CN109553140A - The long-range control method of household water-purifying machine - Google Patents
The long-range control method of household water-purifying machine Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000012545 processing Methods 0.000 claims abstract description 8
- 238000001514 detection method Methods 0.000 claims abstract description 7
- 238000009790 rate-determining step (RDS) Methods 0.000 claims abstract description 7
- 239000007787 solid Substances 0.000 claims description 23
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 22
- 239000011159 matrix material Substances 0.000 claims description 16
- 238000010295 mobile communication Methods 0.000 claims description 12
- 230000001186 cumulative effect Effects 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 5
- 239000000284 extract Substances 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 239000012634 fragment Substances 0.000 claims description 3
- 238000005316 response function Methods 0.000 claims description 3
- 238000004088 simulation Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 230000007704 transition Effects 0.000 claims description 3
- 238000000746 purification Methods 0.000 claims 1
- 230000000717 retained effect Effects 0.000 claims 1
- 238000009434 installation Methods 0.000 description 4
- 238000000108 ultra-filtration Methods 0.000 description 3
- 238000001914 filtration Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 239000008399 tap water Substances 0.000 description 2
- 235000020679 tap water Nutrition 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 229920000742 Cotton Polymers 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000012528 membrane Substances 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
Classifications
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
- C02F1/001—Processes for the treatment of water whereby the filtration technique is of importance
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
- C02F1/44—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis
- C02F1/444—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis by ultrafiltration or microfiltration
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F9/00—Multistage treatment of water, waste water or sewage
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G06T5/70—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/751—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
- C02F1/28—Treatment of water, waste water, or sewage by sorption
- C02F1/283—Treatment of water, waste water, or sewage by sorption using coal, charred products, or inorganic mixtures containing them
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
Abstract
The method that image content matches and then consumer is helped to realize that household water-purifying machine remotely detects and controls self-servicely, including identification accessory step and long-range detection rate-determining steps are carried out convenient for automation the present invention provides a kind of.The present invention overcomes consumers in the prior art to lack the problem of professional knowledge can not judge failure accessory, and image data processing aspect has the advantages that discrimination is high, identification error rate is low, so that consumer voluntarily can judge failure according to the voltage of on-site test, electric current etc. (can be realized by the universal meter of low cost) and replace accessory.It is tested through 1000 times, number of success is 895 times；And it is small compared to other image-recognizing methods tools data volume in need, it is particularly suitable for situations such as consumer's uploading pictures quality is unintelligible, resolution is not high, size is small.
Description
Technical field
The invention belongs to water purifier detection technique fields, and in particular to a kind of long-range control method of household water-purifying machine.
Background technique
The style of household water-purifying machine is very more.As the frequency that water purifier updates is continuously improved, specialized maintenance
Expense is constantly soaring, some models are difficult to obtain the maintenance service of profession after purchase 3 years.For example, water purifier appearance is common
Failure includes: that 1, water purifier can be used normally, but be discharged the smaller and smaller of quantitative change.Such case consumer first has to observe
Whether whether family hydraulic pressure changes, if family hydraulic pressure becomes smaller, can be solved using booster pump is increased.If hydraulic pressure does not have any
Whether variation, the originally water quality that can observe water are deteriorated, and connect glass water and stand half an hour observation, if water quality variation please increase
Fore filter gives tap water one coarse filtration.If replacement water purifier filter core can be considered in water consumer out of question, it should
It is PP cotton filter element and active carbon filter core uses more than the time clogging, replacement filter core can solves.2, water purifier can
With normal use, but the water come out is more muddy.In this case the tap water that consumer looks first at into is matter
Quantitative change is far short of what is expected, if front filtration system please much be increased by being deteriorated, assuming that it has not, being that ultrafiltration water purifier can check ultrafiltration
Whether film ruptures, if rupture please be replaced.Can also check the sealing ring of ultrafiltration membrane it is whether intact have do not have modification, if having these
Situation please be reinstalled or be replaced.That is, consumer how efficiently oneself repair some failures just at
For a kind of urgent need in the market.
Through retrieving, disclosing one kind application No. is Chinese utility model patent CN201620273065.8 be can automatically detect
And the water purifier of reparation is reminded in time, and the shell including being equipped with independent first cavity and the second cavity, the interior installation of the first cavity
The outlet pipe of housing bottom, installation in the second cavity are stretched out in water tank, motor, electrical component and control device, the installation of water tank downside
One group of filter cylinder by placed in series is equipped with a filter core in each filter cylinder, and TDS probe is equipped in each pipeline, wherein
The filter cylinder of side connects water tank, the open-mouth connecting cover plate of the first cavity, on the cover board installation control control by another pipeline
Panel and prompting screen, control device are electrically connected control panel, screen and TDS are reminded to pop one's head in.However, this technology needs water purifier certainly
Body is provided with certain auxiliary device, does not meet the configuration of existing most water purifiers existing on the market, more inadaptable
Remote failure detection needs.
Summary of the invention
In view of the above analysis, the main purpose of the present invention is to provide one kind convenient for automation carry out image content match into
And the method for helping consumer to realize that household water-purifying machine remotely detects and controls self-servicely, including identification accessory step and long-range inspection
Survey rate-determining steps.
Further, the identification accessory step includes:
(1) accessory image data to be identified is acquired；
(2) image data is transferred to Cloud Server；
(3) picture recognition is carried out；
(4) information is fed back.
Further, the step (1) includes at least two that accessory to be identified is obtained using intelligent mobile communication equipment
Picture.
Further, collected picture is uploaded to cloud clothes including the use of intelligent mobile communication equipment by the step (2)
Business device.
Further, the step (3) includes that each picture received to Cloud Server carries out bulk processing, and characteristic value is asked
It takes, characteristic value compares.
Further, the intelligent mobile communication equipment includes smart phone.
Further, carrying out bulk processing to picture includes: to carry out light intensity average operation to picture, by the shared of each width picture
Picture region retains, and removes the picture fragment of picture the right and left；
Wherein, picture feature value seek include: one of picture that Cloud Server is received carry out compressing and converting, generate
Resolution is not less than the color image I of 128*128 Pixel Dimensions, and constructs solid color picture I ', solid color picture I '
The correspondence picture for being picture I under certain gray scale, the gray value g of solid color picture I ' is by color space linear expression are as follows:
G=αrIr+αgIg+αbIb
Wherein αr>=0, αg>=0, αb>=0, αr+αg+αb=1
α in formular, αg, αbFor undetermined parameter, Ir, Ig, IbIt is the color channel values of picture I；
Building such as minor function:
In formula, x, y are pixel, and l ' is the set of all pixels of picture I, gx, gyThe gray value of respectively x and y, δX, y
The x in colour model space, the euclidean metric of y pixel are converted into for picture I；
By pixel x, y and δX, yFollowing objective function is set:
Wherein, Δ gX, y=gx-gy, σ is scale factor and is preset value, gX, yIndicate the gray value at pixel (x, y)；
Parameter alpha when calculating target function E (g) is maximum valuer, αg, αb；
The extraction of characteristic value includes: to adopt to reduce influence of the light intensity to picture in each picture that Cloud Server receives
Influence with comparison extended function simulation light intensity to picture, extracts characteristic value using Harris's matrix, specifically comprises the following steps:
If the solid color figure obtained after gray scale of the GAUSS sliding average to above-mentioned solid color picture is handled
Piece meets following distribution G (x, y, σ), and it is as follows to construct L function:
L (x, y, σ, ρ)=ρ I ' (x, y) G (x, y, σ)
In formula, (x, y) indicates that the pixel of above-mentioned solid color picture, the gray value of each pixel are represented as it respectively
Quotient between gray value itself and the maximum modulus value max of E (g), ρ are scaling experience factor and are maximum equal to objective function E (g)
α when valuer, αg, αbQuadratic sum, I ' (x, y) be above-mentioned solid color picture light intensity；
Establish comparison extended function, it may be assumed that
Wherein, c is comparison center of extension and the center is one of the pixel that above-mentioned (x, y) is indicated, λ is preset comparison
Extend slope and is equal to ρ/max；The auto-correlation square of each pixel of above-mentioned solid color picture is calculated using Harris's matrix
Battle array:
Wherein x, y are pixel coordinate, and N is photo resolution, then compare and extend picture characteristic response function are as follows:
R (x, y, c)=detA (x, y, fc)-k (traceA (x, y, fc))2
Wherein, k is invariant, and det () function representation seeks the function of the value of the determinant of square matrix A, trace () letter
Number indicates to seek the function of the mark of matrix；
With (x, y) be variable, seek function R definite integral change between each leisure 0-255 of x and y during when value, and
By the value added up to obtain it is cumulative and, by the characteristic value Rt cumulative and as color image I；
Picture feature value relatively include: above-mentioned color image I is denoted as picture X ' to be compared, if reference picture X with to than
It is expressed as transition matrix H compared with the transformation relation between picture X ', the reference picture X is pre-stored in Cloud Server
The picture of each accessory of water purifier:
Wherein,
(x ', y ') is the point of reference picture, and (x, y) is point corresponding with above-mentioned point in image to be compared；
Euclidean distance between (x ', y ') and (x, y) two o'clock and Hamming distance are calculated from when the two are between
Information feedback is carried out when comparing difference less than preset threshold, otherwise by picture X ' to be compared replace with other not with reference picture X
The picture that compared, Cloud Server receives repeats the calculating of above-mentioned relatively difference, carries out information when if being less than preset threshold
Feedback；If all pictures that Cloud Server receives difference compared between reference picture X, which is not present, is less than default threshold
The case where value, then compared with reference picture X to be replaced with to each picture not received with Cloud Server picture and continue
The calculating of above-mentioned comparison difference, until the comparison difference is less than preset threshold.
Further, medium-long range detection rate-determining steps include: to be called from Cloud Server according to the accessory identified
Parametic fault Value Data library compatible with the accessory feeds back to intelligent mobile communication equipment reference.
The invention has the following beneficial effects:
The present invention overcomes consumers in the prior art to lack the problem of professional knowledge can not judge failure accessory, and picture
Have the advantages that discrimination is high, identification error rate is low in terms of data processing, so that consumer can voluntarily examine according to scene
Voltage, electric current of survey etc. (can be realized by the universal meter of low cost) judge failure and replace accessory.It is tested through 1000 times, at
Function number is 895 times；And it is small compared to other image-recognizing methods tools data volume in need, it is particularly suitable on consumer
Situations such as blit tablet quality is unintelligible, resolution is not high, size is small.
Detailed description of the invention
Attached drawing 1 is the flow chart of method of the invention.
Specific embodiment
As shown in Figure 1, preferred embodiment in accordance with the present invention, provides a kind of convenient for automation progress image content matching
And then consumer is helped to realize the method that household water-purifying machine remotely detects and controls self-servicely, including identification accessory step and long-range
Detect rate-determining steps.
Preferably, the identification accessory step includes:
(1) accessory image data to be identified is acquired；
(2) image data is transferred to Cloud Server；
(3) picture recognition is carried out；
(4) information is fed back.
Preferably, the step (1) includes at least two figures that accessory to be identified is obtained using intelligent mobile communication equipment
Piece.
Preferably, collected picture is uploaded to cloud service including the use of intelligent mobile communication equipment by the step (2)
Device.
Preferably, the step (3) includes that each picture received to Cloud Server carries out bulk processing, and characteristic value is asked
It takes, characteristic value compares.
Preferably, the intelligent mobile communication equipment includes smart phone.
Preferably, carrying out bulk processing to picture includes: to carry out light intensity average operation to picture, by the shared figure of each width picture
Panel region retains, and removes the picture fragment of picture the right and left；
Wherein, picture feature value seek include: one of picture that Cloud Server is received carry out compressing and converting, generate
Resolution is not less than the color image I of 128*128 Pixel Dimensions, and constructs solid color picture I ', solid color picture I '
The correspondence picture for being picture I under certain gray scale, the gray value g of solid color picture I ' is by color space linear expression are as follows:
G=αrIr+αgIg+αbIb
Wherein αr>=0, αg>=0, αb>=0, αr+αg+αb=1
α in formular, αg, αbFor undetermined parameter, Ir, Ig, IbIt is the color channel values of picture I；
Building such as minor function:
In formula, x, y are pixel, and l ' is the set of all pixels of picture I, gx, gyThe gray value of respectively x and y, δX, y
The x in colour model space, the euclidean metric of y pixel are converted into for picture I；
By pixel x, y and δX, yFollowing objective function is set:
Wherein, Δ gX, y=gx-gy, σ is scale factor and is preset value, gX, yIndicate the gray value at pixel (x, y)；
Parameter alpha when calculating target function E (g) is maximum valuer, αg, αb；
The extraction of characteristic value includes: to adopt to reduce influence of the light intensity to picture in each picture that Cloud Server receives
Influence with comparison extended function simulation light intensity to picture, extracts characteristic value using Harris's matrix, specifically comprises the following steps:
If the solid color figure obtained after gray scale of the GAUSS sliding average to above-mentioned solid color picture is handled
Piece meets following distribution G (x, y, σ), and it is as follows to construct L function:
L (x, y, σ, ρ)=ρ I ' (x, y) G (x, y, σ)
In formula, (x, y) indicates that the pixel of above-mentioned solid color picture, the gray value of each pixel are represented as it respectively
Quotient between gray value itself and the maximum modulus value max of E (g), ρ are scaling experience factor and are maximum equal to objective function E (g)
α when valuer, αg, αbQuadratic sum, I ' (x, y) be above-mentioned solid color picture light intensity；
Establish comparison extended function, it may be assumed that
Wherein, c is comparison center of extension and the center is one of the pixel that above-mentioned (x, y) is indicated, λ is preset comparison
Extend slope and is equal to ρ/max；The auto-correlation square of each pixel of above-mentioned solid color picture is calculated using Harris's matrix
Battle array:
Wherein x, y are pixel coordinate, and N is photo resolution, then compare and extend picture characteristic response function are as follows:
R (x, y, c)=detA (x, y, fc)-k (traceA (x, y, fc))2
Wherein, k is invariant, and det () function representation seeks the function of the value of the determinant of square matrix A, trace () letter
Number indicates to seek the function of the mark of matrix；
With (x, y) be variable, seek function R definite integral change between each leisure 0-255 of x and y during when value, and
By the value added up to obtain it is cumulative and, by the characteristic value Rt cumulative and as color image I；
Picture feature value relatively include: above-mentioned color image I is denoted as picture X ' to be compared, if reference picture X with to than
It is expressed as transition matrix H compared with the transformation relation between picture X ', the reference picture X is pre-stored in Cloud Server
The picture of each accessory of water purifier:
Wherein,
(x ', y ') is the point of reference picture, and (x, y) is point corresponding with above-mentioned point in image to be compared；
Euclidean distance between (x ', y ') and (x, y) two o'clock and Hamming distance are calculated from when the two are between
Information feedback is carried out when comparing difference less than preset threshold, otherwise by picture X ' to be compared replace with other not with reference picture X
The picture that compared, Cloud Server receives repeats the calculating of above-mentioned relatively difference, carries out information when if being less than preset threshold
Feedback；If all pictures that Cloud Server receives difference compared between reference picture X, which is not present, is less than default threshold
The case where value, then compared with reference picture X to be replaced with to each picture not received with Cloud Server picture and continue
The calculating of above-mentioned comparison difference, until the comparison difference is less than preset threshold.
Preferably, medium-long range detection rate-determining steps include: is called from Cloud Server according to the accessory that identifies and
The accessory compatible parametic fault Value Data library feeds back to intelligent mobile communication equipment reference.
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 long-range control method of household water-purifying machine, including identification accessory step and long-range detection rate-determining steps.
2. the method according to claim 1, wherein the accessory identification step includes:
(1) accessory image data to be identified is acquired；
(2) image data is transferred to Cloud Server；
(3) picture recognition is carried out；
(4) information is fed back.
3. according to the method described in claim 2, it is characterized in that, the step (1) includes using intelligent mobile communication equipment
Obtain at least two pictures of accessory to be identified.
4. according to the method described in claim 3, it is characterized in that, the step (2) is including the use of intelligent mobile communication equipment
Collected picture is uploaded into Cloud Server.
5. according to the method described in claim 4, it is characterized in that, the step (3) include Cloud Server is received it is each
Picture carries out bulk processing, and the seeking of characteristic value, characteristic value compares.
6. according to the method described in claim 2, it is characterized in that, the intelligent mobile communication equipment includes smart phone.
7. according to the method described in claim 5, it is characterized in that, carrying out bulk processing to picture includes: to carry out light intensity to picture
The shared picture region of each width picture is retained, removes the picture fragment of picture the right and left by average operation；
Wherein, picture feature value seek include: one of picture that Cloud Server is received carry out compressing and converting, generate parsing
Degree is not less than the color image I of 128*128 Pixel Dimensions, and constructs solid color picture I ', which is figure
Correspondence picture of the piece I under certain gray scale, the gray value g of solid color picture I ' is by color space linear expression are as follows:
G=αrIr+αgIg+αbIb
Wherein αr>=0, αg>=0, αb>=0, αr+αg+αb=1
α in formular, αg, αbFor undetermined parameter, Ir, Ig, IbIt is the color channel values of picture I；
Building such as minor function:
In formula, x, y are pixel, and l ' is the set of all pixels of picture I, gx, gyThe gray value of respectively x and y, δX, yFor figure
Piece I is converted into the x in colour model space, the euclidean metric of y pixel；
By pixel x, y and δX, yFollowing objective function is set:
Wherein, Δ gX, y=gx-gy, σ is scale factor and is preset value, gX, yIndicate the gray value at pixel (x, y)；
Parameter alpha when calculating target function E (g) is maximum valuer, αg, αb；
The extraction of characteristic value include: in order to reduce influence of the light intensity to picture in each picture that Cloud Server receives, using pair
Influence than extended function simulation light intensity to picture, extracts characteristic value using Harris's matrix, specifically comprises the following steps:
If the solid color picture obtained after gray scale of the GAUSS sliding average to above-mentioned solid color picture is handled is full
Following distribution G (x, y, σ) of foot, and it is as follows to construct L function:
L (x, y, σ, ρ)=ρ I (x, y) G (x, y, σ)
In formula, (x, y) indicates that the pixel of above-mentioned solid color picture, the gray value of each pixel are represented as its respectively gray scale
Quotient of the value itself between the maximum modulus value max of E (g), when ρ is scaling experience factor and is maximum value equal to objective function E (g)
αr, αg, αbQuadratic sum, I ' (x, y) be above-mentioned solid color picture light intensity；
Establish comparison extended function, it may be assumed that
Wherein, c is comparison center of extension and the center is one of the pixel that above-mentioned (x, y) is indicated, λ is preset comparison extension
Slope and be equal to ρ/max；The autocorrelation matrix of each pixel of above-mentioned solid color picture is calculated using Harris's matrix:
Wherein x, y are pixel coordinate, and N is photo resolution, then compare and extend picture characteristic response function are as follows:
R (x, y, c)=detA (x, y, fc)-k (traceA (x, y, fc))2
Wherein, k is invariant, and det () function representation seeks the function of the value of the determinant of square matrix A, trace () function table
Show the function for seeking the mark of matrix；
With (x, y) for variable, seek function R definite integral change between each leisure 0-255 of x and y during when value, and should
Value added up to obtain it is cumulative and, by the characteristic value Rt cumulative and as color image I；
Picture feature value relatively includes: that above-mentioned color image I is denoted as picture X ' to be compared, if reference picture X and figure to be compared
Transformation relation between piece X ' is expressed as transition matrix H, and the reference picture X is pre-stored water purification in Cloud Server
The picture of each accessory of machine:
Wherein,
(x ', y ') is the point of reference picture, and (x, y) is point corresponding with above-mentioned point in image to be compared；
Euclidean distance between (x ', y ') and (x, y) two o'clock and Hamming distance are calculated from when the two comparisons between
Difference carries out information feedback when being less than preset threshold, and picture X ' to be compared is otherwise replaced with other not compared with reference picture X
The picture that cross, Cloud Server receives repeats the calculating of above-mentioned relatively difference, carries out information feedback when if being less than preset threshold；
If the feelings less than preset threshold are not present in all pictures that Cloud Server receives difference compared between reference picture X
Condition, then compared with reference picture X to be replaced with to each picture not received with Cloud Server picture and continue above-mentioned ratio
Compared with the calculating of difference, until the comparison difference is less than preset threshold.
8. according to the method described in claim 7, its medium-long range detection rate-determining steps include: according to the accessory that identifies from cloud
Parametic fault Value Data library compatible with the accessory is called in server, feeds back to intelligent mobile communication equipment reference.
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