CN116303560A - Parallel data analysis method for flight data - Google Patents
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Abstract
The invention belongs to the field of industrial design research and development, and particularly relates to a parallel data analysis method for flight data. The analysis efficiency of the whole data can be effectively improved by a parallel analysis means of the data package of the flight data file, so that the data use efficiency of engineering designers is improved; according to the characteristics of the flight data, the time value and the parameter value are subjected to coding compression storage, so that the storage space of the analyzed data can be reduced, and the storage cost is saved; after the flight data file is analyzed and stored in the distributed column database in the parameter granularity, an efficient parameter query service interface can be provided, the rapid query display of the parameter curve is realized, and the data analysis efficiency of engineering designers can be improved; according to the method, log recording is carried out on the analysis process, so that analysis fault diagnosis is facilitated; the method adopts the architecture design of the micro-service, has high cohesion and low coupling, can adopt containerized deployment, is convenient to deploy and has strong expandability.
Description
Technical Field
The invention belongs to the field of industrial design research and development, and particularly relates to a parallel data analysis method for flight data.
Background
The aircraft can generate a large amount of flight data in the processes of test, pilot flight and equipment use, and the data has important values in the aspects of model development, identification evaluation, maintenance, repair, accident investigation and the like. The flight data is in a binary file format, and is stored in an enterprise file storage system after being transmitted back, each aircraft engineering professional technician performs data checking and analysis by adopting various data analysis software after inquiring, downloading and preprocessing the files, and the whole process is time-consuming. With the great improvement of the informatization capability of the airplane, the flight data is also rapidly expanded, and great challenges are brought to the processing, storage, analysis and management of the data.
In the field of Internet, big data technology has been widely used, and significant effects have been achieved in business such as electronic commerce, intelligent recommendation, logistics distribution, advertisement marketing, etc. In the aviation industry field, 2015 boeing constitutes aviation data analysis laboratory, gathers huge amount of data that produces in flight, based on big data processing system and flight test data analysis platform, instructs design, manufacturing and operation with the result of data analysis, has effectively supported the development and the production of novel aircraft, has improved efficiency.
In order to improve the data query analysis efficiency, the flight data binary files are required to be analyzed and stored according to the parameter granularity, the flight data binary files are transferred to the traditional relational database through a single-edition analysis tool, the analysis time is long, the analyzed data space is expanded, and the cost is high.
Disclosure of Invention
The purpose of the invention is that: the method solves the problems of parameter level data analysis and data storage of massive flight data binary files, so that second-level parameter granularity query service is provided, and the data use efficiency of engineering designers is improved.
The technical scheme of the invention is as follows:
a parallel data analysis method facing to flight data comprises the following steps:
and step 1, after the flight data file is transmitted back, storing the flight data file in a NAS file storage system. The flight data file is a binary file, and consists of a file header and tens of millions of data packets. The file header contains information: aircraft number, departure time, decoding dictionary version number. Each data packet records a plurality of sensor signal parameter values of a certain aircraft subsystem at a moment, and consists of a data packet head and a data packet body. The data packet head is of a fixed length, is provided with a data packet starting identifier, comprises an aircraft subsystem identifier, packet acquisition time and packet body length information, and consists of a plurality of sensor signal parameter values.
Step 2 the decoding dictionary service component loads multiple versions of decoding rule files defining the relative start word, start bit, data type and data length of each sensor signal parameter in the data packet.
And 3, after the NAS file storage system is mounted on the server where the file analysis component is located, the file analysis component comprises an unpacking module, a package analysis module, a data compression module and a warehousing module. The unpacking module reads the binary file of the flight data, intercepts the data packet according to the length of the packet body when the start identifier of the data packet is detected, and transmits the data packet to the packet analysis module for processing.
And 4, after the packet analysis module receives the data packet, calling a decoding dictionary service component according to the decoding dictionary version number of the data packet and the aircraft subsystem identification to obtain analysis rule information, specifically information of relative initial words, initial bits, data types and data lengths of all sensor signal parameters in the data packet.
And 5, reading the sensor signal parameters in the data packet into a byte array according to the relative initial word, initial bit and data length by the packet analysis module according to analysis rule information, and carrying out analysis conversion according to the data type. And thus, the parameter value of each sensor signal in the data packet is obtained and transmitted to a data compression module for processing.
And 6, the data compression processing module receives the sensor signal parameter values analyzed by the data packets, constructs the parameter values at a plurality of moments into time sequence values for each different sensor signal, carries out coding compression, and sends the compressed data to the warehousing module for processing.
And 7, the warehousing module writes the data after the sensor signals are compressed into a distributed column database.
Further, the method further comprises analysis scheduling, a plurality of file analysis components can be deployed on a plurality of servers before the step 2, and are managed through the analysis scheduling component, and analysis can be scheduled simultaneously for a plurality of flight data files in the NAS file system.
Furthermore, the method also comprises a parallel unpacking mode in the step 4, wherein the package analysis module adopts a multithreading mode and simultaneously carries out parallel analysis on a plurality of data packages.
Furthermore, the method also comprises a coding compression mode of the step 6, wherein the acquisition time sequence value is compressed by delta-of-delta coding, the sensor signal parameter value is compressed by XOR coding, and the storage space of the data after analysis can be reduced by coding compression, so that the storage cost is saved.
Further, the method also comprises a log record of the analysis process, wherein the log record component records the starting time, the ending time, the analysis time consumption, the analysis file name, the analysis file size, the number of sensor signal values after analysis and package analysis abnormal information of the whole analysis process.
Further, the system also comprises a data query service, wherein the data query service component provides a query interface of sensor signal parameter granularity, inputs the aircraft number, the landing information, the aircraft subsystem and the sensor signal name, and returns a time sequence value of a next sensor signal in a certain flying landing process by querying a distributed column database, and the column database is provided with an index, so that second-level return of the query interface can be realized, and the data query display efficiency can be improved.
Further, the decoding rule file in the step 2 is csv file storage or database table storage.
Further, the data types of the sensor signal parameters in step 5 may be discrete amounts and continuous amounts, the continuous amounts including int type, float type.
The invention has the beneficial effects that:
(1) The analysis efficiency of the whole data can be effectively improved by a parallel analysis means of the data package of the flight data file, so that the data use efficiency of engineering designers is improved;
(2) According to the characteristics of the flight data, the time value and the parameter value are subjected to coding compression storage, so that the storage space of the analyzed data can be reduced, and the storage cost is saved;
(3) After the flight data file is analyzed and stored in the distributed column database in the parameter granularity, an efficient parameter query service interface can be provided, the rapid query display of the parameter curve is realized, and the data analysis efficiency of engineering designers can be improved;
(4) According to the method, log recording is carried out on the analysis process, so that analysis fault diagnosis is facilitated;
(5) The method adopts the architecture design of the micro-service, has high cohesion and low coupling, can adopt containerized deployment, is convenient to deploy and has strong expandability.
Drawings
FIG. 1 is a binary file structure of flight data;
wherein: the flight data file consists of a file header and tens of millions of data packets. The file header contains information:
aircraft number, departure time, decoding dictionary version number. Each data packet records a plurality of sensor signal parameter values of a certain aircraft subsystem at a moment, and consists of a data packet head and a data packet body. The data packet head is of a fixed length, comprises a data packet starting identifier, and comprises an aircraft subsystem identifier, packet acquisition time and packet body length information, wherein the data packet body consists of a plurality of sensor signal parameter values;
FIG. 2 is a diagram of a flight data parallel data parsing component architecture;
fig. 3 is a diagram of a process for parallel parsing of flight data.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The parallel data analysis method for the flight data comprises the following steps:
and step 1, after the flight data file is transmitted back, storing the flight data file in a NAS file storage system. The flight data file is a binary file, and consists of a file header and tens of millions of data packets. The file header contains information: aircraft number, departure time, decoding dictionary version number. Each data packet records a plurality of sensor signal parameter values of a certain aircraft subsystem at a moment, and consists of a data packet head and a data packet body. The data packet head is of a fixed length, is provided with a data packet starting identifier, comprises an aircraft subsystem identifier, packet acquisition time and packet body length information, and consists of a plurality of sensor signal parameter values.
Step 2 the decoding dictionary service component loads multiple versions of decoding rule files defining the relative start word, start bit, data type and data length of each sensor signal parameter in the data packet.
And 3, after the NAS file storage system is mounted on the server where the file analysis component is located, the file analysis component comprises an unpacking module, a package analysis module, a data compression module and a warehousing module. The unpacking module reads the binary file of the flight data, intercepts the data packet according to the length of the packet body when the start identifier of the data packet is detected, and transmits the data packet to the packet analysis module for processing.
And 4, after the packet analysis module receives the data packet, calling a decoding dictionary service component according to the decoding dictionary version number of the data packet and the aircraft subsystem identification to obtain analysis rule information, specifically information of relative initial words, initial bits, data types and data lengths of all sensor signal parameters in the data packet.
And 5, reading the sensor signal parameters in the data packet into a byte array according to the relative initial word, initial bit and data length by the packet analysis module according to analysis rule information, and carrying out analysis conversion according to the data type. And thus, the parameter value of each sensor signal in the data packet is obtained and transmitted to a data compression module for processing.
And 6, the data compression processing module receives the sensor signal parameter values analyzed by the data packets, constructs the parameter values at a plurality of moments into time sequence values for each different sensor signal, carries out coding compression, and sends the compressed data to the warehousing module for processing.
And 7, the warehousing module writes the data after the sensor signals are compressed into a distributed column database.
Furthermore, the method also comprises analysis scheduling, wherein a plurality of file analysis components can be deployed on a plurality of servers before the step 2, and are managed through the analysis scheduling component, and analysis can be scheduled and performed simultaneously for a plurality of flight data files in the NAS file system, so that the analysis concurrency number is improved, and the whole analysis efficiency is improved. The method also comprises a parallel unpacking mode in the step 4, wherein the package analysis module adopts a multithreading mode and simultaneously carries out parallel analysis on a plurality of data packages. The method also comprises a coding compression mode of the step 6, wherein the acquisition time sequence value is compressed by delta-of-delta coding, the sensor signal parameter value is compressed by XOR coding, and the storage space of the data after analysis can be reduced by coding compression, so that the storage cost is saved. The method also comprises a log record of the analysis process, wherein the log record component records the starting time, the ending time, the analysis time consumption, the analysis file name, the analysis file size, the number of sensor signal values after analysis and the packet analysis abnormal information of the whole analysis process. The analysis process can be traced back through the analysis process log for analysis of abnormal fault diagnosis. The system also comprises a data query service, wherein the data query service component provides a query interface of sensor signal parameter granularity, inputs the aircraft number, the landing information, the aircraft subsystem and the sensor signal name, and returns a time sequence value of a next sensor signal in a certain flying landing process by querying a distributed column database, and the column database is provided with an index, so that second-level return of the query interface can be realized, and the data query display efficiency can be improved. The decoding rule file in step 2 may be a csv file storage, or may be a database table storage. The data types of the sensor signal parameters in step 5 may be discrete amounts and continuous amounts, the continuous amounts including int type, float type.
Example 1
Fig. 1 shows a block diagram of a binary file of flight data, each of which consists of a header and tens of millions of data packets. The file header contains information including airplane number, departure time, decoding dictionary version number. Each data packet records a plurality of sensor signal parameter values of a certain aircraft subsystem at a moment, and consists of a data packet head and a data packet body. The data packet header is of a fixed length, and is provided with a data packet start identifier (for example, hexadecimal number FEFEFE), an aircraft subsystem identifier, packet acquisition time and packet body length information, the data packet body is composed of a plurality of sensor signal parameter values, and the relative position, length and data type of each sensor signal in the data packet body are defined by a decoding rule file.
Fig. 2 shows a two-dimensional table format diagram of a decoding rule, stored in a csv file or relational database. Each row defines the relative start word, start bit, data length and data type of a certain sensor signal parameter in the data packet.
FIG. 3 illustrates a component architecture diagram for data parsing, including a parse scheduling component, a decode dictionary component, a data parsing component, a parse log component, a distributed database. The data analysis component comprises a file unpacking module, a package analysis module, a data compression module and a warehouse-in module.
An embodiment of a flight data parallel data analysis method is mainly implemented by the following steps:
and step 1, after the flight taking-off and landing are completed, the flight data file is transmitted back to be stored in an enterprise NAS file storage. And (3) deploying a LINUX server system of the file analysis component, and mounting NAS file storage.
And 2, importing decoding dictionary rule csv files of multiple versions into a mysql relational database, connecting a decoding dictionary service component with mysql database to load decoding rule data, providing an analysis rule information query interface for a file analysis component, wherein input parameters of the query interface are decoding dictionary version numbers and identification of an aircraft subsystem, outputting data packet analysis two-dimensional table information under corresponding conditions, and each row of a two-dimensional table defines relative initial words, initial bits, data lengths and data types of certain sensor signal parameters in the data packet.
And 3, the unpacking module of the file analysis component reads the binary file of the flight data in the NAS file storage, and obtains the flight number, the take-off time and the decoding dictionary version number information by reading the file header. And then starting to scan the file byte by byte, reading the data packet header when the data packet start identifier (hexadecimal number FEFEFE) is matched, obtaining the information of the aircraft subsystem identification, the packet acquisition time and the packet body length of the data packet, intercepting the data packet according to the packet body length, and transmitting the data packet to a packet analysis module for processing.
And 4, after receiving the data packet, the packet analysis module calls the query interface service of the decoding dictionary assembly according to the decoding dictionary version number in the flight data file header and the aircraft subsystem identification in the data packet header as input information to obtain analysis rule information, wherein the analysis rule information specifically comprises relative initial words, initial bits, data types and data length information of each sensor signal parameter.
And 5, the packet analysis module analyzes sensor signal parameters in the data packet one by one according to the analysis rule information, performs analysis and conversion according to the data type, and temporarily stores the sensor signal parameters into byte arrays, wherein different sensor signal parameters are different byte arrays. For a certain sensor signal parameter, when the temporary storage value is a certain number (1000), the time sequence value is transmitted to the data compression module for processing.
And 6, after the data compression processing module receives the sensor signal sequence value, carrying out coding compression processing, wherein the signal parameter sequence is compressed by using an XOR (exclusive or) code, and the compressed data is transmitted to the warehousing module for processing. The XOR compression logic is specifically as follows:
1) The first value is not compressed
2) If the result of XOR with the preamble is 0 (i.e., the same value), the value is 0 with only one bit of storage
3) If the XOR result is not 0, the first bit of control is 1 and the next value is the following
a) When the control bit is 0, the data block of the significant bit is contained by the previous data block
b) When the control bit is 1, the next 5 bits are used to store the number of leading 0 s, then 6 bits are used to store the length of the XOR intermediate non-0 bits, and finally the intermediate non-0 bits are stored
And 7, the warehousing module writes the compressed data of the sensor signals into a distributed column database HBASE.
The foregoing is merely a detailed description of the invention, which is not a matter of routine skill in the art. However, the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A parallel data analysis method for flight data is characterized by comprising the following steps:
step 1, after the flight data file is transmitted back, storing the flight data file in a NAS file storage system; the flight data file is a binary file and consists of a file header and tens of millions of data packets; the file header contains information: aircraft number, departure time, decoding dictionary version number; each data packet records a plurality of sensor signal parameter values of a certain aircraft subsystem at a moment, and consists of a data packet head and a data packet body; the data packet head is of a fixed length, is provided with a data packet starting identifier, comprises an aircraft subsystem identifier, packet acquisition time and packet body length information, and comprises a plurality of sensor signal parameter values;
step 2, a decoding dictionary service component loads decoding rule files of multiple versions, wherein the decoding rule defines relative initial words, initial bits, data types and data lengths of signal parameters of each sensor in a data packet;
step 3, after the NAS file storage system is mounted on the server where the file analysis component is located, the file analysis component comprises an unpacking module, a package analysis module, a data compression module and a warehousing module; the unpacking module reads the binary file of the flight data, intercepts the data packet according to the length of the packet body when detecting the start identifier of the data packet, and transmits the data packet to the packet analysis module for processing;
step 4, after the packet analysis module receives the data packet, calling a decoding dictionary service component according to the decoding dictionary version number of the data packet and the aircraft subsystem identification to obtain analysis rule information, specifically the information of the relative initial words, initial bits, data types and data lengths of all sensor signal parameters in the data packet;
step 5, the packet analysis module reads the sensor signal parameters in the data packet into a byte array according to the relative initial word, initial bit and data length according to analysis rule information, and performs analysis conversion according to the data type; thereby obtaining the signal parameter value of each sensor in the data packet, and transmitting the signal parameter value to a data compression module for processing;
step 6, the data compression processing module receives the sensor signal parameter values analyzed by the data packets, constructs the parameter values at a plurality of moments into time sequence values for each different sensor signal, carries out coding compression, and sends the compressed data to the warehousing module for processing;
and 7, the warehousing module writes the data after the sensor signals are compressed into a distributed column database.
2. The parallel data analysis method for flight data according to claim 1, further comprising analysis scheduling, wherein a plurality of file analysis components can be deployed on a plurality of servers before the step 2, and the analysis can be scheduled simultaneously for a plurality of flight data files in the NAS file system by managing the analysis scheduling components.
3. The method for parallel data analysis for flight data according to claim 1, further comprising a parallel unpacking mode of step 4, wherein the package analysis module adopts a multithreading mode to simultaneously analyze a plurality of data packages in parallel.
4. The parallel data analysis method for flight data according to claim 1, further comprising the encoding compression mode of step 6, wherein the acquisition time sequence value is compressed by delta-of-delta encoding, the sensor signal parameter value is compressed by XOR encoding, the data storage space after analysis can be reduced by encoding compression, and the storage cost is saved.
5. The parallel data analysis method for flight data according to claim 1, further comprising an analysis process log record, wherein the analysis log component records the starting time, the ending time, the analysis time consumption, the analysis file name, the analysis file size, the number of sensor signal values after analysis and package analysis abnormal information of the whole analysis process.
6. The parallel data analysis method for flight data according to claim 1, further comprising a data query service, wherein the data query service component provides a query interface of sensor signal parameter granularity, inputs an aircraft number, landing information, an aircraft subsystem to which the data belongs, and a sensor signal name, and returns a time sequence value of a next sensor signal in a certain flight landing process by querying a distributed column database, wherein the column database is provided with an index, and can realize second-level return of the query interface.
7. The parallel data analysis method for flight data according to claim 1, wherein the decoding rule file in the step 2 is csv file storage or database table storage.
8. The method according to claim 1, wherein the data type of the sensor signal parameter in step 5 is discrete or continuous, and the continuous includes int type and float type.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116737172A (en) * | 2023-08-11 | 2023-09-12 | 杭州初灵信息技术股份有限公司 | Small particle data packet analysis system and method |
| CN116933143A (en) * | 2023-09-15 | 2023-10-24 | 成都旋极历通信息技术有限公司 | Flight parameter data classification method |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116737172A (en) * | 2023-08-11 | 2023-09-12 | 杭州初灵信息技术股份有限公司 | Small particle data packet analysis system and method |
| CN116737172B (en) * | 2023-08-11 | 2023-12-12 | 杭州初灵信息技术股份有限公司 | Small particle data packet analysis system and method |
| CN116933143A (en) * | 2023-09-15 | 2023-10-24 | 成都旋极历通信息技术有限公司 | Flight parameter data classification method |
| CN116933143B (en) * | 2023-09-15 | 2023-11-21 | 成都旋极历通信息技术有限公司 | Flight parameter data classification method |
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