Embedded time sequence processing method and device for test data of aircraft power supply system
By deploying embedded timing database split components in aircraft power supply system tests and processing and uploading test data, the problem that the existing technology cannot meet the ns-level timestamp accuracy and high-speed data upload stability is solved, and the safety and accuracy of high-resolution timestamp processing and test process is achieved.
Patent Information
- Application Number
- CN202411993305.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-31
- Publication Date
- 2025-05-06
AI Technical Summary
The existing timing database cannot meet the ns-level timestamp accuracy requirements of aviation test data, and packet loss and delay problems are prone to occur when high-speed data is uploaded, which affects the control accuracy and security of the test process.
By deploying embedded timing database split components on the host or gateway, collecting and combining packet test data, using compression technology to reduce the amount of data, and processing high-frequency data at the gateway to improve timestamp accuracy, and finally uploading the data to the cloud timing database.
High-resolution timestamp processing of aviation test data is realized, network data congestion is reduced, and control accuracy and safety of the test process is improved.
Smart Images
Figure CN119946084A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of data processing technology, and specifically relates to an embedded timing processing method and device for aircraft power supply system test data. Background Art
[0002] In the scenario of system testing and verification in the aviation field, it is necessary to store various types of experimental data. The data will be used later for the analysis of various parameters during the test, the qualification judgment of the test results, the comparison and verification of historical data, etc.
[0003] The data generated during the test process is accompanied by a time tag. When processing this type of experimental data, the data time tag is usually used as the basis for screening, querying, exporting, etc. In the field of industrial Internet of Things, a time series database is used to manage this type of data.
[0004] The time tag accuracy of existing time series databases is at the millisecond level, which can meet the storage requirements of general sensor reporting information. However, for high-speed data acquisition during aviation test, the sampling rate is usually 72kS / s to 2MS / s. At a sampling rate of 2MS / s, each sampling point is 500ns apart, so the accuracy of data timestamps needs to reach the ns level, and existing time series databases cannot meet this requirement.
[0005] At present, in the deployment scenario of industrial Internet of Things, the time series database is deployed in the cloud of the Internet of Things, and the data upload path of the device is: device → gateway → network → cloud database, or sensor → network → cloud database. In the scenario of high-speed data collection and upload, multiple collection points upload data to the cloud at the same time. The large amount of data in the network may cause packet loss, delay, etc. At the same time, during the test process, the real-time control instructions sent by the cloud to the test equipment through the network will also be disturbed, affecting the accuracy and safety of the test process control. Therefore, the existing time series database deployment method cannot fully cover the data storage needs in the military test scenario. Summary of the invention
[0006] In order to solve the above problems, the present application provides an embedded timing processing method and device for aircraft power supply system test data, which meets the high-resolution timestamp processing requirements of aviation structure testing and verification, and at the same time solves the problem of network data congestion when uploading large amounts of data in the scenario of synchronous acquisition of multiple sampling points, as well as other problems caused by congestion.
[0007] The first aspect of the present application provides an embedded timing processing method for aircraft power supply system test data, mainly comprising:
[0008] Step S1, collecting test data by a time series database component deployed in a host or gateway in an embedded manner;
[0009] Step S2: when the collected test data is low-frequency data not higher than the frequency threshold, the collection point name, timestamp and data body are packaged; when the collected test data is high-frequency data higher than the frequency threshold, the collection point name, start and end time, sampling interval and compressed data body are packaged;
[0010] Step S3: Send the compressed and packaged data to the time series database entity deployed in the cloud, and the time series database entity writes the data into a data form.
[0011] Preferably, before step S1, the method further comprises:
[0012] Step S0, receiving the time series database main body configuration program sent from the cloud, and configuring the time series database split component according to the same database interface as the time series database main body, wherein the host or gateway is deployed near the sampling point, each host or gateway corresponds to a sampling point, and multiple hosts or gateways are networked with a cloud.
[0013] Preferably, step S2 further comprises:
[0014] Step S21, processing the test data according to the processing logic given and embedded in the cloud;
[0015] Step S22: resample and assemble packets according to the data upload rate set on the cloud.
[0016] Preferably, in step S2, when compressing the data body, the compression ratio is not less than 1:25.
[0017] Preferably, step S3 further includes:
[0018] According to the start and end time of the packaged data and the sampling interval, the decompressed data is sequentially timestamped and then written into the data form of the time series database.
[0019] The second aspect of the present application provides an aircraft power supply system test data embedded timing processing system, mainly comprising:
[0020] A data acquisition module is used to collect test data by using a time series database component deployed on a host or a gateway in an embedded manner;
[0021] A data processing module, for packaging the collection point name, timestamp and data body when the collected test data is low-frequency data not higher than the frequency threshold, and for packaging the collection point name, start and end time, sampling interval and compressed data body when the collected test data is high-frequency data higher than the frequency threshold;
[0022] The data compression and sending module is used to send the compressed and packaged data to the time series database entity deployed in the cloud, and the time series database entity writes the data into the data form.
[0023] Preferably, the system further comprises:
[0024] The embedded data component configuration module is used to receive the time series database main body configuration program sent from the cloud, and configure the time series database split component according to the same database interface as the time series database main body, wherein the host or gateway is deployed near the sampling point, each host or gateway corresponds to a sampling point, and multiple hosts or gateways are networked with a cloud.
[0025] Preferably, the data processing module includes:
[0026] A logic processing unit, used to process the test data according to the processing logic given and embedded in the cloud;
[0027] The resampling unit is used to resample the packets according to the data upload rate set by the cloud.
[0028] Preferably, in the data processing module, when compressing the data body, the compression ratio is not less than 1:25.
[0029] Preferably, the system further comprises:
[0030] The time processing module is used to sequentially enter timestamps into the decompressed data according to the start and end time of the packaged data and the sampling interval, and then write them into the data form of the time series database body.
[0031] This application decouples the timestamping work from the data uploading work, improving the accuracy and security of the test process control. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] Figure 1 This is a logical diagram of data processing by a host or gateway in a preferred embodiment of the method for embedded timing processing of aircraft power supply system test data of the present application. DETAILED DESCRIPTION
[0033] In order to make the purpose, technical scheme and advantages of the implementation of this application clearer, the technical scheme in the implementation of this application will be described in more detail in combination with the drawings in the implementation of this application. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described implementation is a part of the implementation of this application, not all of the implementations. The implementation described below with reference to the drawings is exemplary and is intended to be used to explain this application, and cannot be understood as a limitation on this application. Based on the implementation in this application, all other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. The implementation of this application is described in detail below in combination with the drawings.
[0034] The first aspect of the present application provides an embedded timing processing method for aircraft power supply system test data, mainly comprising:
[0035] Step S1, collecting test data by a time series database component deployed in a host or gateway in an embedded manner;
[0036] Step S2: when the collected test data is low-frequency data not higher than the frequency threshold, the collection point name, timestamp and data body are packaged; when the collected test data is high-frequency data higher than the frequency threshold, the collection point name, start and end time, sampling interval and compressed data body are packaged;
[0037] Step S3: Send the compressed and packaged data to the time series database entity deployed in the cloud, and the time series database entity writes the data into a data form.
[0038] refer to Figure 1 In the prior art, the edge gateway directly inserts the collected data into the cloud time series database through its own low-frequency collection program according to the remote insertion API of the time series data. In step S2 of the present application, the collected data is distinguished, and the high-frequency data is processed preferentially at the gateway, and the cloud time series database is mapped to the gateway. Based on the embedded design, the time series database split component is deployed locally at the gateway. The time series database split component is the same as the time series database body on the cloud. It receives the data in a given format transmitted by the remote insertion API of the time series data, and then compresses it and uploads it to the cloud periodically.
[0039] The low-frequency data in this application refers to data with a collection and transmission frequency less than or equal to 1MB / s, and the corresponding high-frequency data generally refers to data with a collection and transmission frequency greater than 1MB / s.
[0040] The gateway of this application mainly refers to a host with data processing capabilities deployed near the sampling point. The host is equipped with a heterogeneous ARM+FPGA board through a PCIe slot. The embedded database component supports running in X86 CPU and ARMCPU, and is compatible with Windows and various Linux distributions. To this end, in some optional implementations, step S1 further includes:
[0041] Step S0, receiving the time series database main body configuration program sent from the cloud, and configuring the time series database split component according to the same database interface as the time series database main body, wherein the host or gateway is deployed near the sampling point, each host or gateway corresponds to a sampling point, and multiple hosts or gateways are networked with a cloud.
[0042] It can be understood that the present application dynamically loads an embedded time series database split component in the heterogeneous board of the host in advance, and implants the high compression ratio characteristics of the time series database into the near-device end, so that in the test process, in the scenario where a large amount of data is collected, to control the network process, it is only necessary to send the compressed test data and the collection start and end time, and the sampling interval to the cloud. The cloud can calculate the theoretical collection time for each data based on this, and then enter a high-frequency timestamp with a timestamp accuracy of ns, and the test is not affected by network bandwidth fluctuations.
[0043] In an alternative implementation, the cloud can also send down algorithm files, such as the effective value analysis algorithm based on GJB181B. The gateway receives the configuration file and transmits it to the internal heterogeneous board through PCIe. The ARM side downloads the algorithm in the form of a bit stream into the planned dynamic resource area of FPGA to perform real-time processing and analysis of the collected high-frequency data.
[0044] The test equipment and the gateway transmit the analog data (e.g., voltage) of multiple channels collected during the test process via TCP. The gateway sends the test start command, and the test equipment sends the packet header, data, and packet tail in sequence according to the transmission protocol. The ARM end of the high-speed processing board unpacks the data according to the communication protocol corresponding to the device issued by the cloud platform. The packet header contains the sampling rate information of the voltage data; the data contains the voltage data of each channel sorted by the acquisition channel number; and the packet tail is the end mark. The voltage data is transmitted to the FPGA algorithm module via the high-speed data intra-board bus (AXI).
[0045] In some optional implementations, step S2 further includes:
[0046] Step S21, processing the test data according to the processing logic given and embedded in the cloud;
[0047] Step S22: resample and assemble packets according to the data upload rate set on the cloud.
[0048] In this embodiment, in step S21, the FPGA algorithm module processes the collected data, for example, calculating the effective value and frequency according to the voltage data, calculating the effective value once per half-wave, and the data analysis results are transmitted to the x86 CPU in real time through the PCIe bus. In step S22, the gateway resamples and reports according to the data upload rate set by the cloud, supports a refresh rate of 200ms and above, and the analysis results are packaged according to the package grouping method described above, and the device ID, analysis algorithm name and other content can also be added. Finally, it is pushed to the cloud platform through the MQTT protocol.
[0049] It is worth noting that since the sampling frequency of the aircraft power supply system test data is relatively fixed, the packaged data does not contain the timestamp of each sampling point, but only contains metadata such as the start and end time and the sampling interval. After the packaged data is sent to the cloud time series database, the timestamp corresponding to each sampling point data is restored according to the metadata. The above package method saves the storage and communication overhead of the timestamp part. In addition, the number of acquisition points contained in each data packet is configurable, and the default is 1 million points per packet.
[0050] In some optional implementations, in step S2, when compressing the data body, the compression ratio is not less than 1:25.
[0051] In some optional implementations, step S3 further includes:
[0052] According to the start and end time of the packaged data and the sampling interval, the decompressed data is sequentially timestamped and then written into the data form of the time series database.
[0053] It should also be noted that in step S3, due to network reasons, when the time series database split component deployed in the host or gateway in an embedded manner cannot connect to the cloud time series database, the packaged data is first saved to the local file system of the embedded host, and when the network is reconnected, it is retransmitted to the cloud time series database, and the cache in the local file system is cleared.
[0054] The second aspect of the present application provides an aircraft power supply system test data embedded timing processing system corresponding to the above method, mainly comprising:
[0055] A data acquisition module is used to collect test data by using a time series database component deployed on a host or a gateway in an embedded manner;
[0056] A data processing module, for packaging the collection point name, timestamp and data body when the collected test data is low-frequency data not higher than the frequency threshold, and for packaging the collection point name, start and end time, sampling interval and compressed data body when the collected test data is high-frequency data higher than the frequency threshold;
[0057] The data compression and sending module is used to send the compressed and packaged data to the time series database entity deployed in the cloud, and the time series database entity writes the data into the data form.
[0058] In some optional embodiments, the system further comprises:
[0059] The embedded data component configuration module is used to receive the time series database main body configuration program sent from the cloud, and configure the time series database split component according to the same database interface as the time series database main body, wherein the host or gateway is deployed near the sampling point, each host or gateway corresponds to a sampling point, and multiple hosts or gateways are networked with a cloud.
[0060] In some optional implementations, the data processing module includes:
[0061] A logic processing unit, used to process the test data according to the processing logic given and embedded in the cloud;
[0062] The resampling unit is used to resample the packets according to the data upload rate set by the cloud.
[0063] In some optional implementations, in the data processing module, when compressing the data body, the compression ratio is not less than 1:25.
[0064] In some optional embodiments, the system further comprises:
[0065] The time processing module is used to sequentially enter timestamps into the decompressed data according to the start and end time of the packaged data and the sampling interval, and then write them into the data form of the time series database body.
[0066] Although the present application has been described in detail above with general descriptions and specific implementation schemes, it is obvious to those skilled in the art that some modifications or improvements may be made to the present application. Therefore, these modifications or improvements made without departing from the spirit of the present application all fall within the scope of protection claimed in the present application.
Claims
1. An embedded timing processing method for aircraft power supply system test data, characterized in that: include: Step S1, collecting test data by a time series database component deployed in a host or gateway in an embedded manner; Step S2: when the collected test data is low-frequency data not higher than the frequency threshold, the collection point name, timestamp and data body are packaged; when the collected test data is high-frequency data higher than the frequency threshold, the collection point name, start and end time, sampling interval and compressed data body are packaged; Step S3: Send the compressed and packaged data to the time series database entity deployed in the cloud, and the time series database entity writes the data into a data form.
2. The method for embedded timing processing of aircraft power supply system test data according to claim 1, characterized in that: Before step S1, the method further comprises: Step S0, receiving the time series database main body configuration program sent from the cloud, and configuring the time series database split component according to the same database interface as the time series database main body, wherein the host or gateway is deployed near the sampling point, each host or gateway corresponds to a sampling point, and multiple hosts or gateways are networked with a cloud.
3. The method for embedded timing processing of aircraft power supply system test data according to claim 1, characterized in that: Step S2 further comprises: Step S21, processing the test data according to the processing logic given and embedded in the cloud; Step S22: resample and assemble packets according to the data upload rate set on the cloud.
4. The method for embedded timing processing of aircraft power supply system test data according to claim 1, characterized in that: In step S2, when compressing the data body, the compression ratio is not less than 1:
25.
5. The method for embedded timing processing of aircraft power supply system test data according to claim 1, characterized in that: Step S3 further includes: According to the start and end time of the packaged data and the sampling interval, the decompressed data is sequentially timestamped and then written into the data form of the time series database.
6. An embedded timing processing system for aircraft power supply system test data, characterized in that: include: A data acquisition module is used to collect test data by using a time series database component deployed on a host or a gateway in an embedded manner; A data processing module, for packaging the collection point name, timestamp and data body when the collected test data is low-frequency data not higher than the frequency threshold, and for packaging the collection point name, start and end time, sampling interval and compressed data body when the collected test data is high-frequency data higher than the frequency threshold; The data compression and sending module is used to send the compressed and packaged data to the time series database entity deployed in the cloud, and the time series database entity writes the data into the data form.
7. The aircraft power supply system test data embedded timing processing system as claimed in claim 6, characterized in that: The system further comprises: The embedded data component configuration module is used to receive the time series database main body configuration program sent from the cloud, and configure the time series database split component according to the same database interface as the time series database main body, wherein the host or gateway is deployed near the sampling point, each host or gateway corresponds to a sampling point, and multiple hosts or gateways are networked with a cloud.
8. The aircraft power supply system test data embedded timing processing system as claimed in claim 6, characterized in that: The data processing module comprises: A logic processing unit, used to process the test data according to the processing logic given and embedded in the cloud; The resampling unit is used to resample the packets according to the data upload rate set by the cloud.
9. The aircraft power supply system test data embedded timing processing system as claimed in claim 6, characterized in that: In the data processing module, when compressing the data body, the compression ratio is not less than 1:
25.
10. The aircraft power supply system test data embedded timing processing system according to claim 6, characterized in that: The system further comprises: The time processing module is used to sequentially enter timestamps into the decompressed data according to the start and end time of the packaged data and the sampling interval, and then write them into the data form of the time series database body.