CN113837622A - Coal consumption data multidimensional drilling analysis method and device, storage medium and computing equipment - Google Patents
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Abstract
The invention relates to a coal consumption data multidimensional drilling analysis method, which comprises the following steps: establishing a coal consumption factor index model; acquiring coal consumption data in real time, and extracting and recording coal consumption factor indexes corresponding to the coal consumption data according to the coal consumption factor index model; and inquiring the coal consumption factor indexes, and presenting the corresponding obtained target factor indexes in a time axis form. And establishing a data drilling window corresponding to the target factor index, wherein the data drilling popup window is used for displaying the coal consumption factor index model corresponding to the current target factor index and/or formula factors contained in the coal consumption factor index model. Extracting and analyzing related coal consumption factor indexes according to the coal consumption factor index model by establishing the coal consumption factor index model; and then obtain the target factor index that operating personnel needed, solved present to carry out data analysis not directly perceived, data contrast inconvenient and the low problem of analysis efficiency to the coal consumption.
Description
Technical Field
The invention relates to the technical field of coal consumption analysis, in particular to a coal consumption data multidimensional drilling analysis method, a coal consumption data multidimensional drilling analysis device, a storage medium and computing equipment.
Background
The anti-balance power supply standard coal consumption rate is a main economic index of thermal power generation enterprises and also a main reference index of the thermal power generation enterprises for energy conservation and consumption reduction, and the coal consumption determines the economic benefit of the thermal power generation enterprises. In order to improve the economic benefit of power generation enterprises, the power generation enterprises increasingly pay more attention to the analysis of coal consumption indexes, so that main factors influencing the coal consumption are found out.
At present, various coal consumption data analysis methods exist, however, the methods are difficult to conveniently and quickly know the related index data conditions affecting coal consumption, and also difficult to quickly and conveniently perform trend analysis on historical data of specified factor indexes in each time period. Aiming at the technical problems of non-visual data, inconvenient data comparison and low analysis efficiency in the prior art, an effective solution is not provided at present.
Disclosure of Invention
Based on this, it is necessary to provide a coal consumption data multidimensional drilling analysis method, device, storage medium and computing device, aiming at the problems of non-intuitive data analysis, inconvenient data comparison and low analysis efficiency of the existing coal consumption data analysis.
A coal consumption data multidimensional drilling analysis method comprises the following steps:
establishing a coal consumption factor index model;
acquiring coal consumption data in real time, and extracting and recording coal consumption factor indexes corresponding to the coal consumption data according to the coal consumption factor index model;
and inquiring the coal consumption factor indexes, and presenting the corresponding obtained target factor indexes in a time axis form.
And establishing a data drilling window corresponding to the target factor index, wherein the data drilling popup window is used for displaying the coal consumption factor index model corresponding to the current target factor index and/or formula factors contained in the coal consumption factor index model.
The coal consumption data multidimensional drilling analysis method disclosed by the embodiment of the invention can be used for extracting and analyzing related coal consumption factor indexes by establishing the coal consumption factor index model according to the coal consumption factor index model; and then obtain the target factor index that operating personnel needed, solved present to carry out data analysis not directly perceived, data contrast inconvenient and the low problem of analysis efficiency to the coal consumption.
In one preferred embodiment, the method further comprises:
judging whether the formula factors comprise measuring point data or not,
if the data of the measuring points are included, measuring point codes corresponding to the data of the measuring points are displayed;
and if the measured point data is not included, further displaying the coal consumption factor index model corresponding to the current formula factor and/or a next-level coal consumption factor index model and a corresponding formula factor contained in the coal consumption factor index model through drilling a pop-up window.
In one preferred embodiment, the method further comprises:
and classifying the coal consumption factor indexes to present the coal consumption factor indexes in a classified manner.
In the above embodiment, the factor indicators are classified, so that the historical data corresponding to the factor indicators can also be classified and presented.
In one preferred embodiment, the types of the coal consumption factor indicators are classified into a unit performance indicator, a steam turbine performance indicator, a heater performance indicator, a condenser performance indicator, an air preheater performance indicator, a boiler performance indicator, a deviation influence coal consumption indicator, an auxiliary unit consumption indicator, and an auxiliary power consumption indicator.
In one preferred embodiment, the querying the target factor indicator and presenting the target factor indicator in the form of a time axis includes:
creating a graphical display interface corresponding to the target factor index;
according to the input instruction, inquiring the coal consumption factor index to obtain a target factor index;
and in the graphical display interface, presenting the target factor indexes in a time axis grading way.
In this embodiment, the real-time data of the coal consumption factor indicators displayed on the interfaces such as the classification list, the schematic diagram and the like in the method may have corresponding hyperlinks, and a pop-up data drill window may be clicked and may display a recent past one-hour historical trend of the current indicator.
In one preferred embodiment, the presenting of the target factor indicators in a timeline hierarchy includes:
taking the moment of acquiring the coal consumption data as a time node for acquiring the corresponding target factor index;
and the target factor indexes are presented in a grading way according to the recorded time nodes from low to high in units of one or more of minutes, hours, class values, days, weeks, months, quarters or years.
The time dimension in the present embodiment includes, but is not limited to, minutes, half-hours, shift values, days, weeks, months, seasons, years, and the like, and a part or all of the time dimension is used as necessary.
In one preferred embodiment, the presenting of the target factor indicators in a timeline hierarchy includes:
acquiring the current time unit level presented by the current target factor index;
and inquiring and presenting the target factor indexes of a time unit level lower than the current time unit level according to the current time unit level information.
In the above embodiment, the time periods of the time axis may be displayed in a hierarchical manner according to the requirements of the actual usage scenario, so that when the time period of the current level is displayed, the more detailed historical data of the target factor index of the corresponding time period of the next level is displayed according to the requirements, which is convenient for the user to analyze the historical data.
In one preferred embodiment, the method further comprises:
and summarizing the obtained target factor indexes, wherein the summarizing mode comprises accumulation, difference, average and/or weighted average.
In this embodiment, the method may further summarize historical data related to the target factor index, and include various analysis manners such as accumulation, interpolation, averaging, and/or weighted averaging of the historical data, where the weighted average index includes, but is not limited to, a unit load, a main steam flow, and a boiler coal combustion amount.
A coal consumption data multidimensional drilling analysis system comprises:
the modeling module is used for establishing a coal consumption factor index model;
the factor index extraction module is used for acquiring coal consumption data in real time, and extracting and recording coal consumption factor indexes corresponding to the coal consumption data according to the coal consumption factor index model;
the data presentation module is used for inquiring the coal consumption factor indexes and presenting the corresponding obtained target factor indexes in a time axis form;
and the data drilling module is used for establishing a data drilling window corresponding to the target factor index, and the data drilling popup window is used for displaying the coal consumption factor index model corresponding to the current target factor index and/or formula factors contained in the coal consumption factor index model.
The coal consumption data multidimensional drilling analysis method disclosed by the embodiment of the invention can be used for extracting the factor indexes related to the analysis of the coal consumption according to the coal consumption factor index model by establishing the coal consumption factor index model; and then obtain coal-fired unit real-time and historical operating data, solved current to the coal consumption carry on the data analysis not directly perceived, the data contrast is inconvenient and the analysis inefficiency problem.
A storage medium, comprising a stored program, wherein an apparatus on which the storage medium is located is controlled to perform the method described above when the program is run.
The storage medium disclosed by the above embodiment of the invention utilizes a coal consumption data multidimensional drilling analysis method, and can extract factor indexes related to analysis of coal consumption according to a coal consumption factor index model by establishing the coal consumption factor index model; and then obtain coal-fired unit real-time and historical operating data, solved current to the coal consumption carry on the data analysis not directly perceived, the data contrast is inconvenient and the analysis inefficiency problem.
A computing device comprising a processor, wherein the processor is configured to execute a program, wherein the program when executed performs the method described above.
The computing equipment disclosed by the embodiment of the invention utilizes a coal consumption data multidimensional drilling analysis method, can extract the factor indexes related to the analysis of coal consumption according to the coal consumption factor index model by establishing the coal consumption factor index model; and then obtain coal-fired unit real-time and historical operating data, solved current to the coal consumption carry on the data analysis not directly perceived, the data contrast is inconvenient and the analysis inefficiency problem.
Drawings
FIG. 1 is a schematic flow chart of a multidimensional drilling analysis method for coal consumption data according to a preferred embodiment of the present invention;
fig. 2 is a schematic block diagram of a coal consumption data multidimensional drilling analysis system according to a preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that when an element is referred to as being "disposed on" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not represent the only embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
As shown in fig. 1, a preferred embodiment of the present invention discloses a coal consumption data multidimensional drilling analysis method, which includes:
s10: establishing a coal consumption factor index model;
in this step, a coal consumption factor index model is established, which can be obtained according to the current coal consumption and the operation data of the unit as follows. In this embodiment, the factor index model includes a factor index formula. The factor index formula can establish the following operation model of the current coal consumption, the operation data of the unit and the following coal consumption factor index, and the factor index formula comprises at least one formula factor.
S20: and acquiring coal consumption data in real time, and extracting and recording the coal consumption factor indexes corresponding to the coal consumption data according to the coal consumption factor index model.
In this step, the coal consumption data is obtained in real time in the step S20, and according to the coal consumption factor index model, the factor index formula of the factor index model may be specifically used, so that the corresponding coal consumption factor index may be extracted, and the obtained coal consumption factor index may be stored and recorded.
In this embodiment, the step S20 of the method may further include classifying the coal consumption factor index, so as to present the target factor index in a classified manner.
Specifically, the classifying the factor indicators may include: the method comprises the following steps of generating set performance index, steam turbine performance index, heater performance index, condenser performance index, air preheater performance index, boiler performance index, deviation influence coal consumption index, auxiliary unit power consumption index and the like. Therefore, the historical data of the corresponding factor indexes can be classified and presented.
S30: and inquiring the coal consumption factor indexes, and presenting the corresponding target factor indexes in a time axis form.
The target factor indexes are presented in the form of the historical time axis in the form of the time axis, so that the historical trend of each coal consumption factor index is favorably analyzed, and the visual analysis of relevant factors influencing the coal consumption is facilitated.
Specifically, in this step, the step S30 of the method may further include the following subdivision processes:
s31: creating a graphical display interface corresponding to the target factor index;
s32: according to the input instruction, inquiring the coal consumption factor index to obtain a target factor index;
s33: and in the graphical display interface, presenting the target factor indexes in a time axis grading way.
In this embodiment, a graphical interface corresponding to the target factor indicator is created in the above step, specifically, the graphical interface may be a linear trend graph, a bar graph, or the like, and besides, a classification list may be presented on one side of the graphical interface for each classification of the coal consumption factor indicators, and the classification list may be presented and recorded in real time. The graphical interface can display the real-time data related to the coal consumption factor indexes in the forms of a classification list or a schematic diagram and the like.
In more detail, the target factor indicators of the upper pair of records are presented in a timeline hierarchy, including:
the data display units of the target factor indexes are presented in a grading mode from low to high in one or more of minutes, hours, shift values, days, weeks, months, quarters or years.
The time dimension in the present embodiment includes, but is not limited to, minutes, half-hours, shift values, days, weeks, months, seasons, years, and the like, and a part or all of the time dimension of an event is used as necessary.
When the time unit dimension is 'year' as a unit, the time period is 1 month to 12 months of the year; when the time unit dimension is 'season' as a unit, the time period is from the first month to the last month of the season; when the time unit dimension is 'month' as a unit, the time period is from 1 day to the last day of the month; when the time unit dimension is 'day', the time period is from 0 point to 23 points of the day, 59 minutes and 59 seconds; when the time unit dimension is 'duty value' as a unit, the time period is from the starting time to the ending time of the duty value; the time unit dimension is "hours" as the unit, and the time period is from 0 minutes to 59 minutes and 59 seconds of that hour. The method can further inquire out the historical data list according to the time category, the time period, the ID data group and the like.
In more detail, the target factor indicators are presented in a timeline hierarchy, including:
acquiring the current time unit level presented by the current target factor index;
and inquiring and presenting the target factor indexes of a time unit level lower than the current time unit level according to the current time unit level information.
In the above embodiment, the time period of the time axis may be displayed in stages according to the requirement of the actual usage scenario, for example, the current historical data displaying the corresponding coal consumption factor index is displayed in a unit level of "day", and when the operator inputs an instruction corresponding to a certain day by clicking or the like according to the requirement, the historical data displaying the coal consumption factor index in a unit of the next level of the certain day, for example, is displayed in a unit of "shift value" or "hour". Therefore, when the time period of the current level is displayed, more detailed historical data of the corresponding time period of the next level can be displayed according to requirements, and a user can conveniently analyze the historical data.
The historical data list can also inquire the historical data of the coal consumption factor indexes according to time dimensions such as minutes, hours, shift values, days, weeks, months, seasons, years and the like, the first of the inquiry list is time, and the time values above minutes can be clicked to inquire the next-stage time dimension data.
The data drilling of the time dimension can quickly inquire and analyze the data condition of each calculation factor index of the current data, and the data drilling of the time dimension can quickly inquire and analyze the data condition of a certain time period or a certain moment.
S40: and establishing a data drilling window corresponding to the target factor index, wherein the data drilling popup window is used for displaying the coal consumption factor index model corresponding to the current target factor index and/or formula factors contained in the coal consumption factor index model.
In this step, the data drilling window is established to display the coal consumption factor index model and the formula factors contained in the coal consumption factor index model, and meanwhile, the historical trend of the current index in the latest hour can be checked, and the time period of the historical trend can be changed.
The above formula factor is a coal consumption factor index represented in the above coal consumption factor index model, for example: the formula included in the coal consumption factor index model is a ═ a + b, a is the coal consumption factor index, and a and b are the formula factors of the formula, which is also one of the formula factors for representing the coal consumption factor index.
Specifically, in step S40, the method further includes:
judging whether the formula factors comprise measuring point data or not, and if so, displaying measuring point codes corresponding to the measuring point data; and if the measured point data is not included, further displaying the coal consumption factor index model corresponding to the current formula factor and/or a next-stage coal consumption factor index model and a corresponding formula factor contained in the coal consumption factor index model through drilling a pop-up window.
In this embodiment, the real-time data of the index displayed by the interface such as the classification list, the schematic diagram and the like in the method has a hyperlink, and a pop-up data drilling window can be clicked, the pop-up window displays the real-time data of the calculation formula and the formula factor list, the formula factor real-time data can be popped up according to the continuous clicking operation of an operator and the like, the real-time data of the next-stage calculation formula of the data and the real-time data of the formula factor list are displayed, and the like, until the real-time data of the last-stage formula factor list is the measured point data, the measured point code is displayed, and the information such as the measured position, the measured time and the like of the data can be obtained through the measured point code.
When the coal consumption factor index model comprises a plurality of formula factor indexes, the formula factor indexes can be displayed in the form of a list and the like. If the formula factor index list data has obvious abnormal data, the index data can be drilled and viewed preferentially. And the operator closes the current drilling window and can return the real-time data of the previous-stage calculation formula and the formula factor list.
If the formula factor index is displayed in a list form, the method further includes a corresponding relationship table of variable names and index names.
For example, the index variable name formula is "ab + abc + abcd", and the correspondence between the variable name and the index name is as follows:
| name of variable | Index name |
| ab | Index 1 |
| abcd | Index 2 |
| abc | Index 3 |
The list is sorted by variable name length in reverse order, as follows:
| name of variable | Index name |
| abcd | Index 2 |
| abc | Index 3 |
| ab | Index 1 |
And traversing the list, and replacing variable names in the formula with index names line by line. For example, the formula after the first row replacement is 'ab + abc + index 2', the formula after the second row replacement is 'ab + index 3+ index 2', the formula after the third row replacement is 'index 1+ index 3+ index 2', and the formula is the final Chinese character name description formula.
The pop-up window displays the data of the calculation formula and the formula factor list, has a function of adding and comparing, and can add the indexes and other optional indexes in the data list in the pop-up window into the current historical data query list.
In the present embodiment, the formula factor list is an index list required for calculating the target index. Each index row corresponds to an ID, and the rows can be traversed to form an index ID array. The first column of the historical data list is a time column, and the other columns take the index name as a column name and display the historical data value of each coal consumption factor index in a time period. The number of columns is changeable, each coal consumption factor index corresponds to an ID, and the index columns are displayed according to the ID array.
An operator can click the name (column name) of the index in the formula factor list, and a pop-up window displays the coal consumption factor index model of the index and the formula factor index list. Clicking a 'join contrast' button in the popup, traversing a formula factor index list to obtain an index ID array, automatically closing the popup, combining the obtained index ID array with the existing index ID array in the historical data list, removing repeated IDs to form a new index ID array, and displaying an index column and historical data according to the new index ID array.
By comparing historical data of the associated indexes, specific time and specific indexes of abnormal data can be conveniently searched.
The method can also comprise the following steps: and summarizing the obtained target factor indexes, wherein the summarizing mode comprises accumulation, difference, average and/or weighted average.
In this embodiment, the method may further summarize historical data corresponding to the target factor index, and include various analysis manners such as accumulation, interpolation, averaging, and/or weighted averaging of the historical data, where the weighted average index includes, but is not limited to, unit load, main steam flow, and boiler coal combustion amount.
In this embodiment, the weighted average indicator includes a unit load, a main steam flow, a boiler coal combustion amount, and the like. The time unit dimension includes minutes, half-hours, shift values, days, weeks, months, seasons, years, etc., and some or all of the time dimension is used as needed. The data summarization rule is that minute data is summarized into half-hour data or hour data, hour data is summarized into day data, hour data or half-hour data is summarized into shift value data, day data is summarized into week data and month data, and month data is summarized into season data and year data.
In the embodiment of the application, target factor indexes corresponding to the analyzed coal consumption factor indexes are extracted by establishing a coal consumption factor index model, and historical data of time dimensions such as minutes, hours, shift values, days, weeks, months, seasons, years and the like are extracted, calculated and summarized; the real-time data of the coal consumption factor indexes are displayed in the forms of graphical display interfaces, lists and the like, the data of the coal consumption factor indexes can be popped up in a data drilling window in a command mode of clicking in a hyperlink mode and the like, the data of the coal consumption factor indexes are displayed in the popping-up window, the real-time data of the coal consumption factor index models and the real-time data of the coal consumption factor indexes are analyzed, meanwhile, the recent historical trend of the current indexes can be checked, the formula factor real-time data can be continuously clicked to drill and inquired until the real-time data of the last-stage formula factor list are measured point data, and measured point codes are displayed. In the process, factor index operation data related to coal consumption is extracted, and factor extraction and multi-time-dimension grading data summarization of a related calculation formula are performed to realize data visualization and historical data layering in the coal consumption calculation process, so that a multi-dimension drilling analysis query method for the coal consumption data is realized, and a new, convenient and efficient analysis reference method is provided for power generation operators to perform coal consumption data deviation analysis. And further solve the problem that the data of the coal consumption analysis process in the prior art is not intuitive.
As shown in fig. 2, another preferred embodiment of the present invention discloses a coal consumption data multidimensional drilling analysis system 100, wherein the coal consumption data multidimensional drilling analysis system 100 includes a modeling module 110, a factor index extraction module 120, a historical data presentation module 130, and a data drilling module 140:
the modeling module 110 is used for establishing a coal consumption factor index model.
The modeling module 110 establishes a coal consumption factor index model, which can be obtained according to the current coal consumption and the operation data of the unit as follows. In this embodiment, the factor index model includes a factor index formula. The factor index formula can establish the following operation model of the current coal consumption, the operation data of the unit and the following coal consumption factor index, and the factor index formula comprises at least one formula factor.
The factor index extraction module 120 is configured to obtain coal consumption data and unit operation data of a coal-fired unit in real time, and extract and record factor indexes corresponding to the coal consumption data and the unit operation data according to the coal consumption factor index model;
the factor index extraction module 120 obtains the coal consumption data in real time, and according to the coal consumption factor index model, the factor index formula of the factor index model can be specifically used, so that the corresponding coal consumption factor index can be extracted, and the obtained coal consumption factor index is stored and recorded.
The factor index extracting module 120 may further include classifying the coal consumption factor index to present the target factor index in a classified manner.
Specifically, the classifying the factor indicators may include: the method comprises the following steps of generating set performance index, steam turbine performance index, heater performance index, condenser performance index, air preheater performance index, boiler performance index, deviation influence coal consumption index, auxiliary unit power consumption index and the like. Therefore, the historical data of the corresponding factor indexes can be classified and presented.
The historical data presentation module 130 queries the factor index according to the input instruction to obtain a target factor index, and presents the historical data corresponding to the target factor index in a time axis form.
The historical data presentation module 130 presents the coal consumption factor indexes in the form of a historical time axis in the form of a time axis, so that the historical trend of each coal consumption factor index is favorably analyzed, and the intuitive analysis of relevant factors influencing the coal consumption is facilitated.
The historical data presentation module 130 may further include an interface creation unit 131, an index query unit 132, and an index presentation unit 133.
The interface creating unit 131 is configured to create a graphical display interface corresponding to the coal consumption factor index;
the index query unit 132 is configured to query the coal consumption factor index according to the input instruction;
the indicator presenting unit 133 is configured to present the coal consumption factor indicators in a time axis hierarchy in the graphical display interface.
In this embodiment, the interface creating unit 131 creates a graphical interface corresponding to the target factor indicator, specifically, the graphical interface may be a linear trend graph, a bar graph, or the like, and besides, the graphical interface may also present a classification list on one side of the graphical interface for each classification of the coal consumption factor indicator, and the classification list may present and record the coal consumption factor indicator in real time. The graphical interface can display the real-time data of the indexes related to the coal consumption factor indexes in the forms of a classification list or a schematic diagram and the like.
The indicator presenting unit 133 is configured to present the coal consumption factor indicators in a time axis hierarchy in the graphical display interface. In more detail, the recorded coal consumption factor indexes are presented in a time axis grading mode, and the method comprises the following steps:
the coal consumption factor indexes are presented in grades from low to high in one or more of minutes, hours, shift values, days, weeks, months, quarters or years.
The time dimension in the present embodiment includes, but is not limited to, minutes, half-hours, shift values, days, weeks, months, seasons, years, and the like, and a part or all of the time dimension of an event is used as necessary.
When the time unit dimension is 'year' as a unit, the time period is 1 month to 12 months of the year; when the time unit dimension is 'season' as a unit, the time period is from the first month to the last month of the season; when the time unit dimension is 'month' as a unit, the time period is from 1 day to the last day of the month; when the time unit dimension is 'day', the time period is from 0 point to 23 points of the day, 59 minutes and 59 seconds; when the time unit dimension is 'duty value' as a unit, the time period is from the starting time to the ending time of the duty value; the time unit dimension is "hours" as the unit, and the time period is from 0 minutes to 59 minutes and 59 seconds of that hour. The method can further inquire out the historical data list according to the time category, the time period, the ID data group and the like.
In more detail, the index presenting unit 133 includes:
a time unit obtaining unit for obtaining a current time unit level presented by the current history data;
and the low-level unit query unit is used for querying and presenting the coal consumption factor index which is lower than the current time unit level by a time unit level according to the current time unit level information.
In the above embodiment, the time period of the time axis may be displayed in stages according to the requirement of the actual usage scenario, for example, the current historical data displaying the corresponding coal consumption factor index is displayed in a unit level of "day", and when the operator inputs an instruction corresponding to a certain day by clicking or the like according to the requirement, the historical data displaying the coal consumption factor index in a unit of the next level of the certain day, for example, is displayed in a unit of "shift value" or "hour". Therefore, when the time period of the current level is displayed, more detailed historical data of the corresponding time period of the next level can be displayed according to requirements, and a user can conveniently analyze the historical data.
The historical data list can also inquire the historical data of the coal consumption factor indexes according to time dimensions such as minutes, hours, shift values, days, weeks, months, seasons, years and the like, the first of the inquiry list is time, and the time values above minutes can be clicked to inquire the next-stage time dimension data.
The data drilling of the calculation dimension of the formula can quickly inquire and analyze the data condition of each calculation factor index of the current data, and the data drilling of the time dimension can quickly inquire and analyze the data condition of a certain time period or a certain moment.
The data drilling module 140 is configured to establish a data drilling window corresponding to the target factor indicator, where the data drilling popup is configured to display the coal consumption factor indicator model corresponding to the current target factor indicator and/or a formula factor included in the coal consumption factor indicator model.
The data drilling module 140 is configured to display the coal consumption factor index model and the formula factors included in the coal consumption factor index model by establishing a data drilling window, and meanwhile, the historical trend of the current index in the last hour can be checked, and the historical trend time period can be changed.
Specifically, the data drilling module 140 further includes:
the judging unit is used for judging whether the formula factors comprise measuring point data or not, and if the formula factors comprise the measuring point data, displaying measuring point codes corresponding to the measuring point data; and if the measured point data is not included, further displaying the coal consumption factor index model corresponding to the current formula factor and/or a next-stage coal consumption factor index model and a corresponding formula factor contained in the coal consumption factor index model through drilling a pop-up window.
In this embodiment, the real-time data of the index displayed by the interfaces such as the classification list, the schematic diagram and the like in the method has a hyperlink, a pop-up data drilling window can be clicked, the pop-up window displays the real-time data of the calculation formula and the formula factor list, the real-time data of the formula factor can be continuously clicked, the real-time data of the calculation formula and the formula factor list of the next stage of the data is displayed, and the process is repeated until the real-time data of the formula factor list of the last stage is the measured point data, the measured point code is displayed, and the information of the measured position, the measured time and the like of the data can be obtained through the measured point code.
When the coal consumption factor index model comprises a plurality of formula factor indexes, the formula factor indexes can be displayed in the form of a list and the like. If the formula factor index list data has obvious abnormal data, the index data can be drilled and viewed preferentially. And the operator closes the current drilling window and can return the real-time data of the previous-stage calculation formula and the formula factor list.
The pop-up window displays the data of the calculation formula and the formula factor list, has a function of adding and comparing, and can add the indexes and other optional indexes in the data list in the pop-up window into the current historical data query list.
In the present embodiment, the formula factor list is an index list required for calculating the target index. Each index row corresponds to an ID, and the rows can be traversed to form an index ID array. The first column of the historical data list is a time column, and the other columns take the index name as a column name and display the historical data value of each coal consumption factor index in a time period. The number of columns is changeable, each coal consumption factor index corresponds to an ID, and the index columns are displayed according to the ID array.
An operator can click the name (column name) of the index in the formula factor list, and a pop-up window displays the coal consumption factor index model of the index and the formula factor index list. Clicking a 'join contrast' button in the popup, traversing a formula factor index list to obtain an index ID array, automatically closing the popup, combining the obtained index ID array with the existing index ID array in the historical data list, removing repeated IDs to form a new index ID array, and displaying an index column and historical data according to the new index ID array.
By comparing historical data of the associated indexes, specific time and specific indexes of abnormal data can be conveniently searched.
The system can further comprise a summarizing module used for summarizing the obtained coal consumption factor indexes, wherein the summarizing mode comprises accumulation, difference, average and/or weighted average.
In this embodiment, the summarizing module summarizes the historical data corresponding to the coal consumption factor index, and includes various analysis methods such as accumulation, interpolation, averaging and/or weighted averaging of the historical data, and the weighted average index includes, but is not limited to, the unit load, the main steam flow rate, and the boiler coal combustion amount.
In this embodiment, the weighted average indicator includes a unit load, a main steam flow, a boiler coal combustion amount, and the like. The time unit dimension includes minutes, half-hours, shift values, days, weeks, months, seasons, years, etc., and some or all of the time dimension is used as needed. The data summarization rule is that minute data is summarized into half-hour data or hour data, hour data is summarized into day data, hour data or half-hour data is summarized into shift value data, day data is summarized into week data and month data, and month data is summarized into season data and year data.
In the embodiment of the application, by establishing a coal consumption factor index model, extracting real-time and historical operating data of the coal-fired unit corresponding to the analyzed coal consumption factor index, and extracting and calculating historical data of time dimensions such as minutes, hours, shift values, days, weeks, months, seasons, years and the like; the real-time data of the coal consumption factor indexes are displayed in the forms of graphical display interfaces, lists and the like, the data of the coal consumption factor indexes can be popped up in a data drilling window in a command mode of clicking in a hyperlink mode and the like, the data of the coal consumption factor indexes are displayed in the popping-up window, the real-time data of the coal consumption factor index models and the real-time data of the coal consumption factor indexes are analyzed, meanwhile, the recent historical trend of the current indexes can be checked, the formula factor real-time data can be continuously clicked to drill and inquired until the real-time data of the last-stage formula factor list are measured point data, and measured point codes are displayed. In the process, factor index operation data related to coal consumption is extracted, and factor extraction and multi-time-dimension grading data summarization of a related calculation formula are performed to realize data visualization and historical data layering in the coal consumption calculation process, so that multi-dimension drilling analysis query of the coal consumption data is realized, and a new, convenient and efficient analysis reference is provided for power generation operators to perform coal consumption data deviation analysis. And further solve the problem that the data of the coal consumption analysis process in the prior art is not intuitive.
The coal consumption data multidimensional drilling analysis system disclosed by the embodiment of the invention can extract the factor indexes related to the analysis coal consumption according to the coal consumption factor index model by establishing the coal consumption factor index model; and then obtain coal-fired unit real-time and historical operating data, solved current to the coal consumption carry on the data analysis not directly perceived, the data contrast is inconvenient and the analysis inefficiency problem.
A storage medium, comprising a stored program, wherein an apparatus on which the storage medium is located is controlled to perform the method described above when the program is run.
The storage medium disclosed by the above embodiment of the invention utilizes a coal consumption data multidimensional drilling analysis method, and can extract factor indexes related to analysis of coal consumption according to a coal consumption factor index model by establishing the coal consumption factor index model; and then obtain coal-fired unit real-time and historical operating data, solved current to the coal consumption carry on the data analysis not directly perceived, the data contrast is inconvenient and the analysis inefficiency problem.
A computing device comprising a processor, wherein the processor is configured to execute a program, wherein the program when executed performs the method described above.
The computing equipment disclosed by the embodiment of the invention utilizes a coal consumption data multidimensional drilling analysis method, can extract the factor indexes related to the analysis of coal consumption according to the coal consumption factor index model by establishing the coal consumption factor index model; and then obtain coal-fired unit real-time and historical operating data, solved current to the coal consumption carry on the data analysis not directly perceived, the data contrast is inconvenient and the analysis inefficiency problem.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to:
the technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A coal consumption data multidimensional drilling analysis method is characterized by comprising the following steps:
establishing a coal consumption factor index model;
acquiring coal consumption data in real time, and extracting and recording coal consumption factor indexes corresponding to the coal consumption data according to the coal consumption factor index model;
inquiring the coal consumption factor indexes, and presenting the correspondingly obtained target factor indexes in a time axis form;
and establishing a data drilling window corresponding to the target factor index, wherein the data drilling popup window is used for displaying the coal consumption factor index model corresponding to the current target factor index and/or formula factors contained in the coal consumption factor index model.
2. The coal consumption data multidimensional drilling analysis method according to claim 1, further comprising:
judging whether the formula factors comprise measuring point data or not,
if the data of the measuring points are included, measuring point codes corresponding to the data of the measuring points are displayed;
and if the measured point data is not included, further displaying the coal consumption factor index model corresponding to the current formula factor and/or a next-level coal consumption factor index model and a corresponding formula factor contained in the coal consumption factor index model through drilling a pop-up window.
3. The coal consumption data multidimensional drilling analysis method according to claim 1, further comprising:
and classifying the coal consumption factor indexes to present the coal consumption factor indexes in a classified manner.
4. The coal consumption data multidimensional drilling and analyzing method according to claim 3, wherein the types of the coal consumption factor indexes are classified into a unit performance index, a steam turbine performance index, a heater performance index, a condenser performance index, an air preheater performance index, a boiler performance index, a deviation influence coal consumption index, an auxiliary unit consumption index and an auxiliary machine power consumption index.
5. The coal consumption data multidimensional drilling analysis method according to claim 1, wherein the querying the coal consumption factor index and presenting the target factor index in a time axis form comprises:
creating a graphical display interface corresponding to the target factor index;
inquiring the coal consumption factor index according to the input instruction;
and in the graphical display interface, presenting the target factor indexes in a time axis grading way.
6. The coal consumption data multidimensional drilling analysis method according to claim 5, wherein the target factor indexes are presented in a time axis hierarchy, and the method comprises the following steps:
taking the moment of acquiring the coal consumption data as a time node for acquiring the corresponding target factor index;
and the target factor indexes are presented in a grading way according to the recorded time nodes from low to high in units of one or more of minutes, hours, class values, days, weeks, months, quarters or years.
7. The coal consumption data multidimensional drilling analysis method according to claim 6, wherein the target factor indexes are presented in a time axis hierarchy, and the method comprises the following steps:
acquiring the current time unit level presented by the current target factor index;
and inquiring and presenting the target factor indexes of a time unit level lower than the current time unit level according to the current time unit level information.
8. The coal consumption data multidimensional drilling analysis method according to claim 1, further comprising:
and summarizing the obtained target factor indexes, wherein the summarizing mode comprises accumulation, difference, average and/or weighted average.
9. A coal consumption data multidimensional drilling analysis system is characterized by comprising:
the modeling module is used for establishing a coal consumption factor index model;
the factor index extraction module is used for acquiring coal consumption data in real time, and extracting and recording coal consumption factor indexes corresponding to the coal consumption data according to the coal consumption factor index model;
the data presentation module is used for inquiring the coal consumption factor indexes and presenting the corresponding obtained target factor indexes in a time axis form;
and the data drilling module is used for establishing a data drilling window corresponding to the target factor index, and the data drilling popup window is used for displaying the coal consumption factor index model corresponding to the current target factor index and/or formula factors contained in the coal consumption factor index model.
10. A storage medium, characterized in that the storage medium comprises a stored program, wherein the device on which the storage medium is located is controlled to perform the method according to any of claims 1-8 when the program is run.
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