CN105809577B - Power plant informatization data classification processing method based on rules and components - Google Patents

Abstract

The invention discloses a classification processing method of power plant informatization data based on rules and components, which comprises the following steps: step (1), establishing a classification model according to the characteristics of power plant informatization data; step (2) establishing or selecting a proper component from a component library based on the classification model and the application requirement; step (3) establishing or selecting a proper rule from a rule base based on the classification model and the application requirement; and (4) aiming at the data needing to be processed, establishing or selecting a proper task from a task library based on corresponding components and rules, providing specific parameters to start the task, and processing the informatization data of the power plant. The method fully considers the diversity and complexity of the power plant information data, collects, analyzes, processes, sends and stores the data according to application requirements based on components and rules, and can provide support for other applications based on the power information data.

Description

Power plant informatization data classification processing method based on rules and components

The technical field is as follows:

the invention relates to a method for processing data in the field of computers, in particular to a method for analyzing and processing informatization data of a power plant through rules and components.

Background art:

with the continuous deepening of the informatization of the power industry and the continuous development of the computer technology, the businesses and the production of a plurality of units and departments in the power industry are more and more dependent on computers and software, so that the working efficiency can be improved, and higher reliability and flexibility can be provided for the production operation and the business management of enterprises. However, due to different industry informatization degrees and complexity of working environments of the power industry, the problems that various types of data and various software systems coexist and the like exist in the power industry at present, analysis and processing of the informatization data become key problems in an industry informatization process, and a method and a framework with good operability and universality are provided for data processing of the power industry, and become important points of attention of industry experts and scholars.

The power plant is a basic supporting node of the power industry, the diversity and the complexity of the power plant information data are very typical, and the analysis and the processing of a plurality of power industry data are based on the power plant information data, so the power plant information data are used as research objects in the invention. Due to differences in power generation modes and informatization degrees, types and characteristics of data to be processed in each power plant are also various, for example, a thermal power plant, a hydraulic power plant, a wind power plant, a nuclear power plant, a biomass power plant and the like need to process different service data, and many power plants simultaneously operate an equipment operation control system, an information management system, a truck scale/rail scale metering system, a fuel test analysis system and the like, so that the source and storage formats of the data are also complicated. At present, a unified processing method and a framework aiming at the informationized data are lacked in a power plant, and various data are respectively processed by adopting various different tools, so that the invention provides a classification processing method of the informationized data of the power plant based on rules and components, and the informationized data of various complex and diverse power plants can be uniformly processed based on application requirements.

The invention content is as follows:

the invention mainly aims to provide a classification processing method of power plant informatization data based on rules and components, which fully considers the characteristics of diversity and complexity of power plant informatization data, establishes a classification model containing data characteristics, determines components and rules supporting three main stages of data processing, collection, analysis processing and sending and storage based on the classification model and application requirements, describes a typical processing method of each type of data through tasks, and maintains the components, the rules and the tasks in a resource library so as to facilitate the reuse of the resources. The invention provides a method with better flexibility and universality for the processing of the power plant information data and also provides support for other applications based on the power plant information data.

The invention aims to be realized by the following technical scheme:

a classification processing method of power plant information data based on rules and components comprises the following steps:

step (1), establishing a classification model according to the characteristics of power plant informatization data;

step (2) establishing or selecting a proper component from a component library based on the classification model and the application requirement;

step (3) establishing or selecting a proper rule from a rule base based on the classification model and the application requirement;

and (4) aiming at the data needing to be processed, establishing or selecting a proper task from a task library based on corresponding components and rules, providing specific parameters to start the task, and processing the informatization data of the power plant.

According to the above features, the classification model has a hierarchical structure, and can be established according to application requirements and data characteristics, each leaf node in the model corresponds to a type of data, and a non-leaf node describes a certain characteristic of the type of data.

According to the above features, the method for creating or selecting a suitable component in a component library comprises two main stages, a first stage of retrieving each node of the classification model and determining relevant characteristics of the data to be processed, and a second stage of creating or selecting a suitable component in the component library based on the retrieved data characteristics.

According to the above features, the method of creating or selecting suitable rules in the rule base comprises two main stages, a first stage of retrieving each node of the classification model and determining relevant characteristics of the data to be processed, and a second stage of creating or selecting suitable rules in the rule base based on the retrieved data characteristics and application requirements.

According to the above feature, the step (4) specifically includes the steps of:

step (4.1) based on the determined task and application requirements, providing specific parameters used in each stage of data acquisition, analysis processing, sending and storage;

and (4.2) creating a task execution space, creating each task instance by a task execution engine, completing the work of required component instantiation, rule loading and the like, and starting an actual data processing process.

Description of the drawings:

FIG. 1 is a general schematic diagram of a classification processing method for plant informatization data according to the present invention;

FIG. 2 is a diagram of the relationship between classification models, resource pools, and data processing tasks in the present invention.

The specific implementation mode is as follows:

the present invention will be described in further detail with reference to the accompanying drawings.

As shown in fig. 1, a general schematic diagram of the classification processing method for the plant informatization data provided by the invention is described, wherein solid arrows indicate that the informatization data sequentially passes through a collector, an analysis processor and a transmitter, dashed arrows indicate that a task execution engine schedules and controls rules of the collector, the analysis processor and the transmitter, rectangular arrows indicate that appropriate components, rules and tasks are selected and output from a component library, a rule library and a task library, and newly established or modified on the original basis are also stored in a resource library. The resource library is used for storing related resources of data processing and supporting reuse of components, rules and tasks. The classification processing method provided by the invention comprises the following specific implementation steps:

(1) establishing a classification model

By analyzing the characteristics of the plant information data and establishing a classification model with a hierarchical structure based on an application environment, as shown in fig. 2, each specific type of data corresponds to one leaf node in the model, and a non-leaf node represents a certain characteristic of the data, so that subsequent work can be carried out based on the type and the characteristic of the data. The power plant informatization data is various and complex, such as: each type of data has different sources, storage formats, contents, destinations and the like, the classification model is established according to the characteristics and application requirements of the data, and the non-leaf nodes encapsulate the characteristics required to be used in the data processing process. The characteristics of the plant information data are more, characteristics packaged by non-leaf nodes in a classification model need to be selected according to requirements, and the main characteristics relate to: the data can be original production and service data of the power plant or monitoring data of an information system of the power plant; the storage format of the data, namely the data can be stored in common files such as excel, word, txt and the like, and can also be stored in files which can be operated only by a specific tool; content of data — data may be text, numbers, or special models; data destination-similar to the source of the data, the processed data may need to be stored in a database, a file, etc., or may need to be sent out via a network according to a certain protocol format.

(2) Determining suitable components

Based on the characteristics of each type of data in the classification model, appropriate components need to be determined for the entire data processing process. Of course, if there is no suitable component in the component library, the original component can be modified according to the requirement, or some new components can be customized, and these components will also be saved in the component library. As shown in fig. 1 and 2, the overall data processing process is divided into three major phases, each of which may require corresponding component support. The first stage is data acquisition, and suitable components can be selected or created according to relevant characteristics such as the source of data in the classification model, for example: if the data comes from a table of a certain database, a corresponding database driving component is needed to support the acquisition of the data; the network snooping protocol component is required to support the collection of data if the data originates from the network interface snooping. The second phase is data analysis processing, if only simple statistics, association, calculation and other operations are performed on the data, the support of components may not be needed, but if more complex statistics analysis, data mining or some special processing is involved, the support of related components is also needed, such as: data is text content, and its tendency and sensitive words need to be analyzed, then a corresponding text analysis component is needed to support the analysis processing of the data. The third phase is data transmission and storage, which is similar to the first phase and also needs to select or create a suitable component according to the destination and other relevant characteristics of the data, such as: after data processing, the data needs to be stored in a table of a certain database, and a driving component of the corresponding database is needed to support data transmission.

(3) Determining appropriate rules

Depending on the application requirements, it may also be necessary to determine appropriate rules for the entire data processing process based on the classification model. The rules are encapsulated with specific business logic, can be selected from a rule base, can be created or modified on the original basis, and new rules are stored in the rule base. As shown in fig. 1 and 2, the three main stages of the data processing process all require appropriate rules for control. The first stage is data acquisition, and the created or selected acquisition rule packages the specific operation method and flow for data acquisition by using the components, and the acquisition rule and the corresponding components form an acquisition device to be responsible for data acquisition. The second stage is data processing analysis, the created and selected processing rules encapsulate the logic and specific operation method for data processing by using components, and the processing rules and corresponding components form an analysis processor for data analysis and processing. The third stage is data transmission storage, the created or selected transmission rule encapsulates the specific operation method and data format for data transmission storage by using the components, and the transmission rule and the corresponding components form a transmitter to be responsible for the data transmission storage work.

(4) Establishing data processing tasks

The power plant information data are various, and the collection, processing, sending and storage processes of each kind of data need to be clear, so that the correctness of the data processing work can be ensured. Here, a corresponding data processing task is established for each type of data, a suitable task can be selected from the task library as well, a new task can be created according to requirements or modified on the original basis, and the new task can be saved in the task library as well. The task is a complete processing method for packaging a type of data based on a classification model, namely components and rules determined in three main stages of data processing are explicitly recorded in the task, usually, one task describes a typical processing process of a type of power plant informatization data, and if the same or similar type of data needs to be processed subsequently, the corresponding task can be directly reused or modified on the basis of the original task.

(5) Initiating data processing tasks

Based on the tasks that have been determined, we can start a specific data acquisition process, i.e. start a data processing task. As shown in fig. 1 and 2, initiating a data processing task comprises two phases, the first phase being the provision of specific parameters, i.e. the provision of specific data processing parameters based on the task that has been determined. Such as in the data acquisition or transmission storage phase: the database driving component is adopted, and generally an IP address of a database operation server, a database monitoring port number, a database service name, a database login user name/password, a table name for storing data and the like are provided; by adopting the file component, a file path, a file name, a file extension name and the like are generally required to be provided; with network listen or transmit components, it is generally necessary to provide a listen protocol name, a listen port, a data sampling interval, etc. And in the data analysis processing stage: with some component of a data mining or data analysis algorithm, it is necessary to provide some condition parameters for the algorithm to run and to perform initial parameters. And in the second stage, based on specific parameters and corresponding tasks, a task execution space is created, each task instance is created by a task execution engine (including a rule engine), required components are instantiated, corresponding rules are loaded to control program execution, and the whole processes of data acquisition, analysis processing and transmission storage are completed.

An example of a thermal power plant is given below, and a brief description will be given of an embodiment of the present invention in conjunction with information data to be processed by the example. The method provided by the invention is adopted to process data according to the implementation steps given above:

(1) establishing a classification model

Table 1 example data classification model

Analyzing the characteristics of informationized data required to be processed by the thermal power plant, establishing a classification model by combining with actual application requirements, and selecting four data for explaining in order to simplify an example, as shown in table 1, because a root node has no practical significance, all levels of nodes below the root node and meanings thereof are listed, a first level node encapsulates the source characteristics of the data, a second level node encapsulates the destination characteristics of the data, a third level node encapsulates the processing characteristics of the data, leaf nodes correspond to four different types of data respectively, and each type of data has an internal unique identifier, thereby ensuring the accuracy in model retrieval.

(2) Determining suitable components

The components that need to be used throughout the data process are determined based on the classification model and the application requirements. In the data acquisition stage: the data source characteristics of the primary nodes of the retrieval and analysis model are mainly retrieved, and the four types of data sources are different, so that the data source characteristics are supported by an Oracle database driving component, an equipment control system interface component (software interface component), an Excel file component and a Word file component respectively. In the data analysis processing stage: the data processing characteristics of three-level nodes of the retrieval analysis model are mainly retrieved, the first three types of data only comprise simple data association and extraction operations and do not need component support, and the last type of data needs complex text information analysis and therefore needs the support of a text analysis component. In the data transmission and storage stage: the data destination characteristic of the secondary node of the analysis model is mainly retrieved, and all four kinds of information need to be stored in the MySQL database, so that the support of a MySQL database driving component is needed.

(3) Determining appropriate rules

The rules that need to be used throughout the data process are determined based on the classification model and the application requirements. In the data acquisition stage: the four types of data are acquired by using corresponding components, and by analyzing application requirements, specific data contents of how to use the components for data acquisition and acquisition are explicitly written in the rules. In the data analysis processing stage: by analyzing application requirements, the first two data require rules to control their association, here using the device ID as the association identifier, the third data require rules to control the extracted key information, and the fourth data require rules to control the operating mode of the component. In the data transmission and storage stage: all four types of data are stored in the database, and the database driving component needs to be controlled to write the data into the corresponding table in the rule.

(4) Establishing data processing tasks

Three data processing tasks are established here based on the components and rules determined for the four types of data in the previous steps. The first task contains the first two kinds of data, and the task records the components and rules determined in the three main stages of data acquisition, analysis processing and transmission storage. Similarly, the second and third tasks record data processing information of the third and fourth data, respectively.

(5) Initiating data processing tasks

Specific parameter information is provided for the data to be collected. In the data acquisition stage: the first data needs to provide parameters such as an Oracle database address, a service name, a port, a user name/password, a table name and the like, the second data needs to provide parameters such as an IP address, a user name/password, authority and the like according to specific requirements of a software interface, the third data is similar to the fourth data, and information such as an address, a path, a file name, a file extension name and the like of a host where a file is located needs to be provided. In the data analysis processing stage: the fourth data needs to provide parameters such as a data dictionary for text analysis, emotion analysis keywords and the like. In the data transmission and storage stage: all four kinds of data need to provide parameters such as MySQL data address, service name, port, table space name, table name, field name and the like. Based on these already provided parameter information, a specific data processing procedure can be started by starting a number of instantiated tasks.

Claims (2)

1. A classification processing method of power plant information data based on rules and components comprises the following steps:

the method comprises the following steps that (1) according to different characteristics of different power plant information data, a classification model which has a hierarchical structure and comprises leaf nodes and non-leaf nodes is established for the different power plant information data, so that the different power plant information data are uniformly organized in the classification model; the classification model is established according to application requirements and data characteristics, and the classification model comprises different types of power plant informatization data and characteristics corresponding to the different types of power plant informatization data; one leaf node in the classification model corresponds to one type of power plant information data, a non-leaf node describes a certain characteristic of the corresponding type of power plant information data, and the characteristic of the power plant information data comprises any characteristic of a source characteristic, a destination characteristic and a processing characteristic of the data;

searching model nodes of the classification model based on application requirements, determining relevant characteristics of data to be processed, and establishing or selecting proper different components respectively used for acquiring, processing, sending and storing the data from a component library based on the searched data characteristics;

step (3) retrieving model nodes of the classification model based on application requirements, determining relevant characteristics of data to be processed, and establishing or selecting proper different rules for respectively acquiring, processing, sending and storing the data from a rule base based on the retrieved data characteristics; the acquisition rule and the corresponding acquisition component form an acquisition device for being responsible for the acquisition work of the data, the processing rule and the corresponding processing component form an analysis processor for being responsible for the analysis processing work of the data, and the sending rule and the corresponding sending component form a sender for being responsible for the sending and storing work of the data;

and (4) establishing or selecting a proper task from a task library based on a corresponding collector, an analysis processor and a transmitter which are respectively composed of different components and rules for collecting, processing, transmitting and storing the data according to the data to be processed, providing a specific parameter starting task, and processing the power plant information data, wherein the task in the task library can be reused.

2. The classification processing method for the plant informatization data according to claim 1, characterized in that the step (4) specifically comprises the following steps:

step (4.1) based on the determined task and application requirements, providing specific parameters used in each stage of data acquisition, analysis processing, sending and storage;

and (4.2) creating a task execution space, creating each task instance by a task execution engine, completing the needed component instantiation and rule loading work, and starting an actual data processing process.

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