CN111932097A - Data quality monitoring method and device based on electric vehicle service platform - Google Patents
Data quality monitoring method and device based on electric vehicle service platform Download PDFInfo
- Publication number
- CN111932097A CN111932097A CN202010757256.2A CN202010757256A CN111932097A CN 111932097 A CN111932097 A CN 111932097A CN 202010757256 A CN202010757256 A CN 202010757256A CN 111932097 A CN111932097 A CN 111932097A
- Authority
- CN
- China
- Prior art keywords
- charging equipment
- data
- message
- operation data
- electric vehicle
- 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
- 238000012544 monitoring process Methods 0.000 title claims abstract description 77
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000011156 evaluation Methods 0.000 claims abstract description 51
- 230000008569 process Effects 0.000 claims abstract description 16
- 238000012806 monitoring device Methods 0.000 claims abstract description 8
- 238000013441 quality evaluation Methods 0.000 claims description 19
- 238000004364 calculation method Methods 0.000 claims description 13
- 238000011084 recovery Methods 0.000 claims description 9
- 238000001914 filtration Methods 0.000 claims description 8
- 230000001960 triggered effect Effects 0.000 claims description 5
- 238000012423 maintenance Methods 0.000 abstract description 8
- 238000004458 analytical method Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 9
- 238000004590 computer program Methods 0.000 description 7
- 238000012545 processing Methods 0.000 description 7
- 230000002159 abnormal effect Effects 0.000 description 6
- 230000006870 function Effects 0.000 description 5
- 230000008901 benefit Effects 0.000 description 3
- 230000002457 bidirectional effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0823—Errors, e.g. transmission errors
- H04L43/0829—Packet loss
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0823—Errors, e.g. transmission errors
- H04L43/0847—Transmission error
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0852—Delays
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Physics & Mathematics (AREA)
- Environmental & Geological Engineering (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Signal Processing (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Quality & Reliability (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses a data quality monitoring method and a data quality monitoring device based on an electric vehicle service platform, which are used for analyzing a plurality of indexes of accuracy, reliability and timeliness of the data quality of electric vehicle charging equipment and establishing an electric vehicle data quality overall evaluation method so as to inform operation and maintenance personnel in time and analyze and process problems of equipment, stations and the like with frequent problems in data quality.
Description
Technical Field
The invention belongs to the technical field of data management, and particularly relates to a data quality monitoring method based on an electric vehicle service platform, and further relates to a data quality monitoring device based on the electric vehicle service platform.
Background
With the improvement of the life quality of people, the number of newly added automobiles increases year by year in the present year, and the environmental and energy crisis also increased. The electric automobile is driven by electric energy, has the advantages of cleanness and high efficiency, can effectively reduce exhaust emission and petroleum dependence, has remarkable energy-saving and emission-reducing effects, and can improve economic benefits and social benefits. In recent years, various policies have been promulgated from various countries around the world to support the technical research of electric vehicles and promote the development of the industry. Monitoring of electric automobile charging pile running state helps helping operation and maintenance personnel to know the electric automobile condition of charging in real time, ensures charging equipment safety and stability operation, satisfies user's demand of charging.
The data quality is mainly based on the fact that collected and uploaded original data continuously acquire event, state, early warning and other multi-data source information of equipment and a system, efficient real-time data collection is conducted to form an analysis data source, abnormal data or abnormal generation reasons are rapidly located through analysis and evaluation, and evaluation on the quality of the data uploaded by the equipment is facilitated. At present, because data quality information is dispersed in a plurality of application modules of an electric vehicle service platform, and there is no comprehensive, scientific and intuitive data quality index, operation and maintenance personnel cannot accurately master the basic data quality of the system, and monitoring analysis on the accuracy, reliability and timeliness of the data is lacked, the invention provides a data quality monitoring method based on the electric vehicle service platform, which is used for integrally evaluating the data quality from a plurality of dimensions, timely informing the operation and maintenance personnel of problems, and analyzing and processing problems of equipment, stations and the like with frequent problems in the data quality.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a data quality monitoring method and device based on an electric vehicle service platform, which are used for monitoring and analyzing the accuracy, reliability and timeliness of data.
In order to solve the technical problem, the invention provides a data quality monitoring method based on an electric vehicle service platform, which comprises the following steps:
acquiring original operation data of electric vehicle charging equipment;
monitoring the accuracy, reliability and timeliness of original operation data of the electric automobile charging equipment to obtain accuracy, reliability and timeliness evaluation index values;
and calculating to obtain a final evaluation result based on the accuracy, reliability and timeliness evaluation index values and the weights of the evaluation indexes.
Further, the specific process of monitoring the accuracy of the original operation data of the electric vehicle charging equipment to obtain the accuracy evaluation index value is as follows:
1) judging whether the charging equipment operation data is accurate according to any one or combination of the following modes:
the first method is as follows: judging whether partial data loss exists or not according to the message length agreed by the operation data message of the charging equipment; if the situation that partial data are lost is judged, the reported message data of the charging equipment is judged to be inaccurate;
the second method comprises the following steps: according to the equipment number of the charging equipment operation data message, comparing and inquiring with the charging equipment number of the charging equipment asset database to judge whether the charging equipment exists, and if the charging equipment does not exist, judging that the reported charging equipment message data is inaccurate;
the third method comprises the following steps: inquiring whether the original charging equipment information stored in a charging equipment asset database in the electric automobile service platform is consistent with the information sent by the charging equipment or not according to the serial number of the charging equipment; if the reported message data of the charging equipment is inconsistent, the reported message data of the charging equipment is judged to be inaccurate;
2) and counting the data accuracy of the charging equipment operation data message according to the judgment result, wherein the calculation method of the data accuracy of the charging equipment operation data message comprises the following steps:
X1an indicator of accuracy of the data uploaded by the charging device, N1The data uploaded to the charging equipment is the accurate message quantity, and N is the total number of the messages uploaded by the charging equipment.
Further, the reliability monitoring is performed on the original operation data of the electric vehicle charging equipment, and the specific process of obtaining the reliability evaluation index value is as follows:
when the situation that the content indicated by the original operation data of the electric automobile charging equipment is triggered to alarm filtering and both an alarm message and a recovery message are marked as invalid messages is monitored, the original operation data of the electric automobile charging equipment is unreliable messages;
the method for calculating the data reliability of the charging equipment operation data message comprises the following steps:
X2reliability index for charging device upload data, N2The number of the messages with invalid data uploaded to the charging equipment is N, and the N is the total number of the messages uploaded to the charging equipment.
Further, the specific process of monitoring the original operation data of the electric vehicle charging equipment in time to obtain the timeliness evaluation index value is as follows:
comparing the timestamp carried by the charging equipment operation data message with the local server time, and if the local server time exceeds the equipment carried timestamp and the time difference between the local server time and the equipment carried timestamp exceeds a set value, judging that the charging equipment operation data message sent by the charging equipment is not timely;
the method for calculating the data timeliness of the charging equipment operation data message comprises the following steps:
X3reliability index for charging device upload data, N3The number of the messages when the data uploaded by the charging equipment is not in time is shown, and N is the total number of the messages uploaded by the charging equipment.
Further, the calculation formula of the evaluation result is as follows:
X=λ1X1+λ2X2+λ3X3
in the formula, XiRepresents a data quality evaluation index, i ═ 1, 2, 3, and λiRepresents a data quality evaluation index weight, and1+λ2+λ3=1。
correspondingly, the invention also provides a data quality monitoring device based on the electric vehicle service platform, which comprises a data acquisition module, a quality monitoring module and a quality evaluation module, wherein:
the data acquisition module is used for acquiring original operation data of the electric automobile charging equipment;
the quality monitoring module is used for monitoring the accuracy, reliability and timeliness of original operation data of the electric automobile charging equipment to obtain accuracy, reliability and timeliness evaluation index values;
and the quality evaluation module is used for calculating and obtaining a final evaluation result based on the accuracy, reliability and timeliness evaluation index values and the weights of all the evaluation indexes.
Furthermore, the quality monitoring module comprises a data accuracy monitoring module for carrying out accuracy monitoring on the original operation data of the electric automobile charging equipment, and the specific process of obtaining the accuracy evaluation index value is as follows:
1) judging whether the charging equipment operation data is accurate according to any one or combination of the following modes:
the first method is as follows: judging whether partial data loss exists or not according to the message length agreed by the operation data message of the charging equipment; if the situation that partial data are lost is judged, the reported message data of the charging equipment is judged to be inaccurate;
the second method comprises the following steps: according to the equipment number of the charging equipment operation data message, comparing and inquiring with the charging equipment number of the charging equipment asset database to judge whether the charging equipment exists, and if the charging equipment does not exist, judging that the reported charging equipment message data is inaccurate;
the third method comprises the following steps: inquiring whether the original charging equipment information stored in a charging equipment asset database in the electric automobile service platform is consistent with the information sent by the charging equipment or not according to the serial number of the charging equipment; if the reported message data of the charging equipment is inconsistent, the reported message data of the charging equipment is judged to be inaccurate;
2) and counting the data accuracy of the charging equipment operation data message according to the judgment result, wherein the calculation method of the data accuracy of the charging equipment operation data message comprises the following steps:
X1an indicator of accuracy of the data uploaded by the charging device, N1The data uploaded to the charging equipment is the accurate message quantity, and N is the total number of the messages uploaded by the charging equipment.
Further, the quality monitoring module comprises a data quasi-reliable monitoring module for performing reliability monitoring on the original operation data of the electric vehicle charging equipment, and the specific process of obtaining the reliability evaluation index value is as follows:
when the situation that the content indicated by the original operation data of the electric automobile charging equipment is triggered to alarm filtering and both an alarm message and a recovery message are marked as invalid messages is monitored, the original operation data of the electric automobile charging equipment is unreliable messages;
the method for calculating the data reliability of the charging equipment operation data message comprises the following steps:
X2reliability index for charging device upload data, N2The number of the messages with invalid data uploaded to the charging equipment is N, and the N is the total number of the messages uploaded to the charging equipment.
Further, in the quality monitoring module, including data timeliness monitoring module for carry out timeliness monitoring to electric automobile battery charging outfit original operation data, obtain the concrete process of timeliness evaluation index numerical value and do:
comparing the timestamp carried by the charging equipment operation data message with the local server time, and if the local server time exceeds the equipment carried timestamp and the time difference between the local server time and the equipment carried timestamp exceeds a set value, judging that the charging equipment operation data message sent by the charging equipment is not timely;
the method for calculating the data timeliness of the charging equipment operation data message comprises the following steps:
X3reliability index for charging device upload data, N3The number of the messages when the data uploaded by the charging equipment is not in time is shown, and N is the total number of the messages uploaded by the charging equipment.
Further, in the quality evaluation module, the calculation formula of the evaluation result is as follows:
X=λ1X1+λ2X2+λ3X3
in the formula, XiRepresents a data quality evaluation index, i ═ 1, 2, 3, and λiRepresents a data quality evaluation index weight, and1+λ2+λ3=1。
compared with the prior art, the invention has the following beneficial effects: the method analyzes the data quality of the electric vehicle charging equipment from multiple indexes of accuracy, reliability and timeliness, establishes an electric vehicle data quality overall evaluation method, and is convenient for informing operation and maintenance personnel in time to analyze and process problems of equipment, stations and the like with frequent data quality problems.
Drawings
FIG. 1 is a block diagram of the overall system architecture of the present invention;
FIG. 2 is a data accuracy monitoring process;
FIG. 3 is a data reliability monitoring process;
FIG. 4 is a flow chart of data timeliness monitoring.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The data quality monitoring system based on the electric vehicle service platform, disclosed by the invention, is shown in fig. 1, and comprises a calculation engine module, a data quality monitoring module and a data quality analysis and evaluation module which are deployed on the electric vehicle service platform, so that the accuracy, reliability and timeliness of the operation data of the electric vehicle charging equipment acquired by the electric vehicle service platform are guaranteed. The operation data of the electric automobile charging equipment comprises charging power and charging electric quantity data of the charging pile.
The calculation engine module is used as a communication interface between the electric automobile service platform and the electric automobile charging equipment to acquire original operation data of the electric automobile charging equipment. The calculation engine module, the data quality monitoring module and the data quality analysis and evaluation module realize data bidirectional interaction by issuing MQ (message queue) messages. The operating data of the charging equipment is transmitted to a TCP/IP interface of the calculation engine module through a TCP/IP protocol, the calculation engine module assembles the data of the TCP/IP interface through an MQTT (message queue telemetry transport) protocol, and the data bidirectional interaction is realized through issuing MQ messages, the data quality monitoring module and the data quality analysis and evaluation module.
The data quality monitoring module comprises a data accuracy monitoring module, a data reliability monitoring module and a data timeliness monitoring module, wherein the data accuracy monitoring module, the data reliability monitoring module and the data timeliness monitoring module are used for monitoring the accuracy, reliability and timeliness evaluation indexes of the operating data of the charging equipment; and the index management module determines the evaluation index of the data quality.
And the data quality analysis and evaluation module obtains an evaluation result according to the numerical value of the evaluation index and the weight corresponding to the configuration, and integrally evaluates the running data quality of the electric vehicle charging equipment obtained by the electric vehicle service platform.
The data quality monitoring module in the invention specifically comprises:
(1) data accuracy monitoring module
And the data accuracy monitoring module is used for monitoring the accuracy of the operating data of the charging equipment to obtain the numerical value of the accuracy evaluation index.
Data accuracy refers to whether the basic data carried by the data uploaded by a given device conforms to the device itself. In data quality monitoring, accuracy is of crucial importance. The equipment can carry data such as equipment serial numbers when sending data, because reasons such as equipment itself, numbering mistake scheduling problem probably appears when equipment registers, consequently need monitor the accuracy of data, when discovering wrong data, in time inform the operation and maintenance personnel to handle.
The format of the operation data message sent by the charging equipment to the electric vehicle service platform is as follows:
as shown in fig. 2, the specific steps of data accuracy monitoring are as follows:
1) the charging equipment sends a charging equipment operation data message to the electric automobile service platform;
2) judging whether partial data loss exists or not according to the length of a message appointed by a charging equipment operation data message sent by the charging equipment; if the length of the charging equipment operation data message sent by the charging equipment is smaller than the length agreed by the message, judging that the charging equipment operation data message sent by the charging equipment has partial data loss, namely the reported charging equipment message data is inaccurate, and marking the charging equipment as 'abnormal information sent by equipment';
3) according to the equipment number of the charging equipment operation data message, comparing and inquiring with the charging equipment number of a charging equipment asset database of an electric vehicle service platform to judge whether the charging equipment exists, if the reported charging equipment number cannot be inquired, judging that the equipment number reports a mistake, namely the equipment does not exist, and marking the equipment with 'abnormal information uploading';
the charging equipment asset database stores equipment numbers of charging piles, charging pile types (direct current charging piles and alternating current charging piles) and charging power ranges (maximum charging power and minimum charging power of the charging piles in a charging state) of the charging piles in a jurisdiction area of the electric automobile service platform;
4) inquiring whether the original charging equipment information stored in a charging equipment asset database in the electric automobile service platform is consistent with the information sent by the charging equipment or not according to the serial number of the charging equipment; as described above, the original information of the charging device includes the charging pile type and the charging power meter range of the charging pile; if the information sent by the charging equipment is inconsistent with the original information of the charging equipment, marking the charging equipment as 'abnormal information sent by the equipment';
5) according to the data accuracy rate of the charging equipment operation data message counted in the steps 3) and 4), informing equipment operation and maintenance personnel to operate and maintain the charging equipment with the 'abnormal information sent on the equipment' mark; the method for calculating the data accuracy of the charging equipment operation data message comprises the following steps:
X1to chargeAccuracy index of data uploaded by electrical equipment, N1And judging the number of the messages uploaded by the charging equipment to be accurate for the electric vehicle service platform, wherein N is the total number of the messages uploaded by the charging equipment and received by the electric vehicle service platform.
(2) Data reliability monitoring module
And the data reliability monitoring module is used for monitoring the reliability of the operating data of the charging equipment to obtain the numerical value of the reliability evaluation index.
The problems of frequent alarm and the like may exist in some devices, but the frequent alarm may affect the normal operation of the electric vehicle service platform, and wastes operation and maintenance resources. Therefore, in order to solve the problem, a function of monitoring and processing data such as fault alarm and the like needs to be performed frequently. For each fault type in the fault and alarm directory, anti-shake processing for the same fault and alarm information is added. Under the condition that the alarm information is jittered (the equipment frequently sends the alarm information within a certain time), if the filtering triggering condition is met, a scheme of delay pushing is carried out to filter out jittering signals, so that the fault alarm continues in an alarm state during the jittering period, and the recovery information is not sent until the jittering is finished.
As shown in fig. 3, the data reliability monitoring includes the following steps:
1) when the charging equipment finds alarm data, the charging equipment sends an alarm message to an electric automobile service platform, after the electric automobile service platform receives the alarm message sent by the charging equipment, the time difference between the current alarm time and the last alarm time is judged, if the alarm time difference is smaller than set time (set to be 1 second), the frequency reporting time is 1, if the frequency reporting occurs for a plurality of times within a certain time (for example, the frequency reporting time is greater than 10 times within every 5 minutes), alarm filtering is triggered, an alarm filtering mark is set to be 1, and at the moment, if the alarm message and the recovery message are both marked as invalid messages, the unreliable messages are not sent;
2) when the charging equipment finds the alarm data, the charging equipment sends a recovery alarm message to the electric automobile service platform, when the electric automobile service platform receives the recovery message, if the difference between the alarm time received this time and the last alarm time is greater than the set time (set to 1 second), the frequency reporting frequency is returned to 0, the alarm filtering mark is returned to 0, and at the moment, the alarm message and the recovery alarm message which are sent again are marked to be sent normally.
The method for calculating the data reliability of the charging equipment operation data message comprises the following steps:
X2reliability index for charging device upload data, N2And judging the number of messages of which the data uploaded by the charging equipment is invalid (unreliable messages) for the electric vehicle service platform, wherein N is the total number of the messages uploaded by the charging equipment and received by the electric vehicle service platform.
(3) Data timeliness monitoring
And the data timeliness monitoring module is used for monitoring the timeliness of the operating data of the charging equipment to obtain the value of the timeliness evaluation index.
Data timeliness refers to the temporal expectation of data accessibility and availability, representing the ability of data to be acquired in a timely manner when needed.
As shown in fig. 4, the specific steps of data timeliness monitoring are as follows:
1) the charging equipment transmits a charging equipment operation data message carrying an equipment local timestamp to the electric automobile service platform;
2) analyzing the operation data of the charging equipment, comparing a timestamp carried by the equipment with the time of a local server, and if the time of the local server exceeds the time stamp carried by the equipment and the time difference between the time of the local server and the time stamp carried by the equipment exceeds a set value, judging that the operation data message of the charging equipment sent by the charging equipment is not timely and carrying out delay marking on the equipment so as to prompt the equipment to be processed.
The method for calculating the data timeliness of the charging equipment operation data message comprises the following steps:
X3reliability index for charging device upload data, N3And judging the number of messages when the data uploaded by the charging equipment is not in time for the electric vehicle service platform, wherein N is the total number of the messages uploaded by the charging equipment and received by the electric vehicle service platform.
The data quality analysis and evaluation module calculates each evaluation index of the data quality evaluation, and integrally evaluates the data quality of the electric vehicle charging equipment operation acquired by the electric vehicle service platform by using a weighted average method.
The weight of each index is defined between 0 and 1, and their sum is equal to 1, the overall evaluation of the data quality is divided into four levels, namely: unqualified in the score of 1-59, qualified in the score of 60-70, good in the score of 71-90, excellent in the score of 91-100, and the calculation formula is (X)iRepresentative data quality evaluation index, i ═ 1, 2, 3):
X=λ1X1+λ2X2+λ3X3
in the formula ofiRepresents a data quality evaluation index weight, and1+λ2+λ3=1。
the problem information found by the data quality evaluation supports feedback according to each data quality evaluation index, and the data quality problems of the piles in a certain area can be subjected to detailed analysis and feedback from a single pile, a manufacturer and a client for display; meanwhile, classified statistics according to time and data quality sources is supported; and the historical data is stored according to the data quality analysis result, and the data quality development trend is analyzed. And moreover, the data quality can be evaluated according to the regional information, the overall data quality in the region is ranked, the subentry index evaluation result set can be filtered according to the region, various problems existing in the current region are highlighted, a data quality rectification proposal is generated, and the region is supervised to rectify the data quality as soon as possible.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A data quality monitoring method based on an electric vehicle service platform is characterized by comprising the following processes:
acquiring original operation data of electric vehicle charging equipment;
monitoring the accuracy, reliability and timeliness of original operation data of the electric automobile charging equipment to obtain accuracy, reliability and timeliness evaluation index values;
and calculating to obtain a final evaluation result based on the accuracy, reliability and timeliness evaluation index values and the weights of the evaluation indexes.
2. The data quality monitoring method based on the electric vehicle service platform as claimed in claim 1, wherein the specific process of monitoring the accuracy of the original operation data of the electric vehicle charging equipment and obtaining the accuracy evaluation index value is as follows:
1) judging whether the charging equipment operation data is accurate according to any one or combination of the following modes:
the first method is as follows: judging whether partial data loss exists or not according to the message length agreed by the operation data message of the charging equipment; if the situation that partial data are lost is judged, the reported message data of the charging equipment is judged to be inaccurate;
the second method comprises the following steps: according to the equipment number of the charging equipment operation data message, comparing and inquiring with the charging equipment number of the charging equipment asset database to judge whether the charging equipment exists, and if the charging equipment does not exist, judging that the reported charging equipment message data is inaccurate;
the third method comprises the following steps: inquiring whether the original charging equipment information stored in a charging equipment asset database in the electric automobile service platform is consistent with the information sent by the charging equipment or not according to the serial number of the charging equipment; if the reported message data of the charging equipment is inconsistent, the reported message data of the charging equipment is judged to be inaccurate;
2) and counting the data accuracy of the charging equipment operation data message according to the judgment result, wherein the calculation method of the data accuracy of the charging equipment operation data message comprises the following steps:
X1an indicator of accuracy of the data uploaded by the charging device, N1The data uploaded to the charging equipment is the accurate message quantity, and N is the total number of the messages uploaded by the charging equipment.
3. The data quality monitoring method based on the electric vehicle service platform as claimed in claim 1, wherein the reliability monitoring is performed on the original operation data of the electric vehicle charging equipment, and the specific process of obtaining the reliability evaluation index value is as follows:
when the situation that the content indicated by the original operation data of the electric automobile charging equipment is triggered to alarm filtering and both an alarm message and a recovery message are marked as invalid messages is monitored, the original operation data of the electric automobile charging equipment is unreliable messages;
the method for calculating the data reliability of the charging equipment operation data message comprises the following steps:
X2reliability index for charging device upload data, N2The number of the messages with invalid data uploaded to the charging equipment is N, and the N is the total number of the messages uploaded to the charging equipment.
4. The data quality monitoring method based on the electric vehicle service platform as claimed in claim 1, wherein the specific process of monitoring the original operation data of the electric vehicle charging equipment in time and obtaining the timeliness evaluation index value is as follows:
comparing the timestamp carried by the charging equipment operation data message with the local server time, and if the local server time exceeds the equipment carried timestamp and the time difference between the local server time and the equipment carried timestamp exceeds a set value, judging that the charging equipment operation data message sent by the charging equipment is not timely;
the method for calculating the data timeliness of the charging equipment operation data message comprises the following steps:
X3reliability index for charging device upload data, N3The number of the messages when the data uploaded by the charging equipment is not in time is shown, and N is the total number of the messages uploaded by the charging equipment.
5. The data quality monitoring method based on the electric vehicle service platform as claimed in claim 1, wherein the evaluation result is calculated by the following formula:
X=λ1X1+λ2X2+λ3X3
in the formula, XiRepresents a data quality evaluation index, i ═ 1, 2, 3, and λiRepresents a data quality evaluation index weight, and1+λ2+λ3=1。
6. the utility model provides a data quality monitoring device based on electric automobile service platform, characterized by, including data acquisition module, quality monitoring module and quality evaluation module, wherein:
the data acquisition module is used for acquiring original operation data of the electric automobile charging equipment;
the quality monitoring module is used for monitoring the accuracy, reliability and timeliness of original operation data of the electric automobile charging equipment to obtain accuracy, reliability and timeliness evaluation index values;
and the quality evaluation module is used for calculating and obtaining a final evaluation result based on the accuracy, reliability and timeliness evaluation index values and the weights of all the evaluation indexes.
7. The data quality monitoring device based on the electric vehicle service platform as claimed in claim 6, wherein the quality monitoring module comprises a data accuracy monitoring module for performing accuracy monitoring on the original operation data of the electric vehicle charging equipment, and the specific process of obtaining the accuracy evaluation index value is as follows:
1) judging whether the operation data of the charging equipment is accurate according to any one or combination of the following modes;
the first method is as follows: judging whether partial data loss exists or not according to the message length agreed by the operation data message of the charging equipment; if the situation that partial data are lost is judged, the reported message data of the charging equipment is judged to be inaccurate;
the second method comprises the following steps: according to the equipment number of the charging equipment operation data message, comparing and inquiring with the charging equipment number of the charging equipment asset database to judge whether the charging equipment exists, and if the charging equipment does not exist, judging that the reported charging equipment message data is inaccurate;
the third method comprises the following steps: inquiring whether the original charging equipment information stored in a charging equipment asset database in the electric automobile service platform is consistent with the information sent by the charging equipment or not according to the serial number of the charging equipment; if the reported message data of the charging equipment is inconsistent, the reported message data of the charging equipment is judged to be inaccurate;
2) and counting the data accuracy of the charging equipment operation data message according to the judgment result, wherein the calculation method of the data accuracy of the charging equipment operation data message comprises the following steps:
X1an indicator of accuracy of the data uploaded by the charging device, N1The data uploaded to the charging equipment is the accurate message quantity, and N is the total number of the messages uploaded by the charging equipment.
8. The data quality monitoring device based on the electric vehicle service platform according to claim 6, wherein the quality monitoring module comprises a data quasi-reliable monitoring module for performing reliability monitoring on the original operation data of the electric vehicle charging equipment, and the specific process of obtaining the reliability evaluation index value is as follows:
when the situation that the content indicated by the original operation data of the electric automobile charging equipment is triggered to alarm filtering and both an alarm message and a recovery message are marked as invalid messages is monitored, the original operation data of the electric automobile charging equipment is unreliable messages;
the method for calculating the data reliability of the charging equipment operation data message comprises the following steps:
X2reliability index for charging device upload data, N2The number of the messages with invalid data uploaded to the charging equipment is N, and the N is the total number of the messages uploaded to the charging equipment.
9. The data quality monitoring device based on the electric vehicle service platform according to claim 6, wherein the quality monitoring module comprises a data timeliness monitoring module for monitoring the timeliness of the original operation data of the electric vehicle charging equipment, and the specific process of obtaining the timeliness evaluation index value comprises the following steps:
comparing the timestamp carried by the charging equipment operation data message with the local server time, and if the local server time exceeds the equipment carried timestamp and the time difference between the local server time and the equipment carried timestamp exceeds a set value, judging that the charging equipment operation data message sent by the charging equipment is not timely;
the method for calculating the data timeliness of the charging equipment operation data message comprises the following steps:
X3reliability index for charging device upload data, N3The number of the messages when the data uploaded by the charging equipment is not in time is shown, and N is the total number of the messages uploaded by the charging equipment.
10. The data quality monitoring device based on the electric vehicle service platform as claimed in claim 6, wherein in the quality evaluation module, the calculation formula of the evaluation result is as follows:
X=λ1X1+λ2X2+λ3X3
in the formula, XiRepresents a data quality evaluation index, i ═ 1, 2, 3, and λiRepresents a data quality evaluation index weight, and1+λ2+λ3=1。
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010757256.2A CN111932097A (en) | 2020-07-31 | 2020-07-31 | Data quality monitoring method and device based on electric vehicle service platform |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010757256.2A CN111932097A (en) | 2020-07-31 | 2020-07-31 | Data quality monitoring method and device based on electric vehicle service platform |
Publications (1)
Publication Number | Publication Date |
---|---|
CN111932097A true CN111932097A (en) | 2020-11-13 |
Family
ID=73314985
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010757256.2A Pending CN111932097A (en) | 2020-07-31 | 2020-07-31 | Data quality monitoring method and device based on electric vehicle service platform |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111932097A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115130852A (en) * | 2022-06-24 | 2022-09-30 | 重庆长安新能源汽车科技有限公司 | Data transmission quality evaluation method, device, equipment and medium for Internet of vehicles equipment |
-
2020
- 2020-07-31 CN CN202010757256.2A patent/CN111932097A/en active Pending
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115130852A (en) * | 2022-06-24 | 2022-09-30 | 重庆长安新能源汽车科技有限公司 | Data transmission quality evaluation method, device, equipment and medium for Internet of vehicles equipment |
CN115130852B (en) * | 2022-06-24 | 2024-06-07 | 深蓝汽车科技有限公司 | Data transmission quality assessment method and device for Internet of vehicles equipment |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN114063507B (en) | Remote equipment control system based on intelligent agriculture and control method thereof | |
CN109639477B (en) | Secondary equipment online monitoring and analyzing system and method | |
CN112556829A (en) | Equipment vibration acquisition monitoring system and method | |
CN104574219A (en) | System and method for monitoring and early warning of operation conditions of power grid service information system | |
CN113271224A (en) | Node positioning method and device, storage medium and electronic device | |
CN117691722B (en) | Lithium battery charging safety monitoring and early warning method and system | |
CN113848843B (en) | Self-diagnosis analysis system based on intelligent optimization energy-saving system | |
CN113157521B (en) | Monitoring method and monitoring system for block chain full life cycle | |
CN115208059A (en) | Transformer substation power and environment monitoring alarm processing system and method | |
CN111932097A (en) | Data quality monitoring method and device based on electric vehicle service platform | |
CN117311295B (en) | Production quality improving method and system based on wireless network equipment | |
CN114546776A (en) | Abnormal data monitoring method based on cloud platform | |
CN106709659A (en) | LNG gas station equipment management system | |
CN112449019A (en) | IMS intelligent Internet of things operation and maintenance management platform | |
CN112446645A (en) | Power management service system based on Internet of things | |
CN112508438A (en) | Scheduling dependence calculation method based on electric power big data | |
CN111509839A (en) | Trip event model analysis method based on alarm signal | |
CN111722601A (en) | Cement production line real-time monitoring system | |
CN101650788A (en) | Method and system for electronic monitoring of administrative operations | |
CN114328111A (en) | Machine room energy consumption monitoring and safety monitoring method | |
CN111539642B (en) | Object-oriented power plant data acquisition and processing system and method thereof | |
CN112559584A (en) | Remote acquisition and regulation system based on detection and monitoring signal samples | |
CN113129160A (en) | Electric power communication network inspection method based on equipment state perception and intellectualization | |
CN110601885A (en) | Artificial intelligence public cloud abnormity indication alarm system | |
CN113063900B (en) | Oil smoke monitoring system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
WD01 | Invention patent application deemed withdrawn after publication | ||
WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20201113 |