CN105703777B - A kind of method and apparatus for compressing refrigerator reported data - Google Patents
A kind of method and apparatus for compressing refrigerator reported data Download PDFInfo
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- CN105703777B CN105703777B CN201610074990.2A CN201610074990A CN105703777B CN 105703777 B CN105703777 B CN 105703777B CN 201610074990 A CN201610074990 A CN 201610074990A CN 105703777 B CN105703777 B CN 105703777B
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
- H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
Abstract
The present invention relates to a kind of method and apparatus for compressing refrigerator reported data, comprising: obtains original message data；B-tree data library is constructed according to the original message data；When receive report message data when, report message data to classify for described；The data item of each classification reported in message data is searched from the b-tree data library with the presence or absence of corresponding compressed value；If it is present the data item reported in message data is replaced with the corresponding compressed value；The corresponding compressed value is constituted to the message data of compression.The present invention will report the data item in message data to replace with corresponding compressed value by searching the corresponding compressed value of data item of each classification reported in message data from b-tree data library, to complete the compression of data, save memory space.
Description
Technical field
The present invention relates to refrigerator arts, more particularly to a kind of method and apparatus for compressing refrigerator reported data.
Background technique
Currently, the reported data for refrigerator directly stores, any compression processing is not done, can be generated so huge
Data volume carrys out huge pressure for storage tape.If only compressed to the wherein data in reported data, caused by press
Contracting space is little, and general compression does not exceed 20%, also can carry out immense pressure as a result, for storage tape.
Summary of the invention
The present invention provides a kind of method and apparatus for compressing refrigerator reported data, to solve mass data that refrigerator reports
Storage problem.
The technical scheme to solve the above technical problems is that a kind of method for compressing refrigerator reported data, comprising:
Obtain original message data；
B-tree data library is constructed according to the original message data；
When receive report message data when, report message data to classify for described；
The data item of each classification reported in message data is searched from the b-tree data library with the presence or absence of correspondence
Compressed value；
If it is present the data item reported in message data is replaced with the corresponding compressed value；
The corresponding compressed value is constituted to the message data of compression.
The beneficial effects of the present invention are: by searching the reporting in message data of each classification from b-tree data library
The corresponding compressed value of data item, and the data item in message data will be reported to replace with corresponding compressed value, to complete data
Compression, save memory space.
Based on the above technical solution, the present invention can also be improved as follows.
Further, described to include: according to original message data building b-tree data library
The original message data is classified to obtain multiple classification data；
Obtain historical baseline data；
According to the probability of occurrence of each data item in each classification data of historical baseline data statistics；
The probability of occurrence is arranged according to sequence from big to small；
Compressed value is successively assigned to the probability of occurrence arranged by descending order with the sequence of 16 incrementals；
According to each data item and compressed value generation binary tree structure in each classification data；
The binary tree structure is stored in the b-tree data library.
Beneficial effect using above-mentioned further scheme is: occurring generally by the way that original message data is classified, is counted
Rate and imparting compressed value, to constitute b-tree data library, b-tree data library can store all original message datas pair
The compressed value answered, in order to search corresponding compressed value from b-tree data library, and carry out when in the presence of message data is reported
Replacement.
Further, the original message data includes that switching load data, actual temperature data, reserved data, state are negative
Carry data, operational mode data, setting temperature data and internal data, wherein the actual temperature data includes multiple reality
Temperature data item, the setting temperature data include multiple setting temperature data items.
Beneficial effect using above-mentioned further scheme is: original message data includes various data, can learn refrigerator
In original message data all include which type, and message data is conveniently reported to search from the original message data of classification
Corresponding compressed value.
Further, it is described classified the original message data to obtain multiple classification data include:
The multiple actual temperature data item is classified to obtain multiple actual temperature classification data；
The multiple setting temperature data item is classified to obtain multiple setting temperature classifications data；
The switching load data, the multiple actual temperature classification data, the reserved data, the state load number
According to, the operational mode data, the setting temperature classifications data and internal data constitute the multiple classification data.
Beneficial effect using above-mentioned further scheme is:, can by the way that the data in original message data are classified
So as to which message data is reported more easily to find corresponding compressed value from b-tree data library.
Further, each data item according in each classification data and the compressed value generate binary tree
Structure includes:
Calculate in each classification data the probability of preceding n item data item and, wherein n is positive integer；
If the probability of the preceding n item data item and be not less than preset probability threshold value, and n be not more than preset data
The preceding n item data item and the preceding n corresponding compressed values are then generated the binary tree structure by item threshold value；
Alternatively,
If the probability of the preceding n item data item and be less than the preset probability threshold value, and n be equal to it is described preset
Whole n item data items and the corresponding compressed value of whole n item data item are then generated the binary tree by data item threshold value
Shape structure.
Beneficial effect using above-mentioned further scheme is: passing through the probability and and data item to preceding n item data item
The judgement of item number constitutes binary tree structure, also, preceding n item data item corresponds to the minor matters point of binary tree, and compressed value corresponds to y-bend
The leaf node of tree, to more clearly show binary tree structure.
The technical scheme to solve the above technical problems is that a kind of device for compressing refrigerator reported data, comprising:
Original message data acquiring unit, for obtaining original message data；
B-tree data library construction unit, for constructing b-tree data library according to the original message data；
Taxon, for receive report message data in the case where, report message data to classify for described；
Searching unit, for searching the data item of each classification reported in message data from the b-tree data library
With the presence or absence of corresponding compressed value；
Replacement unit is used in the presence of the corresponding compressed value, by the data item reported in message
Replace with the corresponding compressed value；
Compressed packet data composing unit, for the corresponding compressed value to be constituted to the message data of compression.
The beneficial effects of the present invention are: that searches each classification from b-tree data library by searching for unit reports message
The corresponding compressed value of data item in data, and that the data item in message data will be reported to replace with is corresponding by replacement unit
Compressed value saves memory space to complete the compression of data.
Based on the above technical solution, the present invention can also be improved as follows.
Further, b-tree data library construction unit includes:
Original message data taxon is classified the original message data to obtain multiple classification data；
Historical baseline data capture unit, for obtaining historical baseline data；
Statistic unit, it is general for the appearance according to each data item in each classification data of historical baseline data statistics
Rate；
Sequencing unit, for arranging the probability of occurrence according to sequence from big to small；
Given unit, for successively being assigned to the probability of occurrence arranged by descending order with the sequence of 16 incrementals
Compressed value；
Generation unit, according to each data item and compressed value generation binary tree knot in each classification data
Structure；
Storage unit, for the binary tree structure to be stored in the b-tree data library.
Beneficial effect using above-mentioned further scheme is: occurring generally by the way that original message data is classified, is counted
Rate and imparting compressed value, to constitute b-tree data library, b-tree data library can store all original message datas pair
The compressed value answered, in order to search corresponding compressed value from b-tree data library, and carry out when in the presence of message data is reported
Replacement.
Further, the original message data includes that switching load data, actual temperature data, reserved data, state are negative
Carry data, operational mode data, setting temperature data and internal data, wherein the actual temperature data includes multiple reality
Temperature data item, the setting temperature data include multiple setting temperature data items.
Beneficial effect using above-mentioned further scheme is: original message data includes various data, can learn refrigerator
In original message data all include which type, and message data is conveniently reported to search from the original message data of classification
Corresponding compressed value.
Further, the original message data taxon includes:
Actual temperature data item taxon, for being classified the multiple actual temperature data item to obtain multiple realities
Border temperature classifications data；
Temperature data item taxon is set, for being classified the multiple setting temperature data item to obtain multiple set
Set temperature classifications data；
Multiple classification data Component units are used for the switching load data, the multiple actual temperature classification data, institute
State reserved data, the state load data, the operational mode data, the setting temperature classifications data and internal data structure
At the multiple classification data.
Beneficial effect using above-mentioned further scheme is:, can by the way that the data in original message data are classified
So as to which message data is reported more easily to find corresponding compressed value from b-tree data library.
Further, the generation unit includes:
Calculate in each classification data the probability of preceding n item data item and, wherein n is positive integer；
If the probability of the preceding n item data item and be not less than preset probability threshold value, and n be not more than preset data
The preceding n item data item and the preceding n corresponding compressed values are then generated the binary tree structure by item threshold value；
Alternatively,
If the probability of the preceding n item data item and be less than the preset probability threshold value, and n be equal to it is described preset
Whole n item data items and the corresponding compressed value of whole n item data item are then generated the binary tree by data item threshold value
Shape structure.
Beneficial effect using above-mentioned further scheme is: passing through the probability and and data item to preceding n item data item
The judgement of item number constitutes binary tree structure, also, preceding n item data item corresponds to the minor matters point of binary tree, and compressed value corresponds to y-bend
The leaf node of tree, to more clearly show binary tree structure.
Detailed description of the invention
Fig. 1 is a kind of method flow diagram for compressing refrigerator reported data provided in an embodiment of the present invention；
Fig. 2 is switching load data item probability of occurrence distribution schematic diagram provided in an embodiment of the present invention；
Fig. 3 is environment temperature probability of occurrence distribution schematic diagram provided in an embodiment of the present invention；
Fig. 4 is original message data provided in an embodiment of the present invention classification schematic diagram；
Fig. 5 is switching load data item binary tree structural schematic diagram provided in an embodiment of the present invention；
Fig. 6 is a kind of schematic device for compressing refrigerator reported data provided in an embodiment of the present invention.
In attached drawing, parts list represented by the reference numerals are as follows:
10, original message data acquiring unit, 20, b-tree data library construction unit, 30, taxon, 40, lookup list
Member, 50, replacement unit, 60, compressed packet data composing unit.
Specific embodiment
The principle and features of the present invention will be described below with reference to the accompanying drawings, and the given examples are served only to explain the present invention, and
It is non-to be used to limit the scope of the invention.
Fig. 1 is a kind of method flow diagram for compressing refrigerator reported data provided in an embodiment of the present invention.
Referring to Fig.1, step S101 obtains original message data.
Step S102 constructs b-tree data library according to the original message data.
Step S103, when receive report message data when, report message data to classify for described.
Step S104, searched from the b-tree data library each classification the data item reported in message data whether
There are corresponding compressed values, if it is present executing step S105；If it does not exist, then executing step S106.
Here, binary tree structure is stored in b-tree data library, wherein corresponding data item is binary tree structure
Minor matters point, it is the leaf node of binary tree structure that compressed value is corresponding.When searching each classification from b-tree data library
When reporting the corresponding compressed value of the data item in message data, the data item pair of each classification reported in message data is first searched
The minor matters point answered, then the corresponding leaf node of minor matters point is obtained, to obtain the corresponding compressed value of leaf node.
The data item reported in message data is replaced with the corresponding compressed value by step S105.
Step S106 retains the data item reported in message data.
The corresponding compressed value is constituted the message data of compression by step S107.
In one embodiment of the invention, described to include: according to original message data building b-tree data library
The original message data is classified to obtain multiple classification data；
Obtain historical baseline data；
According to the probability of occurrence of each data item in each classification data of historical baseline data statistics；
The probability of occurrence is arranged according to sequence from big to small；
Compressed value is successively assigned to the probability of occurrence arranged by descending order with the sequence of 16 incrementals；
According to each data item and compressed value generation binary tree structure in each classification data；
The binary tree structure is stored in the b-tree data library.
Here, original message data is classified to obtain switching load data, and each in statistic switch load data
The probability of occurrence of data item arranges the probability of occurrence of data item each in switching load data according to sequence from big to small,
It is specific as shown in table 1:
Table 1
Specifically, the probability of occurrence of each data item can be as shown in Fig. 2, work as switching load data in switching load data
In data item be 01,01,03,10,00 when, probability of occurrence 33%；When the data item in switching load data be 01,01,
When 13,00,00, probability of occurrence 4%.Pass through the probability of occurrence of each data item in the available switching load data of Fig. 2.
Original message data is subjected to available ambient temperature data of classifying, each data item in ambient temperature data
Probability of occurrence as shown in figure 3, when the data item in ambient temperature data be 18.5 degree when, probability of occurrence 0.5%；Work as environment
When data item in temperature data is 19 degree, probability of occurrence 0.7%.By each in the available ambient temperature data of Fig. 3
The probability of occurrence of data item, probability of occurrence are in normal distribution, and 95% or more data item all concentrates in certain region.
In one embodiment of the invention, the original message data include switching load data, actual temperature data,
Reserved data, state load data, operational mode data, setting temperature data and internal data, wherein the actual temperature number
According to including multiple actual temperature data items, the setting temperature data includes multiple setting temperature data items.
In one embodiment of the invention, described to be classified the original message data to obtain multiple classification data
Include:
The multiple actual temperature data item is classified to obtain multiple actual temperature classification data；
The multiple setting temperature data item is classified to obtain multiple setting temperature classifications data；
The switching load data, the multiple actual temperature classification data, the reserved data, the state load number
According to, the operational mode data, the setting temperature classifications data and internal data constitute the multiple classification data.
Specifically, original message data includes switching load data, actual temperature data, reserved data, state load number
According to, operational mode data, setting temperature data and internal data, wherein the actual temperature data includes multiple actual temperatures
Data item can be such as, but not limited to, be specially 17 actual temperature data items, setting temperature data includes multiple settings
Temperature data item, can be such as, but not limited to, is specially 10 setting temperature data items, specifically can refer to as shown in Figure 4
Original message data classification schematic diagram, as shown in figure 4,17 actual temperature data items are classified to obtain 17 actual temperatures
Classification data is equivalent to the secondary classification to actual temperature data item；10 setting temperature data items are classified to obtain 10
A setting temperature classifications data are equivalent to the secondary classification to setting temperature data item, to constitute 32 classification data.
In one embodiment of the invention, each data item and the pressure according in each classification data
Contracting value generates binary tree structure
Calculate in each classification data the probability of preceding n item data item and, wherein n is positive integer；
If the probability of the preceding n item data item and be not less than preset probability threshold value, and n be not more than preset data
The preceding n item data item and the preceding n corresponding compressed values are then generated the binary tree structure by item threshold value；
Alternatively,
If the probability of the preceding n item data item and be less than the preset probability threshold value, and n be equal to it is described preset
Whole n item data items and the corresponding compressed value of whole n item data item are then generated the binary tree by data item threshold value
Shape structure.
Here, by taking switching load data item as an example, by table 1 it is found that the probability of switching load data item and being
95.64%, wherein n 12.Probability and it is greater than 95%, and n is less than 16, then 12 item data items is directly generated binary tree
Structure specifically can refer to switching load data binary tree structural schematic diagram as shown in Figure 5, be in switching load data item
When 01,01,03,10,00,00,00, c0,00,00, probability of occurrence 35.8443%, compressed value 0.Switching load data item
Corresponding is the minor matters point of binary tree structure, and it is the leaf node of binary tree structure that compressed value is corresponding.
If n is 16,16 item data items are then directly generated binary tree structure by probability and less than 95%.
A kind of method for compressing refrigerator reported data provided in an embodiment of the present invention, constructs y-bend by original message data
Database is set, if finding the corresponding compression of data item of each classification reported in message data from b-tree data library
Value, then will report the data item in message data to replace with corresponding compressed value, and constitute the message data of compression, to save
Memory space.
Fig. 6 is a kind of schematic device for compressing refrigerator reported data provided in an embodiment of the present invention.
Referring to Fig. 6, the device of compression refrigerator reported data includes original message data acquiring unit 10, b-tree data library
Construction unit 20, taxon 30, searching unit 40, replacement unit 50 and compressed packet data composing unit 60.
Original message data acquiring unit 10, for obtaining original message data.
B-tree data library construction unit 20, for constructing b-tree data library according to the original message data.
Taxon 30, for receive report message data in the case where, report message data to be divided for described
Class.
Searching unit 40, for searching the data of each classification reported in message data from the b-tree data library
Item whether there is corresponding compressed value.
Replacement unit 50 is used in the presence of the corresponding compressed value, by the data reported in message
Item replaces with the corresponding compressed value.
Compressed packet data composing unit 60, for the corresponding compressed value to be constituted to the message data of compression.
In one embodiment of the invention, b-tree data library construction unit 20 includes:
21 (not shown) of original message data taxon is classified the original message data to obtain multiple classification
Data；
22 (not shown) of historical baseline data capture unit, for obtaining historical baseline data；
23 (not shown) of statistic unit, for according to each data in each classification data of historical baseline data statistics
The probability of occurrence of item；
24 (not shown) of sequencing unit, for arranging the probability of occurrence according to sequence from big to small；
25 (not shown) of given unit, for by descending order arrangement probability of occurrence with the suitable of 16 incrementals
Sequence successively assigns compressed value；
26 (not shown) of generation unit, according to each data item and compressed value generation in each classification data
Binary tree structure；
27 (not shown) of storage unit, for the binary tree structure to be stored in the b-tree data library.
In one embodiment of the invention, the original message data include switching load data, actual temperature data,
Reserved data, state load data, operational mode data, setting temperature data and internal data, wherein the actual temperature number
According to including multiple actual temperature data items, the setting temperature data includes multiple setting temperature data items.
In one embodiment of the invention, the original message data taxon 21 includes:
211 (not shown) of actual temperature data item taxon, for being divided the multiple actual temperature data item
Class obtains multiple actual temperature classification data；
212 (not shown) of temperature data item taxon is set, for being divided the multiple setting temperature data item
Class obtains multiple setting temperature classifications data；
Multiple 213 (not shown) of classification data Component units are used for the switching load data, the multiple actual temperature
Classification data, the reserved data, the state load data, the operational mode data, the setting temperature classifications data
The multiple classification data is constituted with internal data.
In one embodiment of the invention, the generation unit 26 includes:
Calculate in each classification data the probability of preceding n item data item and, wherein n is positive integer；
If the probability of the preceding n item data item and be not less than preset probability threshold value, and n be not more than preset data
The preceding n item data item and the preceding n corresponding compressed values are then generated the binary tree structure by item threshold value；
Alternatively,
If the probability of the preceding n item data item and be less than the preset probability threshold value, and n be equal to it is described preset
Whole n item data items and the corresponding compressed value of whole n item data item are then generated the binary tree by data item threshold value
Shape structure.
A kind of device compressing refrigerator reported data provided in an embodiment of the present invention, constructs y-bend by original message data
Database is set, if finding the corresponding compression of data item of each classification reported in message data from b-tree data library
Value, then will report the data item in message data to replace with corresponding compressed value, and constitute the message data of compression, to save
Memory space.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (8)
1. a kind of method for compressing refrigerator reported data characterized by comprising
Obtain original message data；
B-tree data library is constructed according to the original message data；
When receive report message data when, report message data to classify for described；
The data item of each classification reported in message data is searched from the b-tree data library with the presence or absence of corresponding pressure
Contracting value；
If it is present the data item reported in message data is replaced with the corresponding compressed value；
The corresponding compressed value is constituted to the message data of compression, wherein described according to original message data building two
Fork sets database
The original message data is classified to obtain multiple classification data；
Obtain historical baseline data；
According to the probability of occurrence of each data item in each classification data of historical baseline data statistics；
The probability of occurrence is arranged according to sequence from big to small；
Compressed value is successively assigned to the probability of occurrence arranged by descending order with the sequence of 16 incrementals；
According to each data item and compressed value generation binary tree structure in each classification data；
The binary tree structure is stored in the b-tree data library.
2. a kind of method for compressing refrigerator reported data according to claim 1, which is characterized in that the original message number
According to including switching load data, actual temperature data, reserved data, state load data, operational mode data, setting temperature number
According to and internal data, wherein the actual temperature data includes multiple actual temperature data items, and the setting temperature data includes
Multiple setting temperature data items.
3. it is according to claim 2 it is a kind of compress refrigerator reported data method, which is characterized in that it is described will be described original
Message data is classified to obtain multiple classification data
The multiple actual temperature data item is classified to obtain multiple actual temperature classification data；
The multiple setting temperature data item is classified to obtain multiple setting temperature classifications data；
The switching load data, the multiple actual temperature classification data, the reserved data, the state load data,
The operational mode data, the setting temperature classifications data and internal data constitute the multiple classification data.
4. a kind of method for compressing refrigerator reported data according to claim 1, which is characterized in that described according to described each
Each data item and the compressed value in a classification data generate binary tree structure
Calculate in each classification data the probability of preceding n item data item and, wherein n is positive integer；
If the probability of the preceding n item data item and be not less than preset probability threshold value, and n be not more than preset data item threshold
The preceding n item data item and the preceding n corresponding compressed values are then generated the binary tree structure by value；
Alternatively,
If the probability of the preceding n item data item and be less than the preset probability threshold value, and n be equal to the preset data
Whole n item data items and the corresponding compressed value of whole n item data item are then generated the binary tree knot by item threshold value
Structure.
5. a kind of device for compressing refrigerator reported data characterized by comprising
Original message data acquiring unit, for obtaining original message data；
B-tree data library construction unit, for constructing b-tree data library according to the original message data；
Taxon, for receive report message data in the case where, report message data to classify for described；
Searching unit, for searched from the b-tree data library each classification the data item reported in message data whether
There are corresponding compressed values；
Replacement unit, in the presence of the corresponding compressed value, the data item reported in message to be replaced
For the corresponding compressed value；
Compressed packet data composing unit, for the corresponding compressed value to be constituted to the message data of compression, wherein described two
Fork sets database sharing unit
Original message data taxon is classified the original message data to obtain multiple classification data；
Historical baseline data capture unit, for obtaining historical baseline data；
Statistic unit, for the probability of occurrence according to each data item in each classification data of historical baseline data statistics；
Sequencing unit, for arranging the probability of occurrence according to sequence from big to small；
Given unit, for successively assigning compression to the probability of occurrence arranged by descending order with the sequence of 16 incrementals
Value；
Generation unit, according to each data item and compressed value generation binary tree structure in each classification data；
Storage unit, for the binary tree structure to be stored in the b-tree data library.
6. a kind of device for compressing refrigerator reported data according to claim 5, which is characterized in that the original message number
According to including switching load data, actual temperature data, reserved data, state load data, operational mode data, setting temperature number
According to and internal data, wherein the actual temperature data includes multiple actual temperature data items, and the setting temperature data includes
Multiple setting temperature data items.
7. a kind of device for compressing refrigerator reported data according to claim 6, which is characterized in that the original message number
Include: according to taxon
Actual temperature data item taxon obtains multiple practical temperature for being classified the multiple actual temperature data item
Spend classification data；
Temperature data item taxon is set, obtains multiple setting temperature for being classified the multiple setting temperature data item
Spend classification data；
Multiple classification data Component units, for switching load data, the multiple actual temperature classification data, described pre-
Residual evidence, the state load data, the operational mode data, the setting temperature classifications data and internal data constitute institute
State multiple classification data.
8. a kind of device for compressing refrigerator reported data according to claim 5, which is characterized in that the generation unit packet
It includes:
Calculate in each classification data the probability of preceding n item data item and, wherein n is positive integer；
If the probability of the preceding n item data item and be not less than preset probability threshold value, and n be not more than preset data item threshold
The preceding n item data item and the preceding n corresponding compressed values are then generated the binary tree structure by value；
Alternatively,
If the probability of the preceding n item data item and be less than the preset probability threshold value, and n be equal to the preset data
Whole n item data items and the corresponding compressed value of whole n item data item are then generated the binary tree knot by item threshold value
Structure.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103379136A (en) * | 2012-04-17 | 2013-10-30 | 中国移动通信集团公司 | Compression method and decompression method of log acquisition data, compression apparatus and decompression apparatus of log acquisition data |
| CN105135591A (en) * | 2015-07-01 | 2015-12-09 | 西安理工大学 | Train air conditioning unit fault diagnosing method based on multi-classification strategy |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20010053963A1 (en) * | 2000-06-16 | 2001-12-20 | Lg Electronics Inc. | Refrigerator and method for controlling the same |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103379136A (en) * | 2012-04-17 | 2013-10-30 | 中国移动通信集团公司 | Compression method and decompression method of log acquisition data, compression apparatus and decompression apparatus of log acquisition data |
| CN105135591A (en) * | 2015-07-01 | 2015-12-09 | 西安理工大学 | Train air conditioning unit fault diagnosing method based on multi-classification strategy |
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