CN113887861A - Power transmission and transformation main equipment quasi-real-time data monitoring system - Google Patents

Power transmission and transformation main equipment quasi-real-time data monitoring system Download PDF

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CN113887861A
CN113887861A CN202110967636.3A CN202110967636A CN113887861A CN 113887861 A CN113887861 A CN 113887861A CN 202110967636 A CN202110967636 A CN 202110967636A CN 113887861 A CN113887861 A CN 113887861A
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张玉波
欧阳健娜
张炜
唐捷
黄志都
崔志美
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Electric Power Research Institute of Guangxi Power Grid Co Ltd
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Abstract

The invention discloses a quasi-real-time data monitoring system of power transmission and transformation main equipment, which relates to the technical field of power transmission and transformation equipment monitoring, and realizes the real-time monitoring of the running state of primary equipment by the collection, fusion and integrated monitoring of the quasi-real-time data of the power transmission and transformation main equipment through a data access module and a data processing module; the processing results of the data defect analysis module, the risk data evaluation module and the alarm module can monitor and release the alarm and early warning information of the power transmission and transformation main equipment, and the running state of the equipment can be mastered in real time; through data online rate, availability ratio scheduling problem that can also pay attention to the accurate real-time data monitoring system of power transmission and transformation owner equipment continuously, supervise each unit and carry out system operation and maintenance, rectification, help the steady operation of all kinds of equipment monitoring systems of guarantee.

Description

Power transmission and transformation main equipment quasi-real-time data monitoring system
Technical Field
The invention belongs to the technical field of power transmission and transformation equipment monitoring, and particularly relates to a quasi-real-time data monitoring system for power transmission and transformation main equipment.
Background
In the daily use and operation of the power equipment, due to the influence of factors such as load, internal stress, abrasion, corrosion, etc., the individual parts or the whole of the power equipment can change in the aspects of form, components, electrical performance, etc., and the performance deterioration phenomenon can reduce the reliability of the power equipment, and even cause accidents for serious people.
The power transmission and transformation monitoring equipment mainly monitors the running states of electrical equipment, mechanical equipment and the like in power transmission and transformation links, acquires relevant information of the running states and the running quality of the equipment through various sensors, and dynamically tracks the development states of various degradation processes, so that an electric power operation and maintenance management department can maintain and replace the equipment in time before the equipment possibly breaks down or the performance of the equipment is reduced to influence normal work, and the safety, the stability and the reliability of the operation of the equipment are guaranteed.
Therefore, the on-time data monitoring of the visible power transmission and transformation main equipment is very important, but at present, a quasi-real-time data monitoring system for the power transmission and transformation main equipment is not provided, so that the on-time data monitoring of the power transmission and transformation main equipment is needed, data support is provided for power workers, and the operation of a power grid is assisted to be guaranteed.
Disclosure of Invention
The invention aims to provide a quasi-real-time data monitoring system for power transmission and transformation main equipment, so that the defect that the existing quasi-real-time data monitoring system for the power transmission and transformation main equipment is not available is overcome.
In order to achieve the above object, the present invention provides a quasi-real-time data monitoring system for power transmission and transformation main equipment, comprising: .
The data access module is used for accessing quasi-real-time data of the power transmission and transformation main equipment;
the quasi real-time data bin is used for storing the data transmitted by the data access module;
the data processing module is used for sorting, classifying and correlating the quasi-real-time data of the power transmission and transformation main equipment accessed by the data access module;
the defect data analysis module is used for acquiring defect data processed by the data processing module and analyzing and processing the defect data; and
and the risk data evaluation module is used for carrying out risk evaluation according to various equipment data obtained by processing of the defect data analysis module.
The system further comprises a display module, wherein the display module is used for displaying data processed by the data processing module, the defect data analysis module and the risk data evaluation module in combination with a map.
The system further comprises an alarm module, wherein the alarm module is used for judging whether to alarm according to the defect data processed by the data processing module.
Further, the data access module accesses the time sensitive network by adopting a quasi-real-time Ethernet.
Further, the data processing module is configured to perform sorting, classifying and association processing on the quasi-real-time data of the power transmission and transformation main device accessed by the data access module, and includes:
acquiring quasi-real-time data of the power transmission and transformation main equipment through the data access module;
classifying and correlating the quasi real-time data according to the data type, the voltage grade, the equipment type and the data source;
evaluating the equipment facing to suppliers according to all data of each type of equipment, performing grading and interval linear distribution processing on different equipment, and displaying the different equipment through a display module;
and respectively processing all the devices of each type to obtain abnormal state data, wherein the abnormal state data is defect data.
Further, the defect data analysis module of the data defect analysis module is configured to obtain defect data processed by the data processing module, and the analyzing and processing of the defect data includes:
acquiring defect data processed by a data processing module;
determining the defect state of the equipment according to the defect data;
further analyzing the abnormal state, and analyzing the reasons and the occurring parts caused by the defects of the equipment and the trend distribution rule of various defects along with the operation years;
counting equipment manufacturers and equipment models with higher equipment defect incidence;
and displaying the abnormal state through a display module in a form or bar chart mode according to a further analysis result of the abnormal state and the equipment manufacturer and the equipment model.
Further, the risk data evaluation module performs risk evaluation according to various types of device data obtained by the device processing module, including:
establishing an artificial intelligence risk assessment model by adopting a BP neural network, wherein the output of the artificial intelligence risk assessment model is the consequence caused by equipment abnormity and the fault probability of the equipment;
inputting the result processed by the defect data analysis module into the artificial intelligence risk assessment model to obtain the consequence caused by equipment abnormality and the fault probability of the equipment;
and comprehensively evaluating the equipment risk and determining the equipment risk level according to the result caused by the equipment abnormality and the fault probability of the equipment.
Furthermore, a Flume interceptor is connected to the quasi-real-time Ethernet access time sensitive network and is connected to the quasi-real-time data warehouse through the Flume interceptor.
Compared with the prior art, the invention has the following beneficial effects:
the power transmission and transformation main equipment quasi-real-time data monitoring system provided by the invention is used for accessing the quasi-real-time data of the power transmission and transformation main equipment through the data access module; the quasi-real-time data warehouse stores the data transmitted by the data access module; the data processing module is used for carrying out processing such as sorting, classification and association on the quasi-real-time data of the power transmission and transformation main equipment accessed by the data access module; the defect data analysis module is used for acquiring defect data processed by the data processing module and analyzing and processing the defect data; and the risk data evaluation module is used for carrying out risk evaluation according to various equipment data obtained by processing of the defect data analysis module. The method comprises the following steps of collecting, fusing and monitoring quasi-real-time data of the power transmission and transformation main equipment in an integrated manner through a data access module and a data processing module, so that the real-time monitoring of the running state of primary equipment is realized; the processing results of the data defect analysis module, the risk data evaluation module and the alarm module can monitor and release the alarm and early warning information of the power transmission and transformation main equipment, and the running state of the equipment can be mastered in real time; the problems of online data rate, availability rate and the like of the quasi-real-time data monitoring system of the power transmission and transformation main equipment can be continuously concerned, and all units are supervised to carry out system operation, maintenance and rectification and help to ensure the stable operation of all equipment monitoring systems.
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In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only one embodiment of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a quasi-real-time data monitoring system of power transmission and transformation main equipment according to the present invention.
Detailed Description
The technical solutions in the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 shows a quasi-real-time data monitoring system for electric transmission and transformation main equipment according to an embodiment of the present invention, which includes: a data access module, a quasi-real-time data bin, a data processing module, a defect data analysis module and a risk data evaluation module,
the data access module is used for accessing quasi-real-time data of the power transmission and transformation main equipment;
the quasi real-time data bin is used for storing the data transmitted by the data access module;
the data processing module is used for carrying out processing such as sorting, classification and association on the quasi-real-time data of the power transmission and transformation main equipment accessed by the data access module;
the defect data analysis module is used for acquiring defect data processed by the data processing module and analyzing and processing the defect data;
and the risk data evaluation module is used for carrying out risk evaluation according to various equipment data obtained by processing of the defect data analysis module.
The power transmission and transformation main equipment quasi-real-time data monitoring system is used for accessing quasi-real-time data of the power transmission and transformation main equipment through the data access module; the quasi-real-time data warehouse stores the data transmitted by the data access module; the data processing module is used for carrying out processing such as sorting, classification and association on the quasi-real-time data of the power transmission and transformation main equipment accessed by the data access module; the defect data analysis module is used for acquiring defect data processed by the data processing module and analyzing and processing the defect data; and the risk data evaluation module is used for carrying out risk evaluation according to various equipment data obtained by processing of the defect data analysis module. The method comprises the following steps of collecting, fusing and monitoring quasi-real-time data of the power transmission and transformation main equipment in an integrated manner through a data access module and a data processing module, so that the real-time monitoring of the running state of primary equipment is realized; the processing results of the data defect analysis module, the risk data evaluation module and the alarm module can monitor and release the alarm and early warning information of the power transmission and transformation main equipment, and the running state of the equipment can be mastered in real time; the problems of online data rate, availability rate and the like of the quasi-real-time data monitoring system of the power transmission and transformation main equipment can be continuously concerned, and all units are supervised to carry out system operation, maintenance and rectification and help to ensure the stable operation of all equipment monitoring systems.
In one embodiment, the power transmission and transformation main equipment quasi-real-time data monitoring system further comprises a display module, and the display module is used for displaying data processed by the data processing module, the defect data analysis module and the risk data evaluation module in combination with a map.
Specifically, the display module obtains, according to the data processing module: the data type, the voltage level, the equipment type, the data source and the like are combined with a map to display data according to different unit levels; in addition, the display data processing result, the intermediate data, and the like may be performed according to other settings.
In one embodiment, the power transmission and transformation main equipment quasi-real-time data monitoring system further comprises an alarm module, and the alarm module is used for judging whether an alarm is needed or not according to the defect data processed by the data processing module.
The alarm module specifically comprises: a threshold alarm module, a trend alarm module and an associated alarm module,
the threshold alarm module processes the analysis result of the defect data analysis module, sends out a corresponding threshold alarm and displays the threshold alarm through the display module;
the trend alarm module is used for obtaining the defect development trend of the equipment by combining threshold alarm processing according to the analysis result of the defect data analysis module and displaying the defect development trend through the display module;
the correlation alarm module firstly informs the results of the threshold alarm module and the trend alarm module to background monitoring personnel; then acquiring corresponding original quasi real-time data from the quasi real-time data bin, searching a corresponding data source according to the original quasi real-time data, and simultaneously sending results for a threshold value alarm module and a trend alarm module to a data source end; if the source changes the communication mode of the mobile terminal of the data monitoring personnel, the results of the threshold value alarm module and the trend alarm module are sent to the mobile terminal of the monitoring personnel, and the results are displayed through the display module; the alarm result can be reminded at the fastest speed through the associated alarm, and meanwhile, the alarm can be reminded through other monitors, so that the real-time performance, the timeliness and the accuracy of monitoring of the equipment are guaranteed.
The alarm module realizes the comprehensive alarm of key equipment by combining a threshold alarm module, a trend alarm module and an associated alarm module, and timely presents users in various notification modes.
In one embodiment, the alarm module displays various alarm contents in the form of tags.
In one embodiment, the threshold alarm module divides the threshold range of each type of defect data analyzed by the defect data analysis module, marks corresponding severity on the divided threshold range, judges which threshold range the defect data analyzed by the defect data analysis module belongs to, and sends out a prompt according to the severity of the threshold range, wherein the severity is: general defects, major defects, economic defects, fifth-order events, fourth-order events, third-order events, second-order events, first-order events, general accidents, major accidents, and pallet major accidents.
The trend alarm module obtains the defect development trend of the equipment by combining threshold alarm processing according to the analysis result of the defect data analysis module, and comprises the following steps:
and constructing a trend prediction module according to the analysis result of the defect data analysis module and the data and the result analyzed by the threshold alarm module of the threshold alarm module, obtaining the development trend of the corresponding defect through the trend prediction module, and setting the corresponding damage according to the defect of each type of equipment by the trend alarm module.
In one embodiment, the trend prediction module uses a linear fit model. The trend preset result y = weight of the severity of the threshold alarm module x fault probability x 100%, correspondingly, the larger y is, the earlier the defect needs to be processed, and y corresponds to the development degree of the defect.
In one embodiment, the data access module accesses the time-sensitive network by using a quasi-real-time ethernet.
The quasi-real-time Ethernet is accessed into the time-sensitive network, the work of the non-standard real-time Ethernet special chip is separated, the packaging and analysis work is delivered to a standard Ethernet controller based on PC or IPC, and a data frame receiving and transmitting mechanism is delivered to an FPGA at an industrial gateway for completion; when the data frame is transmitted to the industrial gateway, the complete data frame of the non-standard real-time Ethernet in the period is analyzed and transmitted to the slave station of the non-standard real-time Ethernet, so that the real-time data can be aligned in multiple aspects to be acquired, a special communication chip is replaced, complicated mapping relation processing is avoided, and the cost can be greatly reduced.
In one embodiment, the data processing module is configured to perform processing such as sorting, classifying, and associating on the quasi-real-time data of the power transmission and transformation main device accessed by the data access module, and includes:
s11, acquiring quasi-real-time data of the power transmission and transformation main equipment through the data access module;
s12, classifying and correlating the quasi-real-time data according to the data type, the voltage level, the equipment type and the data source, and eliminating redundant voice data by adopting an artificial intelligent data detection method;
s13, evaluating the equipment facing to suppliers according to all data of each type of equipment, specifically, evaluating the suppliers from the aspects of access rate, online rate, failure rate, after-sales service and the like of the equipment, performing grading and linear distribution processing among different equipment, and then displaying through a display module, wherein the difference between good and bad can be effectively opened through a display result;
and S14, respectively processing all the devices of each type to obtain abnormal state data, wherein the abnormal state data are defect data.
In one embodiment, the step of processing all the devices of each type by the data processing module to obtain the abnormal state data includes the following steps:
s1401, data of one type of equipment is classified into single-state quantity data and multi-state quantity data, voice data and image data in the single-state quantity data and the multi-state quantity data are recognized by utilizing an intelligent voice processing mutual technology and an intelligent image recognition technology, and the single-state quantity data and the multi-state quantity data are converted into text data;
s1402, fitting each single state quantity data through an AR model according to the normal state value range of each single state quantity data;
s1403, a self-organizing neural network module is constructed, and historical data after the AR model is fitted are input into the self-organizing neural network module for training to obtain a trained self-organizing neural network module;
s1404, fitting each single state quantity data acquired in real time through an AR model, inputting the data into a trained self-organizing neural network module to obtain a time sequence of the single state quantity data, judging whether the single state quantity data accord with AR distribution, if so, judging that the single state quantity data are normal data, otherwise, judging that the single state quantity data are abnormal data;
s1405, obtaining a transition probability matrix through the trained self-organizing neural network module by the multi-state quantity data;
and S1406, judging whether abnormal data exist or not through a density-based clustering algorithm according to the transition probability matrix, wherein the abnormal data are defect data.
By adopting the intelligent voice interaction technology, the intelligent image recognition technology, the deep learning algorithm and the like, the working mode of the mouse pad main equipment for quasi-real-time data detection is optimized, the professional management is enhanced, and a solid foundation is laid for smoothly and efficiently finishing the monitoring work.
In one embodiment, the power transmission and transformation main equipment comprises: main transformer, circuit breaker and transmission line.
In one embodiment, the defect data analysis module of the data defect analysis module is configured to obtain defect data processed by the data processing module, and the analyzing and processing the defect data includes:
s21, acquiring defect data processed by the data processing module;
s22, determining the defect state of the equipment according to the defect data;
s23, further analyzing the abnormal state, and analyzing the reasons caused by the defects of the equipment, the occurrence positions, the trend distribution rule of various defects along with the delivery years and the like;
s24, counting equipment manufacturers and equipment models with higher equipment defect incidence;
and S25, displaying the abnormal state through a display module in a form of a table or a bar chart and the like according to the further analysis result of the abnormal state and the equipment manufacturer and the equipment model.
The defect of the equipment can be pre-judged in advance through the analysis result of the defect data analysis module, and support is provided for the operation and maintenance strategy formulation of the equipment.
In one embodiment, the risk data evaluation module performs risk evaluation according to various types of device data processed by the device processing module, and includes:
s31, establishing an artificial intelligence risk assessment model by adopting a BP neural network, wherein the output of the artificial intelligence risk assessment model is the consequence caused by equipment abnormity and the fault probability of the equipment;
s32, inputting the results processed by the defect data analysis module into the artificial intelligence risk assessment model to obtain the consequences caused by equipment abnormality and the failure probability of the equipment;
and S33, comprehensively evaluating the equipment risk and determining the equipment risk level according to the result caused by the equipment abnormality and the fault probability of the equipment.
In addition, the artificial intelligence risk assessment model determines the consequences caused by equipment abnormity and the fault probability of equipment according to the defect data, then automatically takes the defect data as training samples, and trains the artificial intelligence risk assessment model according to the training samples when a certain number of the training samples are reached so as to improve the accuracy of the artificial intelligence risk assessment model.
In the comprehensive evaluation process, the product of the result caused by the equipment abnormality and the fault probability is used as the basis for grading.
In one embodiment, a Flume interceptor is connected to the quasi-real-time ethernet access time sensitive network and connected to the quasi-real-time data warehouse through the Flume interceptor.
Specifically, a standard ethernet controller in the quasi-real-time ethernet access time sensitive network is connected to a Flume interceptor.
The Flume is a distributed, reliable and available data collection system, can effectively collect, aggregate and move a large amount of data, can be transferred to a centralized data warehouse from a plurality of different sources, and enables the whole process of data access of the power transmission and transformation main equipment quasi-real-time data monitoring system to be more reliable through the power transmission and transformation main equipment quasi-real-time data monitoring system.
In addition, the cloud server can be connected with the Flume interceptor, and different quasi-real-time data, such as equipment accounts, defect records, defect analysis reports and the like, can be accessed through the other cloud servers.
It will be apparent to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely illustrated, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the mobile terminal is divided into different functional units or modules to perform all or part of the above described functions. Each functional module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional modules are only used for distinguishing one functional module from another, and are not used for limiting the protection scope of the application. The specific working process of the module in the mobile terminal may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above disclosure is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or modifications within the technical scope of the present invention, and shall be covered by the scope of the present invention.

Claims (8)

1.一种输变电主设备准实时数据监测系统，其特征在于，包括：1. a quasi-real-time data monitoring system for power transmission and transformation main equipment, is characterized in that, comprises: 数据接入模块，所述数据接入模块用于接入输变电主设备的准实时数据；a data access module, which is used to access the quasi-real-time data of the main power transmission and transformation equipment; 准实时数据仓，所述准实时数据仓用于存储所述数据接入模块传输的数据；A quasi-real-time data warehouse, the quasi-real-time data warehouse is used to store the data transmitted by the data access module; 数据处理模块，所述数据处理模块用于对数据接入模块接入的输变电主设备的准实时数据进行整理、分类以及关联处理；a data processing module, which is used for sorting, classifying and correlating the quasi-real-time data of the main power transmission and transformation equipment accessed by the data access module; 缺陷数据分析模块，所述缺陷数据分析模块用于获取所述数据处理模块处理得到的缺陷数据，并对所述缺陷数据进行分析处理；以及A defect data analysis module, the defect data analysis module is configured to acquire defect data processed by the data processing module, and analyze and process the defect data; and 风险数据评估模块，所述风险数据评估模块用于根据缺陷数据分析模块处理得到的各类设备数据进行风险评估。A risk data assessment module, which is used to perform risk assessment according to various types of equipment data processed by the defect data analysis module. 2.根据权利要求1所述的输变电主设备准实时数据监测系统，其特征在于，还包括展示模块，所述展示模块用于对数据处理模块处理、缺陷数据分析模块以及风险数据评估模块处理的数据进行展示的数据结合地图进行展示。2. The quasi-real-time data monitoring system for main power transmission and transformation equipment according to claim 1, further comprising a display module, the display module is used to process the data processing module, the defect data analysis module and the risk data evaluation module The processed data is displayed The data is displayed in combination with the map. 3.根据权利要求1所述的输变电主设备准实时数据监测系统，其特征在于，还包括报警模块，所述报警模块用于根据所述数据处理模块处理得到的缺陷数据进行判断是否需要报警。3. The quasi-real-time data monitoring system for main power transmission and transformation equipment according to claim 1, further comprising an alarm module, which is used to judge whether it is necessary according to the defect data processed by the data processing module. Call the police. 4.根据权利要求1所述的输变电主设备准实时数据监测系统，其特征在于，所述数据接入模块采用准实时以太网接入时间敏感网络。4 . The quasi-real-time data monitoring system for main power transmission and transformation equipment according to claim 1 , wherein the data access module adopts quasi-real-time Ethernet to access a time-sensitive network. 5 . 5.根据权利要求1所述的输变电主设备准实时数据监测系统，其特征在于，所述数据处理模块用于对数据接入模块接入的输变电主设备的准实时数据进行整理、分类以及关联处理包括：5 . The quasi-real-time data monitoring system for main power transmission and transformation equipment according to claim 1 , wherein the data processing module is used to sort out the quasi-real-time data of the main power transmission and transformation equipment accessed by the data access module. 6 . , classification, and association processing include: 通过所述数据接入模块获取输变电主设备的准实时数据；Obtain quasi-real-time data of the main power transmission and transformation equipment through the data access module; 根据数据类型、电压等级、设备类型、数据源对所述准实时数据进行分类，并进行关联；Classify and associate the quasi-real-time data according to data type, voltage level, device type, and data source; 根据每一种类型设备的所有数据对所述设备进行面向供应商的评价，并对不同设备采取分档次、分区间线性分布处理，后通过显示模块进行显示；According to all the data of each type of equipment, the equipment is evaluated for suppliers, and different equipment is processed by grades and divisions linearly distributed, and then displayed through the display module; 分别对每一种类型设备的所有进行处理得到异常状态数据，所述异常状态数据为缺陷数据。The abnormal state data is obtained by separately processing all equipment of each type, and the abnormal state data is defect data. 6.根据权利要求1所述的输变电主设备准实时数据监测系统，其特征在于，6. The quasi-real-time data monitoring system for main power transmission and transformation equipment according to claim 1, characterized in that, 所述数据缺陷分析模块缺陷数据分析模块用于获取所述数据处理模块处理得到的缺陷数据，并对所述缺陷数据进行分析处理包括：The defect data analysis module of the data defect analysis module is used to obtain the defect data processed by the data processing module, and analyze and process the defect data, including: 获取数据处理模块处理得到的缺陷数据；Obtain the defect data processed by the data processing module; 根据所述缺陷数据确定设备的缺陷状态；Determine the defect state of the equipment according to the defect data; 对所述异常状态进行进一步分析，分析设备的缺陷造成的原因、发生部位以及各类缺陷随投运年限的趋势分布规律；The abnormal state is further analyzed, and the causes and locations of equipment defects are analyzed, as well as the trend distribution law of various defects with the operating years; 统计设备缺陷发生率较高的设备厂家和设备型号；Statistical equipment manufacturers and equipment models with a high incidence of equipment defects; 根据对所述异常状态进行进一步分析结果和设备厂家和设备型号以表格或柱形图方式通过显示模块显示。According to the result of further analysis on the abnormal state and the equipment manufacturer and equipment model, it is displayed through the display module in the form of a table or a bar graph. 7.根据权利要求1所述的输变电主设备准实时数据监测系统，其特征在于，所述风险数据评估模块根据设备处理模块处理得到的各类设备数据进行风险评估包括：7. The quasi-real-time data monitoring system for main power transmission and transformation equipment according to claim 1, wherein the risk data assessment module performs risk assessment according to various types of equipment data processed by the equipment processing module, comprising: 采用BP神经网络建立人工智能风险评估模型，所述人工智能风险评估模型的输出为设备异常造成的后果、设备发生的故障概率；A BP neural network is used to establish an artificial intelligence risk assessment model, and the output of the artificial intelligence risk assessment model is the consequences caused by abnormal equipment and the probability of failure of the equipment; 将缺陷数据分析模块处理的结果输入所述人工智能风险评估模型，得到设备异常造成的后果、设备发生的故障概率；Input the result processed by the defect data analysis module into the artificial intelligence risk assessment model, and obtain the consequences caused by abnormal equipment and the probability of equipment failure; 根据所述设备异常造成的后果、设备发生的故障概率综合评估设备风险的大小和确定设备风险的级别。According to the consequences caused by the abnormality of the equipment and the probability of failure of the equipment, the size of the equipment risk is comprehensively evaluated and the level of the equipment risk is determined. 8.根据权利要求1所述的输变电主设备准实时数据监测系统，其特征在于，在所述准实时以太网接入时间敏感网络连接有Flume拦截器，通过Flume拦截器与准实时数据仓连接。8. The quasi-real-time data monitoring system of the main power transmission and transformation equipment according to claim 1, wherein the quasi-real-time Ethernet access time-sensitive network is connected with a Flume interceptor, and the quasi-real-time data is connected by the Flume interceptor. warehouse connection.
CN202110967636.3A 2021-08-23 2021-08-23 Power transmission and transformation main equipment quasi-real-time data monitoring system Pending CN113887861A (en)

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