CN109117550A - Accuracy support method and device, terminal, the medium of flow sensor - Google Patents
Accuracy support method and device, terminal, the medium of flow sensor Download PDFInfo
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- CN109117550A CN109117550A CN201810900624.7A CN201810900624A CN109117550A CN 109117550 A CN109117550 A CN 109117550A CN 201810900624 A CN201810900624 A CN 201810900624A CN 109117550 A CN109117550 A CN 109117550A
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- 238000005259 measurement Methods 0.000 abstract description 24
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F25/00—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume
- G01F25/10—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume of flowmeters
Abstract
The present invention discloses the accuracy support method and device, terminal, medium of a kind of flow sensor.The accuracy support method of flow sensor of the invention is judged on platform the accuracy of the flow sensor (i.e. in production scene or laboratory) by a large amount of data rule, makes and timely judging, and be automatically repaired the accuracy of measurement data.It solves the influence of the laboratory environment of product and the variation flow sensor of live use environment, realizes the real-time amendment of accuracy variation in use.The accuracy ensuring equipment of flow sensor of the invention includes detection unit one, detection unit two, detection unit three, calibration unit, instantaneous flow comparing unit, unit of averaging, average value judging unit, compensating unit.
Description
Technical field
The present invention relates to one of big data application field accuracy support method more particularly to a kind of flow sensors
Accuracy support method and its device, terminal, computer readable storage medium.
Background technique
The variation of laboratory environment is affected to calibrational capacity sensor, and the variation of live use environment can similarly give
Application traffic sensor affects, and the environmental change probability in laboratory is relatively low, that is to say, that and environment is relatively stable, but simultaneously
Not representing this laboratory, there is no environmental changes, if ignoring the variation of laboratory environment, the standard of application traffic sensor
Exactness will decline.However in practical application, often ignore the variation of laboratory environment, on the other hand, application traffic sensor
Itself also generates measurement error when environment changes from production scene to use site.
Summary of the invention
The purpose of the present invention is to provide the accuracy support method and its device of a kind of flow sensor, computer are whole
End, computer readable storage medium can correct in real time the standard for using flow sensor in the use process with flow sensor
Exactness variable quantity.
The present invention is implemented with the following technical solutions: a kind of accuracy support method of flow sensor comprising following
Step:
Instantaneous flow k of the detection in production scene or the indoor calibrational capacity sensor of experiment0；
Under conditions of the original factory coefficient of holding application traffic sensor is constant, the application of different use sites is detected
The instantaneous flow of flow sensor obtains data group w5Are as follows: k11, k12... ..., k1m；
Calibrate the coefficient of the application traffic sensor of different use sites；
In different times, different process ranges, the instantaneous of the application traffic sensor of different use sites is detected
Flow obtains multi-group data group W6, every group of data group W6Are as follows: k21, k22... ..., k2m；
By every group of data group W6With data group W5It compares, obtains multi-group data group W7, every group of data group W7Are as follows: k21-k11,
k22-k12... ..., k2m-k1m；
To more data group W6It is averaged Δ '；
The application traffic sensor of use site is when detecting instantaneous flow, the instantaneous flow k and calibration stream that will test
The instantaneous flow k of quantity sensor0It compares, and judges whether comparison result is equal to average value Δ '；
If comparison result is equal to average value Δ ', terminate, otherwise instantaneous flow k is compensated until comparison result
Equal to average value Δ '.
As a further improvement of the foregoing solution, the coefficient calibration of application traffic sensor is passed using ratio of precision application traffic
The higher instrument of the precision of sensor goes to measure and calibrate.
As a further improvement of the foregoing solution, the compensation uses software compensation.
The present invention also provides a kind of accuracy ensuring equipments of flow sensor, define production scene or the indoor stream of experiment
Quantity sensor is calibrational capacity sensor, and the flow sensor for defining each use site is application traffic sensor, calibration stream
Quantity sensor and application traffic sensor have same model, and the accuracy ensuring equipment of the flow sensor includes:
Detection unit one is used to detect the instantaneous flow k in production scene or the indoor calibrational capacity sensor of experiment0；
Detection unit two is used under conditions of the original factory coefficient of holding application traffic sensor is constant, and detection is different
The instantaneous flow of the application traffic sensor of use site, obtains data group w5Are as follows: k11, k12... ..., k1m；
Calibration unit is used to calibrate the coefficient of the application traffic sensor of different use sites；
Detection unit three is used to detect the application stream of different use sites in different times, different process ranges
The instantaneous flow of quantity sensor obtains multi-group data group W6, every group of data group W6Are as follows: k21, k22... ..., k2m；
Instantaneous flow comparing unit is used for every group of data group W6With data group W5It compares, obtains multi-group data group W7, often
Group data group W7Are as follows: k21-k11, k22-k12... ..., k2m-k1m；
Unit of averaging is used for more data group W7It is averaged Δ '；
Average value judging unit is used for the application traffic sensor of use site when detecting instantaneous flow, will test
The instantaneous flow k of instantaneous flow k and calibrational capacity sensor0It compares, and judges whether comparison result is equal to average value Δ '；
If compensating unit for comparison result be not equal to average value Δ ', to instantaneous flow k carry out software compensation until
Comparison result is equal to average value Δ '.
As a further improvement of the foregoing solution, the coefficient calibration of application traffic sensor is passed using ratio of precision application traffic
The higher instrument of the precision of sensor goes to measure and calibrate.
As a further improvement of the foregoing solution, the compensation uses software compensation.
The present invention also provides a kind of terminals comprising memory, processor and is stored on the memory
And the computer program that can be run on the processor, the processor realize above-mentioned flow sensor when executing described program
Accuracy support method the step of.
The present invention also provides a kind of computer readable storage mediums, are stored thereon with computer program, and described program is located
When managing device and executing, the step of realizing the accuracy support method of above-mentioned flow sensor.
The accuracy support method of flow sensor of the invention is judged on platform (i.e. by a large amount of data rule
In production scene or laboratory) flow sensor accuracy, make and timely judging, and be automatically repaired the standard of measurement data
Exactness.Solves the influence of the laboratory environment of product and the variation flow sensor of live use environment, realization is using
The real-time amendment of accuracy variation in the process.
Detailed description of the invention
Fig. 1 is the flow diagram of the accuracy of measurement method of the raising flow sensor of embodiment 1.
Fig. 2 is the modular structure schematic diagram of the accuracy of measurement device of the raising flow sensor of embodiment 2.
Fig. 3 is the flow diagram of the accuracy support method of the flow sensor of embodiment 7.
Fig. 4 is the flow diagram of the accuracy support method of another flow sensor of embodiment 8.
Fig. 5 is the modular structure schematic diagram of the accuracy ensuring equipment of the flow sensor of embodiment 9.
Fig. 6 is the flow diagram of the product quality support method of the flow sensor of embodiment 16.
Fig. 7 is the modular structure schematic diagram of the product quality ensuring equipment of the flow sensor of embodiment 17.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.
Embodiment 1
The present embodiment discloses a kind of accurate come the measurement for improving flow sensor based on flow sensor with repeated data
Degree method.One flow sensor has many flow points, and the repeatability of flow point refers to a flow sensor in the same stream
Amount point repeatedly measures the repeatability of one group of obtained data.Flow sensor is to have certain mistake in certain range of flow
Difference with method of comparison detection is that can generate cumulative errors in practical application.The accuracy error of flow sensor is not under normal circumstances
Obtain 3 times more than repeatability error.Precision based on the data in same flow point repeatability and in different range abilities
The accuracy of measurement method of difference, the raising flow sensor of the present embodiment is with repeatability error come detection flows sensor
The repeatability of different points within the scope of certain flow, thus to determine the accuracy in range of flow.
The flow sensor to be mentioned of the present embodiment is divided into two parts, and a part is in production scene or laboratory
, it is defined herein as calibrational capacity sensor, the measurement error of this kind of flow sensor is close to zero, and all kinds of coefficients are very steady
It is fixed, therefore in the accuracy of measurement method of the raising flow sensor subsequently to be introduced, in production scene or laboratory
Interior flow sensor only needs to acquire when acquiring data once substantially.Another part is the flow in different use sites
Sensor, each use site install at least one flow sensor, are defined herein as application traffic sensor.Use site
Environment is different from production scene or laboratory, and condition much deviates ideal conditions.Therefore, the measurement of application traffic sensor is deposited
In probabilistic error, the even same application traffic sensor also can in different moments for the measurement of same target
Generate different measured values；Different surveys can also be generated by being measured for same target using different application traffic sensors
Magnitude.Therefore, the accuracy of measurement for how calibrating the flow sensor that these are in different use sites is shown in practical applications
It obtains particularly critical.
Referring to Fig. 1, the accuracy of measurement method of the raising flow sensor of the present embodiment includes the following steps.
Step S11, defines production scene or the indoor flow sensor of experiment is calibrational capacity sensor, acquisition calibration stream
The average repeated data of each flow point of quantity sensor, thus to obtain data group W1Are as follows: x1, x2... ..., xn, wherein n table
Show the flow point quantity of flow sensor, xnIndicate calibrational capacity sensor in the average repeated data of n-th of flow point.
Wherein, after each flow point carries out repeated data acquisition at least three times, corresponding discharge is can be obtained in averaging
The average repeated data of point.
Step S12, define each use site flow sensor be application traffic sensor, calibrational capacity sensor and
Application traffic sensor has same model；The every of each application traffic sensor of different use sites is acquired in the same time
The repeated data of a flow point, thus to obtain data group W2Are as follows: { (y11, y12... ..., y1n), (y21, y22... ...,
y2n) ... ..., (ym1, ym2... ..., ymn), wherein m indicates the quantity of application traffic sensor, ymnIndicate m-th of application stream
Repeated data of the quantity sensor in n-th of flow point.
Step S13, point repeats step S12 in different times, thus to obtain multi-group data group W2。
Step S14, for the same flow point of same application flow sensor, by every group of data group W2Middle corresponding discharge point
Repeated data and data group W1The average repeated data of correspondence compare and take difference, obtain multi-group data group W3, every group of number
According to a group W3Are as follows: { (Δ11=y11-x1, Δ12=y12-x2... ..., Δ1n=y1n-xn), (Δ21=y11-x1, Δ22=y12-
x2... ..., Δ2n=y1n-xn) ... ..., (Δn1=y11-x1, Δn2=y12-x2... ..., Δnn=y1n-xn)}。
Step S15 is averaged (i.e. to multi-group data group W all differences3It is averaged), obtain average value Δ.
Step S16 judges every group of data group W3In difference whether be equal to average value Δ.
If every group of data group W3In difference be equal to average value Δ, then terminate.Otherwise (i.e. if every group of data group W3In
Difference be not equal to average value Δ), then carry out step S17: adjusting the coefficient of respective application flow sensor until corresponding difference
Equal to difference average value Δ.
Wherein, the coefficient for adjusting respective application flow sensor can use hardware adjustments, such as directly to respective application stream
The coefficient magnitude of quantity sensor is adjusted.Software adjustment can also be used, to the measured value of respective application flow sensor into
Row software compensation, such as to corresponding difference be less than difference average value Δ the case where, just compensated, to corresponding difference greater than difference put down
The case where mean value Δ, carries out negative compensation.In the repeated DATA REASONING of subsequent application traffic sensor, so that it may continuous
It adopts and goes to correct in this way.
The accuracy of measurement method of the raising flow sensor of the present embodiment, it is first assumed that calibrational capacity sensor is averaged
Accurately, by the average repeated data using calibrational capacity sensor as reference standard, then repeated data are exactly
By big data application, use the average value for the repeated data for widely applying flow sensor for reference standard, it is covert to calibrate
The error of the physical presence of calibrational capacity sensor, while the application traffic sensor of deviation average is adjusted, it is answered to improve
With the accuracy of flow sensor.
Embodiment 2
Present embodiments provide a kind of accuracy of measurement device for improving flow sensor, the accuracy of measurement of the present embodiment
Device uses the accuracy of measurement method of the raising flow sensor of embodiment 1.
Referring to Fig. 2, accuracy of measurement device includes repeated data acquisition unit 1, repeated data acquisition unit
22, difference comparing unit 3, average value acquiring unit 4, dif ference judgment unit 5, adjusting unit 6.
Defining production scene or the indoor flow sensor of experiment is calibrational capacity sensor, repeated data acquisition unit
The average repeated data of one 1 each flow point for acquiring calibrational capacity sensor, thus to obtain data group W1Are as follows: x1,
x2... ..., xn.Wherein, n indicates the flow point quantity of flow sensor, xnIndicate calibrational capacity sensor in n-th of flow point
Average repeated data.Wherein, after each flow point carries out repeated data acquisition at least three times, averaging be can be obtained
The average repeated data of corresponding discharge point.
The flow sensor for defining each use site is application traffic sensor, calibrational capacity sensor and application traffic
Sensor has same model.Repeated data acquisition unit 22 is used to acquire each of different use sites in the same time
The repeated data of each flow point of application traffic sensor, thus to obtain data group W2Are as follows: { (y11, y12... ..., y1n),
(y21, y22... ..., y2n) ... ..., (ym1, ym2... ..., ymn)}.Wherein, m indicates the quantity of application traffic sensor, ymnIt indicates
Repeated data of m-th of application traffic sensor in n-th of flow point.
Each application traffic of 22 multi collect difference use site of repeated data acquisition unit is put in different times
The repeated data of each flow point of sensor, thus to obtain multi-group data group W2。
Difference comparing unit 3 is used for the same flow point for same application flow sensor, by the weight of corresponding discharge point
Renaturation data and data group W1The average repeated data of correspondence compare and take difference, obtain multi-group data group W3, every group of data group
W3Are as follows: { (Δ11=y11-x1, Δ12=y12-x2... ..., Δ1n=y1n-xn), (Δ21=y11-x1, Δ22=y12-x2... ...,
Δ2n=y1n-xn) ... ..., (Δn1=y11-x1, Δn2=y12-x2... ..., Δnn=y1n-xn)}。
Average value acquiring unit 4 obtains average value Δ for being averaged to all differences.
Dif ference judgment unit 5 is for judging every group of data group W3In difference whether be equal to average value Δ.If every group of number
According to a group W3In difference be equal to average value Δ, then terminate.If adjusting unit 6 is used for every group of data group W3In difference be not equal to
Average value Δ then adjusts the coefficient of respective application flow sensor until corresponding difference is equal to difference average value Δ.
Wherein, unit 6 is adjusted when adjusting the coefficient of respective application flow sensor, can use hardware adjustments, it is such as straight
It connects and the coefficient magnitude of respective application flow sensor is adjusted；Software adjustment can also be used, respective application flow is passed
The case where measured value of sensor carries out software compensation, is such as less than difference average value Δ to corresponding difference, is just compensated, to corresponding
Difference is greater than the case where difference average value Δ, carries out negative compensation.
The accuracy of measurement device of embodiment has the phase of the accuracy of measurement method of the raising flow sensor of embodiment 1
Same beneficial effect.
Embodiment 3
The present embodiment provides a kind of terminals comprising memory, processor and is stored on the memory
And the computer program that can be run on the processor.The processor realizes the raising of embodiment 1 when executing described program
The step of accuracy of measurement method of flow sensor.
The accuracy of measurement method of the raising flow sensor of embodiment 1 in use, can be answered in the form of software
With being such as designed to independently operated program, on computer terminals, terminal can be computer, smart phone etc. for installation.
It can also be designed to the program of embedded operation, installation on computer terminals, is such as mounted on single-chip microcontroller.
Embodiment 4
The present embodiment provides a kind of computer readable storage mediums, are stored thereon with computer program.Described program is located
Manage device execute when, realize embodiment 1 raising flow sensor accuracy of measurement method the step of.
The accuracy of measurement method of the raising flow sensor of embodiment 1 in use, can be answered in the form of software
With, be such as designed to computer readable storage medium can independently operated program, computer readable storage medium can be USB flash disk, if
U-shield is counted into, is designed to start the program of entire method by external triggering by USB flash disk.
Embodiment 5
The present embodiment provides a kind of flow sensor, the flow sensor uses the raising flow sensor of embodiment 1
Accuracy of measurement method adjust or correct, to improve the accuracy of measurement.
Embodiment 6
The present embodiment provides a kind of Internet of Things big data acquisition processing system, the Internet of Things big data acquisition processing system is directed to
The various appliance devices of user carry out data acquisition, then do the various processing needed to the data of acquisition back, then will place
Data after reason are shown, or are uploaded to network, or are collected to have access to server for client and be checked.
Defining production scene or the indoor flow sensor of experiment is calibrational capacity sensor, defines each use site
Flow sensor is application traffic sensor, and calibrational capacity sensor and application traffic sensor have same model.
The Internet of Things big data acquisition processing system first receives the average repetition of each flow point of calibrational capacity sensor
Property data, thus to obtain data group W1Are as follows: x1, x2... ..., xn, wherein n indicates the flow point quantity of flow sensor, xnIt indicates
Average repeated data of the calibrational capacity sensor in n-th of flow point.Wherein, each flow point carries out repetition at least three times
Property data acquisition after, be averaging the average repeated data that corresponding discharge point can be obtained.
Later, the Internet of Things big data receiving processing system acquires each application stream of different use sites in the same time
The repeated data of each flow point of quantity sensor, thus to obtain data group W2Are as follows: { (y11, y12... ..., y1n), (y21,
y22... ..., y2n) ... ..., (ym1, ym2... ..., ymn), wherein m indicates the quantity of application traffic sensor, ymnIndicate m
Repeated data of a application traffic sensor in n-th of flow point.
Then, the Internet of Things big data acquisition processing system puts repetition in different times and receives the every of different use sites
The repeated data of each flow point of a application traffic sensor, thus to obtain multi-group data group W2。
Then, the Internet of Things big data acquisition processing system is directed to the same flow point of same application flow sensor, will
The repeated data and data group W of corresponding discharge point1The average repeated data of correspondence compare and take difference, obtain multi-group data
Group W3, every group of data group W3Are as follows: { (Δ11=y11-x1, Δ12=y12-x2... ..., Δ1n=y1n-xn), (Δ21=y11-x1, Δ22
=y12-x2... ..., Δ2n=y1n-xn) ... ..., (Δn1=y11-x1, Δn2=y12-x2... ..., Δnn=y1n-xn)}。
Followed by the Internet of Things big data acquisition processing system is averaged all differences, obtains average value Δ, then judge
Every group of data group W3In difference whether be equal to average value Δ, if every group of data group W3In difference be equal to average value Δ, then tie
Beam, if every group of data group W3In difference be not equal to average value Δ, then adjust respective application flow sensor coefficient until
Corresponding difference is equal to difference average value Δ.
Wherein, the coefficient for adjusting respective application flow sensor can use hardware adjustments, such as directly to respective application stream
The coefficient magnitude of quantity sensor is adjusted.Software adjustment can also be used by the Internet of Things big data acquisition processing system,
The case where is carried out by software compensation, is such as less than difference average value Δ to corresponding difference for the measured value of respective application flow sensor,
The case where just being compensated, being greater than difference average value Δ to corresponding difference, carries out negative compensation.
Embodiment 7
The detection data of the application traffic sensor of use site, precision can by environment variation and change.It is general this
Kind variation is ignored, and only can consider that environmental change or even precision from laboratory (namely production environment) to use site are wanted
Not high flowmeter is sought, all without considering the environmental change in laboratory to use site.
For the environmental change in laboratory to use site, and for the constant flow sensor of instantaneous flow, this
Embodiment provides a kind of accuracy support method of flow sensor.Referring to Fig. 3, the flow sensor of the present embodiment is accurate
Degree support method includes the following steps.
Step S21 calibrates the coefficient of the application traffic sensor of different use sites.The coefficient school of application traffic sensor
Quasi- generally to be gone to measure and be calibrated using the higher instrument of precision of ratio of precision application traffic sensor, regulation uses precision in national standard
The instrument more three times higher than sensor to be measured.
Step S22 detects instantaneous flow of each application traffic sensor in different process ranges, obtains multiple groups
Data group W4, every group of data group W4Are as follows: Z21, Z22... ..., Z2u, wherein u represents the quantity of process range.
Step S23, the application traffic sensor of use site is when detecting instantaneous flow, the instantaneous flow k that will test
With the Z within the scope of corresponding process2uIt compares.
If the Z within the scope of instantaneous flow k and corresponding process2uIt is identical, then terminate, otherwise, carries out step S24: to wink
Shi Liuliang k, which carries out software compensation, makes the Z within the scope of instantaneous flow k and corresponding process2uIt is identical.
The present embodiment pass through calibrate in advance different use sites application traffic sensor coefficient, then with calibration after
Instantaneous flow of the application traffic sensor in different range abilities brings the reference as subsequent detection as standard value, because
This can be modified subsequent if generating error and the comparison with standard value.
Embodiment 8
The present embodiment provides a kind of accuracy support methods of flow sensor.The variation of laboratory environment is to calibrational capacity
Sensor affects, and the variation of live use environment can similarly be affected to application traffic sensor, the ring in laboratory
It is relatively low that border changes probability, that is to say, that and environment is relatively stable, but does not represent this laboratory and environmental change is not present, if
Ignore the variation of laboratory environment, then the accuracy of application traffic sensor will decline.However in practical application, often neglect
The slightly variation of laboratory environment, on the other hand, application traffic sensor itself occurs from production scene to use site in environment
When variation, measurement error is also generated.So needing in the use process with flow sensor, flow sensor is used in amendment in real time
Accuracy variable quantity.The difference of the present embodiment and embodiment 7 is, the environment of the use site of the present embodiment and it is non-constant not
Become, goes the accuracy for ensureing flow sensor in such a situa-tion.
Referring to Fig. 4, the accuracy support method of the flow sensor of the present embodiment includes the following steps.
Step S31, instantaneous flow k of the detection in production scene or the indoor calibrational capacity sensor of experiment0。
Step S32 is detected different using existing under conditions of the original factory coefficient of holding application traffic sensor is constant
The instantaneous flow of the application traffic sensor of field, obtains data group w5Are as follows: k11, k12... ..., k1m。
Step S33 calibrates the coefficient of the application traffic sensor of different use sites.The coefficient school of application traffic sensor
Quasi- generally to be gone to measure and be calibrated using the higher instrument of precision of ratio of precision application traffic sensor, regulation uses precision in national standard
The instrument more three times higher than sensor to be measured.Step S34 is detected different using existing in different times, different process ranges
The instantaneous flow of the application traffic sensor of field, obtains multi-group data group W6, every group of data group W6Are as follows: k21, k22... ..., k2m。
Step S35, by every group of data group W6With data group W5It compares, obtains multi-group data group W7, every group of data group W7
Are as follows: k21-k11, k22-k12... ..., k2m-k1m。
Step S36, to more data group W6It is averaged Δ '.
Step S37, the application traffic sensor of use site is when detecting instantaneous flow, the instantaneous flow k that will test
With the instantaneous flow k of calibrational capacity sensor0It compares, and judges whether comparison result is equal to average value Δ '.
If comparison result is equal to average value Δ ', terminate, otherwise (i.e. if comparison result is not equal to average value Δ '),
It carries out step S38: software compensation being carried out to instantaneous flow k until comparison result is equal to average value Δ '.
The present embodiment judges on platform that the flow (i.e. in production scene or laboratory) is passed by a large amount of data rule
The accuracy of sensor, makes and timely judging, and is automatically repaired the accuracy of measurement data.Solves the laboratory environment of product
With the influence of the variation flow sensor of live use environment, repairing in real time for accuracy variation in use is realized
Just.
Embodiment 9
Present embodiments provide a kind of accuracy ensuring equipment of flow sensor, the standard of the flow sensor of the present embodiment
Exactness ensuring equipment uses the accuracy support method of the flow sensor of embodiment 7.
Referring to Fig. 5, accuracy ensuring equipment includes detection unit 1, detection unit 2 12, calibration unit 13, detection
Unit 3 14, instantaneous flow comparing unit 15, unit 17 of averaging, average value judging unit 18, compensating unit 19.
Defining production scene or the indoor flow sensor of experiment is calibrational capacity sensor, defines each use site
Flow sensor is application traffic sensor, and calibrational capacity sensor and application traffic sensor have same model.
Detection unit 1 is used to detect the instantaneous flow in production scene or the indoor calibrational capacity sensor of experiment
k0.Detection unit 2 12 is used under conditions of the original factory coefficient of holding application traffic sensor is constant, and detection difference makes
With the instantaneous flow of the application traffic sensor at scene, data group w is obtained5Are as follows: k11, k12... ..., k1m.Calibration unit 13 is used for
Calibrate the coefficient of the application traffic sensor of different use sites.
Detection unit 3 14 is used to detect the application of different use sites in different times, different process ranges
The instantaneous flow of flow sensor obtains multi-group data group W6, every group of data group W6Are as follows: k21, k22... ..., k2m。
Instantaneous flow comparing unit 15 is used for every group of data group W6With data group W5It compares, obtains multi-group data group W7,
Every group of data group W7Are as follows: k21-k11, k22-k12... ..., k2m-k1m.Unit 17 of averaging is used for more data group W7It is averaged
Δ'.Average value judging unit 18 is used for the application traffic sensor of use site when detecting instantaneous flow, the wink that will test
The instantaneous flow k of Shi Liuliang k and calibrational capacity sensor0It compares, and judges whether comparison result is equal to average value Δ '.Such as
Fruit comparison result is equal to average value Δ ', then terminate, otherwise (i.e. if comparison result is not equal to average value Δ '), compensating unit 19
For carrying out software compensation to instantaneous flow k until comparison result is equal to average value Δ '.
The accuracy of measurement device of embodiment has the phase of the accuracy of measurement method of the raising flow sensor of embodiment 1
Same beneficial effect.
Embodiment 10
The present embodiment provides a kind of terminals comprising memory, processor and is stored on the memory
And the computer program that can be run on the processor.The processor is realized embodiment 7 or is implemented when executing described program
The step of accuracy support method of the flow sensor of example 8.
The accuracy support method of the flow sensor of embodiment 7 or embodiment 8 in use, can in the form of software into
Row application is such as designed to independently operated program, and on computer terminals, terminal can be computer, intelligent hand for installation
Machine etc..It can also be designed to the program of embedded operation, installation on computer terminals, is such as mounted on single-chip microcontroller.
Embodiment 11
The present embodiment provides a kind of computer readable storage mediums, are stored thereon with computer program.Described program is located
When managing device and executing, the step of realizing the accuracy support method of the flow sensor of embodiment 7 or embodiment 8.
The accuracy support method of the flow sensor of embodiment 7 or embodiment 8 in use, can in the form of software into
Row application, be such as designed to computer readable storage medium can independently operated program, computer readable storage medium can be U
Disk is designed to U-shield, is designed to start the program of entire method by external triggering by USB flash disk.
Embodiment 12
The present embodiment provides a kind of flow sensor, the flow sensor is passed using the flow of embodiment 7 or embodiment 8
The accuracy support method of sensor come correct application traffic sensor detection instantaneous flow, to ensure the standard of flow sensor
Exactness.
Embodiment 13
The present embodiment provides a kind of flow sensor, the flow sensor is not only with the stream of embodiment 7 or embodiment 8
The accuracy support method of quantity sensor come correct application traffic sensor detection instantaneous flow, to ensure flow sensor
Accuracy, also adjust or correct using the accuracy of measurement method of the raising flow sensor of embodiment 1, to improve survey
The accuracy of amount.
Embodiment 14
The present embodiment provides a kind of Internet of Things big data acquisition processing system, the Internet of Things big data acquisition processing system is directed to
The various appliance devices of user carry out data acquisition, then do the various processing needed to the data of acquisition back, then will place
Data after reason are shown, or are uploaded to network, or are collected to have access to server for client and be checked.
Defining production scene or the indoor flow sensor of experiment is calibrational capacity sensor, defines each use site
Flow sensor is application traffic sensor, and calibrational capacity sensor and application traffic sensor have same model.
The Internet of Things big data acquisition processing system is first received in production scene or the indoor calibrational capacity sensing of experiment
The instantaneous flow k of device0；Again under conditions of the original factory coefficient of holding application traffic sensor is constant, different uses are received
The instantaneous flow of the application traffic sensor at scene, obtains data group w5Are as follows: k11, k12... ..., k1m。
The Internet of Things big data acquisition processing system then calibrates the coefficient of the application traffic sensor of different use sites,
And after the calibration of the coefficient of application traffic sensor, in different times, different process ranges, the Internet of Things big data is adopted
Collection processing system also receives the instantaneous flow of the application traffic sensor of different use sites, obtains multi-group data group W6, every group
Data group W6Are as follows: k21, k22... ..., k2m；Again by every group of data group W6With data group W5It compares, obtains multi-group data group W7, often
Group data group W7Are as follows: k21-k11, k22-k12... ..., k2m-k1m；Later, to more data group W7It is averaged Δ '.
When detecting instantaneous flow, the Internet of Things big data acquisition processing system connects the application traffic sensor of use site
Receive the instantaneous flow k of the instantaneous flow k and calibrational capacity sensor that detect0It compares, and judges whether comparison result is equal to
Average value Δ '.If comparison result is equal to average value Δ ', terminate, otherwise (i.e. if comparison result is not equal to average value
Δ '), the Internet of Things big data acquisition processing system carries out software compensation to instantaneous flow k until comparison result is equal to average value
Δ’。
Internet of Things big data acquisition processing system judges on platform (i.e. production scene or experiment by a large amount of data rule
It is indoor) flow sensor accuracy, make and timely judging, and be automatically repaired the accuracy of measurement data.Solves production
The influence of the variation flow sensor of the laboratory environment of product and live use environment, realizes accuracy in use
The real-time amendment of variation.
Embodiment 15
For the present embodiment on the basis of embodiment 14, Internet of Things big data acquisition processing system also receives calibrational capacity sensor
Each flow point average repeated data, thus to obtain data group W1Are as follows: x1, x2... ..., xn, wherein n indicates that flow passes
The flow point quantity of sensor, xnIndicate calibrational capacity sensor in the average repeated data of n-th of flow point.Wherein, each
After flow point carries out repeated data acquisition at least three times, it is averaging the average repeated number that corresponding discharge point can be obtained
According to.
Later, the Internet of Things big data receiving processing system acquires each application stream of different use sites in the same time
The repeated data of each flow point of quantity sensor, thus to obtain data group W2Are as follows: { (y11, y12... ..., y1n), (y21,
y22... ..., y2n) ... ..., (ym1, ym2... ..., ymn), wherein m indicates the quantity of application traffic sensor, ymnIndicate m
Repeated data of a application traffic sensor in n-th of flow point.
Then, the Internet of Things big data acquisition processing system puts repetition in different times and receives the every of different use sites
The repeated data of each flow point of a application traffic sensor, thus to obtain multi-group data group W2。
Then, the Internet of Things big data acquisition processing system is directed to the same flow point of same application flow sensor, will
The repeated data and data group W of corresponding discharge point1The average repeated data of correspondence compare and take difference, obtain multi-group data
Group W3, every group of data group W3Are as follows: { (Δ11=y11-x1, Δ12=y12-x2... ..., Δ1n=y1n-xn), (Δ21=y11-x1, Δ22
=y12-x2... ..., Δ2n=y1n-xn) ... ..., (Δn1=y11-x1, Δn2=y12-x2... ..., Δnn=y1n-xn)}。
Followed by the Internet of Things big data acquisition processing system is averaged all differences, obtains average value Δ, then judge
Every group of data group W3In difference whether be equal to average value Δ, if every group of data group W3In difference be equal to average value Δ, then tie
Beam, if every group of data group W3In difference be not equal to average value Δ, then adjust respective application flow sensor coefficient until
Corresponding difference is equal to difference average value Δ.
Wherein, the coefficient for adjusting respective application flow sensor can use hardware adjustments, such as directly to respective application stream
The coefficient magnitude of quantity sensor is adjusted.Software adjustment can also be used by the Internet of Things big data acquisition processing system,
The case where is carried out by software compensation, is such as less than difference average value Δ to corresponding difference for the measured value of respective application flow sensor,
The case where just being compensated, being greater than difference average value Δ to corresponding difference, carries out negative compensation.
Embodiment 16
The present embodiment provides a kind of product quality support methods of flow sensor.Existing flow sensor is actually being answered
In, product quality goes wrong the principle taken and controlled afterwards, maintenance or replacement.The present embodiment can guarantee that product is being asked
It before topic, is analyzed by data, to judge the failure of instrument, accomplishes to prevent in advance.
Referring to Fig. 6, the product quality support method of the flow sensor of the present embodiment includes the following steps.
Step S41, same pipeline install two flow sensors of identical bore.
Step S42, real-time synchronization acquire the instantaneous flow of two flow sensors, and mutually compare.
Step S43, when there is deviation in the instantaneous flow of two flow sensors, the instantaneous flow of two flow sensors
The instantaneous flow with respective primitive accumulation compares respectively, and the instantaneous flow of the primitive accumulation is instantaneous in a period of time
Flow average value.
Step S44, if the instantaneous flow of some flow sensor and the instantaneous flow deviation of its primitive accumulation are more than one
It is abnormal then to judge that this flow sensor occurs for a preset value.Therefore, this flow sensor needs on-call maintenance and replacement.
Abnormal sensor on-call maintenance or replacement can reduce the risk that equipment fault causes production to be stopped work.
Step S45, if the instantaneous flow of some flow sensor and the instantaneous flow deviation of its primitive accumulation are zero,
Judge that the measurement of this flow sensor is accurate.
The product quality support method of the flow sensor of the present embodiment, done at runtime by two flow sensors and
When compare, when occur data deviate in time and respective primitive accumulation comparing, cause to give birth to so as to reduce equipment fault
The risk stopped work is produced, and the accuracy of the data of flow sensor accomplishes to monitor constantly.
Embodiment 17
A kind of product quality ensuring equipment of flow sensor is present embodiments provided, the flow sensor of the present embodiment
Product quality ensuring equipment uses the product quality support method of the flow sensor of embodiment 15.
Referring to Fig. 7, the product quality ensuring equipment of flow sensor include comparing unit 1, comparing unit 2 33,
Two instantaneous flow acquisition units 31, conclusion judging unit 34.
Two instantaneous flow acquisition units 31 are used for respectively to the flow for two identical bores being mounted on same pipeline
Sensor real-time synchronization acquires instantaneous flow.
Comparing unit 1 is used to compare to the instantaneous flow of two flow sensors of identical bore.
Comparing unit 2 33 is used for when deviation occurs in the instantaneous flow of two flow sensors, two flow sensors
Instantaneous flow of the instantaneous flow respectively with respective primitive accumulation compares, and the instantaneous flow of the primitive accumulation is a period of time
Interior instantaneous flow average value.
If conclusion judging unit 34 is for the instantaneous flow of some flow sensor and the instantaneous flow of its primitive accumulation
Deviation is more than a preset value, then it is abnormal to judge that this flow sensor occurs；If the instantaneous flow of some flow sensor
Instantaneous flow deviation with its primitive accumulation is zero, then judges that the measurement of this flow sensor is accurate.When judge this flow pass
When sensor occurs abnormal, this flow sensor needs on-call maintenance and replacement.Therefore, abnormal sensor on-call maintenance or
Replacement can reduce the risk that equipment fault causes production to be stopped work.
Embodiment 18
The present embodiment provides a kind of terminals comprising memory, processor and is stored on the memory
And the computer program that can be run on the processor.The processor realizes the flow of embodiment 16 when executing described program
The step of product quality support method of sensor.
The product quality support method of the flow sensor of embodiment 16 in use, can be answered in the form of software
With being such as designed to independently operated program, on computer terminals, terminal can be computer, smart phone etc. for installation.
It can also be designed to the program of embedded operation, installation on computer terminals, is such as mounted on single-chip microcontroller.
Embodiment 19
The present embodiment provides a kind of computer readable storage mediums, are stored thereon with computer program.Described program is located
Manage device execute when, realize embodiment 16 flow sensor product quality support method the step of.
The product quality support method of the flow sensor of embodiment 16 in use, can be answered in the form of software
With, be such as designed to computer readable storage medium can independently operated program, computer readable storage medium can be USB flash disk, if
U-shield is counted into, is designed to start the program of entire method by external triggering by USB flash disk.
Embodiment 20
The present embodiment provides a kind of flow sensor, the flow sensor uses the production of the flow sensor of embodiment 16
Quality support method ensures the product quality of flow sensor in use process, causes production to stop to reduce equipment fault
The risk of work.
Embodiment 21
The present embodiment provides a kind of flow sensor, the flow sensor is not only with the flow sensor of embodiment 16
Product quality support method ensure the product quality of flow sensor in use process, so that reducing equipment fault causes to give birth to
The risk stopped work is produced, application traffic is also corrected using the accuracy support method of the flow sensor of embodiment 7 or embodiment 8
The instantaneous flow of sensor detection, to ensure the accuracy of flow sensor.
Embodiment 22
The present embodiment provides a kind of flow sensor, the flow sensor first aspect is passed using the flow of embodiment 16
The product quality support method of sensor ensures the product quality of flow sensor in use process, leads to reduce equipment fault
The risk for causing production to stop work；Second aspect also uses the accuracy support method of the flow sensor of embodiment 7 or embodiment 8
The instantaneous flow for correcting the detection of application traffic sensor, to ensure the accuracy of flow sensor；The third aspect also uses reality
The accuracy of measurement method of the raising flow sensor of example 1 is applied to adjust or correct, to improve the accuracy of measurement.
Embodiment 23
The present embodiment provides a kind of Internet of Things big data acquisition processing system, the Internet of Things big data acquisition processing system is directed to
The various appliance devices of user carry out data acquisition, then do the various processing needed to the data of acquisition back, then will place
Data after reason are shown, or are uploaded to network, or are collected to have access to server for client and be checked.
Defining production scene or the indoor flow sensor of experiment is calibrational capacity sensor, defines each use site
Flow sensor is application traffic sensor, and calibrational capacity sensor and application traffic sensor have same model.
The Internet of Things big data acquisition processing system receives the stream for two identical bores being mounted on same pipeline respectively
The real-time instantaneous flow of quantity sensor, and compare the instantaneous flow of two flow sensors of identical bore.The big number of Internet of Things
(the instantaneous stream of i.e. two flow sensors when there is deviation according to the instantaneous flow that acquisition processing system analyzes two flow sensors
When measuring not identical), the Internet of Things big data acquisition processing system also by the instantaneous flow of two flow sensors respectively and respectively
The instantaneous flow of primitive accumulation compare, the instantaneous flow of the primitive accumulation is that the instantaneous flow in a period of time is average
Value.
If the Internet of Things big data acquisition processing system judges the instantaneous flow and its original product of some flow sensor
Tired instantaneous flow deviation is more than a preset value, then gives a warning abnormal to prompt this flow sensor to occur；The object
If the instantaneous flow of some flow sensor of the United Nations General Assembly's data acquisition processing system judgement and the instantaneous flow of its primitive accumulation are inclined
Difference is zero, then it is assumed that the measurement of this flow sensor is accurate.When thinking that the measurement of this flow sensor is accurate, it can not issue and appoint
What is alerted.When judging that this flow sensor occurs abnormal, this flow sensor needs on-call maintenance and replacement.Therefore,
Abnormal sensor on-call maintenance or replacement can reduce the risk that equipment fault causes production to be stopped work.
Embodiment 24
On the basis of embodiment 23, Internet of Things big data acquisition processing system also first receives and is in production scene the present embodiment
Or the instantaneous flow k of the indoor calibrational capacity sensor of experiment0；Keeping the original factory coefficient of application traffic sensor not again
Under conditions of change, the instantaneous flow of the application traffic sensor of different use sites is received, data group w is obtained5Are as follows: k11,
k12... ..., k1m；Then the coefficient of the application traffic sensor of different use sites is calibrated.
The Internet of Things big data acquisition processing system is after the coefficient calibration of application traffic sensor, in different times, no
When with process range, the Internet of Things big data acquisition processing system also receives the application traffic sensor of different use sites
Instantaneous flow, obtain multi-group data group W6, every group of data group W6Are as follows: k21, k22... ..., k2m；Again by every group of data group W6Sum number
According to a group W5It compares, obtains multi-group data group W7, every group of data group W7Are as follows: k21-k11, k22-k12... ..., k2m-k1m；Later, right
More data group W7It is averaged Δ '.
When detecting instantaneous flow, the Internet of Things big data acquisition processing system connects the application traffic sensor of use site
Receive the instantaneous flow k of the instantaneous flow k and calibrational capacity sensor that detect0It compares, and judges whether comparison result is equal to
Average value Δ '.If comparison result is equal to average value Δ ', terminate, otherwise (i.e. if comparison result is not equal to average value
Δ '), the Internet of Things big data acquisition processing system carries out software compensation to instantaneous flow k until comparison result is equal to average value
Δ’。
Internet of Things big data acquisition processing system judges on platform (i.e. production scene or experiment by a large amount of data rule
It is indoor) flow sensor accuracy, make and timely judging, and be automatically repaired the accuracy of measurement data.Solves production
The influence of the variation flow sensor of the laboratory environment of product and live use environment, realizes accuracy in use
The real-time amendment of variation.
Embodiment 25
For the present embodiment on the basis of embodiment 24, Internet of Things big data acquisition processing system also receives calibrational capacity sensor
Each flow point average repeated data, thus to obtain data group W1Are as follows: x1, x2... ..., xn, wherein n indicates that flow passes
The flow point quantity of sensor, xnIndicate calibrational capacity sensor in the average repeated data of n-th of flow point.Wherein, each
After flow point carries out repeated data acquisition at least three times, it is averaging the average repeated number that corresponding discharge point can be obtained
According to.
Later, the Internet of Things big data receiving processing system acquires each application stream of different use sites in the same time
The repeated data of each flow point of quantity sensor, thus to obtain data group W2Are as follows: { (y11, y12... ..., y1n), (y21,
y22... ..., y2n) ... ..., (ym1, ym2... ..., ymn), wherein m indicates the quantity of application traffic sensor, ymnIndicate m
Repeated data of a application traffic sensor in n-th of flow point.
Then, the Internet of Things big data acquisition processing system puts repetition in different times and receives the every of different use sites
The repeated data of each flow point of a application traffic sensor, thus to obtain multi-group data group W2。
Then, the Internet of Things big data acquisition processing system is directed to the same flow point of same application flow sensor, will
The repeated data and data group W of corresponding discharge point1The average repeated data of correspondence compare and take difference, obtain multi-group data
Group W3, every group of data group W3Are as follows: { (Δ11=y11-x1, Δ12=y12-x2... ..., Δ1n=y1n-xn), (Δ21=y11-x1, Δ22
=y12-x2... ..., Δ2n=y1n-xn) ... ..., (Δn1=y11-x1, Δn2=y12-x2... ..., Δnn=y1n-xn)}。
Followed by the Internet of Things big data acquisition processing system is averaged all differences, obtains average value Δ, then judge
Every group of data group W3In difference whether be equal to average value Δ, if every group of data group W3In difference be equal to average value Δ, then tie
Beam, if every group of data group W3In difference be not equal to average value Δ, then adjust respective application flow sensor coefficient until
Corresponding difference is equal to difference average value Δ.
Wherein, the coefficient for adjusting respective application flow sensor can use hardware adjustments, such as directly to respective application stream
The coefficient magnitude of quantity sensor is adjusted.Software adjustment can also be used by the Internet of Things big data acquisition processing system,
The case where is carried out by software compensation, is such as less than difference average value Δ to corresponding difference for the measured value of respective application flow sensor,
The case where just being compensated, being greater than difference average value Δ to corresponding difference, carries out negative compensation.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (8)
1. a kind of accuracy support method of flow sensor, which is characterized in that itself the following steps are included:
Instantaneous flow k of the detection in production scene or the indoor calibrational capacity sensor of experiment0；
Under conditions of the original factory coefficient of holding application traffic sensor is constant, the application traffic of different use sites is detected
The instantaneous flow of sensor obtains data group w5Are as follows: k11, k12... ..., k1m；
Calibrate the coefficient of the application traffic sensor of different use sites；
In different times, different process ranges, the instantaneous flow of the application traffic sensor of different use sites is detected,
Obtain multi-group data group W6, every group of data group W6Are as follows: k21, k22... ..., k2m；
By every group of data group W6With data group W5It compares, obtains multi-group data group W7, every group of data group W7Are as follows: k21-k11, k22-
k12... ..., k2m-k1m；
To more data group W6It is averaged Δ '；
When detecting instantaneous flow, the instantaneous flow k and calibrational capacity that will test are passed the application traffic sensor of use site
The instantaneous flow k of sensor0It compares, and judges whether comparison result is equal to average value Δ '；
If comparison result is equal to average value Δ ', terminate, otherwise instantaneous flow k is compensated until comparison result is equal to
Average value Δ '.
2. the accuracy support method of flow sensor as described in claim 1, which is characterized in that application traffic sensor
Coefficient calibration is gone to measure and be calibrated using the higher instrument of precision of ratio of precision application traffic sensor.
3. the accuracy support method of flow sensor as described in claim 1, which is characterized in that the compensation uses software
Compensation.
4. a kind of accuracy ensuring equipment of flow sensor, defining production scene or the indoor flow sensor of experiment is calibration
Flow sensor, the flow sensor for defining each use site is application traffic sensor, calibrational capacity sensor and application
Flow sensor has same model, which is characterized in that the accuracy ensuring equipment of the flow sensor includes:
Detection unit one is used to detect the instantaneous flow k in production scene or the indoor calibrational capacity sensor of experiment0；
Detection unit two is used to detect different uses under conditions of the original factory coefficient of holding application traffic sensor is constant
The instantaneous flow of the application traffic sensor at scene, obtains data group w5Are as follows: k11, k12... ..., k1m；
Calibration unit is used to calibrate the coefficient of the application traffic sensor of different use sites；
Detection unit three is used in different times, different process ranges, and the application traffic for detecting different use sites passes
The instantaneous flow of sensor obtains multi-group data group W6, every group of data group W6Are as follows: k21, k22... ..., k2m；
Instantaneous flow comparing unit is used for every group of data group W6With data group W5It compares, obtains multi-group data group W7, every group of number
According to a group W7Are as follows: k21-k11, k22-k12... ..., k2m-k1m；
Unit of averaging is used for more data group W7It is averaged Δ '；
Average value judging unit is used for the application traffic sensor of use site when detecting instantaneous flow, and what be will test is instantaneous
The instantaneous flow k of flow k and calibrational capacity sensor0It compares, and judges whether comparison result is equal to average value Δ '；
If compensating unit is not equal to average value Δ for comparison result ', software compensation is carried out to instantaneous flow k until comparing
As a result it is equal to average value Δ '.
5. the accuracy ensuring equipment of flow sensor as claimed in claim 4, which is characterized in that application traffic sensor
Coefficient calibration is gone to measure and be calibrated using the higher instrument of precision of ratio of precision application traffic sensor.
6. the accuracy ensuring equipment of flow sensor as claimed in claim 4, which is characterized in that the compensation uses software
Compensation.
7. a kind of terminal comprising memory, processor and be stored on the memory and can be in the processing
The computer program run on device, which is characterized in that the processor is realized as described in claim 1 when executing described program
The step of accuracy support method of flow sensor.
8. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that described program is by processor
When execution, the step of realizing the accuracy support method of flow sensor as described in claim 1.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150160326A1 (en) * | 2012-07-06 | 2015-06-11 | Giesecke & Devrient Gmbh | Calibration of a Magnetic Sensor |
| CN104807968A (en) * | 2015-05-11 | 2015-07-29 | 杭州北辰光电技术有限公司 | Gas sensor and identification and calibration method thereof |
| CN105547344A (en) * | 2015-12-08 | 2016-05-04 | 武昌船舶重工集团有限公司 | Test equipment calibration device and calibration method thereof |
| CN106501549A (en) * | 2016-10-19 | 2017-03-15 | 中航飞机股份有限公司西安飞机分公司 | A kind of measurement calibration steps of numerical control compressed air shotblasting machine flow velocity |
| CN107657083A (en) * | 2017-09-05 | 2018-02-02 | 天津市电力科技发展有限公司 | A kind of intellectual water meter is in Line synthesis error calibration method |
-
2018
- 2018-08-09 CN CN201810900624.7A patent/CN109117550A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150160326A1 (en) * | 2012-07-06 | 2015-06-11 | Giesecke & Devrient Gmbh | Calibration of a Magnetic Sensor |
| CN104807968A (en) * | 2015-05-11 | 2015-07-29 | 杭州北辰光电技术有限公司 | Gas sensor and identification and calibration method thereof |
| CN105547344A (en) * | 2015-12-08 | 2016-05-04 | 武昌船舶重工集团有限公司 | Test equipment calibration device and calibration method thereof |
| CN106501549A (en) * | 2016-10-19 | 2017-03-15 | 中航飞机股份有限公司西安飞机分公司 | A kind of measurement calibration steps of numerical control compressed air shotblasting machine flow velocity |
| CN107657083A (en) * | 2017-09-05 | 2018-02-02 | 天津市电力科技发展有限公司 | A kind of intellectual water meter is in Line synthesis error calibration method |
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Application publication date: 20190101 |