CN113536050B - Distribution network monitoring system curve data query processing method - Google Patents
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Abstract
The application discloses a distribution network monitoring system curve data query processing method, which comprises the following steps: according to the information of the measuring points selected by the user, automatically searching database data according to a default period; analyzing the time length of the data retrieval, and if the time length exceeds a preset value, performing the retrieval twice; constructing a data index based on the data obtained after the retrieval is finished and according to a VSM retrieval model, and caching the data in a memory; analyzing the abnormal point data by adopting an isolated forest algorithm, and identifying abnormality of the data with high abnormality index; and for normal operation working condition data, displaying the condition that the data quantity is too large, analyzing the time period data interval relation according to the screen resolution, carrying out index display by utilizing the index data, displaying an abnormal mark on an abnormal point in the index data, and drawing a curve. The application can rapidly, efficiently and accurately display the data concerned by the user, reduce the system operation pressure, improve the data display efficiency and rapidly display the curve data of the real field operation condition.
Description
Technical Field
The application relates to the technical field of distribution network and data query, in particular to a distribution network monitoring system curve data query processing method.
Background
With the continuous progress of the informatization technology level, the data analysis requirement in the domestic distribution network monitoring control field is continuously developed, and the field device operation data curve needs to be displayed in front of a user timely and efficiently; at present, a mainstream system collects real-time data of field devices through a network for storage, and a full data drawing method is mostly adopted for a curve, namely, for each data inquiry, full data inquiry in a designated period is carried out, and the curve is drawn; due to the improvement of the field hardware level, the real-time data sampling interval is continuously shortened, millisecond-level data storage is achieved at present, and the annual data storage capacity of a single measuring point of the system is tens of millions. At the same time of applying the current data retrieval mode to the system database, long-time delay, clamping and other reactions occur in curve drawing, so that the data analysis efficiency of a user and the safety and stability of the system are greatly influenced.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
The present application has been made in view of the above-described problems occurring in the prior art.
Therefore, the technical problems solved by the application are as follows: when the existing data retrieval mode gives the system database extremely high pressure, long time delay, clamping and other reactions occur in curve drawing, so that the data analysis efficiency of a user and the safety and stability of the system are greatly influenced.
In order to solve the technical problems, the application provides the following technical scheme: according to the information of the measuring points selected by the user, automatically searching database data according to a default period; analyzing the time length of the data retrieval, and if the time length exceeds a preset value, performing the retrieval twice; constructing a data index based on the data obtained after the retrieval is finished and according to a VSM retrieval model, and caching the data in a memory; analyzing the abnormal point data by adopting an isolated forest algorithm, and identifying abnormality of the data with high abnormality index; and for normal operation working condition data, displaying the condition that the data quantity is too large, analyzing the time period data interval relation according to the screen resolution, carrying out index display by utilizing the index data, displaying an abnormal mark on an abnormal point in the index data, and drawing a curve.
As a preferable scheme of the distribution network monitoring system curve data query processing method, the application comprises the following steps: the automatic database data retrieval according to the default time period according to the user-selected measuring point information comprises the steps that a curve tool provides a default time period selection frame according to the user-selected measuring point information, and the user selects the default time period to conduct initial database data retrieval.
As a preferable scheme of the distribution network monitoring system curve data query processing method, the application comprises the following steps: the searching for two times comprises the steps of dividing time periods for the first searching, starting multi-thread synchronous searching, and merging the searching results; the secondary retrieval adopts a multi-line Cheng Zengliang retrieval strategy, individual thread refreshing management is carried out on each curve, data query is synchronously carried out, and the increment time is the curve refreshing period.
As a preferable scheme of the distribution network monitoring system curve data query processing method, the application comprises the following steps: the data retrieval further comprises the step of custom condition configuration retrieval: the user carries out history recall retrieval for a long time period based on a configurable condition retrieval frame, and different statistical types are provided, wherein the statistical types are selected, average value, maximum value and minimum value display; for long-time period data retrieval, a multithreading segmentation retrieval strategy is adopted, separation is carried out according to time periods, multi-time period parallel retrieval is carried out, and retrieval completion is combined.
As a preferable scheme of the distribution network monitoring system curve data query processing method, the application comprises the following steps: the analysis of the abnormal point data comprises the steps of establishing a data index in a memory according to a VSM retrieval model and managing data point information based on the condition that a large amount of data exceeds screen display resolution and a large amount of invalid points and coincident points exist in the data.
As a preferable scheme of the distribution network monitoring system curve data query processing method, the application comprises the following steps: the curve tool adopts an isolated forest algorithm to detect and analyze abnormal data, calculates data abnormality indexes, eliminates and displays invalid data, and comprises the steps of constructing N iTree, randomly sampling each tree without replacement to generate a training set, wherein the iTree is a random binary tree, and a data set DataSet is given to define that all attributes in the data set are continuous variables; and (3) the test data is sent down along the corresponding branches on the iTree tree to reach leaf nodes, the path length h (x) passing in the process is recorded, and the h (x) is carried into an outlier scoring function to obtain outlier scores.
As a preferable scheme of the distribution network monitoring system curve data query processing method, the application comprises the following steps: the outlier scoring function includes,
where s (x, n) represents an abnormality index of record x at an itrate composed of training data of n samples.
As a preferable scheme of the distribution network monitoring system curve data query processing method, the application comprises the following steps: the judgment standard of the outlier comprises that the value range of s (x, n) is [0,1], when the value range of s (x, n) is [0.65,1], the value range of s (x, n) is [0,0.38], if the value of s (x, n) of more than eighty percent of training samples is within the range of (0.38,0.65), the whole data set has no outlier.
The application has the beneficial effects that: according to the application, the data query method is optimized from mass field industrial control data, and the obtained data is subjected to optimization analysis, screening and display, so that the data concerned by a user is displayed rapidly, efficiently and accurately, the system operation pressure is reduced, the data display efficiency is improved, and the curve data of the real field operation condition is displayed rapidly.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
fig. 1 is a basic flow diagram of a method for querying and processing curve data of a distribution network monitoring system according to an embodiment of the present application.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present application can be understood in detail, a more particular description of the application, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
While the embodiments of the present application have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the application. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Also in the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected, and coupled" should be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Example 1
Referring to fig. 1, for an embodiment of the present application, a method for querying and processing curve data of a distribution network monitoring system is provided, including:
s1: according to the information of the measuring points selected by the user, automatically searching database data according to a default period; it should be noted that:
according to the measurement point information selected by the user, database data retrieval is automatically carried out according to a default time period, specifically, according to the measurement point information selected by the user, a curve tool provides a default time period selection frame, the user can select the default time period to carry out initial database data retrieval, the initial database data retrieval is carried out for a full data time period, then multi-line Cheng Zengliang retrieval is carried out, independent thread refreshing management is carried out on each curve, data inquiry is synchronously carried out, and the incremental retrieval time period is a curve refreshing time period;
in addition, a user condition search interface is provided to support a user-defined condition configuration search function, and in particular, a configurable condition search frame is provided, a user can carry out long-time historical recall search, different statistical types are provided at the same time, the search is divided into picking points, average values, maximum values and minimum value display, for long-time data search, a multi-thread segmented search mode is adopted to ensure search efficiency and reduce database pressure, separation is carried out according to time intervals, multi-time parallel search is carried out, and search completion is combined.
S2: analyzing the time length of data retrieval, and if the time length exceeds a preset value, performing retrieval twice; it should be noted that:
the search performed in two times includes:
the first retrieval is carried out for time segment segmentation, multi-thread synchronous retrieval is started, and retrieval results are combined;
the secondary retrieval adopts a multi-line Cheng Zengliang retrieval strategy, individual thread refreshing management is carried out on each curve, data query is synchronously carried out, and the increment time is the curve refreshing period.
S3: constructing a data index based on the data obtained after the retrieval is finished and according to a VSM retrieval model, and caching the data in a memory; it should be noted that:
for a large amount of data, under the condition that the resolution ratio of screen display is exceeded, a large amount of invalid points and coincident points exist in the data.
S4: analyzing the abnormal point data by adopting an isolated forest algorithm, and identifying abnormality of the data with high abnormality index; it should be noted that:
the curve tool adopts an Isolation Forest algorithm to detect and analyze abnormal data, calculates data abnormality indexes, and eliminates and displays invalid data;
the algorithm flow is as follows:
(1) Constructing N iTree, randomly sampling each tree without replacement to generate a training set; the iTree is a random binary tree, a data set DataSet is given, and all attributes in the data set are assumed to be continuous variables;
(2) And (3) predicting: the prediction process is to make the test data go down along the corresponding branches on the iTree tree, go to reach the leaf nodes, and record the path length h (x) passed in the process; and h (x) is carried into an outlier scoring function to obtain an outlier score, wherein the formula is as follows:
where s (x, n) represents an abnormality index of record x at an itrate composed of training data of n samples.
The judging standard of the abnormal point comprises the following steps:
s (x, n) is in the range of [0,1], s (x, n) is in the range of [0.65,1] and is in the normal point, s (x, n) is in the range of [0,0.38], and if s (x, n) of more than eighty percent of training samples is in the range of (0.38,0.65), the whole data set has no abnormal value.
S5: and for normal operation working condition data, displaying the condition that the data quantity is too large, analyzing the data interval relation of the time period according to the screen resolution, carrying out index display by utilizing index data, displaying an abnormal mark on an abnormal point in the index data, and drawing a curve.
According to the method, the data query index is built through the VSM model, the data index table is built in real time, data caching is carried out, curve acquisition data can be quickly acquired from the cache, and curve data acquisition efficiency is greatly optimized; meanwhile, aiming at the condition of long-time data display, an Isolation Forest algorithm is adopted to screen invalid data, high-impact factor data are drawn, and curve drawing and display are efficiently carried out under the condition that curve trend quality is not lost, so that a further effective means is provided for solving the problem of long-time large-data-volume curve drawing and clamping.
Example 2
In order to verify and explain the technical effects adopted in the method, the traditional technical scheme and the method are adopted for comparison test, and the test results are compared by means of scientific demonstration to verify the true effects of the method.
The traditional technical scheme is as follows: the full data drawing method is adopted, namely, for each data inquiry, the full data inquiry is carried out in a designated period, and the full data inquiry is drawn on the curve, so that the curve drawing has long delay, clamping and other reactions, the analysis efficiency and accuracy are low, and the safety and the stability of the system are low.
Compared with the traditional method, the method has higher analysis efficiency and accuracy; in the embodiment, the traditional full data drawing method and the method are adopted to respectively measure and compare the efficiency and accuracy of the distribution network monitoring control data analysis in real time.
Test environment: and simulating the operation of the distribution network field device and the acquisition and analysis of simulated data on a simulation platform, starting automatic test equipment by using a traditional method and the method, and realizing the simulation test of the two methods by using MATLB software programming, thereby obtaining the simulation data according to experimental results. Each method tests 20 groups of data, calculates and obtains analysis time of each group of data and an obtained curve, and compares calculation errors with actual time and the curve which are input by simulation; the results are shown in the following table.
Table 1: comparison table of experimental results.
| Test item | Conventional method | The method of the application |
| Time delay/ms | 1.76 | 0.58 |
| Efficiency/% | 93.2 | 96.8 |
| Accuracy/% | 91.3 | 97.2 |
Compared with the traditional method, the method has lower time delay and higher data analysis efficiency and accuracy, fully proves that the implementation of the method can quickly perform data query on large-capacity curve data points, simultaneously analyzes the curve data points obtained by query, displays abnormal points and normal trend points, can screen out invalid points efficiently, greatly improves the system operation efficiency and curve display effect, remarkably improves the working efficiency of monitoring staff, and reduces the system operation pressure.
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present application may be modified or substituted without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered in the scope of the claims of the present application.
Claims (1)
1. The curve data query processing method of the distribution network monitoring system is characterized by comprising the following steps of:
according to the information of the measuring points selected by the user, automatically searching database data according to a default period;
analyzing the time length of the data retrieval, and if the time length exceeds a preset value, performing the retrieval twice;
constructing a data index based on the data obtained after the retrieval is finished and according to a VSM retrieval model, and caching the data in a memory;
analyzing the abnormal point data by adopting an isolated forest algorithm, and identifying abnormality of the data with high abnormality index;
for normal operation working condition data, displaying the condition that the data quantity is too large, analyzing the data interval relation of a time period according to the screen resolution, carrying out index display by utilizing index data, displaying an abnormal mark on an abnormal point in the index data, and drawing a curve;
providing a default time interval selection frame by a curve tool according to the measurement point information selected by a user, selecting the default time interval for initial database data retrieval, dividing the time interval by the first retrieval, starting multi-thread synchronous retrieval, combining the retrieval results, carrying out independent thread refreshing management on each curve by adopting a multi-thread Cheng Zengliang retrieval strategy by the second retrieval, and synchronously carrying out data query, wherein the increment time is the curve refreshing period;
the data retrieval further comprises the following steps of self-defining condition configuration retrieval: the user carries out long-time historical recall search based on a configurable condition search frame, and simultaneously provides different statistical types, wherein the statistical types are selected, average value, maximum value and minimum value display, and for long-time data search, a multithread segmented search strategy is adopted, separation is carried out according to time intervals, parallel search of multiple time intervals is carried out, and search completion is combined;
analyzing abnormal point data, based on the condition that a large amount of data exceeds the screen display resolution, wherein a large amount of invalid points and coincident points exist in the data, establishing a data index in a memory according to a VSM (virtual switch model) retrieval model, and managing data point information;
the method comprises the steps that a curve tool adopts an isolated forest algorithm to detect and analyze abnormal data, calculates a data abnormality index, eliminates and displays invalid data, constructs N iTree, randomly makes non-return sampling for each tree to generate a training set, the iTree is a random binary tree, a data set DataSet is given, all attributes in the data set are defined to be continuous variables, test data is moved downwards on the iTree along corresponding branches until reaching leaf nodes, the path length h (x) passing through in the process is recorded, and the h (x) is brought into an abnormal value scoring function to obtain an abnormal value score;
the outlier scoring function includes,
wherein s (x, n) represents an abnormality index of record x in an itrate composed of training data of n samples;
the judgment standard of the abnormal point is that the value range of s (x, n) is [0,1], when the value range of s (x, n) is [0.65,1], the abnormal point is represented by the abnormal point, when the value range of s (x, n) is [0,0.38], if the value of s (x, n) of more than eighty percent of training samples is in the (0.38,0.65) range, the whole data set has no abnormal value.
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