CN109743224A - Electrically-charging equipment data processing method and device - Google Patents
Electrically-charging equipment data processing method and device Download PDFInfo
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- CN109743224A CN109743224A CN201811614937.2A CN201811614937A CN109743224A CN 109743224 A CN109743224 A CN 109743224A CN 201811614937 A CN201811614937 A CN 201811614937A CN 109743224 A CN109743224 A CN 109743224A
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Abstract
The invention discloses a kind of electrically-charging equipment data processing method and device.This method comprises: obtaining the data on flows of charging pile；Statistic of classification is carried out to the data on flows from different charging piles, obtains the data on flows corresponding to each charging pile；It is predicted according to data on flows of the data on flows of each charging pile to subsequent time, obtains predicted flow rate data；When the data on flows of the subsequent time of charging pile and the gap of predicted flow rate data exceed preset threshold, abnormality alarm is issued.Through the invention, achieved the effect that sound an alarm in time when Traffic Anomaly occurs in electrically-charging equipment.
Description
Technical field
The present invention relates to electrically-charging equipment fields, in particular to a kind of electrically-charging equipment data processing method and device.
Background technique
Now with the increasingly developed of charging pile, the safety for controlling network is gradually taken seriously, in order to protect charging to set
Network security is applied, flow detection is carried out in electrically-charging equipment network and is urgently realized with audit work.
If operation irregularity occurs in electrically-charging equipment, the abnormal conditions such as is invaded, needs timely learning and processing of following up,
There is no the schemes that are monitored to the flow of electrically-charging equipment in the related technology, thus when there is Traffic Anomaly in electrically-charging equipment without
Method timely learning.
Aiming at the problem that being unable to learn in time when Traffic Anomaly occurs in electrically-charging equipment in the related technology, not yet propose have at present
The solution of effect.
Summary of the invention
The main purpose of the present invention is to provide a kind of electrically-charging equipment data processing method and device, to solve electrically-charging equipment
There is the problem of being unable to learn in time when Traffic Anomaly.
To achieve the goals above, according to an aspect of the invention, there is provided a kind of electrically-charging equipment data processing method,
This method comprises: obtaining the data on flows of charging pile；Statistic of classification is carried out to the data on flows from different charging piles, is obtained
Data on flows corresponding to each charging pile；It is carried out according to data on flows of the data on flows of each charging pile to subsequent time pre-
It surveys, obtains predicted flow rate data；Exceed in the gap of the data on flows and the predicted flow rate data of the subsequent time of charging pile
When preset threshold, abnormality alarm is issued.
Further, after issuing abnormality alarm, the method also includes: draw the change of predicted flow rate data at any time
Change the actual flow datagram of figure and charging pile；The variation diagram and actual flow datagram are shown on interface.
Further, the data on flows for obtaining charging pile includes: to obtain the data packet received from monitoring host network card；It is logical
Filtering rule is crossed, the TCP flow amount packet in the data packet is extracted；The source IP in the IP packet of layer is wrapped according to the TCP flow amount
Field judges whether present flow rate packet is data on flows that corresponding charging pile is sent；If it is, obtaining the conduct of present flow rate packet
The data on flows of charging pile.
Further, it is predicted, is obtained pre- according to data on flows of the data on flows of each charging pile to subsequent time
Measurement of discharge data include: to acquire the data on flows of the charging pile of predetermined time period as sample data；Based on the sample number
According to the data on flows ARIMA model for establishing each charging pile；Data on flows ARIMA model based on each charging pile is to charging pile
The data on flows of subsequent time is predicted, predicted flow rate data are obtained.
Further, before issuing abnormality alarm, the method also includes: judge the opening time of abnormality alarm function
It whether is more than default sleeping time；If the opening time of the abnormality alarm function is not above default sleeping time, etc.
Time to be opened was not above after default sleeping time issues abnormality alarm again.
To achieve the goals above, according to another aspect of the present invention, a kind of electrically-charging equipment data processing dress is additionally provided
It sets, which includes: acquiring unit, for obtaining the data on flows of charging pile；Statistic unit, for from different chargings
The data on flows of stake carries out statistic of classification, obtains the data on flows corresponding to each charging pile；Predicting unit, for according to each
The data on flows of charging pile predicts the data on flows of subsequent time, obtains predicted flow rate data；Alarm unit is used for
When the gap of the data on flows of the subsequent time of charging pile and the predicted flow rate data exceeds preset threshold, issue abnormal alert
Report.
Further, described device further include: drawing unit, for drawing predicted flow rate after issuing abnormality alarm
Data change with time the actual flow datagram of figure and charging pile；Display unit, for showing the variation on interface
Figure and actual flow datagram.
Further, the acquiring unit includes: acquisition module, for obtaining the data received from monitoring host network card
Packet；Extraction module, for extracting the TCP flow amount packet in the data packet by filtering rule；Judgment module, for according to institute
It states TCP flow amount and wraps the source IP field in the IP packet of layer and judge whether present flow rate packet is flow number that corresponding charging pile is sent
According to；Processing module, for when the judgment result is yes, obtaining data on flows of the present flow rate packet as charging pile.
To achieve the goals above, according to another aspect of the present invention, a kind of storage medium is additionally provided, including storage
Program, wherein equipment where controlling the storage medium in described program operation executes electrically-charging equipment number of the present invention
According to processing method.
To achieve the goals above, according to another aspect of the present invention, a kind of processor is additionally provided, for running journey
Sequence, wherein described program executes electrically-charging equipment data processing method of the present invention when running.
The data on flows that the present invention passes through acquisition charging pile；Classification system is carried out to the data on flows from different charging piles
Meter obtains the data on flows corresponding to each charging pile；According to the data on flows of each charging pile to the flow number of subsequent time
According to being predicted, predicted flow rate data are obtained；In the data on flows of the subsequent time of charging pile and the gap of predicted flow rate data
When beyond preset threshold, abnormality alarm is issued, solves the problems, such as to be unable to learn in time when Traffic Anomaly occurs in electrically-charging equipment, into
And achieve the effect that sound an alarm in time when Traffic Anomaly occurs in electrically-charging equipment.
Detailed description of the invention
The attached drawing constituted part of this application is used to provide further understanding of the present invention, schematic reality of the invention
It applies example and its explanation is used to explain the present invention, do not constitute improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is the flow chart of electrically-charging equipment data processing method according to an embodiment of the present invention；
Fig. 2 is the overall workflow design figure of the embodiment of the present invention；
Fig. 3 is the schematic diagram that function according to an embodiment of the present invention realizes GUI；
Fig. 4 is the schematic diagram of the selection according to an embodiment of the present invention charging pile IP to be checked；
Fig. 5 is the schematic diagram of traffic monitoring time range according to an embodiment of the present invention；
Fig. 6 is the traffic monitoring figure of different moments according to an embodiment of the present invention；
Fig. 7 is AR according to an embodiment of the present invention, and MA model summarizes schematic diagram；
Fig. 8 is the schematic diagram of electrically-charging equipment data processing equipment according to an embodiment of the present invention.
Specific embodiment
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.The present invention will be described in detail below with reference to the accompanying drawings and embodiments.
In order to make those skilled in the art more fully understand application scheme, below in conjunction in the embodiment of the present application
Attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is only
The embodiment of the application a part, instead of all the embodiments.Based on the embodiment in the application, ordinary skill people
Member's every other embodiment obtained without making creative work, all should belong to the model of the application protection
It encloses.
It should be noted that the description and claims of this application and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to embodiments herein described herein.In addition, term " includes " and " tool
Have " and their any deformation, it is intended that cover it is non-exclusive include, for example, containing a series of steps or units
Process, method, system, product or equipment those of are not necessarily limited to be clearly listed step or unit, but may include without clear
Other step or units listing to Chu or intrinsic for these process, methods, product or equipment.
The embodiment of the invention provides a kind of electrically-charging equipment data processing methods.
Fig. 1 is the flow chart of electrically-charging equipment data processing method according to an embodiment of the present invention, as shown in Figure 1, this method
The following steps are included:
Step S102: the data on flows of charging pile is obtained；
Step S104: carrying out statistic of classification to the data on flows from different charging piles, obtains corresponding to each charging
The data on flows of stake；
Step S106: it is predicted, is obtained pre- according to data on flows of the data on flows of each charging pile to subsequent time
Measurement of discharge data；
Step S108: exceed preset threshold in the data on flows of the subsequent time of charging pile and the gap of predicted flow rate data
When, issue abnormality alarm.
The embodiment is using the data on flows for obtaining charging pile；Classify to the data on flows from different charging piles
Statistics obtains the data on flows corresponding to each charging pile；According to the data on flows of each charging pile to the flow of subsequent time
Data are predicted, predicted flow rate data are obtained；In the data on flows of the subsequent time of charging pile and the difference of predicted flow rate data
When away from exceeding preset threshold, abnormality alarm is issued, solves the problems, such as to be unable to learn in time when Traffic Anomaly occurs in electrically-charging equipment,
And then achieve the effect that sound an alarm in time when Traffic Anomaly occurs in electrically-charging equipment.
In embodiments of the present invention, each charging pile has data on flows, and same or other non-datas on flows such as charge
The daily maintenance related data etc. of stake, what the technical solution of the present embodiment obtained is the data on flows of charging pile, is filled due to each
Electric stake has the data on flows of oneself, thus carries out statistic of classification to the data on flows from different charging piles, for example, obtaining
Corresponding to the data on flows of each charging pile, using the data on flows of each charging pile as reference frame to the flow of subsequent time
Data are predicted, then the real traffic data of charging pile subsequent time are compared with the data on flows of prediction, if
Two gap datas exceed preset threshold range, then it is abnormal to illustrate that the data on flows of charging pile exists, issues abnormality alarm at this time.
In this way, the Traffic Anomaly situation that can occur with timely learning electrically-charging equipment, and prompting can be sounded an alarm in time.
Optionally, after issuing abnormality alarm, predicted flow rate data is drawn and are changed with time the reality of figure and charging pile
Border data on flows figure；Variation diagram and actual flow datagram are shown on interface.
It, can after being predicted using the data on flows of each charging pile as reference frame the data on flows of subsequent time
To draw predicted flow rate data variation figure, after issuing abnormality alarm, predicted flow rate data can be changed with time figure
It is shown together with the actual flow datagram of charging pile, so that user more intuitively checks carry out data comparison.
Optionally, the data on flows for obtaining charging pile includes: to obtain the data packet received from monitoring host network card；Pass through
Filtering rule extracts the TCP flow amount packet in data packet；The judgement of the source IP field in the IP packet of layer is wrapped according to TCP flow amount to work as
Whether preceding flow packet is data on flows that corresponding charging pile is sent；If it is, obtaining stream of the present flow rate packet as charging pile
Measure data.
Optionally, it is predicted, is predicted according to data on flows of the data on flows of each charging pile to subsequent time
Data on flows includes: to acquire the data on flows of the charging pile of predetermined time period as sample data；It is established based on sample data
The data on flows ARIMA model of each charging pile；Based on the data on flows ARIMA model of each charging pile to a period of time under charging pile
The data on flows at quarter is predicted, predicted flow rate data are obtained.
Optionally, before issuing abnormality alarm, judge whether the opening time of abnormality alarm function is more than default sleep
Time；If the opening time of abnormality alarm function is not above default sleeping time, the opening time is waited to be not above pre-
If abnormality alarm is issued after sleeping time again.
Since abnormality alarm is needed using time series analysis, and time series analysis is needed to previous sample
It practises, so abnormality alarm function will sleep 100 seconds after starting traffic monitoring, after waiting has enough samples to be analyzed, then
Volume forecasting is carried out, makes the more accurate of prediction, greatly reduces abnormal rate of false alarm.
The embodiment of the invention also provides a kind of preferred embodiments, implement below with reference to preferred embodiment to the present invention
The technical solution of example is illustrated.
In order to the appearance of abnormal conditions such as preferably find electrically-charging equipment operation irregularity, invaded, when research is based on
Between sequence analyze traffic behavior dynamic monitoring and audit technique, establish the normal discharge row of electrically-charging equipment Yu rear end pipe platform
For mode, such as unit time traffic, communication frequency.By real-time traffic acquire and analyze, and with normal discharge behavior mould
Formula carries out matching the mode that notes abnormalities, such as situations such as flow increases sharply, frequency increases.
This system is broadly divided into three big modules, is flow collection module, flow analysis module and output module respectively.
Flow collection module major function is that each charging pile is acquired and is classified to the flow that monitoring host is sent；
Flow analysis module, for each charging pile, is analyzed respectively the data classified, and according to having acquired
The data on flows arrived is predicted the data of subsequent time in real time, is sounded an alarm to abnormal data；
Output module major function is to export to the result of analysis, including check each moment flow diagram and alarm signal
Breath.Fig. 2 is the overall workflow design figure of the embodiment of the present invention, as shown in Fig. 2, this system opens one to each charging pile
A process is monitored information analysis respectively and carries out exception monitoring, and the operation of each process is essentially identical.
Fig. 3 is the schematic diagram that function according to an embodiment of the present invention realizes GUI, and Fig. 4 is choosing according to an embodiment of the present invention
The schematic diagram for the charging pile IP to be checked is selected, as shown in figure 4, user can select different device IP to open at device IP
Or the traffic monitoring of corresponding charging pile is exited, Fig. 5 is the schematic diagram of traffic monitoring time range according to an embodiment of the present invention,
As shown in figure 5, user can select the time range of traffic monitoring on interface, Fig. 6 is difference according to an embodiment of the present invention
The traffic monitoring figure at moment, as shown in fig. 6,10 minutes discharge records change before the current time of this IP of 10.10.18.16,
The changes in flow rate for reflecting this IP in this 10 minutes apparent can be captured if any abnormal flow, certainly, this system
Flow analysis module can also alarm automatically abnormal flow.
Specifically, each module specific works content is as follows:
1, flow collection module
The design philosophy of flow collection module is to capture the data packet all received from monitoring host network card, passed through
Filter rule, TCP flow amount packet is left, remaining discarding.From the source IP field in the IP packet that TCP data wraps layer, so that it may know
This packet of road is the data on flows that corresponding charging pile is sent, and according to this mode, is sent to monitoring master to the charging pile of different IP
The data on flows of machine is classified.After classification, every 1 second, the data on flows size that n charging pile is sent is counted respectively, into
The record of row internal system.The result of record is predicted in real time for flow analysis module progress flow and abnormal alarm, supplies simultaneously
Module carries out the drafting of moment flow diagram out.
From discharge record at most only records current time, first 24 hours each charging pile flows send size statistics, and 24 is small
When before data abandoned.
2, flow analysis module
Flow analysis module be this function realize nucleus module, design philosophy be using time series algorithm, according to
The flow information collected before predicts the flow information of subsequent time, by the predicted value of subsequent time and practical acquisition
Value compare, if exceed certain threshold, sounded an alarm to system, and to output module provide abnormal host believe substantially
Cease (abnormal host IP etc.) and its corresponding warning message.
2.1, time series analysis brief introduction
Time series is exactly briefly the sequence of values formed on each time point, and time series analysis is exactly to pass through observation
Following value of historical data prediction.A bit is required emphasis herein, time series analysis is not the recurrence about the time,
It mainly studies the changing rule of itself.
2.2, time series analysis basic model
ARMA model [ARMA (p, q)] is one of model mostly important in time series, it mainly by
Two parts composition: AR represents p rank autoregressive process, and MA represents q rank moving average process, and formula is as follows:
The reduced form of model is；
Wherein；
θq(B)=1- θ1B-θ2B2-...-θqBq
According to form, characteristic and the auto-correlation of model and the feature of partial autocorrelation function, AR, MA model summarizes such as Fig. 7,
In time series, ARIMA model is more operations of difference d on the basis of arma modeling.
2.3, suitable d, p, q are selected
Requirement of the ARIMA model to time series is leveling style.Therefore, when obtaining the time series of a non-stationary,
First have to do is the difference for doing time series, until obtaining a stationary time series.If to time series be d times it is poor
A stationary sequence can just be obtained by dividing, then ARIMA (p, d, q) model can be used, wherein d is difference number, thus
To a suitable d value.
AR model stationarity differentiate: characteristic root differentiate: p characteristic root in unit circle then steadily (absolute value is less than 1), from
And can also derive autoregressive coefficient root of polynomial (absolute value is greater than 1) all outside unit circle, it is looked for according to this method of discrimination
To suitable p value.
MA model belongs to the analysis model of stationary time series, is abbreviated MA (q), and Random Sequence is 0 mean value white noise
Sequence, equally first centralization model when analysis.MA model has properties: constant mean, constant variance, and auto-covariance function is only
It is related to lag order, and q rank truncation, auto-correlation coefficient q rank truncation, partial autocorrelation hangover.It can be found according to this property
Suitable q value.
2.4, this paper predictor calculation
Relatively suitable d can be automatically generated by the self study to data, p, q value, and using ARIMA (p, q,
D), the flow value of subsequent time is predicted according to 100 seconds before current time discharge records.
2.5, anomaly and alarm
Actual flow when new at the time of reach and by flow collection module classification statistics after, it is pre- with step 2.4
Measured value compares, if being higher than a determining threshold, issues abnormality alarm to output module.Exception monitoring is real-time perfoming
, each moment is all monitoring, so ensure that the real-time of anomaly.
3, output module
Output module is divided into two large divisions, and one is discharge record figure to each charging pile, and one is to the different of charging pile
Normal alarm record.
Recording content includes: discharge record figure, and entire traffic monitoring analytic function has been made into GUI mode；It can choose and look into
It sees the flow information figure of which specific charging pile, while also can choose flow at the time of checking corresponding charging pile flow information and becoming
Change figure, could support up 24 hours before checking current time changes in flow rate.
In order to increase function to d, it is initial to have carried out random small integer to the record of initialization for the self study accuracy of p, q
Change process works well by actual test.
Because abnormality alarm is needed using time series analysis, and time series analysis is needed to previous sample
It practises, so abnormality alarm function will sleep 100 seconds after starting traffic monitoring, after waiting has enough samples to be analyzed, then
Volume forecasting is carried out, makes the more accurate of prediction, greatly reduces abnormal rate of false alarm.
It should be noted that step shown in the flowchart of the accompanying drawings can be in such as a group of computer-executable instructions
It is executed in computer system, although also, logical order is shown in flow charts, and it in some cases, can be with not
The sequence being same as herein executes shown or described step.
The embodiment of the invention provides a kind of electrically-charging equipment data processing equipment, which can be used for executing of the invention real
Apply the electrically-charging equipment data processing method of example.
Fig. 8 is the schematic diagram of electrically-charging equipment data processing equipment according to an embodiment of the present invention, as shown in figure 8, the device
Include:
Acquiring unit 10, for obtaining the data on flows of charging pile；
Statistic unit 20 obtains corresponding to every for carrying out statistic of classification to the data on flows from different charging piles
The data on flows of a charging pile；
Predicting unit 30, for being predicted according to the data on flows of each charging pile the data on flows of subsequent time,
Obtain predicted flow rate data；
Alarm unit 40, for the data on flows of the subsequent time in charging pile and the gap of predicted flow rate data beyond pre-
If when threshold value, issuing abnormality alarm.
The embodiment uses acquiring unit 10, for obtaining the data on flows of charging pile；Statistic unit 20, for coming from
The data on flows of different charging piles carries out statistic of classification, obtains the data on flows corresponding to each charging pile；Predicting unit 30,
For predicting according to the data on flows of each charging pile the data on flows of subsequent time, predicted flow rate data are obtained；Report
Alert unit 40, when exceeding preset threshold for the data on flows of the subsequent time in charging pile and the gap of predicted flow rate data,
Abnormality alarm is issued, to solve the problems, such as to be unable to learn in time when Traffic Anomaly occurs in electrically-charging equipment, and then has been reached
There is the effect sounded an alarm in time when Traffic Anomaly in electrically-charging equipment.
Optionally, the device further include: drawing unit, for drawing predicted flow rate data after issuing abnormality alarm
Change with time the actual flow datagram of figure and charging pile；Display unit, for showing variation diagram and reality on interface
Data on flows figure.
Optionally, acquiring unit 10 includes: acquisition module, for obtaining the data packet received from monitoring host network card；
Extraction module, for extracting the TCP flow amount packet in data packet by filtering rule；Judgment module, for according to TCP flow amount packet
Source IP field in the IP packet on upper layer judges whether present flow rate packet is data on flows that corresponding charging pile is sent；Handle mould
Block, for when the judgment result is yes, obtaining data on flows of the present flow rate packet as charging pile.
The electrically-charging equipment data processing equipment includes processor and memory, and above-mentioned acquiring unit, statistic unit etc. are equal
In memory as program unit storage, above procedure unit stored in memory is executed by processor to realize accordingly
Function.
Include kernel in processor, is gone in memory to transfer corresponding program unit by kernel.Kernel can be set one
Or more, to sound an alarm in time when Traffic Anomaly occurs in electrically-charging equipment by adjusting kernel parameter.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/
Or the forms such as Nonvolatile memory, if read-only memory (ROM) or flash memory (flash RAM), memory include that at least one is deposited
Store up chip.
The embodiment of the invention provides a kind of storage mediums, are stored thereon with program, real when which is executed by processor
The existing electrically-charging equipment data processing method.
The embodiment of the invention provides a kind of processor, the processor is for running program, wherein described program operation
Electrically-charging equipment data processing method described in Shi Zhihang.
The embodiment of the invention provides a kind of equipment, equipment include processor, memory and storage on a memory and can
The program run on a processor, processor perform the steps of the data on flows for obtaining charging pile when executing program；To coming from
The data on flows of different charging piles carries out statistic of classification, obtains the data on flows corresponding to each charging pile；It is filled according to each
The data on flows of electric stake predicts the data on flows of subsequent time, obtains predicted flow rate data；In lower a period of time of charging pile
When the data on flows at quarter and the gap of predicted flow rate data exceed preset threshold, abnormality alarm is issued.Equipment herein can be with
It is server, PC, PAD, mobile phone etc..
Present invention also provides a kind of computer program products, when executing on data processing equipment, are adapted for carrying out just
The program of beginningization there are as below methods step: the data on flows of charging pile is obtained；To the data on flows from different charging piles into
Row statistic of classification obtains the data on flows corresponding to each charging pile；According to the data on flows of each charging pile to subsequent time
Data on flows predicted, obtain predicted flow rate data；In the data on flows and predicted flow rate number of the subsequent time of charging pile
According to gap exceed preset threshold when, issue abnormality alarm.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/
Or the forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable Jie
The example of matter.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including element
There is also other identical elements in process, method, commodity or equipment.
It will be understood by those skilled in the art that embodiments herein can provide as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
The above is only embodiments herein, are not intended to limit this application.To those skilled in the art,
Various changes and changes are possible in this application.It is all within the spirit and principles of the present application made by any modification, equivalent replacement,
Improve etc., it should be included within the scope of the claims of this application.
Claims (10)
1. a kind of electrically-charging equipment data processing method characterized by comprising
Obtain the data on flows of charging pile；
Statistic of classification is carried out to the data on flows from different charging piles, obtains the data on flows corresponding to each charging pile；
It is predicted according to data on flows of the data on flows of each charging pile to subsequent time, obtains predicted flow rate data；
When the data on flows of the subsequent time of charging pile and the gap of the predicted flow rate data exceed preset threshold, issue different
Normal alarm.
2. the method according to claim 1, wherein after issuing abnormality alarm, the method also includes:
Predicted flow rate data are drawn to change with time the actual flow datagram of figure and charging pile；
The variation diagram and actual flow datagram are shown on interface.
3. the method according to claim 1, wherein the data on flows for obtaining charging pile includes:
The data packet received is obtained from monitoring host network card；
By filtering rule, the TCP flow amount packet in the data packet is extracted；
The source IP field in the IP packet of layer, which is wrapped, according to the TCP flow amount judges whether present flow rate packet is corresponding charging pile hair
The data on flows sent；
If it is, obtaining data on flows of the present flow rate packet as charging pile.
4. the method according to claim 1, wherein according to the data on flows of each charging pile to subsequent time
Data on flows is predicted that obtaining predicted flow rate data includes:
The data on flows of the charging pile of predetermined time period is acquired as sample data；
The data on flows ARIMA model of each charging pile is established based on the sample data；
Data on flows ARIMA model based on each charging pile predicts the data on flows of charging pile subsequent time, obtains
Predicted flow rate data.
5. the method according to claim 1, wherein before issuing abnormality alarm, the method also includes:
Whether the opening time for judging abnormality alarm function is more than default sleeping time；
If the opening time of the abnormality alarm function is not above default sleeping time, the opening time is waited to be not above
Abnormality alarm is issued again after default sleeping time.
6. a kind of electrically-charging equipment data processing equipment characterized by comprising
Acquiring unit, for obtaining the data on flows of charging pile；
Statistic unit obtains corresponding to each charging for carrying out statistic of classification to the data on flows from different charging piles
The data on flows of stake；
Predicting unit obtains pre- for being predicted according to the data on flows of each charging pile the data on flows of subsequent time
Measurement of discharge data；
Alarm unit, for the data on flows of the subsequent time in charging pile and the gap of the predicted flow rate data beyond default
When threshold value, abnormality alarm is issued.
7. device according to claim 6, which is characterized in that described device further include:
Drawing unit, for after issuing abnormality alarm, drafting predicted flow rate data change with time figure and charging pile
Actual flow datagram；
Display unit, for showing the variation diagram and actual flow datagram on interface.
8. device according to claim 6, which is characterized in that the acquiring unit includes:
Module is obtained, for obtaining the data packet received from monitoring host network card；
Extraction module, for extracting the TCP flow amount packet in the data packet by filtering rule；
Judgment module, for wrapping whether the source IP field in the IP packet of layer judges present flow rate packet according to the TCP flow amount
It is the data on flows that corresponding charging pile is sent；
Processing module, for when the judgment result is yes, obtaining data on flows of the present flow rate packet as charging pile.
9. a kind of storage medium, which is characterized in that the storage medium includes the program of storage, wherein run in described program
When control the storage medium where equipment perform claim require any one of 1 to 5 described in electrically-charging equipment data processing side
Method.
10. a kind of processor, which is characterized in that the processor is for running program, wherein right of execution when described program is run
Benefit require any one of 1 to 5 described in electrically-charging equipment data processing method.
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