Vehicle time sequence operation and maintenance data online compression and storage system and method

Abstract

The invention belongs to the technical field of vehicle time sequence operation and maintenance data, and particularly relates to a vehicle time sequence operation and maintenance data online compression and storage system and method, and the system comprises an operation and maintenance data collection module which is used for collecting operation and maintenance data on a vehicle bus; the operation and maintenance data analysis module is used for performing effective data field extraction on the acquired operation and maintenance data according to a bus protocol, analyzing the operation and maintenance data according to coefficient and offset requirements, and realizing actual physical quantity characterization of the operation and maintenance data; the operation and maintenance data classification processing module is used for classifying the operation and maintenance data according to data characteristics; the operation and maintenance data compression module is used for selecting a data compression algorithm according to the data type and performing compression processing on the classified operation and maintenance data; and the operation and maintenance data storage module is used for establishing a vehicle number-bus node-physical system-physical quantity four-layer data hierarchical structure according to a vehicle operation and maintenance data bus structure, and writing the compressed operation and maintenance data into an embedded time sequence database.

Description

Technical Field

[0001] This invention belongs to the technical field of vehicle time-series operation and maintenance data, specifically to a system and method for online compression and storage of vehicle time-series operation and maintenance data. By analyzing the characteristics of vehicle time-series operation and maintenance data, this system and method are constructed based on these characteristics, enabling efficient online lossless compression and storage of vehicle time-series operation and maintenance data. This invention is applicable to any system for collecting and storing vehicle time-series operation and maintenance data. Background Art

[0002] With the continuous development of vehicle informatization and intelligence, the number of parameters of time-series operation and maintenance data collected from real vehicles is increasing, and the amount of data stored is increasing. While data has become an important resource for vehicles, it has also brought a huge burden to vehicle data collection and storage. In order to cope with the ever-expanding data information, increasing the capacity of data storage hard disks and improving the computing power of data processing chips have become the only choice for vehicle time-series operation and maintenance data management. However, expanding hard disk capacity and improving chip computing power only solve the data storage problem at the cost of increased production costs, but have limited effectiveness in terms of fast and stable online data transmission. A method for online lossless compression storage of vehicle time-series operation and maintenance data is studied. Based on the characteristics of vehicle time-series operation and maintenance data, efficient lossless compression storage of data is achieved, which can effectively improve the online management capabilities of vehicle time-series operation and maintenance data and provide efficient data support for vehicle online health management and remote operation and maintenance control technology.

[0003] A search of relevant domestic and international patents and literature revealed that the patent "A Time Series Data Compression Method" (CN 116865767A) proposes classifying time series data into four categories: fixed value type, arithmetic difference data type, Gauge type, and Counter type. It then compresses the Gauge type using an XOR logical operation, while the Counter type uses a delta operation and an XOR logical operation. However, this invention fails to propose a classification method and corresponding compression scheme tailored to the characteristics of vehicle time series operation and maintenance data, and thus fails to meet the compression and storage requirements for online operation and maintenance data of specific vehicle types. The patent "A Clustering-Based Time Series Data Compression Method and System" (CN 110704408A) proposes dividing data into several blocks, clustering each block using a similarity measurement method and a clustering algorithm, and then compressing each block using an optimized compression algorithm. However, this invention suffers from the large amount of data computation and high processor power requirements, and fails to meet the requirements for fast and efficient online compression of vehicle operation and maintenance data. The patent "A method for adaptive data compression of time-series databases" (CN 114665885B) proposes segmenting data values ​​and using a neural network classifier to optimize the compression algorithm and compress the data. However, this invention also has the problem of high processor computing power requirements and cannot meet the needs of fast and efficient online compression of vehicle operation and maintenance data. Summary of the Invention

[0004] (1) Technical issues to be resolved

[0005] The technical problem to be solved by this invention is how to provide a system and method for online compression and storage of vehicle time-series operation and maintenance data. This system can be applied to any vehicle time-series operation and maintenance data collection and storage system, achieving efficient online lossless compression of vehicle time-series operation and maintenance data. The purpose of this invention is to provide a method for online compression and storage of vehicle time-series operation and maintenance data, thereby improving the online management capabilities of vehicle time-series operation and maintenance data and providing efficient data support for online vehicle health management and remote operation and maintenance control.

[0006] (2) Technical solution

[0007] To solve the above technical problems, the present invention provides an online compression and storage system for vehicle time series operation and maintenance data, the system comprising:

[0008] Operation and maintenance data acquisition module, which is used to collect operation and maintenance data on the vehicle bus;

[0009] The operation and maintenance data parsing module is used to extract valid data fields from the collected operation and maintenance data according to the bus protocol, parse the operation and maintenance data according to the coefficient and offset requirements, and realize the actual physical quantity representation of the operation and maintenance data;

[0010] An operation and maintenance data classification processing module, which is used to classify operation and maintenance data according to data characteristics;

[0011] The operation and maintenance data compression module is used to select a data compression algorithm according to the data type and compress the classified operation and maintenance data;

[0012] The operation and maintenance data storage module is used to establish a four-layer data hierarchy structure of vehicle number-bus node-physical system-physical quantity according to the vehicle operation and maintenance data bus structure, and write the compressed operation and maintenance data into the embedded time series database.

[0013] Wherein, the vehicle bus includes a CAN bus and a Flexray bus.

[0014] Among them, the operation and maintenance data on the vehicle bus includes speed, current, voltage, torque, pressure, temperature, liquid level, flow sensor information, switch control signals, system control instructions, and diagnostic signals of gear position, fault, and controller heartbeat.

[0015] The operation and maintenance data classification processing module classifies the operation and maintenance data, and the classification includes:

[0016] (1) Divide the operation and maintenance data into two types of data blocks: timestamp and data value;

[0017] (2) Divide the data values ​​into high-frequency data and low-frequency data according to the frequency of change;

[0018] (3) Divide data values ​​into discrete data and continuous data according to whether they change continuously;

[0019] Vehicle operation and maintenance data is divided into five categories: timestamp data, high-frequency continuous data, high-frequency discrete data, low-frequency continuous data, and low-frequency discrete data. The data types of the five categories of data are identified by the first byte.

[0020] The operation and maintenance data classification processing module divides the operation and maintenance data into two types of data blocks: timestamp and data value. The classification standard is as follows:

[0021]

[0022] The operation and maintenance data classification processing module divides the data values ​​into high-frequency data and low-frequency data according to the frequency of change;

[0023] The classification criteria are as follows:

[0024]

[0025]

[0026] The operation and maintenance data classification processing module divides the data value into discrete data and continuous data according to whether it changes continuously;

[0027] The classification criteria are as follows:

[0028]

[0029] The operation and maintenance data classification processing module divides the vehicle operation and maintenance data into five categories: timestamp data, high-frequency continuous data, high-frequency discrete data, low-frequency continuous data, and low-frequency discrete data, and identifies the data type of the five categories of data by the first byte, as shown in the following table;

[0030]

[0031] The operation and maintenance data compression module selects a data compression algorithm according to the data type and compresses the operation and maintenance data as follows:

[0032] 1) Timestamp data; Timestamp data is fixed-difference incremental data, and is compressed using the delta-of-delta compression method. The first value of the timestamp data is stored in the second byte, and the second difference value (DOD value) of the data is stored in the third byte.

[0033] 2) High-frequency continuous data: Data such as speed, current, voltage, torque, and pressure are high-frequency continuously changing data, and are compressed using the run-length encoding method. The run length is stored in the second byte, and the element value is stored in the third byte.

[0034] 3) High-frequency discrete data: Controller heartbeat, system control instructions and other data are high-frequency discrete changing data. Delta coding compression method is used for data compression. The first value of the data value is saved in the second byte, and the primary difference (Delta value) of the data value is saved in the third byte.

[0035] 4) Low-frequency continuous data: Temperature, liquid level and other data are low-frequency continuous data, and the bitmap index compression method is used for data compression, and the bitmap value of the data value is saved through the second byte;

[0036] 5) Low-frequency discrete data: switch control signals, fault signals, gear signals and other data are low-frequency discrete data. Dictionary coding compression method is used for data compression, and the dictionary value of the data value is saved through the second byte.

[0037] In addition, the present invention also provides an online compression storage method for vehicle time series operation and maintenance data, which is implemented based on the compression storage system and includes:

[0038] Step S1: The operation and maintenance data acquisition module collects the operation and maintenance data on the vehicle bus;

[0039] Step S2: The operation and maintenance data parsing module extracts valid data fields from the collected operation and maintenance data according to the bus protocol, and parses the operation and maintenance data according to the coefficient and offset requirements to achieve actual physical quantity representation of the operation and maintenance data;

[0040] Step S3: The operation and maintenance data classification processing module classifies the operation and maintenance data according to data characteristics;

[0041] Step S4: The operation and maintenance data compression module selects a data compression algorithm according to the data type and compresses the classified operation and maintenance data;

[0042] Step S5: The operation and maintenance data storage module establishes a four-layer data hierarchy structure of vehicle number-bus node-physical system-physical quantity according to the vehicle operation and maintenance data bus structure, and writes the compressed operation and maintenance data into the embedded time series database.

[0043] (3) Beneficial effects

[0044] Compared with the prior art, the present invention has the following effects:

[0045] This vehicle time-series operation and maintenance data online compression and storage system and method analyzes the characteristics of vehicle time-series operation and maintenance data to construct an online data compression system and compression method based on the characteristics of vehicle time-series operation and maintenance data. It successfully solves the technical problem of low efficiency in the collection, compression and storage of vehicle time-series operation and maintenance data. This method can be applied to any vehicle time-series operation and maintenance data collection and storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a schematic diagram of the modules of the online compression and storage system for time series operation and maintenance data of the present invention;

[0047] Figure 2 This is a schematic diagram of the online compression and storage process of time series operation and maintenance data of the present invention;

[0048] Figure 3 This is a schematic diagram of the time series operation and maintenance data blocks of the present invention;

[0049] Figure 4 This is a schematic diagram of data value classification according to the present invention;

[0050] Figure 5 Schematic diagram of the time series operation and maintenance data compression solution of the present invention;

[0051] Figure 6 This is a schematic diagram of the hierarchical structure of the time series operation and maintenance data storage of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, content, and advantages of the present invention more clear, the specific implementation methods of the present invention are further described in detail below with reference to the accompanying drawings and examples.

[0053] To solve the above technical problems, the present invention provides an online compression and storage system for vehicle time series operation and maintenance data, the system comprising:

[0054] Operation and maintenance data acquisition module, which is used to collect operation and maintenance data on the vehicle bus;

[0055] The operation and maintenance data parsing module is used to extract valid data fields from the collected operation and maintenance data according to the bus protocol, parse the operation and maintenance data according to the coefficient and offset requirements, and realize the actual physical quantity representation of the operation and maintenance data;

[0056] An operation and maintenance data classification processing module, which is used to classify operation and maintenance data according to data characteristics;

[0057] The operation and maintenance data compression module is used to select a data compression algorithm according to the data type and compress the classified operation and maintenance data;

[0058] The operation and maintenance data storage module is used to establish a four-layer data hierarchy structure of vehicle number-bus node-physical system-physical quantity according to the vehicle operation and maintenance data bus structure, and write the compressed operation and maintenance data into the embedded time series database.

[0059] Wherein, the vehicle bus includes a CAN bus and a Flexray bus.

[0060] Among them, the operation and maintenance data on the vehicle bus includes speed, current, voltage, torque, pressure, temperature, liquid level, flow sensor information, switch control signals, system control instructions, and diagnostic signals of gear position, fault, and controller heartbeat.

[0061] The operation and maintenance data classification processing module classifies the operation and maintenance data, and the classification includes:

[0062] (1) Divide the operation and maintenance data into two types of data blocks: timestamp and data value;

[0063] (2) Divide the data values ​​into high-frequency data and low-frequency data according to the frequency of change;

[0064] (3) Divide data values ​​into discrete data and continuous data according to whether they change continuously;

[0065] Vehicle operation and maintenance data is divided into five categories: timestamp data, high-frequency continuous data, high-frequency discrete data, low-frequency continuous data, and low-frequency discrete data. The data types of the five categories of data are identified by the first byte.

[0066] The operation and maintenance data classification processing module divides the operation and maintenance data into two types of data blocks: timestamp and data value. The classification standard is as follows:

[0067]

[0068] The operation and maintenance data classification processing module divides the data values ​​into high-frequency data and low-frequency data according to the frequency of change;

[0069] The classification criteria are as follows:

[0070]

[0071]

[0072] The operation and maintenance data classification processing module divides the data value into discrete data and continuous data according to whether it changes continuously;

[0073] The classification criteria are as follows:

[0074]

[0075] The operation and maintenance data classification processing module divides the vehicle operation and maintenance data into five categories: timestamp data, high-frequency continuous data, high-frequency discrete data, low-frequency continuous data, and low-frequency discrete data, and identifies the data type of the five categories of data by the first byte, as shown in the following table;

[0076]

[0077] The operation and maintenance data compression module selects a data compression algorithm according to the data type and compresses the operation and maintenance data as follows:

[0078] 1) Timestamp data; Timestamp data is fixed-difference incremental data, and is compressed using the delta-of-delta compression method. The first value of the timestamp data is stored in the second byte, and the second difference value (DOD value) of the data is stored in the third byte.

[0079] 2) High-frequency continuous data: Data such as speed, current, voltage, torque, and pressure are high-frequency continuously changing data, and are compressed using the run-length encoding method. The run length is stored in the second byte, and the element value is stored in the third byte.

[0080] 3) High-frequency discrete data: Controller heartbeat, system control instructions and other data are high-frequency discrete changing data. Delta coding compression method is used for data compression. The first value of the data value is saved in the second byte, and the primary difference (Delta value) of the data value is saved in the third byte.

[0081] 4) Low-frequency continuous data: Temperature, liquid level and other data are low-frequency continuous data, and the bitmap index compression method is used for data compression, and the bitmap value of the data value is saved through the second byte;

[0082] 5) Low-frequency discrete data: switch control signals, fault signals, gear signals and other data are low-frequency discrete data. Dictionary coding compression method is used for data compression, and the dictionary value of the data value is saved through the second byte.

[0083] In addition, the present invention also provides an online compression storage method for vehicle time series operation and maintenance data, which is implemented based on the compression storage system and includes:

[0084] Step S1: The operation and maintenance data acquisition module collects the operation and maintenance data on the vehicle bus;

[0085] Step S2: The operation and maintenance data parsing module extracts valid data fields from the collected operation and maintenance data according to the bus protocol, and parses the operation and maintenance data according to the coefficient and offset requirements to achieve actual physical quantity representation of the operation and maintenance data;

[0086] Step S3: The operation and maintenance data classification processing module classifies the operation and maintenance data according to data characteristics;

[0087] Step S4: The operation and maintenance data compression module selects a data compression algorithm according to the data type and compresses the classified operation and maintenance data;

[0088] Step S5: The operation and maintenance data storage module establishes a four-layer data hierarchy structure of vehicle number-bus node-physical system-physical quantity according to the vehicle operation and maintenance data bus structure, and writes the compressed operation and maintenance data into the embedded time series database.

[0089] Example 1

[0090] In order to better understand the present invention, the following specific embodiments are combined with the attached Figure 1 Time series operation and maintenance data online compression storage system module composition, attached Figure 2 Time series operation and maintenance data online compression storage process, attached Figure 3 Schematic diagram of time series operation and maintenance data block, Figure 4 Data value classification diagram, attached Figure 5 Time series operation and maintenance data compression solution, Figure 6The hierarchical structure of time series operation and maintenance data storage is described in detail.

[0091] (101) Collecting CAN, FLEXRAY and other bus operation and maintenance data; collecting sensor information such as vehicle speed, current, voltage, torque, pressure, temperature, liquid level, flow, switch control signals, system control instructions, and CAN, FLEXRAY bus operation and maintenance data such as gear position, fault, controller heartbeat, etc.;

[0092] (102) Parse the operation and maintenance data according to the bus protocol; extract the valid data fields of the collected operation and maintenance data according to the bus protocols such as CAN and FLEXRAY, parse the operation and maintenance data according to the coefficient and offset requirements, and realize the actual physical quantity representation of the operation and maintenance data;

[0093] (103) Blocking the parsed operation and maintenance data; dividing the parsed time series operation and maintenance data into two types of data blocks: timestamp and data value;

[0094] (1031) Timestamp: Record the time parameter in the time series operation and maintenance data as a timestamp. The data format is usually xx:xx:xx:xxx. Set the timestamp data type identifier to 1 and identify the timestamp data type by the first byte.

[0095] (1032) data value; recording other parameters other than the time parameter in the time series operation and maintenance data as data values;

[0096] (104) Classify data values ​​according to data characteristics; classify data values ​​according to the frequency of change and whether they change continuously, and divide them into four categories: high-frequency continuous data, high-frequency discrete data, low-frequency continuous data, and low-frequency discrete data;

[0097] (1041) High-frequency continuous data: Data values ​​in the time series operation and maintenance data that have a stable time of less than 100ms and have infinite values ​​and continuously changing are classified as high-frequency continuous data. The high-frequency continuous data type identifier is set to 2, and the high-frequency continuous data type is identified by the first byte. Typical high-frequency continuous data include speed, current, voltage, torque, and pressure data.

[0098] (1042) High-frequency discrete data: Data values ​​in the time series operation and maintenance data that have a stable time of less than 100ms and have finite values ​​and discontinuous changes are classified as high-frequency discrete data. The high-frequency discrete data type identifier is set to 3, and the high-frequency discrete data type is identified by the first byte. Typical high-frequency discrete data include controller heartbeat and system control instruction data.

[0099] (1043) Low-frequency continuous data: Data values ​​in time series operation and maintenance data that have a stable time of ≥100ms and have infinite values ​​and continuously changing are classified as low-frequency continuous data. The low-frequency continuous data type identifier is set to 4, and the low-frequency continuous data type is identified by the first byte. Typical low-frequency continuous data include temperature and liquid level data.

[0100] (1044) Low-frequency discrete data: Data values ​​in the time series operation and maintenance data that have a stable time of ≥100ms, a finite value, and non-continuous changes are classified as low-frequency discrete data. The low-frequency discrete data type identifier is set to 5, and the low-frequency discrete data type is identified by the first byte. Typical low-frequency discrete data include switch control signals, fault signals, and gear position signal data.

[0101] (105) compressing the operation and maintenance data according to the set timestamp and data value compression algorithm; selecting a data compression algorithm according to the data type and compressing the operation and maintenance data;

[0102] (1051) Timestamp data; the timestamp data is compressed using a delta-of-delta compression method, with the first value of the timestamp data being stored in the second byte and the arithmetic difference value of the data being stored in the third byte;

[0103] (1052) High-frequency continuous data; the high-frequency continuous data is compressed using a run-length encoding method, with the run length stored in the second byte and the data value stored in the third byte;

[0104] (1053) High frequency discrete data; the high frequency discrete data is compressed using a Delta coding compression method, wherein the first value of the data value is stored in the second byte quantity, and the difference of the data value is stored in the third byte quantity;

[0105] (1054) low-frequency continuous data; low-frequency continuous data is compressed using a bitmap index compression method, and the bitmap value corresponding to the data value is saved through the second byte;

[0106] (1055) low-frequency discrete data; low-frequency discrete data is compressed using a dictionary coding compression method, and the dictionary value corresponding to the data value is saved through the second byte;

[0107] (106) The compressed operation and maintenance data is stored in the database according to the data hierarchy structure; according to the vehicle operation and maintenance data bus structure, a four-layer data hierarchy structure of vehicle number-bus node-physical system-physical quantity is established, and the compressed operation and maintenance data is written into the embedded time series database;

[0108] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An online compression storage system for vehicle time series operation and maintenance data, characterized in that: The system comprises: Operation and maintenance data acquisition module, which is used to collect operation and maintenance data on the vehicle bus; The operation and maintenance data parsing module is used to extract valid data fields from the collected operation and maintenance data according to the bus protocol, parse the operation and maintenance data according to the coefficient and offset requirements, and realize the actual physical quantity representation of the operation and maintenance data; An operation and maintenance data classification processing module, which is used to classify operation and maintenance data according to data characteristics; The operation and maintenance data compression module is used to select a data compression algorithm according to the data type and compress the classified operation and maintenance data; The operation and maintenance data storage module is used to establish a four-layer data hierarchy structure of vehicle number-bus node-physical system-physical quantity according to the vehicle operation and maintenance data bus structure, and write the compressed operation and maintenance data into the embedded time series database.

2. The online compression storage system for vehicle time series operation and maintenance data according to claim 1, characterized in that: The vehicle bus includes a CAN bus and a Flexray bus.

3. The online compression storage system for vehicle time series operation and maintenance data according to claim 1, characterized in that: The operation and maintenance data on the vehicle bus includes speed, current, voltage, torque, pressure, temperature, liquid level, and flow sensor information, switch control signals, system control instructions, and diagnostic signals of gear position, fault, and controller heartbeat.

4. The online compression storage system for vehicle time series operation and maintenance data according to claim 1, characterized in that: The operation and maintenance data classification processing module classifies the operation and maintenance data, and the classification includes: (1) Divide the operation and maintenance data into two types of data blocks: timestamp and data value; (2) Divide the data values ​​into high-frequency data and low-frequency data according to the frequency of change; (3) Divide data values ​​into discrete data and continuous data according to whether they change continuously; Vehicle operation and maintenance data is divided into five categories: timestamp data, high-frequency continuous data, high-frequency discrete data, low-frequency continuous data, and low-frequency discrete data. The data types of the five categories of data are identified by the first byte.

5. The online compression storage system for vehicle time series operation and maintenance data according to claim 4, characterized in that: The operation and maintenance data classification processing module divides the operation and maintenance data into two types of data blocks: timestamp and data value. The classification criteria are as follows:

6. The online compression storage system for vehicle time series operation and maintenance data according to claim 5, characterized in that: The operation and maintenance data classification processing module divides the data values ​​into high-frequency data and low-frequency data according to the frequency of change; The classification criteria are as follows:

7. The online compression storage system for vehicle time series operation and maintenance data according to claim 6, characterized in that: The operation and maintenance data classification processing module divides the data value into discrete data and continuous data according to whether it changes continuously; The classification criteria are as follows:

8. The online compression storage system for vehicle time series operation and maintenance data according to claim 7, characterized in that: The operation and maintenance data classification processing module divides the vehicle operation and maintenance data into five categories: timestamp data, high-frequency continuous data, high-frequency discrete data, low-frequency continuous data, and low-frequency discrete data, and identifies the data type of the five categories of data by the first byte, as shown in the following table; 9. The online compression storage system for vehicle time series operation and maintenance data according to claim 8, characterized in that: The operation and maintenance data compression module selects a data compression algorithm according to the data type and compresses the operation and maintenance data as follows: 1) Timestamp data; Timestamp data is fixed-difference incremental data, and is compressed using the delta-of-delta compression method. The first value of the timestamp data is stored in the second byte, and the second difference of the data is stored in the third byte. 2) High-frequency continuous data: Data such as speed, current, voltage, torque, and pressure are high-frequency continuously changing data, and are compressed using the run-length encoding method. The run length is stored in the second byte, and the element value is stored in the third byte. 3) High-frequency discrete data: Controller heartbeat, system control instructions and other data are high-frequency discrete changing data. Delta coding compression method is used for data compression. The first value of the data value is saved by the second byte, and the primary difference of the data value is saved by the third byte. 4) Low-frequency continuous data: Temperature, liquid level and other data are low-frequency continuous data, and the bitmap index compression method is used for data compression, and the bitmap value of the data value is saved through the second byte; 5) Low-frequency discrete data: switch control signals, fault signals, gear signals and other data are low-frequency discrete data. Dictionary coding compression method is used for data compression, and the dictionary value of the data value is saved through the second byte.

10. A method for online compression and storage of vehicle time series operation and maintenance data, characterized in that: The compression storage method is implemented based on the compression storage system according to claim 9, and the compression storage method includes: Step S1: The operation and maintenance data acquisition module collects the operation and maintenance data on the vehicle bus; Step S2: The operation and maintenance data parsing module extracts valid data fields from the collected operation and maintenance data according to the bus protocol, and parses the operation and maintenance data according to the coefficient and offset requirements to achieve actual physical quantity representation of the operation and maintenance data; Step S3: The operation and maintenance data classification processing module classifies the operation and maintenance data according to data characteristics; Step S4: The operation and maintenance data compression module selects a data compression algorithm according to the data type and compresses the classified operation and maintenance data; Step S5: The operation and maintenance data storage module establishes a four-layer data hierarchy structure of vehicle number-bus node-physical system-physical quantity according to the vehicle operation and maintenance data bus structure, and writes the compressed operation and maintenance data into the embedded time series database.

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