CN114896309A - Method and system for converting and displaying monitoring data of hydropower station - Google Patents
Method and system for converting and displaying monitoring data of hydropower station Download PDFInfo
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Abstract
The invention provides a method and a system for converting and displaying monitoring data of a hydropower station, wherein the method comprises the following steps: acquiring user demand information, and reading corresponding configuration information based on the demand information; assembling all configuration information based on a preset first assembly rule to obtain configuration items; determining original data of the user equipment according to the configuration items; analyzing the original data based on the enumeration strategy and the configuration information to obtain analyzed data; assembling the analysis data based on a preset second assembly rule to obtain operation data; the operation data and the configuration items are respectively displayed, and the problems that in the same monitoring page, due to the fact that different hydropower stations have different monitoring points to be displayed, the realization and the maintenance are difficult, different hydropower stations, equipment and monitoring points have different business meanings, the technical realization workload of a data conversion algorithm and a display method is large, the data conversion algorithm and the display method of different monitoring points are repeated, once a certain algorithm or method is changed, the maintenance is difficult, and errors are easily caused are solved.
Description
Technical Field
The invention relates to the technical field of automatic measurement and control, in particular to a method and a system for displaying monitoring data conversion of a hydropower station.
Background
Whether the hydroelectric station dam can safely operate or not only directly affects the economic benefit of a power plant, but also is closely related to the lives and properties of downstream people, national economic development and ecological environment, and means for accurately displaying the hydroelectric station monitoring data in real time is particularly important, in the method for displaying the hydroelectric station monitoring data in a conversion mode, developers define all monitoring points to be displayed in a monitoring page, then the programs acquire data without business meaning from the monitoring points of hydroelectric station monitoring equipment through monitoring point information, the developers realize a data conversion algorithm aiming at each monitoring point, convert the data without business meaning into the data with business meaning, and finally display the data with business meaning in a system according to a display mode of business requirements, so that the hydropower station monitoring data can be accurately displayed in real time, but the method is on the same monitoring page, because different hydropower stations have different displayed monitoring points and are difficult to realize and maintain, and different hydropower stations, equipment and monitoring points have different business meanings, the technical realization workload of the data conversion algorithm and the display method is large, and the data conversion algorithm and the display method of different monitoring points are repeated, so that once some algorithm or method is changed, the maintenance is difficult, and errors are easy to cause, therefore, a method and a system for converting and displaying monitoring data of the hydropower stations are urgently needed, are used for solving the problems that in the same monitoring page, different hydropower stations have different displayed monitoring points and are difficult to realize and maintain, different hydropower stations, equipment and monitoring points have different business meanings, the technical realization workload of the data conversion algorithm and the display method is large, and the data conversion algorithm and the display method of different monitoring points are repeated, once some algorithm or method is changed, the maintenance is difficult, and the problem of error is easily caused.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a hydropower station monitoring data conversion display method and a system, which are used for solving the problems that the realization and maintenance are difficult due to different monitoring points to be displayed by different hydropower stations on the same monitoring page, different hydropower stations, equipment and monitoring points have different business meanings, the technical realization workload of a data conversion algorithm and a display method is large, the data conversion algorithm and the display method of different monitoring points are repeated, and once a certain algorithm or method is changed, the maintenance is difficult and errors are easily caused.
A method for displaying hydropower station monitoring data conversion comprises the following steps:
acquiring user demand information, and reading corresponding configuration information based on the demand information;
assembling all configuration information based on a preset first assembly rule to obtain configuration items;
displaying the configuration items;
determining original data of the user equipment according to the configuration items; analyzing the original data based on the enumeration strategy and the configuration information to obtain analyzed data;
assembling the analysis data based on a preset second assembly rule to obtain operation data;
and displaying the operation data.
As an embodiment of the present invention, the determining step of the configuration information is as follows:
obtaining the dimensionality of the power station;
determining configuration information according to the dimensionality of the power station based on a preset configuration rule; the configuration information comprises any one or combination of a monitoring point name, a monitoring point code, a reading address, a writing address, a data type and data precision.
The type of the configuration item comprises any one of a function page type, a specific monitoring point type and a power station type.
As an embodiment of the present invention, determining raw data of a user equipment according to a configuration item includes:
based on a preset third assembly rule, intelligently assembling request parameters of the original data of the batch query equipment according to configuration items;
and acquiring the original data of the user equipment in batch according to the request parameters.
As an embodiment of the present invention, parsing original data based on an enumeration policy and configuration information to obtain parsed data includes:
circulating all the configuration information, and determining a corresponding enumeration strategy according to the operation type in the configuration information;
and correspondingly analyzing the original data based on the corresponding enumeration strategy to obtain analyzed data.
As an embodiment of the present invention, the enumeration policy includes: any one of a Bit enumeration strategy, an S16 enumeration strategy, a U16Bit enumeration strategy, an S32 enumeration strategy, an AbsS16 enumeration strategy and a U16Bitdouble enumeration strategy;
the Bit enumeration strategy specifically comprises the following steps: acquiring a first address difference, and acquiring a corresponding first original value in original data based on the first address difference; formatting the first original value based on a preset formatting configuration to obtain analytic data;
the S16 enumeration policy specifically includes: acquiring a second address difference, and acquiring a corresponding second original value in the original data based on the second address difference; converting the second original value to a signed 16 digit decimal number; processing the data precision of the 16-digit decimal number with the symbol according to the corresponding configuration information to obtain analysis data;
the U16Bit enumeration strategy specifically comprises the following steps: acquiring a third address difference, and acquiring a corresponding third original value in the original data based on the third address difference; converting the third raw value to an unsigned 16 decimal number; acquiring Bit bits corresponding to 16 decimal numbers without symbols in the corresponding configuration information; converting the Bit into a corresponding 10-system number; formatting the 10-system number based on preset formatting configuration to obtain analytic data;
the S32 enumeration policy specifically includes: acquiring a fourth address difference, and acquiring a corresponding high-order original value and a corresponding low-order original value in original data based on the fourth address difference; converting the high-order original value and the low-order original value into 32-bit binary numbers based on a mode of combining binary high 16 bits with binary low 16 bits; converting 32-bit binary number into 10-system number with symbols to obtain analytic data;
AbsS16 enumerates a policy, which specifically includes: acquiring a fifth address difference, and acquiring a corresponding fifth original value in the original data based on the fifth address difference; converting the fifth raw value to a signed 16 digit decimal number; processing the data precision of the 16-digit decimal number with the symbol according to the corresponding configuration information to obtain precision data; taking an absolute value of the precision data to obtain analytic data;
the U16BitDouble enumeration policy specifically includes: acquiring a sixth address difference, and acquiring a corresponding sixth original value in the original data based on the sixth address difference; converting the sixth original value to an unsigned 16 decimal number; acquiring a plurality of Bit bits corresponding to 16 decimal numbers without symbols in the corresponding configuration information; converting a plurality of Bit bits into corresponding 10-system numbers; and formatting the 10-system number based on preset formatting configuration to obtain analysis data.
As an embodiment of the present invention, after obtaining the operation data of the current user equipment, the method further includes:
selecting a proper monitoring node according to the node matching degree of the current user equipment, applying an abnormal data judgment request to the data center, and providing the operation data of the current user equipment to the data center;
after receiving the application and agreeing, the data center selects corresponding types of historical operating data, historical operating data abnormal judgment results, models and model convergence conditions according to the types of the monitoring nodes;
training the model based on the historical operating data, the historical operating data abnormal judgment result and the model convergence condition until the result is converged to obtain an abnormal data judgment model;
inputting the operation data into an abnormal data judgment model to obtain an abnormal judgment result;
if the abnormal judgment result is data abnormality, returning a data abnormality result through the monitoring node;
and carrying out exception marking on the operation data corresponding to the current user equipment.
As an embodiment of the present invention, selecting a suitable monitoring node according to the node matching degree of the current user equipment includes:
node numbering is carried out on each monitoring node in advance to obtain unique first numbering information;
acquiring second serial number information of the current user equipment; wherein the second number information includes: the device type number, the device area number and the device use number;
judging whether first number information which is completely the same as the second number information exists in all the monitoring nodes;
if the current user equipment exists, obtaining a first monitoring node, and using the first monitoring node as a monitoring node of the current user equipment;
if not, removing any number in the second number information based on a preset first importance screening rule to obtain third number information;
judging whether first number information containing third number information exists in all monitoring nodes or not;
if the current user equipment exists, obtaining a second monitoring node, and using the second monitoring node as the monitoring node of the current user equipment;
if the number does not exist, removing any number in the third number information based on a preset second importance degree screening rule to obtain fourth number information;
judging whether first number information containing fourth number information exists in all monitoring nodes or not;
if the current user equipment exists, obtaining a third monitoring node, and taking the third monitoring node as the monitoring node of the current user equipment;
if not, sending an abnormal judgment failure signal;
and when the number of the second monitoring nodes or the third monitoring nodes is multiple, one second monitoring node or one third monitoring node is selected as the monitoring node of the current user equipment.
As an embodiment of the present invention, a method for displaying monitoring data conversion of a hydropower station further includes:
when the abnormal judgment result is data abnormal, the data center acquires second operation data of the user equipment with all the node matching degrees matched with the current monitoring node based on the current monitoring node; wherein the second operation data carries a unique device tag;
inputting all the second operation data into an abnormal data judgment model respectively, and outputting a plurality of abnormal judgment results carrying unique marks;
acquiring third operation data with abnormal data judgment results in the second operation data;
acquiring second original data of the user equipment corresponding to the third operation data;
classifying the second original data based on the type of the preset monitoring data to obtain a second original data set; each data in the second original data set carries a monitoring data type;
collecting all monitoring data types carried in the second original data set, and establishing a common monitoring data type set;
acquiring abnormal information of a monitoring device matched with the monitoring data type in the common monitoring data type set; wherein the exception information includes: abnormal reasons in the monitoring period, abnormal data corresponding to the abnormal reasons, historical monitoring data and abnormal judgment results corresponding to the historical monitoring data;
establishing a plurality of anomaly analysis and diagnosis models respectively according to the anomaly information of each monitoring device;
respectively inputting all the second original data set data into corresponding anomaly analysis and diagnosis models to obtain a plurality of anomaly analysis and diagnosis results;
respectively judging whether the abnormal analysis diagnosis result exists in each second original data set or not as data with abnormal data;
classifying all second original data sets with data abnormality according to the monitoring data types of the abnormal data to obtain a plurality of third original data sets; the third original data set comprises a plurality of second original data sets of which abnormal data are of the same monitoring data type;
judging whether the number of the second original data sets in each third original data set exceeds a preset large-area abnormal number threshold of equipment or not based on a preset large-area abnormal rule of the equipment;
if the number of the second original data sets exceeds the preset large-area abnormal number threshold value, taking the third original data set with the number of the second original data sets exceeding the preset large-area abnormal number threshold value as a fourth original data set;
determining a monitoring device with large-area equipment abnormity as a first abnormity monitoring device based on the corresponding monitoring data type in the fourth original data set;
determining first abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set;
sending large-area same-equipment abnormal alarm information, carrying out large-area same-equipment abnormal marking on second operation data corresponding to the fourth original data set, and displaying a first abnormal monitoring device and first abnormal user equipment;
if the number of the second original data sets does not exceed the preset large-area abnormal number threshold value, taking a third original data set of which the number of the second original data sets does not exceed the preset large-area abnormal number threshold value as a fifth original data set;
determining a second abnormal monitoring device with abnormality based on the corresponding monitoring data type in the fifth original data set;
determining second abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set;
and sending equipment abnormity alarm information, carrying out abnormity marking on second operation data corresponding to the fifth original data set, and displaying a second abnormity monitoring device and second abnormity user equipment.
A system for hydropower station monitoring data conversion demonstration, comprising:
the front-end module is used for acquiring user demand information and reading corresponding configuration information based on the demand information;
the first assembly module is used for assembling all the configuration information based on a preset first assembly rule to obtain a configuration item;
the back end module is used for determining the original data of the user equipment according to the configuration items; analyzing the original data based on the enumeration strategy and the configuration information to obtain analyzed data;
the second assembly module is used for assembling the analysis data based on a preset second assembly rule to obtain operation data;
the front-end module is also used for respectively displaying the operation data and the configuration items.
The invention has the beneficial effects that:
1. the incidence relation between the monitoring page and the monitoring points is solved through the configuration items, so that the monitoring points displayed on the monitoring page can be dynamically changed, the realization is simple, and the maintenance is easy and convenient;
2. the configuration items realize the accurate control of a single monitoring point, the enumeration strategy and the display mode of the monitoring point can be conveniently modified, and the data conversion and display requirements of different power stations and different equipment can be met;
3. by classifying the data of the monitoring points and summarizing the data into various different enumeration strategies and display methods, the reusability and reliability are improved, the workload is reduced, and the expansibility is achieved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a method flow diagram of a method and system for displaying data conversion of hydropower stations in accordance with an embodiment of the present invention;
FIG. 2 is a method timing diagram illustrating an overall method of a method and system for converting hydropower station monitoring data according to an embodiment of the invention;
FIG. 3 is a flow chart of the assembly of raw data into operational data in a method and system for hydropower station monitoring data conversion demonstration in an embodiment of the invention;
fig. 4 is a schematic diagram illustrating specific analysis of enumeration strategies in a method and a system for displaying hydropower station monitoring data conversion according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Referring to fig. 1 and fig. 2, an embodiment of the present invention provides a method for displaying monitoring data conversion of a hydropower station, including:
s1, acquiring user demand information, and reading corresponding configuration information based on the demand information;
s2, assembling all configuration information based on a preset first assembly rule to obtain configuration items;
s3, displaying the configuration items;
s4, determining the original data of the user equipment according to the configuration items;
s5, analyzing the original data based on the enumeration strategy and the configuration information to obtain analyzed data;
s6, assembling analysis data based on a preset second assembly rule to obtain operation data;
s7, displaying the operation data;
the working principle of the technical scheme is as follows: the method comprises the steps of classifying and defining configuration information in advance, acquiring user demand information during operation, reading corresponding configuration information based on the demand information, assembling all configuration information based on a preset first assembly rule to obtain a configuration item, wherein the preset first assembly rule is preferably a configuration rule personalized according to the user demand information according to a power station, a function page, a specific monitoring point and the like, and is used for meeting personalized requirements of different services of different power stations, for example: the unit overview function page of the power station A needs to show power grid frequency monitoring points, and the power station B does not show the power grid frequency monitoring points; the unit overview page needs to display monitoring points such as unit voltage, unit current, guide vane opening, exciting current, unit rotating speed and the like, and the state monitoring page needs to display monitoring point parameters such as DI input, system remote signaling, AI off-limit, speed regulating system and the like; the excitation mode needs to be displayed in a text mode, the terminal voltage and the terminal current need to be displayed in a digital mode, and the DI/start-up mode is displayed in a signal lamp mode; determining original data of the user equipment according to the configuration items, and analyzing the original data based on the enumeration strategy and the configuration information to obtain analyzed data; based on the preset second assembly rule, assembling and analyzing data to obtain operation data, wherein the operation data is preferably JSON format data, furthermore, a monitoring page can display monitoring points to be displayed according to configuration information, meanwhile, different display items can be displayed in different forms according to business requirements and combination of the configuration information, the displayed data can issue operation to the issued monitoring points through the configuration information, for example, in a unit overview page, a system can display and monitor items such as AGC operation, intelligent power generation, guide vane opening, oil pressure, exciting current, unit rotating speed and the like in real time, and can issue instructions to the items such as AGC operation and intelligent power generation;
the beneficial effects of the above technical scheme are: the incidence relation between the monitoring page and the monitoring points is solved through the configuration items, so that the monitoring points displayed on the monitoring page can be dynamically changed, the realization is simple, and the maintenance is easy and convenient; the configuration items realize the accurate control of a single monitoring point, the enumeration strategy and the display mode of the monitoring point can be conveniently modified, and the data conversion and display requirements of different power stations and different equipment can be met; by classifying the data of the monitoring points and summarizing the data into various different enumeration strategies and display methods, the reusability and reliability are improved, the workload is reduced, and the expansibility is achieved.
In one embodiment, the configuration information is determined as follows:
obtaining the dimensionality of the power station;
determining configuration information according to the dimensionality of the power station based on a preset configuration rule; the configuration information comprises any one or combination of a monitoring point name, a monitoring point code, a reading address, a writing address, a data type and data precision;
the working principle and the beneficial effects of the technical scheme are as follows: configuring configuration information in advance according to the dimensionality of the power station; the configuration information comprises any one or combination of a monitoring point name, a monitoring point code, a reading address, a writing address, a data type and data precision, and the specific content of the configuration information can be adjusted according to different configuration items; for example, a monitoring point for the governor operating condition is configured, coded as 401262, the read address and the write address are both 401262, and the data type is s16 (signed 16-bit integer data).
In one embodiment, the type of configuration item includes any one of a function page type, a specific monitoring point type, and a power station type.
Referring to fig. 3, in an embodiment, determining raw data of a user equipment according to a configuration item includes:
based on a preset third assembly rule, intelligently assembling request parameters of the original data of the batch query equipment according to configuration items;
acquiring original data of the user equipment in batches according to the request parameters;
the working principle and the beneficial effects of the technical scheme are as follows: classifying according to services in a program, and enumerating all analysis enumeration strategies in advance; the method comprises analytic enumeration strategies such as Bit switching value data, 16-Bit integer data with symbols in S16, 16-Bit integer data without symbols in U16Bit, taking the nth Bit as Bit, integrating two 16 integers in S32 into a 32-Bit integer, and taking absolute value of the 16-Bit integer data with symbols in AbsS 16; when the page is opened, a long connection based on websocket can be established between the page and a background monitoring program, and the data change of the equipment is monitored in real time, specifically: when the system runs, the function page loads the specified configuration items in the codes according to the service requirements, the monitoring program of the background can intelligently assemble request parameters for inquiring the data of the equipment in batches by analyzing the configuration items, and then the original data of the user equipment is obtained in batches according to the assembled request parameters. The original data is provided in the form of an address code. For example, the request address field is 235-238, the original data is in [0,0,1,1] format.
In one embodiment, parsing the raw data based on the enumeration policy and the configuration information to obtain parsed data includes:
circulating all the configuration information, and determining a corresponding enumeration strategy according to the operation type in the configuration information;
correspondingly analyzing the original data based on the corresponding enumeration strategy to obtain analyzed data;
the working principle and the beneficial effects of the technical scheme are as follows: analyzing service data which can be understood by service personnel according to the configuration information and the original data by combining the configuration information and an enumeration algorithm; for example, the fault analysis of the monitoring amount DI speed regulator is red light, yellow light, green light and white light display, the front pool water level analysis is 10 meters (number + unit format), the operation mode is analyzed to be a constant terminal voltage text mode, and the like, so that the data conversion and display requirements of different power stations and different equipment are met.
Referring to FIG. 4, in one embodiment, an enumeration policy includes: any one of a Bit enumeration strategy, an S16 enumeration strategy, a U16Bit enumeration strategy, an S32 enumeration strategy, an AbsS16 enumeration strategy and a U16Bitdouble enumeration strategy;
the Bit enumeration strategy specifically comprises the following steps: acquiring a first address difference, and acquiring a corresponding first original value in original data based on the first address difference; formatting the first original value based on a preset formatting configuration to obtain analytic data;
the S16 enumeration policy specifically includes: acquiring a second address difference, and acquiring a corresponding second original value in the original data based on the second address difference; converting the second original value to a signed 16 digit decimal number; processing the data precision of the 16-digit decimal number with the symbol according to the corresponding configuration information to obtain analysis data;
the U16Bit enumeration strategy specifically comprises the following steps: acquiring a third address difference, and acquiring a corresponding third original value in the original data based on the third address difference; converting the third raw value to an unsigned 16 decimal number; acquiring Bit bits corresponding to 16 decimal numbers without symbols in the corresponding configuration information; converting the Bit into a corresponding 10-system number; formatting the 10-system number based on preset formatting configuration to obtain analytic data;
the S32 enumeration policy specifically includes: acquiring a fourth address difference, and acquiring a corresponding high-order original value and a corresponding low-order original value in original data based on the fourth address difference; converting the high-order original value and the low-order original value into 32-bit binary numbers based on a mode of combining binary high 16 bits with binary low 16 bits; converting 32-bit binary number into 10-system number with symbols to obtain analytic data;
AbsS16 enumerates a policy, which specifically includes: acquiring a fifth address difference, and acquiring a corresponding fifth original value in the original data based on the fifth address difference; converting the fifth raw value to a signed 16 digit decimal number; processing the data precision of the 16-digit decimal number with the symbol according to the corresponding configuration information to obtain precision data; taking an absolute value of the precision data to obtain analytic data;
the U16BitDouble enumeration policy specifically includes: acquiring a sixth address difference, and acquiring a sixth original value corresponding to the original data based on the sixth address difference; converting the sixth original value to an unsigned 16 decimal number; acquiring a plurality of Bit bits corresponding to 16 decimal numbers without symbols in the corresponding configuration information; converting a plurality of Bit bits into corresponding 10-system numbers; and formatting the 10-system number based on preset formatting configuration to obtain analysis data.
In one embodiment, after obtaining the operation data of the current user equipment, the method further includes:
selecting a proper monitoring node according to the node matching degree of the current user equipment, applying an abnormal data judgment request to the data center, and providing the operation data of the current user equipment to the data center;
after receiving the application and agreeing, the data center selects corresponding types of historical operating data, historical operating data abnormal judgment results, models and model convergence conditions according to the types of the monitoring nodes;
training the model based on the historical operating data, the historical operating data abnormal judgment result and the model convergence condition until the result is converged to obtain an abnormal data judgment model;
inputting the operation data into an abnormal data judgment model to obtain an abnormal judgment result;
if the abnormal judgment result is data abnormality, returning a data abnormality result through the monitoring node;
performing exception marking on the running data corresponding to the current user equipment;
the working principle of the technical scheme is as follows: after the operation data of the current user equipment is obtained, at intervals, the terminal selects a proper monitoring node according to the node matching degree of the user equipment corresponding to the current operation data, applies an abnormal data judgment request to the data center and provides the operation data of the current user equipment to the data center, wherein the data center is laid in advance; after the data center receives the application and agrees, selecting corresponding types of historical operating data, historical operating data abnormal judgment results, models and model convergence conditions according to the types of the monitoring nodes, wherein the historical operating data only intercepts operating data within preset time, and trains the models based on the historical operating data, the historical operating data abnormal judgment results and the model convergence conditions until the results are converged to obtain abnormal data judgment models; preferably, each abnormal data judgment model is newly trained, the old model is discarded after the newly trained model is generated, the judgment precision is favorably improved, after the model is obtained, the operation data is input into the abnormal data judgment model to obtain an abnormal judgment result, and if the abnormal judgment result is data abnormality, the abnormal data judgment result is returned through the monitoring node; performing exception marking on the running data corresponding to the current user equipment; simultaneously carrying out abnormity marking on the displayed current operation data and sending out a first alarm signal;
the beneficial effects of the above technical scheme are: in the current hydropower station safety monitoring automation system re-operation process, the early warning threshold value or the early warning range of corresponding monitoring parameters are mostly fixedly set, once the early warning threshold value or the early warning range is exceeded, early warning information is sent out, the early warning mode too depends on the early warning threshold value or the early warning range defined manually, and the early warning mode is not perfectly suitable for the early warning judgment of each monitoring point device.
In one embodiment, selecting an appropriate monitoring node according to the node matching degree of the current user equipment includes:
node numbering is carried out on each monitoring node in advance to obtain unique first numbering information;
acquiring second serial number information of the current user equipment; wherein the second number information includes: the device type number, the device area number and the device use number;
judging whether first number information which is completely the same as the second number information exists in all the monitoring nodes;
if the current user equipment exists, obtaining a first monitoring node, and using the first monitoring node as a monitoring node of the current user equipment;
if not, removing any number in the second number information based on a preset first importance screening rule to obtain third number information;
judging whether first number information containing third number information exists in all monitoring nodes or not;
if the current user equipment exists, obtaining a second monitoring node, and using the second monitoring node as the monitoring node of the current user equipment;
if the number does not exist, removing any number in the third number information based on a preset second importance degree screening rule to obtain fourth number information;
judging whether first number information containing fourth number information exists in all monitoring nodes or not;
if the current user equipment exists, obtaining a third monitoring node, and taking the third monitoring node as the monitoring node of the current user equipment;
if not, sending an abnormal judgment failure signal;
when the number of the second monitoring nodes or the third monitoring nodes is multiple, one second monitoring node or one third monitoring node is selected as the monitoring node of the current user equipment;
the working principle of the technical scheme is as follows: node numbering is carried out on each monitoring node in advance to obtain unique first numbering information; acquiring second serial number information of the current user equipment; wherein the second number information includes: the device type number, the device area number and the device use number; furthermore, the second numbering information can be expanded to improve the accuracy of node matching; judging whether first number information which is completely the same as the second number information exists in all the monitoring nodes; if the current user equipment exists, obtaining a first monitoring node, and using the first monitoring node as a monitoring node of the current user equipment; in the initial stage of data center setup, a first monitoring node matched with all user equipment is generally established; if not, removing any number in the second number information based on a preset first importance screening rule to obtain third number information; presetting a first importance degree screening rule, preferably judging the removed number type according to the actual situation; judging whether first number information containing third number information exists in all monitoring nodes or not; if the current user equipment exists, obtaining a second monitoring node, and using the second monitoring node as the monitoring node of the current user equipment; when the second monitoring node is generally adopted, the types of equipment representing the hydropower station are increased; if the number does not exist, removing any number in the third number information based on a preset second importance degree screening rule to obtain fourth number information; the preset second importance degree screening rule is preferably not repeated with the preset first importance degree screening rule; judging whether first number information containing fourth number information exists in all monitoring nodes or not; if the current user equipment exists, obtaining a third monitoring node, and taking the third monitoring node as the monitoring node of the current user equipment; when a third monitoring node is generally used, the equipment representing the hydropower station is changed into one through major changeStep one, sending request information for updating the monitoring node to a user; if the node information does not exist, sending an abnormal judgment failure signal, and applying for updating the monitoring node information; when the number of the second monitoring nodes or the third monitoring nodes is multiple, one second monitoring node or one third monitoring node is selected as the monitoring node of the current user equipment; furthermore, if the first monitoring node is not obtained and there are a plurality of second monitoring nodes or third monitoring nodes, the second monitoring node or the third monitoring node may be determined by a node trust degree calculation formula, wherein the node trust degree formula is preferably: trust i ＝α*self i +β*public i Wherein, Trust i For the node confidence of the ith monitoring node, alpha and beta are preset weighted values, beta + alpha is 1, self i Number of times, public, that the ith monitoring node was selected as the second monitoring node or the third monitoring node for the current device i The number of times that the ith monitoring node was selected as the second monitoring node or the third monitoring node for the other devices; selecting a monitoring node with the maximum node trust degree as a second monitoring node or a third monitoring node of the current user equipment, wherein the selected monitoring node can be selected only when the selected monitoring node is not in use;
the beneficial effects of the above technical scheme are: through the scheme, the appropriate monitoring nodes are quickly determined, if each monitoring device is provided with an independent path to transmit data to the data center for judgment, the data center needs to acquire corresponding information according to the type of each monitoring device to establish an abnormal data judgment model, when the number of the monitoring devices is increased, the data calculation resource consumption of the data center is increased, and the monitoring nodes are beneficial to reducing the data calculation resource consumption of the data center.
In one embodiment, a method for hydropower station monitoring data conversion display further comprises:
when the abnormal judgment result is data abnormal, the data center acquires second operation data of the user equipment with all the node matching degrees matched with the current monitoring node based on the current monitoring node; wherein the second operation data carries a unique device tag;
inputting all the second operation data into an abnormal data judgment model respectively, and outputting a plurality of abnormal judgment results carrying unique marks;
acquiring third operation data with abnormal data judgment results in the second operation data;
acquiring second original data of the user equipment corresponding to the third operation data;
classifying the second original data based on the type of the preset monitoring data to obtain a second original data set; each data in the second original data set carries a monitoring data type;
collecting all monitoring data types carried in the second original data set, and establishing a common monitoring data type set;
acquiring abnormal information of a monitoring device matched with the monitoring data type in the common monitoring data type set; wherein the exception information includes: abnormal reasons in the monitoring period, abnormal data corresponding to the abnormal reasons, historical monitoring data and abnormal judgment results corresponding to the historical monitoring data;
establishing a plurality of anomaly analysis and diagnosis models respectively according to the anomaly information of each monitoring device;
respectively inputting all the second original data set data into corresponding anomaly analysis and diagnosis models to obtain a plurality of anomaly analysis and diagnosis results;
respectively judging whether the abnormal analysis diagnosis result exists in each second original data set or not as data with abnormal data;
classifying all second original data sets with data abnormality according to the monitoring data types of the abnormal data to obtain a plurality of third original data sets; the third original data set comprises a plurality of second original data sets of which abnormal data are of the same monitoring data type;
judging whether the number of the second original data sets in each third original data set exceeds a preset large-area abnormal number threshold of equipment or not based on a preset large-area abnormal rule of the equipment;
if the number of the second original data sets exceeds the preset large-area abnormal number threshold value, taking the third original data set with the number of the second original data sets exceeding the preset large-area abnormal number threshold value as a fourth original data set;
determining a monitoring device with large-area equipment abnormity as a first abnormity monitoring device based on the corresponding monitoring data type in the fourth original data set;
determining first abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set;
sending large-area same-equipment abnormal alarm information, carrying out large-area same-equipment abnormal marking on second operation data corresponding to the fourth original data set, and displaying a first abnormal monitoring device and first abnormal user equipment;
if the number of the second original data sets does not exceed the preset large-area abnormal number threshold value, taking a third original data set of which the number of the second original data sets does not exceed the preset large-area abnormal number threshold value as a fifth original data set;
determining a second abnormal monitoring device with abnormality based on the corresponding monitoring data type in the fifth original data set;
determining second abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set;
sending equipment abnormality alarm information, carrying out abnormality marking on second operation data corresponding to the fifth original data set, and displaying a second abnormality monitoring device and second abnormal user equipment;
the working principle of the technical scheme is as follows: when the abnormal judgment result of a certain device is data abnormality, the data center acquires second operation data of the user equipment with all the node matching degrees matched with the current monitoring node based on the current monitoring node; then all the second operation data are respectively input into an abnormal data judgment model, and a plurality of abnormal judgment results carrying unique marks are output; acquiring third operation data with abnormal data judgment results in the second operation data; acquiring second original data of the user equipment corresponding to the third operation data; classifying the second original data based on the type of the preset monitoring data to obtain a second original data set; the preset monitoring data types include, but are not limited to, a unit voltage data type, a unit current data type, a guide vane opening data type, an excitation current data type, a unit rotating speed data type and the like; each data in the second original data set carries a monitoring data type; collecting all monitoring data types carried in the second original data set, and establishing a common monitoring data type set; acquiring abnormal information of a monitoring device matched with the monitoring data type in the common monitoring data type set; wherein the exception information includes: abnormal reasons in the monitoring period, abnormal data corresponding to the abnormal reasons, historical monitoring data and abnormal judgment results corresponding to the historical monitoring data; establishing a plurality of anomaly analysis and diagnosis models respectively according to the anomaly information of each monitoring device; respectively inputting all the second original data set data into corresponding anomaly analysis and diagnosis models to obtain a plurality of anomaly analysis and diagnosis results; respectively judging whether the abnormal analysis diagnosis result exists in each second original data set or not as data with abnormal data; classifying all second original data sets with data abnormality according to the monitoring data types of the abnormal data to obtain a plurality of third original data sets; the third original data set comprises a plurality of second original data sets of which abnormal data are of the same monitoring data type; judging whether the number of the second original data sets in each third original data set exceeds a preset large-area abnormal number threshold of equipment or not based on a preset large-area abnormal rule of the equipment; if the number of the second original data sets exceeds the preset large-area abnormal number threshold value, taking the third original data set with the number of the second original data sets exceeding the preset large-area abnormal number threshold value as a fourth original data set; determining a monitoring device with large-area equipment abnormity as a first abnormity monitoring device based on the corresponding monitoring data type in the fourth original data set; determining first abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set; sending large-area same-equipment abnormal alarm information, carrying out large-area same-equipment abnormal marking on second operation data corresponding to the fourth original data set, and displaying a first abnormal monitoring device and first abnormal user equipment; if the number of the second original data sets does not exceed the preset large-area abnormal number threshold value, taking a third original data set of which the number of the second original data sets does not exceed the preset large-area abnormal number threshold value as a fifth original data set; determining a second abnormal monitoring device with abnormality based on the corresponding monitoring data type in the fifth original data set; determining second abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set; sending equipment abnormality alarm information, carrying out abnormality marking on second operation data corresponding to the fifth original data set, and displaying a second abnormality monitoring device and second abnormal user equipment; furthermore, all second original data sets without data abnormality are used as sixth original data sets, second abnormality information of monitoring devices corresponding to other monitoring data types except the monitoring data type in the common monitoring data type set in the sixth original data sets is obtained, a plurality of second abnormality analysis and diagnosis models are established, and then a third monitoring device and third different common user equipment with abnormality are detected and displayed in the same mode;
the beneficial effects of the above technical scheme are: when the early warning information exists, monitoring personnel are generally allocated to carry out troubleshooting and analysis on related equipment according to the early warning information, however, the method only carries out troubleshooting on single equipment, cannot well play the troubleshooting effect of global control, and the abnormal phenomenon of the equipment is often multiple and concurrent, the mode of troubleshooting a single device needs to be performed by manual unified analysis after all troubleshooting work is finished to determine whether the large-area device is abnormal or not, and the problem of low efficiency exists, when a certain device has an abnormality, based on the preset type of the device, comprehensively checking whether all the devices of the same type have the abnormality, related equipment with the large-area equipment abnormity problem is rapidly determined, and workers can be assisted to rapidly make related judgment on the abnormity globally, so that the abnormity processing efficiency is improved.
A system for hydropower station monitoring data conversion demonstration, comprising:
the front-end module is used for acquiring user demand information and reading corresponding configuration information based on the demand information;
the first assembly module is used for assembling all the configuration information based on a preset first assembly rule to obtain a configuration item;
the back end module is used for determining the original data of the user equipment according to the configuration items; analyzing the original data based on the enumeration strategy and the configuration information to obtain analyzed data;
the second assembly module is used for assembling the analysis data based on a preset second assembly rule to obtain operation data;
the front-end module is also used for respectively displaying the operation data and the configuration items.
The working principle and the beneficial effect of different internal functional modules in the system for displaying the hydropower station monitoring data conversion can refer to the working principle and the beneficial effect correspondingly mentioned in the method for displaying the hydropower station monitoring data conversion, and repeated description is not repeated here.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A method for displaying monitoring data conversion of a hydropower station is characterized by comprising the following steps:
acquiring user demand information, and reading corresponding configuration information based on the demand information;
assembling all the configuration information based on a preset first assembly rule to obtain configuration items;
displaying the configuration items;
determining original data of the user equipment according to the configuration items; analyzing the original data based on an enumeration strategy and the configuration information to obtain analyzed data;
assembling the analysis data based on a preset second assembly rule to obtain operation data;
and displaying the operating data.
2. The method for hydropower station monitoring data conversion demonstration according to claim 1, wherein the determination of the configuration information comprises:
obtaining the dimensionality of the power station;
determining configuration information according to the dimensionality of the power station based on a preset configuration rule; the configuration information comprises any one or combination of a monitoring point name, a monitoring point code, a reading address, a writing address, a data type and data precision.
3. The method for the conversion and display of hydropower station monitoring data according to claim 1, wherein the type of the configuration item comprises any one of a function page type, a specific monitoring point type and a power station type.
4. The method for hydropower station monitoring data conversion display according to claim 1, wherein the determining raw data of the user equipment according to the configuration item comprises:
based on a preset third assembly rule, intelligently assembling request parameters of the original data of the batch query equipment according to the configuration items;
and acquiring the original data of the user equipment in batch according to the request parameters.
5. The method of claim 1, wherein the parsing the raw data based on the enumeration strategy and the configuration information to obtain parsed data comprises:
circulating all the configuration information, and determining a corresponding enumeration strategy according to the operation type in the configuration information;
and correspondingly analyzing the original data based on the corresponding enumeration strategy to obtain analyzed data.
6. The method of claim 5, wherein the enumeration strategy comprises: any one of a Bit enumeration strategy, an S16 enumeration strategy, a U16Bit enumeration strategy, an S32 enumeration strategy, an AbsS16 enumeration strategy and a U16Bitdouble enumeration strategy;
the Bit enumeration strategy specifically includes: acquiring a first address difference, and acquiring a corresponding first original value in the original data based on the first address difference; formatting the first original value based on a preset formatting configuration to obtain analysis data;
the S16 enumeration policy specifically includes: acquiring a second address difference, and acquiring a corresponding second original value in the original data based on the second address difference; converting the second original value to a signed 16 digit decimal number; processing the data precision of the 16-digit decimal number with the symbol according to the corresponding configuration information to obtain analysis data;
the U16Bit enumeration strategy specifically includes: acquiring a third address difference, and acquiring a corresponding third original value in the original data based on the third address difference; converting the third raw value to an unsigned 16 decimal number; acquiring Bit bits corresponding to the 16-digit decimal number without symbols in the configuration information; converting the Bit into a corresponding 10-system number; formatting the 10-system number based on preset formatting configuration to obtain analytic data;
the S32 enumeration policy specifically includes: acquiring a fourth address difference, and acquiring a corresponding high-order original value and a corresponding low-order original value in the original data based on the fourth address difference; converting the high-order original value and the low-order original value into 32-bit binary numbers based on a binary high-order 16-bit combined binary low-order 16-bit mode; converting the 32-bit binary number into a 10-system number with symbols to obtain analytic data;
the AbsS16 enumeration policy specifically includes: acquiring a fifth address difference, and acquiring a fifth original value corresponding to the original data based on the fifth address difference; converting the fifth raw value to a signed 16 digit decimal number; processing the data precision of the 16-digit decimal number with the symbol according to the corresponding configuration information to obtain precision data; obtaining an absolute value of the precision data to obtain analytic data;
the U16BitDouble enumeration policy specifically includes: acquiring a sixth address difference, and acquiring a corresponding sixth original value in the original data based on the sixth address difference; converting the sixth original value to an unsigned 16 decimal; obtaining a plurality of Bit bits corresponding to the unsigned 16 decimal number in the configuration information; converting a plurality of the Bit bits into corresponding 10-system numbers; and formatting the 10-system number based on preset formatting configuration to obtain analysis data.
7. The method for hydropower station monitoring data conversion display according to claim 1, wherein after obtaining the operation data of the current user equipment, the method further comprises:
selecting a proper monitoring node according to the node matching degree of the current user equipment, applying an abnormal data judgment request to a data center, and providing the operation data of the current user equipment to the data center;
after receiving the application and agreeing, the data center selects corresponding types of historical operating data, historical operating data abnormal judgment results, models and model convergence conditions according to the types of the monitoring nodes;
training the model based on the historical operating data, the historical operating data abnormal judgment result and the model convergence condition until the result is converged to obtain an abnormal data judgment model;
inputting the operating data into the abnormal data judgment model to obtain an abnormal judgment result;
if the abnormal judgment result is data abnormal, returning a data abnormal result through the monitoring node;
and carrying out exception marking on the operation data corresponding to the current user equipment.
8. The method for performing conversion display on hydropower station monitoring data according to claim 7, wherein the selecting a suitable monitoring node according to the node matching degree of the current user equipment comprises:
node numbering is carried out on each monitoring node in advance to obtain unique first numbering information;
acquiring second serial number information of the current user equipment; wherein the second number information includes: the device type number, the device area number and the device use number;
judging whether first number information which is completely the same as the second number information exists in all monitoring nodes or not;
if the current user equipment exists, obtaining a first monitoring node, and using the first monitoring node as a monitoring node of the current user equipment;
if not, removing any number in the second number information based on a preset first importance screening rule to obtain third number information;
judging whether first number information containing the third number information exists in all monitoring nodes or not;
if the current user equipment exists, obtaining a second monitoring node, and using the second monitoring node as the monitoring node of the current user equipment;
if the number does not exist, removing any number in the third number information based on a preset second importance degree screening rule to obtain fourth number information;
judging whether first number information containing the fourth number information exists in all monitoring nodes or not;
if the current user equipment exists, obtaining a third monitoring node, and using the third monitoring node as the monitoring node of the current user equipment;
if not, sending an abnormal judgment failure signal;
and when the number of the second monitoring nodes or the third monitoring nodes is multiple, optionally selecting one second monitoring node or one third monitoring node as the monitoring node of the current user equipment.
9. The method for hydropower station monitoring data conversion demonstration of claim 7, further comprising:
when the abnormal judgment result is data abnormal, the data center acquires second operation data of the user equipment with all the node matching degrees matched with the current monitoring node based on the current monitoring node; wherein the second operation data carries a unique device tag;
inputting all the second operation data into the abnormal data judgment model respectively, and outputting a plurality of abnormal judgment results carrying unique marks;
acquiring third operation data with abnormal data judgment results in the second operation data;
acquiring second original data of the user equipment corresponding to the third operation data;
classifying the second original data based on a preset monitoring data type to obtain a second original data set; each data in the second original data set carries a monitoring data type;
collecting all monitoring data types carried in the second original data set, and establishing a common monitoring data type set;
acquiring abnormal information of the monitoring device matched with the monitoring data type in the common monitoring data type set; wherein the anomaly information includes: abnormal reasons in a monitoring period, abnormal data corresponding to the abnormal reasons, historical monitoring data and abnormal judgment results corresponding to the historical monitoring data;
establishing a plurality of anomaly analysis and diagnosis models respectively according to the anomaly information of each monitoring device;
respectively inputting all the second original data set data into corresponding anomaly analysis and diagnosis models to obtain a plurality of anomaly analysis and diagnosis results;
respectively judging whether the second original data set has abnormal analysis and diagnosis results which are data abnormal;
classifying all second original data sets with data abnormality according to the monitoring data types of the abnormal data to obtain a plurality of third original data sets; the third original data set comprises a plurality of second original data sets of which abnormal data are of the same monitoring data type;
judging whether the number of the second original data sets in each third original data set exceeds a preset large-area abnormal number threshold of equipment or not based on a preset large-area abnormal rule of the equipment;
if the number of the second original data sets exceeds the preset large-area abnormal number threshold value, taking the third original data set with the number of the second original data sets exceeding the preset large-area abnormal number threshold value as a fourth original data set;
determining a monitoring device with large-area equipment abnormity as a first abnormity monitoring device based on the corresponding monitoring data type in the fourth original data set;
determining first abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set;
sending large-area same-equipment abnormal alarm information, performing large-area same-equipment abnormal marking on second operation data corresponding to the fourth original data set, and displaying the first abnormal monitoring device and the first abnormal user equipment;
if the number of the second original data sets does not exceed the preset large-area abnormal number threshold value, taking a third original data set of which the number of the second original data sets does not exceed the preset large-area abnormal number threshold value as a fifth original data set;
determining a second abnormal monitoring device with abnormality based on the corresponding monitoring data type in the fifth original data set;
determining second abnormal user equipment according to the unique equipment mark corresponding to the fourth original data set;
and sending equipment abnormity alarm information, carrying out abnormity marking on second operation data corresponding to the fifth original data set, and displaying the second abnormity monitoring device and the second abnormity user equipment.
10. A system for hydropower station monitoring data conversion display is characterized by comprising:
the front-end module is used for acquiring user demand information and reading corresponding configuration information based on the demand information;
the first assembly module is used for assembling all the configuration information based on a preset first assembly rule to obtain configuration items;
the back end module is used for determining the original data of the user equipment according to the configuration items; analyzing the original data based on an enumeration strategy and the configuration information to obtain analyzed data;
the second assembly module is used for assembling the analysis data based on a preset second assembly rule to obtain operation data;
the front-end module is further used for displaying the operation data and the configuration items respectively.
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