CN106706017A - Device stability test method and device stability test apparatus - Google Patents
Device stability test method and device stability test apparatus Download PDFInfo
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- CN106706017A CN106706017A CN201611113043.6A CN201611113043A CN106706017A CN 106706017 A CN106706017 A CN 106706017A CN 201611113043 A CN201611113043 A CN 201611113043A CN 106706017 A CN106706017 A CN 106706017A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D18/00—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
Abstract
The invention belongs to the technical field of industrial measurement and control, provides a device stability test method and a device stability test apparatus, and aims to solve the problem in the prior art that the standard is fuzzy between different parties and between different people, especially between manufacturers and customers, as there lacks a quantitative standard for data waveform judgment. Compared with the prior art in which the performance of devices (such as components and sensors) is judged subjectively in general and there lacks specific quantitative standards, in the technical scheme provided by the invention, for understanding of the performance of devices such as stability, indexes characterizing the data waveform similarity of devices are quantified using a mathematical formula. Therefore, the understanding of device performance is more objective. Different parties and between different people, especially between manufacturers and customers, are more likely to agree on the performance standards of devices.
Description
Technical field
The invention belongs to industrial measurement and control technical field, more particularly to a kind of device stability method of testing and device.
Background technology
In industrial measurement and control field, (for example heat endurance is surveyed for the performance test of device products (such as component, sensor)
Examination, sensitivity test, the similitude test of data waveform) it is particularly important for understanding the performance of device related fields.
Inventor has found part performance testing index, the similitude of such as data waveform, typically with master in existing technology
See and judge, lack specific quantitative criteria.
The content of the invention
A kind of device stability method of testing and device, it is intended to solve in the prior art to the judgement shortage amount of data waveform
Change standard, so as to cause not Tongfang, different people, the problem that especially standard is obscured between manufacturer and client.
The first aspect of the embodiment of the present invention, there is provided a kind of device stability method of testing, methods described includes：
Using Pearson correlation coefficient formulaSame device is calculated in first condition
And the value of the coefficient correlation between the data waveform exported under second condition, the r is the value of the coefficient correlation, the ∑ table
Show summation, the n be it is every kind of under the conditions of the total number of the data waveform that exports, the xiIt is i ＆ lt under the conditions of the first
The data waveform of output, the yiIt is the data waveform of i ＆ lt output under the conditions of second, it is describedIt is the xi
Expectation, it is describedIt is the yiExpectation, the eligible 1≤i of the i≤n；
If the value of the coefficient correlation belongs to the first preset threshold range, the stable performance of the device is judged.
The another aspect of the embodiment of the present invention, there is provided a kind of device stability test device, described device includes：
Coefficient correlation computing module, for using Pearson correlation coefficient formulaMeter
The value of the coefficient correlation between the data waveform that same device is exported under first condition and second condition is calculated, the r is described
The value of coefficient correlation, the ∑ represents summation, the n be it is every kind of under the conditions of the total number of the data waveform that exports, it is described
xiIt is the data waveform of i ＆ lt output under the conditions of the first, the yiIt is the number of i ＆ lt output under the conditions of second
It is described according to waveformIt is the xiExpectation, it is describedIt is the yiExpectation, the eligible 1≤i of the i≤n；
Determination module, if belonging to the first preset threshold range for the value of the coefficient correlation, judges the device
Stable performance.
The beneficial effect that exists compared with prior art of technical scheme that the present invention is provided is：A kind of device stability is provided
Method of testing, the data wave that same device is exported under first condition and second condition is calculated using Pearson correlation coefficient formula
The value of the coefficient correlation between shape；If the value of the coefficient correlation belongs to the first preset threshold range, the device is judged
Stable performance.Typically sentence with subjectivity relative to the understanding in the prior art to device (such as component, sensor) aspect of performance
It is disconnected, lack for specific quantitative criteria, the technical scheme that the present invention is provided uses number in aspect of performances such as understanding device stabilities
Learn formula to have quantified to characterize index of the device in terms of data waveform similitude, therefore more objectivity, make not Tongfang, difference
People, the especially performance standard between manufacturer and client to device are more easily achieved unanimously.
Brief description of the drawings
Technical scheme in order to illustrate more clearly the embodiments of the present invention, below will be to embodiment or description of the prior art
Needed for the accompanying drawing to be used be briefly described, it should be apparent that, drawings in the following description are only more of the invention
Embodiment, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these
Accompanying drawing obtains other accompanying drawings.
Fig. 1 is that the device stability method of testing that one embodiment of the invention is provided realizes flow chart；
Fig. 2-a show that the device of calculating first that one embodiment of the invention is provided is exported under first condition and second condition
Data waveform coefficient correlation schematic diagram；
Fig. 2-b show that the device of calculating second that one embodiment of the invention is provided is exported under first condition and second condition
Data waveform coefficient correlation schematic diagram；
Fig. 3-a show that the device of calculating first that one embodiment of the invention is provided is exported under first condition and second condition
Data waveform Fu Leixie distances schematic diagram；
As Fig. 3-b show that the device of calculating second that one embodiment of the invention is provided is defeated under first condition and second condition
The schematic diagram of the Fu Leixie distances of the data waveform for going out；
Fig. 4 is the device stability test device structural representation that another embodiment of the present invention is provided；
Fig. 5 is the device stability test device structural representation that another embodiment of the present invention is provided；
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.
In below describing, in order to illustrate rather than the explanation schematic diagram in order to limit, giving many technical characteristics, so as to
Cut thoroughly and understand the embodiment of the present invention.However, it will be clear to one skilled in the art that in other realities without these details
Apply and can also realize the present invention in example.In other situations, the detailed description to well-known device and method is omitted, with
Exempt from unnecessary details and hinder description of the invention.
Device can, including the various electronic components including sensor, be not limited thereto in the embodiment of the present invention.
In order to effectively solve to lack quantitative criteria to the judgement of data waveform in the prior art, so as to cause not Tongfang, no
Same people, the especially fuzzy problem of standard, device stability test side provided in an embodiment of the present invention between manufacturer and client
Method includes：Using Pearson correlation coefficient formulaSame device is calculated in first condition
And the value of the coefficient correlation between the data waveform exported under second condition, the r is the value of the coefficient correlation, the ∑ table
Show summation, the n be it is every kind of under the conditions of the total number of the data waveform that exports, the xiIt is i ＆ lt under the conditions of the first
The data waveform of output, the yiIt is the data waveform of i ＆ lt output under the conditions of second, it is describedIt is the xi
Expectation, it is describedIt is the yiExpectation, the eligible 1≤i of the i≤n；If it is pre- that the value of the coefficient correlation belongs to first
If threshold range, then the stable performance of the device is judged.It is described in detail individually below.
Fig. 1 shows that the device stability method of testing that one embodiment of the invention is provided realizes flow chart, its executive agent
Can be device stability test device, for example, the application program of device stability test device.For convenience of description, Fig. 1 is only
Part related to the present embodiment is shown, its process mainly includes step S101 and S102, and details are as follows：
S101, using Pearson correlation coefficient formulaSame device is calculated first
The value of the coefficient correlation between the data waveform exported under condition and second condition, r is the value of coefficient correlation, and ∑ represents summation, n
It is the total number of data waveform exported under the conditions of every kind of, xiIt is the data waveform of i ＆ lt output under the conditions of the first, yiIt is
The data waveform of i ＆ lt output under the conditions of two kinds,It is xiExpectation,It is yiExpectation, the eligible 1≤i of i≤n.
It should be noted that the formation condition of first condition and second condition for output waveform, the two be it is different, first
The difference of condition and second condition can be presented as temperature, humidity, in air pressure, vibration, supply voltage and supply frequency at least
One difference.
As Fig. 2-a show what the first device that one embodiment of the invention is provided was exported under first condition and second condition
The schematic diagram of data waveform, such as Fig. 2-b show the second device of one embodiment of the invention offer in first condition and Article 2
The schematic diagram of the data waveform exported under part, simply an x is exemplarily respectively given in Fig. 2-a and Fig. 2-biWith a yiIt is bent
Line, in fact, xiAnd yiEach expression is a suite line, and solid line represents x in Fig. 2-a and Fig. 2-biCertain curve in curve group,
Dotted line represents y in Fig. 2-a and Fig. 2-biCertain curve in curve group.What solid line was represented in Fig. 2-a is in the first condition
The output quantity of one device, what dotted line was represented is the output quantity of the first device under a second condition in Fig. 2-a.Solid line table in Fig. 2-b
What is shown is the output quantity of the second device in the first condition, and what dotted line was represented in Fig. 2-b is the second device under a second condition
Output quantity.
By calculating, the phase relation between the data waveform that the first device is exported under first condition and second condition
Several value r is 0.99848430, and the correlation between the data waveform that the second device is exported under first condition and second condition
The value r of coefficient is 0.99509519.
S102, if the value of coefficient correlation belongs to the first preset threshold range, the stable performance of decision device.
For example, the correlation coefficient r of the first device calculated in Fig. 2-a is the second device calculated in 0.99848430, Fig. 2-b
The correlation coefficient r of part is 0.99509519, and the two belongs to the first preset threshold range [0.98,1], illustrates the first device and the
The performance of two devices is stablized.
It should be noted that the value of coefficient correlation is used for judging the data waveform exported under first condition and second condition
Trend is moved towards, the value of coefficient correlation is bigger, then the data waveform for being exported under first condition and second condition is more similar, the property of device
Can be relatively more stable.
Knowable to the value r of the coefficient correlation calculated respectively from Fig. 2-a and Fig. 2-b, the coefficient correlation of the first device in Fig. 2-a
Value rs of the value r more than the coefficient correlation of the second device in Fig. 2-b, then for illustrating the first device with respect to the second device, data wave
Shape moves towards that trend is more consistent or more like, and performance is relatively more stable.
Optionally, if the value in coefficient correlation belongs to the first preset threshold range, judge that the performance of the device is steady
After fixed, device stability method of testing can also include：Step S103 and step S104.
S103, using computing formulaThe Fu Leixie distances between output data waveform are calculated,
Cm is the Fu Leixie distances, and ∑ represents summation, n' be it is every kind of under the conditions of output data waveform total number, x 'iIt is first
The data waveform of the i-th ' secondary output, y ' under the conditions of kindiIt is the data waveform of the i-th ' secondary output under the conditions of second, i' is eligible
1≤i'≤n'。
As Fig. 3-a show what the first device that one embodiment of the invention is provided was exported under first condition and second condition
The schematic diagram of data waveform, such as Fig. 3-b show the second device of one embodiment of the invention offer in first condition and Article 2
The schematic diagram of the data waveform exported under part, simply an x ' is exemplarily respectively given in Fig. 3-a and Fig. 3-biWith a y 'i
Curve, in fact, x 'iWith y 'iEach expression is a suite line, and solid line represents x ' in Fig. 3-a and Fig. 3-biCertain in curve group
Dotted line represents y ' in curve, Fig. 3-a and Fig. 3-biCertain curve in curve group.What solid line was represented in Fig. 3-a is at first
The output quantity of the first device under part, what dotted line was represented is the output quantity of the first device under a second condition in Fig. 3-a.In Fig. 3-b
What solid line was represented is the output quantity of the second device in the first condition, and what dotted line was represented in Fig. 3-b is under a second condition second
The output quantity of device.
By calculating, the Fu Leixie between the data waveform that the first device is exported under first condition and second condition
It is 129.646454348 apart from cm, and between the data waveform that the second device is exported under first condition and second condition not
It is 445.149827148 that thunder is had a rest apart from cm.
S104, Ruo Fuleixie distance belong to the second preset threshold range, then judge that the performance of the device is more stable.
For example, the Fu Leixie of the first device calculated in Fig. 3-a is calculating in 129.646454348, Fig. 3-b apart from cm
The Fu Leixie of the second device is 445.149827148 apart from cm, and the Fu Leixie of the first device and the second device is belonged to apart from cm
Second preset threshold range [0,450], illustrates that the first device and the performance of the second device are stablized.
It should be noted that Fu Leixie distances are used for judging between the data waveform exported under first condition and second condition
Difference, apart from smaller, then the data waveform for being exported under first condition and second condition is more similar, the performance phase of device for Fu Leixie
To more stable.
Knowable to the Fu Leixie calculated respectively from Fig. 3-a and Fig. 3-b is apart from cm, in Fig. 3-a the Fu Leixie of the first device away from
Fu Leixie distance cm from cm less than the second device in Fig. 3-b, then for illustrating the first device with respect to the second device, data waveform
Difference it is smaller (more like), performance is more stable.
It should be noted that n and n' are all higher than preset value in foregoing description.
The value of the coefficient correlation for whether being calculated in Fig. 2-a and Fig. 2-b, or the Fu Leixie calculated in Fig. 3-a and Fig. 3-b
Distance, the two is all based on mathematical statistics, and the premise of mathematical statistics is gathered data has to comply with large sample requirement, because
This, theoretically, n and n' are bigger, and value and the Fu Leixie distance of the coefficient correlation being calculated respectively are more accurate, can more reflect
The actual performance of device.
It should be noted that the data waveform of the first device and the second device is random output.In this way, be calculated
Value and the Fu Leixie distance of coefficient correlation are more objective, can more reflect the actual performance of device.
Device stability method of testing provided in an embodiment of the present invention, same device is calculated using Pearson correlation coefficient formula
The value of the coefficient correlation between the data waveform that part is exported under first condition and second condition；If the value category of the coefficient correlation
In the first preset threshold range, then the stable performance of the device is judged.Relative in the prior art to device (such as first device
Part, sensor) aspect of performance understanding it is general with subjective judgement, for lacking specific quantitative criteria, the technology that the present invention is provided
Scheme understand device stability aspect of performance quantified using mathematical formulae characterize device in terms of data waveform similitude
Index, more objectivity, make not Tongfang, different people, and especially the performance standard between manufacturer and client to device is easier
Reach an agreement.
Fig. 4 shows the device stability test device structural representation that another embodiment of the present invention is provided.For the ease of
Illustrate, Fig. 4 illustrate only the part related to the embodiment of the present invention.The device stability test device of Fig. 4 examples includes correlation
Coefficients calculation block 201 and determination module 202, wherein：
Coefficient correlation computing module 201, for using Pearson correlation coefficient formula
The value of the coefficient correlation between the data waveform that same device is exported under first condition and second condition is calculated, the r is institute
State the value of coefficient correlation, ∑ represents summation, n be it is every kind of under the conditions of the total number of data waveform that exports, xiIt is the first condition
The data waveform of lower i ＆ lt output, yiIt is the data waveform of i ＆ lt output under the conditions of second,It is xiExpectation,For
yiExpectation, the eligible 1≤i of i≤n.
It should be noted that the formation condition of first condition and second condition for output waveform, the two be it is different, first
The difference of condition and second condition can be presented as temperature, humidity, in air pressure, vibration, supply voltage and supply frequency at least
One difference.
The present embodiment is identical with partial content in the inventive method embodiment, therefore Fig. 2-a and figure in borrowing method embodiment
2-b is described.
The schematic diagram of the data waveform that the first device is exported under first condition and second condition is represented such as Fig. 2-a, is such as schemed
2-b represents the schematic diagram of the data waveform that the second device is exported under first condition and second condition, in Fig. 2-a and Fig. 2-b only
It is exemplarily respectively to give an xiWith a yiCurve, in fact, xiAnd yiEach expression is a suite line, Fig. 2-a and figure
Solid line represents x in 2-biDotted line represents y in certain curve in curve group, Fig. 2-a and Fig. 2-biCertain curve in curve group.
What solid line was represented is the output quantity of the first device in the first condition in Fig. 2-a, and what dotted line was represented in Fig. 2-a is in second condition
The output quantity of lower first device.What solid line was represented is the output quantity of the second device in the first condition in Fig. 2-b, empty in Fig. 2-b
What line was represented is the output quantity of the second device under a second condition.
Calculated by coefficient correlation computing module 201, what the first device was exported under first condition and second condition
The value r of the coefficient correlation between data waveform is 0.99848430, and the second device is exported under first condition and second condition
Data waveform between coefficient correlation value r be 0.99509519.
Determination module 202, if belonging to the first preset threshold range for the value of coefficient correlation, the performance of decision device is steady
It is fixed.
For example, the correlation coefficient r of the first device that coefficient correlation computing module 201 is calculated is 0.99848430 in Fig. 2-a,
The correlation coefficient r of the second device that coefficient correlation computing module 201 is calculated is 0.99509519 in Fig. 2-b, and the two belongs to the
One preset threshold range [0.98,1], determination module 202 judges that the first device and the performance of the second device are stablized.
It should be noted that the value of coefficient correlation is used for judging the data waveform exported under first condition and second condition
Trend is moved towards, the value of coefficient correlation is bigger, then the data waveform for being exported under first condition and second condition is more similar, the property of device
Can be relatively more stable.
From Fig. 2-a and Fig. 2-b knowable to the value r of the coefficient correlation that coefficient correlation computing module 201 is calculated respectively, Fig. 2-a
In the first device coefficient correlation value rs of the value r more than the coefficient correlation of the second device in Fig. 2-b, then determination module 202 judge
For first device is with respect to the second device, data waveform moves towards that trend is more consistent or more like, and performance is more stable.
It should be noted that n is more than preset value in foregoing description.
The value of the coefficient correlation that coefficient correlation computing module 201 is calculated based on mathematical statistics, and before mathematical statistics
It is that gathered data has to comply with large sample requirement to carry, therefore, theoretically, n is bigger, and coefficient correlation computing module 201 is calculated
The value of the coefficient correlation for obtaining is more accurate, can more reflect the actual performance of device.
It should be noted that the data waveform of the first device and the second device is random output.In this way, coefficient correlation meter
The value for calculating the coefficient correlation that module 201 is calculated is more objective, can more reflect the actual performance of device.
It should be noted that the device stability test device that provides of another embodiment of the present invention shown in figure 4 above
In implementation method, for convenience and simplicity of description, only carried out for example, in practical application with the division of above-mentioned each functional module
Can as needed, such as the convenient consideration of the realization of the configuration requirement or software of corresponding hardware, and above-mentioned functions are distributed
Completed by different functional module, will the internal structure of device stability test device be divided into different functional modules, with
Complete all or part of function described above.And, in practical application, corresponding functional module in the present embodiment can be with
It is to be realized by corresponding hardware, it is also possible to corresponding software is performed by corresponding hardware and is completed, for example, determination module, Ke Yishi
Hardware with decision-making function, for example, determinant, or be able to carry out corresponding computer program so as to complete decision-making function
General processor or other hardware devices, and the present embodiment in the corresponding function module can carry out respective change and be located at
In different from one or more embodiment devices of the present embodiment, may be alternatively located in same embodiment before difference in functionality module or
(refer to the annexation of functional module) afterwards.In addition, the specific name of each functional module also only to facilitate mutually distinguish, and
It is not used in the protection domain of limitation the application.(each embodiment that this specification is provided can all apply foregoing description principle).
Device stability test device shown in Fig. 4 can also include Fu Leixie distance calculation modules 301 and judge module
302, the device stability test device structural representation that another embodiment of the present invention is provided is shown in such as Fig. 5.Wherein：
Fu Leixie distance calculation modules 301, for using computing formulaCalculate the number of output
According to the Fu Leixie distances between waveform, cm is Fu Leixie distances, and ∑ represents summation, n' be it is every kind of under the conditions of output data waveform
Total number, x 'iIt is the data waveform of the i-th ' secondary output under the conditions of the first, y 'iIt is the number of the i-th ' secondary output under the conditions of second
According to waveform, the eligible 1≤i' of i'≤n'.
The present embodiment is identical with partial content in the inventive method embodiment, therefore Fig. 3-a and figure in borrowing method embodiment
3-b is described.
The schematic diagram of the data waveform that the first device is exported under first condition and second condition is represented such as Fig. 3-a, is such as schemed
3-b represents the schematic diagram of the data waveform that the second device is exported under first condition and second condition, in Fig. 3-a and Fig. 3-b only
It is exemplarily respectively to give an x 'iWith a y 'iCurve, in fact, x 'iWith y 'iEach expression is a suite line, Fig. 3-a
X ' is represented with solid line in Fig. 3-biDotted line represents y ' in certain curve in curve group, Fig. 3-a and Fig. 3-biCertain in curve group
Curve.What solid line was represented is the output quantity of the first device in the first condition in Fig. 3-a, and what dotted line was represented in Fig. 3-a is
The output quantity of the first device under the conditions of two.What solid line was represented is the output quantity of the second device in the first condition in Fig. 3-b, Fig. 3-
What dotted line was represented is the output quantity of the second device under a second condition in b.
Calculated by Fu Leixie distance calculation modules 301, the first device is exported under first condition and second condition
Data waveform between Fu Leixie be 129.646454348 apart from cm, and the second device is under first condition and second condition
Fu Leixie between the data waveform of output is 445.149827148 apart from cm.
Judge module 302, the second preset threshold range is belonged to for Ruo Fuleixie distances, then judge that the performance of device is more steady
It is fixed.
For example, the Fu Leixie of the first device that Fu Leixie distance calculation modules 301 are calculated is apart from cm in Fig. 3-a
The Fu Leixie of the second device that Fu Leixie distance calculation modules 301 are calculated is apart from cm in 129.646454348, Fig. 3-b
445.149827148, the Fu Leixie of the first device and the second device belongs to the second preset threshold range [0,450] apart from cm,
Illustrate that the first device and the performance of the second device are stablized.
It should be noted that Fu Leixie distances are used for judging the difference under first condition and second condition between output waveform
Different, apart from smaller, then the data waveform for being exported under first condition and second condition is more similar, and the performance of device is relative more for Fu Leixie
Stabilization.
Knowable to the Fu Leixie that Fu Leixie distance calculation modules 301 are calculated respectively from Fig. 3-a and Fig. 3-b is apart from cm, Fig. 3-a
In the first device Fu Leixies of the Fu Leixie apart from cm less than the second device in Fig. 3-b apart from cm, then judge module 302 judges the
For one device is with respect to the second device, the difference of data waveform is smaller (more like), and performance is more stable.
It should be noted that n' is more than preset value in foregoing description.
In Fig. 3-a and Fig. 3-b Fu Leixie distance calculation modules 301 calculate Fu Leixie distances based on mathematical statistics,
And the premise of mathematical statistics is gathered data has to comply with the requirement of large sample, therefore, theoretically, n' is bigger, Fu Leixie
The Fu Leixie distances that distance calculation module 301 is calculated are more accurate, can more reflect the actual performance of device.
It should be noted that the data waveform of the first device and the second device is random output.In this way, Fu Leixie distances
The Fu Leixie distances that computing module 301 is calculated are more objective, can more reflect the actual performance of device.
It should be noted that the content such as information exchange, implementation procedure in said apparatus embodiment between each module/unit
And embodiment entire content, due to being based on same design with the inventive method embodiment, technique effect and the present invention that it brings
Embodiment of the method is identical, and particular content can be found in the narration in the inventive method embodiment, and here is omitted.
It should be noted that it is related to the words such as " first ", " second " in all embodiments of the invention, such as the first device, first
Preset threshold range, is only herein the convenience stated and refer to, and is not meant in specific implementation of the invention certain
Have corresponding first device and the first preset threshold range.
Those of ordinary skill in the art are further appreciated that all or part of step realized in above-described embodiment method is can
Completed with instructing the hardware of correlation by program, described program can be stored in a computer read/write memory medium
In, described storage medium, including ROM/RAM, disk, CD etc..
Above content be combine specific preferred embodiment the principle of the invention and implementation method are made it is further in detail
Describe in detail bright, it is impossible to assert that specific implementation of the invention is confined to these explanations, be only intended to help and understand the method for the present invention
And its core concept；For simultaneously for general technical staff of the technical field of the invention, present inventive concept is not being departed from
On the premise of make some equivalent substitutes or obvious modification, and performance or purposes are identical, should all be considered as belonging to the present invention by
The scope of patent protection that the claims submitted to determine.
Claims (10)
1. a kind of device stability method of testing, it is characterised in that methods described includes：
Using Pearson correlation coefficient formulaSame device is calculated in first condition and
The value of the coefficient correlation between the data waveform exported under the conditions of two, the r is the value of the coefficient correlation, and the ∑ is represented to be asked
With, the n be it is every kind of under the conditions of the total number of the data waveform that exports, the xiIt is i ＆ lt output under the conditions of the first
The data waveform, the yiIt is the data waveform of i ＆ lt output under the conditions of second, it is describedIt is the xiPhase
Hope, it is describedIt is the yiExpectation, the eligible 1≤i of the i≤n；
If the value of the coefficient correlation belongs to the first preset threshold range, the stable performance of the device is judged.
2. the method for claim 1, it is characterised in that if the value in the coefficient correlation belongs to the first default threshold
Value scope, then judge after the stable performance of the device, methods described also includes：
Using computing formulaThe Fu Leixie distances between the data waveform of the output are calculated, it is described
Cm is the Fu Leixie distances, and the ∑ represents summation, the n' be it is every kind of under the conditions of export the data waveform it is total individual
Number, the x 'iIt is the data waveform of the i-th ' secondary output under the conditions of the first, the y 'iFor i-th ' is secondary defeated under the conditions of second
The data waveform for going out, the eligible 1≤i '≤n ' of i'；
If the Fu Leixie distances belong to the second preset threshold range, judge that the performance of the device is more stable.
3. method as claimed in claim 1 or 2, it is characterised in that the value of the coefficient correlation is used for judging described first
The data waveform exported under part and second condition moves towards trend, and the value of the coefficient correlation is bigger, then the first condition and
The data waveform exported under second condition is more similar, and the performance of the device is relatively more stable.
4. method as claimed in claim 2, it is characterised in that the Fu Leixie distances are used for judging the first condition and the
Difference between the data waveform exported under the conditions of two, the Fu Leixie apart from smaller, then the first condition and second condition
The data waveform of lower output is more similar, and the performance of the device is relatively more stable.
5. the method as described in claim 2 or 4, it is characterised in that the n and the n' are all higher than preset value.
6. a kind of device stability test device, it is characterised in that described device includes：
Coefficient correlation computing module, for using Pearson correlation coefficient formulaCalculate same
The value of the coefficient correlation between the data waveform that one device is exported under first condition and second condition, the r is the correlation
The value of coefficient, the ∑ represents summation, the n be it is every kind of under the conditions of the total number of the data waveform that exports, the xiFor
The data waveform of i ＆ lt output, the y under the conditions of the firstiIt is the data wave of i ＆ lt output under the conditions of second
Shape, it is describedIt is the xiExpectation, it is describedIt is the yiExpectation, the eligible 1≤i of the i≤n；
Determination module, if belonging to the first preset threshold range for the value of the coefficient correlation, judges the performance of the device
Stabilization.
7. device as claimed in claim 6, it is characterised in that described device also includes：
Fu Leixie distance calculation modules, for using computing formulaCalculate the data wave of the output
Fu Leixie distances between shape, the cm is the Fu Leixie distances, and the ∑ represents summation, the n' be it is every kind of under the conditions of it is defeated
The total number of the data waveform for going out, the x 'iIt is the data waveform of the i-th ' secondary output under the conditions of the first, the y 'i
It is the data waveform of the i-th ' secondary output under the conditions of second, the eligible 1≤i' of the i'≤n'；
Judge module, if belonging to the second preset threshold range for the Fu Leixie distances, judges the performance of the device more
Stabilization.
8. device as claimed in claims 6 or 7, it is characterised in that the value of the coefficient correlation is used for judging described first
The data waveform exported under part and second condition moves towards trend, and the value of the coefficient correlation is bigger, then the first condition and
The data waveform exported under second condition is more similar, and the performance of the device is relatively more stable.
9. device as claimed in claim 7, it is characterised in that the Fu Leixie distances are used for judging the first condition and the
Difference between the data waveform exported under the conditions of two, the Fu Leixie apart from smaller, then the first condition and second condition
The data waveform of lower output is more similar, and the performance of the device is relatively more stable.
10. the device as described in claim 7 or 9, it is characterised in that the n and the n' are all higher than preset value.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101770516A (en) * | 2010-01-12 | 2010-07-07 | 深圳先进技术研究院 | Method for excavating tropical cyclone motion track channel |
| US20100191790A1 (en) * | 2009-01-29 | 2010-07-29 | Agilent Technologies, Inc. | System and method for correlation scoring of signals |
| CN103196630A (en) * | 2013-03-13 | 2013-07-10 | 浙江省电力公司电力科学研究院 | Method and device of evaluating accuracy of ammonia escape monitoring value |
| CN103235350A (en) * | 2013-04-12 | 2013-08-07 | 中国海洋石油总公司 | Method and device for testing stability and graduating radioactivity logging instrument |
| CN104092481A (en) * | 2014-07-17 | 2014-10-08 | 江苏林洋电子股份有限公司 | Method for distinguishing power distribution area and phase through voltage characteristics |
-
2016
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100191790A1 (en) * | 2009-01-29 | 2010-07-29 | Agilent Technologies, Inc. | System and method for correlation scoring of signals |
| CN101770516A (en) * | 2010-01-12 | 2010-07-07 | 深圳先进技术研究院 | Method for excavating tropical cyclone motion track channel |
| CN103196630A (en) * | 2013-03-13 | 2013-07-10 | 浙江省电力公司电力科学研究院 | Method and device of evaluating accuracy of ammonia escape monitoring value |
| CN103235350A (en) * | 2013-04-12 | 2013-08-07 | 中国海洋石油总公司 | Method and device for testing stability and graduating radioactivity logging instrument |
| CN104092481A (en) * | 2014-07-17 | 2014-10-08 | 江苏林洋电子股份有限公司 | Method for distinguishing power distribution area and phase through voltage characteristics |
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