CN110096036A - A kind of determination method, device and equipment of equipment state - Google Patents
A kind of determination method, device and equipment of equipment state Download PDFInfo
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- CN110096036A CN110096036A CN201810082723.9A CN201810082723A CN110096036A CN 110096036 A CN110096036 A CN 110096036A CN 201810082723 A CN201810082723 A CN 201810082723A CN 110096036 A CN110096036 A CN 110096036A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41885—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by modeling, simulation of the manufacturing system
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32339—Object oriented modeling, design, analysis, implementation, simulation language
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The application provides a kind of determination method, device and equipment of equipment state, this method comprises: obtaining the corresponding product data of product of production equipment production；Obtain the sensing data of sensor acquisition relevant to the production equipment；According to the product data and the sensing data, the corresponding characteristic of the production equipment is obtained；The corresponding equipment state of the production equipment is determined according to the characteristic.By the technical solution of the application, the equipment state of production equipment is detected in time, the equipment state of production equipment can be assessed, can predict whether production equipment breaks down, failure is repaired in time, guarantee product quality.
Description
Technical field
This application involves field of communication technology, the determination method, device and equipment of especially a kind of equipment state.
Background technique
In field of industrial production, the production of product is the composition of sequence of operations and step, each production link be all by
The result that many factors influence.In field of industrial production, " people, machine, material, method, ring " is five principal elements of production process, people
Refer to operator, machine refers to production equipment (being referred to as production machine), and material refers to production material, and method refers to production technology
(being referred to as production method), ring refers to production environment.
Production equipment is the important component of above-mentioned five factors, and the influence to production result is very big.If production is set
It is standby abnormal, then it will lead to product and quality problems or even production failure occur.It is therefore desirable to be able to which detection production in time is set
Standby state, and effective detection means of current not production equipment state.
Summary of the invention
The application provides a kind of determination method of equipment state, which comprises
Obtain the corresponding product data of product of production equipment production；
Obtain the sensing data of sensor acquisition relevant to the production equipment；
According to the product data and the sensing data, the corresponding characteristic of the production equipment is obtained；
The corresponding equipment state of the production equipment is determined according to the characteristic.
The application provides a kind of determination method of equipment state, which comprises
Obtain the sensing data of sensor acquisition relevant to particular types of devices；
The corresponding characteristic of the particular types of devices is obtained according to the sensing data；
The corresponding equipment state of the particular types of devices is determined according to the characteristic.
The application provides a kind of determining device of equipment state, and described device includes:
Module is obtained, for obtaining the corresponding product data of product of production equipment production；It obtains and the production equipment
The sensing data of relevant sensor acquisition；According to the product data and the sensing data, obtains the production and set
Standby corresponding characteristic；
Determining module, for determining the corresponding equipment state of the production equipment according to the characteristic.
The application provides a kind of for determining the analytical equipment of equipment state, comprising: processor, for obtaining production equipment
The corresponding product data of the product of production；Obtain the sensing data of sensor acquisition relevant to the production equipment；According to
The product data and the sensing data obtain the corresponding characteristic of the production equipment；According to the characteristic
Determine the corresponding equipment state of the production equipment.
Based on the above-mentioned technical proposal, in the embodiment of the present application, production can be obtained according to product data and sensing data
The corresponding characteristic of equipment, and the corresponding equipment state of production equipment is determined according to characteristic, thus detection production in time
The equipment state of equipment can assess the equipment state of production equipment, can predict whether production equipment breaks down,
Failure is repaired in time, guarantees product quality.Aforesaid way provides a kind of modeling analysis mode based on sensing data,
For assessing the equipment state of production equipment, the analysis ability of industrial production practitioner is promoted, fast and accurately diagnosis production is set
The failure of standby equipment state or even look-ahead production equipment occurs, and the maintenance plan of production equipment is assisted, as far as possible
The maintenance that production equipment is carried out in the case where not affecting the normal production, pushes the benefit of industrial enterprise to get a promotion.
Detailed description of the invention
It, below will be to the application in order to clearly illustrate the embodiment of the present application or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described below
Attached drawing is only some embodiments as described in this application, for those of ordinary skill in the art, can also be according to this Shen
Please these attached drawings of embodiment obtain other attached drawings.
Fig. 1 is the flow chart of the determination method of the equipment state in a kind of embodiment of the application；
Fig. 2 is the process structure schematic diagram in a kind of embodiment of the application；
Fig. 3 is the flow chart of the determination method of the equipment state in the application another embodiment；
Fig. 4 is the structure chart of the determining device of the equipment state in a kind of embodiment of the application.
Specific embodiment
In the term that the embodiment of the present application uses merely for the sake of for the purpose of describing particular embodiments, rather than limit this Shen
Please.The "an" of singular used in the application and claims, " described " and "the" are also intended to including most shapes
Formula, unless context clearly shows that other meanings.It is also understood that term "and/or" used herein refers to comprising one
A or multiple associated any or all of project listed may combine.
It will be appreciated that though various letters may be described using term first, second, third, etc. in the embodiment of the present application
Breath, but these information should not necessarily be limited by these terms.These terms are only used to for same type of information being distinguished from each other out.For example,
In the case where not departing from the application range, the first information can also be referred to as the second information, and similarly, the second information can also be with
The referred to as first information depends on context.
It is proposed that a kind of determination method of equipment state, this method can be applied to analytical equipment in the embodiment of the present application, it should
Analytical equipment can include but is not limited to PC (Personal Computer, personal computer), terminal device, laptop,
Server etc., with no restrictions to the type of this analytical equipment.It is shown in Figure 1, it is the stream of the determination method of above equipment state
Journey illustrated example, this method may comprise steps of:
Step 101, the corresponding product data of product of production equipment production are obtained.
Step 102, the sensing data of sensor acquisition relevant to the production equipment is obtained.
Step 103, according to the product data and the sensing data, the corresponding characteristic of the production equipment is obtained.
Step 104, the corresponding equipment state of the production equipment is determined according to this feature data.
In one example, above-mentioned execution sequence is intended merely to facilitate description to provide example, in practical applications,
Sequence is executed between can also changing the step, with no restrictions to this execution sequence.Moreover, in other embodiments, and it is different
The fixed sequence for showing and describing according to this specification is come the step of executing correlation method, step included by method can be than this
It is more or less described in specification.In addition, single step described in this specification, it in other embodiments may quilt
Multiple steps are decomposed into be described；Multiple steps described in this specification may also be merged into other embodiments
Single step is described.
For step 103, in one example, for " according to the product data and the sensing data, obtaining the production
The process of the corresponding characteristic of equipment ", can include but is not limited to such as under type:
Product data corresponding with same temporal information and sensing data are associated, and utilize the product after association
Data and sensing data obtain the corresponding characteristic of the production equipment.That is, can use and same temporal information
Corresponding product data and sensing data obtain the corresponding characteristic of the production equipment, that is, production equipment production
Product corresponding to characteristic.
For the process of " will product data corresponding with same temporal information and sensing data be associated ", can wrap
It includes: obtaining first time information from product data, and obtain the second temporal information from sensing data；Then, according to this
First time information and second temporal information determine product data corresponding with same temporal information and sensing data, and
Determining product data and sensing data are associated.
For step 103, in one example, for " according to the product data and the sensing data, obtaining the production
The process of the corresponding characteristic of equipment ", can include but is not limited to such as under type:
Corresponding particular model is chosen for the product, and using the particular model to the product data and the sensing data
It is handled, obtains the corresponding characteristic of the production equipment.Further, the particular model can include but is not limited to:
Time series models；Alternatively, regression model；Alternatively, Tree-structure Model.
For step 104, in one example, for " determining the corresponding equipment of the production equipment according to this feature data
The process of state " can include but is not limited to such as under type: judge whether this feature data are abnormal data；If abnormal number
According to can then determine that the corresponding equipment state of the production equipment is abnormality；If not abnormal data, then can determine the life
Producing the corresponding equipment state of equipment is normal condition.
In one example, for the process of " judging whether this feature data are abnormal data ", may include but unlimited
In such as under type: mode one, according to the comparison result of this feature data and normal parameter judges whether this feature data are abnormal
Data；Wherein, which is to indicate the normal parameter information of the production equipment.Alternatively, mode two, according to this feature data
With the comparison result of anomaly parameter, judge whether this feature data are abnormal data；Wherein, which is to indicate the production
The parameter information of unit exception.Alternatively, mode three, obtain the production equipment production the corresponding multiple characteristics of multiple products
According to, and it is comparative between the multiple characteristic of utilization, it analyzes in the multiple characteristic with the presence or absence of abnormal data.
For mode three, in one example, for " obtain the production equipment production the corresponding multiple spies of multiple products
The process of sign data " may include: the corresponding multiple production batch of multiple products for obtaining production equipment production；Pass through institute
Multiple production batch inquiry mapping relations are stated, the corresponding multiple characteristics of multiple production batch are obtained；Wherein, the mapping relations
It is the mapping relations of production batch and characteristic.
Further, " according to the product data and the sensing data, the corresponding characteristic of the production equipment is being obtained
According to " after, the corresponding production batch of the product can also be obtained from the product data, and establish the production batch and this feature
The mapping relations of data.Based on this mapping relations, so that it may execute and " inquire mapping relations by the multiple production batch, obtain
To the corresponding multiple characteristics of multiple production batch " operation.
For mode three, in one example, for " it is comparative between the multiple characteristic of utilization, analyze institute
State in multiple characteristics with the presence or absence of abnormal data " process, if may include: exist in the multiple characteristic it is specified
Type feature data can then determine that the specified type characteristic is abnormal data.Wherein, the specified type characteristic with
The difference of other feature data is greater than preset threshold.
Based on the above-mentioned technical proposal, in the embodiment of the present application, production can be obtained according to product data and sensing data
The corresponding characteristic of equipment, and the corresponding equipment state of production equipment is determined according to characteristic, thus detection production in time
The equipment state of equipment can assess the equipment state of production equipment, can predict whether production equipment breaks down,
Failure is repaired in time, guarantees product quality.Aforesaid way provides a kind of modeling analysis mode based on sensing data,
For assessing the equipment state of production equipment, the analysis ability of industrial production practitioner is promoted, fast and accurately diagnosis production is set
The failure of standby equipment state or even look-ahead production equipment occurs, and the maintenance plan of production equipment is assisted, as far as possible
The maintenance that production equipment is carried out in the case where not affecting the normal production, pushes the benefit of industrial enterprise to get a promotion.
Below in conjunction with concrete application scene, the above scheme of the embodiment of the present application is described in detail.
In field of industrial production, production equipment (such as automated production equipment) can dispose one or more sensing
Device, the sensor are used to carry out data acquisition to the process of manufacture of production equipment, sensing data are obtained, for the side of differentiation
Just, the collected data of sensor can be known as sensing data, is based on this sensing data, automation control may be implemented
System, and the production process of production equipment is monitored and is alarmed.
For example, can dispose temperature sensor in production equipment, which can acquire process of manufacture
Temperature information.Alternatively, can dispose pressure sensor in production equipment, which can acquire process of manufacture
Pressure information.Alternatively, can dispose vibrating sensor in production equipment, which can acquire process of manufacture
Impact force or acceleration information.Alternatively, can dispose range sensor in production equipment, which can acquire life
Produce the object moving distance of process.
Certainly, the sensor is several examples of the application, without limitation, and the collected number of sensor
According to, such as above-mentioned temperature information, pressure information, object moving distance, it is exactly sensing data.
Based on the collected sensing data of sensor, the embodiment of the present application proposes a kind of determination method of equipment state,
Be one towards field of industrial production, based on sensing data equipment state determination method, can by data mining,
The means such as mathematical modeling, machine learning determine the characteristic of production equipment, and determine production equipment using this feature data
Whether equipment state, prediction production equipment break down, to assess the equipment health portrait (Machine of production equipment
Health Profile).For example, predicting that the following production equipment breaks down by the modeling analysis for having production batch data
Probability promote the analysis ability of industrial production practitioner, fast and accurately for assisting the maintenance decision of production equipment
The operation health status of production equipment is diagnosed, the failure of look-ahead production equipment occurs, so that the maintenance of production equipment
It can be carried out in the case where not affecting the normal production as far as possible, the benefit of industrial enterprise is pushed to get a promotion.
In order to more clearly illustrate the determination method of above equipment state, the applied field of the embodiment of the present application is first introduced
Scape, for the convenience of description, being illustrated by taking the silicon wafer cutting technique of field of industrial production as an example.Certainly, silicon wafer cutting technique
It is an example of field of industrial production, without limitation, all application scenarios in production equipment deployment sensor,
With using the determination method of above equipment state, implementation process is similar with the process of silicon wafer cutting technique, in this application scene
In, it is illustrated by taking silicon wafer cutting technique as an example.
In silicon wafer cutting technique, production equipment is used to silicon ingot being cut into silicon wafer, this silicon wafer is equivalent to production equipment
The product of production.In cutting process, production equipment can acquire the product data of silicon wafer, which may include but not
It is limited to one of the following contents or any combination: the manufacturing schedule of the acquisition time of product data, the production batch of silicon wafer, silicon wafer,
It certainly can also include other contents, it is without limitation.
For example, production equipment collects product data 1- product data 6, these product data can be as shown in table 1, so
Afterwards, production equipment can store these product data into database.Certainly, in practical applications, production equipment collects
Product data far more than the product data in table 1, subsequent be exemplified by Table 1 is illustrated.Production equipment is often cut into one
Silicon wafer is equivalent to and produces a product (i.e. silicon wafer), and when one product of production, so that it may multiple product data are collected,
If product data 1- product data 3 are the product data for product 1, product data 4- product data 6 are the productions for product 2
Product data.
Table 1
| Product data mark | Acquisition time | Production batch | Manufacturing schedule |
| Product data 1 | 2017.12.17-10:32:28 | 20171217001 | 10% |
| Product data 2 | 2017.12.17-12:32:30 | 20171217001 | 60% |
| Product data 3 | 2017.12.17-14:20:28 | 20171217001 | 90% |
| Product data 4 | 2017.12.17-15:06:28 | 20171217002 | 5% |
| Product data 5 | 2017.12.17-16:32:30 | 20171217002 | 40% |
| Product data 6 | 2017.12.17-17:40:28 | 20171217002 | 95% |
In one example, sensor (such as range sensor) can be disposed in production equipment, which can be with
The object moving distance for acquiring process of manufacture as sensor can be deployed on the cutting part of production equipment, and senses
Device is used to acquire the moving distance of tapered shaft (i.e. silicon chip cutter tapered shaft), i.e., silicon ingot is cut into silicon wafer in cutting part
In the process, the moving distance of tapered shaft is acquired.For example, in the initial state, the moving distance of tapered shaft is 0, at this time cutting part
Part not yet cuts silicon ingot；The moving distance of cutting with cutting part to silicon ingot, tapered shaft is increasing, and passes
Sensor can collect the moving distance of tapered shaft, such as the moving distance of tapered shaft is 2 centimetres, 4 centimetres, is not limited this
System.
In cutting process, sensor can collect sensing data, which can include but is not limited to
One of the following contents or any combination: the moving distance of the acquisition time of sensing data, tapered shaft.Certainly, sensor number
According to that can also include other contents, with no restrictions to this sensing data.
For example, sensor collects sensing data 1- sensing data 6, these sensing datas can be as shown in table 2,
Then, sensor stores these sensing datas into database.Certainly, in practical applications, the collected biography of sensor
Sensor data can be subsequent by taking table 2 as an example far more than the sensing data in table 2.Production equipment is often cut into a silicon wafer, phase
When producing a product (i.e. silicon wafer), and produce a product, so that it may collect multiple sensing datas, such as sense
Device data 1- sensing data 3 is the sensing data for product 1, and sensing data 4- sensing data 6 is for product 2
Sensing data.
Table 2
Based on the product data (as shown in table 1) and sensing data (as shown in table 2) stored in database, so that it may really
Determine the equipment state of production equipment, such as determine the equipment state of production equipment itself, alternatively, some component is (such as in production equipment
Cutting part) equipment state.This process is described in detail below.
It is shown in Figure 2, be the process structure schematic diagram in the embodiment of the present application, which can include but is not limited to:
Data Layer, pretreatment layer, aspect of model layer, configuration layer, tap layer and application layer.Wherein:
1, data Layer.It can store sensing data, product data, MES in the database
(ManufacturingExecution System, manufacturing enterprise's production process execute system) data, quality verify data, work
Skill sets data etc., these data are the widely used data of industrial processes, are not done to the data type in database
Limitation, as long as including sensing data, product data.In data Layer, can be obtained from database sensing data and
Product data, and sensing data and product data are supplied to pretreatment layer.
Wherein, product data are the corresponding product data of product of production equipment production, can be as shown in table 1.Sensor
Data are the sensing datas of sensor acquisition relevant to production equipment, can be as shown in table 2.
2, pretreatment layer.After obtaining sensing data and product data, can to sensing data and product data into
Row pretreatment (such as suppressing exception value), and sensing data and product data are associated.
Wherein, due to that may include exceptional value in sensing data, after obtaining sensing data, first judge
It whether there is exceptional value in sensing data.If it is, the exceptional value in sensing data is deleted, if it is not, then not needing
Delete the exceptional value in sensing data.For example, it is assumed that the length of final products (i.e. silicon wafer) is 10 centimetres, then the shifting of tapered shaft
Dynamic distance does not exceed 10 centimetres, therefore, if sensing data includes the moving distance greater than 10 centimetres, this sensor number
According to being exactly exceptional value, need to be deleted.
Wherein, due to that may include exceptional value in product data, after obtaining product data, first judge product number
It whether there is exceptional value in.If it is, the exceptional value in product data is deleted, if it is not, then not needing to delete product number
Exceptional value in.For example, manufacturing schedule does not exceed 100%, if product data include the manufacturing schedule greater than 100%,
This product data is exactly exceptional value, needs to be deleted.
Wherein, due to including that temporal information (in order to distinguish conveniently, the temporal information in product data is claimed in product data
For first time information, i.e. acquisition time in table 1), and include that temporal information (in order to distinguish conveniently, is incited somebody to action in sensing data
Temporal information in sensing data is known as the second temporal information, i.e. acquisition time in table 2), it therefore, can will be with same a period of time
Between the corresponding product data of information and sensing data be associated.Specifically, first time information is obtained from product data,
And the second temporal information is obtained from sensing data, it is determining and same according to the first time information and second temporal information
The corresponding product data of one temporal information and sensing data, and determining product data and sensing data are associated.
For example, the first time information of product data 1 be 2017.12.17-10:32:28, sensing data 1 second when
Between information be 2017.12.17-10:32:28, therefore, product data 1 and sensing data 1 and same temporal information
" 2017.12.17-10:32:28 " is corresponding, it can is associated product data 1 and sensing data 1.It is similar, it can be with
Product data 2 and sensing data 2 are associated, product data 3 and sensing data 3 are associated, by product data 4
It is associated with sensing data 4, product data 5 and sensing data 5 is associated, by product data 6 and sensor number
It is associated according to 6.
Further, pretreatment layer can also be by the product data and sensing data (such as product data 1 and biography after association
The incidence relation of sensor data 1, the incidence relation of product data 2 and sensing data 2, product data 3 and sensing data 3
Incidence relation etc., and so on) it is supplied to aspect of model layer.
3, aspect of model layer.After being associated with product data and sensing data after, can use association after production
Product data and sensing data obtain the corresponding characteristic of production equipment.I.e., it is possible to using corresponding with same temporal information
Product data and sensing data obtain the corresponding characteristic of production equipment.
Specifically, corresponding particular model can be chosen for the product, and using the particular model to the product after association
Data and sensing data are handled, and the corresponding characteristic of the production equipment is obtained.Particular model may include but unlimited
In: time series models；Alternatively, regression model；Alternatively, Tree-structure Model.
For example, the incidence relation of the available product data 1 of the aspect of model layer and sensing data 1,2 and of product data
The incidence relation of sensing data 2, the incidence relation of product data 3 and sensing data 3, product data 4 and sensing data 4
Incidence relation, the incidence relations of product data 5 and sensing data 5, product data 6 and sensing data 6 incidence relation.
Then, due to the corresponding same production batch " 20171217001 " of product data 1, product data 2 and product data 3, that is,
It says, the corresponding same product (i.e. product 1) of product data 1, product data 2 and product data 3 therefore can be by product data 1
Same group of input number is used as with sensing data 1, product data 2 and sensing data 2, product data 3 and sensing data 3
According to this group of input data is used to train the product data of product 1.It similarly, can be by product data 4 and sensing data 4, product
Data 5 and sensing data 5, product data 6 and sensing data 6 are used as same group of input data, this group of input data is used for
The product data of training product 2.
Assuming that particular model is time series models, then it can be by product data 1 and sensing data 1,2 and of product data
Sensing data 2, product data 3 and sensing data 3 are used as input data, export to time series models, time series mould
Type carries out modeling analysis and feature extraction according to these input datas, obtains characteristic A.It similarly, can also be by product data 4
Time series mould is given with the output of sensing data 4, product data 5 and sensing data 5, product data 6 and sensing data 6
Type, time series models carry out modeling analysis and feature extraction according to these data, obtain characteristic B.
Further, features described above data A and characteristic B i.e. the corresponding characteristic of production equipment.
Wherein, the related definition of time series models can be as follows: production and scientific research in, to some or
Certain group variable is observed and measured, and will be arranged at a series of moment according to chronological order, and be used for explanatory variable and correlation
Mathematic(al) representation, the arrangement set of obtained discrete digital composition is properly termed as time series, this having time meaning
Sequence is also referred to as dynamic data.Time series analysis is the time series data obtained according to systematic observation, passes through curve matching
Carry out the theory and method of founding mathematical models with parameter Estimation, it is generally (such as non-linear using curve matching and method for parameter estimation
Least square method) it carries out.
Assuming that particular model is regression model, then it can be by product data 1 and sensing data 1, product data 2 and sensing
Device data 2, product data 3 and sensing data 3 are used as input data, output to regression model, by the regression model according to
These input datas carry out modeling analysis and feature extraction, to obtain characteristic A.It similarly, can also be by 4 He of product data
Sensing data 4, product data 5 and sensing data 5, product data 6 and the output of sensing data 6 are to regression model, by institute
It states regression model and carries out modeling analysis and feature extraction according to these data, to obtain characteristic B.
Further, features described above data A and characteristic B i.e. the corresponding characteristic of production equipment.
Wherein, the related definition of regression model (also referred to as regression analysis model) can be as follows: regression analysis is used for
Specific dependence of the variable (explained variable) about another (a little) variable (explanatory variable) is studied, from one group of sample
Data are set out, and determine the relationship between variable to the credibility of these relational expressions, and from influencing a certain particular variables
All multivariables in find out which variable influence it is significant, which is not significant.Furthermore, it is possible to using required relational expression, according to
The value of one or several variables predicts perhaps to control the value of another particular variables and provides this prediction or control
The levels of precision of system.
Assuming that particular model is Tree-structure Model, then by product data 1 and sensing data 1, product data 2 and can pass
Sensor data 2, product data 3 and sensing data 3 are used as input data, export to Tree-structure Model, by Tree-structure Model root
Modeling analysis and feature extraction are carried out according to these input datas, to obtain characteristic A.It similarly, can also be by product data 4
It exports with sensing data 4, product data 5 and sensing data 5, product data 6 and sensing data 6 to Tree-structure Model,
Modeling analysis and feature extraction are carried out according to these data by Tree-structure Model, to obtain characteristic B.
Further, features described above data A and characteristic B i.e. the corresponding characteristic of production equipment.
Wherein, the related definition of Tree-structure Model can be as follows: tree construction is a kind of important nonlinear data knot
Structure is the structure that data element (being known as node in tree) is organized by branch's relationship.
In above process, describe time series models, regression model, Tree-structure Model processing mode, for " when
Between series model, regression model, Tree-structure Model modeling analysis and feature extraction carried out according to input data " process, herein
With no restrictions, as long as according to the available characteristic of input data.
For example, being based on time series models, it is assumed that using product data as abscissa, sat using sensing data as vertical
Mark, then product data 1 and the corresponding coordinate points 1 of sensing data 1, product data 2 and sensing data 2 correspond to a coordinate
The corresponding coordinate points 3 of point 2, product data 3 and sensing data 3.If coordinate points 1, coordinate points 2 and coordinate points 3 form one
Straight line, then features described above data can be the slope of this straight line, i.e. time series models carry out modeling point according to input data
After analysis and feature extraction, obtained characteristic is the slope of straight line.If coordinate points 1, coordinate points 2 and coordinate points 3 form one
Curve, then features described above data can be the change rate of this curve, i.e. time series models are modeled according to input data
After analysis and feature extraction, obtained characteristic is the change rate of curve.Certainly, characteristic can also be other contents,
The characteristic of different models may be the same or different, without limitation.
Aspect of model layer, can also be by the corresponding feature of the production equipment after obtaining the corresponding characteristic of production equipment
Data are supplied to tap layer.For example, characteristic A can be supplied to tap layer by aspect of model layer, and can by above-mentioned processing
Characteristic B is supplied to tap layer.
4, configuration layer.Config option is provided a user, relevant information is inputted according to the config option by user.
For example, config option can be normal parameter, it is based on this, user can be defeated in configuration layer according to the config option
Enter the normal parameter of product, and the normal parameter is to indicate the normal parameter information of production equipment, for example, characteristic X etc..
Based on this, if the difference between characteristic A/ characteristic B and characteristic X is less than threshold value, characteristic A/ feature
Data B be it is normal, i.e., the equipment state of production equipment be normal condition.If characteristic A/ characteristic B and characteristic X it
Between difference when being not less than threshold value, then characteristic A/ characteristic B is abnormal, i.e., the equipment state of production equipment is abnormal shape
State.
For example, config option can be anomaly parameter, it is based on this, user can be defeated in configuration layer according to the config option
Enter the anomaly parameter of product, and the anomaly parameter is the parameter information for indicating production equipment exception, for example, characteristic Y etc..
Based on this, if the difference between characteristic A/ characteristic B and characteristic Y is less than threshold value, characteristic A/ feature
Data B is exception, i.e., the equipment state of production equipment is abnormality.If characteristic A/ characteristic B and characteristic Y it
Between difference be not less than threshold value when, then characteristic A/ characteristic B be normal, i.e., the equipment state of production equipment be normal shape
State.
For example, config option can be production lot information, it is based on this, user can configure according to the config option
Layer input equipment information and production batch, such as facility information A, production batch " 20171217001 ", production batch
" 20171217002 " indicate that production batch " 20171217001 " corresponding product, production batch " 20171217002 " are corresponding
Product is that the corresponding production equipment of facility information A is produced.
Wherein, which can include but is not limited to following one or any combination: device type, equipment machine
Platform, part of appliance with no restrictions to this facility information as long as being based on the facility information, can uniquely indicate that a production is set
It is standby, i.e., corresponding production equipment can be known by facility information.
In conclusion normal parameter after obtaining normal parameter, can be supplied to tap layer by configuration layer.Alternatively, configuration
Anomaly parameter can be supplied to tap layer after obtaining anomaly parameter by layer.Alternatively, configuration layer is obtaining facility information and production
After the corresponding relationship of batch, the corresponding relationship of facility information and production batch can be supplied to tap layer.Certainly, above-mentioned to be
Several examples of configuration layer, it is without limitation.
5, tap layer.The phase of the corresponding characteristic of production equipment (being provided by aspect of model layer), user's input is being provided
After information (being provided by configuration layer) is provided, the corresponding equipment state of production equipment can be determined according to this feature data.Specifically, sentencing
Whether disconnected this feature data are abnormal data；If so, determining that the corresponding equipment state of production equipment is abnormality；If it is not, really
Determining the corresponding equipment state of production equipment is normal condition.
For example, configuration layer provides normal parameter (such as characteristic if aspect of model layer provides characteristic A/ characteristic B
According to X), then it can be according to the comparison result of characteristic A/ characteristic B and normal parameter (such as characteristic X), judging characteristic
Whether data A/ characteristic B is abnormal data.For example, if difference between characteristic A/ characteristic B and characteristic X
When less than threshold value, it is determined that characteristic A/ characteristic B is normal data, accordingly, it is determined that the corresponding equipment shape of production equipment
State is normal condition.If the difference between characteristic A/ characteristic B and characteristic X is not less than threshold value, it is determined that special
Sign data A/ characteristic B is abnormal data, accordingly, it is determined that the corresponding equipment state of production equipment is abnormality.
For example, configuration layer provides anomaly parameter (such as characteristic if aspect of model layer provides characteristic A/ characteristic B
According to Y), then it can be according to the comparison result of characteristic A/ characteristic B and anomaly parameter (such as characteristic Y), judging characteristic
Whether data A/ characteristic B is abnormal data.For example, if difference between characteristic A/ characteristic B and characteristic Y
When less than threshold value, it is determined that characteristic A/ characteristic B is abnormal data, accordingly, it is determined that the corresponding equipment shape of production equipment
State is abnormality.If the difference between characteristic A/ characteristic B and characteristic X is not less than threshold value, it is determined that special
Sign data A/ characteristic B is normal data, accordingly, it is determined that the corresponding equipment state of production equipment is normal condition.
For example, configuration layer provides facility information and production batch if aspect of model layer provides characteristic A/ characteristic B
Corresponding relationship, then obtain production equipment production the corresponding multiple characteristics of multiple products, and utilize multiple characteristics
Between it is comparative, analyze in multiple characteristics with the presence or absence of abnormal data.
Wherein, since product data may include production batch, ginseng is shown in Table 1, and therefore, aspect of model layer is being got
After characteristic, production batch can also be obtained from product data, and establishes reflecting for the production batch and this feature data
Penetrate relationship.For example, aspect of model layer can establish the mapping relations of characteristic A and production batch 20171217001, and establish
The mapping relations of characteristic B and production batch 20171217002.Based on this, aspect of model layer is by characteristic A and production
The mapping relations of the mapping relations of batch 20171217001, characteristic B and production batch 20171217002 are supplied to excavation
Layer.
Wherein, configuration layer, can be by the facility information A of user's input, life after the relevant information for receiving user's input
Produce batch " 20171217001 ", production batch " 20171217002 " is supplied to tap layer.
In conclusion the mapping relations of tap layer available characteristic A and production batch 20171217001；Feature
The mapping relations of data B and production batch 20171217002；Facility information A, production batch " 20171217001 ", production batch
The corresponding relationship of " 20171217002 ", be based on this, tap layer determine facility information A correspond to production batch " 20171217001 " and
Production batch " 20171217002 ", and determine facility information A character pair data A and characteristic B, that is to say, that it is described more
A characteristic is characterized data A and characteristic B.Certainly, an above-mentioned only example, in practical applications, facility information A
Corresponding multiple characteristics can be more, by taking character pair data A- characteristic D as an example.
Then, whether tap layer can use comparative between multiple characteristics, analyze in multiple characteristics and deposit
In abnormal data.Specifically, can determine specified type spy if there are specified type characteristics in multiple characteristics
Levying data is abnormal data.Wherein, the difference of the specified type characteristic and other feature data is greater than preset threshold.Example
Such as, if the difference between characteristic A and characteristic B is greater than between preset threshold and characteristic A and characteristic C
Difference is greater than difference between preset threshold and characteristic A and characteristic D and is greater than preset threshold, and characteristic B, spy
It is identical or approximate to levy data C, characteristic D, then it is abnormal data that characteristic A, which is specified type feature data,.
Certainly, above-mentioned analysis mode only analyzes the example that whether there is abnormal data in multiple characteristics, right
This analysis mode is with no restrictions.For example, can be analyzed in multiple characteristics according to correlation analysis with the presence or absence of abnormal
Data, generally, for a production equipment, the characteristic of most of product of production may be normal, few portion
It may be abnormal for dividing the characteristic of product.Moreover, the time it is forward the normal probability of characteristic it is larger, and the time is rearward
Characteristic exception probability it is larger.
6, application layer.It can use the corresponding multiple characteristics of production equipment, whether prediction production equipment will be sent out in future
Raw failure.Specifically, can use the corresponding multiple characteristics of production equipment, the index trend of multiple characteristics is analyzed,
And using the health status of the index trend prediction production equipment, i.e. whether prediction production equipment can be sent out in some following time
Raw failure, to form the health portrait for production equipment.
For example, ranking results of the characteristic A- characteristic D according to chronological order are as follows: characteristic A, characteristic
According to B, characteristic C, characteristic D, i.e. the time gap current time of characteristic A is maximum, and the time interval of characteristic D
From current time minimum.Although characteristic A, characteristic B, characteristic C, characteristic D are not abnormal data,
It is that characteristic A, characteristic B, characteristic C, characteristic D become closer to apart from abnormal conditions, such as assumes abnormal mark
Standard is 0.5, and characteristic A is 0.8, characteristic B is 0.7, characteristic C is 0.6, characteristic D is 0.55, then illustrates
With the propulsion of time, the characteristic of the product of production equipment production becomes closer to apart from abnormal conditions, therefore, prediction
For production equipment in some following time, the probability to break down is very big, the health portrait of production equipment be the future may appear
Failure.If characteristic A, characteristic B, characteristic C, characteristic D are not present and become closer to apart from abnormal conditions
Phenomenon then predicts production equipment in some following time, and the health portrait of the probability very little to break down, production equipment is not
Carry out probability of malfunction very little.
In one example, new process parameter can be provided, and technological parameter is recommended according to the state of production equipment
User, user can be used new process parameter and produce, and the data that production process is formed are collected again, for point later
Used in analysis, and so on, on-line off-line closed loop is formed, benign cycle is promoted.
Based on similarly applying conceiving with the above method, the embodiment of the present application also proposes a kind of determination side of equipment state
Method, it is shown in Figure 3, be the flow chart of this method, this method may comprise steps of:
Step 301, the sensing data of sensor acquisition relevant to particular types of devices is obtained.
Step 302, the corresponding characteristic of the particular types of devices is obtained according to the sensing data.
Step 303, the corresponding equipment state of the particular types of devices is determined according to this feature data.
Wherein, particular types of devices can include but is not limited to production equipment (such as automated production equipment).
It wherein, can for the process of " obtaining the corresponding characteristic of the particular types of devices according to the sensing data "
To include but is not limited to: according to the corresponding product data of product of production equipment production, sensor relevant to the production equipment
The sensing data of acquisition obtains the corresponding characteristic of the production equipment.
Wherein, the realization of step 301- step 303 may refer to repeat no more shown in Fig. 1 or Fig. 2.
Based on similarly applying conceiving with the above method, the embodiment of the present application also provides a kind of determining dress of equipment state
It sets, as shown in figure 4, the structure chart of the determining device for the equipment state, described device include:
Module 401 is obtained, for obtaining the corresponding product data of product of production equipment production；It obtains and is set with the production
The sensing data of standby relevant sensor acquisition；According to the product data and the sensing data, the production is obtained
The corresponding characteristic of equipment；
Determining module 402, for determining the corresponding equipment state of the production equipment according to the characteristic.
The acquisition module 401 is specifically used for that it is corresponding to obtain production equipment according to product data and sensing data
During characteristic, product data corresponding with same temporal information and sensing data are associated；Utilize association
Product data and sensing data afterwards obtain the corresponding characteristic of production equipment.
The acquisition module 401 is specifically used for that it is corresponding to obtain production equipment according to product data and sensing data
During characteristic, corresponding particular model is chosen for the product, using the particular model to the product data
It is handled with the sensing data, obtains the corresponding characteristic of production equipment.
The determining module 402, specifically in the mistake for determining the corresponding equipment state of production equipment according to characteristic
Cheng Zhong judges whether the characteristic is abnormal data；If so, determining that the corresponding equipment state of the production equipment is abnormal
State；If it is not, determining that the corresponding equipment state of the production equipment is normal condition.
The determining module 402, specifically for during whether judge the characteristic is abnormal data, according to
The comparison result of the characteristic and normal parameter judges whether the characteristic is abnormal data；Wherein, described normal
Parameter is to indicate the normal parameter information of production equipment；Alternatively,
According to the comparison result of the characteristic and anomaly parameter, judge whether the characteristic is abnormal data；
Wherein, the anomaly parameter is the parameter information for indicating production equipment exception；Alternatively,
Obtain the corresponding multiple characteristics of multiple products of the production equipment production；Utilize the multiple characteristic
Between it is comparative, analyze in the multiple characteristic with the presence or absence of abnormal data.
Based on similarly applying conceiving with the above method, the embodiment of the present application also provides a kind of for determining equipment state
Analytical equipment, the analytical equipment may include processor；Wherein: the processor, for obtaining the product of production equipment production
Corresponding product data；Obtain the sensing data of sensor acquisition relevant to the production equipment；According to the product number
According to the sensing data, obtain the corresponding characteristic of the production equipment；The life is determined according to the characteristic
Produce the corresponding equipment state of equipment.
Based on similarly applying conceiving with the above method, the embodiment of the present application also provides a kind of machine readable storage medium,
Several computer instructions are stored on the machine readable storage medium, the computer instruction is performed to be located as follows
Reason: the corresponding product data of product of production equipment production are obtained；Obtain the sensing of sensor acquisition relevant to production equipment
Device data；According to the product data and sensing data, the corresponding characteristic of the production equipment is obtained；According to the spy
Sign data determine the corresponding equipment state of production equipment.
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.A kind of typically to realize that equipment is computer, the concrete form of computer can
To be personal computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant, media play
In device, navigation equipment, E-mail receiver/send equipment, game console, tablet computer, wearable device or these equipment
The combination of any several equipment.
For convenience of description, it is divided into various units when description apparatus above with function to describe respectively.Certainly, implementing this
The function of each unit can be realized in the same or multiple software and or hardware when application.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes computer usable program code that the embodiment of the present application, which can be used in one or more,
The computer implemented in computer-usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of program product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It is generally understood that being realized by computer program instructions each in flowchart and/or the block diagram
The combination of process and/or box in process and/or box and flowchart and/or the block diagram.It can provide these computer journeys
Sequence instruct to general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices processor with
A machine is generated, so that the instruction generation executed by computer or the processor of other programmable data processing devices is used for
Realize the dress for the function of specifying in one or more flows of the flowchart and/or one or more blocks of the block diagram
It sets.
Moreover, these computer program instructions also can store be able to guide computer or other programmable datas processing set
In standby computer-readable memory operate in a specific manner, so that instruction stored in the computer readable memory generates
Manufacture including command device, the command device are realized in one process of flow chart or multiple processes and/or block diagram one
The function of being specified in a box or multiple boxes.
These computer program instructions can also be loaded into computer or other programmable data processing devices, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer
Or the instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram
The step of function of being specified in one box or multiple boxes.
The above description is only an example of the present application, is not intended to limit this application.For those skilled in the art
For, various changes and changes are possible in this application.All any modifications made within the spirit and principles of the present application are equal
Replacement, improvement etc., should be included within the scope of the claims of this application.
Claims (17)
1. a kind of determination method of equipment state, which is characterized in that the described method includes:
Obtain the corresponding product data of product of production equipment production；
Obtain the sensing data of sensor acquisition relevant to the production equipment；
According to the product data and the sensing data, the corresponding characteristic of the production equipment is obtained；
The corresponding equipment state of the production equipment is determined according to the characteristic.
2. the method according to claim 1, wherein described according to the product data and the sensor number
According to obtaining the process of the corresponding characteristic of the production equipment, specifically include:
Product data corresponding with same temporal information and sensing data are associated；
Using the product data and sensing data after association, the corresponding characteristic of the production equipment is obtained.
3. according to the method described in claim 2, it is characterized in that, it is described will product data corresponding with same temporal information and
The process that sensing data is associated, specifically includes:
First time information is obtained from product data, and the second temporal information is obtained from sensing data；
According to the first time information and second temporal information, determine product data corresponding with same temporal information and
Sensing data, and determining product data and sensing data are associated.
4. method according to claim 1 or 2, which is characterized in that described according to the product data and the sensor
Data obtain the process of the corresponding characteristic of the production equipment, specifically include:
Corresponding particular model is chosen for the product, and using the particular model to the product data and the sensor
Data are handled, and the corresponding characteristic of the production equipment is obtained.
5. according to the method described in claim 4, it is characterized in that, the particular model includes:
Time series models；Alternatively, regression model；Alternatively, Tree-structure Model.
6. the method according to claim 1, wherein
The process of the corresponding equipment state of the production equipment is determined according to the characteristic, comprising:
Judge whether the characteristic is abnormal data；
If so, determining that the corresponding equipment state of the production equipment is abnormality；
If not, it is determined that the corresponding equipment state of the production equipment is normal condition.
7. according to the method described in claim 6, it is characterized in that,
It is described judge the characteristic whether be abnormal data process, specifically include:
According to the comparison result of the characteristic and normal parameter, judge whether the characteristic is abnormal data；Wherein,
The normal parameter is to indicate the normal parameter information of production equipment；Alternatively,
According to the comparison result of the characteristic and anomaly parameter, judge whether the characteristic is abnormal data；Wherein,
The anomaly parameter is the parameter information for indicating production equipment exception；Alternatively,
Obtain the corresponding multiple characteristics of multiple products of the production equipment production；Using between the multiple characteristic
It is comparative, analyze in the multiple characteristic with the presence or absence of abnormal data.
8. the method according to the description of claim 7 is characterized in that
The process of the corresponding multiple characteristics of multiple products for obtaining the production equipment production, comprising:
Obtain the corresponding multiple production batch of multiple products of the production equipment production；
Mapping relations are inquired by the multiple production batch, obtain the corresponding multiple characteristics of the multiple production batch；
Wherein, the mapping relations are the mapping relations of production batch and characteristic.
9. according to the method described in claim 8, it is characterized in that, described according to the product data and the sensor number
According to, after obtaining the corresponding characteristic of the production equipment, the method also includes:
The corresponding production batch of the product is obtained from the product data；
Establish the mapping relations of the production batch Yu the characteristic.
10. the method according to the description of claim 7 is characterized in that the comparison using between the multiple characteristic
Property, it analyzes in the multiple characteristic with the presence or absence of abnormal data, comprising:
If there are specified type characteristics in multiple characteristics, it is determined that the specified type characteristic is abnormal number
According to the difference of the specified type characteristic and other feature data is greater than preset threshold.
11. a kind of determination method of equipment state, which is characterized in that the described method includes:
Obtain the sensing data of sensor acquisition relevant to particular types of devices；
The corresponding characteristic of the particular types of devices is obtained according to the sensing data；
The corresponding equipment state of the particular types of devices is determined according to the characteristic.
12. a kind of determining device of equipment state, which is characterized in that described device includes:
Module is obtained, for obtaining the corresponding product data of product of production equipment production；It obtains related to the production equipment
Sensor acquisition sensing data；According to the product data and the sensing data, the production equipment pair is obtained
The characteristic answered；
Determining module, for determining the corresponding equipment state of the production equipment according to the characteristic.
13. device according to claim 12, which is characterized in that the acquisition module is specifically used for according to the production
Product data and the sensing data during obtaining the corresponding characteristic of the production equipment, will be believed with the same time
It ceases corresponding product data and sensing data is associated；Using the product data and sensing data after association, institute is obtained
State the corresponding characteristic of production equipment.
14. device according to claim 12 or 13, which is characterized in that the acquisition module is specifically used for according to institute
Product data and the sensing data are stated, are the product during obtaining the corresponding characteristic of the production equipment
Corresponding particular model is chosen, and the product data and the sensing data are handled using the particular model,
Obtain the corresponding characteristic of the production equipment.
15. device according to claim 12, which is characterized in that the determining module is specifically used for according to the spy
During sign data determine the corresponding equipment state of the production equipment, judge whether the characteristic is abnormal data；
If so, determining that the corresponding equipment state of the production equipment is abnormality；If not, it is determined that the production equipment is corresponding
Equipment state is normal condition.
16. device according to claim 15, which is characterized in that
The determining module, specifically for during whether judge the characteristic is abnormal data, according to the spy
The comparison result for levying data and normal parameter, judges whether the characteristic is abnormal data；Wherein, the normal parameter is
Indicate the normal parameter information of production equipment；Alternatively,
According to the comparison result of the characteristic and anomaly parameter, judge whether the characteristic is abnormal data；Wherein,
The anomaly parameter is the parameter information for indicating production equipment exception；Alternatively,
Obtain the corresponding multiple characteristics of multiple products of the production equipment production；Using between the multiple characteristic
It is comparative, analyze in the multiple characteristic with the presence or absence of abnormal data.
17. a kind of for determining the analytical equipment of equipment state characterized by comprising processor, for obtaining production equipment
The corresponding product data of the product of production；Obtain the sensing data of sensor acquisition relevant to the production equipment；According to
The product data and the sensing data obtain the corresponding characteristic of the production equipment；According to the characteristic
Determine the corresponding equipment state of the production equipment.
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