CN111198982A - Time series telemetry data compensation method and device and server - Google Patents
Time series telemetry data compensation method and device and server Download PDFInfo
- Publication number
- CN111198982A CN111198982A CN201911355577.3A CN201911355577A CN111198982A CN 111198982 A CN111198982 A CN 111198982A CN 201911355577 A CN201911355577 A CN 201911355577A CN 111198982 A CN111198982 A CN 111198982A
- Authority
- CN
- China
- Prior art keywords
- telemetry data
- data
- time
- telemetry
- compensating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Accounting & Taxation (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Finance (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Selective Calling Equipment (AREA)
Abstract
The embodiment of the application is applicable to the field of time series data processing, and provides a time series telemetry data compensation method, a time series telemetry data compensation device, a server and a computer readable storage medium. The method comprises the steps of obtaining a telemetering data group, and when the state of the time sequence of the telemetering data group is detected to be a non-steady state, compensating the time sequence of the telemetering data group to obtain the telemetering data group of which the state of the time sequence is a steady state. The embodiment of the application compensates the telemetering data group of which the time sequence state is the non-steady state, and the telemetering data group of which the time sequence state is the steady state is obtained, so that a time sequence model can be built according to the telemetering data group, and the follow-up analysis of the charging process of a user according to the time sequence model is facilitated.
Description
Technical Field
The present application relates to the field of time series data processing, and in particular, to a method and an apparatus for compensating time series telemetry data, a server, and a computer-readable storage medium.
Background
With the development of transportation, the applications of electric vehicles are gradually increased, and the cruising ability of electric vehicles mainly depends on a charging device such as a charging pile.
The user places an order on the charging platform through the mobile terminal, then the user charges the order through the charging device to the charging station appointed by the charging platform, and correspondingly, the charging device can record telemetering data in the charging process of the user.
In the prior art, a time series model is constructed by acquiring telemetry data in the user charging process from a charging device, so that the user charging process can be analyzed subsequently, such as statistical characteristic analysis or development rule analysis. The establishment of the time series model requires that the time series of the telemetering data is stable, but in the actual establishment of the time series model, the time series of the obtained telemetering data is non-stable, so that the time series model cannot be established, and the subsequent analysis of the charging process of the user is not facilitated.
Disclosure of Invention
In view of this, the embodiment of the present application provides a method for compensating time series telemetry data, so as to solve the problem that a time series model cannot be constructed in the prior art, which is not beneficial to analyzing the subsequent charging process of a user.
A first aspect of an embodiment of the present application provides a method, including:
acquiring a telemetry data set, wherein the telemetry data set comprises at least two pieces of telemetry data;
and when the state of the time sequence of the telemetering data group is detected to be a non-steady state, compensating the time sequence of the telemetering data group to obtain the telemetering data group of which the state of the time sequence is a steady state.
Optionally, the acquiring the telemetry data set includes:
acquiring charging order data corresponding to the user identification data;
acquiring the telemetering data according to the positioning data of the charging order data;
and arranging the telemetry data according to a time sequence to form the telemetry data group.
Optionally, when detecting that the state of the time series of the telemetry data set is a non-stationary state, compensating the time series of the telemetry data set to obtain the telemetry data set of which the state of the time series is a stationary state, including:
detecting whether a time interval between first telemetry data and second telemetry data is larger than a preset time interval, wherein the first telemetry data and the second telemetry data are two pieces of telemetry data in the telemetry data group and are sequentially arranged in the time sequence;
if so, the state of the time series of the telemetry data set is a non-steady state;
and compensating the time sequence of the telemetry data group to obtain the telemetry data of which the state of the time sequence is a steady state.
Optionally, compensating the time series of the telemetry data set to obtain a telemetry data set with a steady state in the time series, including:
adding compensation telemetry data in a time interval between the first telemetry data and the second telemetry data;
and taking the telemetry data group added with the compensation telemetry data as a time-series telemetry data group with a steady state.
Optionally, before adding the compensation telemetry data in the time interval between the first telemetry data and the second telemetry data, the method further includes:
generating the compensated telemetry data from the first telemetry data and the second telemetry data.
Optionally, adding compensation telemetry data in a time interval between the first telemetry data and the second telemetry data, comprising:
calculating the adding times of the compensation telemetry data according to the time interval between the first telemetry data and the second telemetry data and a preset time interval;
adding the compensation telemetry data in a time interval between the first telemetry data and the second telemetry data at a preset time interval by taking the time of the first telemetry data or the second telemetry data as a starting point according to the adding times.
Optionally, when detecting that the state of the time series of the telemetry data set is a non-stationary state, compensating the time series of the telemetry data set to obtain the telemetry data set of which the state of the time series is a stationary state, the method further includes:
and storing the telemetry data group with the time series state as the steady state into a preset database.
A second aspect of an embodiment of the present application provides an apparatus for compensating time-series telemetry data, including:
the acquisition module is used for acquiring a telemetry data set, and the telemetry data set comprises at least two pieces of telemetry data;
and the detection module is used for compensating the time sequence of the telemetering data group when detecting that the state of the time sequence of the telemetering data group is a non-steady state, so as to obtain the telemetering data group of which the state of the time sequence is a steady state.
Optionally, the obtaining module includes:
the first obtaining sub-module is used for obtaining charging order data corresponding to the user identification data;
the second acquisition submodule is used for acquiring the telemetering data according to the positioning data of the charging order data; and the arrangement submodule is used for arranging the telemetry data according to the time sequence to form the telemetry data group.
Optionally, the detection module includes:
the detection sub-module is used for detecting whether a time interval between first telemetering data and second telemetering data is larger than a preset time interval or not, wherein the first telemetering data and the second telemetering data are two telemetering data in the telemetering data group, and the sequence of the first telemetering data and the second telemetering data is front and back;
a confirmation submodule, configured to determine that the state of the time series of the telemetry data set is a non-stationary state if the determination result is positive;
and the compensation submodule is used for compensating the time sequence of the telemetry data set to obtain the telemetry data of which the state of the time sequence is a stable state.
Optionally, the compensation sub-module includes:
an adding unit for adding compensation telemetry data in a time interval between the first telemetry data and the second telemetry data;
and the confirmation unit is used for taking the telemetry data group added with the compensation telemetry data as a time-series telemetry data group with a steady state.
Optionally, the detection module includes:
a generation sub-module to generate the compensated telemetry data from the first telemetry data and the second telemetry data.
Optionally, the adding unit includes:
the calculating subunit is used for calculating the adding times of the compensation telemetering data according to the time interval between the first telemetering data and the second telemetering data and a preset time interval;
and the adding subunit is used for adding the compensation telemetry data in a time interval between the first telemetry data and the second telemetry data by using the time of the first telemetry data or the second telemetry data as a starting point according to the adding times and using a preset time interval.
Optionally, the compensation device further comprises:
and the storage module is used for storing the telemetering data group with the stable state in the time sequence into a preset database.
A third aspect of an embodiment of the present application provides a server, including: a memory, a processor and a computer program stored in the memory and executable on the processor, the processor when executing the computer program implementing the steps of the method for compensating time series telemetry data as described above.
A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, including: the computer-readable storage medium stores a computer program which, when executed by a processor, performs the steps of the method of compensating, for example, time series telemetry data.
In a fifth aspect, the present application provides a computer program product, which when run on a server, causes the server to execute the method for compensating time series telemetry data according to any one of the first aspect.
It is understood that the beneficial effects of the second aspect to the fifth aspect can be referred to the related description of the first aspect, and are not described herein again.
Compared with the prior art, the embodiment of the application has the advantages that: according to the method and the device, the time sequence of the telemetering data group is compensated when the state of the time sequence of the telemetering data group is detected to be in a non-steady state by acquiring the telemetering data group, the telemetering data group of which the state is in a steady state is obtained, and the problem that in the prior art, a time sequence model cannot be built due to the fact that the state of the time sequence of the telemetering data group is in the non-steady state, and therefore the follow-up analysis of the charging process of a user according to the time sequence model is not facilitated is avoided.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic diagram of a compensation system for time series telemetry data according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating a method for compensating time series telemetry data according to a second embodiment of the present application;
FIG. 3 is another schematic flow chart diagram of a method for compensating time series telemetry data according to a third embodiment of the present application;
FIG. 4 is a flowchart illustrating an implementation of step S302 in FIG. 3 of a method for compensating time-series telemetry data according to a fourth embodiment of the present disclosure;
fig. 5 is a flowchart illustrating an implementation of step S202 in fig. 2 of the method for compensating time-series telemetry data according to the fifth embodiment of the present application;
FIG. 6 is a schematic flow chart illustrating a method for compensating time series telemetry data according to a sixth embodiment of the present disclosure;
FIG. 7 is an interactive schematic diagram of a compensation system for time series telemetry data provided in a seventh embodiment of the present application;
FIG. 8 is a schematic structural diagram of an apparatus for compensating time-series telemetry data according to an eighth embodiment of the present application;
fig. 9 is a schematic diagram of a server provided in the ninth embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Example one
Referring to fig. 1, a schematic structural diagram of a compensation system for time-series telemetry data provided in an embodiment of the present application may include a server 11, a terminal device 12 communicatively connected to the server, and a charging device 13 communicatively connected to the server.
The server is used for searching the terminal equipment according to the user identification data, sending the user identification data to the terminal equipment, acquiring charging order data corresponding to the user identification data returned by the terminal equipment, searching the charging device according to the positioning data of the charging order data, sending the positioning data of the charging order data to the charging device, acquiring the telemetering data returned by the charging device according to the positioning data of the charging order data, arranging the telemetering data according to a time sequence to form a telemetering data group, and when the state of detecting the time sequence of the telemetering data group is a non-steady state, compensating the time sequence of the telemetering data group to obtain the telemetering data group of which the state of the time sequence is a steady state.
Wherein the positioning data and the telemetry data correspond to the same charging device.
The terminal equipment is used for receiving the user identification data, searching the charging order data corresponding to the user identification data, and returning the charging order data to the server.
The terminal device includes, but is not limited to, a mobile phone or a computer.
The charging device is used for receiving the positioning data, searching the telemetering data corresponding to the positioning data and returning the telemetering data to the server.
The charging device may be a device for charging a vehicle, such as a charging pile.
In the embodiment of the application, the server acquires the locating data corresponding to the charging device from the terminal equipment through the user identification data, and acquires the telemetering data corresponding to the charging process of the user from the charging device according to the locating data, the telemetering data is arranged according to the time sequence to form a telemetering data group, when the state of the time sequence for detecting the telemetering data group is a non-steady state, the time sequence for detecting the telemetering data group is compensated, the telemetering data group with the stable state of the time sequence is obtained, so that the time sequence model is subsequently established according to the telemetering data group, and the charging process of the user is analyzed.
Example two
Referring to fig. 2, a flow chart of a method for compensating time-series telemetry data provided by an embodiment of the present application, where the method may be specifically applied to a server, may include the following steps:
s201, acquiring a telemetry data set.
The telemetering data group comprises at least two pieces of telemetering data, and the telemetering data group is a data group formed by arranging the telemetering data according to a time sequence;
the telemetering data refers to real-time data received by the charging device through a set sensor, namely data recorded in the process of charging the user vehicle, and for example, the telemetering data includes, but is not limited to, current data, voltage data, power data and the like.
It is understood that the server obtains telemetry data corresponding to the charging process of the user from the charging device, and then arranges the telemetry data in time sequence to form a telemetry data group.
S202, when the state of the time sequence of the telemetering data group is detected to be a non-steady state, the time sequence of the telemetering data group is compensated, and the telemetering data group with the time sequence state being a steady state is obtained.
The time sequence of the telemetering data group is a sequence formed by arranging numerical values of the telemetering data on different times according to time sequence;
the above-mentioned state of the time series is a steady state, which means that the data variable of the time series does not change with time, that is, the data variable of the time series shows a long-term trend and finally tends to a constant or a linear function, for example, the time series of the array is "1 s, 3s, 5s, 7s, 9 s", then the state of the time series of the array is a steady state:
the non-stationary state of the time series means that the data variable of the time series changes with time, that is, the data variable of the time series cannot show a long-term trend and finally tends to be a constant or a linear function, for example, the time series of the array is "1 s, 2s, 5s, 8s, 10 s", and then the state of the time series of the array is the non-stationary state.
It will be appreciated that the state of the time series of telemetry data sets is transitioned from a non-stationary state to a stationary state by compensating for the time series of telemetry data sets that are in a non-stationary state.
In the embodiment of the application, the telemetering data group with the non-steady state can be compensated to obtain the telemetering data group with the steady state time sequence, so that a time sequence model can be built through the telemetering data group with the steady state time sequence, and the charging process of a user can be analyzed according to the time sequence model.
EXAMPLE III
The purpose of this embodiment is to present a detailed description of the process of acquiring a telemetry data set.
Referring to fig. 3, another flow chart of a method for compensating time-series telemetry data provided in an embodiment of the present application is shown, where the method may be specifically applied to a server, and the method may include the following steps:
step S301, charging order data corresponding to the user identification data is obtained.
The user identification data may refer to data identifying charging details of a user, that is, data binding the charging details of the user, and include, but are not limited to, a user ID, an order ID, and the like;
the charging order data may refer to data recorded in a process that a user logs in a charging platform of the terminal device, places an order through the charging platform, and then charges the vehicle to a station specified by the charging platform, that is, data recording details of charging details of the user on the charging platform, for example, the data includes, but is not limited to, a user ID, an order electric quantity, a user mobile phone number, an order duration, an equipment ID of the charging device, a socket serial number of the charging device, an order ending reason code, an equipment type of the charging device, an order starting time, an order ending time, a station ID of the charging device, a station name of the charging device, a box factory number of the charging device, and the like.
Specifically, the server searches the terminal device through the user identification data, the server sends the user identification data to the terminal device, and the charging order data corresponding to the user identification data returned by the terminal device is sent to the server.
The terminal device refers to a terminal device used by a user, such as a mobile phone or a computer.
It can be understood that, a user logs in the charging platform of the terminal device through the user ID, places an order on the charging platform to generate an order ID, and then, in the process that the user charges the vehicle through the charging device to the charging station specified by the charging platform, the terminal device records the charging order data corresponding to the user identification data, so that the server can obtain the charging order data corresponding to the user identification data from the terminal device through the user identification data.
And step S302, acquiring telemetering data according to the positioning data of the charging order data.
Wherein the positioning data and the telemetry data correspond to the same charging device;
the positioning data refers to data including charging device identity information corresponding to the order ID, that is, data bound to charging device identity information for charging the user vehicle, and includes, but is not limited to, an equipment ID of the charging device, an equipment type of the charging device, a socket number of the charging device, the order ID, an order start time, an order end time, and the like;
the telemetering data refers to real-time data received by the charging device through a set sensor, namely data recorded in the process of charging the user vehicle, and for example, the telemetering data includes, but is not limited to, current data, voltage data, power data and the like.
Specifically, the server searches the charging device through the positioning data, the positioning data is sent to the charging device, and the charging device returns the telemetering data corresponding to the positioning data to the server.
It can be understood that, a user places an order on the charging platform through the terminal device, and then the user charges through the charging device to a charging station specified by the charging platform, the terminal device records an order ID of the user and location data of the charging device corresponding to the order ID, such as an equipment ID of the charging device, an equipment type of the charging device, a socket serial number of the charging device, and correspondingly, the charging device also records telemetry data corresponding to the order ID, such as current data, voltage data, power data, and the like, through the sensor, so that the server can search for the corresponding charging device through the location data and obtain the telemetry data corresponding to the location data from the charging device.
And step S303, arranging the telemetering data according to a time sequence to form a telemetering data group.
It will be appreciated that since the telemetry data sets are formed by time-series arrangement of telemetry data, subsequent detection of the time-series status of telemetry data is facilitated.
And S304, when the state of the time sequence of the telemetering data group is detected to be a non-steady state, compensating the time sequence of the telemetering data group to obtain the telemetering data group of which the state of the time sequence is a steady state.
It should be noted that step S304 is the same as step S202, and is not described herein again.
In the embodiment of the application, charging order data of a user are acquired through terminal equipment, then telemetering data of the user are acquired through a charging device, and finally the telemetering data are arranged according to a time sequence to form a telemetering data group, so that the state of the time sequence of the telemetering data group can be detected conveniently, a time sequence model can be subsequently built according to the telemetering data group, and the charging process of the user is analyzed by using the built time sequence model.
Example four
The purpose of this embodiment is to specifically describe step S302 in the third embodiment.
Referring to fig. 4, a flowchart illustrating an implementation of step S302 in fig. 3 of a time-series telemetry data provided in this embodiment of the present application, where the method may be specifically applied to the server in the third embodiment, and the method may include the following steps:
step S401, charging order data corresponding to the user identification data is obtained.
The user identification data may refer to data identifying charging details of a user, that is, data binding the charging details of the user, and include, but are not limited to, a user ID, an order ID, and the like;
the charging order data may refer to data recorded in a process that a user logs in a charging platform of the terminal device, places an order through the charging platform, and then charges the vehicle to a station specified by the charging platform, that is, data recording details of charging details of the user on the charging platform, for example, the data includes, but is not limited to, a user ID, an order electric quantity, a user mobile phone number, an order duration, an equipment ID of the charging device, a socket serial number of the charging device, an order ending reason code, an equipment type of the charging device, an order starting time, an order ending time, a station ID of the charging device, a station name of the charging device, a box factory number of the charging device, and the like.
It should be noted that step S401 is the same as step S301, and is not described herein again.
Step S402, searching positioning data of the charging order data.
The positioning data refers to data including charging device identity information corresponding to the order ID, that is, data bound to charging device identity information for charging the user vehicle, and includes, for example, but not limited to, an equipment ID of the charging device, an equipment type of the charging device, a socket serial number of the charging device, a box factory number of the charging device, the order ID, an order start time, and an order end time.
Step S403 generates acquisition request information from the positioning data.
The acquisition request information is used for indicating the charging device to return telemetering data.
Specifically, the identification address information is searched from the configuration file according to the positioning data, and the positioning data is added to the identification address information to obtain the acquisition request information.
It should be noted that the identification address information may be a URL, i.e., a network address.
It can be understood that the configuration file of the server stores the identification address information of the charging device, the identification address can be searched from the configuration file according to the positioning data, and then the positioning data is added to the identification address information to obtain the acquisition request information, so as to prepare for subsequent access to the charging device.
Step S404, sending the acquisition request information to the charging device.
It is understood that the charging device may be accessed by obtaining the request message, such that the charging device may return telemetry data to the server upon receiving the request message.
And step S405, receiving the telemetering data returned by the charging device.
Wherein the positioning data and the telemetry data correspond to the same charging device;
the positioning data refers to data including charging device identity information corresponding to the order ID, that is, data bound to charging device identity information for charging the user vehicle, and includes, for example, but is not limited to, an equipment ID of the charging device, an equipment type of the charging device, a socket number of the charging device, the order ID, an order start time, an order end time, and the like;
the telemetering data refers to real-time data received by the charging device through a set sensor, namely, data bound to charging device identity information for charging a user vehicle, and includes, but is not limited to, current data, voltage data, power data and the like.
It is understood that, after receiving the acquisition request message, the charging device parses the positioning data from the acquisition request message, searches for the telemetry data according to the positioning data, and then returns the telemetry data to the server.
And step S406, arranging the telemetric data according to a time sequence to form a telemetric data group.
It will be appreciated that since the telemetry data sets are formed by time-series arrangement of telemetry data, subsequent detection of the time-series status of telemetry data is facilitated.
And step S407, when the state of the time sequence of the telemetering data group is detected to be a non-steady state, compensating the time sequence of the telemetering data group to obtain the telemetering data group of which the state of the time sequence is a steady state.
It should be noted that steps S406 to S407 are the same as steps S303 to S304, and are not described herein again.
In the embodiment of the application, the identification address information is searched from the configuration file according to the positioning data of the charging order data, the positioning data is added to the identification address information, and the acquisition request information is obtained, so that the charging device is accessed by using the acquisition request information, and the effect of effectively acquiring the telemetering data returned by the charging device is achieved.
EXAMPLE five
The purpose of this embodiment is to present a detailed description of the process of detecting the state of the time series of telemetry data and the process of compensating for the time series of telemetry data sets.
Referring to fig. 5, a flowchart illustrating an implementation of step S202 in fig. 2 of the compensation method for time-series telemetry provided in the embodiment of the present application, where the method may be specifically applied to the server in the second embodiment, and the method may include the following steps:
step S501, whether the time interval between the first telemetric data and the second telemetric data is larger than a preset time interval is detected.
Wherein the first telemetry data and the second telemetry data are two telemetry data in a telemetry data group with a sequence in time series being a front-back sequence, for example, the time series of the telemetry data group is "90 s, 120s, 170s, 210 s", then the time of the first telemetry data may be "120 s" as described above, and the time of the second telemetry data may be "170 s" as described above;
the predetermined time interval refers to a constant that is preset to the time-series data variable of the telemetry data set, i.e., to make the time variable of each telemetry data in the telemetry data set exhibit a long-term trend and eventually trend, and may be 90S, for example.
It will be appreciated that the present embodiment detects the state of the time series of telemetry data sets in the following manner: and detecting whether the time interval between any two telemetric data in the time sequence in the sequence of front and back in the telemetric data group is larger than a preset time interval.
In some embodiments, the manner of detecting the state of the time series of telemetry data sets may be: it is detected whether the mean of the time series of telemetry data sets is a time-independent constant.
In other embodiments, the manner of detecting the state of the time series of telemetry data sets may also be: it is detected whether the variance of the time series of the telemetry data set is a time-independent constant.
And step S502, if yes, the state of the time series of the telemetry data set is a non-steady state.
It is understood that if the time interval between the first telemetry data and the second telemetry data is detected to be greater than the predetermined time interval, the telemetry data variable of the time series of the telemetry data set, i.e., the time interval between the telemetry data, cannot exhibit a long-term trend and eventually becomes a constant or linear function, indicating that the state of the time series of the telemetry data set is a non-stationary state.
For example, the preset time interval is 90S, if the time interval between the first telemetry data and the second telemetry data is 60S, it is detected that the time interval between the first telemetry data and the second telemetry data is smaller than the preset time interval, and the state of the time series of the telemetry data is a steady state;
the preset time interval is 90S, if the time interval between the first telemetering data and the second telemetering data is 100S, the time interval between the first telemetering data and the second telemetering data is detected to be larger than the preset time interval, and the state of the time sequence of the telemetering data is a non-steady state.
And S503, compensating the time sequence of the telemetry data group to obtain the telemetry data with the time sequence in a stable state.
Specifically, the process of compensating the time series of the telemetry data set according to the following three steps, namely, the first step, the second step and the last step, and obtaining the telemetry data with the time series of the steady state is specifically described.
First, compensation telemetry data is generated from the first telemetry data and the second telemetry data.
The compensated telemetry data is added to the telemetry data group to compensate the time series of the telemetry data group.
By way of example and not limitation, an average telemetry between the first telemetry and the second telemetry is calculated as the value of the compensation telemetry, e.g., "2A current data and 4V voltage data" for the first telemetry and "3A current data and 6V voltage data" for the second telemetry, and "2.5A current value and 5V voltage data" for the compensation telemetry.
Compensation telemetry data is then added during the time interval between the first telemetry data and the second telemetry data.
By way of example and not limitation, the process of adding compensation telemetry data during the time interval between the first telemetry data and the second telemetry data is described in detail below in terms of a first step and a second step.
The first step is as follows: and calculating the adding times of the compensation telemetry data according to the time interval between the first telemetry data and the second telemetry data and the preset time interval.
It is understood that the present embodiment calculates the number of additions of the compensation telemetry data according to the relationship between the time interval between the first telemetry data and the second telemetry data and the multiple of the preset time interval, that is, the time interval between the first telemetry data and the second telemetry data is greater than the multiple of the preset time interval as the value of the number of additions of the compensation telemetry data.
For example, the preset time interval is 90s, and when the interval between the first telemetry data and the second telemetry data is detected to be 130s, the value of the adding times of the compensation telemetry data is 1 time because the 130s is greater than the 1 time multiple value of the 90s and less than the 2 time multiple value of the 90 s;
the preset time interval is 90s, and when the interval between the first telemetry data and the second telemetry data is 210s, the value of the adding time of the compensation telemetry data is 2 times because the 210s is greater than the value of 2 times of 90s and less than the value of 3 times of 90 s.
The second step is that: and adding compensation telemetry data in a time interval between the first telemetry data and the second telemetry data at a preset time interval by taking the time of the first telemetry data or the second telemetry data as a starting point according to the adding times.
For example, the preset time interval is 90s, the time of the first telemetry data is 2019-10-209: 18:10, and the time of the second telemetry data is 2019-10-209: 20:10, then, the time interval between the first telemetry data and the second telemetry data is 130s, the number of times of adding the compensation telemetry data is 1, the time of the first telemetry data is taken as a starting point, the compensation telemetry data is added once at the time interval of 90s from the time of the first telemetry data, namely, the time of the compensation telemetry data added to the time interval between the first telemetry data and the second telemetry data is 2019-10-199: 19: 40;
for example, the preset time interval is 90s, the time of the first telemetry data is 2019-10-209: 18:10, and the time of the second telemetry data is 2019-10-209: 21:40, then, the time interval between the first telemetry data and the second telemetry data is 210s, the adding times of the compensation telemetry data are 2 times, the time of the first telemetry data is taken as a starting point, the compensation telemetry data is added once at the time interval which is 90s away from the time of the first telemetry data, namely the time of the first compensation telemetry data is 2019-10-209: 19:40, then the compensation telemetry data is added once again at the time interval which is 90s away from the time of the compensation telemetry data, namely the time of the second compensation telemetry data is 2019-10-209: 21:10, and finally the time of the two compensation telemetry data added into the time interval between the first telemetry data and the second telemetry data is 2019-10-209: 21:10 respectively 209: 19:40 and 2019-10-209: 21: 10.
And finally, taking the telemetry data group added with the compensation telemetry data as a time-series telemetry data group with a steady state.
It can be understood that, in the telemetry data set, the time sequence of the telemetry data set is compensated by adding the compensation telemetry data to the time interval between two telemetry data in the time sequence in the front-back order in the telemetry data set, so that the time interval between any two telemetry data in the time sequence in the front-back order in the telemetry data set is a preset time interval, thus, the data variable of the time sequence of the telemetry data set does not change along with the change of time, the data variable of the time sequence shows a long-term trend and finally tends to a constant or a linear function, and the telemetry data set after adding the telemetry data is the telemetry data set in the time sequence in a steady state.
According to the method and the device, the state of the time series of the telemetering data group is judged by detecting whether the first telemetering data and the second telemetering data exist in the telemetering data group, and if the telemetering data group is detected to have the first telemetering data and the second telemetering data, the purpose of compensating the telemetering data group of the time series in the non-stationary state is achieved by adding the compensation telemetering data in the time interval between the first telemetering data and the second telemetering data, and the telemetering data group of the time series in the stationary state is obtained.
EXAMPLE six
The purpose of this embodiment is to compensate the telemetry data in the non-stationary state of the time series, and then perform subsequent processing on the telemetry data in the stationary state of the time series.
Fig. 6 is a schematic flow chart of a method for compensating time-series telemetry data according to an embodiment of the present disclosure, where the method may be specifically applied to a server, and the method may include the following steps:
s601, acquiring a telemetry data set.
S602, when the state of the time sequence of the telemetering data group is detected to be a non-steady state, the time sequence of the telemetering data group is compensated, and the telemetering data group with the time sequence state being a steady state is obtained.
It should be noted that steps S601 to S602 are the same as steps S201 to S202, and are not described again here.
And S603, storing the telemetry data group with the time sequence state being the steady state into a preset database.
The preset database may be a mongodb non-relational database.
It can be understood that, because the mongodb non-relational database has the advantages of flexible structure, freer table structure change, no cost for alter every time, suitability for quick service iteration, natural fit with most languages, support arrays, nested documents and other data types, the telemetering data group with the time series state being the steady state is stored in the mongodb non-relational database, and a user reads data from the preset data group without extra processing, so that the user can experience high efficiency and smoothness.
According to the embodiment of the application, the telemetering data group with the stable state of the time sequence is stored in the preset database, so that a user can read data from the preset database without extra processing, convenience is provided for building a time sequence model for the telemetering data group with the stable state according to the state of the time sequence, and the follow-up charging process of the user is further utilized for analysis.
EXAMPLE seven
Referring to fig. 7, an interactive schematic view of a compensation method for time series telemetry data provided in an embodiment of the present application is provided, where a main flow execution body of the embodiment is a compensation system, the compensation system includes a server, a terminal device communicatively connected to the server, and a charging device communicatively connected to the server, and a process of the compensation system is detailed as follows:
step S701, after searching the terminal equipment according to the user identification data, the server sends the user identification data to the terminal equipment;
step S702, after receiving the user identification data, the terminal equipment searches for charging order data corresponding to the user identification data;
step S703, the terminal equipment returns the charging order data to the server;
step S704, the server receives the charging order data returned by the terminal equipment, searches the charging device according to the positioning data of the charging order, and then sends the positioning data of the charging order data to the charging device;
step S705, after the charging device receives the positioning data, searching telemetering data corresponding to the positioning data;
step S706, the charging device returns the telemetering data to the server;
and step S707, after the server receives the telemetering data returned by the charging device, arranging the telemetering data according to a time sequence to form a telemetering data group.
Step S708, when the server detects that the state of the time series of the telemetry data set is a non-stationary state, compensating the time series of the telemetry data set to obtain the telemetry data set of which the state of the time series is a stationary state.
In the embodiment of the application, the server can compensate the telemetering data group in a non-steady state to obtain the telemetering data group in a steady state time sequence, so that a time sequence model can be built through the telemetering data group in the steady state time sequence, and the charging process of a user can be analyzed according to the time sequence model.
Example eight
The following describes a compensation apparatus for time series telemetry data provided by the embodiments of the present application. The time-series telemetry data compensation device of the present embodiment corresponds to the time-series telemetry data compensation method described above.
Fig. 8 is a schematic structural diagram of an apparatus for compensating time-series telemetry data according to an embodiment of the present disclosure, where the apparatus may be specifically integrated in a server, and the apparatus may include:
an obtaining module 81 configured to obtain a telemetry data set, where the telemetry data set includes at least two pieces of telemetry data;
and the detection module 82 is configured to compensate the time series of the telemetry data set when detecting that the time series of the telemetry data set is in a non-stationary state, so as to obtain the telemetry data set in a stationary state.
Optionally, the obtaining module includes:
the first obtaining sub-module is used for obtaining charging order data corresponding to the user identification data;
the second acquisition submodule is used for acquiring the telemetering data according to the positioning data of the charging order data; and the arrangement submodule is used for arranging the telemetry data according to the time sequence to form the telemetry data group.
Optionally, the detection module includes:
the detection sub-module is used for detecting whether a time interval between first telemetering data and second telemetering data is larger than a preset time interval or not, wherein the first telemetering data and the second telemetering data are two telemetering data in the telemetering data group, and the sequence of the first telemetering data and the second telemetering data is front and back;
a confirmation submodule, configured to determine that the state of the time series of the telemetry data set is a non-stationary state if the determination result is positive;
and the compensation submodule is used for compensating the time sequence of the telemetry data set to obtain the telemetry data of which the state of the time sequence is a stable state.
Optionally, the compensation sub-module includes:
an adding unit for adding compensation telemetry data in a time interval between the first telemetry data and the second telemetry data;
and the confirmation unit is used for taking the telemetry data group added with the compensation telemetry data as a time-series telemetry data group with a steady state.
Optionally, the detection module includes:
a generation sub-module to generate the compensated telemetry data from the first telemetry data and the second telemetry data.
Optionally, the adding unit includes:
the calculating subunit is used for calculating the adding times of the compensation telemetering data according to the time interval between the first telemetering data and the second telemetering data and a preset time interval;
and the adding subunit is used for adding the compensation telemetry data in a time interval between the first telemetry data and the second telemetry data by using the time of the first telemetry data or the second telemetry data as a starting point according to the adding times and using a preset time interval.
Optionally, the compensation device further comprises:
and the storage module is used for storing the telemetering data group with the stable state in the time sequence into a preset database.
According to the embodiment of the application, the telemetering data group with the non-steady state can be compensated, the telemetering data group with the steady state time sequence is obtained, a time sequence model can be built through the telemetering data group with the steady state time sequence, and the follow-up analysis of the user charging process according to the time sequence model is facilitated.
Fig. 9 is a schematic diagram of a server 9 provided in an embodiment of the present application. As shown in fig. 9, the server 9 of this embodiment includes: a processor 90, a memory 91 and a computer program 92, such as a push messaging program, stored in said memory 91 and operable on said processor 90. The processor 90, when executing the computer program 92, implements the steps in the above-described method embodiment of compensating for time series telemetry data, such as steps S201-S202 shown in fig. 2. Alternatively, the processor 90, when executing the computer program 92, implements the functions of the modules/units in the above-described device embodiments, such as the functions of the modules 81 to 82 shown in fig. 8.
Illustratively, the computer program 92 may be partitioned into one or more modules/units that are stored in the memory 91 and executed by the processor 90 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 92 in the server 9. For example, the computer program 92 may be divided into an obtaining module, an analyzing module, a searching module, and a pushing module, and the specific functions of each module are as follows:
the acquisition module is used for acquiring a telemetry data set, and the telemetry data set comprises at least two pieces of telemetry data;
and the detection module is used for compensating the time sequence of the telemetering data group when detecting that the state of the time sequence of the telemetering data group is a non-steady state, so as to obtain the telemetering data group of which the state of the time sequence is a steady state.
The server 9 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The server 9 may include, but is not limited to, a processor 90, a memory 91. Those skilled in the art will appreciate that fig. 9 is merely an example of a server 9 and does not constitute a limitation of the server 9 and may include more or fewer components than shown, or some components in combination, or different components, e.g., the server 9 may also include input output devices, network access devices, buses, etc.
The Processor 90 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 91 may be an internal storage unit of the server 9, such as a hard disk or a memory of the server 9. The memory 91 may also be an external storage device of the server 9, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) and the like provided on the server 9. Further, the memory 91 may also include both an internal storage unit of the server 9 and an external storage device. The memory 91 is used for storing the computer program and other programs and data required by the server 9. The memory 91 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed server and method may be implemented in other ways. For example, the above-described server embodiments are merely illustrative, and for example, the division of the modules or units is only one logical functional division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A method of compensating time series telemetry data, comprising:
acquiring a telemetry data set, wherein the telemetry data set comprises at least two pieces of telemetry data;
and when the state of the time sequence of the telemetering data group is detected to be a non-steady state, compensating the time sequence of the telemetering data group to obtain the telemetering data group of which the state of the time sequence is a steady state.
2. The method of compensating time series telemetry data in accordance with claim 1, wherein the acquiring a set of telemetry data comprises:
acquiring charging order data corresponding to the user identification data;
acquiring the telemetering data according to the positioning data of the charging order data;
and arranging the telemetry data according to a time sequence to form the telemetry data group.
3. The method for compensating time series telemetry data according to claim 1 or 2, wherein the step of compensating the time series of the telemetry data group to obtain the telemetry data group with the time series of the stationary state when the time series of the telemetry data group is detected to be in the non-stationary state comprises the steps of:
detecting whether a time interval between first telemetry data and second telemetry data is larger than a preset time interval, wherein the first telemetry data and the second telemetry data are two pieces of telemetry data in the telemetry data group and are sequentially arranged in the time sequence;
if so, the state of the time series of the telemetry data set is a non-steady state;
and compensating the time sequence of the telemetry data group to obtain the telemetry data of which the state of the time sequence is a steady state.
4. The method of compensating time series telemetry data according to claim 3, wherein the step of compensating the time series of the telemetry data set to obtain a time series telemetry data set with a steady state comprises:
adding compensation telemetry data in a time interval between the first telemetry data and the second telemetry data;
and taking the telemetry data group added with the compensation telemetry data as a time-series telemetry data group with a steady state.
5. The method of compensating for time series telemetry data according to claim 4, wherein prior to adding the compensating telemetry data in the time interval between the first telemetry data and the second telemetry data, further comprising:
generating the compensated telemetry data from the first telemetry data and the second telemetry data.
6. The method of compensating for time series telemetry data according to claim 4, wherein adding compensating telemetry data in the time interval between the first telemetry data and the second telemetry data comprises:
calculating the adding times of the compensation telemetry data according to the time interval between the first telemetry data and the second telemetry data and a preset time interval;
adding the compensation telemetry data in a time interval between the first telemetry data and the second telemetry data at a preset time interval by taking the time of the first telemetry data or the second telemetry data as a starting point according to the adding times.
7. The method for compensating time-series telemetry data according to claim 1 or 2, wherein the step of compensating the time-series telemetry data set when the time-series telemetry data set is detected to be in a non-stationary state, and after obtaining the time-series telemetry data set in a stationary state, further comprises:
and storing the telemetry data group with the time series state as the steady state into a preset database.
8. An apparatus for compensating time series telemetry data, comprising:
the acquisition module is used for acquiring a telemetry data set, and the telemetry data set comprises at least two pieces of telemetry data;
and the detection module is used for compensating the time sequence of the telemetering data group when detecting that the state of the time sequence of the telemetering data group is a non-steady state, so as to obtain the telemetering data group of which the state of the time sequence is a steady state.
9. A server comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program performs the steps of the method of compensating time series telemetry data according to any of claims 1 to 7.
10. Computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method for compensating time-series telemetry data according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911355577.3A CN111198982A (en) | 2019-12-25 | 2019-12-25 | Time series telemetry data compensation method and device and server |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911355577.3A CN111198982A (en) | 2019-12-25 | 2019-12-25 | Time series telemetry data compensation method and device and server |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111198982A true CN111198982A (en) | 2020-05-26 |
Family
ID=70746801
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911355577.3A Pending CN111198982A (en) | 2019-12-25 | 2019-12-25 | Time series telemetry data compensation method and device and server |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111198982A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170337227A1 (en) * | 2016-05-17 | 2017-11-23 | Microsoft Technology Licensing, Llc | Multidimensional application monitoring visualization and search |
| CN107577648A (en) * | 2017-09-04 | 2018-01-12 | 北京京东尚科信息技术有限公司 | For handling the method and device of multivariate time series data |
| CN109238303A (en) * | 2018-10-25 | 2019-01-18 | 麒麟合盛网络技术股份有限公司 | A kind of exercise data compensation method and device |
| CN109635854A (en) * | 2018-11-26 | 2019-04-16 | 国网冀北电力有限公司 | Based on markovian charging pile failure prediction method and device |
| CN109948664A (en) * | 2019-02-28 | 2019-06-28 | 深圳智链物联科技有限公司 | Charge mode recognition methods, device, terminal device and storage medium |
-
2019
- 2019-12-25 CN CN201911355577.3A patent/CN111198982A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170337227A1 (en) * | 2016-05-17 | 2017-11-23 | Microsoft Technology Licensing, Llc | Multidimensional application monitoring visualization and search |
| CN107577648A (en) * | 2017-09-04 | 2018-01-12 | 北京京东尚科信息技术有限公司 | For handling the method and device of multivariate time series data |
| CN109238303A (en) * | 2018-10-25 | 2019-01-18 | 麒麟合盛网络技术股份有限公司 | A kind of exercise data compensation method and device |
| CN109635854A (en) * | 2018-11-26 | 2019-04-16 | 国网冀北电力有限公司 | Based on markovian charging pile failure prediction method and device |
| CN109948664A (en) * | 2019-02-28 | 2019-06-28 | 深圳智链物联科技有限公司 | Charge mode recognition methods, device, terminal device and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108427705B (en) | Electronic device, distributed system log query method and storage medium | |
| CN111898643B (en) | Semantic matching method and device | |
| CN110113196B (en) | Protocol configuration method, device, equipment and medium | |
| CN104205153A (en) | Mobile communication terminal and method of recommending application or content | |
| CN103064933A (en) | Data query method and system | |
| CN109918594B (en) | Information display method and device | |
| CN104133765B (en) | The test case sending method of network activity and test case server | |
| CN110704677B (en) | Program recommendation method and device, readable storage medium and terminal equipment | |
| CN104866985A (en) | Express bill number identification method, device and system | |
| CN110750433A (en) | Interface test method and device | |
| US20200204688A1 (en) | Picture book sharing method and apparatus and system using the same | |
| CN104765792A (en) | Dimension data storing method, device and system | |
| CN102970380B (en) | Obtain method and the cloud storage server of the media data of cloud storage file | |
| CN111002859A (en) | Method and device for identifying private patch board of charging pile, terminal equipment and storage medium | |
| CN116827774A (en) | Service analysis method, device, equipment and storage medium | |
| CN109522334B (en) | Lack material inquiring party, lack material inquiring system and electronic equipment | |
| CN106651408B (en) | Data analysis method and device | |
| CN111198982A (en) | Time series telemetry data compensation method and device and server | |
| CN108959294A (en) | A kind of method and apparatus accessing search engine | |
| CN106294700A (en) | The storage of a kind of daily record and read method and device | |
| CN111162792A (en) | Compression method and device for power load data | |
| CN107180281B (en) | Path planning optimization method, device and equipment for electric automobile | |
| CN113787977A (en) | Vehicle maintenance method, communication device, and storage medium | |
| CN111047388A (en) | Splicing method and device of charging data and server | |
| CN113011017B (en) | Data processing method, device, equipment and storage medium based on product modularization |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |