CN106597162A - Method for improving reliability of radio-frequency identification tag of low-voltage mutual inductor based on experience modal decomposition - Google Patents
Method for improving reliability of radio-frequency identification tag of low-voltage mutual inductor based on experience modal decomposition Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/003—Environmental or reliability tests
Abstract
The invention discloses a method for improving the reliability of a radio-frequency identification tag of a low-voltage mutual inductor based on experience modal decomposition, and the method comprises the steps: measuring the performance data of the radio-frequency identification tag of the low-voltage mutual inductor under the factors of different temperature, humidity, mutual inductor coil electric quantities and electromagnetic interference intensities, and building a basic expert database of the radio-frequency identification tag of the mutual inductor; measuring the data of the radio-frequency identification tag of the low-voltage mutual inductor in a normal environment, and building a normal database of the radio-frequency identification tag of the low-voltage mutual inductor in the normal environment; measuring the data of the radio-frequency identification tag of the low-voltage mutual inductor in an on-site environment, and building an on-site database of the RFID(radio-frequency identification) tag of the low-voltage mutual inductor in the on-site environment; and carrying out the analysis of the built basic expert database, normal database and onsite database based on an error analysis method based on the EMD (Empirical Mode Decomposition).
Description
Technical field
The present invention relates to empirical mode decomposition method, more particularly, to a kind of low based on empirical mode decomposition EMD liftings
The method of pressure transformer RFID reliabilities.
Background technology
RFID (Radio Frequency Identification) is REID, also known as electronic tag, wirelessly
RF identification, is a kind of communication technology, can recognize specific objective by radio signals and read and write related data, and without the need for identification
System sets up machinery or optical contact with the specific objective time.RFID system is mainly made up of electronic tag, card reader and antenna,
Electronic tag includes electromagnetic induction coupled apparatus, the chip of storage identity information.At this stage, also there are some RFID in power system
Related application, such as line data-logging, batch meter be anti-electricity-theft, substation inspection, switch cubicle are patrolled and examined, electric energy meter pre-payment.But should
, often towards general asset management type application, function is relatively simple, it is impossible to meet electric-power metering field comprehensively for class RF tag
Demand.The RF tag use environment of the metering transformer in power system is relative complex, especially outdoor use environment
It is more severe, need the environmental factor for considering to relate generally to：Temperature, humidity, highfield, high-intensity magnetic field, passive metal shielding etc..
Consider that the extreme environment (high temperature, stress) in the manufacturing process of transformer, transformer information privacy (must be based on " country simultaneously
Grid company power information key management system ") etc. link, existing RF tag can not meet current demand, therefore need
Develop the RF tag of the special reliability of metering transformer.
Prior art：2014106711882 disclose a kind of passive ultrahigh frequency radio frequency identification Reliability Modeling,
Read range mainly to wireless radio frequency identification mark, link power damped expoential breakpoint distance, discrimination carry out calculating analysis.
But the factor important for the wireless radio frequency identification mark unfailing performance impact of power system application, the such as temperature of local environment,
The factors such as humidity, highfield, high-intensity magnetic field are not analyzed.
The content of the invention
To improve the low voltage mutual inductor RFID tag reliability of field of power application, need to affecting low pressure mutual
The various factors of sensor RFID tag reliability is analyzed, and is known by the low voltage mutual inductor radio frequency under the different factors of acquisition
The ultimate range and its corresponding received signal strength indicator of distinguishing label measurement, analyzes various environmental factors to low voltage mutual inductor
The impact of RFID tag reliability result.
In order to solve the above problems, the present invention proposes a kind of method, and methods described includes：
Measurement low voltage mutual inductor RFID tag is dry in different temperatures, humidity, mutual inductor coil turn on angle and electromagnetism
The performance data under strength factor is disturbed, the basic data experts database of transformer RFID tag is set up；
The data of low pressure mutual inductance RFID tag, set up transformer RF identification under home under measurement home
The normal data storehouse of label；
The data of low voltage mutual inductor RFID tag under measure field environment, set up transformer RFID under site environment
Spot database；
Based on the error analysis method of empirical mode decomposition, to the basic data experts database, the normal data storehouse set up
And spot database carries out error analysis, so that it is determined that the corresponding factor of data reliability is affected, and by affecting number
Could be adjusted to lift low voltage mutual inductor RFID tag reliability according to the corresponding factor of reliability.
Preferably, the error analysis method based on empirical mode decomposition, comprises the steps：
The basic data experts database is deducted into normal data database data, the error information that different factors are caused is obtained；
The field data experts database is deducted into normal data database data, the error information that site environment is caused is obtained；
The error information caused to the site environment determines shadow using the data analysing method based on empirical mode decomposition
Ring the corresponding factor of data reliability.
Preferably, the basic expert database, normal data storehouse, site environment database are including data item<It is maximum
Distance, the signal strength signal intensity of reception is indicated>.
Preferably, the basic data experts database for setting up transformer RFID tag, comprises the steps：
Ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under different temperatures factor
Signal strength signal intensity is indicated；
Ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under different humidity factor
Signal strength signal intensity is indicated；
Ultimate range of the measurement different model low voltage mutual inductor RFID tag under different electromagnetic interference factors and connect
The signal strength signal intensity of receipts is indicated；
Ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under peak power factor
Signal strength signal intensity is indicated；And
Ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under most half power points factor
Signal strength signal intensity indicate.
Preferably, set up under home and measure the normal data storehouse of low voltage mutual inductor RFID tag, including：
What measurement different model low voltage mutual inductor RFID tag home ultimate range and home were received
Signal strength signal intensity.
Preferably, set up under site environment and measure the spot database of low voltage mutual inductor RFID tag, including：
What measurement different model low voltage mutual inductor RFID tag site environment ultimate range and site environment were received
Signal strength signal intensity.
Preferably, the error information caused to the site environment is using the data analysis based on empirical mode decomposition
Method, it is determined that affecting the corresponding factor of data reliability：
The basic data experts database is D；
The normal data storehouse is Dnormal；
The spot database is Dfield；
The basic data experts database D deducts the home database Dnormal, obtain
Using the DfieldDeduct normal data set Dnormal, obtain
WillAccording to eigenvibration Mode Decomposition time series data, a series of intrinsic mode functions IMF are resolved into, it is right
The error information that the site environment is caused is using the data analysing method based on empirical mode decomposition, it is determined that affecting data reliability
The corresponding factor of property.
Based on another embodiment of the invention, the present invention provides a kind of system, and the system includes：
DATA REASONING unit, for measuring low voltage mutual inductor RFID tag in different temperatures, humidity, mutual inductor coil
Performance data under turn on angle and electromagnetic interference strength factor, the basic data expert for setting up transformer RFID tag
Storehouse；The data of low pressure mutual inductance RFID tag, set up transformer RFID tag under home under measurement home
Normal data storehouse；The data of low voltage mutual inductor RFID tag under measure field environment, set up transformer under site environment
The spot database of RFID；
Data analysis unit, for the error analysis method based on empirical mode decomposition, to the basic data set up
Experts database, normal data storehouse, spot database carry out error analysis, so that it is determined that the corresponding factor of data reliability is affected, and
And could be adjusted to lift low voltage mutual inductor RFID tag reliability by the corresponding factor to affecting data reliability.
Preferably, the data analysis unit can be also used for：
The basic data experts database is deducted into normal data database data, the error information that different factors are caused is obtained；
The field data experts database is deducted into normal data database data, the error information that site environment is caused is obtained；
The error information caused to the site environment determines shadow using the data analysing method based on empirical mode decomposition
Ring the corresponding factor of data reliability.
The present invention proposes a kind of data analysing method based on empirical mode decomposition to RF identification under low voltage mutual inductor
Reliability influence factor is analyzed, and finds in various impact environmental impact factors, and determines maximum effect factor, improves
The measurement distance of RFID tag and lifting reliability under low voltage mutual inductor.
Description of the drawings
By reference to the following drawings, the illustrative embodiments of the present invention can be more fully understood by：
Fig. 1 is to lift low voltage mutual inductor radio frequency identification marking based on empirical mode decomposition according to one kind of embodiment of the present invention
Sign the method flow diagram of reliability；
Fig. 2 is a kind of error analysis flow chart based on empirical mode decomposition according to embodiment of the present invention；
Fig. 3 is a kind of low voltage mutual inductor RFID tag fundamental diagram according to embodiment of the present invention.
Specific embodiment
With reference now to accompanying drawing, the illustrative embodiments of the present invention are introduced, however, the present invention can be with many different shapes
Formula is not limited to embodiment described herein implementing, there is provided these embodiments are to disclose at large and fully
The present invention, and fully pass on the scope of the present invention to person of ordinary skill in the field.For showing for being illustrated in the accompanying drawings
Term in example property embodiment is not limitation of the invention.In the accompanying drawings, identical cells/elements are attached using identical
Icon is remembered.
Unless otherwise stated, term (including scientific and technical terminology) used herein has to person of ordinary skill in the field
It is common to understand implication.Further it will be understood that the term limited with the dictionary being usually used, is appreciated that and it
The linguistic context of association area has consistent implication, and is not construed as Utopian or excessively formal meaning.
Fig. 1 is to lift low voltage mutual inductor radio frequency identification marking based on empirical mode decomposition according to one kind of embodiment of the present invention
Sign the method flow diagram of reliability.The present invention obtains RFID tag at different temperatures, humidity, transformer energization situation, angle
The RFID tag ultimate range measured under the conditions of degree measurement and electromagnetic interference etc. and the signal of corresponding reception are strong
Degree indicate RSSI, set up the basic data experts database of transformer RFID tag, then with site environment under measurement result
Carry out carrying out data analysis based on the error analysis method of empirical mode decomposition, obtain to RFID tag reliability effect most
Big factor, reaches the method for improving RFID tag reliability under low voltage mutual inductor.
Preferably, embodiment proposed by the present invention, measures first at different temperatures, humidity, transformer energization situation, angle
The different model RFID tag ultimate range measured under the environment such as degree measurement and electromagnetic interference and corresponding reception
Signal strength signal intensity indicate RSSI, set up the basic data experts database of transformer RFID tag.Preferably, by the 3 of sensor
Plant model and be designated as a1, a2, a3 respectively；The environmental factor of experiment is divided into：Temperature factor, humidity factor, mutual inductor coil are powered
Amount, electromagnetic interference strength, are designated as respectively b1, b2, b3, b4.The different factor grade of each experimental selection at least two, such as temperature
At least two grades can be selected.The experiment that embodiment of the present invention is carried out is comprised the following steps that：
A) respectively by three kinds of different models a1, a2, a3 are placed individually into different experimental situations b1, b2, b3, b4,
Ultimate range and its signal strength signal intensity instruction RSSI that its RFID tag to be measured are measured under various environment, ten are carried out every time
Group experimental record its data finally remove mean value, set up the basic data experts database of transformer RFID tag, are designated as
Wherein
I=a1,a2,a3, j=b1,b2,b3,b4, n=1,2.
Therefore each group will collect following data set：
B) using the normal ring being placed under home with the low voltage mutual inductor RFID tag of step a) same models
The signal strength signal intensity normal data storehouse D that border ultimate range and home are receivednormal, using basic data experts databaseIn
Every group of data deduct Dnormal, obtainFor the error information that different condition factor is caused.
C) obtain the maximum that is placed under site environment with the low voltage mutual inductor RFID tag of step a) same models away from
From and home receive signal strength signal intensity spot database Dfield, using DfieldDeduct normal data set Dnormal, obtain
Obtain the overall error of the signal strength signal intensity that low voltage mutual inductor RFID tag ultimate range and site environment are received under site environment
Curve:
D) the overall error curve of the signal strength signal intensity for being received site environment based on Empirical mode decomposition is decomposed, due to
Empirical mode decomposition can be by non-stationary, nonlinear signal decomposition into a series of intrinsic mode functions IMF, while eigen mode letter
Number IMF must is fulfilled for following two conditions：
1, for one group of data, extreme point and zero passage are counted out must be equal or at most mutually almost；
2, the mean value of the envelope constituted in arbitrfary point, the envelope and local minimum point being made up of a little louder local pole is
Zero.This method essence is to obtain eigenvibration pattern by characteristic time scale, during then by eigenvibration pattern decomposing
Between sequence data.A kind of algorithm of time series data x (t) empirical mode decomposition is presented herein below：
(1) systematic influence factor overall error curve is confirmedIt is all to have maximum point and minimum point, utilize
Upper and lower envelope x of the Cubic Spline Fitting to primary signal x (t)max(t) and xmin(t), xmaxT () utilizes three for maximum point
Secondary spline fit curve, xminT () is that minimum point utilizes Cubic Spline Fitting curve, and calculate their mean value curve m11
(t), m11T () is obtained by formula 4.
m11(t)=[xmax(t)+xmin(t)]/2.(formula 4)
M is deducted in primary signal x (t)11T () obtains h11(t), h11T () is obtained by formula 5.
h11(t)=x (t)-m11(t).(formula 5)
Judge h11T whether () meet condition 1 and condition 2 simultaneously, by h11T the local feature of () carries out resolving into a series of
Intrinsic mode functions IMF.If h11(t) while meet condition 1 and condition 2, then h11T () is used as decompositing in primary signal x (t)
Single order intrinsic mode functions IMF.If h11T () can not simultaneously meet condition 1 and condition 2, then by h11T () replaces in x (t) repetitions
The step of face, obtains h1k(t).Step 5 iteration, further determines that the factor for affecting RFID tag reliability effect big.
h1k(t)=h1(k-1)(t)-m1k(t).(formula 6)
In formula 6, k >=2, until h1kT () meets intrinsic mode functions IMF condition, this process is called intrinsic mode functions IMF sieve
Choosing, thus decomposites single order IMF from primary signal x (t), is denoted as
c1(t)=h1k(t).(formula 7)
(2) c is deducted from primary signal curve x (t)1T () obtains single order residual signal r1(t)
r1(t)=x (t)-c1(t).(formula 8)
By r1T () replaces primary signal x (t) repeat step (1), 2 rank intrinsic mode functions IMF are obtained successively, until n rank sheets
Levy modular function IMF and residual signal rn(t), and rnT () is monotonic function, then primary signal can be expressed as intrinsic mode functions IMF
With form x (t) of residual signal sum,
By step (1), (2), resolution error data are come by eigenvibration pattern, progressively remove the big margin of error of fluctuation
According to each characteristic component decomposited through empirical modal method can be considered that the error Jing system that variant environment is produced in system is passed
It is delivered to the output result of end.By embodiments of the present invention, the maximum point of error curve is gradually reduced, error curve
Minimum point increases, therefore, each characteristic information included in sub- curve that decomposes can be extracted and recognized, find its with it is aforementioned
The error information that different condition factor is causedCorresponding relation be capable of achieving positioning to error source, corresponding relation refers to experiment
Room is corresponding with the error curve relation at different temperatures under site environment, and in the same manner different humidity is also corresponding
's.Various different condition factors get a promotion to the analysis of the accuracy result of RFID tag reliability effect, and then obtain
The key factor that equipment is had a significant impact.
Fig. 2 is a kind of error analysis flow chart based on empirical mode decomposition according to embodiment of the present invention.Based on Jing
The overall error curve for testing the signal strength signal intensity that Mode Decomposition receives site environment is decomposed, due to Empirical mode decomposition energy
It is enough by non-stationary, nonlinear signal decomposition into a series of intrinsic mode functions IMF, while intrinsic mode functions IMF must be fulfilled for
Lower two conditions：
1, for one group of data, extreme point and zero passage are counted out must be equal or at most mutually almost；
2, the mean value of the envelope constituted in arbitrfary point, the envelope and local minimum point being made up of a little louder local pole is
Zero.This method essence is to obtain eigenvibration pattern by characteristic time scale, during then by eigenvibration pattern decomposing
Between sequence data.A kind of algorithm of time series data x (t) empirical mode decomposition is presented herein below：
(1) systematic influence factor overall error curve is confirmedAll to have maximum point and minimum point, t is
Time sequence function, n is the fertility signal of last intrinsic mode functions, using Cubic Spline Fitting to primary signal x (t) it is upper,
Lower envelope line xmax(t) and xmin(t), xmaxT () is that maximum point utilizes Cubic Spline Fitting curve, xminT () is minimum point
Using Cubic Spline Fitting curve, and calculate their mean value curve m11(t), m11T () is obtained by formula 4.
m11(t)=[xmax(t)+xmin(t)]/2.(formula 4)
M is deducted in primary signal x (t)11T () obtains h11(t), h11T () is obtained by formula 5.
h11(t)=x (t)-m11(t).(formula 5)
Judge h11T whether () meet condition 1 and condition 2 simultaneously, by h11T the local feature of () carries out resolving into a series of
Intrinsic mode functions IMF.If h11(t) while meet condition 1 and condition 2, then h11T () is used as decompositing in primary signal x (t)
Single order intrinsic mode functions IMF.If h11T () can not simultaneously meet condition 1 and condition 2, then by h11T () replaces in x (t) repetitions
The step of face, obtains h1k(t).Step 5 iteration, further determines that the factor for affecting RFID tag reliability effect big.
h1k(t)=h1(k-1)(t)-m1k(t).(formula 6)
In formula 6, k >=2, until h1kT () meets intrinsic mode functions IMF condition, this process is called intrinsic mode functions IMF sieve
Choosing, thus decomposites single order IMF from primary signal x (t), is denoted as
c1(t)=h1k(t).(formula 7)
(2) c is deducted from primary signal curve x (t)1T () obtains single order residual signal r1(t),
r1(t)=x (t)-c1(t).(formula 8)
By r1T () replaces primary signal x (t) repeat step (1), 2 rank intrinsic mode functions IMF are obtained successively, until n rank sheets
Levy modular function IMF and residual signal rn(t), and rnT () is monotonic function, then primary signal can be expressed as intrinsic mode functions IMF
With form x (t) of residual signal sum,
Fig. 3 is a kind of low voltage mutual inductor RFID tag fundamental diagram according to embodiment of the present invention.Such as Fig. 2 institutes
Show, RFID tag read write line sends electromagnetic signal, electromagnetic signal Jing electromagnetic induction coupler is converted into electric energy, be that radio frequency is known
Distinguishing label is powered, and activates RFID tag, and the RFID tag being activated sends the identity information of storage.It is this by electromagnetism
The size of the faint electric power signal of signal conversion, will affect the identification of RFID tag.
According to embodiment of the present invention, the present invention provides a kind of empirical mode decomposition lifting low voltage mutual inductor radio frequency that is based on and knows
The system of distinguishing label reliability, system includes：
DATA REASONING unit, for measuring low voltage mutual inductor RFID tag in different temperatures, humidity, mutual inductor coil
Performance data under turn on angle and electromagnetic interference strength factor, the basic data expert for setting up transformer RFID tag
Storehouse；The data of low pressure mutual inductance RFID tag, set up transformer RFID tag under home under measurement home
Normal data storehouse；The data of low voltage mutual inductor RFID tag under measure field environment, set up transformer under site environment
The spot database of RFID；
Data analysis unit, for the error analysis method based on empirical mode decomposition, to the basic data expert for setting up
Storehouse, normal data storehouse, spot database is analyzed, and comprises the steps：
Basic data experts database is deducted into normal data database data, the error information that different factors are caused is obtained；
Field data experts database is deducted into normal data database data, the error information that site environment is caused is obtained；
The error information caused to site environment is using the data analysing method based on empirical mode decomposition, it is determined that affecting number
According to the corresponding factor of reliability.
The present invention proposes a kind of data analysing method based on empirical mode decomposition to RF identification under low voltage mutual inductor
Reliability influence factor is analyzed, and finds in various impact environmental impact factors, and determines maximum effect factor, improves
The measurement distance of RFID tag and lifting reliability under low voltage mutual inductor.
The present invention is described by reference to a small amount of embodiment.However, it is known in those skilled in the art, as
What subsidiary Patent right requirement was limited, except the present invention other embodiments disclosed above equally fall the present invention's
In the range of.
Normally, all terms for using in the claims are all solved according to them in the usual implication of technical field
Release, unless clearly defined in addition wherein.It is all of to be all opened ground with reference to " one/described/be somebody's turn to do [device, component etc.] "
At least one of described device, component etc. example is construed to, unless otherwise expressly specified.Any method disclosed herein
Step all need not be run with disclosed accurate order, unless explicitly stated otherwise.
Claims (9)
1. it is a kind of based on empirical mode decomposition lifted low voltage mutual inductor RFID tag reliability method, methods described bag
Include：
Measurement low voltage mutual inductor RFID tag is strong in different temperatures, humidity, mutual inductor coil turn on angle and electromagnetic interference
Performance data under degree factor, sets up the basic data experts database of transformer RFID tag；
The data of low pressure mutual inductance RFID tag, set up transformer RFID tag under home under measurement home
Normal data storehouse；
The data of low voltage mutual inductor RFID tag under measure field environment, set up the scene of transformer RFID under site environment
Database；
Based on the error analysis method of empirical mode decomposition, to set up the basic data experts database, normal data storehouse and
Spot database carries out error analysis, so that it is determined that affect data reliability corresponding factor, and by affect data can
Could be adjusted to lift low voltage mutual inductor RFID tag reliability by the corresponding factor of property.
2. method according to claim 1, the error analysis method based on empirical mode decomposition, walk including following
Suddenly：
The basic data experts database is deducted into normal data database data, the error information that different factors are caused is obtained；
The field data experts database is deducted into normal data database data, the error information that site environment is caused is obtained；
The error information caused to the site environment is using the data analysing method based on empirical mode decomposition, it is determined that affecting number
According to the corresponding factor of reliability.
3. method according to claim 1, the basic expert database, normal data storehouse, site environment database bag
Including data item is<Ultimate range, the signal strength signal intensity of reception is indicated>.
4. method according to claim 3, the basic data experts database for setting up transformer RFID tag, including
Following steps：
The signal of ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under different temperatures factor
Intensity is indicated；
The signal of ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under different humidity factor
Intensity is indicated；
Ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under different electromagnetic interference factors
Signal strength signal intensity is indicated；
The signal of ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under peak power factor
Intensity is indicated；And
The letter of ultimate range and reception of the measurement different model low voltage mutual inductor RFID tag under most half power points factor
Number intensity is indicated.
5. method according to claim 1, sets up under home and measures the normal of low voltage mutual inductor RFID tag
Database, including：
The signal that measurement different model low voltage mutual inductor RFID tag home ultimate range and home are received
Intensity.
6. method according to claim 1, sets up under site environment and measures the scene of low voltage mutual inductor RFID tag
Database, including：
The signal that measurement different model low voltage mutual inductor RFID tag site environment ultimate range and site environment are received
Intensity.
7. method according to claim 1, the error information caused to the site environment is using being based on Empirical Mode
The data analysing method that state is decomposed, it is determined that affecting the corresponding factor of data reliability：
The basic data experts database is D；
The normal data storehouse is Dnormal；
The spot database is Dfield；
The basic data experts database D deducts the home database Dnormal, obtain
Using the DfieldDeduct normal data set Dnormal, obtain
WillAccording to eigenvibration Mode Decomposition time series data, a series of intrinsic mode functions IMF are resolved into, to described
The error information that site environment is caused is using the data analysing method based on empirical mode decomposition, it is determined that affecting data reliability
Correspondence factor.
8. it is a kind of based on empirical mode decomposition lifted low voltage mutual inductor RFID tag reliability system, the system bag
Include：
DATA REASONING unit, is powered for measuring low voltage mutual inductor RFID tag in different temperatures, humidity, mutual inductor coil
Performance data under amount and electromagnetic interference strength factor, sets up the basic data experts database of transformer RFID tag；Survey
The data of low pressure mutual inductance RFID tag, set up the normal of transformer RFID tag under home under amount home
Database；The data of low voltage mutual inductor RFID tag under measure field environment, set up transformer RFID under site environment
Spot database；
Data analysis unit, for the error analysis method based on empirical mode decomposition, to the basic data expert for setting up
Storehouse, normal data storehouse, spot database carry out error analysis, so that it is determined that affecting the corresponding factor of data reliability, and lead to
Cross the corresponding factor to affecting data reliability to could be adjusted to lift low voltage mutual inductor RFID tag reliability.
9. system according to claim 8, the data analysis unit can be also used for：
The basic data experts database is deducted into normal data database data, the error information that different factors are caused is obtained；
The field data experts database is deducted into normal data database data, the error information that site environment is caused is obtained；
The error information caused to the site environment is using the data analysing method based on empirical mode decomposition, it is determined that affecting number
According to the corresponding factor of reliability.
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| CN110346143A (en) * | 2019-08-06 | 2019-10-18 | 江苏今创车辆有限公司 | Hyperfrequency noise assists empirical mode decomposition method |
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