CN109885575A - A kind of cutting fluid intelligent finely identifying system and method - Google Patents
A kind of cutting fluid intelligent finely identifying system and method Download PDFInfo
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Abstract
The invention discloses a kind of intelligent fine identifying systems of cutting fluid, including basic data management subsystem, General subsystem of integrated query and the database connecting with cutting fluid identification management subsystem, database is also connect with basic data management subsystem and General subsystem of integrated query.The identifying and analyzing method that the present invention carries out identification in parallel using principal component analysis-included angle cosine and principal component analysis-mahalanobis distance algorithm and consistency is checked, identification is accurate and precision is high, be conducive to improve cutting fluid discriminance analysis efficiency, improve the automation level of enterprises, reduces personnel cost.
Description
Technical field
The invention belongs to cutting fluid identification technology fields, and in particular to a kind of cutting fluid intelligent finely identifying system and side
Method.
Background technique
With manufacturing fast development, requirement of the enterprise to the function, performance, reliability of mechanical equipment etc. is more next
It is higher, and component part one of of the cutting fluid system as mechanical equipment, to performance mechanical performance, improve product quality and section
About energy etc. is most important.Cutting fluid plays corresponding lubrication anti-attrition as crucial position, cooling, cleaning, sealing, prevents
The important function such as rust anticorrosion, buffering, thereby, it is ensured that the quality of cutting fluid is the necessary condition for guaranteeing mechanical equipment and working normally.
In addition, though many enterprises are during transition and upgrade in very various information-based and automatic Buildings in China's manufacturing
If gaining ground, but it is not high to the attention degree of cutting fluid, therefore to the fining identifying and analyzing method of cutting fluid and application side
It is seldom studied in face.Based on the above circumstances, identifying and analyzing method and application study are refined to cutting fluid quality, moistened to realizing
It lays a solid foundation in terms of the functions such as lubricating oil quality Identification analysis precision is high, efficiency is fast, intelligent, automation, also to the information of enterprise
Changing construction has the function of actively promoting.
In this information age, enterprise must just carry out carrying out in terms of information system management to keep pace with the times
Transition and upgrade, either which link of business administration, should all pay attention to information system management, could integrate with well with the epoch.
Summary of the invention
For above-mentioned deficiency in the prior art, the intelligent fine identifying system of cutting fluid provided by the invention and method solution
It has determined the low problem of existing cutting fluid identifying system accuracy of identification.
In order to achieve the above object of the invention, a kind of the technical solution adopted by the present invention are as follows: intelligent fine identification of cutting fluid
System, including cutting fluid identify management subsystem, and the basic data connecting with cutting fluid identification management subsystem
Management subsystem, General subsystem of integrated query and database, the database also with basic data management subsystem and comprehensive inquiry
Subsystem connection；
The cutting fluid identification management subsystem is for typing sample data to be identified and according to basic data management subsystem
The data that system provides identify the cutting fluid in sample data to be identified；
The basic data management subsystem is for providing the data information of cutting fluid in cutting fluid identification process；
The database is used to store the data of basic data management subsystem typing, and storage General subsystem of integrated query
In data；
The General subsystem of integrated query is for inquiring and generating statistical report form.
Further, cutting fluid identification management subsystem includes sample managing unit to be identified, master sample data
Typing unit, master sample training unit and sample recognition unit to be identified；
The sample managing unit to be identified is used to sample data to be identified importing database, carries out data query sum number
Data preprocess；
The master sample data entry element is used to master sample data importing database, and establishes corresponding fingerprint
Map, and pictorialization master sample data show sample component information；
The master sample training unit is for handling simultaneously analytical standard sample data, building network neural and contrast standard
Sample information obtains and shows master sample training result；
The sample recognition unit to be identified is for carrying out sample data processing and analysis, sample to be identified in tranining database
Product data obtain the discriminance analysis result of sample data to be identified.
Further, the basic data management subsystem include Subscriber Unit administrative unit, identification instrument administrative unit,
Supplier management unit, cutting fluid administrative unit, chemical component administrative unit, identification condition management subunit, identification calibration management
Unit, weight and restriction range administrative unit and training parameter setting unit；
The Subscriber Unit administrative unit is for managing Subscriber Unit information；
The identification instrument administrative unit is for establishing identification instrument archives, the information of typing identification instrument；
The supplier management unit is used to establish the news file of supplier；
The cutting fluid administrative unit is for establishing cutting fluid type information archives；
The chemical component administrative unit is used for all kinds of chemical components of typing；
Condition when the identification condition management subunit is identified for typing, establishes environment-identification archive information；
Identification calibration administrative unit be used for according to the different identification conditions appearance time different with ingredient typing with
The degree of deviation, formation judge chromatography component data category standard；
The weight and restriction range administrative unit are used to be arranged the upper intensity limit and lower limit of identification each constituent of benchmark,
And the weight of identification each constituent of benchmark is set；
The training parameter setting unit is for being arranged identification parameter.
Further, the General subsystem of integrated query includes that sample queries unit, report query unit and batch quality are looked into
Ask unit；
The sample queries unit has been entered into systematic sample data for inquiring, and generates query result and checks sample
Information；
The report queries unit is for inquiring obtained analysis report；
The batch quality query unit is for checking same supplier with a batch of sample recognition result and specific knowledge
Other information.
Further, the intelligent fine identifying system of the cutting fluid further includes managing and maintaining subsystem；
The subsystem that manages and maintains includes database connection unit and DB Backup unit；
The database connection unit is for connecting basic data management subsystem, General subsystem of integrated query and database
It connects；
The DB Backup unit is for the data in backup database.
A kind of intelligent fine recognition methods of cutting fluid, comprising the following steps:
S1, in basic data management subsystem typing cutting fluid to be identified data information needed for identification process, and
Database is imported using the data information of cutting fluid to be identified as sample data to be identified；
S2, sample data to be identified is pre-processed by sample managing unit to be identified；
S3, master sample data are imported by database by master sample data entry element；
S4, by the master sample data in master sample training unit tranining database, obtain master sample data
Training result；
S5, according to the training result of master sample data, by sample recognition unit tranining database to be identified wait know
Other sample data, obtains the training result of sample data to be identified；
S6, dimension-reduction treatment is carried out using training result of the Principal Component Analysis to sample data to be identified；
S7, Cosin method and mahalanobis distance algorithm are utilized respectively to the training result of the sample data to be identified after dimensionality reduction
Discriminance analysis is carried out, corresponding included angle cosine discriminance analysis result and mahalanobis distance discriminance analysis result are obtained；
S8, the corresponding finger-print of master sample data is established by master sample data entry element；And judge angle
Whether cosine discriminance analysis result and mahalanobis distance discriminance analysis result are consistent with corresponding finger-print；
If so, entering step S9；
If it is not, then increasing the master sample data for importeding into database, and return step S3；
S9, the similitude and otherness for analyzing included angle cosine discriminance analysis result and mahalanobis distance discriminance analysis result are raw
At corresponding analysis report, the fine recognition result of cutting fluid is obtained.
Further, in the step S1, in basic data management subsystem typing cutting fluid to be identified in identification process
Needed for data information specifically include:
(1), the Subscriber Unit information belonging to typing cutting fluid to be identified in service management unit；
(2), the identification instrument archive information needed for typing cutting fluid to be identified in identification instrument administrative unit；
(3), the vendor profile information belonging to typing cutting fluid to be identified in supplier management unit；
(4), in the title of cutting fluid administrative unit typing cutting fluid to be identified；
(5), in chemical component administrative unit typing cutting fluid to be identified chemical name and its corresponding chemical formula；
(6), the auxiliary device information of the identification instrument needed for identifying condition management subunit typing cutting fluid to be identified；
(7), test condition and chemical component needed for typing cutting fluid identification process in identification calibration administrative unit,
And determine identification benchmark；
(8), the weight and intensity of identification benchmark are set in weight and restriction range administrative unit；
(9), frequency of training, the Principle component extraction ratio of sample recognition unit to be identified are set in training parameter setting unit
Example and principal component are because of subnumber.
Further, pretreated method is carried out to sample data to be identified in the step S2 specifically: merge or delete
Except similarity degree is greater than 90% identification reference data in sample data to be identified.
Further, it is reported in the step S9 by General subsystem of integrated query query analysis, the cutting fluid checked
Fine recognition result.
The invention has the benefit that cutting fluid intelligence fining identifying system provided by the invention and method are using master
The identification point that constituent analysis-included angle cosine and principal component analysis-mahalanobis distance algorithm carry out identification in parallel and consistency is checked
Analysis method, identification is accurate and precision is high, is conducive to improve cutting fluid discriminance analysis efficiency, improves the automation level of enterprises, reduces
Personnel cost.
Detailed description of the invention
Fig. 1 is the intelligent fine identifying system structure chart of cutting fluid provided by the invention.
Fig. 2 is cutting fluid Intelligent fine recognition methods flow chart provided by the invention.
Specific embodiment
A specific embodiment of the invention is described below, in order to facilitate understanding by those skilled in the art this hair
It is bright, it should be apparent that the present invention is not limited to the ranges of specific embodiment, for those skilled in the art,
As long as various change is in the spirit and scope of the present invention that the attached claims limit and determine, these variations are aobvious and easy
See, all are using the innovation and creation of present inventive concept in the column of protection.
As shown in Figure 1, a kind of intelligent fine identifying system of cutting fluid, including cutting fluid identify management subsystem, and
Basic data management subsystem, General subsystem of integrated query and the database being connect with cutting fluid identification management subsystem,
The database is also connect with basic data management subsystem and General subsystem of integrated query；
The cutting fluid identification management subsystem is for typing sample data to be identified and according to basic data management subsystem
The data that system provides identify the cutting fluid in sample data to be identified；
The basic data management subsystem is for providing the data information of cutting fluid in cutting fluid identification process；
The database is used to store the data of basic data management subsystem typing, and storage General subsystem of integrated query
In data；
The General subsystem of integrated query is for inquiring and generating statistical report form.
Wherein, cutting fluid identification management subsystem include sample managing unit to be identified, master sample data entry element,
Master sample training unit and sample recognition unit to be identified；
The sample managing unit to be identified is used to sample data to be identified importing database, carries out data query sum number
Data preprocess；
The master sample data entry element is used to master sample data importing database, and establishes corresponding fingerprint
Map, and pictorialization master sample data show sample component information；
The master sample training unit is for handling simultaneously analytical standard sample data, building network neural and contrast standard
Sample information obtains and shows master sample training result；
The sample recognition unit to be identified is for carrying out sample data processing and analysis, sample to be identified in tranining database
Product data obtain the discriminance analysis result of sample data to be identified.
Wherein, basic data management subsystem includes Subscriber Unit administrative unit, identification instrument administrative unit, supplier's pipe
Manage unit, cutting fluid administrative unit, chemical component administrative unit, identification condition management subunit, identification calibration administrative unit, weight
And restriction range administrative unit and training parameter setting unit；
The Subscriber Unit administrative unit is for managing Subscriber Unit information；
The identification instrument administrative unit is for establishing identification instrument archives, the information of typing identification instrument；
The supplier management unit is used to establish the news file of supplier；
The cutting fluid administrative unit is for establishing cutting fluid type information archives；
The chemical component administrative unit is used for all kinds of chemical components of typing；
Condition when the identification condition management subunit is identified for typing, establishes environment-identification archive information；
Identification calibration administrative unit be used for according to the different identification conditions appearance time different with ingredient typing with
The degree of deviation, formation judge chromatography component data category standard；
The weight and restriction range administrative unit are used to be arranged the upper intensity limit and lower limit of identification each constituent of benchmark,
And the weight of identification each constituent of benchmark is set；
The training parameter setting unit is for being arranged all identification parameters.
Wherein, the General subsystem of integrated query includes sample queries unit, report query unit and batch quality cargo tracer
Member；
The sample queries unit has been entered into systematic sample data for inquiring, and generates query result and checks sample
Information；
The report queries unit is for inquiring obtained analysis report；
The batch quality query unit is for checking same supplier with a batch of sample recognition result and specific knowledge
Other information.
The intelligent fine identifying system of above-mentioned cutting fluid further includes managing and maintaining subsystem；
The subsystem that manages and maintains includes database connection unit, DB Backup unit, database journal compression
Unit, database recovery unit, user's switch unit, change of secret code unit and help unit；
The database connection unit is for connecting basic data management subsystem, General subsystem of integrated query and database
It connects；
The DB Backup unit is for the data in backup database.
The database journal compression unit is for the log file data in compressed data library；
The database recovery unit is used to restore the file data in database；
User's switch unit changes login user for returning to login interface；
The change of secret code unit is for changing user password；
The help unit is for providing system operation instruction.
As shown in Fig. 2, the present invention also provides a kind of intelligent fine recognition methods of cutting fluid, including following step
It is rapid:
S1, in basic data management subsystem typing cutting fluid to be identified data information needed for identification process, and
Database is imported using the data information of cutting fluid to be identified as sample data to be identified；
In above-mentioned steps S1, in basic data management subsystem typing cutting fluid to be identified number needed for identification process
It is believed that breath specifically includes:
(1), the Subscriber Unit information belonging to typing cutting fluid to be identified in service management unit；
(2), the identification instrument archive information needed for typing cutting fluid to be identified in identification instrument administrative unit；Including knowing
It is the title of other instrument, specifications and models, silent using unit, custodian, performance state, source mode, production firm and identification benchmark
Recognize deviation etc., and sets sample data to be identified and read initial row and read column；
(3), the vendor profile information belonging to typing cutting fluid to be identified in supplier management unit；Including supplier
Title, supplier property and address, supplier contact person and its telephone number and mailbox etc.；
(4), in the title of cutting fluid administrative unit typing cutting fluid to be identified；
(5), in chemical component administrative unit typing cutting fluid to be identified chemical name and its corresponding chemical formula；
(6), the auxiliary device information of the identification instrument needed for identifying condition management subunit typing cutting fluid to be identified；
(7), test condition and chemical component needed for typing cutting fluid identification process in identification calibration administrative unit,
And determine identification benchmark and upper lower deviation or deviation ratio；
(8), setting identifies the weight of benchmark and the upper limit value and lower limit of intensity in weight and restriction range administrative unit
Value；
(9), frequency of training, the Principle component extraction ratio of sample recognition unit to be identified are set in training parameter setting unit
Example and principal component are because of subnumber.
S2, sample data to be identified is pre-processed by sample managing unit to be identified；
Pretreated method is carried out to sample data to be identified in above-mentioned steps S2 specifically: merge or delete sample to be identified
Similarity degree is greater than 90% identification reference data in product data.
S3, master sample data are imported by database by master sample data entry element；
S4, pass through master sample training unit training standard sample data, obtain the training result of master sample data；
S5, according to the training result of master sample data, pass through sample recognition unit to be identified training sample number to be identified
According to obtaining the training result of sample data to be identified；
S6, dimension-reduction treatment is carried out using training result of the Principal Component Analysis to sample data to be identified；
Principal Component Analysis is a kind of technology analyzed, simplify data set；After principal component analysis, multiple variables transformations are few
It counts several integrated data indexs and ensure that integrated data index is able to reflect the raw information of the overwhelming majority, maximizing
Guarantee that data are distortionless while are simplified data.
S7, Cosin method and mahalanobis distance algorithm are utilized respectively to the training result of the sample data to be identified after dimensionality reduction
Discriminance analysis is carried out, corresponding included angle cosine discriminance analysis result and mahalanobis distance discriminance analysis result are obtained；
Wherein, Cosin method is to use two vectorial angle cosine values in vector space as between two individuals of measurement
The measurement of difference, cosine value is closer to 1, then two vectors are more similar；Included angle cosine is defined as: assuming that the slope of straight line l1 and l2
In the presence of the steering angle of respectively k1 and k2, l1 to l2 are θ, then the angle of tan θ=(k2-k1)/(1+k1k2) l1 and l2 is θ；
Mahalanobis distance algorithm is proposed by India's statistician's Mahalanobis, indicates the covariance distance of data,
It is a kind of method of similarity for effectively calculating two unknown sample collection, it is not influenced by dimension, the horse between two o'clock
Family name's distance is unrelated with the measurement unit of initial data, can also exclude the interference of the correlation between variable.Not with Euclidean distance
Be it in view of contacting between various characteristics (such as: the information about height can bring one about weight
Information, because the two is related) and be that scale is unrelated, i.e., independently of measurement scale.It is μ, association for a mean value
Variance matrix is the multivariable vector of Σ, and mahalanobis distance is [(x- μ) ' Σ ^ (- 1) (x- μ)] ^ (1/2).
S8, the corresponding finger-print of master sample data is established by master sample data entry element；And judge angle
Whether cosine discriminance analysis result and mahalanobis distance discriminance analysis result are consistent with corresponding finger-print；
If so, entering step S9；
If it is not, then increasing the master sample data for importeding into database, and return step S3；
S9, the similitude and otherness for analyzing included angle cosine discriminance analysis result and mahalanobis distance discriminance analysis result are raw
At corresponding analysis report, the fine recognition result of cutting fluid is obtained.
The analysis report generated in above-mentioned steps S9 can be inquired by General subsystem of integrated query, and that checks cuts
Cut the fine recognition result of liquid.
The invention has the benefit that cutting fluid intelligence fining identifying system provided by the invention and method are using master
The identification point that constituent analysis-included angle cosine and principal component analysis-mahalanobis distance algorithm carry out identification in parallel and consistency is checked
Analysis method, identification is accurate and precision is high, is conducive to improve cutting fluid discriminance analysis efficiency, improves the automation level of enterprises, reduces
Personnel cost.
Claims (9)
1. a kind of intelligent fine identifying system of cutting fluid, which is characterized in that identify management subsystem, Yi Jijun including cutting fluid
Basic data management subsystem, General subsystem of integrated query and the database being connect with cutting fluid identification management subsystem, institute
Database is stated also to connect with basic data management subsystem and General subsystem of integrated query；
The cutting fluid identification management subsystem is mentioned for typing sample data to be identified and according to basic data management subsystem
The data of confession identify the cutting fluid in sample data to be identified；
The basic data management subsystem is for providing the data information of cutting fluid in cutting fluid identification process；
The database is used to store in the data of basic data management subsystem typing, and storage General subsystem of integrated query
Data；
The General subsystem of integrated query is for inquiring and generating statistical report form.
2. the intelligent fine identifying system of cutting fluid according to claim 1, which is characterized in that the cutting fluid identification pipe
Reason subsystem includes sample managing unit to be identified, master sample data entry element, master sample training unit and to be identified
Sample recognition unit；
The sample managing unit to be identified is used to sample data to be identified importing database, carries out data query and data are pre-
Processing；
The master sample data entry element is used to master sample data importing database, and establishes corresponding fingerprint image
Spectrum, and pictorialization master sample data show sample component information；
The master sample training unit is for handling simultaneously analytical standard sample data, building network neural and contrast standard sample
Information obtains and shows master sample training result；
The sample recognition unit to be identified is for carrying out sample data processing and analysis, sample number to be identified in tranining database
According to obtaining the discriminance analysis result of sample data to be identified.
3. the intelligent fine identifying system of cutting fluid according to claim 1, which is characterized in that the basic data management
Subsystem includes Subscriber Unit administrative unit, identification instrument administrative unit, supplier management unit, cutting fluid administrative unit, changes
Learn composition management unit, identification condition management subunit, identification calibration administrative unit, weight and restriction range administrative unit and training
Parameter set unit；
The Subscriber Unit administrative unit is for managing Subscriber Unit information；
The identification instrument administrative unit is for establishing identification instrument archives, the information of typing identification instrument；
The supplier management unit is used to establish the news file of supplier；
The cutting fluid administrative unit is for establishing cutting fluid type information archives；
The chemical component administrative unit is used for all kinds of chemical components of typing；
Condition when the identification condition management subunit is identified for typing, establishes environment-identification archive information；
The identification calibration administrative unit is used for according to the different identification conditions appearance time different with ingredient typing and deviation
Degree, formation judge chromatography component data category standard；
The weight and restriction range administrative unit are used to be arranged the upper intensity limit and lower limit of identification each constituent of benchmark, and set
Set the weight of identification each constituent of benchmark；
The training parameter setting unit is for being arranged identification parameter.
4. the intelligent fine identifying system of cutting fluid according to claim 1, which is characterized in that the comprehensive inquiry subsystem
System includes sample queries unit, report query unit and batch quality query unit；
The sample queries unit has been entered into systematic sample data for inquiring, and generates query result and checks that sample is believed
Breath；
The report queries unit is for inquiring obtained analysis report；
The batch quality query unit is for checking same supplier with a batch of sample recognition result and specific identification letter
Breath.
5. the intelligent fine identifying system of cutting fluid according to claim 1, which is characterized in that the cutting fluid is intelligent
Fine identifying system further includes managing and maintaining subsystem；
The subsystem that manages and maintains includes database connection unit and DB Backup unit；
The database connection unit is for connecting basic data management subsystem, General subsystem of integrated query and database；
The DB Backup unit is for the data in backup database.
6. a kind of intelligent fine recognition methods of cutting fluid, which comprises the following steps:
S1, in basic data management subsystem typing cutting fluid to be identified data information needed for identification process, and will be to
Identify that the data information of cutting fluid imports database as sample data to be identified；
S2, sample data to be identified is pre-processed by sample managing unit to be identified；
S3, master sample data are imported by database by master sample data entry element；
S4, by the master sample data in master sample training unit tranining database, obtain the training of master sample data
As a result；
S5, according to the training result of master sample data, pass through sample to be identified in sample recognition unit tranining database to be identified
Product data obtain the training result of sample data to be identified；
S6, dimension-reduction treatment is carried out using training result of the Principal Component Analysis to sample data to be identified；
S7, it is utilized respectively the training result progress of Cosin method and mahalanobis distance algorithm to the sample data to be identified after dimensionality reduction
Discriminance analysis obtains corresponding included angle cosine discriminance analysis result and mahalanobis distance discriminance analysis result；
S8, the corresponding finger-print of master sample data is established by master sample data entry element；And judge included angle cosine
Whether discriminance analysis result and mahalanobis distance discriminance analysis result are consistent with corresponding finger-print；
If so, entering step S9；
If it is not, then increasing the master sample data for importeding into database, and return step S3；
S9, the similitude and otherness for analyzing included angle cosine discriminance analysis result and mahalanobis distance discriminance analysis result, generation pair
The analysis report answered obtains the fine recognition result of cutting fluid.
7. the intelligent fine recognition methods of cutting fluid according to claim 6, which is characterized in that in the step S1,
Basic data management subsystem typing cutting fluid to be identified data information needed for identification process specifically includes:
(1), the Subscriber Unit information belonging to typing cutting fluid to be identified in service management unit；
(2), the identification instrument archive information needed for typing cutting fluid to be identified in identification instrument administrative unit；
(3), the vendor profile information belonging to typing cutting fluid to be identified in supplier management unit；
(4), in the title of cutting fluid administrative unit typing cutting fluid to be identified；
(5), in chemical component administrative unit typing cutting fluid to be identified chemical name and its corresponding chemical formula；
(6), the auxiliary device information of the identification instrument needed for identifying condition management subunit typing cutting fluid to be identified；
(7), test condition and chemical component needed for typing cutting fluid identification process in identification calibration administrative unit, and really
Surely benchmark is identified；
(8), the weight and intensity of identification benchmark are set in weight and restriction range administrative unit；
(9), be arranged in training parameter setting unit the frequency of training of sample recognition unit to be identified, Principle component extraction ratio and
Principal component is because of subnumber.
8. the intelligent fine recognition methods of cutting fluid according to claim 6, which is characterized in that treated in the step S2
Identify that sample data carries out pretreated method specifically: merge or delete similarity degree in sample data to be identified and be greater than 90%
Identification reference data.
9. the intelligent fine recognition methods of cutting fluid according to claim 6, which is characterized in that pass through in the step S9
The report of General subsystem of integrated query query analysis, the fine recognition result for the cutting fluid checked.
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| CN108009740A (en) * | 2017-12-14 | 2018-05-08 | 四川大学 | A kind of intelligent fine identifying system of essence spice for cigarette and method |
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Application publication date: 20190614 |
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