. 2 is a schematic structural diagram of a blast furnace condition inference device in the embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-3.
A person skilled in the art, after reading the present specification, may make modifications to the present embodiments as necessary without inventive contribution, but only within the scope of the claims of the present application are protected by patent laws.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all 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 addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship, unless otherwise specified.
In the actual smelting process, because the contents of metal elements in different batches of ores or raw materials are different, the factors to be considered in smelting are the same as much as possible for different metals; further, the types of blast furnaces are different, so that the conditions of the blast furnaces are various. In the embodiment of the present application, blast furnace ironmaking is taken as a main scenario for illustration, but this is not intended to limit the application scenario of the embodiment of the present application.
The embodiment of the application provides a blast furnace condition reasoning method, which is executed by electronic equipment, and referring to fig. 1, the method comprises steps S101 to S105, wherein:
and step S101, acquiring the furnace condition type of the blast furnace.
In the embodiment of the present application, the furnace condition type of the blast furnace may be input by a user, or after the type of the raw material and the model of the blast furnace are obtained, the corresponding furnace condition type may be determined based on a mapping relationship between a preset combination of the type and the model and the furnace condition type.
And S102, acquiring a corresponding inference rule based on the furnace condition type.
In the embodiment of the application, after the furnace condition type is obtained, all inference rules corresponding to the furnace condition type can be determined. Further, each inference rule should include at least one judgment condition, and each judgment condition has two judgment results, namely true and false, where each judgment result corresponds to a preset possible state.
And step S103, analyzing the inference rule to obtain a parameter type.
In the embodiment of the present application, whether the determination condition in each inference rule is satisfied is determined, that is, whether the parameter of the corresponding type meets the determination condition is determined, if yes, the determination condition is satisfied, and if not, the determination condition is not satisfied. Therefore, each judgment condition should also include the corresponding parameter type. By analyzing the inference rules, the parameter types required to be acquired in each inference rule, such as hydrogen concentration, oxygen concentration, temperature, etc., can be obtained.
And S104, acquiring target parameters in the blast furnace based on the parameter types.
In the embodiment of the application, after the parameter type is obtained, the corresponding parameter in the blast furnace, namely the target parameter, is obtained based on the parameter type; further, some parameter types need to obtain the variation, and some parameter types are real-time quantities, so that each parameter type is also associated with the variation and/or the real-time quantity.
And S105, carrying out furnace condition reasoning based on the target parameters and the reasoning rules, and determining the furnace condition state of the blast furnace.
Specifically, after the target parameters are acquired, the target parameters are inferred through the determined inference rule, and then the furnace condition state of the blast furnace can be obtained. Wherein, the state of the furnace condition of the blast furnace can be any one or a combination of a phenomenon, a reaction stage and a fault. For example, it may be that the reaction rate is normal, the second stage of the reaction, there is a water leak, etc.
Further, the inference can be performed in real time or at intervals, and is not limited in any way in the embodiments of the present application.
Compared with the prior art that all furnace conditions adopt fixed inference rules, the scheme of the method is that after the furnace condition types are obtained, corresponding inference rules are obtained based on the furnace condition types, and different inference rules can be adopted for inference aiming at different furnace conditions, so that each furnace condition can be inferred under a more appropriate inference rule to obtain a more accurate inference result; meanwhile, after the inference rule is analyzed, the needed target parameters are determined and obtained, the acquisition time and cost of useless parameters are reduced, the inference time and cost can be reduced, and the more accurate state in the blast furnace can be obtained conveniently.
Further, in order to increase the applicability of the present application and to better meet the actual production requirements, step S102 may include step S1O21 (not shown in the figure) and step S1022 (not shown in the figure), wherein:
S1O21, acquiring a corresponding inference rule based on the furnace condition type and the preset mapping relation between the furnace condition type and the inference rule;
and S1O22, acquiring an inference rule input by a user.
Specifically, the inference rule may be acquired by the electronic device, or may be input by the user, or modified by the user based on the inference rule acquired by the electronic device.
In actual production, some furnace conditions are not standard, for example, the content of some batches of raw materials is greatly different or uneven, so that all the existing preset reasoning rules may not meet the furnace conditions at the moment; however, the user can make a self-defined modification, which may be to re-input the inference rule, or to modify the inference rule based on the existing inference rule similar to the inference rule, so as to adapt to the current furnace condition.
Further, step S104 may include step S1041 (not shown in the figure), step S1042 (not shown in the figure), and step S1043 (not shown in the figure), wherein:
s1041, acquiring a current target parameter at the current moment in the blast furnace based on the parameter type;
step S1042, obtaining a contrast parameter in the blast furnace based on the parameter type, wherein the contrast parameter is a target parameter of the blast furnace at a contrast moment, and the contrast moment is a moment corresponding to a preset period before the current moment;
in step S1043, the target parameters include a current target parameter and a comparison parameter.
Specifically, the current target parameter is a real-time parameter and can be directly used for judging the corresponding judgment condition, and the comparison parameter is used for calculating the variation of the corresponding type of parameter with the current target parameter and then used for calculating the corresponding judgment condition. For each judgment condition, the corresponding preset periods of the parameters of the required variable quantity can be different or the same; similarly, for the preset period, no specific limitation is made in the embodiment of the present application; each preset condition is modifiable and adjustable, and the preset period is included in a modifiable range.
Further, the acquisition target parameter may be acquired in real time or acquired at intervals, and therefore, each parameter type is also associated with the acquisition frequency.
That is, step S105 may include step S1051 (not shown in the figure) and step S1052 (not shown in the figure), in which:
step S1051, determining parameter variation based on the current target parameter and the contrast parameter;
and step S1052, carrying out furnace condition reasoning based on the parameter variation and the reasoning rule.
Further, a method for reasoning the furnace condition of the blast furnace further comprises the following steps:
and step S106 (not shown in the figure), determining operation suggestions required to be executed based on the furnace condition state and the preset mapping relation between the furnace condition state and the operation suggestions.
Specifically, each furnace condition state and the corresponding operation suggestion can be associated, and after the furnace condition state is obtained through the inference rule, the operation suggestion required to be executed by the furnace condition state is obtained and then output through the display device or the audio device, so that the user can know the operation suggestion conveniently. Meanwhile, the operation suggestion can be added, deleted and modified by the user.
Further, in order to facilitate the tracing of the historical data, the method for reasoning the furnace condition of the blast furnace may further include step S107 (not shown in the figure) to step S109 (not shown in the figure), wherein:
s107, sequencing all the furnace condition states according to the time sequence;
and S108, generating associated information by the target parameters, the parameter variation and the inference rules corresponding to each furnace condition state, and associating the associated information with the furnace condition state.
Specifically, for the completed inference process, the judgment condition in each inference rule, the parameter corresponding to each judgment condition, and the result of whether each judgment condition is true or not are used to generate one piece of association information, and then a plurality of pieces of association information corresponding to each inference rule are combined.
Step S109, the judgment conditions established and the judgment conditions not established in each piece of related information are differentially marked.
Further, the result of the furnace condition status obtained by an inference rule may be obtained based on the results of a plurality of determination conditions, for example, the result of the furnace condition status being water leakage is obtained by an inference rule, wherein the inference rule includes A, B and C, wherein the water leakage is obtained by assuming that a is true, B is true, and C is false.
In fact, after the inference process is performed, data tracing is performed by the user to determine whether the method or the logic is reliable, so as to modify the inference rule. The established and the non-established judgment conditions are marked in a differentiation mode, so that a user can check the conditions visually, the time for comparing one by one is reduced, and the efficiency is improved.
Further, the user does not trace back all the inference processes, but for some specific types of furnace condition states, such as the ones that can cause accidents, the user needs to verify, and therefore, further, the inference method of the blast furnace condition may further include step SA 1-step SA2, in which:
step SA1, obtaining information to be confirmed, wherein the information to be confirmed is associated information corresponding to a preset type of furnace condition state;
step SA2, sending the information to be confirmed to a preset address.
Specifically, as for the preset type of the furnace condition state, the preset address is not limited in the embodiment of the present application, and may be a mailbox, a database, or a cloud disk.
The above embodiment introduces a method for reasoning the furnace condition of the blast furnace from the perspective of the method flow, and the following embodiment introduces a device for reasoning the furnace condition of the blast furnace from the perspective of the virtual module or the virtual unit, which is described in detail in the following embodiment.
The embodiment of the present application provides an inference device for a furnace condition of a blast furnace, as shown in fig. 2, the inference device 200 may specifically include a furnace condition type obtaining module 201, an inference rule obtaining module 202, an analysis module 203, a target parameter obtaining module 204, and an inference module 205, where:
a furnace condition type obtaining module 201, configured to obtain a furnace condition type of the blast furnace;
an inference rule obtaining module 202, configured to obtain a corresponding inference rule based on a furnace condition type;
the analysis module 203 is used for analyzing the inference rule to obtain a parameter type;
a target parameter obtaining module 204, configured to obtain a target parameter in the blast furnace based on the parameter type;
and the reasoning module 205 is used for carrying out furnace condition reasoning based on the target parameters and the reasoning rules to determine the furnace condition state of the blast furnace.
In a possible implementation manner, when the inference rule obtaining module 202 obtains the corresponding inference rule based on the furnace condition type, it is specifically configured to:
acquiring a corresponding inference rule based on the furnace condition type and a preset mapping relation between the furnace condition type and the inference rule;
and acquiring an inference rule input by a user.
In a possible implementation manner, when the target parameter obtaining module 204 obtains the target parameter in the blast furnace based on the parameter type, it is specifically configured to:
acquiring a current target parameter at the current moment in the blast furnace based on the parameter type;
acquiring a contrast parameter in the blast furnace based on the parameter type, wherein the contrast parameter is a target parameter of the blast furnace at a contrast moment, and the contrast moment is a moment corresponding to a preset period before the current moment;
the target parameters include a current target parameter and a comparison parameter.
In one possible implementation, when the inference module 205 performs furnace condition inference based on the target parameters and the inference rules, it is specifically configured to:
determining parameter variation based on the current target parameter and the comparison parameter;
and carrying out furnace condition reasoning based on the parameter variation and the reasoning rule.
In one possible implementation, the apparatus 200 further includes:
and the operation suggestion determining module is used for determining the operation suggestions to be executed based on the furnace condition states and the preset mapping relation between the furnace condition states and the operation suggestions.
In one possible implementation, the apparatus 200 further includes:
the sequencing module is used for sequencing all the furnace condition states according to the time sequence;
the correlation module is used for generating correlation information from the target parameters, the parameter variation and the inference rule corresponding to each furnace condition state and correlating the correlation information with the furnace condition states;
and the marking module is used for marking the satisfied judgment condition and the unsatisfied judgment condition in each piece of associated information in a differentiation mode.
In one possible implementation, the apparatus 200 further includes:
the to-be-confirmed information acquisition module is used for acquiring the to-be-confirmed information, wherein the to-be-confirmed information is associated information corresponding to a preset type of furnace condition state;
and the sending module is used for sending the information to be confirmed to a preset address.
In an embodiment of the present application, an electronic device is provided, as shown in fig. 3, where the electronic device 300 shown in fig. 3 includes: a processor 301 and a memory 303. Wherein processor 301 is coupled to memory 303, such as via bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that the transceiver 304 is not limited to one in practical applications, and the structure of the electronic device 300 is not limited to the embodiment of the present application.
The Processor 301 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 301 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
The Memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.
The memory 303 is used for storing application program codes for executing the scheme of the application, and the processor 301 controls the execution. The processor 301 is configured to execute application program code stored in the memory 303 to implement the aspects illustrated in the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. But also a server, etc. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
The present application provides a computer-readable storage medium, on which a computer program is stored, which, when running on a computer, enables the computer to execute the corresponding content in the foregoing method embodiments.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The foregoing is only a partial embodiment of the present application, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present application, and these modifications and decorations should also be regarded as the protection scope of the present application.
Claims (10)
1. A blast furnace condition reasoning method is characterized by comprising the following steps:
acquiring the type of the furnace condition of the blast furnace;
acquiring a corresponding inference rule based on the furnace condition type;
analyzing the reasoning rule to obtain a parameter type;
acquiring target parameters in the blast furnace based on the parameter types;
and carrying out furnace condition reasoning based on the target parameters and the reasoning rules to determine the furnace condition state of the blast furnace.
2. The method for reasoning the furnace condition of the blast furnace according to claim 1, wherein the obtaining of the corresponding reasoning rule based on the furnace condition type comprises:
acquiring a corresponding inference rule based on the furnace condition type and a preset mapping relation between the furnace condition type and the inference rule;
and acquiring an inference rule input by a user.
3. The method for inferring the condition of a blast furnace according to claim 1, wherein: the obtaining of the target parameters in the blast furnace based on the parameter types comprises:
acquiring a current target parameter at the current moment in the blast furnace based on the parameter type;
acquiring a contrast parameter in the blast furnace based on the parameter type, wherein the contrast parameter is a target parameter of the blast furnace at a contrast moment, and the contrast moment is a moment corresponding to a preset period before the current moment;
the target parameters comprise a current target parameter and a comparison parameter.
4. The method for inferring a condition of a blast furnace according to claim 3, wherein: the furnace condition reasoning based on the target parameters and the reasoning rules comprises the following steps:
determining a parameter variation based on the current target parameter and the comparison parameter;
and carrying out furnace condition reasoning based on the parameter variation and the reasoning rule.
5. The method for inferring a condition of a blast furnace according to claim 1, further comprising:
and determining the operation suggestions required to be executed based on the furnace condition state and the preset mapping relation between the furnace condition state and the operation suggestions.
6. The method of claim 1, wherein each of the inference rules includes at least one predetermined judgment condition, and further comprising:
sequencing all the furnace condition states according to the time sequence;
generating associated information by using the target parameters, the parameter variation and the inference rule corresponding to each furnace condition state, and associating the associated information with the furnace condition state;
and carrying out differentiation marking on the satisfied judgment condition and the unsatisfied judgment condition in each piece of associated information.
7. The method for inferring a condition of a blast furnace according to claim 6, further comprising:
acquiring information to be confirmed, wherein the information to be confirmed is associated information corresponding to a preset type of furnace condition state;
and sending the information to be confirmed to a preset address.
8. An inference device of blast furnace conditions, comprising:
the furnace condition type acquisition module is used for acquiring the furnace condition type of the blast furnace;
the inference rule obtaining module is used for obtaining a corresponding inference rule based on the furnace condition type;
the analysis module is used for analyzing the inference rule to obtain a parameter type;
the target parameter acquisition module is used for acquiring target parameters in the blast furnace based on the parameter types;
and the reasoning module is used for carrying out furnace condition reasoning based on the target parameters and the reasoning rules and determining the furnace condition state of the blast furnace.
9. An electronic device, comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in the memory and configured to be executed by the at least one processor, the at least one application configured to: a method of reasoning for the furnace conditions of a blast furnace as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, comprising: a computer program which can be loaded by a processor and which performs the method according to any of claims 1-7.
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