Data processing method and device

Abstract

The invention provides a data processing method and device. The data processing method comprises the following steps: acquiring operation data of the wind generating set; identifying the data type of the operation data; and performing time alignment processing on the operation data according to the data type of the operation data to obtain processed data, thereby improving the orderliness of the data.

Description

Technical Field

[0001] The present disclosure relates to the technical field of wind power generation. More specifically, the present disclosure relates to a data processing method and device. Background Art

[0002] At present, integrated auxiliary control has begun to be developed as a control core of wind turbines. The core functions of the system may include: data collection and processing, scheduling and execution of diagnostic models, uploading of diagnostic results and control of wind turbines. Because integrated auxiliary control will collect sensory data from different devices and different installation locations, how to save the data from these data sources in the database in chronological order is a difficult task. Summary of the invention

[0003] According to an exemplary embodiment of the present disclosure, a data processing method is provided, including: acquiring operating data of a wind turbine generator set; identifying a data type of the operating data; and performing time alignment processing on the operating data according to the data type of the operating data to obtain processed data.

[0004] Optionally, after identifying the data type of the operating data, the method further includes: determining a data structure corresponding to the data type; and performing structured processing on the operating data based on the operating data structure.

[0005] Optionally, the data type includes a digital signal type and an analog signal type. The analog signal type may correspond to a first data structure, and the digital signal type may correspond to a second data structure. The first data structure may include a first timestamp and first data, and the second data structure may include a second timestamp, a heartbeat signal, and second data. The first timestamp indicates the time when the data is acquired, and the second timestamp indicates the time of the data acquisition system when the second data is converted from analog to digital.

[0006] Optionally, the step of performing structured processing on the operating data based on the data structure includes: when the data structure is a first data structure, processing the operating data into first structured processing data including a first timestamp and the operating data; when the data structure is a second data structure, processing the operating data into second structured processing data including a second timestamp, a heartbeat signal and the operating data.

[0007] Optionally, performing time alignment processing on the running data according to the data type of the running data includes: determining an alignment duration based on a basic data packet of a data source where the running data is located, wherein the basic data packet includes a timestamp of a first packet of data from the data source; and performing time alignment processing on the running data based on the alignment duration.

[0008] Optionally, the step of performing time alignment processing on the operating data according to the data type of the operating data also includes: in response to detecting a deviation in the time alignment processing, updating the alignment duration by adjusting the basic data packet; and performing time alignment processing on the operating data based on the updated alignment duration.

[0009] Optionally, the step of performing time alignment processing on the running data based on the alignment duration may include: when the data type is an analog signal type, performing time alignment processing on the running data based on the alignment duration; when the data type is a digital signal type, adjusting the alignment duration based on a second timestamp and a heartbeat signal, and performing time alignment processing on the running data based on the adjusted alignment duration.

[0010] Optionally, after acquiring the operating data of the wind turbine generator set, the method may further include: in response to detecting the existence of lost operating data, performing data interpolation on the acquired operating data according to a predetermined data interpolation principle.

[0011] Optionally, after acquiring the operating data of the wind turbine generator set, the method further includes: caching the operating data, and after performing time alignment processing on the operating data to obtain the processed data, the method further includes: storing the processed data in batches.

[0012] According to an exemplary embodiment of the present disclosure, there is provided a data processing device, including: a data acquisition unit, configured to acquire operating data of a wind turbine generator set; a type identification unit, configured to identify a data type of the operating data; and a time alignment unit, configured to perform time alignment processing on the operating data according to the data type of the operating data to obtain processed data.

[0013] Optionally, the device may further include a structure processing unit configured to: determine a data structure corresponding to the data type; and perform structured processing on the operation data based on the operation data structure.

[0014] Optionally, the data type includes a digital signal type and an analog signal type. The analog signal type may correspond to a first data structure, and the digital signal type may correspond to a second data structure. The first data structure may include a first timestamp and first data, and the second data structure may include a second timestamp, a heartbeat signal, and second data. The first timestamp indicates the time when the data is acquired, and the second timestamp indicates the time of the data acquisition system when the second data is converted from analog to digital.

[0015] Optionally, the structure processing unit may be configured to: when the data structure is a first data structure, process the running data into first structure processing data including a first timestamp and the running data; and when the data structure is a second data structure, process the running data into second structure processing data including a second timestamp, a heartbeat signal and the running data.

[0016] Optionally, the time alignment unit may be configured to: determine the alignment duration based on a basic data packet of a data source where the running data is located, wherein the basic data packet includes a timestamp of a first packet of data from the data source; and perform time alignment processing on the running data based on the alignment duration.

[0017] Optionally, the time alignment unit may be further configured to: in response to detecting a deviation in the time alignment processing, update the alignment duration by adjusting the basic data packet; and perform time alignment processing on the running data based on the updated alignment duration.

[0018] Optionally, the time alignment unit can be configured to: when the data type is an analog signal type, perform time alignment processing on the running data based on the alignment duration; when the data type is a digital signal type, adjust the alignment duration based on a second timestamp and a heartbeat signal, and perform time alignment processing on the running data based on the adjusted alignment duration.

[0019] Optionally, the device may further include a data interpolation unit configured to: after acquiring the operating data of the wind turbine generator set, in response to detecting the existence of lost operating data, perform data interpolation on the acquired operating data according to a predetermined data interpolation principle.

[0020] Optionally, the device may further include a data cache unit, configured to: after acquiring the operating data of the wind turbine generator set, cache the operating data, and the device may further include a batch storage unit, configured to: after performing time alignment processing on the operating data and obtaining the processed data, batch store the processed data.

[0021] According to an exemplary embodiment of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the data processing method according to the exemplary embodiment of the present disclosure is implemented.

[0022] According to an exemplary embodiment of the present disclosure, there is provided a computing device, including: at least one processor; and at least one memory storing a computer program, wherein when the computer program is executed by the at least one processor, a data processing method according to an exemplary embodiment of the present disclosure is implemented.

[0023] According to an exemplary embodiment of the present disclosure, a computer program product is provided, and instructions in the computer program product can be executed by a processor of a computer device to implement a data processing method according to an exemplary embodiment of the present disclosure.

[0024] According to the data processing method and device of the exemplary embodiment of the present disclosure, the operating data of the wind turbine generator set is first acquired, the data type of the operating data is identified, and then the operating data is time-aligned according to the data type of the operating data to obtain processed data, thereby improving the orderliness of the data.

[0025] Additional aspects and / or advantages of the present general inventive concept will be set forth in part in the following description and in part will be apparent from the description or may be learned through practice of the present general inventive concept. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and other objects and features of the exemplary embodiments of the present disclosure will become more apparent through the following description in conjunction with the accompanying drawings which exemplarily illustrate the embodiments, in which:

[0027] Figure 1 A flowchart showing a data processing method according to an exemplary embodiment of the present disclosure;

[0028] Figure 2A An example of a data structure showing a doubly linked list;

[0029] Figure 2B A schematic diagram illustrating data processing and storage according to an exemplary embodiment of the present disclosure;

[0030] Figure 3 A block diagram showing a data processing apparatus according to an exemplary embodiment of the present disclosure; and

[0031] Figure 4 A schematic diagram illustrating a computing device according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0032] Reference will now be made in detail to exemplary embodiments of the present disclosure, examples of which are shown in the accompanying drawings, wherein like reference numerals refer to like parts throughout. The embodiments will be described below with reference to the drawings in order to explain the present disclosure.

[0033] Figure 1 A flow chart showing a data processing method according to an exemplary embodiment of the present disclosure. Figure 1The data processing method in the invention can be executed by the integrated auxiliary control system of the wind turbine generator set (also referred to as the auxiliary control system). The auxiliary control system includes a variety of data acquisition devices that can be used to collect the operation data of the wind turbine generator set (the data of each data acquisition device is used as a data source). The auxiliary control system can obtain the data of each data source respectively, and process the obtained data to store the processed data in the database, so as to avoid the data being in a disorderly state in the database.

[0034] Reference Figure 1 In step S101, the operation data of the wind turbine generator set is obtained. For example, the operation data of the wind turbine generator set is obtained through a data acquisition device in the auxiliary control system (for example, a blade vibration monitoring (BMS) sensor).

[0035] In an exemplary embodiment of the present disclosure, after acquiring the operating data of the wind turbine generator set in step S101, the method may further include: caching the operating data.

[0036] Here, the operation data of the wind turbine generator set obtained can also be called raw data, which is stored in the raw data buffer area. The raw data buffer area is used to store the raw data pushed in real time by different data sources. Here, a multi-threaded design can be adopted, and each data source has a separate data receiving thread, and the received raw data is temporarily stored in the raw data buffer area. In other words, the operation data of the wind turbine generator set can be obtained from multiple data sources.

[0037] In step S102, the data type of the operation data is identified. Various data type identification technologies may be used for identification, and the present disclosure is not limited thereto.

[0038] Here, the data type may include a digital signal type and an analog signal type.

[0039] Specifically, the operating data of wind turbines obtained include digital signals and analog signals, including both analog input and digital input, network card, etc. The differences in various data sources and data interfaces cause the time delay and data alignment of the data itself to be inconsistent. The characteristics of analog signals are strong timing and low delay, but more resources are required for processing; digital signals have a relatively large time delay because they have undergone a first-level digital processing, and the delays of different digital interfaces are also inconsistent. For example, RS-485 transmission data can be stable at the millisecond level, but the delay of the network port communication itself is uncertain, so data from different data sources should be treated differently.

[0040] In an exemplary embodiment of the present disclosure, after the data type of the operating data is identified in step S102 , a data structure corresponding to the data type may be determined; and the operating data may be structured based on the data structure.

[0041] In an exemplary embodiment of the present disclosure, the analog signal type may correspond to a first data structure, and the digital signal type may correspond to a second data structure. The first data structure may include a first timestamp and first data, and the second data structure may include a second timestamp, a heartbeat signal, and second data. The first timestamp indicates the time when the first data is acquired, and the second timestamp indicates the time of the data acquisition system when the second data is converted from analog to digital, thereby improving the accuracy of data processing through the corresponding data structure.

[0042] Specifically, for analog signals, data acquisition uses the acquisition board that comes with the auxiliary control system of the wind turbine generator set. The timestamp is the time system of the auxiliary control system itself, and its timeliness and reliability are relatively high. Therefore, the data storage structure is simple and only includes two parts: timestamp and data. The timestamp is used to record the time when the data reaches the auxiliary control, and the data refers to the data value after the model signal is sampled.

[0043] For digital signals, due to the delay of analog-to-digital conversion and data transmission, the timestamp of the digital signal cannot use the auxiliary control system's own time system. Instead, it uses the time of the data acquisition system during analog-to-digital conversion. In order to reduce data time deviation, a timing clock needs to be added inside the digital collector to generate self-incrementing heartbeat data. This auxiliary clock is used to ensure the consistency of data and timestamp. Therefore, in addition to the timestamp, a heartbeat signal is added to the digital signal data structure to reduce time deviation.

[0044] In an exemplary embodiment of the present disclosure, the step of performing structured processing on the running data based on the data structure may include: when the data structure is a first data structure, processing the running data into first structured processing data including a first timestamp and the running data; when the running data structure is a second data structure, processing the running data into second structured processing data including a second timestamp, a heartbeat signal and the running data, thereby improving the accuracy of the structure processing.

[0045] In step S103, time alignment processing is performed on the operating data according to the data type of the operating data to obtain processed data.

[0046] In an exemplary embodiment of the present disclosure, the step of performing time alignment processing on the operation data according to the data type of the operation data may include: determining the alignment duration based on a basic data packet of a data source where the operation data is located, wherein the basic data packet includes a timestamp of a first packet of data from the data source; performing time alignment processing on the operation data based on the alignment duration, thereby improving the accuracy of the time alignment. Here, the basic data packet may be cached in a basic data packet cache area.

[0047] In an exemplary embodiment of the present disclosure, the step of performing time alignment processing on the operation data according to the data type of the operation data may also include: in response to detecting that there is a deviation in the time alignment processing, updating the alignment duration by adjusting the basic data packet; performing time alignment processing on the operation data based on the updated alignment duration, thereby improving the accuracy of the time alignment by updating the alignment duration to make the alignment duration more optimized. Various detection techniques can be used to detect the deviation, and the present disclosure does not limit this. The size of the basic data packet can be increased or decreased, thereby increasing or shortening the alignment duration.

[0048] In an exemplary embodiment of the present disclosure, the step of performing time alignment processing on running data based on the alignment duration may include: when the data type is an analog signal type, performing time alignment processing on the running data based on the alignment duration; when the data type is a digital signal type, adjusting the alignment duration based on the second timestamp and the heartbeat signal, and performing time alignment processing on the running data based on the adjusted alignment duration, thereby distinguishing the data types and performing time alignment processing separately.

[0049] In an exemplary embodiment of the present disclosure, after obtaining the operating data of the wind turbine generator set in step S101, it may also include: in response to detecting the existence of lost operating data, data interpolation is performed on the acquired operating data according to a predetermined data interpolation principle, so as to avoid obvious data step jump problems. For a data source with missing data, data interpolation is performed according to the data interpolation principle, and the interpolation result is stored in the original data buffer area, waiting for use when the data is aligned again. Various existing technologies can be used to detect data loss. The predetermined data interpolation principle can be any data interpolation principle (for example, linear interpolation), and the present disclosure does not limit this. When performing data interpolation, a multi-threaded design can be used to perform data interpolation on different data sources respectively.

[0050] As examples, basic principles of data alignment may include, but are not limited to, the following principles:

[0051] a) The basic unit time of all time series data time alignment is, for example, 20 ms. In addition, the basic unit time of alignment can also be other durations, which is not limited in the present disclosure.

[0052] b) When starting up, for a data source, the timestamp of the first data packet of the data source is used as the basic data packet, and subsequent data alignment is performed based on this.

[0053] c) If it is an analog signal, the timestamp is considered to be real and is aligned directly according to the timestamp.

[0054] d) If it is a digital signal, it needs to be compared with the basic data packet (i.e., timestamp). If the time spanned by the heartbeat signal matches the timestamp, for example, the timestamp is 14:20:20 on June 14, 2023, 100 milliseconds, the heartbeat value of the heartbeat signal is 100, and the timestamp of the new queue is: 14:20:20 on June 14, 2023, 120 milliseconds, the heartbeat value is 101, and the heartbeat signal differs by 1 time interval of exactly 20ms. The data is considered to be true and directly aligned with other data in the cache. If the timestamp and the heartbeat signal have a deviation greater than 20ms, the basic time needs to be adjusted. For example, in the example above, if the heartbeat signal is 102, the theoretical difference between the two timestamps is 40ms, and the actual difference is 20ms. At this time, it is necessary to compare whether the time deviation of the next set of data is 20ms more. If so, the basic time needs to be adjusted to the new input value, otherwise the original timestamp is maintained. The time tag deviation of different data sources is obtained by statistical means, and the different data source times are regularly inferred and compensated to solve the problem of no standard time synchronization mechanism.

[0055] e) The aligned data is cached to a certain length and then stored in batches. The current default value is 10 (it can also be other values, and the present disclosure does not impose any restrictions on this). This reduces the number of storage times and reduces the read and write pressure on the database.

[0056] f) The timestamp of data entry must be an integer multiple of the data sampling period. If the data is collected in a period of 20ms, the timestamp in the database must be 100 milliseconds at 14:20:20 on June 14, 2023, 120 milliseconds at 14:20:20 on June 14, 2023, 140 milliseconds at 14:20:20 on June 14, 2023, 160 milliseconds at 14:20:20 on June 14, 2023, 180 milliseconds at 14:20:20 on June 14, 2023, 200 milliseconds at 14:20:20 on June 14, 2023, and 101 milliseconds at 14:20:20 on June 14, 2023, or 110 milliseconds at 14:20:20 on June 14, 2023. This is convenient for data storage, retrieval and viewing.

[0057] g) If data is lost, for example, the heartbeat signal of the previous data is 101, and the heartbeat signal of the next set of data is 103, the heartbeat signal is not filled in, but the timestamp must be filled in; the data content is filled with the average value of the previous set of data and this data.

[0058] h) If two identical data appear, you need to select the data with a timestamp closer to the sampling period for filling.

[0059] In an exemplary embodiment of the present disclosure, after performing time alignment processing on the operation data in step S103 to obtain processed data, the method may further include: storing the processed data in batches. Here, the processed data may be stored in batches in an ordered data buffer area.

[0060] When storing in batches, a data cache mechanism can be used. Data is received in fixed length and written into the database in batches after alignment. The cache uses a bidirectional circular linked list data structure, and the size of each channel cache space can be set dynamically.

[0061] Figure 2A An example of a doubly linked list data structure is shown. Figure 2B A schematic diagram showing data processing and storage according to an exemplary embodiment of the present disclosure.

[0062] The cabin vibration monitoring (CMS) 150MB (to meet 1 minute requirements), tower vibration monitoring (TMS) 1MB, blade vibration monitoring (BMS) 2MB, and open platform communications unified architecture (OPCUA) 2MB data structure can be preset.

[0063] like Figure 2A As shown in the figure, a bidirectional circular linked list is a type of linear list structure, also known as a bidirectional circular linked list. This data structure enables a large amount of data to be recorded in memory without going through a database. A one-way linked list can only search in one direction, while a bidirectional linked list can search forward or backward. A bidirectional linked list has three integer values: value (or data), backward node link, and forward node link. Figure 2A The curved arrows in the represent forward or backward node links.

[0064] A single-thread design can be used. When the aligned data reaches a certain amount, it is written into the database in batches. Through the data cache mechanism, a section of data is saved in the memory to avoid data loss caused by the inability to obtain data from a certain data source in real time due to external interference.

[0065] like Figure 2B As shown, when acquiring the operation data of the wind turbine generator set, data from multiple data sources are received by the data receiving module and stored in the original data buffer area. After determining the data type of the operation data, the data alignment module can perform data alignment processing on the data in the original data buffer area based on the basic data packet in the basic data buffer area according to the determined data type of the operation data, and the processed data is stored in the ordered data buffer area.

[0066] like Figure 2BAs shown, when the data in the ordered data buffer area meets the storage condition (for example, reaches a predetermined number), the data in the ordered data buffer area is written into the database through the data writing module. In addition, in the process of data alignment, in response to detecting that there is a deviation in the time alignment process, it can be determined whether the basic data packet is abnormal. When the basic data packet is abnormal, the basic data packet in the basic data buffer area is adjusted by the basic data packet adjustment module. In addition, in the process of data alignment, in response to detecting that there is lost running data, it can be determined whether the basic data packet is abnormal. When it is determined that the basic data packet is abnormal, the data in the original data buffer area can also be interpolated by the interpolation module. For data sources with lost data, data interpolation is performed according to the data interpolation principle, and the interpolation result is stored in the original data buffer area, waiting for use when data alignment is performed again. The predetermined data interpolation principle can be any data interpolation principle, and the present disclosure does not limit this. When performing data interpolation, a multi-threaded design can be used to perform data interpolation on different data sources respectively.

[0067] The above has been combined Figures 1 to 2B The data processing method according to the exemplary embodiment of the present disclosure is described. Figure 3 A data processing apparatus and units thereof according to exemplary embodiments of the present disclosure are described.

[0068] Figure 3 A block diagram illustrating a data processing apparatus according to an exemplary embodiment of the present disclosure.

[0069] Reference Figure 3 The data processing device includes a data acquisition unit 31, a type identification unit 32, and a time alignment unit 33.

[0070] The data acquisition unit 31 is configured to acquire operating data of the wind turbine generator set.

[0071] In an exemplary embodiment of the present disclosure, the data processing device may further include a data interpolation unit (not shown), which is configured to: after acquiring the operating data of the wind turbine generator set, in response to detecting the existence of lost operating data, perform data interpolation on the acquired operating data according to a predetermined data interpolation principle.

[0072] In an exemplary embodiment of the present disclosure, the data processing device may further include a data cache unit (not shown) configured to cache the operation data after acquiring the operation data of the wind turbine generator set.

[0073] The type identification unit 32 is configured to identify the data type of the operation data. Here, the data type may include a digital signal type and an analog signal type.

[0074] In an exemplary embodiment of the present disclosure, the analog signal type may correspond to a first data structure, and the digital signal type may correspond to a second data structure. The first data structure may include a first timestamp and first data, and the second data structure may include a second timestamp, a heartbeat signal, and second data. The first timestamp indicates the time when the first data is acquired, and the second timestamp indicates the time of the data acquisition system when the second data is converted from analog to digital.

[0075] In an exemplary embodiment of the present disclosure, the data processing apparatus may further include a structure processing unit (not shown) configured to: determine a data structure corresponding to a data type; and perform structured processing on the operation data based on the operation data structure.

[0076] In an exemplary embodiment of the present disclosure, the structure processing unit may be configured to: when the data structure is a first data structure, process the running data into first structure-processed data including a first timestamp and the running data; and when the data structure is a second data structure, process the running data into second structure-processed data including a second timestamp, a heartbeat signal and the running data.

[0077] The time alignment unit 33 is configured to perform time alignment processing on the operation data according to the data type of the operation data to obtain processed data. In an exemplary embodiment of the present disclosure, the time alignment unit 33 may be configured to: determine the alignment duration based on the basic data packet of the data source where the operation data is located. Here, the basic data packet may include the timestamp of the first packet of data of the data source; and perform time alignment processing on the operation data based on the alignment duration.

[0078] In an exemplary embodiment of the present disclosure, the time alignment unit 33 may also be configured to: in response to detecting a deviation in the time alignment processing, update the alignment duration by adjusting the basic data packet; and perform time alignment processing on the running data based on the updated alignment duration.

[0079] In an exemplary embodiment of the present disclosure, the time alignment unit 33 may be configured to perform time alignment processing on the operation data based on the data type and the alignment duration.

[0080] In an exemplary embodiment of the present disclosure, the time alignment unit 33 may be configured to: when the data type is an analog signal type, perform time alignment processing on the running data based on the alignment duration; when the data type is a digital signal type, adjust the alignment duration based on the second timestamp and the heartbeat signal, and perform time alignment processing on the running data based on the adjusted alignment duration.

[0081] In an exemplary embodiment of the present disclosure, the data processing device may further include a batch storage unit (not shown), which is configured to: after performing time alignment processing on the operating data to obtain processed data, store the processed data in batches.

[0082] In addition, according to an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium on which a computer program is stored. When the computer program is executed, the data processing method according to the exemplary embodiment of the present disclosure is implemented.

[0083] In an exemplary embodiment of the present disclosure, the computer-readable storage medium may carry one or more programs, and when the computer program is executed, the following steps may be implemented: acquiring operating data of a wind turbine generator set; identifying a data type of the operating data; and performing time alignment processing on the operating data according to the data type of the operating data to obtain processed data.

[0084] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In an embodiment of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a computer program that may be used by or in conjunction with an instruction execution system, device or device. The computer program contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof. The computer-readable storage medium may be contained in any device; it may also exist alone without being assembled into the device.

[0085] In addition, according to the exemplary embodiments of the present disclosure, a computer program product is also provided, and instructions in the computer program product can be executed by a processor of a computer device to complete the data processing method according to the exemplary embodiments of the present disclosure.

[0086] The above has been combined Figure 3 The data processing device according to the exemplary embodiment of the present disclosure is described. Figure 4 A computing device according to an exemplary embodiment of the present disclosure is described.

[0087] Figure 4A schematic diagram illustrating a computing device according to an exemplary embodiment of the present disclosure.

[0088] Reference Figure 4 According to the exemplary embodiment of the present disclosure, the computing device 4 includes a memory 41 and a processor 42. The memory 41 stores a computer program. When the computer program is executed by the processor 42, the data processing method according to the exemplary embodiment of the present disclosure is implemented.

[0089] In an exemplary embodiment of the present disclosure, when the computer program is executed by the processor 42, the following steps can be implemented: acquiring operating data of the wind turbine generator set; identifying the data type of the operating data; and performing time alignment processing on the operating data according to the data type of the operating data to obtain processed data.

[0090] Figure 4 The computing device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0091] The above has been referred to Figures 1 to 4 The data processing method and apparatus according to the exemplary embodiments of the present disclosure are described. However, it should be understood that: Figure 3 The data processing apparatus and its units shown in the figure may be respectively configured as software, hardware, firmware or any combination of the above items to perform specific functions. Figure 4 The computing device shown in is not limited to including the components shown above, but some components may be added or deleted as needed, and the above components may also be combined.

[0092] According to the data processing method and device of the exemplary embodiment of the present disclosure, the operating data of the wind turbine generator set is first acquired, the data type of the operating data is identified, and then the operating data is time-aligned according to the data type of the operating data to obtain processed data, thereby improving the orderliness of the data.

[0093] While the present disclosure has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure as defined by the following claims.

Claims

1. A data processing method, characterized in that: The method comprises: Obtaining the operating data of wind turbines; Identifying a data type of the operating data; Time alignment processing is performed on the operating data according to the data type of the operating data to obtain processed data.

2. The method according to claim 1, characterized in that After identifying the data type of the operating data, the method further includes: determining a data structure corresponding to the data type; The operation data is structured based on the data structure.

3. The method according to claim 2, characterized in that The data types include digital signal types and analog signal types. The analog signal type corresponds to a first data structure, and the digital signal type corresponds to a second data structure. The first data structure includes a first timestamp and first data. The second data structure includes a second timestamp, a heartbeat signal, and second data. The first timestamp indicates the time when the first data is acquired, and the second timestamp indicates the time of the data acquisition system when the second data is converted from analog to digital.

4. The method according to claim 3, characterized in that: The step of performing structured processing on the operation data based on the data structure comprises: When the data structure is a first data structure, processing the operation data into first structured processed data including a first timestamp and the operation data; When the data structure is a second data structure, the operating data is processed into second structured processed data including a second timestamp, a heartbeat signal, and the operating data.

5. The method according to claim 1, characterized in that The performing time alignment processing on the operation data according to the data type of the operation data includes: Determine the alignment duration based on a basic data packet of a data source where the running data is located, wherein the basic data packet includes a timestamp of a first data packet of the data source; The operation data is time-aligned based on the alignment duration.

6. The method according to claim 5, characterized in that The step of performing time alignment processing on the operation data according to the data type of the operation data further comprises: In response to detecting a deviation in the time alignment process, updating the alignment duration by adjusting the basic data packet; The operation data is time-aligned based on the updated alignment duration.

7. The method according to claim 5, characterized in that The step of performing time alignment processing on the operation data based on the alignment duration includes: When the data type is an analog signal type, performing time alignment processing on the operation data based on the alignment duration; When the data type is a digital signal type, the alignment duration is adjusted based on the second timestamp and the heartbeat signal, and time alignment processing is performed on the operating data based on the adjusted alignment duration.

8. The method according to claim 1, characterized in that After obtaining the operating data of the wind turbine generator set, the method further includes: In response to detecting the existence of lost operating data, data interpolation is performed on the acquired operating data according to a predetermined data interpolation principle.

9. A data processing device, characterized in that: include: A data acquisition unit is configured to acquire operation data of the wind turbine generator set; a type identification unit, configured to identify a data type of the operation data; The time alignment unit is configured to perform time alignment processing on the operation data according to the data type of the operation data to obtain processed data.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the data processing method according to any one of claims 1 to 8 is implemented.

11. A computing device, characterized in that: include: at least one processor; At least one memory stores a computer program, and when the computer program is executed by the at least one processor, the data processing method according to any one of claims 1 to 8 is implemented.

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