Method and system for detecting scada data, electronic equipment and storage medium

Abstract

The application discloses a kind of detection method, system, electronic equipment and storage medium of SCADA data.The detection method includes the following steps: obtaining the detection data of SCADA system acquisition needing detection, the detection data includes fan data or wind field data;According to the detection data, obtain the detection task corresponding to the detection data;Run the detection task to detect the detection data.The application can automatically obtain the wind turbine generator data collected by SCADA system, and automatically match the corresponding detection task according to the wind field data, and automatically complete the detection of wind turbine generator data according to the detection task, realize the automatic detection of wind turbine generator data collected by SCADA system, improve the detection efficiency of data detection, save labor cost.

Description

Technical Field

[0001] This invention relates to the field of data detection, and in particular to a method, system, electronic device, and storage medium for detecting SCADA data. Background Technology

[0002] Currently, SCADA (Supervisory Control and Data Acquisition) systems are computer-based DCS and power automation monitoring systems. They have a wide range of applications, including data acquisition and monitoring control, and process control in fields such as power, metallurgy, petroleum, chemical, gas, and railway. In power systems, SCADA systems are the most widely used and technologically mature. They play a crucial role in remote control systems, monitoring and controlling field equipment to achieve functions such as data acquisition, equipment control, measurement, parameter adjustment, and various signal alarms—the so-called "four remote" functions. RTU (Remote Terminal Unit) and FTU (Feeder Terminal Unit) are important components. They play a significant role in the comprehensive automation construction of modern substations.

[0003] The data collected by the SCADA system, including wind turbine data and wind farm data, can only be accurately verified manually. Manual verification is time-consuming, inefficient, and inaccurate, and results cannot be obtained in a timely and accurate manner. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art, which is that the accuracy of data collected by SCADA system is low and the detection efficiency is low, and to provide a solution.

[0005] The present invention solves the above-mentioned technical problems through the following technical solution:

[0006] A method for detecting SCADA data, the method comprising the following steps:

[0007] Acquire the data to be detected collected by the SCADA system, including wind turbine data or wind farm data;

[0008] Based on the data to be detected, obtain the detection task corresponding to the data to be detected;

[0009] The detection task is run to detect the data to be detected.

[0010] Preferably, the step of running the detection task to detect the data to be detected specifically includes:

[0011] The detection task is run at a preset time interval to detect the data corresponding to the detection task.

[0012] Preferably, the step of running the detection task to detect the data to be detected specifically includes:

[0013] Obtain multiple detection rules associated with the detection task;

[0014] The data to be detected is detected according to multiple detection rules.

[0015] Preferably, after the step of acquiring the data to be detected collected by the SCADA system, the detection method further includes:

[0016] The data to be detected is stored in different data tables according to the data type of the data to be detected;

[0017] Match the corresponding detection task to the data table according to the detection requirements;

[0018] The step of obtaining the detection task corresponding to the data to be detected specifically includes:

[0019] The detection task corresponding to the data table is obtained based on the data table.

[0020] Preferably, after the step of obtaining multiple detection rules associated with the detection task, the detection method further includes:

[0021] Determine whether the same field in the same data table corresponds to multiple detection rules; if so, obtain the priority of the multiple detection rules.

[0022] The steps of running the detection task to detect the data to be detected specifically include:

[0023] The same field of the same data table is detected sequentially according to the priority order of the multiple detection rules.

[0024] Preferably, after the step of running the detection task to detect the data to be detected, the detection method further includes:

[0025] Generate the detection results and write them into the database.

[0026] Preferably, after the step of writing the detection result into the database, the detection method further includes:

[0027] A multi-dimensional data quality report is generated based on the test results.

[0028] A SCADA data detection system, the detection system comprising:

[0029] The acquisition module is used to acquire the data to be detected collected by the SCADA system, including wind turbine data or wind farm data.

[0030] The acquisition module is also used to acquire a detection task corresponding to the data to be detected based on the data to be detected;

[0031] The detection module is used to run the detection task to detect the data to be detected.

[0032] Preferably, the detection module is further configured to run the detection task according to a preset time interval to detect the data corresponding to the detection task.

[0033] Preferably, the acquisition module is also used to acquire multiple detection rules associated with the detection task;

[0034] The detection module is also used to detect the data to be detected according to multiple detection rules.

[0035] The detection system also includes a data storage module and a matching module;

[0036] The data storage module is used to store the data to be detected into different data tables according to the data type of the data to be detected;

[0037] The matching module is used to match the corresponding detection task to the data table according to the detection requirements;

[0038] The acquisition module is also used to acquire the detection task corresponding to the data table based on the data table.

[0039] Preferably, the detection system further includes a judgment module;

[0040] The judgment module is used to determine whether the same field in the same data table corresponds to multiple detection rules. If so, the acquisition module is called.

[0041] The acquisition module is also used to acquire the priority of multiple detection rules;

[0042] The detection module further includes performing detection on the same field of the same data table in sequence according to the priority order of the multiple detection rules.

[0043] Preferably, the detection system further includes a result generation module;

[0044] The result generation module is used to generate detection results and write the detection results into the database.

[0045] Preferably, the result generation module is further configured to generate a multi-dimensional data quality report based on the detection results.

[0046] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the SCADA data detection method described above.

[0047] A computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the SCADA data detection method described above.

[0048] The positive and progressive effects of this invention are as follows: it can automatically acquire wind turbine generator data collected by the SCADA system, automatically match the corresponding detection task according to the wind field data, and automatically complete the detection of wind turbine generator data according to the detection task, thereby realizing automated detection of wind turbine generator data collected by the SCADA system, improving the detection efficiency of data detection, and saving labor costs. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the first process of the SCADA data detection method according to Embodiment 1 of the present invention.

[0050] Figure 2 This is a schematic diagram of the second process of the SCADA data detection method in Embodiment 1 of the present invention.

[0051] Figure 3 This is a functional module structure diagram of the SCADA data detection system of Embodiment 2 of the present invention.

[0052] Figure 4 This is a flowchart illustrating the specific implementation of the SCADA data detection system in Embodiment 2 of the present invention.

[0053] Figure 5 This is a schematic diagram of the electronic device according to Embodiment 3 of the present invention. Detailed Implementation

[0054] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein.

[0055] Example 1

[0056] This embodiment provides a method for detecting SCADA data. See [link to relevant documentation] Figure 1 As shown, the detection method includes the following steps:

[0057] S1. Obtain the data to be detected collected by the SCADA system, including wind turbine data or wind farm data.

[0058] S2. Obtain the detection task corresponding to the data to be detected.

[0059] S3. Run the detection task to detect the data to be detected.

[0060] It should be noted that the SCADA system can collect different types of data, including wind turbine data or wind farm data. Wind turbine data can include wind turbine generator data. Data detection is performed by acquiring the data to be detected collected by the SCADA system.

[0061] Users can manually configure the detection tasks corresponding to the data to be tested. After configuration, users can directly obtain the corresponding detection tasks based on the data to be tested. The data to be tested may include wind turbine data, such as: pitch angle, motor current and voltage, converter active and reactive power, coolant temperature, chiller start-up status, gearbox coolant temperature, filter pump status, active / reactive power statistics from the grid side, generator speed, ambient temperature statistics, shutdown / restart status, fault codes, etc. Detection tasks may include nine items: data interval time detection, null value detection, accuracy detection, type detection, value range detection, code detection, correlation detection, deviation detection, and data uniqueness detection.

[0062] Furthermore, in one embodiment, step S3 may include:

[0063] The detection task is run at a preset time interval to detect the data corresponding to the detection task.

[0064] By setting a preset time interval, the detection task can be run continuously to detect the data to be detected, thus achieving continuous detection. Users can manually set the preset time interval.

[0065] Furthermore, in another embodiment, such as Figure 2 As shown, step S3 may include:

[0066] S31. Obtain multiple detection rules associated with the detection task;

[0067] S32. Perform testing on the data to be tested according to multiple testing rules.

[0068] It should be noted that the detection rules can include continuity detection, non-empty detection, precision detection, type detection, value range detection, code detection, and association detection; detailed examples of detection rules are as follows:

[0069] Continuity check: Configure the time interval {"interval":"30"}, with the interval unit being seconds. The data continuity of this field will be checked based on this interval (only for 30s, 10min, and 1s tables; if the time interval is configured as 30s, the time interval must be equal to 30s).

[0070] Not null check: Directly checks whether the data in this field contains null values ​​and NULL (a value that is reserved in calculations to indicate that a pointer does not reference a valid object);

[0071] Precision check: A JSON (Lightweight Data Interchange) configuration `{"accuracy":"0.00"}` is used to parse the decimal precision in the configuration and check whether the data in that field conforms to that precision.

[0072] Type detection: Directly checks whether the data type of this field is consistent with the configured data type (data type: double, string, int);

[0073] Value range detection: The JSON configuration {"max":"100", "min":"20} is parsed to determine whether the data in the field falls within this range;

[0074] Code inspection: Parse the list of codes in the JSON configuration {"F001", "F002", "F003"} and check if the data of the specified field is in this list;

[0075] Association detection: The JSON configuration {"tablename":"windfield", "column":"name"} is parsed to determine if the data for that field can be found in the name field of the windfield table;

[0076] Indicator standard deviation detection: JSON configuration {"max":"100", "min":"20", "range":"20%"}, parse the maximum and minimum values ​​and the range of numerical fluctuation in the configuration, and detect whether the data of this field is within this range (detect whether the value is between 16 and 120);

[0077] Uniqueness check: Check one or more fields (multiple fields are separated by commas). For example, to check the duk field, the JSON configuration is {"duk"}; to check whether the combination of the ct and duk fields is unique in the table, the JSON configuration is {"duk", "ct"}.

[0078] Furthermore, after step S1, as... Figure 2 As shown, the detection method also includes:

[0079] S4. Store the data to be detected in different data tables according to the data type of the data to be detected.

[0080] S5. Match the corresponding detection task to the data table according to the detection requirements.

[0081] It should be noted that the data type to be tested can include file type data and data structure type data. File type data and data structure type data can be stored in different databases. For example, file type data has low testing efficiency but fast storage speed, so file type data can be stored in a Redis database; data structure type data has high testing efficiency, but it needs to be cleaned before testing, i.e., stored in categories. Data structure type data can be cleaned and stored in a MongoDB database.

[0082] Classifying and storing the data to be tested according to its data type can improve the efficiency of obtaining the data and thus improve the efficiency of data testing.

[0083] Further, in one embodiment, step S2 may include:

[0084] Obtain the detection task corresponding to the data table.

[0085] Furthermore, after step S31, such as Figure 2 As shown, the detection method also includes:

[0086] S33. Determine whether the same field in the same data table corresponds to multiple detection rules. If yes, execute S331; otherwise, execute S332. For example, the blade angle field needs to be detected by multiple rules, such as accuracy detection to check the angle accuracy; continuity detection to check whether data is acquired every 30 seconds; and deviation detection to check whether the acquired field is within a reasonable range, etc.

[0087] S331. Obtain the priority of multiple detection rules. Execute step S32 after step S331.

[0088] S332. Perform detection on the fields of the data table according to the obtained detection rules. Step S36 is executed after step S332.

[0089] The steps in S32 may also include:

[0090] The same field in the same data table is tested sequentially according to the priority of multiple detection rules.

[0091] It should be noted that detection rules and priority information can be written into the data_check_rules table, and task priority can be configured through the AULT_MIN_DATA table. The smaller the number, the higher the priority level.

[0092] Following steps S32 and S332, the detection method further includes:

[0093] S6. Generate the detection results and write them into the database.

[0094] The test results can be automatically sent to the testing personnel, making it convenient for them to carry out inspections and maintenance based on the test results. The test results can also be sent to the testing personnel via email.

[0095] S7. Generate multi-dimensional data quality reports based on the test results.

[0096] It should be noted that the system can automatically perform tests on the data to be tested, and automatically generate test results after the tests are completed. Then, it can automatically generate multi-dimensional data quality reports based on the test results as needed, which are convenient for testing personnel to review.

[0097] This embodiment can automatically acquire wind turbine generator data collected by the SCADA system, automatically match the corresponding detection task according to the wind field data, and automatically complete the detection of wind turbine generator data according to the detection task. This realizes automated detection of wind turbine generator data collected by the SCADA system, improves the detection efficiency of data detection, and saves labor costs.

[0098] Example 2

[0099] This embodiment provides a SCADA data detection system. The SCADA data detection method provided in Embodiment 1 can be implemented using the SCADA data detection system provided in this embodiment.

[0100] See Figure 3 As shown, the detection system includes:

[0101] The acquisition module 1 is used to acquire the data to be detected collected by the SCADA system, including wind turbine data or wind farm data.

[0102] The acquisition module 1 is also used to acquire the detection task corresponding to the data to be detected based on the data to be detected.

[0103] The detection module 2 is used to run the detection task to detect the data to be detected.

[0104] Furthermore, the detection module 2 is also used to run the detection task according to a preset time interval to detect the data corresponding to the detection task.

[0105] Furthermore, the acquired module 1 is also used to acquire multiple detection rules associated with the detection task.

[0106] Furthermore, the detection module 2 is also used to detect the data to be detected according to multiple detection rules.

[0107] Furthermore, the detection system also includes a data storage module 3 and a matching module 4.

[0108] The data storage module 3 is used to store the data to be detected into different data tables according to the data type of the data to be detected.

[0109] The matching module 4 is used to match the corresponding detection task to the data table according to the detection requirements.

[0110] The acquisition module 1 is also used to acquire the detection task corresponding to the data table according to the data table.

[0111] Furthermore, the detection system also includes a judgment module 5.

[0112] The judgment module 5 is used to determine whether the same field in the same data table corresponds to multiple detection rules. If so, the acquisition module 1 is called.

[0113] The acquisition module 1 is also used to acquire the priority of multiple detection rules.

[0114] The detection module further includes performing detection on the same field of the same data table in sequence according to the priority order of the multiple detection rules.

[0115] Furthermore, the detection system also includes a result generation module 6;

[0116] The result generation module 6 is used to generate detection results and write the detection results into the database.

[0117] Furthermore, the result generation module 6 is also used to generate a multi-dimensional data quality report based on the detection results.

[0118] It should be noted that the working process of the SCADA data detection system provided in this embodiment can be described through one implementation method. In this implementation method, the detection task is referred to as an inspection task, and the detection rule is referred to as an inspection rule; they have the same meaning. See also Figure 4As shown, the process begins with configuring the data source (i.e., the data collected by the SCADA system, referred to as the data source in this implementation). This configuration involves configuring the data to be tested. In this embodiment, an interface for configuring the data source is provided, allowing testing personnel to easily observe the data and manage the database and tables of the data source, i.e., cleaning and storing the data to be tested, facilitating quick retrieval of the corresponding data during testing. Next, inspection rules are configured, with a configuration interface for easy configuration and viewing by testing personnel. Then, team member information is configured, with different team members responsible for different data, facilitating timely transmission of test results to the corresponding team members. Scheduled inspection tasks are configured, with preset time intervals set. Inspection tasks can be run at set intervals to test the data. After testing, the results are stored in the database. Multi-dimensional data quality reports can be generated based on the test results, displayed through the interface for easy viewing by testing personnel. The inspection results can also be sent to preset team members via email, enabling team members to resolve issues based on the test results.

[0119] This embodiment can automatically acquire wind turbine generator data collected by the SCADA system, automatically match the corresponding detection task according to the wind field data, and automatically complete the detection of wind turbine generator data according to the detection task. This realizes automated detection of wind turbine generator data collected by the SCADA system, improves the detection efficiency of data detection, and saves labor costs. This embodiment also provides a visual configuration interface, which is convenient for inspection personnel to operate and view the detection results.

[0120] Example 3

[0121] Figure 5 This is a schematic diagram of an electronic device provided in Embodiment 3 of the present invention. It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the SCADA data detection method of Embodiment 1 described above. Figure 5 The electronic device 30 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0122] The electronic device 30 may be in the form of a general-purpose computing device, such as a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including memory 32 and processor 31).

[0123] Bus 33 includes a data bus, an address bus, and a control bus.

[0124] The memory 32 may include volatile memory, such as random access memory (RAM) 321 and / or cache memory 322, and may further include read-only memory (ROM) 323.

[0125] The memory 32 may also include a program / utility 325 having a set (at least one) of program modules 324, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0126] The processor 31 executes various functional applications and data processing by running computer programs stored in the memory 32, such as the SCADA data detection method of Embodiment 1 of the present invention.

[0127] Electronic device 30 can also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 35. Furthermore, the model-generated device 30 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public network, such as the Internet) via network adapter 36. As shown, network adapter 36 communicates with other modules of the model-generated device 30 via bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0128] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0129] Example 4

[0130] The present invention also provides a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the SCADA data detection method of the aforementioned embodiment 1.

[0131] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0132] In a possible implementation, the present invention can also be implemented as a program product comprising program code, which, when the program product is run on a terminal device, is used to cause the terminal device to perform the steps of the SCADA data detection method of Embodiment 1.

[0133] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A method for detecting SCADA data, characterized in that, The detection method includes the following steps: Acquire the data to be detected collected by the SCADA system, including wind turbine data or wind farm data; Based on the data to be detected, obtain the detection task corresponding to the data to be detected; The detection task is run to detect the data to be detected; The steps of running the detection task to detect the data to be detected specifically include: Obtain multiple detection rules associated with the detection task; The data to be detected is detected according to multiple detection rules; The detection rules include continuity detection, non-empty detection, precision detection, type detection, value range detection, code detection, and association detection; After the step of acquiring the data to be detected collected by the SCADA system, the detection method further includes: The data to be detected is stored in different data tables according to the data type of the data to be detected; Match the corresponding detection task to the data table according to the detection requirements; The step of obtaining the detection task corresponding to the data to be detected specifically includes: Obtain the detection task corresponding to the data table according to the data table; After the step of obtaining multiple detection rules associated with the detection task, the detection method further includes: Determine whether the same field in the same data table corresponds to multiple detection rules; if so, obtain the priority of the multiple detection rules. The step of detecting the data to be detected according to multiple detection rules specifically includes: The same field of the same data table is detected sequentially according to the priority order of the multiple detection rules.

2. The SCADA data detection method as described in claim 1, characterized in that, The steps of running the detection task to detect the data to be detected specifically include: The detection task is run at a preset time interval to detect the data corresponding to the detection task.

3. The SCADA data detection method as described in claim 1, characterized in that, After the step of running the detection task to detect the data to be detected, the detection method further includes: Generate the detection results and write them into the database.

4. The SCADA data detection method as described in claim 3, characterized in that, After the step of writing the detection result into the database, the detection method further includes: A multi-dimensional data quality report is generated based on the test results.

5. A SCADA data detection system, characterized in that, The detection system includes: The acquisition module is used to acquire the data to be detected collected by the SCADA system, including wind turbine data or wind farm data. The acquisition module is also used to acquire a detection task corresponding to the data to be detected based on the data to be detected; The detection module is used to run the detection task to detect the data to be detected; The acquisition module is also used to acquire multiple detection rules associated with the detection task; The detection module is also used to detect the data to be detected according to multiple detection rules; The detection rules include continuity detection, non-empty detection, precision detection, type detection, value range detection, code detection, and association detection; The detection system also includes a data storage module and a matching module; The data storage module is used to store the data to be detected into different data tables according to the data type of the data to be detected; The matching module is used to match the corresponding detection task to the data table according to the detection requirements; The acquisition module is also used to acquire the detection task corresponding to the data table according to the data table; The detection system also includes a judgment module, which is used to determine whether the same field in the same data table corresponds to multiple detection rules. If so, the acquisition module is called. The acquisition module is also used to acquire the priority of multiple detection rules; The detection module further includes performing detection on the same field of the same data table in sequence according to the priority order of the multiple detection rules.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the SCADA data detection method as described in any one of claims 1-4.

7. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the SCADA data detection method as described in any one of claims 1-4.

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