CN115327675B - Method, system, equipment and storage medium for monitoring running state of meteorological equipment - Google Patents
Method, system, equipment and storage medium for monitoring running state of meteorological equipment Download PDFInfo
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- CN115327675B CN115327675B CN202211251471.0A CN202211251471A CN115327675B CN 115327675 B CN115327675 B CN 115327675B CN 202211251471 A CN202211251471 A CN 202211251471A CN 115327675 B CN115327675 B CN 115327675B
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Abstract
The invention relates to an artificial intelligence technology, and discloses a method, a system, equipment and a storage medium for monitoring the running state of meteorological equipment. The method comprises the steps that a target meteorological device is collected through a data collection layer to obtain a target real-time data set; acquiring a preset coding rule, and identifying target meteorological equipment to obtain a target equipment code; establishing a target transmission data list based on the corresponding relation between the target equipment code and the target real-time data set, and sending the target transmission data list to a data analysis layer; establishing a meteorological index set, and clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result; and analyzing the target clustering result to obtain a target running state evaluation result, and combining a decision processing layer with a preset alarm scheme to carry out alarm monitoring on the target meteorological equipment. Compared with the prior art, the remote monitoring method and the remote monitoring system improve timeliness, accuracy and reliability of remote monitoring of meteorological equipment.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a method, a system, equipment and a storage medium for monitoring the running state of meteorological equipment.
Background
With the development of society and the progress of science and technology, the dependence of clothes and food residents on weather becomes more and more compact, so that the accurate and reliable weather data provided by weather service is increasingly important for policy decision and people's life. In order to improve the meteorological data acquisition capacity and improve the early warning capacity of natural disasters such as drought, flood, geological disasters and the like, ground observation stations are constructed in a large scale. Such as a single rain station, a single visibility station, a four-element automatic weather station, a six-element automatic weather station, and a partially professional weather observation station, for example. The stable operation of the weather equipment is the basis and the premise of weather service, the daily operation monitoring of the weather equipment is enhanced, the monitoring capability and level are improved, the problems occurring in equipment operation and data transmission are timely found, the faults are processed, and the method has very important significance for well accurate weather forecast and fine weather service. Generally speaking, the existing method has the defects that the operation related data of the meteorological equipment cannot be comprehensively collected, and further the operation data of the equipment cannot be effectively utilized to accurately and efficiently evaluate the operation state of the equipment, so that the remote monitoring effect of the meteorological equipment is poor.
Therefore, how to comprehensively and accurately acquire real-time operation data of the meteorological equipment through a computer technology, and then objectively and effectively evaluate the operation state of the meteorological equipment after intelligent analysis, and finally perform equipment remote monitoring pertinently based on an evaluation result becomes a problem to be solved urgently.
Disclosure of Invention
The invention mainly aims to provide a method, a system, equipment and a storage medium for monitoring the running state of meteorological equipment, aiming at comprehensively collecting running related data of target meteorological equipment, carrying out multi-dimensional accurate and objective evaluation on the meteorological equipment through cluster analysis and further carrying out targeted alarm monitoring on the target meteorological equipment.
In order to achieve the purpose, the invention provides a method for monitoring the running state of meteorological equipment, which comprises the following steps:
the collection step comprises: carrying out multi-dimensional data acquisition on the target meteorological equipment through a data acquisition layer to obtain a target real-time data set;
and (3) encoding: acquiring a preset coding rule, and coding and identifying the target meteorological equipment according to the preset coding rule to obtain a target equipment code;
a transmission step: establishing a target transmission data list based on the corresponding relation between the target equipment code and the target real-time data set, and sending the target transmission data list to a data analysis layer;
clustering: establishing a meteorological index set, and clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result;
a monitoring step: and analyzing the target clustering result to obtain a target running state evaluation result, and combining a decision processing layer with a preset alarm scheme to carry out alarm monitoring on the target meteorological equipment.
In addition, in order to achieve the above object, the present invention further provides a system for monitoring an operating state of a weather device, where the system for monitoring an operating state of a weather device includes a memory and a processor, where the memory stores a program for monitoring an operating state of a weather device, and the program for monitoring an operating state of a weather device, when executed by the processor, implements the following steps:
the collection step comprises: carrying out multi-dimensional data acquisition on the target meteorological equipment through a data acquisition layer to obtain a target real-time data set;
and (3) encoding: acquiring a preset coding rule, and coding and identifying the target meteorological equipment according to the preset coding rule to obtain a target equipment code;
a transmission step: establishing a target transmission data list based on the corresponding relation between the target equipment code and the target real-time data set, and sending the target transmission data list to a data analysis layer;
a clustering step: establishing a meteorological index set, and clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result;
a monitoring step: and analyzing the target clustering result to obtain a target running state evaluation result, and combining a decision processing layer with a preset alarm scheme to carry out alarm monitoring on the target meteorological equipment.
In addition, to achieve the above object, the present invention further provides a computer device, which includes a processor and a memory;
the processor is used for processing and executing the meteorological equipment running state monitoring method;
the memory, coupled to the processor, for storing the weather equipment operating condition monitoring program, which when executed by the processor, causes the system to perform the steps of the weather equipment operating condition monitoring method.
In addition, to achieve the above object, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a weather equipment operation status monitoring program, and the weather equipment operation status monitoring program is executable by at least one processor to cause the at least one processor to execute the steps of the weather equipment operation status monitoring method according to any one of the above items.
The method comprises the steps that multi-dimensional data acquisition is carried out on target meteorological equipment through a data acquisition layer to obtain a target real-time data set; the method comprises the steps of obtaining a preset coding rule, carrying out coding identification on target meteorological equipment according to the preset coding rule to obtain a target equipment code, establishing a target transmission data list based on the corresponding relation between the target equipment code and a target real-time data set, sending the target transmission data list to a data analysis layer, establishing a meteorological index set, clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result, analyzing the target clustering result to obtain a target running state evaluation result, and carrying out alarm monitoring on the target meteorological equipment by a decision processing layer in combination with a preset alarm scheme. Compared with the prior art, the multi-dimensional data acquisition is carried out on the target meteorological equipment through the data acquisition layer, and the technical goal of providing a comprehensive and reliable data base for the real-time running state of the subsequent intelligent remote evaluation equipment is achieved. Through carrying out standardized code identification to target meteorological equipment, facilitate for follow-up data transmission and analysis, effectively improve meteorological equipment remote monitoring management efficiency. Through clustering the data, the aim of sequentially carrying out targeted analysis on each meteorological index monitored by the meteorological equipment is achieved, the monitoring and management accuracy of the meteorological equipment is improved, and the technical effect of providing direction guidance for actual maintenance and treatment is achieved. The target meteorological equipment is subjected to alarm monitoring through the decision processing layer, and the effects of improving the timeliness, accuracy and reliability of remote monitoring of the meteorological equipment are achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for monitoring the operating state of meteorological equipment according to the present invention;
FIG. 2 is a schematic flow chart of the method for monitoring the operating condition of the meteorological equipment according to the present invention, wherein the target real-time environment data set and the target meteorological real-time data set are used for establishing the target real-time data set;
fig. 3 is a schematic flow chart of the method for monitoring the operating condition of the meteorological equipment according to the first filtered data set and the second filtered data set to construct the target real-time data set;
fig. 4 is a schematic flow chart illustrating a process of combining the target fixed attribute encoding result and the target dynamic attribute encoding result to obtain the target device code in the meteorological equipment operation state monitoring method of the present invention;
FIG. 5 is a schematic flow chart of the alarm monitoring of the target meteorological equipment based on the alarm level in the method for monitoring the operating state of the meteorological equipment according to the present invention;
FIG. 6 is a schematic view of an operating environment of a program for monitoring an operating condition of a meteorological device according to the present invention;
FIG. 7 is a block diagram of a program for monitoring the operating status of the weather equipment according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth to illustrate, but are not to be construed to limit the scope of the invention.
The invention provides a method for monitoring the running state of meteorological equipment.
As shown in fig. 1, fig. 1 is a schematic flow chart of a method for monitoring an operating state of a meteorological device according to the present invention.
In this embodiment, the method includes:
s100: carrying out multi-dimensional data acquisition on the target meteorological equipment through a data acquisition layer to obtain a target real-time data set, wherein the target real-time data set comprises a plurality of data with time identifications;
s200: acquiring a preset coding rule, and coding and identifying the target meteorological equipment according to the preset coding rule to obtain a target equipment code;
s300: establishing a target transmission data list based on the corresponding relation between the target equipment code and the target real-time data set, and sending the target transmission data list to a data analysis layer;
s400: establishing a meteorological index set, and clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result;
s500: and analyzing the target clustering result to obtain a target running state evaluation result, and combining a decision processing layer with a preset alarm scheme to carry out alarm monitoring on the target meteorological equipment.
The meteorological equipment running state monitoring system comprises a data acquisition layer, a data analysis layer and a decision processing layer. Firstly, the target meteorological equipment in communication connection with the meteorological equipment running state monitoring system is subjected to multidimensional data acquisition through the data acquisition layer, such as device application environment data and device running data. All the acquired data thus constitute the target real-time data set, wherein the target real-time data set comprises a plurality of data with time identification. The time mark refers to the time when the corresponding data is collected. And then, after comprehensive analysis, determining the preset coding rule for carrying out regularized coding identification on the target meteorological equipment. That is, the target weather equipment is characterized by a combination of numbers and letters. Then, according to the target equipment code of the target meteorological equipment obtained after the code identification and the target real-time data set of the target meteorological equipment acquired by the data acquisition layer, a mapping relation between the code and the data is established, and a target transmission data list is obtained. The target transmission data list comprises a one-to-one correspondence relationship between target equipment codes of target meteorological equipment and a target real-time data set, and is used for transmitting the target equipment codes to a data analysis layer of the meteorological equipment running state monitoring system in real time. And then, the data analysis layer analyzes the received target transmission data list, and performs data clustering by combining all meteorological indexes in the meteorological index set, so as to obtain data clustering results corresponding to all meteorological indexes and form the target clustering results. In an exemplary case where a meteorological device is used to monitor visibility of an area, the monitoring index is analyzed to establish a relationship between the index and an influencing factor, so that wind speed and wind power monitoring data are used as clustering data of the visibility index. And finally, comprehensively analyzing the size and the change rule of the data according to the data condition in the clustering result, and determining the evaluation result of the corresponding index. And finally, comprehensively analyzing by related operation and design personnel, determining the preset alarm scheme, and monitoring the alarm of the target meteorological equipment by combining the evaluation result.
As shown in fig. 2, in this embodiment, the method further includes the following steps:
obtaining a target observation field environment of the target meteorological equipment;
establishing an environment influence factor set, and acquiring factor data of the target observation field environment based on the environment influence factor set to obtain a target environment real-time data set;
obtaining a target observation meteorological index set of the target meteorological equipment, wherein the target observation meteorological index set comprises a plurality of meteorological indexes;
acquiring data of the meteorological indexes to obtain a target meteorological real-time data set;
and establishing the target real-time data set based on the target environment real-time data set and the target weather real-time data set.
As shown in fig. 3, in this embodiment, the method further includes the following steps:
collecting a target environment initial data set of the target observation field environment;
obtaining a preset environment data threshold value according to the target environment initial data set;
based on the preset environmental data threshold value, screening the target environmental real-time data set to obtain a first screened data set;
obtaining a target weather historical data set of the target weather equipment;
obtaining a preset meteorological data threshold according to the target meteorological historical data set;
based on the preset meteorological data threshold value, screening the target meteorological real-time data set to obtain a second screened data set;
and establishing the target real-time data set according to the first screening data set and the second screening data set.
When the data acquisition layer is used for acquiring the relevant operation data of the target meteorological equipment, firstly, the target observation field environment of the target meteorological equipment is determined, and the factors influencing the monitoring of the meteorological equipment in the target observation field environment are acquired, so that the target environment real-time data set is obtained. Then, analyzing and determining a target observation meteorological index set of the target meteorological equipment, and sequentially performing data acquisition on the meteorological indexes in the target observation meteorological index set to obtain the target meteorological real-time data set.
Further, initial environmental factors of the target observation field environment are collected to obtain a target environment initial data set, the target environment initial data set is used as a change evaluation standard of the environmental factors, and a preset environmental data threshold value is determined after comprehensive analysis. The preset environmental data threshold refers to the normal variation and fluctuation range of each influence factor in the target observation field environment. Exemplary trees surrounding the observation field environment, the longer they are over time, have an effect on the meteorological device data collected in the observation field. And then, based on the preset environment data threshold, screening the target environment real-time data set to obtain a first screened data set. That is, the data which do not conform to the preset environmental data threshold value and the abnormal environmental factor data are removed, and the retained data form the first screening data set. In addition, historical collected meteorological index data of the target meteorological equipment are collected to obtain the target meteorological historical data set, a preset meteorological data threshold value is determined through comprehensive analysis according to the target meteorological historical data set, and then screening processing is conducted on the target meteorological real-time data set based on the preset meteorological data threshold value to obtain a second screening data set. And finally, establishing the target real-time data set according to the first screening data set and the second screening data set.
The data acquisition layer is used for carrying out multi-dimensional data acquisition on the target meteorological equipment, so that the technical goal of providing a comprehensive and reliable data base for the real-time running state of the subsequent intelligent remote evaluation equipment is realized.
As shown in fig. 4, in this embodiment, the method further includes the following steps:
acquiring attribute characteristics of the target meteorological equipment to obtain a target attribute characteristic set, wherein the target attribute characteristic set comprises a target fixed attribute and a target dynamic attribute;
extracting a first preset rule in the preset coding rules, and carrying out coding identification on the target fixed attribute through the first preset rule to obtain a target fixed attribute coding result;
extracting a second preset rule in the preset coding rules, and carrying out coding identification on the target dynamic attribute through the second preset rule to obtain a target dynamic attribute coding result;
and merging the target fixed attribute coding result and the target dynamic attribute coding result to obtain the target equipment code.
When the target meteorological equipment is coded, firstly, the attribute characteristics of the target meteorological equipment are collected, wherein the attribute characteristics comprise the inherent attribute characteristics and the dynamically-changed attribute characteristics of the target meteorological equipment. Exemplary characteristics such as equipment type, manufacturer identification, production sequence, check code and the like of the meteorological equipment are inherent attribute characteristics which cannot be changed, and characteristics such as maintenance, logistics, verification and the like of the meteorological equipment are attribute characteristics which can be changed. Then, the preset encoding rules are determined, wherein the preset encoding rules comprise a first preset rule and a second preset rule. The first preset rule is used for carrying out coding identification on the target fixed attribute to obtain a target fixed attribute coding result. And the second preset rule is used for carrying out coding identification on the target dynamic attribute to obtain a target dynamic attribute coding result. And finally, combining the target fixed attribute coding result and the target dynamic attribute coding result to obtain the target equipment code. Through carrying out standardized code identification to target meteorological equipment, facilitate for follow-up data transmission and analysis, effectively improve meteorological equipment remote monitoring management efficiency.
In this embodiment, the method further includes the following steps:
counting the missing data in the target transmission data list to obtain a target missing data set;
extracting any missing data in the target missing data set;
acquiring a first preset deletion compensation scheme, and acquiring first adjacent data and second adjacent data of any missing data according to the first preset deletion compensation scheme;
determining whether the first proximity data and/or the second proximity data are missing;
if the first adjacent data and the second adjacent data are not missing, sequentially obtaining a first adjacent data value and a second adjacent data value, and calculating to obtain any missing data value of the any missing data, wherein a calculation formula is as follows:
wherein, the
Refers to the arbitrary missing data value, the x refers to the arbitrary missing data
Refers to the first proximity data value, the x-1 refers to the first proximity data, the
Refers to the second neighboring data value, and the x +1 refers to the second neighboring data.
In this embodiment, the method further includes the following steps:
if the first adjacent data is missing and the second adjacent data is not missing, acquiring third adjacent data and fourth adjacent data of the first adjacent data according to a second preset missing compensation scheme;
sequentially obtaining a third adjacent data value and a fourth adjacent data value, and calculating to obtain the first adjacent data value, wherein the calculation formula is as follows:
wherein, the
Means that said third proximity isA data value, said x-2 referring to said third neighboring data, said
Refers to the fourth neighboring data value, the x-3 refers to the fourth neighboring data;
and obtaining the second adjacent data value, and combining the first adjacent data value to calculate the random missing data value.
After a target transmission data list is established according to the corresponding relation between the target equipment code and the target real-time data set, the data analysis layer counts the missing data in the target transmission data list to obtain a target missing data set.
Further, any missing data in the target missing data set is extracted, and the first preset missing compensation scheme is used for collecting adjacent data of the any missing data, so that the first adjacent data and the second adjacent data are obtained. The first preset deletion compensation scheme is to use an average value of two monitoring data which are adjacent to each other before and after the missing data as a value corresponding to the missing data. After two adjacent data before and after the any missing data are acquired, firstly, whether the first adjacent data and/or the second adjacent data are missing or not is judged, that is, whether the adjacent data of the any missing data are also missing or not is judged. If the first adjacent data and the second adjacent data are not missing, sequentially obtaining a first adjacent data value and a second adjacent data value, and calculating to obtain any missing data value of the any missing data, wherein the calculation formula is as follows:
wherein, the
Refers to the arbitrary missing data value, the x refers to the arbitrary missing data
Refers to the first neighbor data value, the x-1 refers to the first neighbor data, the
Refers to the second neighboring data value, and the x +1 refers to the second neighboring data.
And if the first adjacent data is missing and the second adjacent data is not missing, acquiring third adjacent data and fourth adjacent data of the first adjacent data according to a second preset missing compensation scheme. The second preset deletion compensation scheme is to compensate adjacent data adjacent to any missing data first, and calculate a value for compensating any missing data according to the first preset deletion compensation scheme after compensation. Then, sequentially obtaining a third adjacent data value and a fourth adjacent data value, and calculating to obtain the first adjacent data value, wherein a calculation formula is as follows:
wherein, the
Refers to the third neighboring data value, the x-2 refers to the third neighboring data, the
The second data value is acquired, and the arbitrary missing data value is calculated by combining the first data value and the second data value, wherein the x-3 is the fourth adjacent data value, and the specific calculation method is as follows:
through the preset missing value compensation scheme, the target of performing vacancy compensation on various kinds of missing data such as monitoring missing, transmission missing and the like of the target meteorological equipment is achieved. In addition, counting the total number of missing data in the target missing data set, when the missing data reaches a certain threshold value or the continuous missing data amount reaches a certain threshold value, indicating that abnormality exists in equipment monitoring or transmission and the like, and correspondingly sending alarm information to carry out equipment maintenance and fault repair.
As shown in fig. 5, in this embodiment, the method further includes the following steps:
extracting any result in the target clustering results;
reversely matching the weather indexes represented by the arbitrary results, and recording the weather indexes as arbitrary weather indexes;
collecting historical ring ratio data of any meteorological index, and comparing the historical ring ratio data with any result to obtain a ring ratio change rate;
and determining the alarm grade of the ring ratio change rate through the preset alarm scheme, and carrying out alarm monitoring on the target meteorological equipment based on the alarm grade.
When the alarm monitoring of the target meteorological equipment is carried out through a decision processing layer, any result in the target clustering results is extracted firstly, wherein the any result refers to the monitoring data clustering result of any meteorological index. And then reversely matching the weather indexes of the representations of the arbitrary results, and recording the weather indexes as arbitrary weather indexes. And then, collecting historical ring ratio data of any meteorological index, and comparing the historical ring ratio data with any result to obtain a ring ratio change rate. Specifically, the current real-time monitoring value of certain data is subtracted from the historical ring ratio monitoring value, and the obtained difference is compared with the historical ring ratio monitoring value, so that the ring ratio change rate is obtained. And finally, determining the alarm level of the ring ratio change rate through the preset alarm scheme, wherein in an exemplary case, when the ring ratio change rate reaches 10% -20%, the alarm level is a first-level alarm level, and 20% -30% of the alarm level is a second-level alarm level. And finally, performing alarm monitoring on the target meteorological equipment based on the alarm level. Through clustering the data, the aim of sequentially carrying out targeted analysis on each meteorological index monitored by the meteorological equipment is fulfilled, the monitoring and management accuracy of the meteorological equipment is improved, and the technical effect of providing direction guidance for actual maintenance and treatment is achieved.
The method comprises the steps of establishing an actual development feature set based on big data analysis, wherein the actual development feature set comprises development process features, development technology features and developer organization architecture features; constructing and obtaining a development component function demand set based on the development process characteristics, the development technical characteristics and the developer organization architecture characteristics by combining a cloud primary theory; analyzing a technical architecture, a network architecture and an overall architecture in sequence, and establishing a design principle according to an analysis result; respectively extracting the service infrastructure function requirement, the public infrastructure function requirement and the agile infrastructure function requirement in the development component function requirement set, and sequentially designing by combining the design principle to obtain a service infrastructure, a public infrastructure and an agile infrastructure; and constructing to obtain a cloud native development component based on the service infrastructure, the public infrastructure and the agile infrastructure. Compared with the prior art, the method has the advantages that the actual development process of the software application is subjected to feature acquisition and analysis, the functions which the cloud-native development component should have are determined by combining the cloud-native theory, the development component function requirement set is obtained, the design principle analysis is further carried out on the technology, the network and the whole framework of the design of the cloud-native development component, finally, the sub-modules are sequentially designed, and the cloud-native development component is constructed. The cloud native development component is constructed by using the cloud native theory, so that the technical aim of providing a production line for the development of software application is fulfilled. Therefore, the invention can improve the reuse rate of the enterprise framework and the code, reduce the energy input of developers in developing public basic service, accelerate the development speed and further shorten the software development and delivery cycle.
The invention provides a program for monitoring the running state of meteorological equipment.
Please refer to fig. 6, which is a schematic diagram of an operating environment of the weather equipment operating status monitoring program 10 according to the present invention.
In the present embodiment, the weather-equipment operation-state monitoring program 10 is installed and operated in the electronic device 1. The electronic device 1 may be a desktop computer, a notebook, a palm computer, a server, or other computing equipment. The electronic device 1 may include, but is not limited to, a memory 11, a processor 12, and a display 13. Fig. 6 only shows the electronic device 1 with components 11-13, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may alternatively be implemented.
The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a hard disk or a memory of the electronic device 1. The memory 11 may also be an external storage device of the electronic apparatus 1 in other embodiments, such as a plug-in hard disk provided on the electronic apparatus 1, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic apparatus 1. The memory 11 is used for storing application software installed in the electronic device 1 and various types of data, such as program codes of the weather equipment operation state monitoring program 10. The memory 11 may also be used to temporarily store data that has been output or is to be output.
The processor 12 may be a Central Processing Unit (CPU), microprocessor or other data Processing chip in some embodiments, and is used for executing program codes stored in the memory 11 or Processing data, such as executing the weather equipment operation status monitoring program 10.
The display 13 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch panel, or the like in some embodiments. The display 13 is used for displaying information processed in the electronic apparatus 1 and for displaying a visualized user interface. The components 11-13 of the electronic device 1 communicate with each other via a program bus.
Please refer to fig. 7, which is a block diagram of a program 10 for monitoring the operating status of the weather equipment according to the present invention.
In this embodiment, the weather equipment operation status monitoring program 10 may be divided into one or more modules, and the one or more modules are stored in the memory 11 and executed by one or more processors (in this embodiment, the processor 12) to complete the present invention. For example, in fig. 7, the weather equipment operating condition monitoring program 10 may be divided into an acquisition module 101, an encoding module 102, a transmission module 103, a clustering module 104, and a monitoring module 105. The module of the present invention refers to a series of computer program instruction segments capable of performing specific functions, and is more suitable than a program for describing the execution process of the weather equipment operation status monitoring program 10 in the electronic device 1, wherein:
the acquisition module 101: carrying out multi-dimensional data acquisition on the target meteorological equipment through a data acquisition layer to obtain a target real-time data set, wherein the target real-time data set comprises a plurality of data with time identifications;
the encoding module 102: acquiring a preset coding rule, and coding and identifying the target meteorological equipment according to the preset coding rule to obtain a target equipment code;
the transmission module 103: establishing a target transmission data list based on the corresponding relation between the target equipment code and the target real-time data set, and sending the target transmission data list to a data analysis layer;
the clustering module 104: establishing a meteorological index set, and clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result;
the monitoring module 105: and analyzing the target clustering result to obtain a target running state evaluation result, and combining a decision processing layer with a preset alarm scheme to carry out alarm monitoring on the target meteorological equipment.
The invention also provides an electronic device, which comprises a processor and a memory;
the processor is used for processing the steps of executing the method for monitoring the running state of the meteorological equipment in the first embodiment;
the memory, coupled to the processor, is used for storing a program, which when executed by the processor, causes the system to perform the steps of any of the above-described weather equipment operating condition monitoring methods.
Further, the present invention also provides a computer-readable storage medium storing a weather equipment operation status monitoring program, where the weather equipment operation status monitoring program is executable by at least one processor to cause the at least one processor to execute the weather equipment operation status monitoring method in any one of the above embodiments.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. A meteorological equipment operation state monitoring method is applied to a meteorological equipment operation state monitoring system, the system is in communication connection with target meteorological equipment, and the method comprises the following steps:
the collection step: carrying out multi-dimensional data acquisition on the target meteorological equipment through a data acquisition layer to obtain a target real-time data set;
and (3) encoding: acquiring a preset coding rule, and coding and identifying the target meteorological equipment according to the preset coding rule to obtain a target equipment code;
a transmission step: establishing a target transmission data list based on the corresponding relation between the target equipment code and the target real-time data set, and sending the target transmission data list to a data analysis layer;
a clustering step: establishing a meteorological index set, and clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result;
a monitoring step: analyzing the target clustering result to obtain a target running state evaluation result, combining a decision processing layer with a preset alarm scheme to alarm and monitor the target meteorological equipment, wherein the decision processing layer comprises the following steps:
extracting any result in the target clustering results;
reversely matching the weather indexes represented by the arbitrary results, and recording the weather indexes as arbitrary weather indexes;
collecting historical ring ratio data of any meteorological index, and comparing the historical ring ratio data with any result to obtain a ring ratio change rate;
and determining the alarm grade of the ring ratio change rate through the preset alarm scheme, and carrying out alarm monitoring on the target meteorological equipment based on the alarm grade.
2. The meteorological equipment operating state monitoring method according to claim 1, wherein the collecting step further comprises:
obtaining a target observation field environment of the target meteorological equipment;
establishing an environment influence factor set, and acquiring factor data of the target observation field environment based on the environment influence factor set to obtain a target environment real-time data set;
obtaining a target observation meteorological index set of the target meteorological equipment, wherein the target observation meteorological index set comprises a plurality of meteorological indexes;
acquiring data of the meteorological indexes to obtain a target meteorological real-time data set;
and constructing the target real-time data set based on the target environment real-time data set and the target weather real-time data set.
3. The meteorological equipment operating state monitoring method according to claim 2, wherein the building the target real-time data set based on the target environment real-time data set and the target meteorological real-time data set comprises:
collecting a target environment initial data set of the target observation field environment;
obtaining a preset environment data threshold value according to the target environment initial data set;
based on the preset environmental data threshold, screening the target environment real-time data set to obtain a first screened data set;
obtaining a target weather historical data set of the target weather equipment;
obtaining a preset meteorological data threshold according to the target meteorological historical data set;
based on the preset meteorological data threshold, screening the target meteorological real-time data set to obtain a second screened data set;
and establishing the target real-time data set according to the first screening data set and the second screening data set.
4. The meteorological equipment operating condition monitoring method according to claim 1, wherein the encoding step further comprises:
acquiring attribute characteristics of the target meteorological equipment to obtain a target attribute characteristic set, wherein the target attribute characteristic set comprises a target fixed attribute and a target dynamic attribute;
extracting a first preset rule in the preset coding rules, and carrying out coding identification on the target fixed attribute through the first preset rule to obtain a target fixed attribute coding result;
extracting a second preset rule in the preset coding rules, and carrying out coding identification on the target dynamic attribute through the second preset rule to obtain a target dynamic attribute coding result;
and merging the target fixed attribute coding result and the target dynamic attribute coding result to obtain the target equipment code.
5. The meteorological equipment operating condition monitoring method according to claim 1, wherein the transmitting step further comprises:
counting the missing data in the target transmission data list to obtain a target missing data set;
extracting any missing data in the target missing data set;
acquiring a first preset deletion compensation scheme, and acquiring first adjacent data and second adjacent data of any missing data according to the first preset deletion compensation scheme;
determining whether the first proximity data and/or the second proximity data is missing;
if the first adjacent data and the second adjacent data are not missing, sequentially obtaining a first adjacent data value and a second adjacent data value, and calculating to obtain any missing data value of the any missing data, wherein the calculation formula is as follows:
wherein, the
Refers to the arbitrary missing data value, the x refers to the arbitrary missing data
Refers to the first neighbor data value, the x-1 refers to the first neighbor data, the
Refers to the second neighboring data value, and the x +1 refers to the second neighboring data.
6. The meteorological equipment operating state monitoring method according to claim 5, wherein after the determining whether the first proximity data and/or the second proximity data is/are missing, the method further comprises:
if the first adjacent data is missing and the second adjacent data is not missing, acquiring third adjacent data and fourth adjacent data of the first adjacent data according to a second preset missing compensation scheme;
sequentially obtaining a third adjacent data value and a fourth adjacent data value, and calculating to obtain the first adjacent data value, wherein the calculation formula is as follows:
wherein, the
Refers to the third neighboring data value, the x-2 refers to the third neighboring data, the
Refers to the fourth neighboring data value, the x-3 refers to the fourth neighboring data;
and obtaining the second adjacent data value, and combining the first adjacent data value to calculate to obtain the random missing data value.
7. A weather equipment running state monitoring system comprises a memory and a processor, and is characterized in that the memory stores a weather equipment running state monitoring program, and the weather equipment running state monitoring program realizes the following steps when being executed by the processor:
the collection step comprises: carrying out multi-dimensional data acquisition on target meteorological equipment through a data acquisition layer to obtain a target real-time data set;
and (3) encoding: acquiring a preset coding rule, and coding and identifying the target meteorological equipment according to the preset coding rule to obtain a target equipment code;
a transmission step: establishing a target transmission data list based on the corresponding relation between the target equipment code and the target real-time data set, and sending the target transmission data list to a data analysis layer;
a clustering step: establishing a meteorological index set, and clustering the target transmission data list by the data analysis layer based on a plurality of meteorological indexes in the meteorological index set to obtain a target clustering result;
a monitoring step: analyzing the target clustering result to obtain a target running state evaluation result, and combining a decision processing layer with a preset alarm scheme to perform alarm monitoring on the target meteorological equipment, wherein the alarm monitoring comprises the following steps:
extracting any result in the target clustering results;
reversely matching the weather indexes represented by the arbitrary results, and recording the weather indexes as arbitrary weather indexes;
collecting historical ring ratio data of any meteorological index, and comparing the historical ring ratio data with any result to obtain a ring ratio change rate;
and determining the alarm grade of the ring ratio change rate through the preset alarm scheme, and carrying out alarm monitoring on the target meteorological equipment based on the alarm grade.
8. A computer device comprising a processor and a memory;
the processor configured to process to perform the method of any one of claims 1-6;
the memory coupled with the processor for storing a program that, when executed by the processor, causes the system to perform the steps of the method of any of claims 1-6.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a weather equipment operating condition monitoring program, which is executable by at least one processor to cause the at least one processor to perform the steps of the weather equipment operating condition monitoring method according to any one of claims 1-6.
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