Method and device for acquiring measuring point data of power equipment

Abstract

The invention provides a method and a device for acquiring measuring point data of power equipment, and mainly aims to accurately determine abnormal measuring point data so as to ensure the accuracy of normal measuring point data after the abnormal measuring point data is removed from the measuring point data. According to the main technical scheme of the invention, the method comprises the steps: obtaining the measurement point data of a target type of power equipment in a preset period and a corresponding change trend; determining a time interval when the change rate is continuously zero in the change trend and corresponding first measurement point data; if the time interval is greater than or equal to a preset time interval, obtaining second measurement point data; screening the data of which the deviation from a preset standard value exceeds a preset deviation range in the second measuring point data to obtain third measuring point data; and fitting the normal value range of the measuring point data of the power equipment based on the second measuring point data, and carrying out secondary screening on the third measuring point data so as to determine the normal measuring point data of the power equipment.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method and apparatus for acquiring measurement point data of power equipment. Background Art

[0002] During the operation of the power system, the analysis of the measurement data of power equipment is a key link to ensure the stable operation of the system.

[0003] To ensure the accuracy of power equipment measurement point data, existing technology generally uses a threshold-based approach to screen out abnormal measurement point data. Specifically, a normal threshold range for measurement point data is pre-set, and the measurement point data is then determined to be abnormal if it exceeds this range. However, this approach has limitations. Specifically, it cannot effectively identify abnormal measurement point data hidden within the normal threshold range, resulting in the misidentification of abnormal measurement point data as normal measurement point data, which in turn leads to inaccurate power equipment measurement point data.

[0004] Therefore, a method is urgently needed to accurately determine abnormal measurement point data in the power equipment measurement point data to ensure the accuracy of the power equipment measurement point data after the abnormal measurement point data is eliminated. Summary of the Invention

[0005] The embodiments of the present application provide a method and apparatus for obtaining power equipment measurement point data, the purpose of which is to accurately determine abnormal measurement point data in the power equipment measurement point data to ensure the accuracy of the power equipment measurement point data after the abnormal measurement point data is eliminated.

[0006] In a first aspect, the present application provides a method for obtaining measurement point data of an electric power device, the method comprising:

[0007] Obtain measurement point data of target categories of power equipment within a preset period and the corresponding change trends;

[0008] Determine the time interval in which the rate of change in the change trend is continuously zero and the corresponding first measuring point data;

[0009] If the time interval is greater than or equal to the preset time interval, the first measuring point data is removed from the measuring point data to obtain the second measuring point data;

[0010] Filtering the data of the second measuring point, wherein the deviation from the preset standard value exceeds a preset deviation range, to obtain the data of the third measuring point;

[0011] Fitting the normal value range of the power equipment measurement point data based on the second measurement point data, and performing a secondary screening on the third measurement point data according to the normal value range;

[0012] The data obtained from the secondary screening and the data in the second measuring point data that are within a preset deviation range are determined as normal measuring point data of the power equipment.

[0013] In a second aspect, the present application provides a device for obtaining measurement point data of an electric power device, the device comprising:

[0014] An acquisition unit, used to acquire measurement point data of a target category of power equipment within a preset period and the corresponding change trend;

[0015] The acquisition unit is configured to determine a time interval in which the rate of change in the change trend is continuously zero and corresponding first measuring point data;

[0016] The determining unit is configured to remove the first measuring point data from the measuring point data to obtain the second measuring point data if the time interval is greater than or equal to a preset time interval;

[0017] The determining unit is configured to filter the data of the second measuring point of the acquiring unit, the deviation of which from the preset standard value exceeds a preset deviation range, to obtain the data of the third measuring point;

[0018] a rejection unit, configured to fit the normal value range of the power equipment measurement point data based on the second measurement point data of the determination unit, and perform a secondary screening on the third measurement point data according to the normal value range;

[0019] The elimination unit is configured to determine the data obtained through the secondary screening and the data in the second measuring point data that are within a preset deviation range as normal measuring point data of the power equipment.

[0020] In a third aspect, the present application provides a storage medium for storing a computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the above-mentioned method for obtaining measurement point data of power equipment.

[0021] In a fourth aspect, the present application provides an electronic device comprising a processor and a memory, wherein the processor is configured to call program instructions in the memory to execute the above-mentioned method for obtaining measurement point data of power equipment.

[0022] Compared to the prior art, the present application provides a method and apparatus for obtaining measurement point data of power equipment. Specifically, first, by obtaining the measurement point data of the target category of power equipment within a preset period and the corresponding change trend, and determining the time interval in which the change rate in the change trend is continuously zero and the corresponding first measurement point data, if the time interval is greater than or equal to the preset time interval, the first measurement point data is discarded. This can effectively remove invalid measurement point data that remains unchanged for a long time, reduce data interference, avoid misjudging such data as normal data, and improve the accuracy of the measurement point data. Secondly, the data in the second measurement point data whose deviation from the preset standard value exceeds the preset deviation range is filtered out to obtain the third measurement point data. This can preliminarily identify abnormal data that significantly deviates from the standard and further purify the data sample. Then, based on the second measurement point data, the normal value range of the power equipment measurement point data is fitted, and the third measurement point data is subjected to a secondary screening. This method can mine potential abnormal data hidden within the normal threshold range. Finally, the data obtained from the secondary screening and the data in the second measuring point data that meet the preset deviation range are determined as normal measuring point data, which enables the accurate identification and elimination of abnormal measuring point data, and the determination of normal measuring point data of the power equipment, thereby ensuring the accuracy of the power equipment measuring point data finally obtained, and providing reliable data support for the stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features and advantages of the exemplary embodiments of the present application will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0024] Figure 1 A flow chart schematically illustrates a method for obtaining measurement point data of an electric power device;

[0025] Figure 2 A flow chart schematically illustrates another method for obtaining measurement point data of power equipment;

[0026] Figure 3 A flowchart of a method for visualizing normal measurement point data and abnormal measurement point data is schematically shown;

[0027] Figure 4 The structure diagram of a device for obtaining measurement point data of electric power equipment is schematically shown;

[0028] Figure 5 The structure of another device for acquiring measurement point data of electric power equipment is schematically shown. DETAILED DESCRIPTION

[0029] The following describes exemplary embodiments of the present application in more detail with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Instead, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0030] It should be noted that, unless otherwise specified, the technical or scientific terms used in this application should have the common meanings understood by those skilled in the art to which this application belongs.

[0031] During power system operation, analyzing data from power equipment measurement points is a critical step in ensuring stable system operation. To ensure the accuracy of power equipment measurement point data, prior art generally employs a threshold-based approach to screen for abnormal measurement point data. Specifically, a normal threshold range for measurement point data is pre-set, and the measurement point data is then judged to be abnormal if it exceeds this range. However, this approach has limitations. Specifically, it cannot effectively identify abnormal measurement point data hidden within the normal threshold range, resulting in the misidentification of abnormal measurement point data as normal, leading to inaccurate data collected from power equipment measurement points.

[0032] To this end, the inventors of the present application have proposed a method for obtaining measurement point data of electric power equipment, which can accurately judge abnormal measurement point data in the measurement point data, and then obtain accurate normal measurement point data of the electric power equipment. That is, obtain the measurement point data of the target category of the electric power equipment within a preset period and the corresponding change trend; determine the time interval in which the change rate in the change trend is continuously zero and the corresponding first measurement point data; if the time interval is greater than or equal to the preset time interval, remove the first measurement point data from the measurement point data to obtain the second measurement point data; filter the data in the second measurement point data whose deviation from the preset standard value exceeds the preset deviation range to obtain the third measurement point data; fit the normal value range of the electric power equipment measurement point data based on the second measurement point data, and perform a secondary screening on the third measurement point data according to the normal value range; determine the data obtained by the secondary screening and the data in the second measurement point data that meets the preset deviation range as the normal measurement point data of the electric power equipment. It can be seen that the above technical solution can effectively identify abnormal measurement point data hidden in the normal range, improve the accuracy of the normal measurement point data of the electric power equipment, ensure the stable operation of the power system, and enhance the monitoring capability of the electric power equipment. A method for obtaining measurement point data of electric power equipment in an embodiment of the present application, the specific steps are as follows: Figure 1 Shown, including:

[0033] Step 101: Obtain measurement point data of target categories within a preset period and corresponding change trends.

[0034] In this step, the preset period refers to a pre-set time period that limits the time range for acquiring measurement point data. This period can be determined based on factors such as the operating characteristics of the power equipment and the needs of fault diagnosis, and can be, for example, one week or one month. The specific duration of the preset period is not specified here. A target category refers to a specific type of measurement point, such as a voltage measurement point or a current measurement point, which may be multiple different types of measurement points on the power equipment's dial. Measurement point data refers to data generated during the operation of the power equipment. Measurement point data can specifically be data recorded on the power equipment's dial. Measurement points of power equipment are points used to measure and display parameters related to the equipment's operation. The data acquired at these points reflects the equipment's operating status over the past preset period. Each measurement point data value within the target category of the power equipment within the preset period has corresponding time information for data collection. The time information for all measurement point data collection constitutes the preset period. In this step, the measurement point data also includes the current operating condition of the power equipment. A change trend refers to the change in measurement point data over time, which may exhibit different trends, such as increasing, decreasing, or stable.

[0035] In this step, the trend of measurement point data can be determined based on the collection interval between adjacent measurement point data and the difference between adjacent measurement point data. Alternatively, the preset period can be divided into multiple preset time intervals, and the trend of data within each of the multiple preset time intervals can be determined. The preset time interval is also a predetermined time length used to analyze changes in measurement point data, such as analyzing data trend changes every 1 minute, 5 minutes, or the like. The preset time interval can be determined based on the preset period, where the length of the preset time interval is less than the length of the preset period. The length of the preset time interval is 1 / n of the length of the preset period, where n represents the length of the preset period. Of course, 1 / n can also represent a manually set value. For example, if the preset period is 30 days and n represents the length of the preset period, then the preset time interval is 1 day. When 1 / n represents a manually set value, n is set based on actual conditions. When n represents the length of the preset period, the ratio of the difference between adjacent measurement point data to the interval between measurement point data collection is directly calculated. The trend of measurement point data can be determined from this ratio using a time series method, and the trend can be displayed using a point-line graph. When 1 / n can also represent a manually set value, the difference in measurement point data between the initial time point and the end time point of the preset time interval is determined, and the change rate is determined using this difference. Based on the change rate values within all preset time intervals, a chart is used to display the change trend. The chart data can be a point-line chart, a bar chart, a pie chart, or other chart data that can display the change trend.

[0036] Step 102: Determine the time interval in which the rate of change in the change trend is continuously zero and the corresponding first measuring point data.

[0037] After obtaining the changing trend of the measurement point data in step 101, the time intervals during which the rate of change in the changing trend is continuously zero and the corresponding measurement point data are determined based on the changing trend data. The search can be conducted from the start time of a preset period to the end time of the preset period, or from the end time of the preset period to the start time of the preset period. After determining that the rate of change is continuously zero, the time intervals during which the rate of change is continuously zero are recorded, along with the measurement point data corresponding to the time interval and the acquisition time of the corresponding measurement point data.

[0038] It is worth noting that when the trend of measurement point data changes within multiple preset time intervals, the time intervals in which the rate of change is continuously zero in the change trends within the multiple preset time intervals can be determined simultaneously, and the relevant data can be recorded. Alternatively, the time intervals in which the rate of change is continuously zero in the change trends within the multiple preset time intervals can be determined one by one based on the time sequence of measurement point data collection within the preset time intervals, and the relevant data can be recorded.

[0039] Step 103: If the time interval is greater than or equal to a preset time interval, remove the corresponding measuring point data from the measuring point data to determine second measuring point data.

[0040] In a thermal power plant monitoring system, the measured data of power equipment changes in real time. If the measured data does not change, it indicates that the data at that time is bad data, that is, abnormal measured data. The preset time interval in this step is set based on the actual operation of the power equipment and is not limited here.

[0041] In this step, if the time interval is greater than or equal to the preset time interval, it indicates that the measured point data has not changed within the preset time interval. In other words, the measured point data has the same data value within the time interval, and the measured point data is considered abnormal. Based on the first measured point data and the measured point data, the corresponding measured point data is searched and removed from the measured point data based on the time series, thereby completing the preliminary screening of the measured point data. Specifically, the data removal process may include searching for the collection time point of the corresponding first measured point data, searching for its position in the measured point data based on the collection time point of the corresponding first measured point data, and deleting the corresponding data to determine the second measured point data.

[0042] It is worth noting that in this step, when determining the time interval during which the rate of change in the change trend is continuously zero, a time interval (preset time interval) from the end of the preset period to the start of the preset period can also be determined from the change trend to determine whether the rate of change of the measured point data is continuously zero within the preset time interval. If it is continuously zero, the corresponding first measured point data is removed from the measured point data to determine the second measured point data. For example, if there are 20 days of measured point data and the preset time interval is one day, first determine whether the rate of change in the change trend of the measured point data on the 20th day is continuously zero. If so, remove the corresponding first measured point data from the measured point data to determine the second measured point data.

[0043] Step 104 : Filter the data of the second measuring point whose deviation from the preset standard value exceeds a preset deviation range to obtain the third measuring point data.

[0044] In this step, the deviation of the second measuring point data from a preset standard value is first calculated, and then the deviation is compared with a preset deviation range to determine the third measuring point data. The preset standard value is determined based on the power equipment operating standard and refers to the standard value of the data at this measuring point under different operating conditions of the power equipment. The preset deviation range is also determined based on the equipment operating standard. In this embodiment, if the deviation of the second measuring point data from the preset standard value exceeds the preset deviation range, the second measuring point data is filtered out of the data whose deviation from the preset standard value exceeds the preset deviation range to determine the third measuring point data. The third measuring point data may contain seemingly normal data, but in fact, this data is abnormal data, which is caused by an instrument malfunction. If the deviation of the second measuring point data from the preset standard value does not exceed the preset deviation range, it indicates that there is no abnormal data in the second measuring point data, and the second measuring point data is normal data for the power equipment.

[0045] It is worth noting that when obtaining the preset standard value and the preset deviation range, data under the same equipment operating conditions as the measurement point data are selected.

[0046] Step 105 : Fitting the normal value range of the power equipment measurement point data based on the second measurement point data, and performing a secondary screening on the third measurement point data according to the normal value range.

[0047] In this step, the specific implementation process of fitting the normal value range of the power equipment measurement point data based on the second measurement point data is: calculating the standard deviation and mean of the second measurement point data, and using the standard deviation and mean to determine the first normal value range and the second normal value range, the first normal value range is the range determined by the mean and one times the standard deviation, and the second normal value range is the range determined by the mean and two times the standard deviation.

[0048] The calculation method of mean and standard deviation is:

[0049]

[0050] In the above, μ is the mean, X i is the data of the second measuring point i, n is the total amount of data of the second measuring point, and σ is the standard deviation.

[0051] Based on the above calculation formula, at this time, the first normal value range is (μ-σ, μ+σ), and the second normal value range is (μ-2σ, μ+2σ).

[0052] In this step, the data obtained through the secondary screening is normal measurement point data of the power equipment. There are three specific implementation methods for performing the secondary screening of the third measurement point data based on the normal value range. The first method is to determine the number of third measurement point data that fall within the first normal value range, and then determine the first probability based on this number and the total number of third measurement point data. If the first probability is greater than or equal to a preset first probability, then determine the data obtained through the secondary screening. In this case, the data obtained through the secondary screening is the measurement point data whose third measurement point data fall within the first normal value range. The second method is to determine the number of third measurement point data that fall within the second normal value range, and then determine the second probability based on this number and the total number of third measurement point data. If the second probability is greater than or equal to the preset second probability, then determine the data obtained through the secondary screening. The data obtained through the secondary screening is the measurement point data whose third measurement point data fall within the second normal value range. The third method is to simultaneously obtain a first probability within the first normal value range and a second probability within the second normal value range. If the first probability is greater than or equal to a preset first probability and the second probability is greater than or equal to a preset second probability, the data obtained by the second screening is determined. The data obtained by the second screening is the measurement point data where the third measurement point data falls within the second normal value range.

[0053] Here are some examples to illustrate the above:

[0054] For example, a 1000MW supercritical wet-cooled coal-fired unit shows a DCS meter reading of 132.8°C at the air preheater outlet flue gas temperature (exhaust temperature). The design exhaust temperature under the current load is 109.6°C. This measurement point is suspected to be faulty (the instrument measuring the data is faulty), and the preset interval is 0.5 days. At this point, the preset period for measurement point data (voltage values) is 30 days. The time step (the time interval for collecting data) for the measurement point data within 30 days can be determined independently. It is worth noting that to ensure the integrity of the measurement point data, the time step is set based on actual conditions and is not specifically limited here. For example, if the time step is set to 5 seconds, a value is taken every 5 seconds, resulting in a total of 518,400 measurement point values. Based on the measurement point data within 30 days, the change trend of the measurement point data on the 30th day is determined. If the change rate of the measurement point data on the 30th day is zero, and the time interval of the 30th day (the time interval during which the change rate is continuously zero in the change trend) is greater than 0.5 days, it is determined that the measurement point data on the 30th day (the first measurement point data) has not changed. The first measurement point data at this time is determined to be abnormal measurement point data. At this time, the measurement point data on the 30th day (the first measurement point data) should be discarded from the measurement point data to obtain the second measurement point data. The next step is to determine the data at the second measuring point. Data whose deviation from the preset standard value exceeds the preset deviation range is screened. If the deviation exceeds the preset deviation range, the third measuring point data is obtained. The third measuring point data is then judged based on the third measuring point data in the next step, i.e., based on the 3sigma criterion, if the probability of the third measuring point data falling within the interval (μ-σ, μ+σ) is ≥60% and the probability of the third measuring point data falling within the interval (μ-2σ, μ+2σ) is ≥90%, the third measuring point data falling within the second normal value range is considered normal, and the data variation is caused by other operational reasons. If the probability of the third measuring point data falling within the second normal value range is less than 90%, the third measuring point data not falling within the second normal value range is considered abnormal. At this point, the abnormal measuring point data is eliminated from the third measuring point data to obtain the data obtained from the secondary screening.

[0055] After abnormal measurement point data is determined in step 1, the abnormal measurement point data is removed from the third measurement point data based on a time series method. If multiple abnormal measurement point data exist in the third measurement point data, the multiple abnormal measurement point data are sorted according to the time of their acquisition to obtain a first sort order, and the abnormal measurement point data are removed one by one according to the first sort order. In this step, the abnormal measurement point data in the third measurement point data can also be removed in reverse order of the first sort order. The data obtained from the secondary screening is the data obtained after the abnormal measurement point data is removed from the third measurement point data. This data more accurately reflects the normal operating status of the power equipment and can be used for subsequent fault diagnosis and other analyses.

[0056] In this step, abnormal measurement point data can be eliminated simultaneously with the determination of the abnormal measurement point data. The elimination method includes determining the value and acquisition time of the abnormal measurement point data, searching for the value and acquisition time of the abnormal measurement point data in the third measurement point data, and determining that the search results are correct before eliminating the abnormal measurement point data. In this step, searching for the value and acquisition time of the abnormal measurement point data in the third measurement point data can be performed by traversing data values in the third measurement point data based on the value of the abnormal measurement point data. After determining the value of the abnormal measurement point data, all third measurement point data containing the value of the abnormal measurement point data can be traversed based on the acquisition time to determine the abnormal measurement point data in the third measurement point data. Alternatively, time information can be traversed based on the acquisition time of the abnormal measurement point data. After determining the acquisition time of the abnormal measurement point data, the data value corresponding to the acquisition time in the third measurement point data is determined to be consistent with the value of the abnormal measurement point data, and if they are consistent, the search is confirmed to be correct.

[0057] Step 106: Determine the data obtained from the secondary screening and the data in the second measuring point data that are within a preset deviation range as normal measuring point data of the power equipment.

[0058] Based on the above Figure 1 As can be seen from the implementation method, the present application provides a method for obtaining power equipment measurement point data. This method can effectively identify abnormal measurement point data hidden within a normal range, improve the accuracy of normal measurement point data of power equipment, ensure the stable operation of the power system, and enhance the monitoring capabilities of power equipment. Specifically, first, by obtaining measurement point data of a target category of power equipment within a preset period and the corresponding change trend, and determining the time interval in which the change rate in the change trend is continuously zero and the corresponding first measurement point data, if the time interval is greater than or equal to the preset time interval, the first measurement point data is discarded. This can effectively remove invalid measurement point data that remains unchanged for a long time, reduce data interference, avoid misjudging such data as normal data, and improve the accuracy of the measurement point data. Secondly, the data in the second measurement point data that deviates from the preset standard value beyond the preset deviation range is filtered out to obtain third measurement point data. This method can preliminarily identify abnormal data that significantly deviates from the standard and further purify the data sample. Then, based on the second measurement point data, the normal value range of the power equipment measurement point data is fitted, and the third measurement point data is subjected to a secondary screening. This method can mine potential abnormal data hidden within the normal threshold range. Finally, the data obtained from the secondary screening and the data in the second measuring point data that meet the preset deviation range are determined as normal measuring point data, which enables the accurate identification and elimination of abnormal measuring point data, and the determination of normal measuring point data of the power equipment, thereby ensuring the accuracy of the power equipment measuring point data finally obtained, and providing reliable data support for the stable operation of the power system.

[0059] Furthermore, according to the above Figure 1 The embodiment of the present application shown in FIG. 1 is a method for obtaining the measurement point data of the power equipment. Specifically, Figure 2 Shown, including:

[0060] Step 201: Establish a connection with a database using a data interface.

[0061] In this step, the database refers to a repository containing all data on power equipment measurement points. In this embodiment, the system establishes a connection with the database by: obtaining the database type storing the measurement point data; determining the corresponding data interface based on the database type; configuring connection parameters based on the data interface and establishing a connection with the database to obtain the target category of measurement point data. Specifically, the database type information is obtained by reading a database configuration file, system environment variables, or sending a specific query command to the database management system. For example, a database configuration file (such as one stored in JSON or YAML format) will clearly indicate the database type storing the measurement point data, such as "database_type": "MySQL". Relevant information can also be obtained from environment variables during system startup, such as by setting the environment variable DB_TYPE to "PostgreSQL". Furthermore, the database management system can be used to send commands using command-line tools or APIs to query the database system's identification information to determine the database type storing the measurement point data. Common relational databases include MySQL and PostgreSQL, and non-relational databases include MongoDB. Different types of databases have their own unique data storage structures and specific interfaces. Therefore, it's necessary to determine the database type corresponding to the database storing the measurement point data. This allows you to select the appropriate data interface based on the database type. This can be done by maintaining a mapping table between database types and data interfaces, such as MySQL corresponding to the mysql-connector-python interface and PostgreSQL corresponding to the psycopg2 interface. These data interfaces act as bridges, providing a channel for communication between the system and the database. Finally, based on the selected data interface, you configure the connection parameters. These primarily include key information such as the database host address, port number, username, password, and database name. By correctly configuring these parameters, the system successfully establishes a connection with the database. Once the connection is established, you can execute data queries to accurately retrieve the target measurement point data, laying the foundation for subsequent analysis of power equipment meter data.

[0062] After establishing a connection with the database, the specific implementation method for obtaining the target category of measurement point data is as follows: obtain the target power equipment name, target measurement point location information, and the target data type of the measurement point data; traverse the database based on the target power equipment name and the target measurement point location information to determine the measurement point data of all data types; based on the target data type of the measurement point data, traverse the measurement point data of all data types to obtain the target category of measurement point data. In particular, multi-threaded parallel query technology is used when querying the database. Based on the target power equipment name and target measurement point location information, multiple threads scan different partitions of the database at the same time to quickly locate the measurement point data of all data types, greatly improving the query efficiency. Finally, from the measurement point data of all data types, according to the target data type of the measurement point data, the target category of measurement point data is filtered out.

[0063] Step 202: Acquire measurement point data of a target category of power equipment within a preset period and corresponding change trends.

[0064] In this step, after obtaining the target category's measurement point data in step 201, the data is filtered according to a preset period to obtain measurement point data for the target category of power equipment within the preset period. After obtaining the measurement point data, its corresponding change trend is obtained. This change trend is specifically implemented by dynamically partitioning the measurement point data using a sliding window technique to determine the measurement point data within the sliding window; and determining the change trend of the measurement point data within the determined sliding window using a least squares curve fitting method.

[0065] Specifically, a sliding window is a dynamic data partitioning method, like a "window" that can slide across a data sequence. The window size and sliding step size are pre-set. The window size represents the amount of data analyzed each time, and the sliding step size determines the distance the window moves each time. Taking 30 days of measurement point data as an example, if the window size is 1 day and the step size is 1, then the measurement point data for each day is determined to be the measurement point data within the corresponding sliding window. If the window size is 2 days and the step size is 2, then the measurement point data for the first and second days are used as a window, the third and fourth days as a window, and so on, the twenty-ninth and thirtieth days as a window. Using the above sliding window technology, the measurement point data within the sliding window can be obtained by using the window size and step size parameters. In this embodiment, the core idea of the least squares method is to find a curve that minimizes the sum of the squares of the vertical distances from the data points to the curve. That is, after using the sliding window technology to divide the data into multiple windows, the np.polyfit function is used to perform least squares fitting on the data within each window to obtain the slope of the fitted line, which represents the changing trend of the data. When acquiring the change trend for each window, the change trend of the measured point data within the corresponding windows can be acquired simultaneously for at least two windows, or the change trend of the measured point data within a single window can be acquired one by one. The slope of the fitted curve reflects the change of the measured point data. When the slope is 0, it indicates that the rate of change is 0, indicating that the measured point data within the window has not changed. In this case, the measured point data within the window is abnormal, that is, abnormal data.

[0066] Step 203: Acquire measurement point data of target categories of power equipment within a preset period and corresponding change trends.

[0067] After obtaining the target category's measurement point data and the corresponding change trend in step 202, determine the time interval in which the rate of change is continuously zero in the change trend of each window and the corresponding measurement point data; if the time interval is greater than or equal to the preset time interval, it means that the corresponding measurement point data has not changed. This means that the measurement point data within the time interval is abnormal, that is, abnormal measurement point data (first measurement point data). Remove the abnormal measurement point data from the measurement point data to obtain the second measurement point data, wherein the removal method is to find the acquisition time corresponding to the abnormal measurement point data and the value of the abnormal measurement point data in the measurement point data, and then delete the data accordingly. In order to ensure the accuracy of the second measurement point data, the second measurement point data needs to be further judged. That is, judge and filter the data in the second measurement point data whose deviation from the preset standard value exceeds the preset deviation range to obtain the third measurement point data;

[0068] A normal value range of the electric power equipment measurement point data is fitted based on the second measurement point data, and the third measurement point data is secondary screened according to the normal value range; the data obtained by the secondary screening and the data in the second measurement point data that meets the preset deviation range are determined as the normal measurement point data of the electric power equipment.

[0069] In this embodiment, a preset standard value is first obtained based on the power equipment operating standard. The deviation is calculated based on the preset standard value and the second measuring point data, where the deviation = |second measuring point data - preset standard value| / preset standard value. Data in the second measuring point data that does not deviate from the preset standard value beyond the preset deviation range is determined as normal measuring point data. If the deviation from the preset standard value in the second measuring point data exceeds the preset deviation range, corresponding data that exceeds the preset deviation range is selected from the second measuring point data to determine third measuring point data. The third measuring point data includes both normal and abnormal measuring point data. In this step, the power equipment operating standard is the factory-specified operating standard for equipment in the power system. This standard includes a preset standard value and a preset deviation range for the power equipment measuring point. The preset standard value represents the rated data value of the power equipment in the currently operating unit. The preset deviation range can also be manually set based on the actual operating status of the power equipment. The standard deviation range represents a reasonable range of deviations. Deviation is the ratio of the absolute value of the difference between the data value and the design data to the design data, that is, deviation = |measurement point data-preset standard value| / preset standard value.

[0070] When the deviation is within the preset deviation range, it indicates that the corresponding measurement point data is normal measurement point data. When the deviation is not within the preset deviation range, it indicates that the current operation cannot determine the data in the second measurement point data whose deviation from the preset standard value exceeds the preset deviation range. The standard deviation and mean of the second measurement point data are used to determine abnormal measurement point data to obtain normal measurement point data of the power equipment. Specifically, the following steps are performed: the standard deviation and mean of the second measurement point data are obtained based on the second measurement point data; the normal value range is determined using the mean and standard deviation; the number of the third measurement point data within the normal value range is determined; the probability is determined based on the number and the total number of the third measurement point data; if the probability is greater than or equal to the preset probability, the data obtained by the second screening is determined. Among them, the normal value range includes a first normal value range and a second normal value range. The first normal value range is determined by the mean and one standard deviation, and the second normal value range is determined by the mean and two standard deviations. The first probability and second probability of the third measurement point data within the first normal value range and the second normal value range are determined respectively. When the first probability is greater than or equal to the preset first probability and the second probability is greater than or equal to the second preset probability, the third measuring point data within the second normal value range is determined to be normal measuring point data, and the data of the third measuring point data not within the second normal value range is abnormal measuring point data.

[0071] Step 204: Visualize the normal measurement point data and abnormal data of the power equipment.

[0072] After determining the normal measurement point data of the power equipment in step 203, this embodiment also performs a visual display of the normal measurement point data and abnormal data of the power equipment. The specific operations are as follows: the normal measurement point data of the power equipment are visualized based on the time series to obtain a first visual data graph, and the first visual data graph includes the characteristic data of the normal measurement point data of the power equipment; the abnormal measurement point data are visualized based on the time series to obtain a second visual data graph, and the abnormal measurement point data is characterized by the data obtained by removing the normal measurement point data from the measurement point data; a button is added to the first visual data graph and the second visual data graph respectively, corresponding to the display mode of the first visual data graph and the second visual data graph. The characteristic data of the normal measurement point data of the power equipment can be the peak value, average value, maximum value, minimum value, valley value, etc. of the data reflecting the characteristic data values of the normal measurement point data of the power equipment, and the second visual data graph also includes the specific data value of the abnormal measurement point data, the time of occurrence, and the cause of the abnormality.

[0073] In this embodiment, the specific steps of visualization processing are as follows: Figure 3 As shown:

[0074] Step 301 : Rendering a coordinate system based on a preset period and a numerical range of target category measurement point data.

[0075] In this step, a preset period is obtained, and the horizontal axis of the coordinate system is automatically rendered according to the frequency and time interval of collecting target category measurement point data within the preset period. For example, the preset period is one month. The frequency of collecting target category measurement point data within the period is counted, assuming it is 30 times. Then determine the time interval for each collection, if it is once a day. Take the time starting point as the coordinate origin, and determine the unit length according to the time interval, such as one day corresponds to one unit on the coordinate axis. Mark the collection time points in sequence according to the frequency, and evenly distribute them on the horizontal axis at intervals of unit length starting from the origin, thereby completing the automatic rendering of the horizontal axis. Render the vertical coordinate of the coordinate system according to the numerical range of the target category measurement point data, that is, the maximum and minimum values, and render the vertical axis of the coordinate system. When rendering the vertical axis, the values between adjacent scales are evenly divided according to the numerical range of the target category measurement point data and the desired number of scales, to ensure that the distribution of the data can be displayed more comprehensively and clearly, so as to complete the rendering of the vertical axis in the coordinate system. For example, if the numerical range of the target category measurement point data is 0-100 and 10 scales are expected to be set, the numerical difference between adjacent scales is 10.

[0076] Step 302: Render the normal measurement point data and abnormal measurement point data of the power equipment based on the coordinate system.

[0077] After rendering the coordinate axes of the coordinate system in step 301, a first visualization of the normal measurement point data of the power equipment is rendered based on a time series. Specifically, the normal measurement point data of the power equipment is rendered sequentially according to the time sequence of the data's acquisition. After the rendering of the normal measurement point data is completed, the coordinate system automatically generates information related to the characteristic data of the normal measurement point data of the power equipment, with the characteristic data represented by different markers. Furthermore, a first button for controlling the display of the first visualization is added to the first visualization. After the target features of the normal measurement point data of the power equipment are rendered, the abnormal measurement point data are rendered in the same coordinate system. The abnormal measurement point data is rendered by searching for the acquisition time and specific data values of the abnormal measurement point data and rendering them one by one based on the time sequence of the acquisition time. A second visualization is rendered, displaying abnormal data information. A second button for controlling the display of the second visualization is added to the second visualization. If, during data search, all target category measurement point data is required, the first and second buttons can be clicked to display all of the data. In this case, the normal and abnormal measurement point data of the power equipment are displayed together in the coordinate system. If you only need the normal measurement point data or abnormal measurement point data of the power equipment, you only need to click the first button or the second button. The purpose of this step is to accurately and clearly determine the normal measurement point data and abnormal measurement point data of the power equipment when analyzing the measurement point data of the target category of power equipment within a preset period.

[0078] Furthermore, as a response to the above Figure 1 and Figure 3 The embodiment of the present application provides a device for obtaining the measurement point data of the power equipment, which is mainly used to determine the abnormal measurement point data objectively and accurately to ensure the accuracy of the normal measurement point data of the power equipment after the abnormal measurement point data is eliminated. For the sake of ease of reading, this embodiment of the device will no longer repeat the details of the aforementioned method embodiment, but it should be clear that the device in this embodiment can implement all the contents of the aforementioned method embodiment. The device is as follows Figure 4 As shown, it specifically includes: a device for obtaining measurement point data of power equipment, the device including:

[0079] An acquisition unit 41 is configured to acquire measurement point data of a target category of power equipment within a preset period and corresponding change trends;

[0080] The acquisition unit 41 is configured to determine the time interval in which the rate of change in the change trend is continuously zero and the corresponding first measuring point data;

[0081] The determining unit 42 is configured to remove the first measuring point data from the measuring point data obtained by the acquiring unit 41 to obtain the second measuring point data if the time interval is greater than or equal to a preset time interval;

[0082] The determining unit 42 is configured to filter the data of the second measuring point of the acquiring unit, the deviation of which from the preset standard value exceeds a preset deviation range, to obtain the data of the third measuring point;

[0083] a rejection unit 43 configured to fit the normal value range of the power equipment measurement point data based on the second measurement point data of the determination unit 42, and perform a secondary screening on the third measurement point data according to the normal value range;

[0084] The elimination unit 43 is configured to determine the data obtained through the secondary screening and the data in the second measuring point data that are within a preset deviation range as normal measuring point data of the power equipment.

[0085] Further, such as Figure 5 As shown, the determining unit 42 includes:

[0086] The range acquisition module 421 is used to acquire a preset standard value based on the power equipment operation standard;

[0087] The data calculation module 422 is configured to calculate the deviation based on the preset standard value of the range acquisition module 421 and the second measurement point data, wherein the deviation = |second measurement point data-preset standard value| / preset standard value.

[0088] Further, such as Figure 5 As shown, the elimination unit 43 further includes:

[0089] An acquisition module 431 is configured to acquire a standard deviation and a mean of the second measurement point data based on the second measurement point data;

[0090] A utilization module 432 is configured to determine a normal value range using the mean and standard deviation of the acquisition module 431;

[0091] A quantity determination module 433 is configured to determine the quantity of the third measurement point data within the normal value range of the utilization module 432;

[0092] The number determination module 433 is configured to determine the probability based on the number and the total number of the third measurement point data;

[0093] The determination quantity module 433 is configured to determine the data obtained by the second screening if the probability is greater than or equal to a preset probability.

[0094] Further, such as Figure 5As shown, after determining the normal measurement point data of the power equipment, the device further includes a visualization unit 44, specifically including:

[0095] A first visualization data acquisition module 441 is configured to perform visualization processing on the normal measurement point data based on a time series to acquire a first visualization data graph, wherein the first visualization data graph includes feature data of the normal measurement point data;

[0096] A second visualization data acquisition module 442 is configured to perform visualization processing on the abnormal measurement point data based on a time series to acquire a second visualization data graph, wherein the abnormal measurement point data is characterized by obtaining normal measurement point data and excluding the measurement point data;

[0097] The display module 443 is used to add a button to the first visual data graph and the second visual data graph respectively, and the display mode of the first visual data graph of the first visual data acquisition module 441 and the second visual data graph of the second visual data acquisition module 442.

[0098] Further, such as Figure 5 As shown, before obtaining the measurement point data of the target category of the power equipment within the preset period, the device further includes a connection unit 45, which specifically includes:

[0099] The acquisition type module 451 is used to obtain the database type for storing the measurement point data;

[0100] An interface determination module 452 is configured to determine a corresponding data interface based on the database type of the acquisition type module 451;

[0101] The connection establishment module 453 is configured to configure connection parameters based on the data interface of the interface determination module 452 and establish a connection with the database to obtain the measurement point data of the target category.

[0102] Further, such as Figure 5 As shown, the connection establishment module 453 includes:

[0103] The acquisition type submodule 4531 is used to obtain the target power equipment name, target measurement point location information, and target data type of the measurement point data;

[0104] A traversal submodule 4532 is configured to traverse the database based on the target power equipment name and target measurement point location information of the acquisition type submodule 4531 to determine measurement point data of all data types;

[0105] The traversal submodule 4532 traverses the measuring point data of all data types using a target data type based on the measuring point data to obtain measuring point data of a target category.

[0106] Further, such as Figure 5 As shown, the acquisition unit 41 includes:

[0107] Utilizing module 411, for dynamically dividing the measurement point data using a sliding window technique to determine the measurement point data within a sliding window;

[0108] The trend determination module 412 is configured to determine the change trend of the measurement point data within the sliding window determined by the utilization module 411 by using a least squares method to fit a curve.

[0109] The present application also provides a processor for running a program, wherein the program is executed as follows when it is run: Figure 1 and Figure 3 The method for obtaining measuring point data of electric power equipment.

[0110] In addition, the present application also provides an electronic device, which includes a processor and a memory, wherein the memory is used to store a program, and the processor is coupled to the memory and is used to run the program to perform the following operations: Figure 1 and Figure 3 The method for obtaining measuring point data of electric power equipment.

[0111] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0112] It is understood that the relevant features of the above-described methods and devices can be referenced to each other. In addition, the terms "first," "second," and so on in the above-described embodiments are used to distinguish between the various embodiments and do not represent the superiority or inferiority of each embodiment. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific operating processes of the above-described systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0113] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems may also be used together with the teachings herein. Based on the above description, it is apparent that the structure required for constructing such systems is suitable. In addition, the present application is not directed to any specific programming language. It should be understood that various programming languages may be utilized to implement the present application described herein, and the description of the specific languages above is provided for the purpose of disclosing the preferred embodiment of the present application.

[0114] In addition, the memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0115] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0116] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0118] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0119] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0120] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0121] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for obtaining measurement point data of power equipment, characterized in that: The method comprises: Obtain measurement point data of target categories of power equipment within a preset period and the corresponding change trends; Determine the time interval in which the rate of change in the change trend is continuously zero and the corresponding first measuring point data; If the time interval is greater than or equal to the preset time interval, the first measuring point data is removed from the measuring point data to obtain the second measuring point data; Filtering the data of the second measuring point, wherein the deviation from the preset standard value exceeds a preset deviation range, to obtain the data of the third measuring point; Fitting the normal value range of the power equipment measurement point data based on the second measurement point data, and performing a secondary screening on the third measurement point data according to the normal value range; The data obtained from the secondary screening and the data in the second measuring point data that are within a preset deviation range are determined as normal measuring point data of the power equipment.

2. The method according to claim 1, characterized in that The step of filtering the second measuring point data for data whose deviation from the preset standard value exceeds a preset deviation range to obtain the third measuring point data includes: Based on the power equipment operation standards, obtain the preset standard value; The deviation is calculated based on the preset standard value and the second measuring point data, wherein the deviation=|second measuring point data-preset standard value| / preset standard value.

3. The method according to claim 1, characterized in that The fitting of the normal value range of the electric power equipment measurement point data based on the second measurement point data, and performing a secondary screening on the third measurement point data according to the normal value range, includes: Obtaining a standard deviation and a mean of the second measuring point data according to the second measuring point data; Determine the normal range using the mean and standard deviation; Determine the number of the third measuring point data within the normal value range; determining the probability based on the number and the total number of the third measurement point data; If the probability is greater than or equal to the preset probability, the data obtained by the second screening is determined.

4. The method according to claim 1, wherein After determining that the data is normal measurement point data of the electric power equipment, the method further includes: Performing visualization processing on the normal measurement point data based on a time series to obtain a first visualization data graph, wherein the first visualization data graph includes feature data of the normal measurement point data; Performing visualization processing on the abnormal measuring point data based on the time series to obtain a second visualization data graph, wherein the abnormal measuring point data is characterized as data obtained by removing the normal measuring point data from the measuring point data; A button is added to the first visual data graph and the second visual data graph respectively, corresponding to the display mode of the first visual data graph and the second visual data graph.

5. The method according to claim 1, wherein Before obtaining the target category of measurement point data of the electric power equipment within the preset period, the method includes: Get the database type for storing measurement point data; Determining a corresponding data interface based on the database type; The connection parameters are configured based on the data interface and a connection is established with a database to obtain the measurement point data of the target category.

6. The method according to claim 5, characterized in that The configuring connection parameters based on the data interface and establishing a connection with a database to obtain measurement point data of a target category includes: Obtain the target power equipment name, target measurement point location information, and target data type of the measurement point data; Traversing the database based on the target power equipment name and the target measuring point location information to determine measuring point data of all data types; Based on the target data type of the measuring point data, the measuring point data of all data types are traversed to obtain the measuring point data of the target category.

7. The method according to claim 1, characterized in that The obtaining of target category measurement point data of electric power equipment within a preset period and corresponding change trends includes: Using a sliding window technique, the measuring point data is dynamically divided to determine the measuring point data within the sliding window; The least squares method is used to fit the curve to determine the change trend of the measurement point data within the sliding window.

8. A device for obtaining measurement point data of power equipment, characterized in that: The device comprises: An acquisition unit, used to acquire measurement point data of a target category of power equipment within a preset period and the corresponding change trend; The acquisition unit is configured to determine a time interval in which the rate of change in the change trend is continuously zero and corresponding first measuring point data; The determining unit is configured to remove the first measuring point data from the measuring point data to obtain the second measuring point data if the time interval is greater than or equal to a preset time interval; The determining unit is configured to filter the data of the second measuring point of the acquiring unit, the deviation of which from the preset standard value exceeds a preset deviation range, to obtain the data of the third measuring point; a rejection unit, configured to fit the normal value range of the power equipment measurement point data based on the second measurement point data of the determination unit, and perform a secondary screening on the third measurement point data according to the normal value range; The elimination unit is configured to determine the data obtained through the secondary screening and the data in the second measuring point data that are within a preset deviation range as normal measuring point data of the power equipment.

9. A storage medium, characterized in that: The storage medium is used to store a computer program, wherein when the computer program is running, it controls the device where the storage medium is located to execute the method for obtaining power equipment measurement point data according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device includes a processor and a memory, and the processor is used to call program instructions in the memory to execute the method for obtaining power equipment measurement point data according to any one of claims 1 to 7.

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