CN112256660B - Cast iron production safety monitoring method and device and server - Google Patents
Cast iron production safety monitoring method and device and server Download PDFInfo
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Abstract
According to the cast iron production safety monitoring method, device and server, after a first cast iron equipment running log and a second cast iron equipment running log are obtained, a first working condition log event list of the first cast iron equipment running log and a second working condition log event list of the second cast iron equipment running log are obtained, each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list are obtained, and a first production environment data cluster is obtained; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than the first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue; and processing the influence correction queue to obtain a first safety index evaluation result. Therefore, safety monitoring of cast iron production can be realized.
Description
Technical Field
The invention relates to the technical field of cast iron production, in particular to a cast iron production safety monitoring method, a cast iron production safety monitoring device and a server.
Background
Cast iron is a generic term for alloys consisting mainly of iron, carbon and silicon. In these alloys, the carbon content exceeds the amount that can remain in solid solution in austenite at the eutectic temperature.
In the cast iron production process, serious production accidents can be caused due to the severe production environment, and personal and property losses are caused. Therefore, how to realize safety monitoring of cast iron production is a technical problem to be solved at the present stage.
Disclosure of Invention
In order to improve the problems, the invention provides a cast iron production safety monitoring method, a cast iron production safety monitoring device and a server.
In a first aspect, a cast iron production safety monitoring method is provided, which comprises the following steps:
after a first cast iron equipment running log and a second cast iron equipment running log are obtained, a first working condition log event list of the first cast iron equipment running log and a second working condition log event list of the second cast iron equipment running log are obtained, wherein the first cast iron equipment running log comprises a first cast iron working condition evaluation coefficient, and the second cast iron equipment running log comprises a second cast iron working condition evaluation coefficient;
acquiring each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list to obtain a first production environment data cluster; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than a first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue;
and processing the influence degree correction queue to obtain a first safety index evaluation result, wherein the first safety index evaluation result is used for indicating that the first cast iron working condition evaluation coefficient and the second cast iron working condition evaluation coefficient are the same cast iron working condition evaluation coefficient or different cast iron working condition evaluation coefficients.
Optionally, the determining a production environment influence degree between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue includes: determining each production environment data set in the first production environment data cluster as a current production environment data set, performing the following steps until the first production environment data cluster is traversed: and calculating the influence degree of the production environment of each of the current production environment data set and the first production environment data cluster, and determining the calculated plurality of the production environment influence degrees as a queue element in the influence degree queue.
Optionally, determining a production environment influence degree between two of the production environment data sets comprises: calculating the data characteristic association degrees of the two production environment data sets to obtain association degree distribution; determining the relevancy distribution as the production environment impact between the two production environment data sets.
Optionally, the adjusting the production environment influence smaller than the first preset fusing loudness in the influence queue to the first preset fusing loudness to obtain an influence modification queue includes: determining each production environment influence degree in the influence degree queue as a current influence degree, and executing the following steps until the influence degree queue is traversed: acquiring the current influence degree; adjusting the current degree of influence to the first set fusing loudness when the current degree of influence is less than the first set fusing loudness; and after the traversal is completed, determining the adjusted influence degree queue as the influence degree modification queue.
Optionally, the processing the influence degree modification queue to obtain a first safety index evaluation result includes: converting the influence volume modification queue into queue description information; inputting the influence degree correction queue, the queue description information, the first working condition log event list and the second working condition log event list into a feature identification thread to obtain the associated features of the first cast iron equipment running log and the second cast iron equipment running log; and identifying the associated features by using a preset identification unit to obtain the first safety index evaluation result.
A second aspect provides a cast iron production safety monitoring device, including:
the system comprises a list acquisition module, a list acquisition module and a display module, wherein the list acquisition module is used for acquiring a first working condition log event list of a first cast iron equipment running log and a second working condition log event list of a second cast iron equipment running log after acquiring the first cast iron equipment running log and the second cast iron equipment running log, the first cast iron equipment running log comprises a first cast iron working condition evaluation coefficient, and the second cast iron equipment running log comprises a second cast iron working condition evaluation coefficient;
the queue acquisition module is used for acquiring each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list to obtain a first production environment data cluster; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than a first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue;
and the safety evaluation module is used for processing the influence degree correction queue to obtain a first safety index evaluation result, wherein the first safety index evaluation result is used for indicating that the first cast iron working condition evaluation coefficient and the second cast iron working condition evaluation coefficient are the same cast iron working condition evaluation coefficient or different cast iron working condition evaluation coefficients.
A third aspect provides a server, a processor in which is arranged when running to perform the above method.
By applying the method, the device and the server, after a first cast iron equipment running log and a second cast iron equipment running log are obtained, a first working condition log event list of the first cast iron equipment running log and a second working condition log event list of the second cast iron equipment running log are obtained, each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list are obtained, and a first production environment data cluster is obtained; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than a first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue; and processing the influence degree correction queue to obtain a first safety index evaluation result. Therefore, safety monitoring of cast iron production can be realized.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of a method for monitoring safety of cast iron production according to an embodiment of the present invention.
Fig. 2 is a functional block diagram of a cast iron production safety monitoring device according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a hardware structure of a server according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present invention are the detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features in the embodiments and the examples of the present invention may be combined with each other without conflict.
Referring to fig. 1, a cast iron production safety monitoring method applied to a server is shown, which includes the following steps S11-S13.
Step S11, after a first cast iron device running log and a second cast iron device running log are obtained, a first working condition log event list of the first cast iron device running log and a second working condition log event list of the second cast iron device running log are obtained, wherein the first cast iron device running log comprises a first cast iron working condition evaluation coefficient, and the second cast iron device running log comprises a second cast iron working condition evaluation coefficient.
Step S12, acquiring each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list to obtain a first production environment data cluster; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; and adjusting the production environment influence degree smaller than the first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue.
Step S13, processing the influence degree correction queue to obtain a first safety index evaluation result, wherein the first safety index evaluation result is used for indicating that the first cast iron working condition evaluation coefficient and the second cast iron working condition evaluation coefficient are the same cast iron working condition evaluation coefficient or different cast iron working condition evaluation coefficients.
It can be understood that, by executing the above steps S11-S13, after acquiring a first cast iron device operation log and a second cast iron device operation log, acquiring a first operating condition log event list of the first cast iron device operation log and a second operating condition log event list of the second cast iron device operation log, acquiring each production environment data set in the first operating condition log event list and each production environment data set in the second operating condition log event list, and obtaining a first production environment data cluster; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than a first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue; and processing the influence degree correction queue to obtain a first safety index evaluation result. Therefore, safety monitoring of cast iron production can be realized.
Optionally, the determining a production environment influence degree between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue includes: determining each production environment data set in the first production environment data cluster as a current production environment data set, performing the following steps until the first production environment data cluster is traversed: and calculating the influence degree of the production environment of each of the current production environment data set and the first production environment data cluster, and determining the calculated plurality of the production environment influence degrees as a queue element in the influence degree queue.
Optionally, determining a production environment influence degree between two of the production environment data sets comprises: calculating the data characteristic association degrees of the two production environment data sets to obtain association degree distribution; determining the relevancy distribution as the production environment impact between the two production environment data sets.
Optionally, the adjusting the production environment influence smaller than the first preset fusing loudness in the influence queue to the first preset fusing loudness to obtain an influence modification queue includes: determining each production environment influence degree in the influence degree queue as a current influence degree, and executing the following steps until the influence degree queue is traversed: acquiring the current influence degree; adjusting the current degree of influence to the first set fusing loudness when the current degree of influence is less than the first set fusing loudness; and after the traversal is completed, determining the adjusted influence degree queue as the influence degree modification queue.
Optionally, the processing the influence degree modification queue to obtain a first safety index evaluation result includes: converting the influence volume modification queue into queue description information; inputting the influence degree correction queue, the queue description information, the first working condition log event list and the second working condition log event list into a feature identification thread to obtain the associated features of the first cast iron equipment running log and the second cast iron equipment running log; and identifying the associated features by using a preset identification unit to obtain the first safety index evaluation result.
Referring to fig. 2, there is shown a cast iron production safety monitoring device 200 comprising:
the list obtaining module 210 is configured to obtain a first operating condition log event list of a first cast iron device operating log and a second operating condition log event list of a second cast iron device operating log after obtaining the first cast iron device operating log and the second cast iron device operating log, where the first cast iron device operating log includes a first cast iron operating condition evaluation coefficient, and the second cast iron device operating log includes a second cast iron operating condition evaluation coefficient;
a queue obtaining module 220, configured to obtain each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list to obtain a first production environment data cluster; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than a first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue;
and the safety evaluation module 230 is configured to process the influence correction queue to obtain a first safety index evaluation result, where the first safety index evaluation result is used to indicate that the first cast iron working condition evaluation coefficient and the second cast iron working condition evaluation coefficient are the same cast iron working condition evaluation coefficient or different cast iron working condition evaluation coefficients.
Fig. 3 is a block diagram illustrating a server 110 according to an embodiment of the present invention. The server 110 in the embodiment of the present invention may be a server with data storage, transmission, and processing functions, as shown in fig. 3, the server 110 includes: memory 111, processor 112, network module 113 and cast iron production safety monitoring device 200.
The memory 111, the processor 112, and the network module 113 are electrically connected directly or indirectly to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 111 stores the cast iron production safety monitoring device 200, the cast iron production safety monitoring device 200 includes at least one software functional module which can be stored in the memory 111 in the form of software or firmware (firmware), and the processor 112 executes various functional applications and data processing by running the software programs and modules stored in the memory 111, such as the cast iron production safety monitoring device 200 in the embodiment of the present invention, so as to implement the cast iron production safety monitoring method in the embodiment of the present invention.
The Memory 111 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 111 is used for storing a program, and the processor 112 executes the program after receiving the execution instruction.
The processor 112 may be an integrated circuit chip having data processing capabilities. The Processor 112 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like. The various methods, steps and logic blocks disclosed in embodiments of the present invention 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 network module 113 is used for establishing communication connection between the server 110 and other communication terminal devices through a network, and implementing transceiving operation of network signals and data. The network signal may include a wireless signal or a wired signal.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative and that server 110 may include more or fewer components than shown in fig. 3 or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
An embodiment of the present invention also provides a computer-readable storage medium, which includes a computer program. The computer program controls the server 110 on which the readable storage medium is executed to perform the above-mentioned method.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part thereof, which essentially contributes to the prior art, can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, an electronic device 10, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, 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 identical elements in a process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (5)
1. A cast iron production safety monitoring method is characterized by comprising the following steps:
after a first cast iron equipment running log and a second cast iron equipment running log are obtained, a first working condition log event list of the first cast iron equipment running log and a second working condition log event list of the second cast iron equipment running log are obtained, wherein the first cast iron equipment running log comprises a first cast iron working condition evaluation coefficient, and the second cast iron equipment running log comprises a second cast iron working condition evaluation coefficient;
acquiring each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list to obtain a first production environment data cluster; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than a first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue;
processing the influence degree correction queue to obtain a first safety index evaluation result, wherein the first safety index evaluation result is used for indicating that the first cast iron working condition evaluation coefficient and the second cast iron working condition evaluation coefficient are the same cast iron working condition evaluation coefficient or different cast iron working condition evaluation coefficients; determining a production environment influence degree between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue, including: determining each production environment data set in the first production environment data cluster as a current production environment data set, performing the following steps until the first production environment data cluster is traversed: calculating the production environment influence degree of each of the current production environment data set and the first production environment data cluster, and determining the calculated production environment influence degrees as a queue element in the influence degree queue;
determining a production environment influence level between two of the production environment data sets comprises: calculating the data characteristic association degrees of the two production environment data sets to obtain association degree distribution; determining the relevancy distribution as the production environment impact between the two production environment data sets.
2. The method of claim 1, wherein adjusting the production environment influence of less than the first set fused loudness in the influence queue to the first set fused loudness results in an influence modification queue comprising: determining each production environment influence degree in the influence degree queue as a current influence degree, and executing the following steps until the influence degree queue is traversed: acquiring the current influence degree; adjusting the current degree of influence to the first set fusing loudness when the current degree of influence is less than the first set fusing loudness; and after the traversal is completed, determining the adjusted influence degree queue as the influence degree modification queue.
3. The method according to claim 1, wherein the processing the influence magnitude modification queue to obtain a first safety metric evaluation result comprises: converting the influence volume modification queue into queue description information; inputting the influence degree correction queue, the queue description information, the first working condition log event list and the second working condition log event list into a feature identification thread to obtain the associated features of the first cast iron equipment running log and the second cast iron equipment running log; and identifying the associated features by using a preset identification unit to obtain the first safety index evaluation result.
4. A cast iron production safety monitoring device, characterized by includes:
the system comprises a list acquisition module, a list acquisition module and a display module, wherein the list acquisition module is used for acquiring a first working condition log event list of a first cast iron equipment running log and a second working condition log event list of a second cast iron equipment running log after acquiring the first cast iron equipment running log and the second cast iron equipment running log, the first cast iron equipment running log comprises a first cast iron working condition evaluation coefficient, and the second cast iron equipment running log comprises a second cast iron working condition evaluation coefficient;
the queue acquisition module is used for acquiring each production environment data set in the first working condition log event list and each production environment data set in the second working condition log event list to obtain a first production environment data cluster; determining the influence degree of the production environment between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue; adjusting the production environment influence degree smaller than a first set fixing loudness in the influence degree queue to the first set fixing loudness to obtain an influence degree correction queue;
determining a production environment influence degree between any two production environment data sets in the first production environment data cluster to obtain an influence degree queue, including: determining each production environment data set in the first production environment data cluster as a current production environment data set, performing the following steps until the first production environment data cluster is traversed: calculating the production environment influence degree of each of the current production environment data set and the first production environment data cluster, and determining the calculated production environment influence degrees as a queue element in the influence degree queue;
determining a production environment influence level between two of the production environment data sets comprises: calculating the data characteristic association degrees of the two production environment data sets to obtain association degree distribution; determining the degree of correlation distribution as the degree of production environment influence between the two sets of production environment data;
and the safety evaluation module is used for processing the influence degree correction queue to obtain a first safety index evaluation result, wherein the first safety index evaluation result is used for indicating that the first cast iron working condition evaluation coefficient and the second cast iron working condition evaluation coefficient are the same cast iron working condition evaluation coefficient or different cast iron working condition evaluation coefficients.
5. A server, characterized in that a processor in the server is adapted to perform the method of any of the preceding claims 1-3 when executed.
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| CN202011159798.6A CN112256660B (en) | 2020-10-27 | 2020-10-27 | Cast iron production safety monitoring method and device and server |
| PCT/CN2020/133698 WO2022088381A1 (en) | 2020-10-27 | 2020-12-03 | Safety monitoring method and apparatus for cast iron production, and server |
| JP2022539266A JP7406637B2 (en) | 2020-10-27 | 2020-12-03 | Cast iron production safety monitoring method, equipment and server |
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| WO2022088381A1 (en) | 2022-05-05 |
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